design and use of a cylindrical coordinate measuring machine for non-contact roundness measurement
TRANSCRIPT
The Pennsylvania State University
The Graduate School
College of Engineering
DESIGN AND USE OF A CYLINDRICAL COORDINATE MEASURING
MACHINE FOR NON-CONTACT ROUNDNESS MEASUREMENT
A Thesis in
Mechanical Engineering
by
Mark Elliott Glauner
2002 Mark Elliott Glauner
Submitted in Partial Fulfillment of the Requirements
for the Degree of
Master of Science
December 2002
I grant The Pennsylvania State University the nonexclusive right to use this work for the
University's own purposes and to make single copies of the work available to the public
on a not-for-profit basis if copies are not otherwise available.
Mark Elliott Glauner
We approve the thesis of Mark Elliott Glauner.
Date of Signature
Eric R. Marsh Associate Professor of Mechanical EngineeringThesis Advisor
Panagiotis Michaleris Assistant Professor of Mechanical Engineering
Richard C. Benson Professor of Mechanical Engineering
Head of the Department of Mechanical Engineering
iii
ABSTRACT
The Cylindrical Coordinate Measuring Machine, or C2M2, was developed to
measure the out-of-roundness of cylindrical artifacts. High precision machine
components, coupled with the use of filtering and active error separation, result in out-of-
roundness measurements with microinch-level repeatability and accuracy.
The machine is a four axis positioning system manufactured by Professional
Instruments. Using an air bearing spindle and linear air bearing ways, it achieves
positioning accuracy of approximately 40 microinches with low error motion, which,
when coupled with precise position feedback, makes high precision measurement
possible.
Software was developed using C for Virtual Instrumentation (CVI) that manages
the data acquisition and motion control, effectively automating the test procedure. The
user interface can display a polar representation and harmonic analysis of each cylindrical
cross section, as well as a three-dimensional wireframe model of the artifact surface.
This work builds upon the significant contributions of other MDRL graduate
students. After the lab acquired the machine, Vincent Vigliano installed and configured
the controls. The software borrows from programs written by Vincent Vigliano and
David Schalcosky for similar metrology projects. The specific tasks for this project
include further tuning and programming of the control system, analysis and
troubleshooting of the machine, software adaptation, and integration of the sensors and
data acquisition hardware.
The accuracy and repeatability of this machine are on par with the leading
coordinate measuring machines that are currently available. The C2M2 adds to that the
benefit of non-contact measurement, an important factor in the inspection of delicate
optical-quality artifacts. This represents a significant improvement to the metrology
capabilities of the Penn State Machine Dynamics Research Laboratory.
iv
TABLE OF CONTENTS
LIST OF FIGURES......................................................................................................vi
LIST OF TABLES .......................................................................................................x
ACKNOWLEDGMENTS............................................................................................xi
CHAPTER 1: OVERVIEW .........................................................................................1
1.1 Introduction.....................................................................................................1 1.2 Project Goals ...................................................................................................2 1.3 Definition of Roundness .................................................................................3
1.3.1 Calculation of the Least Squares Center...............................................5 1.3.2 Harmonic Analysis ...............................................................................6
1.4 Background on Cylindricity............................................................................7 1.5 Experimental Methods ....................................................................................8
1.5.1 Diametral Methods ...............................................................................8 1.5.2 Chordal Methods...................................................................................9 1.5.3 Radial Methods .....................................................................................10 1.5.4 Available Probes ...................................................................................13 1.5.5 Grazing Incidence Interferometry.........................................................14
CHAPTER 2: HARDWARE DESIGN AND ANALYSIS .........................................18
2.1 Hardware Setup...............................................................................................18 2.1.1 Machine Design ....................................................................................18 2.1.2 Motion Control System.........................................................................20
2.1.2.1 Motors and Feedback..................................................................20 2.1.2.2 Motion Controller .......................................................................20
2.1.3 Data Acquisition ...................................................................................21 2.1.4 Sensors ..................................................................................................22 2.1.5 Hardware Interaction ............................................................................23
2.2 Active Error Separation ..................................................................................24 2.2.1 Y-Stage Position Tracking....................................................................25
2.3 Error Motions..................................................................................................28 2.3.1 Vibration Measurement ........................................................................28
v
2.3.2 Spindle Analysis ...................................................................................31 2.3.3 Experimental Modal Analysis ..............................................................35 2.3.4 Thermal Effects.....................................................................................39
2.4 Uncertainty Estimation ...................................................................................45 2.4.1 Accuracy of Capacitance Probes ..........................................................46 2.4.2 Accuracy of Data Acquisition...............................................................47 2.4.3 Uncertainty Budget ...............................................................................47
CHAPTER 3: SOFTWARE DESIGN AND USE .......................................................48
3.1 Data Acquisition and Storage .........................................................................49 3.2 Automatic Motion Control..............................................................................50 3.3 Measurement Analysis....................................................................................52 3.4 User Interface..................................................................................................54
3.4.1 Test Setup .............................................................................................55 3.4.2 Acquisition............................................................................................58 3.4.3 Plotting Results .....................................................................................58 3.4.4 Saving Test Data...................................................................................60 3.4.5 Loading Saved Data..............................................................................61
CHAPTER 4: RESULTS .............................................................................................62
4.1 Effects of Digital Filtering ..............................................................................62 4.1.1 Comparison to Moore No. 3 UMM ......................................................65
4.2 Repeatability ...................................................................................................68 4.3 Inspection Capability ......................................................................................69 4.4 Possible Applications......................................................................................72
CHAPTER 5: CONCLUSIONS AND FUTURE WORK...........................................74
BIBLIOGRAPHY ........................................................................................................76
APPENDIX A: WIRING DIAGRAM .........................................................................78
APPENDIX B CVI CODE..........................................................................................79
vi
LIST OF FIGURES
Figure 1–1: Diamond turned aluminum cylinder and flat............................................2
Figure 1–2: Four common definitions for the determination of roundness (after Whitehouse [7]).....................................................................................................4
Figure 1–3: Least squares center of a roundness profile (after Whitehouse [7]). ........5
Figure 1–4: Diametral roundness measurement...........................................................8
Figure 1–5: Illustration of the three-point method (after Gleason [9]). .......................9
Figure 1–6: Axial, face, radial and tilt error motion of a spindle rotor (after ANSI B89.3.4M [12]). ....................................................................................................11
Figure 1–7: Taylor-Hobson Talyrond 290 coordinate measuring machine .................13
Figure 1–8: Schematic of a grazing incidence interferometer (after Badami [16]). ....15
Figure 1–9: Examples of typical fringe patterns from flat grazing incidence interferometry. These patterns indicate (a) part tilt, (b) convexity or concavity of the part, (c) astigmatism (saddle), (d) form error curving to the bottom of the part, and (e) a cylindrical form (after Schalcosky [5]). ..................16
Figure 1–10: Schematic of a cylinder interferometer (after Badami [16]). .................17
Figure 2–1: Schematic of the C2M2..............................................................................19
Figure 2–2: Aerotech motion control hardware with 4020-LS amplifiers...................21
Figure 2–3: National Instruments BNC-2110 breakout box used for data acquisition. ............................................................................................................22
Figure 2–4: Lion Precision C1-C capacitance probe and DTM-10 amplifier..............23
Figure 2–5: Hardware architecture...............................................................................24
Figure 2–6: Two capacitance probes are used in order to compensate for the vibration of the stage.............................................................................................26
vii
Figure 2–7: Two capacitance probes are used to isolate the motion of the stage from the profile of the artifact........................................................................................27
Figure 2–8: Two capacitance probes, at the corners of the stage, are used to measure the yaw motion of the Y stage ................................................................29
Figure 2–9: Motion of the two corners of the Y stage, and the difference between the signals..............................................................................................................30
Figure 2–10: FFT of Measured Stage Vibration. .........................................................31
Figure 2–11: A reference spindle is mounted on top of the test spindle for a master axis test. .....................................................................................................32
Figure 2–12: A capacitance probe, mounted on the left side of the “can,” measures the combined radial error motion of two stacked spindles. A gage ball, seen on the right, restricts only the rotation of the stator of the reference spindle. ..................................................................................................................33
Figure 2–13: Results of master axis test showing the radial error motion of the C2M2 spindle. Plot (a) shows a repeatable radial error motion of 32.5 µin occurring at 79 upr. With a digital low pass filter applied in plot (b), the error motion is reduced to 1.3 µin and is fairly random. ...............................................34
Figure 2–14: Wireframe model of C2M2......................................................................36
Figure 2–15: Mode 4 characterized by translation of Y-axis stage..............................38
Figure 2–16: Bending modes 7, and 8. These represent (a) the X-direction vibration of the Y-axis stage, and (b) clamshell bending of the column. .............39
Figure 2–17: Time traces from probes 1 and 2. Due to thermal expansion in the metrology loop, the artifact appears to have effectively shrunk by 12 µin...........41
Figure 2–18: Curve fit and residual thermal growth after the curve fit is subtracted. .............................................................................................................42
Figure 2–19: Temperature fluctuation over a 56 minute period. .................................43
Figure 2–20: Thermal drift over a one minute period for probe 1 and 2, and the resulting thermal growth. ......................................................................................44
Figure 2–21: Thermal growth and curve fit, and residual error after the curve fit is subtracted. The error can be reduced to less than 0.5 µin....................................45
Figure 3–1: Cylinder City user interface......................................................................49
viii
Figure 3–2: Process for data acquisition. .....................................................................50
Figure 3–3: Flowchart for the motion control process.................................................52
Figure 3–4: A small portion of a polar plot. The light blue lines, known as the cloudband, show the result from each individual revolution of the artifact. The width of the cloudband is the asynchronous, or unrepeatable error. .............54
Figure 3–5: Settings window........................................................................................55
Figure 3–6: Square wave and index pulse from the spindle encoder...........................56
Figure 3–7: Total Indicated Runout gauge used for artifact centering and for zeroing the capacitance probes. ............................................................................57
Figure 3–8: Test Setup Box..........................................................................................58
Figure 3–9: Polar plot and harmonic analysis for an artifact cross-section. ................59
Figure 3–10: Two wireframe models of the same artifact, showing how the model can be rotated for viewing.....................................................................................60
Figure 4–1: Unfiltered result of one step. ....................................................................63
Figure 4–2: The same experimental data, digitally low-pass filtered with a cutoff frequency of 75 upr. ..............................................................................................64
Figure 4–3: A cylindrical artifact is measured using the 'Cylinder City' software on a Moore Universal Measuring Machine...........................................................65
Figure 4–4: Roundness of an artifact and asynchronous error with and without the use of a digital low-pass filter with a cutoff frequency of 75 upr. ........................66
Figure 4–5: Comparison of one measurement with and without the use of digital filtering..................................................................................................................67
Figure 4–6: Asynchronous error levels present in tests run on the C2M2 and on the Moore UMM. ........................................................................................................68
Figure 4–7: The roundness value for ten measurements taken at the same Z-axis height, with and without the use of stage motion compensation. The standard deviation with compensation is 0.116 µin. ...........................................................69
Figure 4–8: A pair of lines drawn on the side of the cylinder with a marker are clearly visible. .......................................................................................................70
Figure 4–9: Roundness of a cylindrical artifact. ..........................................................71
ix
Figure 4–10: The profile measured at 0.1875" shows a protrusion on the surface of the artifact. ..................................................................................................................72
x
LIST OF TABLES
Table 1–1: Roundness signal typology (after Whitehouse [7])....................................7
Table 2–1: Summary of natural frequencies and mode shapes....................................37
Table 2–2: Error multipliers for non-flat targets for Lion Precision C1-C capacitance probes. ...............................................................................................46
Table 2–3: Factors of uncertainty budget.....................................................................47
xi
ACKNOWLEDGMENTS
I would like to thank my advisor, Dr. Marsh, for giving me the opportunity to
learn so much. I could never have predicted how many unique opportunities I would have
to get my hands dirty and absorb countless things about the world of precision
engineering.
My colleagues and the alumni of the MDRL have each taught me so much
through their own independent research. Bob Grejda, Byron Knapp, Vincent Vigliano,
Brian O’Connor, David Schalcosky, Steve Henry, Jeremiah Couey, and Anuj Bhardwaj
all deserve thanks for their mentorship, technical expertise, and generous contributions to
this project. Moreover their friendship made life in the MDRL enjoyable.
Several corporate sponsors also made this project possible. Contributions from
Aerotech, Inc., Kistler, Lion Precision, and Professional Instruments were invaluable.
Steve Ludwig of Aerotech, and Dan Oss of Professional Instruments have also been very
generous with their time and knowledge.
Finally I would like to thank my family for their support that made graduate
school easier. Their unfaltering encouragement never failed to pick me up.
1
Chapter 1
Overview
Precision engineering can be casually defined as “the pursuit of the next decimal point of
accuracy [1].” With this goal, metrologists constantly work to increase the resolution and
accuracy of their instruments in order to evaluate workpieces or processes in finer detail.
One facet of this field is the measurement of workpiece roundness. Many instruments
have been developed that possess the ability to measure a variety of nominally round
parts with very fine accuracy; some of the most recent instruments resolve form errors on
the level of tenths of microinches [2].
1.1 Introduction
There is an increasing demand for accurately measuring workpiece roundness to improve
the manufacturing of roller bearings, diesel fuel injectors, and other cylindrical parts,
which will continue to push the capabilities of metrology. It is predicted that parts with a
roundness error less than 0.2 µin and a cylindrical form error of 4 µin will be
commonplace in the near future, and the accuracy of inspection instruments will need to
keep pace [3]. Thus there is motivation to constantly explore new techniques that may
define the next generation of metrology tools.
Previous projects conducted at the Penn State Machine Dynamics Research
Laboratory have achieved high levels of accuracy in the measurement of ultra-precision
round and circularly flat workpieces. These parts, shown in Figure 1–1, possess superior
surface finish and dimensional accuracy compared to a comparable part manufactured on
a standard lathe. Non-contact inspection is required to avoid damaging the delicate
mirror finish of the typically aluminum, copper or silicon workpieces. Commercially
available non-contact measurement machines are prohibitively expensive, so alternative
probing techniques are being researched [4-6].
2
1.2 Project Goals
The purpose of this work is to develop a measurement system for nominally axis-
symmetric parts that maintains a high level of precision while broadening the range of
allowable workpiece geometries. This project started with a complete air bearing
machine that was designed and built by Professional Instruments Company. Aerotech
provided a complete set of control hardware and software for the PI machine and a
previous MDRL student, Vincent Vigliano, worked with Aerotech engineer Dr. Steve
Ludwick to perform much of the integration work. There was considerable additional
work required to properly drive the machine using the Aerotech U500 controller
including tuning the four axes and chasing down a few lingering mechanical problems so
the first task of this work is to finish tuning the computer control that allows precise
motion of the four axis machine. The second task is to automate the data acquisition
process with custom software written in National Instruments CVI. The final task is to
integrate the Aerotech machine control system to the National Instruments data
Figure 1–1: Diamond turned aluminum cylinder and flat.
3
acquisition system so that a wide range of parts can be handled by the completed
instrument.
The Cylindrical Coordinate Measuring Machine meets these objectives with
accuracy that rivals that demonstrated by other commercially available offerings. In our
instrument, sample workpieces with a right cylindrical shape are inspected by making
roundness measurements at several heights along the workpiece, constructing a three-
dimensional representation of the surface. The system is automated, allowing the
roundness to be measured at up to 100 axial locations. The machine can accommodate
workpieces up to six inches in height and twelve inches in diameter. Measurement
repeatability of ±0.25 µin has been demonstrated, but with a calculated uncertainty of
3.0 µin. This value reflects the thorough analysis of the machine that is presented herein
and is the motivation for the recommendations found in the future work section.
1.3 Definition of Roundness
Many methods have been devised that attempt to quantify the form error of round parts
with a single number. Most of these methods measure the peak-to-valley height between
the innermost and outermost points of the profile. This is known as the out-of-roundness,
or simply roundness. This requires the definition of a center of revolution. The main
differences between these methods pertain to how the center is defined. Examples of the
four main techniques for defining this center are shown in Figure 1–2. Each technique is
illustrated on an exaggerated profile of an out-of-round part. The four methods are
known as the minimum circumscribed circle, the maximum inscribed circle, the
minimum radial separation, and the least squares methods [7,8].
4
The first step of each method is to determine a center. On that center, the
maximum inscribed and minimum circumscribed circles are drawn. The distance
between these rings is called the zone. Example (a) in Figure 1–2 demonstrates the
maximum circumscribed circle (MCC) center. This is also know as the ring gauge
center, since the center is that of the smallest ring that surrounds the outside of the
profile. The name is from the similarity to using a ring gauge. Example (b) illustrates
the maximum inscribed circle (MIC) center. The MIC center is also known as the plug
Figure 1–2: Four common definitions for the determination of roundness (after Whitehouse [7]).
(a) Minimum circumscribed circle (b) Minimum inscribed circle (c) Minimum zone (d) Least squares
Rmin
Rma
(d)
Rmin
Rmax
(c)
Rmax
Rmin
(b)
Rmin
Rmax
(a)
5
rr’
abOLSCθ
OR
gauge center, representing the center of the largest plug gauge that would fit within the
profile without interference. Example (c) shows the minimum radial separation (MRS)
center. This center is determined by finding the position of the maximum inscribed and
minimum circumscribed concentric circles that have the smallest radial separation.
Example (d) shows the parameters that are perhaps the most commonly used in
metrology, the least squares center (LSC) and the resulting least squares zone (LSZ).
The first three methods, the MCC, MIC and minimum zone, are graphical in
nature, because they are controlled by specific graphical features. This makes them
vulnerable to excessive influence from sharp peaks or valleys of the profile. Furthermore
they are difficult to calculate, and may not result in a unique solution.
1.3.1 Calculation of the Least Squares Center
The least squares center can easily be calculated from a set of discrete points describing
the part profile. Figure 1–3 illustrates the least squares center, OLSC, relative to the center
of rotation, OR.
The center is found in Cartesian coordinates by Equations 1.1 and 1.2. For this
project, all data are collected and stored in polar coordinates, which is reflected in
Equations 1.1 and 1.2. The angle θ is given by Equation 1.3.
Figure 1–3: Least squares center of a roundness profile (after Whitehouse [7]).
6
=
=N
iiirN
a1
cos2 θ 1.1
=
=N
iiirN
b1
sin2 θ 1.2
πθ 2countsencoderofnumber
1 ×−= i 1.3
For each point i, the radius r′ is calculated from the least squares center by
Equation 1.4.
( ) ( )22 sincos' brarr iiiii −+−= θθ 1.4
The radius from this center is then used to find the least squares zone. This is
commonly accepted as a measure of the part roundness, and is used for the purposes of
this work. The width of the LSZ is given by Equation 1.5.
)'min()'max(Roundness ii rr −= 1.5
1.3.2 Harmonic Analysis
The round profile is often described by identifying its harmonic content using the Fourier
series. The frequencies are expressed in upr, or undulations per revolution.
Form error is distinguished from surface texture by wavelength; form error
significantly changes the low frequency shape of the cross section, whereas features of
surface texture usually do not deviate greatly from the nominal diameter of the part.
Typically only the lower harmonics have a large enough magnitude to contribute to form
error. Thus the 2nd through 15 wavenumber content, or features that repeat 2 through 15
times per revolution, are referred to as the lobing coefficients. Surface texture, then, is
typically described by the harmonics greater than 15 upr. The 1st wavenumber (1 upr)
component describes only the eccentricity of the workpiece on the axis of rotation and,
for a roundness measurement, is not a contributor to form error. Table 1–1 shows a
breakdown of the harmonic coefficients, their common causes, and their most significant
effects.
Σ
Σ
7
Table 1–1: Roundness signal typology (after Whitehouse [7]).
Fourier Coefficient
Effect Likely Cause
0 Dimension of Part Instrument setup
Tolerance/fit
1 Instrument setup Eccentricity on graph 2 Ovality of part
Instrument setup Component Tilt
3 Trilobe on part Machine tool setup
Distortion of component due to jaws of chuck clamping
4-5 Unequal angle – genuine Equal angle – machine tool
Distortion due to clamping
5-20 Machine tool stiffness Out-of-roundness 20-50 Machine tool stiffness
Regenerative Chatter Out-of-roundness causes
vibration 50-1000 Manufacturing process
signal Out-of-roundness causes
noise
1.4 Background on Cylindricity
The concept of roundness can be extended into three dimensions to describe the form
error of cylindrical parts. The simplest form of this principle is to compare a series of
cross sections of the part, each evaluated using the traditional measures of roundness. To
more thoroughly describe the part, other parameters have been defined that, following the
roundness model, quantify the deviation of the part’s form from that of a perfect cylinder.
As with roundness, the significant criteria are determined by the application. Most
methods attempt to evaluate the conicity of the workpiece and the straightness of its axis,
as well as the overall roundness.
The least squares zone concept can be applied to a cylindrical form as well as a
circular cross-section. A series of circular cross sections are stacked with the axis, known
as the least squares axis, passing through the least squares center of each cross section.
The zone is then determined by the maximum radial separation between the minimum
and maximum radii among all of the cross sections. Since the LSC is used, this method
cannot detect a non-straight axis or component tilt, both of which tend to shift the least
8
square center relative to the machine coordinate system. As is the case with roundness
measurements, this method ignores the absolute radius of the workpiece. The
straightness of the workpiece can independently be determined from the shift of the least
squares center as long as angular consistency is maintained from one measurement to the
next.
1.5 Experimental Methods
Many tools exist to quantify the roundness of circular parts, ranging from simple dial
calipers to advanced, interferometer-based machines. The mechanical techniques can be
grouped into three categories: diametral, chordal, and radial.
1.5.1 Diametral Methods
The diametral method is the most basic and is also the most familiar. The diameter of the
workpiece is measured as the distance between two parallel flat anvils, such as the
calipers of a micrometer. A series of readings is taken as the part is rotated, as shown in
Figure 1–4. The roundness is expressed as one quarter of the difference between the
maximum and minimum readings, as expressed in Equation 1.6. It must be noted that
this method masks errors that have an odd number of lobes. A three lobed part, for
example, will appear perfectly round.
4Roundness 12 dd −= 1.6
Figure 1–4: Diametral roundness measurement.
d2 d1
9
1.5.2 Chordal Methods
Chordal methods use three or more gauging points on the surface of the part instead of
two. An example is the vee-block method in which the part rests between two flat
surfaces that are at an angle to one another. A probe at a third location measures the
change in vertical position of the surface as the part is rotated [7].
In the three-point method, a common form of chordal measurement, the artifact
makes point contact with rounded posts rather than vee-blocks. At a third point in
between, the tip of a transducer targets the part surface, shown in Figure 1–5.
Like the diametral methods, this technique suffers from harmonic suppression.
This means that certain harmonics are attenuated, based on the spacing of the contact
points and the probe. The attenuation for the harmonic order n is given by Equation 1.8.
If α and β from Figure 1–5 are equal angles, particular harmonics will be completely
hidden.
Figure 1–5: Illustration of the three-point method (after Gleason [9]).
αβ
φ
s(φ)
m(φ) 010
10
( ) ( ) ( )( ) ( ) ( )
( ) ( )αβα
βββα
α +Φ+
−−Φ+
−Φ=Φ ssmsin
sinsinsin
sin 1.7
( ) ( ) ( ) ( )22 sinsinsinsincossincossinsinsin
1 αββαββαβαβα
nncnnnG −+−−++
= 1.8
The advantage of this method is that it avoids the need to use a high precision
spindle, upon which most systems rely. Referring to Figure 1–5, if angles α and β are
made to be 60 and 45°, up to the 23rd harmonic can be measured with at least 0.75
sensitivity [9].
1.5.3 Radial Methods
Radial methods compare the workpiece to a reference and are broadly classified as
comparative measurements (as opposed to an absolute measurement) [10]. In roundness
and cylindricity metrology, the reference is usually in the form of an ultra-precision air
bearing spindle.
Radial methods are the most straightforward approach and are therefore the most
common way of generating a polar plot, the most common and intuitive display format.
This shows the workpiece such that the reader can quickly associate features of the graph
to the part. The polar plot is not very useful unless the form error is greatly magnified
with a large radial magnification superimposed on a circle of arbitrary radius to show the
cross-section in greater detail [11].
For any comparative measurement device, the availability of an accurate
reference is crucial. Spindles with fluid film bearings, especially aerostatic bearings, are
often used because they typically possess very high accuracy and repeatability [12].
Furthermore, the error motion is virtually unchanging over time, aided by the fact that
there is no mechanical contact between the rotor and stator during operation. In what is
known as error mapping, the error motion of a bearing can be measured and stored in a
database. Due to its repeatable nature, it can then be subtracted from subsequent
experiments with a high degree of confidence. Error separation techniques can be used to
measure the reference spindle error motion to make an accurate error map [2,11-13].
11
There are four types of spindle error motion that will affect the apparent accuracy
of the measurement reference. These are (a) axial motion, (b) face motion, (c) radial
motion, and (d) tilt motion, as shown in Figure 1–6. Axial motion is measured on the
axis of rotation and is the travel of the rotor along that axis. Similarly, face motion is the
motion of the rotor parallel to the axis of rotation that is measured at a specified radius
from that axis. Pure radial motion is motion of the rotor perpendicular to the axis of
rotation. Tilt motion is the rotation of the rotor about an axis perpendicular to the axis of
rotation [12].
(a) Axial Motion (b) Face Motion
(c) Radial Motion (d) Tilt Motion
Figure 1–6: Axial, face, radial and tilt error motion of a spindle rotor (after ANSI B89.3.4M [12]).
Radiallocation
Axial location
12
In practice, a single measurement reflects the contributions of combinations of
radial, axial, and tilt error motion depending on the location and orientation of the
displacement indicator. For example, the face motion that is measured is a combination
of tilt motion and axial motion. The contribution from tilt error motion increases as the
displacement indicator is moved away from the axis of rotation. Likewise, the apparent
radial motion is a combination of tilt error motion and pure radial error motion. The
effects of tilt error motion are generally larger at a height above the face of the spindle
than at the face itself. Therefore when face or radial motion is discussed, it is always
given at a specific radius on the face or at a specific height above the face, respectively.
Reversal, multistep, or multiprobe error separation techniques are required to characterize
the reference spindle errors [2,12].
Machines are commercially available that test for parameters of roundness and
cylindricity. They span a large spectrum of accuracy, affordability, and size. Most have
the same general configuration, using a high-precision spindle to rotate nominally round
workpieces. Some offer computer numerical control (CNC) and software packages that
automatically perform the measurement and show the results in a convenient user
interface.
One such machine, the Talyrond 290 by Taylor Hobson Precision, arguably
represents the current state of the art. This instrument most closely matches the goals
sought by this project. The Talyrond 290, shown in Figure 1–7 can accommodate pieces
up to 13.7 inches in diameter and 39 inches in height, and weighing up to 165 lbs. It is
capable of performing measurements with 0.05 µin resolution. Its spindle is rated as
having radial error less than 1.6 µin. Its measurement capabilities include roundness,
cylindricity and flatness measurements with harmonic analysis [14].
13
1.5.4 Available Probes
Several means exist to accurately measure small changes in displacement, such as the
fluctuations of the form of an artifact.
The most economical method relies on a mechanical stylus that follows the
surface of the artifact as it is scanned. A transducer measures the deflection of the stylus.
This is the probe used by the Talyrond 290. As with any type of contact measurement,
the possibility exists that the stylus tip can damage the surface finish of a sensitive
artifact. In high-precision applications, the local deflection from the pressure of the
stylus tip may become significant. Additionally, factors such as tip shape, radius, and
wear must be considered.
A very common non-contact transducer is the capacitance probe. These devices
sense the capacitance between two surfaces, the probe tip and the target. Ideally the
target material is electrically conductive, but dielectric and semiconductor materials can
also be used with special considerations. As the distance between the surfaces changes,
so does the capacitance of the air gap. The probe amplifier linearizes the voltage change
Figure 1–7: Taylor-Hobson Talyrond 290 coordinate measuring machine
14
of the underlying measurement and outputs a voltage that is proportional to the air gap
[15].
Another class of non-contact measurement systems use a laser to measure the
distance to the part surface. The variation in the gap width results in a corresponding
change in the intensity of the laser beam that is reflected off of the artifact surface. This
is compared to a reference beam from the same light source. Applying the confocal
principal, a pinhole aperture allows only light that is focused on that point to pass through
to the photo detector. This allows the distinction of the reference beam and the light that
is reflected off of the artifact. Two photodetectors independently measure the intensity of
these two beams of light. A fluctuations in the difference between them is proportional to
the change in distance to the artifact’s surface. This method has been employed
successfully to perform non-contact roundness measurements [3].
1.5.5 Grazing Incidence Interferometry
One other common tool used for non-contact form error metrology is grazing incidence
interferometry. The term refers to the interference between two beams of light, on which
this method is based. The concept can best be summarized using the example of
measuring flatness.
Light passes through a reference prism that splits each beam into two, reflecting
one and allowing the other to pass through and strike the test object. The light that is
reflected serves as the reference beam. That which is allowed to pass, called the test
beam, is then reflected back into the prism where it combines with a reference beam,
parallel to and in phase with the original. This is shown in Figure 1–8.
15
Depending on the phase shift between the reference beam and the test beam, the
two may constructively or destructively interfere. Constructive interference, where the
waveforms of the two beams are in phase, will result in the greatest intensity of the
combined light beam. Destructive interference, where the two beams are out of phase,
caused the beams to effectively cancel each other, resulting in attenuation of the
combined beam intensity. The phase angle between the two beams varies with the width
of the air gap separating the prism from the part. Thus as the gap width changes, so does
the degree of interference. This results in light and dark areas, or fringes, projected onto
the image plane. A single fringe represents a change in the width of the air gap equal to
θλ
cos2, where λ is the wavelength of the light, and θ is the angle of the test beam from
the normal to the part surface. Examples of common fringe patterns and their
interpretations are shown in Figure 1–9. These patterns indicate (a) part tilt, (b)
convexity or concavity of the part, (c) astigmatism (saddle), (d) form error curving to the
bottom of the part, and (e) a cylindrical form. This requires a source of light that is
parallel with a constant, single wavelength, which is provided by a laser [15].
Figure 1–8: Schematic of a grazing incidence interferometer (after Badami [16]).
Air gap
Collimated Incident
Wavefront Image plane
Surface under test
Prism
16
This principle can be applied to measure cylindrical parts as well. Figure 1–10
illustrates the layout used for grazing incidence interferometry of cylindrical surfaces.
The collimator ensures that the beams of light are parallel. Variations in the radius of the
test part affect the path length of the test beam, causing similar fringe patterns to emerge
on the image plane [16].
(a) (b) (c)
(d) (e)
Figure 1–9: Examples of typical fringe patterns from flat grazing incidence interferometry. These patterns indicate (a) part tilt, (b) convexity or concavity of the part,
(c) astigmatism (saddle), (d) form error curving to the bottom of the part, and (e) a cylindrical form (after Schalcosky [5]).
17
Corning Tropel offers a cylinder interferometer applying this configuration. The
CylinderMasterTM 25 accommodates parts up to 25 mm in diameter and 125 mm in
length. The manufacturer claims a resolution of 0.4 µin and an accuracy of 4 µin.
The fringe patterns resulting from form error are more complex than those
resulting from a flatness measurement. Through the use of a camera on the image plane
and computer analysis, the fringes are automatically interpreted into a picture that is more
meaningful to the untrained eye. The CylinderMasterTM software is capable of measuring
roundness, cylindricity, and harmonic analysis for a roundness slice. Its greatest
advantage is the ability to perform non-contact measurement of nearly any material that
possesses a good surface finish. Surface finishes that are acceptable are classified as
precision ground, honed, polished and superfinished [17]. The main shortcoming of this
approach is that only right cylinders can be measured; other geometries will block the
light path.
Figure 1–10: Schematic of a cylinder interferometer (after Badami [16]).
Viewinglens
Point source
Collimator
First grating Second grating
Aperture
Image planePart under
test
18
Chapter 2
Hardware Design and Analysis
The Cylindrical Coordinate Measuring Machine, or C2M2, is the product of the goal of
making high precision roundness measurements. This chapter discusses the operation of
the machine, and the motion control and data acquisition hardware, and presents an
analysis of the machine’s characteristics and performance.
2.1 Hardware Setup
High precision roundness measurements of a wide variety of components are possible
using the C2M2. The machine is a highly accurate four axis positioning system designed
and manufactured by Professional Instruments of Minneapolis, Minnesota.
2.1.1 Machine Design
The machine structure, consisting of the base and column, is cast iron. According to the
manufacturer, the column is installed parallel to the rotational axis to within one arc-
second. The three primary axes are the horizontal axis, vertical axis, and one rotary axis.
Each linear axis is an air bearing stage driven by a ballscrew and servo motor. The rotary
axis is a motorized air bearing spindle, which is mounted in the Y-axis stage. The artifact
or workpiece is mounted on this spindle. A small ball bearing slide is mounted on the
vertical axis carriage for fine X-axis adjustment of the measurement probe. The
arrangement of these components is show in Figure 2–1. The Z-axis provides movement
of the probe parallel to the part axis of rotation. The horizontal axis provides radial
motion of the part with respect to the probe to accommodate parts of varying radii [18].
19
The advantage of using air bearings is the high degree of precision that can be
achieved. The linear air bearings ways suffer significantly less error motion than more
common flat or vee-groove ways. Similarly, the air bearing spindle rotates with much
less error motion than a ball bearing spindle. The error motion of an air bearing spindle
is also highly repeatable and can be mapped if necessary.
Figure 2–1: Schematic of the C2M2
1. Y-axis air bearing stage 2. Air bearing spindle 3. Artifact 4. Capacitance probe holder 5. X-axis ball bearing stage 6. Z-axis air bearing stage
Y
X
Z
1 2
3 4
5 6
20
2.1.2 Motion Control System
One advantage of the C2M2 over traditional coordinate measuring machines is the
addition of computer numerical control. This allows for highly accurate positioning of
the artifact, as well as automation of the test procedure.
2.1.2.1 Motors and Feedback
Closed loop position feedback is provided by optical encoders on the three air bearing
axes. The Y and Z-axis linear stages are each equipped with a Heidenhein LIP401 linear
encoder. The scale has a grating period of 0.00157 in (4µm), and an interpolated pitch of
0.394 µin (10nm). Both axes are driven by Kollmorgen ServoDisc N12M4T DC motors.
The spindle is driven by a Magtech V-Line DC motor and has a Heidenhein ERO-
1324 encoder installed with 4096 counts per revolution. The spindle has a final angular
resolution of 79.1 arc-seconds.
2.1.2.2 Motion Controller
The motion controller is an Aerotech Unidex 500 motion controller running the
Windows-based MMI version 5.18 interface software on a personal computer. Each axis
is driven by an Aerotech 4020-LS linear servo amplifier. The amplifiers and feedback
devices are connected to the U500 control board via an Aerotech BB500 interface board.
The rack of amplifiers and the BB500, on the top shelf, are shown in Figure 2–2.
21
2.1.3 Data Acquisition
Data is acquired using a National Instruments NI-6110 data acquisition card running on a
separate PC. It is connected via a SCSI cable to a BNC-2110 breakout box shown in
Figure 2–3. The card is capable of simultaneously sampling 4 analog channels at 5
million samples per second with 12-bit resolution. Among its other features, it has two
16-bit analog outputs, and analog triggering that are used for this project [19].
Four signals are gathered to form a roundness plot for a given cross section. Two
are the output of two Lion Precision capacitance probes; the first measures the form of
the part and the second provides position feedback of the stage. The third signal is the
square wave output of the rotary encoder on the spindle. A 4096-count encoder is used,
meaning that 4096 square wave cycles are seen for one channel in one rotation of the
spindle. Each square wave passage triggers all channels to be simultaneously sampled,
resulting in 4096 samples per revolution. Spatially-based sampling, rather than time-
based, ensures that data points from consecutive revolutions are perfectly in phase, and
Figure 2–2: Aerotech motion control hardware with 4020-LS amplifiers.
22
removes the effects of spindle speed on data acquisition. The final signal that is sampled
is the index pulse from the encoder. This is a reference point for defining the absolute
angular position of the spindle. Once the angle is known, comparison between different
sets of data is simplified.
2.1.4 Sensors
Two Lion Precision capacitance probes are used for form measurement. Each probe is a
model C1-C with a diameter of 3/8”, driven by a DMT-10 amplifier. These are shown
together in Figure 2–4. Used in Fine range, the sensor is linear over a measurement range
of 0.003 to 0.005”. The driver output is a DC voltage that is inversely proportional to the
gap width at a sensitivity of 10 Volts per thousandth of an inch. The diameter of the
sensor area is 0.067”. The measurement spot size is a circle 30% larger than the sensor
area, with a diameter of 0.0763” [20].
Figure 2–3: National Instruments BNC-2110 breakout box used for data acquisition.
23
2.1.5 Hardware Interaction
These components are assembled as shown in Figure 2–5. The system includes the C2M2
and two personal computers. The motion of the C2M2 is controlled by the U500 motion
controller, run by PC 2, which in turn receives position feedback from the encoders on
the C2M2. The output of the capacitance probes is recorded by the National Instruments
data acquisition system that is run by PC 1. In order to coordinate the experiment, there
is communication between PC 1 and PC 2 as well. PC 1 senses the spindle position via
the BB500 breakout board. In order to index the probe along the Z-axis, PC 1 sends a 5-
volt pulse to an analog input of the BB500. A similar trigger at the end of the test signals
the spindle to stop.
Figure 2–4: Lion Precision C1-C capacitance probe and two-channel DTM-10 amplifier.
24
2.2 Active Error Separation
The traditional philosophy of precision machine design dictates that the machine’s
structural loop should be as stiff as possible. A common rule of thumb is that a
measuring machine should be stiff enough that the user could replace the gauging device
with a cutting tool and machine a part with it. The purpose is to reduce machine
deflections to a level that won’t influence the measurement.
The design of the C2M2, then, is a departure from traditional machine design
principles. The machine is built with an air bearing stage that moves along the sensitive
direction axis. The purpose is to accommodate parts of different geometries. Air bearing
ways were chosen for two reasons. First, they provide a straight and flat axis of travel
Figure 2–5: Hardware architecture.
25
that minimizes motion transverse to the sensitive direction. Furthermore, the frictionless
air bearings allow improved velocity and position control. This is crucial if trying to
follow the contour of a part with a diameter that varies along its length. The result is that
the only mechanical contact between the stage and the machine base is via the ballscrew.
This leads to lower stiffness compared to a traditional machine base and extremely low
damping. Thus, the machine is unsuitable for any machining operations. The lack of
stiffness and damping leads to considerable deflection in the sensitive direction that
strongly influences the data gathered from the probe.
2.2.1 Y-Stage Position Tracking
The solution is to track the motion of the stage and account for it in the measurement. A
second capacitance probe was therefore installed to track the fine vibration of the Y-axis
stage. This is in addition to an identical probe that targets the artifact itself. This
arrangement is shown in Figure 2–6. Probe 1 can clearly be seen in the top of the photo,
targeting the cylindrical artifact. Probe 2 is seen in the lower left hand corner, facing the
side of the stage. A lapped gage block acts as the target surface to avoid effects from the
rough surface finish of the stage.
26
The role of probe 2 is only to provide position feedback for the stage. S2, the
output of probe 2, is a voltage proportional to the displacement of the stage toward the
probe, in the negative Y direction, which will be called B.
The displacement sensed by probe 1 has two components. The first is the artifact
profile. Since the spindle and the artifact ride on top of the stage, the vibration of the
stage also results in a translation of the artifact. Therefore the motion of the stage, B, is
also reflected in S1, the output of probe 1. Figure 2–7 shows the arrangement of the
probes and the components of each.
Figure 2–6: Two capacitance probes are used in order to compensate for the vibration of the stage.
Probe 1
Probe 2
27
Finding difference of S1 and S2 yields the profile of the artifact, as in Equation
2.1.
R = S1-S2 = (B+R)-B 2.1
Continuous position corrections from the Aerotech controller result in step
changes in the data, and also induce additional vibration in the structure. For this reason
it is advantageous to disable the Y-axis while a test is being performed. It is impractical
to try to actively control the stage position when the resolution of the position feedback,
in this case the capacitance probe, is finer than that of the motion controller [21]. This
approach is unacceptable for a manufacturing tool, because any movement in the
structure will manifest itself in the geometry of the part that is being made. For a
measuring machine, however, relative motion between the probe and the part is tolerated
as long as it can be measured and accounted for.
Lasers are commonly used to monitor the small machine deflections, similar to
how the capacitance gauge is used. In the most rigorous case, three laser beams can be
used to track the motion of the stage in a plane. By measuring the deflection of three
Figure 2–7: Two capacitance probes are used to isolate the motion of the stage from the profile of the artifact.
Stage
Artifact
Probe 1
Probe 2
S1=R+B
S2=B
R=r(θ)
B
28
points, the translation and rotation of the stage can be precisely monitored. Through
active error separation this motion could accurately be removed from the data [2].
The Moore Tool Company routinely uses a laser interferometer to track the fine
movements linear stages. “Even with a precision leadscrew, an angular encoder or
resolver knows only about the angular position of that leadscrew; it doesn’t know
anything about the position of what the leadscrew is driving. The encoder feeds the
information back to the control, which makes incremental adjustments. That’s the
accepted definition of a closed-loop system, but is it truly closed?” says Phillip Hannah
of Moore Tool Company [21]. Similarly, the linear encoder mounted directly to the Y-
axis stage does not precisely measure the location of the spindle. This can only be done
by mounting a transducer to the spindle, or as close to it as possible.
2.3 Error Motions
To fully evaluate the performance of the C2M2, it is necessary to measure the error
motions that may affect the experimental data. This includes, primarily, the translation
and yaw of the Y-axis stage and the error motion of the spindle.
2.3.1 Vibration Measurement
In order to evaluate the error motions of the stage in the sensitive direction, two
capacitance probes were mounted at the forward corners to track the motion under typical
operating conditions. While the spindle was run at 16.7 RPM, the output of the two
probes was recorded. The data acquisition used was a DSP Technologies Siglab model
20-42 four-channel, 12-bit signal analyzer, run by a personal computer within the
MATLAB programming environment. Two Lion Precision capacitance probes were
mounted on the machine base as shown in Figure 2–8.
29
Figure 2–9 shows the result from this test. Plot (a) shows the displacement of
both corners, which exhibit periodic vibration that is roughly in phase, indicating
translation along the Y-axis. The motion of the left-hand corner, indicated by probe 1, is
typically greater than that shown by probe 2. This suggests a yaw component in addition
to the translation. Plot (b) shows the difference between these two signals. The
displacement of the left and right corners of the stage can be different by up to 30 µin.
The linear encoder, which sits 6 inches off-axis from the spindle and probe, is
therefore inadequate to measure the displacement of the spindle itself. By interpolation,
it is possible that the translation in the Y-axis between the measurement point and the
encoder may differ by as much as 14 µin. A better way to track the stage motion is to
locate a position sensor in line with the spindle rather than offset from it. In this way, the
translation, including that caused by yaw motion, is equal at the location of the position
feedback device as well as at the location of the capacitance probe that measures the
Figure 2–8: Two capacitance probes, at the corners of the stage, are used to measure the yaw motion of the Y stage
Probe 2 Probe 1
30
artifact form. This is the motivation for adding the second capacitance probe, described
in section 2.2.1.
Figure 2–10 shows the FFT of the data from (a) probe 1, (b) probe 2, and (c) the
difference between them. Both probes show a peak near 40 Hz, which is the translation
of the stage along the Y-axis. This is confirmed by the modal analysis that is discussed in
section 2.3.3. Probe 1, however, shows another strong peak at 22 Hz that is not indicated
by probe 2. This suggests that while the right side of the stage is relatively stationary, the
left side is pivoting around the right at this frequency. It is reasonable to speculate that
the stage is in fact pivoting around the ballscrew, which is located near the right side of
the stage. The second yaw mode is seen at 103 Hz, representing the stage rotating about
its own center.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5-50
0
50Y-Stage Motion
Dis
plac
emen
t (m
icro
inch
es)
Time (s)
Probe 1Probe 2
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5-50
0
50Difference Between Probe 1 and Probe 2
Time (s)
Dis
plac
emen
t (m
icro
inch
es)
Figure 2–9: Motion of the two corners of the Y stage, and the difference between the signals
31
2.3.2 Spindle Analysis
The second significant source of error is the spindle itself. The purpose for using an air
bearing spindle is that it typically offers radial error motion on the order of nanometers.
Furthermore, as mentioned in section 1.5.3, if the error motion is repeatable, error
mapping can be employed.
In order to measure the radial motion of the spindle, a simplified master axis test
was performed [2]. A master axis test was selected due to the relative ease with which it
could be accomplished on an installed spindle. In this technique, a second air bearing
spindle is mounted on top of the first, their rotors fixed together on a common axis of
rotation. The top spindle will be referred to as the reference spindle, and the original
0 20 40 60 80 100 1200
100
200
300(a) FFT of Probe 1
mic
roin
ches
0 20 40 60 80 100 1200
100
200
300(b) FFT of Probe 2
mic
roin
ches
0 20 40 60 80 100 1200
100
200
300(c) FFT of Yaw
mic
roin
ches
Frequency (Hz)
Figure 2–10: FFT of Measured Stage Vibration.
32
spindle will be called the test spindle. The stator of the reference spindle is then
restricted in the rotational axis, but free to translate in its five other degrees of freedom.
This is accomplished by locating a gage ball, which is mounted to the stage, against a
gage block, mounted to the stator of the reference spindle. This arrangement is shown in
Figure 2–11.
By establishing point contact, the stator is restricted in rotation but friction is
negligible in every other direction. A capacitance probe is mounted on the stage, which
targets a second gage block mounted to the stator. In this way, the radial motion of the
stator in the sensitive direction is measured. The resulting motion is a combination of the
error motion of the reference spindle and the test spindle. In a true master axis test, a
reversal would then be performed to separate the error motions of the two spindles,
assuming they are of similar magnitude. The reference spindle in this case is a
Professional Instruments aluminum 3R BLOCK-HEAD , which in previous tests has
Figure 2–11: A reference spindle is mounted on the test spindle for a master axis test.
Reference Rotor
Test Rotor
Point contact between ground and reference
stator
Master axis of rotation
Test spindle stator
Reference Spindle Stator
33
demonstrated radial error motion of less than 0.15 µin. Meanwhile, the test spindle is
suspected to exhibit radial error motion greater than 30 µin. Thus, in this case, the error
motion of the test spindle is known to be much greater than that of the reference spindle,
and the error motion of the reference spindle may be neglected. This is similar to simply
using an artifact that can be assumed to be perfectly round. The probe is mounted to the
stage itself to make the structural loop as small and as stiff as possible. This setup is
shown in Figure 2–12.
Data was recorded using the “Cylinder City” software, developed for this project,
which is discussed in Chapter 3. The result is shown in Figure 2–13. The dominant
feature of plot (a) is a repeatable radial error motion occurring at 79 upr with a magnitude
of 32.5 µin. The source of this peculiar error motion has not been determined, but is
likely due to an error in the spindle installation or motor coupling. It is certainly not
typical of the performance of this model. Plot (b) shows the same data after a digital low-
pass filter is applied with a cutoff of 75 upr. When the 79 upr content is removed, the
Figure 2–12: A capacitance probe, mounted on the left side of the “can,” measures the combined radial error motion of two stacked spindles. A gage ball, seen on the right,
restricts only the rotation of the stator of the reference spindle.
Capacitance probe
Gage ball
34
residual error motion is only 1.3 µin. The harmonic analysis shows several peaks, but
none that are dominant. The asynchronous error motion for the test was 1.3 µin. Since
the error motion is unrepeatable, experimental data will be averaged over several
revolutions. This also limits the benefit of error mapping, which will not be employed in
this project.
(a) (b)
Figure 2–13: Results of master axis test showing the radial error motion of the C2M2 spindle. Plot (a) shows a repeatable radial error motion of 32.5 µin occurring at 79 upr. With a digital low pass filter applied in plot (b), the error motion is reduced to 1.3 µin
and is fairly random.
79 upr
35
2.3.3 Experimental Modal Analysis
A modal analysis was performed on the coordinate measurement machine to explore the
dynamic characteristics of the machine, the results of which revealed some significant
characteristics of the machine.
The analysis was performed using a fixed excitation and roving response method.
The excitation was provided by impact with a Kistler model 9722A500 instrumented
hammer using a medium rubber tip. The pretest indicated that the most effective drive
point would be at the top of the column near a rear corner. An angle block was fixed to
the machine in order to permit an impact at a 45˚ angle to the three axes of the machine,
the purpose of which is to excite modes in each plane. The response was measured using
a Kistler model 8690C5 tri-axial accelerometer with a sensitivity of approximately 1 V/g
in each axis. The accelerometer was moved to 40 different data points and affixed with
beeswax. For each point, 10 averages were used to maximize the coherence of the
frequency response function. No windowing was used since the measured response was
transient and adequately damped. Data was collected with Siglab and analyzed using
STAR modal analysis software.
Figure 2–14 shows the wireframe model of the C2M2 that is constructed from the
40 data points. The specific structures visible in the model, seen here undeformed, are
the base (1), the Y-axis motor mount (2), the Y stage (3), the spindle face (4), the column
(5), the Z-axis stage (6), and the X-axis stage (7). The arrow identifies the location and
direction of the drive point, located at the rear, upper right-hand corner of the column.
36
Table 2–1 lists the first ten modes of vibration that were identified by the modal
analysis.
Figure 2–14: Wireframe model of C2M2
1. Machine base 2. Y-axis motor mount 3. Y-axis stage 4. Spindle 5. Column 6. X-axis fine adjustment stage 7. Z-axis Stage
1
2
3
4 6
7
5
37
The first several modes identified were rigid body modes that occurred at low
frequencies. These are a result of the machine’s vibration on its isolation mounts.
The first structural mode occurs just below 40 Hz, and is the most significant
mode. It is characterized by vibration of the Y-axis carriage along its axis of travel,
illustrated in Figure 2–15. Upon further inspection, this is likely a result of compliance in
the ballscrew flexure. This is detrimental to the machine’s structural stiffness, but is
necessary to allow for misalignment in the ballscrew. This mode is the most significant
for two reasons. The first is that is occurs at a low frequency that may easily be excited
by operation of the machine. The second is that the vibration is along the sensitive
direction of measurement. Thus vibration in this direction directly affects the data taken
by the capacitance gage.
Table 2–1: Summary of natural frequencies and mode shapes
Mode Frequency (Hz)
Damping Ratio (ξ)
Mode Shape
1 4.1 0.041 2 8.3 0.058 3 13.6 0.081
Rigid body
4 39.2 0.038 Y translation of Y stage 5 50.5 0.042 Rotation of spindle rotor 6 117.8 0.004 Yaw of Y-axis stage 7 140.8 0.019 X translation of Y stage 8 198.1 0.015 Clamshell bending of
column 9 321.1 0.004 X-direction rocking of
column 10 355.9 0.29 Twisting of column
38
The significant remaining structural bending modes are shown in Figure 2–16.
Mode seven, the X-direction deflection of the Y-axis stage, is not detrimental because
this motion occurs in the non-sensitive direction and will cause an insignificant
measurement error. The eighth mode, at 198 Hz, represents the “clamshell” bending of
the column. This is significant as it results in translation of the capacitance probe mount
in the sensitive direction, which could directly influence experimental measurements.
Due to the high structural stiffness of the machine base, this vibration is of high
frequency and small displacement and does not cause significant measurement errors.
Mode 4: 39.1 Hz
Figure 2–15: Mode 4 characterized by translation of Y-axis stage.
39
2.3.4 Thermal Effects
Temperature changes may also induce inaccuracies in the measurements. While this
factor is important on most machine tools, the measurement scale of the C2M2 is so fine
that thermal expansion becomes a critical consideration. In many high precision
applications, the entire machine is kept at a constant temperature using temperature-
controlled air. Often this recirculating air can be regulated to a within 1/100 of a degree;
this is far more stable that the ambient temperature in a typical laboratory or shop [21].
Furthermore, maintaining a constant through-flow brings the entire machine into
equilibrium and eliminates temperature gradients that might build up throughout the
course of a test.
(a) Mode 7: 140.8 Hz (b) Mode 8: 198.12 Hz
Figure 2–16: Bending modes 7, and 8. These represent (a) the X-direction vibration of the Y-axis stage, and (b) clamshell bending of the column.
40
Due to the cost and effort required for this retrofit, this luxury is unavailable for
this project. Instead, thermal drift is compensated for in data processing. A polynomial
curve fit is matched to the experimental data, and then subtracted from it.
For this experiment, the machine was set up in its testing configuration but with
the spindle at rest. To record the ambient temperature, a thermistor was placed within the
base of the machine, underneath the Y stage. The thermistor used was a Cole Parmer
model 8502-16 with an analog output sensitivity of 10 mV/°F. The outputs from the two
capacitance probes as well as the temperature were recorded for a period of
approximately an hour. A Siglab unit was used with a sampling frequency of 12.8 Hz for
a record length of nearly 56 minutes. Figure 2–17 (a) shows the output of the two
capacitance probes over the course of the test. Probe 1, as described in section 2.2.1,
indicates that the gap between the probe and artifact increased by 17 µin in this time. In
the same amount of time probe 2 indicated that the gap between the probe and the Y-axis
stage increased only 5 µin. Plot (b) shows the difference between the two signals,
indicating a divergence of 12 µin. This means that if the probes were zeroed at the
beginning of the test, using the stage probe as a reference, it would appear that the artifact
has shrunk 12 µin.
41
This drift can be reduced significantly by fitting a curve to the line and subtracting
it. Figure 2–18 shows the curve fit that is applied to the plot of the thermal growth in the
upper plot, and the lower plot shows the thermal growth with this curve fit subtracted.
The reduction in drift is significant, reducing it to less than 1 µin.
0 10 20 30 40 50 60-5
0
5
10
15(a) Thermal Drift Shown by Capacitance Probes
Mic
roin
ches
Time (minutes)
Probe 1Probe 2
0 10 20 30 40 50 60-5
0
5
10
15(b) Effective Thermal Growth
Mic
roin
ches
Time (minutes)
Figure 2–17: Time traces from probes 1 and 2. Due to thermal expansion in the metrology loop, the artifact appears to have effectively shrunk by 12 µin.
42
This demonstrates that thermal expansion is a slow process, and can be accurately
approximated on the relevant time scale by a second order polynomial curve. The
machine, due to its thermal mass, is slow to follow any rapid temperature fluctuations.
Furthermore the temperature itself changes very little in this short period of time. Figure
2–19 shows the ambient temperature within the machine base, underneath the Y-axis
stage. A FFT of this data reveals no clear period. Similar tests conducted in the same
laboratory in the past have possessed a periodic nature due to the HVAC system. This is
not apparent in this data, perhaps because of the location of the thermistor, the time of
day, the season, or duration of the test. One notable event on this graph occurs just
before the 50-minute point, where a small spike occurs. This is due to work being done
0 10 20 30 40 50 60-5
0
5
10(a) Thermal Growth and Applied Curve Fit
Mic
roin
ches
Time (minutes)
Uncompensated thermal growthCurve fit
0 10 20 30 40 50 60-5
0
5
10(b) Thermal Growth Before and After Subtraction of Curve Fit
Mic
roin
ches
Time (minutes)
Uncompensated error Error after temperature compensation
Figure 2–18: Curve fit and residual thermal growth after the curve fit is subtracted.
43
nearby, indicating that the machine responds, albeit slowly, to its environment. This
spike is also notable because it corresponds to the peak error shown in Figure 2–18.
An individual test will seldom last for more than one minute, so is it important to
look at the effectiveness of the curve fit over a short period. The thermal drift over a one
minute period is shown in Figure 2–20. Plot (a) shows the individual signals of the
capacitance probes, and plot (b) shows the difference between them. In this period the
total thermal growth is less than one µin.
0 10 20 30 40 50 6071.2
71.25
71.3
71.35
71.4
71.45
71.5
71.55
71.6Ambient Temperature Fluctuation
Time (minutes)
Tem
pera
ture
(F)
Figure 2–19: Temperature fluctuation over a 56 minute period.
44
The application of a second order polynomial can reduce this error somewhat, as
shown in Figure 2–21. Plot (a) shows the thermal growth with a polynomial fit to it. Plot
(b) shows the same thermal growth, and the residual error after the curve fit has been
subtracted. For this period the error is reduced to less than 0.5 µin.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-2
-1
0
1
2(a) Thermal Drift Shown by Capacitance Probes
Mic
roin
ches
Time (minutes)
Probe 1Probe 2
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-2
-1
0
1
2(b) Effective Thermal Growth
Mic
roin
ches
Time (minutes)
Figure 2–20: Thermal drift over a one minute period for probe 1 and 2, and the resulting thermal growth.
45
2.4 Uncertainty Estimation
There are several factors that may contribute to the uncertainty of the measurement.
Among these are the accuracy of the instrumentation and data acquisition tools and the
error motions of the machine that cannot be compensated for. These factors can be
assembled into an uncertainty budget, which is a standard method to attach an accuracy
label to the data.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-1
-0.5
0
0.5
1(a) Thermal Growth and Applied Curve Fit
Mic
roin
ches
Time (minutes)
Uncompensated thermal growthCurve fit
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-1
-0.5
0
0.5
1(b) Thermal Growth Before and After Subtraction of Curve Fit
Mic
roin
ches
Time (minutes)
Uncompensated error Error after temperature compensation
Figure 2–21: Thermal growth and curve fit, and residual error after the curve fit is subtracted. The error can be reduced to less than 0.5 µin.
46
2.4.1 Accuracy of Capacitance Probes
The capacitance probes are assumed to have a nominal sensitivity, but their sensitivity is
subject to inaccuracy due to environmental factors as well as the target. The accuracy is
also affected by factors such as the surface finish, the shape of the target, and the
normality of the probe with respect to the target surface.
The curvature of the target surface has an affect on the accuracy of the
capacitance probe because the finitely small spot size of the probe will have a very slight
curvature. The effect is an offset error since the gap width shown is averaged over the
spot size. This is not significant in the operation of the C2M2 since only relative
displacement is significant. The electric field acts differently on this shape of a surface,
however, and causes a sensitivity error as well. Correction factors for different part
geometries are found in Table 2–2. For artifacts larger than 1 inch in diameter, a
correction factor is not needed [20]. Surface finish is not a factor in the operation of the
C2M2 due to the high finish of the single-point diamond turned artifacts.
Table 2–2: Error multipliers for non-flat targets for Lion Precision C1-C capacitance probes.
Diameter Sphere Cylinder 1” 0.93 0.97 ½” 0.77 0.94
Changes in relative humidity and temperature can cause errors of up to 0.5% of
full scale. It is accepted that this can be scaled to 1% of the range over which the gauge
is used (the TIR), which for the C2M2 is nominally less than 50 µin. 1% of this range
results in a maximum uncertainty of 0.5 µin.
47
2.4.2 Accuracy of Data Acquisition
For the data acquisition system, National Instruments quotes an accuracy of 0.3808%
with respect to the input, or RTI. This is a combination of offset error, electrical noise,
temperature, and other factors, and is valid for a measurement range of ±5 V. This leads
to a maximum error of 19 mV, or 0.19 µin [22].
2.4.3 Uncertainty Budget
Several sources of error may influence the roundness measurement. Several are transient
errors, such as those caused by deflections in the metrology loop or electrical noise, are
random and will be minimized by averaging. Other errors are systemic, repeating with
each average. These include thermal errors, sensitivity errors of the capacitance probe
and data acquisition hardware, and the error motion of the spindle. These errors are
random and unrelated, and make a one-time contribution for a given measurement. Thus
it is appropriate to add them in quadrature as shown in Equation 2.2 [23].
( ) ( )22 zxq δδδ +⋅⋅⋅+= 2.2
These errors are compiled in Table 2–3, resulting in a final uncertainty value of
3 µin, using a coverage factor of k = 2.
Table 2–3: Factors of uncertainty budget.
Error Source Accuracy Capacitance Probe 0.5µin Data Acquisition 0.19µin Spindle Roundness 1.3 µin Thermal 0.5 µin Total Uncertainty (k = 2) 3.0 µin
48
Chapter 3
Software Design and Use
New software known as “Cylinder City,” after the term “cylindricity,” was developed to
perform the data acquisition and processing and provide a user interface. The software is
programmed in National Instruments C for Virtual Instrumentation (CVI). The tools for
data acquisition and roundness analysis were carried over from the “Roundcheck”
software previously developed by Vincent Vigliano and subsequently improved by
Robert Grejda and Dave Schalcosky for use in the Penn State Machine Dynamics
Research Laboratory. An additional data acquisition channel was added to provide stage
motion compensation. The acquisition process was modified to store measurements for
several cross sections in matrix form rather than in one array, as was done for a single
roundness measurement. Shown in Figure 3–1, the interface provides for test setup and
control and plots the results of the roundness measurements immediately after the
conclusion of the test.
49
3.1 Data Acquisition and Storage
The general data acquisition process is shown as a flowchart in Figure 3–2. With the Z-
axis stationary, one ‘step’ of data, or one cross section of the artifact, is scanned and
recorded. Sampling is triggered by the square wave signal from the encoder on the
spindle. For the 4096-count encoder being used on the C2M2, 4096 samples per
revolution are taken. With each square wave passage, the capacitance probes are
simultaneously sampled along with the index pulse channel from the encoder. The user
determines during the test setup how many steps will be measured. If the test is
Figure 3–1: Cylinder City user interface.
50
incomplete, the CVI software triggers the U500 motion controller to index the probe, and
another step is measured. Once complete, the stored data is retrieved and analyzed.
3.2 Automatic Motion Control
Although the system is not fully automated, once set up, it is able to complete a surface
measurement of the entire part before operator input is needed. Currently the CVI data
Figure 3–2: Process for data acquisition.
Prompt user for test setup
Sample capacitance probe and index pulse
inputs based on square wave input
Store data for this step
Have enough steps been collected?
Trigger Z stage move to index probe
Analyze stored data
Display results
Acquire
No
Yes
51
acquisition program does not interface directly with the Aerotech U500 hardware. In
fact, the tasks of the motion control and data acquisition are handled by separate
computers, primarily for the sake of convenience. Simple motion control tasks can be
triggered by the CVI software. This is done using an analog output channel on the NI
breakout board to send a signal to an analog input channel on the BB500 breakout board.
Once the Y and Z stages are moved into position, a program is started in the U500
interface that begins rotating the spindle. The user may then begin data acquisition using
the CVI program. This process is described in Figure 3–3. Once one step is complete, a
5 V pulse is sent from the NI card to the U500 board. Upon seeing this pulse, the U500
program moves the Z stage up by a preprogrammed step. After a brief settling period,
CVI then automatically begins acquiring the next step of data. This process continues
automatically until the selected number of steps has been acquired. Upon completion,
CVI sends a pulse via a second analog channel that triggers the U500 to stop the spindle
and quit the program. This simple communication allows a degree of automation that
enables the user to conveniently take many steps of data. This feature, called the autostep
feature, can be turned off if the program is being used on a manual machine, or if manual
control is preferred.
52
3.3 Measurement Analysis
The first step in processing is to perform error separation to compensate for the motion of
the stage by subtracting the data from probe 2 from that of probe 1. Then, using the
index pulse as a marker, the number of data points in each complete revolution is checked
to confirm that the number of points agrees with number of encoder counts. This also
confirms that the index pulse has been found and the test has been run correctly. The
start of the data acquisition does not necessarily coincide with the index marker, so data
before the first and after the last index mark is truncated. This leaves integer number of
Figure 3–3: Flowchart for the motion control process.
Begin spindle rotation
Sample analog channels 1 and 2
Is channel 1 > 1V?
Is channel 2 > 1V?
Index Z-axis one step
Stop Spindle, Exit Program
Select step size
Yes
Yes
No
No
53
revolutions. This also ensures that the dataset starts at an angle of 0°, and an angle vector
can be matched to the data.
If the user selects to use a digital low-pass filter, the filter subroutine then
performs this task. This is done by performing a Fast Fourier Transform (FFT), which
creates a series of bins from low to high frequency. For a cutoff frequency of fc, data in
the bins corresponding to frequencies higher than fc are set to zero. The same principle is
applied to compensate for the eccentricity of the artifact. The off-centeredness of the
artifact appears as the 1 upr content. To center the data, the 1 upr bin is set to zero. By
performing an inverse FFT the signal is reconstructed with the higher frequency content
and the 1 upr content removed. The DC offset is then removed by subtracting the mean
value of the vector.
A temperature compensation routine is then called that attempts to remove any
drift that has occurred throughout the course of the test. As discussed in section 2.3.4, a
2nd order polynomial curve-fit is applied to the vector, and then subtracted from it. By
restricted the polynomial to the second order, it can only follow the general trend of the
vector. It does not attenuate the form measurement in any way.
With the data formatted, the roundness parameters are calculated. The total
indicated runout, or TIR, is simply the difference between the maximum and minimum
measured values. This serves as an indicator of the eccentricity of the artifact. The
asynchronous error for each angular location is found by calculating the difference
between the measured values at that angle. The largest asynchronous error value and the
corresponding angle are stored. Figure 3–4 shows a sample of a roundness plot. The
blue lines represent the data from each individual revolution, and the black line is the
average. The spread of the blue lines is the asynchronous error. A small cloudband, and
hence a low asynchronous error, indicate a highly repeatable test.
54
The mean profile is found by averaging the points measured at each angle over
several revolutions. This mean vector is then used to find the least squares center, or
LSC, using Equations 1.2 and 1.3. For each point of the mean vector, the radius from the
LSC is calculated. Finally, the roundness is calculated from Equation 1.5.
This analysis is completed for each step as they are sequentially retrieved from
the matrix. As each roundness polar plot is generated, it is also stored in a second matrix
that becomes the basis of a three dimensional graph. After each ring has been processed,
this matrix is then plotted in a 3-D graph representing the surface of the part.
In addition to viewing the 3-D surface graph, the user can select a cross section to
be individually displayed on the polar plot.
3.4 User Interface
The user interface provides a control panel from which to run the experiment and a
medium to display the results. An intuitive interface will also allow an inexperienced
operator to easily conduct a test with little training. The interface created for Cylinder
City provides the means to customize the software for use on a variety of different
Figure 3–4: A small portion of a polar plot. The light blue lines, known as the cloudband, show the result from each individual revolution of the artifact. The width of the
cloudband is the asynchronous, or unrepeatable error.
Individual revolution
Average of all revolutions
Asynchronous error
55
machines, and control the acquisition portion of an experiment. The analysis and display
tools are automatic and easily manipulated.
3.4.1 Test Setup
The user interface has two screens that are used for setting up the test and one for running
the test and displaying the results. The first screen that appears upon startup is the
Settings window, shown in Figure 3–5. It is here that the user specifies the number of
‘steps,’ or cross sections of data, that will be taken. Depending on the hardware being
used, the number of encoder counts per revolution and the method of square wave
triggering are set. The sensitivity of the capacitance probes being used, as well as the
step size, is also entered. The step size does not directly control the size of the step,
since this is programmed separately in the U500 G-code. However setting this option
will store the step size used along with the test data for the purposed of documentation.
In Figure 3–6, the index pulse is superimposed over the encoder square wave.
Sampling can occur as the square wave goes from low-to-high, as occurs near 0.18°, or
high-to-low as happens near 0.26°. For a 4096 count encoder, there are 4096 full square
wave cycles. This distinction is important, as the sample must capture the index pulse.
The phasing between the square wave and the index pulse depends on the direction of
Figure 3–5: Settings window.
56
spindle rotation and which square wave signal is used, since many have two channels that
are out of phase by 90°. For the initial setup, it is helpful to use an oscilloscope to
superimpose the two signals to determine the parameters. For the case shown in Figure
3–6, the index pulse at 0° coincides with the low to high transition of the square wave.
The user would select sampling on low to high. Triggering when the square wave goes
low would miss the index mark completely, since this pulse only lasts for one quarter-
cycle of the square wave.
Once the settings are stored, the user is taken to the main panel, which controls
the data acquisition and displays the results. If an artifact is being setup for test for the
first time, it must be centered as closely as possible. The toolbar in the main menu offers
two drop-down menus, ‘Measurement’ and ‘Window.’ Selecting the TIR indicator from
the window menu opens a new window with an image of a dial gauge, shown in Figure
3–7. Two options on this panel allow the user to select which capacitance probe to look
at, and to change the gauge scale. The gauge shows the instantaneous output of the
capacitance probe that is selected. It operates like a mechanical dial gauge, but with
-0.2 -0.1 0 0.1 0.2 0.3-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5Encoder Output
Vol
tage
Angle (degrees)
Square WaveIndex Pulse
Figure 3–6: Square wave and index pulse from the spindle encoder.
57
much higher sensitivity. This is used initially for centering an artifact, and also for
zeroing the capacitance probe amplifiers once the artifact is in position for testing.
Returning to the main panel, the user then may choose the settings that control the
data processing. These are located in the box labeled “Test Setup,” and are shown in
Figure 3–8. First, the user selects the number of revolutions that are averaged.
Recording several revolutions of the artifact is beneficial since averaging will help to
reduce the effects of asynchronous error and yield a more accurate result.
Figure 3–7: Total Indicated Runout gauge used for artifact centering and for zeroing the capacitance probes.
58
Next the A/D range for the National Instruments data acquisition card is set.
Narrowing the range increases the resolution. The ‘units’ menu chooses whether the
results will be displayed in English or metric units. The next two options control whether
thermal compensation and automatic overload rejection will be used. The next option
controls the feature called ‘autostep.’ With autostep on, the Z-axis indexes one step
automatically, and then continues with the next measurement. Finally the user may select
whether a digital low-pass filter is to be used. With this option turned on, a window
becomes available where the cutoff frequency is set.
3.4.2 Acquisition
The three function buttons, ‘acquire’, ‘stop,’ and ‘clear,’ control the acquisition process.
Old data is automatically cleared when a new test is started, but the clear button is added
as a failsafe due to the software’s state of constant evolution.
3.4.3 Plotting Results
Once the test is complete, stored data is processed and displayed. On the right-hand side
of the screen a polar plot of a single cross-section of data is displayed. A close-up is
Figure 3–8: Test Setup Box.
59
shown in Figure 3–9. The black line shows the cloud band as well as the averaged cross-
section profile under radial magnification of more than 100,000:1. The nominal polar
plot radius is scaled to show the features clearly. The gray line is the mean radius from
the least squares center. The green rings bound the mean line on both sides, but not
tightly. It should not be interpreted as measurement of roundness. The display inside the
polar plot gives the measurements for the selected step. The roundness, TIR, and
asynchronous error are given for each step.
Below this polar graph, the FFT for the same step is given. The harmonic
analysis is based on revolutions rather than time, so the units used are upr, or undulations
per revolution, rather than Hertz. Below that are controls for scaling the FFT graph.
Figure 3–9: Polar plot and harmonic analysis for an artifact cross-section.
60
Finally at the bottom of the screen, a window shows what step is being viewed. By
clicking the up or down arrows the user may scroll through each cross-section.
In the center of the screen is a three-dimensional wireframe model of the part
surface. It is the result of stacking the individual polar plots on top of one another like a
stack of pancakes. By clicking on the image with the mouse and moving the cursor, the
user can rotate the model to view it from any angle. Two 3-D plots are shown side by
side in Figure 3–10 demonstrating how the model can be rotated. The model is only a
representation of the surface, so measurements cannot be made from it. Like the polar
plots, the scaling is arbitrarily chosen in order to give the best visualization of the part
surface.
3.4.4 Saving Test Data
Finally, once the test has been completed, the data may be saved. To do this the user
selects ‘save’ from the Measurement drop-down menu at the top of the screen. The user
is asked to select a folder in which the data arrays will be created. For a new test, it is
recommended that an empty folder is selected, or a new one created.
Figure 3–10: Two wireframe models of the same artifact, showing how the model can be rotated for viewing.
61
3.4.5 Loading Saved Data
To recall this data later, ‘Load’ is chosen from the same menu, and the appropriate folder
is chosen. Once the data is loaded, is must be processed again. The settings are
automatically set to those that are stored with the saved data, but may be changed at this
point if desired. The user is prompted to select reload from the measurement menu,
which processes the data according the settings on the screen. If the user changes any of
the analysis settings, such as the filter cutoff frequency, the user must again select reload
to analyze the data according to the new settings.
62
Chapter 4
Results
The relatively high error motion of the spindle can be corrected for, but is still restrictive
to the performance of the C2M2. The master axis test, discussed in section 2.3.2, revealed
radial error motion of 32.5 µin occurring at 79 upr. It is remarkable that the error motion
occurs only at this frequency. In fact, when this data is low-pass filtered below 75 upr,
the result is radial error motion of 1.3 µin, which is not unusual for a motorized air
bearing spindle. This lower frequency content shows asynchronous error of 1.3 µin
presumably due to compliance in the structure and not the spindle.
4.1 Effects of Digital Filtering
Since the error motion is relatively small below the 79 upr content, low pass digital
filtering will remove most of the spindle error from experimental data. Figure 4–1 shows
the results from a typical test without the use of the digital filter. The polar plot is
dominated by the periodic error motion. The roundness indicates that the peak-to-peak
difference of the mean is over 30 µin. The asynchronous error is measured at 21.4 µin.
The FFT also shows a peak at 79 upr that dwarfs the rest of the frequency content, with
its second and third harmonics also visible.
63
The same data was processed with the digital filter selected, with a cutoff
frequency of 75 upr. The result is shown if Figure 4–2. The periodic error motion is
completely gone, and the profile of the part emerges. The roundness indicated for this
test is 4.4 µin, with a greatly reduced asynchronous error value of 1.6 µin.
Figure 4–1: Unfiltered result of one step.
64
The analysis software and data acquisition package were used to conduct a similar
test on a Moore No. 3 Universal Measuring Machine from the Moore Tool Company.
This is a four axis positioning system with high structural stiffness. Rather than the air
bearing ways used in the C2M2, the Moore base uses double V-ways on the three linear
axes [24]. While the straightness of travel does not match that of the linear air bearings,
the stiffness in the axis of travel is far superior.
Figure 4–2: The same experimental data, digitally low-pass filtered with a cutoff
frequency of 75 upr.
65
4.1.1 Comparison to Moore No. 3 UMM
The fourth axis of motion is provided by an air bearing spindle, similar to that used on the
C2M2. The spindle is a non-motorized Professional Instruments model 4R. A
Heidenhein 512-count rotary encoder is installed for position tracking. The setup is
shown in Figure 4–3.
One purpose of using the Moore UMM is to explore the validity of the use of a
digital low pass filter. Out of necessity, data taken with the C2M2 is usually filtered using
a digital low-pass filter with a cutoff frequency of 75 upr. Figure 4–4 (a) shows a
comparison of the roundness data obtained with and without the use of the low-pass
filter. The asynchronous error of the data is shown in plot (b). The use of the filter has a
tendency to reduce the roundness value by an average of 0.09 µin. The asynchronous
error is also reduced at most points by an average of 0.23 µin.
Figure 4–3: A cylindrical artifact is measured using the 'Cylinder City' software on a
Moore Universal Measuring Machine.
66
Figure 4–5 shows a typical measurement where the roundness value has been
reduced by filtering. Plot (a) on the left shows the unfiltered data. Plot (b) shows the
same data after the use of the digital low-pass filter with a cutoff frequency of 75 upr. It
is clear in this example that the use of the filter tends to reduce the sharpness of the
features. In some cases, rounding sharp features also reduces the measured roundness
value.
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
2
4
6
8(a) Effect of Low-Pass Filter on Measured Artifact Roundness
Artifact Height (in.)
Rou
ndne
ss (m
icro
inch
es) Roundness
Roundness with Filter
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
2
4
6
8(b) Effect of Low-Pass Filter on Asynchronous Error
Artifact Height (in.)
Asy
nchr
onou
s E
rror (
mic
roin
ches
)
Asynchronous ErrorAsynch with Filter
Figure 4–4: Roundness of an artifact and asynchronous error with and without the use of
a digital low-pass filter with a cutoff frequency of 75 upr.
67
When measuring the same part on the C2M2 as well as the Moore UMM, it is
impossible to maintain the same datum. Therefore no attempt was made to correlate the
roundness values measured by the two methods. However, it is valid to compare the
levels of asynchronous error present in both tests. Figure 4–6 shows the asynchronous
error for each cross section for a test on the C2M2 as well as the asynchronous error
present when the same artifact was tested on the Moore UMM. In general the
asynchronous error shown by the Moore UMM is much lower. In some cases it achieved
an error value as low as 0.2 µin. The C2M2 consistently exhibits asynchronous error
values between 1 and 2 µin.
(a) (b)
Figure 4–5: Comparison of one measurement (a) without and (b) with the use of digital
filtering.
68
4.2 Repeatability
To measure the repeatability of the C2M2, ten consecutive measurements were taken with
the Z-axis help stationary. Figure 4–7 shows the scatter of the roundness values
calculated from each measurement. This was also a check of the validity of the use of a
second capacitance probe to compensate for the motion of the Y-axis stage. Using this
method of error separation, the data appears more closely clustered. The standard
deviation without compensation is 0.237 µin. With compensation used, the standard
deviation is reduced to 0.116 µin.
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
0.5
1
1.5
2
2.5
3Asynchronous Error of Roundness Measurement
Artifact Height (in.)
Asy
nchr
onou
s E
rror (
mic
roin
ches
)
C2M2 Moore No.3 UMM
Figure 4–6: Asynchronous error levels present in tests run on the C2M2 and on the Moore
UMM.
69
0 1 2 3 4 5 6 7 8 9 102
2.5
3
3.5
4
4.5Repeatability of a Single Scan
Test Number
Rou
ndne
ss (m
icro
inch
es)
With Compensation Without Compensation
Figure 4–7: The roundness value for ten measurements taken at the same Z-axis height, with and without the use of stage motion compensation. The standard deviation with
compensation is 0.116 µin.
4.3 Inspection Capability
The C2M2 is well suited for the evaluation of macroscopic surface features, and the
wireframe plotting feature becomes very useful to visualize the part surface. This is
demonstrated in Figure 4–8 by simply drawing a pair of lines on the side of an aluminum
cylinder with a marker.
+2σ
-2σ
µ
70
Figure 4–8: A pair of lines drawn on the side of the cylinder with a marker are clearly visible.
The C2M2 also proves useful as an inspection tool to evaluate defects in the
surface of the artifact. By plotting the roundness of each step together anomalies in the
form stand out. Figure 4–9 shows the roundness values of a test where 32 cross sections
of the artifact were measured at a vertical spacing of 1/16 inch. The peak roundness
value occurs slightly below a height of 0.2 inches.
71
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
1
2
3
4
5
6
7
8Measured Roundness of a Test Artifact
Artifact Height (in.)
Rou
ndne
ss (m
icro
inch
es)
Figure 4–9: Roundness of a cylindrical artifact.
Upon inspection of the corresponding cross section, shown in Figure 4–10, a
feature juts out from the nominal profile of the cylinder. The wireframe model on the left
also shows this feature, near the bottom-right of the model.
72
Figure 4–10: The profile measured at 0.1875" shows a protrusion on the surface of the artifact.
4.4 Possible Applications
One possible application for this technology is the non-contact measurement of parts with
a delicate surface finish, such as artifacts that are made through single point diamond
turning. The growing field of infrared optics will necessitate such inspection methods.
Furthermore, the field of optics is beginning to include parts with geometries that are
more complex than simple cylinders, such as nonrotationally symmetric shapes. The
generation of more complex shapes is becoming more common with the development of
fast tool servos. Traditional single point diamond turning techniques can only produce
surfaces of revolution. With the addition of active tool control, shapes may be created
73
that are not symmetrical around an axis of rotation. A fast tool servo has been
demonstrated that controls the displacement of the tool via a piezoelectric actuator. The
position of the tool, controlled as a function of the angle of the workpiece, can cut
varying features into the part surface with a maximum travel of up to 787 µin (20 µm).
The C2M2 would be a uniquely suited inspection tool to evaluate the shape of such parts
[25].
74
Chapter 5
Conclusions and Future Work
The C2M2 has demonstrated the ability to make accurate and repeatable roundness
measurements along the length of a cylindrical workpiece and shows promise as a useful
inspection tool. An experimental repeatability study shows that consecutive
measurements lie within ±0.25 µin of the mean with 95% confidence. The calculated
uncertainty is 3 µin, a reflection of the several potential sources measurement error.
Future work may be helpful to realize the unique potential of the machine.
The spindle suffers from radial error motion that is significantly outside of the
manufacturer’s specifications, and could be repaired with a moderate investment.
Elimination of the 79 upr error motion would increase all aspects of the machine’s
performance. Most noticeably, the need for low-pass filtering would be done away with,
increasing the machine’s measurement bandwidth. Eliminating this error motion would
also decrease the overall vibration of the machine, reducing asynchronous error resulting
from machine deflection.
Currently, the error motion of the Y-axis stage is compensated for by tracking the
stage position with a capacitance probe. This yields very good performance, but reduces
the versatility of the machine. If an artifact of a different diameter is to be inspected, the
capacitance probe needs to be relocated so the Y-axis stage can be moved.
This limitation can be solved with the use of a different type of position sensor. It
has been shown that the single Heidenhein linear encoder is insufficient due to its
location relatively far from the spindle. An ideal solution would be to mount a laser
interferometer in line with the spindle. This would provide position feedback that is
comparable in accuracy to the capacitance probe, but would work over a much larger
range. This provides the ability for the Y-axis to be moved to accommodate artifacts of
varying diameters. Another solution may be to mount an additional linear encoder on the
75
opposite side of the stage. By knowing the displacement of each side of the stage, the
position of the spindle could be interpolated.
Other contributions to the uncertainty budget are related to environmental
influences. The thermal growth of the machine, the sensitivity of the capacitance probes,
and the accuracy of the data acquisition system are influenced by variations in ambient
air temperature, pressure, and humidity. Improved temperature control through the use of
an enclosure or air bath would help to mitigate these unknowns.
Further investment in hardware has the potential to yield even greater accuracy
and versatility than is currently achievable. The addition of a non-contact probe provides
a unique measurement tool capable of measuring an artifact with a delicate surface finish,
previously possible only by optical methods. The C2M2 promises to be a useful tool in
the inspection of high-precision workpieces.
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BIBLIOGRAPHY
1. Mel Liebers. Personal Communication. April, 2002.
2. Grejda, Robert D. Axis of Rotation Metrology Tutorial. Presented at the ASPE 17th Annual Meeting, St. Louis, MO, Oct. 21, 2002.
3. Tan, Jiubin; Zhao, Weiqian; Yang, Wenguo. Development of Research on Super-Precision Measurement Techniques for Circle and Cylindrical Contour . Proceedings of SPIE, v. 4222, 2000, pp. 21-26.
4. Vigliano, Vincent. Computer Control for Precision Bearing Analysis. M.S. Thesis, The Pennsylvania State University, 2001.
5. Schalcosky, David C. Design of a Precision Parallel Axis Flatness Inspection Machine. M.S. Thesis, The Pennsylvania State University, 2002.
6. Grejda, Robert D. Use and Calibration of Ultraprecision Axes of Rotation with Nanometer Level Metrology. Ph.D. Thesis, The Pennsylvania State University, 2002.
7. Whitehouse, David J. Handbook of Surface Metrology. Philadelphia: Institute of Physics Publishing, 1994.
8. ANSI B89.3.1-1972. Measurement of Out-of-Roundness. New York, NY: ASME, 1997.
9. Gleason, E., Schwenke, H. A Spindleless Instrument for the Roundness Measurement of Precision Spheres. Precision Engineering, v. 22, 1998, pp. 37-42.
10. Estler, W. Tyler, Evans, Chris J., Shao, L.Z. Uncertainty Estimation For Multiposition Form Error Metrology. Precision Engineering, v. 21, 1997, pp. 72-82.
11. Chetwynd, D.G., Siddall, G.J. Improving the Accuracy of Roundness Measurement. Journal of Physics E: Scientific Instruments, v. 9, 1976, pp. 537-544.
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12. ANSI/ASME B89.3.4M-1985. Axes of Rotation: Methods for Specifying and Testing. New York, NY: ASME, 1992.
13. Horikawa, O., Maruyama, N., Shimada, M. A Low Cost, High Accuracy Roundness Measuring System. Precision Engineering, v. 25, 2001, pp. 200-205.
14. Taylor Hobson Precision. Talyrond 290 Product Sheet. Leicester, England.
15. Slocum, Alexander H. Precision Machine Design. Englewood Cliffs, NJ: Prentice Hall, 1992.
16. Badami, Vivek G. Interferometric Form Metrology for Precision Machined Surfaces. Corning Tropel Corporation. Presented at the 2001 COM Summer School, Fairport, NY, June 2001.
17. Corning Tropel Corporation. CylinderMasterTM 25 Product Sheet. Fairport, NY.
18. Professional Instruments Company/ Apeiron. “C2M2” Cylindrical Coordinate Measuring Machine Product Sheet. Minneapolis, MN.
19. National Instruments Corporation. NI-6110 Product Sheet. Austin, TX.
20. Lion Precision. When Precision Matters… 2000 Catalog. St. Paul, MN: Lion Precision, 2000.
21. Turning to Millionths of an Inch. American Machinist, November, 1984.
22. National Instruments Accuracy Calculator. National Instruments Corporation. http://www.ni.com/cgi.com/cgi-bin/accuracy_2.cgi
23. Taylor, John R. An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements. Sausolito, CA: University Science Books, 1982.
24. Moore, Wayne R. Foundations of Mechanical Accuracy. Bridgeport, CT: The
Moore Special Tool Company, 1989.
25. Dow, Thomas A., Miller, Michelle H., Falter, Peter J. Application of a Fast Tool Servo for Diamond Turning of Nonrotationally Symmetric Surfaces. Precision Engineering, v. 13 n. 4, October 1991, pp. 243-250.
78
79
Appendix B
CVI Code
//Cylinder City (cylindricity) //Mark Glauner //Last mod: 11/13/02 //Based on: //ROUNDCHECK V.2.0 (rndchkv2_1.c) //With help from Flatcheck //Analog acquisition of index //3-D Plotting //Ch 0: Cap //Ch 3: Tach //Ch 2: Cap on Stage ('stage') //PFI1: Squarewave #include "cylinder.h" #include <Dataacq.h> #include <utility.h> #include <formatio.h> #include <ansi_c.h> #include <easyio.h> #include <analysis.h> #include <cvirte.h> /* Needed if linking in external compiler; harmless otherwise */ #include <userint.h> #include "ba_functions.h" #include "cviogl.h" #define FALSE 0 #define TRUE 1 static int options; static int indpanel; static int panelHandle; static int surfaceControl; static int revpanel; static int tirpanel; int begin, encct, ovalcolor; //Prototypes static int SetControlAttributes(void); static int CreatePlot(void);
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int err, month, day, year, hour, minute, minutetens, secs, revdatapresent; int step, datastep, totalsteps, done; double stepsize, delay, pulse; double sense, pi; long buffersize; static char msgBuf[256]; int error; double data[250000], settings[100]; double cap[80000], tach[80000], stage[80000], capfilt[250000], capprime[250000], angleprime[250000], capfund[250000]; double surfacecap[80000][100], surfacestage[80000][100], surfacetach[80000][100]; double capreduced[80000][100], capsurfclean[80000][100]; double angle[200000], xtemp[200000], capfit[200000], capplot[200000]; double capfft[200000], null[200000], fftx[200000], spindlefft[200000]; double vecx[200000], vecy[200000]; double capsave[2000000], stagesave[2000000], tachsave[2000000]; double capm[512]; double asynch[5000], capmean[5000], cappoints[5000], capmean1[5000], capmean2[5000], rlsc[5000], thetalsc[5000], R[5000]; double capmeanstore[5000][100], capplotstore[5000][100], Rstore[5000][100], fftxstore[80000][100]; double caprev[5000]; double spindle2[5000]; double mark[1000][100], backlog[10000], sqcount[10000], captemp[1000], timevec[1000], rpmvec[1000]; double capthermal[128], coef[100]; double polycoefs[10], xvec[10], yvec[10], nullx[10], nully[10]; double mean, mean2, max, min, asymax, capmin, capmax, cpr, upr; double asynchtest2; double testTIR, testTIRstore[100]; double a1, b1, t1, t2; double mserr; double deg; double deg2; double bcircle, a, b, a2, b2; double dcoffset, dcoffset_prev, dcoffset_max; double lsc, lscpart, lscspindle; double astore[100], bstore[100], lscstore[100], asymaxstore[100], degstore[100]; double maxfftstore[100], ifftmaxstore[100], rpmstore[100], varstore[100]; double maxfft, ct; double maxspindlefft; double rmin, rmax, thetamin, thetamax; double revs,maxrevs,datapoints,maxpoints,pt2; double datum, vcap, vcapin, tirscl; double range, range2; double delta; double wait; double del; double xcoor, ycoor;
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double tachmax; double maxupr, xupr, halfpts, ifftmax; double order2, circleval, x, y, max2, min2; double t, delt, rpm, rpm2, backlogval, var, var2; double dddzarray[200000], dddmag[200000], dddphase[200000]; double dddvecx[200000], dddvecy[200000], bobert[900000]; short int trigger, live, datapresent, livebar; int orderpoly, capswitch; int perrev, points, pt, logind; int i, j, k, l, m, n, p, w, revnum, inc; double filtcap[250000]; int order, cutoff; int scale; int fftscale, xpts; int imax, imin; int color; int amode; int test; int reversal; int indon, tirdiv; int rgb, fftcolor, backcolor; int windType; int rangeval, ovldrej, ovld; int rgb, superlightgray, backcolor; int autostep, showstep, loaded; unsigned long scanbacklog; long channum, taskID, rpmID, scanstate, scannum, scanbklg, taskIDtir; short brdcode; char path[300], tempchar[3000]; char filename; int liverev; int main (int argc, char *argv[]) { if (InitCVIRTE (0, argv, 0) == 0) /* Needed if linking in external compiler; harmless otherwise */ return -1; /* out of memory */ if ((panelHandle = LoadPanel (0, "cylinder.uir", PANEL)) < 0) return -1; if ((tirpanel = LoadPanel (0, "cylinder.uir", TIRPANEL)) < 0) return -1; if ((options = LoadPanel (0, "cylinder.uir", OPTIONS)) < 0) return -1; SuspendTimerCallbacks(); SetPanelAttribute (panelHandle, ATTR_WINDOW_ZOOM, VAL_MAXIMIZE); DisplayPanel (panelHandle);
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// Create OpenGL control on CVI panel surfaceControl = OGLConvertCtrl(panelHandle,PANEL_OGLPORT); if (surfaceControl<0) { OGLGetErrorString (surfaceControl, msgBuf, 255); MessagePopup("OGLConvertCtrl Error", msgBuf); goto Error; } // Setup CVIOGL control SetControlAttributes(); OGLRefreshGraph(panelHandle,surfaceControl); superlightgray = MakeColor (1, 1, 1); SetPanelAttribute (panelHandle, ATTR_DIMMED, TRUE); //Default Values pi = 3.1415927; buffersize = 400000; dcoffset_prev=0; Clear1D(astore, 100); Clear1D(bstore, 100); //Time/Day Stamp err = GetSystemDate (&month, &day, &year); err = GetSystemTime (&hour, &minute, &secs); minutetens = minute/10; minute = minute - minutetens*10; //Date and Time SetCtrlVal (panelHandle, PANEL_MONTHBOX, month); SetCtrlVal (panelHandle, PANEL_DAYBOX, day); SetCtrlVal (panelHandle, PANEL_YEARBOX, year); SetCtrlVal (panelHandle, PANEL_HOURBOX, hour); SetCtrlVal (panelHandle, PANEL_MINUTEBOX_2, minutetens); SetCtrlVal (panelHandle, PANEL_MINUTEBOX, minute); //Calibrate the DAQ Board begin = ConfirmPopup ("PCI-6032E Board Calibration", "Do you want to calibrate the DAQ board?"); if (begin) { MessagePopup ("PCI-6032E Board Calibration", "The Data Acquisition Board Will Now be Calibrated.\n" "This may take a few minutes."); Calibrate_E_Series (1, ND_SELF_CALIBRATE, ND_NI_DAQ_SW_AREA, 0); MessagePopup ("PCI-6032E Board Calibration", " Calibration Complete!"); }
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InstallPopup (options); RunUserInterface (); // Dicard CVIOGL control OGLDiscardCtrl(panelHandle,surfaceControl); Error : return error; } //Save Settings int CVICALLBACK savesettings (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: GetCtrlVal(options, OPTIONS_ENCCOUNT, &encct); GetCtrlVal(options, OPTIONS_GAGESENSE, &sense); GetCtrlVal(options, OPTIONS_TOTALSTEPS, &totalsteps); GetCtrlVal(options, OPTIONS_STEPSIZE, &stepsize); //RPM Task/Scan Clock/Buffer nidaqAICreateTask ("daq::1!(0,3)", kNidaqWaveformCapture, &channum, &rpmID); nidaqAIConfigBuffer (rpmID, buffersize, kNidaqContinuous); nidaqAIConfigExternalScanClock (rpmID, "daq::1!(PFILowtoHigh1)"); // Ch B, High to Low nidaqAIStart (rpmID); t1 = Timer(); RemovePopup(0); SetPanelAttribute (panelHandle, ATTR_DIMMED, FALSE); ResumeTimerCallbacks(); break; } return 0; } //INITIATE ACQUISITION: //Triggered 1) by pressing Acquire button on control panel // 2) when called by autostep int CVICALLBACK acquire (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: SuspendTimerCallbacks();
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//Initialize Board Init_DA_Brds (1, &brdcode); done=0; live = 1; //taking data in process livebar = 0; //don't take data for bar indicator pt = 0; //'data' vector indice logind = 0; //'backlog' vector indice ovld = 0; //no overload yet loaded = 0; //new data acquired: not data from file //Time/Day Stamp err = GetSystemDate (&month, &day, &year); err = GetSystemTime (&hour, &minute, &secs); minutetens = minute/10; minute = minute - minutetens*10; //Clear data Clear1D (data, 250000); Clear1D (cap, 80000); Clear1D (tach, 80000); Clear1D (stage, 80000); Clear1D (capprime, 250000); //Delete plots DeleteGraphPlot (panelHandle, PANEL_ROUNDPLOT, -1, VAL_IMMEDIATE_DRAW); DeleteGraphPlot (panelHandle, PANEL_FFTPLOT, -1, VAL_IMMEDIATE_DRAW); //Clear results DefaultCtrl (panelHandle, PANEL_FIM); DefaultCtrl (panelHandle, PANEL_MAXFFT); DefaultCtrl (panelHandle, PANEL_MAXASYNCH); DefaultCtrl (panelHandle, PANEL_ASYANGLE); DefaultCtrl (panelHandle, PANEL_ESYNCH); //Get Encoder Counts/Rev Value GetCtrlVal(options, OPTIONS_ENCCOUNT, &encct); cpr = encct; //Check number of revs GetCtrlVal (panelHandle, PANEL_REVNUM, &revnum); perrev = encct; if(revnum == 0){points = 6*perrev;} // 4 revs if(revnum == 1){points = 10*perrev;} // 8 revs if(revnum == 2){points = 18*perrev;} //16 revs if(revnum == 3){points = 34*perrev;} //32 revs if(revnum == 4){points = 66*perrev;} //64 revs if(revnum == 5){points = 130*perrev;} //128 revs //Create Scan Clock nidaqAICreateTask ("daq::1!(0,2,3)", kNidaqWaveformCapture, &channum, &taskID); GetCtrlVal(options, OPTIONS_SQRLOGIC, &n);
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if(n == 0){ nidaqAIConfigExternalScanClock (taskID, "daq::1!(PFIHighToLow1)");} if(n == 1){ nidaqAIConfigExternalScanClock (taskID, "daq::1!(PFILowToHigh1)");} nidaqAIConfigBuffer (taskID, buffersize, kNidaqContinuous); //Voltage Range GetCtrlVal (panelHandle, PANEL_VOLTRNG, &rangeval); GetCtrlVal (panelHandle, PANEL_OVLDREJ, &ovldrej); nidaqAIConfigChannelLimits (taskID, "daq::1!(3)", 10, -10); //Fixed ranges if(rangeval == 0){range = 0.2, nidaqAIConfigChannelLimits (taskID, "daq::1!(0,2)", range, -range);} if(rangeval == 1){range = 0.5, nidaqAIConfigChannelLimits (taskID, "daq::1!(0,2)", range, -range);} if(rangeval == 2){range = 1.0, nidaqAIConfigChannelLimits (taskID, "daq::1!(0,2)", range, -range);} if(rangeval == 3){range = 2.0, nidaqAIConfigChannelLimits (taskID, "daq::1!(0,2)", range, -range);} if(rangeval == 4){range = 5.0, nidaqAIConfigChannelLimits (taskID, "daq::1!(0,2)", range, -range);} if(rangeval == 5){range = 10.0, nidaqAIConfigChannelLimits (taskID, "daq::1!(0,2)", range, -range);} //Acquisiiton Start nidaqAIStart (taskID); //Display Acquisition Panel wait = 0; SetCtrlVal(panelHandle, PANEL_WAITBAR, wait); ResumeTimerCallbacks(); t = Timer(); timevec[logind] = t; break; } return 0; } //DPLOT //Creates 3D wireframe model static int dplot(void) { int error = 0; //Plot the 3D plot******************************************************** //format the data correctly //first clear a couple vectors Clear1D (capmean, 5000); Clear1D (capplot, 5000); //For each ring get the synchronous for (m=0;m<totalsteps;m++)
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{ //begin of all rings //pick off the current ring from the surface array and //add DC offset (constant for each ring) for (w=0;w<perrev;w++) { capmean[w]=capmeanstore[w][m]; capplot[w]= capmean[w] + dcoffset_max; } //put the ring height in an array for (w=0;w<perrev;w++) { dddzarray[m*perrev+w]=stepsize*m; } //Put the radius of the ring in a vector for (w=0;w<perrev;w++) { dddmag[m*perrev+w] = capplot[w]; } //Put the angle of each point on the ring in a vector for (w=0;w<perrev;w++) { dddphase[m*perrev+w] = angle[w]; } }//end of all rings //take the mag and phase of the circles //and convert to rect ToRect1D (dddmag, dddphase, perrev*totalsteps, &dddvecx[0], &dddvecy[0]); //Assemble the vector for the 3d plot for (p=0;p<perrev*totalsteps/12;p++) { bobert[3*p]=dddvecx[p*12]; bobert[3*p+1]=dddvecy[p*12]; bobert[3*p+2]=dddzarray[p*12]; } //call plot CreatePlot(); //End of 3D plot Error : return error; }
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//NEXTSTEP: //If autostep is on, NEXTSTEP tells U500 to index, then triggers ACQUIRE function call static int nextstep(void) { Clear1D(cap, points); Clear1D(tach, points); Clear1D(stage, points); GetCtrlVal (panelHandle, PANEL_AUTOSTEP, &autostep); if(autostep==0)ResetTextBox (panelHandle, PANEL_STATUSBOX, "acquire when ready"); else{ ResetTextBox (panelHandle, PANEL_STATUSBOX, "Stepping"); AOUpdateChannel (1, "0", 5.0); pulse=0.1; delay=5; Delay(pulse); AOUpdateChannel (1, "0", 0.0); Delay(delay); ResetTextBox (panelHandle, PANEL_STATUSBOX, "Acquiring"); acquire(panelHandle, 0, EVENT_COMMIT, 0, 0, 0); } Error : return error; } //ANALYZE //after all steps of data have been taken, ANALYZE performs calculations for each step static int analyze(void) { wait=0; live=0; datapresent=1; SetCtrlVal(panelHandle, PANEL_WAITBAR, wait); ResetTextBox (panelHandle, PANEL_STATUSBOX, "Scan Complete"); for(step=0;step<totalsteps;step++){ Clear1D(cap, points); Clear1D(stage, points); points=datapoints; //Reset 'points' to global 'datapoints'- may have been changed by last processing loop for(i=0;i<points;i++){ cap[i] = surfacecap[i][step]; stage[i] = surfacestage[i][step]; } //Remove Offset RemoveOffset(cap,points,&cap[0]); RemoveOffset(stage,points,&stage[0]); //Subtract stage error from cap signal to compensate for y stage motion
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Sub1D (cap, stage, points, cap); //Remove Offset, just in case subtraction introduced an offset again RemoveOffset(cap,points,&cap[0]); // New 'cap': remove exactly two revs (beginning|rev#1|.....|end) // points = points - 2revs // Note: mark vector is for this step only, but j is left over the the final step // It is assumed that j is equal for all steps (same # of revs for each step) k=0; for(i=mark[1][step];i<mark[j][step];i++){ capprime[k] = cap[i]; k++; } Clear1D(cap,points); points = points-(2*encct); // store reduced, centered data in new matrix for(i=0;i<points;i++){ cap[i]=capprime[i]; } inc = (points/encct); //angle vecy (rad) for(n=0;n<points;n++)angle[n] = (2*pi*inc*n/points); //Filter and Remove Once Around GetCtrlVal (panelHandle, PANEL_FILTCUTOFF, &cutoff); GetCtrlVal (panelHandle, PANEL_FILTTOGGLE, &n); if(n==1){ Clear1D(null, points);
FFTFilter(cap,null,points,encct,cutoff,&cap[0]); } if(n==0|cutoff==0){ Clear1D(null, points); cutoff = 0; FFTFilter(cap,null,points,encct,cutoff,&cap[0]); } //Temperature Compensation GetCtrlVal (panelHandle, PANEL_THERMAL, &n); orderpoly = 2; if(n == 1)RemoveThermalDrift(cap,xtemp,points,orderpoly, &polycoefs[0], &cap[0]); //Convert to units GetCtrlVal(options, OPTIONS_GAGESENSE, &sense); for(i=0;i<points;i++){ cap[i] = cap[i]*sense; }
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//FFT calculation Copy1D(cap, points, capfft); Clear1D (null,points); FFT (capfft, null, points); for(i=0;i<points;i++){ capfft[i] = pow (capfft[i], 2); null[i] = pow (null[i], 2); capfft[i] = sqrt (capfft[i] + null[i]); capfft[i] = capfft[i]*2/points; } Clear1D (null,points); MaxMin1D (capfft, points, &max, &imax, &min, &imin); maxfft = max; //'fftx' plotting vector revs = inc; ct = 0; for(i=0;i<points;i++){ fftx[i] = (1/revs)*ct; ct = ct + 1 ; fftxstore[i][step] = fftx[i]; } //at upr maxupr = encct/2; halfpts = points/2; MaxMin1D (capfft, halfpts, &max, &imax, &min, &imin); ct = (imax/halfpts)*maxupr; ifftmax = ct; //Truncate data again to get rid of end effects from filtering k=0; for(i=encct;i<(points-encct);i++){ capprime[k] = cap[i]; angleprime[k] = angle[i]; k++; } Clear1D(cap,points); Clear1D(angle,points); points = points-(2*encct); // store reduced, centered data in new matrix for(i=0;i<points;i++){ capreduced[i][step] = capprime[i]; cap[i]=capprime[i]; angle[i]=angleprime[i]; } inc=inc-2; //DC offset removed
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RemoveOffset(cap,points,&cap[0]); //Final Overload reject... MaxMin1D(cap, points, &max, &imax, &min, &imin); if(max == min){ ResetTextBox (panelHandle, PANEL_STATUSBOX, "overload"); } //Acquisition Done wait = 0; SetCtrlVal(panelHandle, PANEL_WAITBAR, wait); //*** //***************CALCULATE MEASUREMENTS**************** //*** //Measurements: //TIR //Asynch. Error //Roundness //FFT //Max FFT //TIR calculation, raw data MaxMin1D (cap, points, &max, &imax, &min, &imin); testTIR = (max - min);//*sense;//in microinches //Maximum asynchronous error motion //Construct 'capmean' which is the mean of all revs Clear1D (capm,512); for(i=0;i<encct;i++){ for(n=0;n<inc;n++){ capm[n] = cap[i + n*encct]; } MaxMin1D (capm, inc, &max, &imax, &min, &imin); asynch[i] = (max - min); Mean (capm, inc-1, &mean); capmean[i] = mean; } MaxMin1D (asynch, encct, &asymax, &imax, &min, &imin); deg = imax*360/(encct-1); //Roundness Measurement (LSC) //'capmean' is mean of all revs MaxMin1D (capmean, encct, &capmax, &imax, &capmin, &imin); for(i=0;i<encct;i++){ capplot[i] = capmean[i] + fabs(capmin); capplot[i] = capplot[i] + bcircle; }
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//find lsc center using 'capmean' ToRect1D (capplot, angle, encct, &vecx[0], &vecy[0]); a=0; b=0; for(i=0;i<encct;i++){ a = a + vecx[i]; b = b + vecy[i];} a = 2*a/encct; b = 2*b/encct; //create 'R' the radial values of the LSC for(i=0;i<encct;i++){ rlsc[i] = vecx[i] - a; thetalsc[i] = vecy[i] - b;} for(i=0;i<encct;i++){ R[i] = sqrt ((rlsc[i]*rlsc[i]) + (thetalsc[i]*thetalsc[i]));} MaxMin1D (R, encct, &max, &imax, &min, &imin); lsc = (max - min); //Store measurements for that step testTIRstore[step] = testTIR; astore[step] = a; bstore[step] = b; lscstore[step] = lsc; asymaxstore[step] = asymax; degstore[step] = deg; maxfftstore[step] = maxfft; ifftmaxstore[step] = ifftmax; rpmstore[step] = rpm; varstore[step] = var; for(i=0;i<encct;i++){ capmeanstore[i][step] = capmean[i]; Rstore[i][step] = R[i]; } //plot this step showstep=step+1; SetCtrlVal (panelHandle, PANEL_SHOWSTEP, showstep); plotstep(panelHandle, 0, EVENT_COMMIT, 0, 0, 0); } //end step loop //Create 3D plot dplot(); step=0; Error : return error; } //Timer int CVICALLBACK timer (int panel, int control, int event,
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void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_TIMER_TICK: if(liverev == 1)break; if(indon == 1)break; if(livebar==1)break; if(live == 0){ if(rpmID == 0)break; //Get Current RPM SuspendTimerCallbacks(); nidaqAICheck (rpmID, &scanstate, &scannum); if(scannum>100000){break;} nidaqAIRead (rpmID, "daq::1!(0)", scannum, -1.0, &xtemp[0]); //Elapsed Time Calculation t2 = Timer(); delt = t2 - t1; t1 = t2; GetCtrlVal(options, OPTIONS_ENCCOUNT, &encct); cpr = encct; rpm2 = (scannum/delt)*(60/cpr); //Live RPM SetCtrlVal(panelHandle, PANEL_RPMBOX2, rpm2); //Live Cap Reading GetCtrlVal(options, OPTIONS_GAGESENSE, &sense); SetCtrlVal(panelHandle, PANEL_BARIND, xtemp[0]*sense); ResumeTimerCallbacks(); break; break;} //*** //************DAQ LOOP START ************** //*** //Wait for Square Wave ResetTextBox (panelHandle, PANEL_STATUSBOX, "waiting for trigger"); if(live == 1){nidaqAICheck (taskID, &scanstate, &scanbklg); } //If the scanbacklog vector has data, //Read in data if(scanbklg>0){ t = Timer(); timevec[logind + 1] = t; SuspendTimerCallbacks(); ResetTextBox (panelHandle, PANEL_STATUSBOX, "triggered"); nidaqAIRead (taskID, "daq::1!(0,2,3)", scanbklg, -1.0, &data[pt]); if(ovldrej == 1 | rangeval == 0){ for(i=pt;i<(pt+scanbklg);i++){ // Overloaded at 99.5% of range if(data[i] > 0.995*range | data[i] < -0.995* range){ovld = 1;}
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} } backlog[logind] = scanbklg; logind++; pt = pt + (3*scanbklg); } //Overload beyond +/- 10 V on autorange, or beyond limits of Fixed scale if(ovld == 1){ ResetTextBox (panelHandle, PANEL_STATUSBOX, "overload"); MessagePopup ("DAQ Error", "Signal overload beyond DAQ limits."); live = 0; datapresent = 0; wait = 0; SetCtrlVal(panelHandle, PANEL_WAITBAR, wait); nidaqAIStop(taskID); nidaqAIDestroyTask(taskID); //RPM Task/Scan Clock/Buffer nidaqAICreateTask ("daq::1!(0,3)", kNidaqWaveformCapture, &channum, &rpmID); nidaqAIConfigBuffer (rpmID, buffersize, kNidaqContinuous); nidaqAIConfigExternalScanClock (rpmID, "daq::1!(PFILowtoHigh1)"); // Ch B, High to Low nidaqAIStart (rpmID); t1 = Timer(); ResumeTimerCallbacks(); break; } //Resume Timer if not complete if(pt<(3*points)){ pt2 = pt; datapoints = points; wait = pt2/(3*datapoints)*100; SetCtrlVal(panelHandle, PANEL_WAITBAR, wait); ResumeTimerCallbacks();} //*** //************DAQ LOOP END ************** //*** //Data Full else{ wait = 0; done=1; SetCtrlVal(panelHandle, PANEL_WAITBAR, wait); ResetTextBox (panelHandle, PANEL_STATUSBOX, "acquisition complete"); SuspendTimerCallbacks();
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nidaqAIStop(taskID); nidaqAIDestroyTask(taskID); //*** //*****************MANIPULATION************** //*** //create cap and tach vector l=0; //'cap','tach','stage' vector index j=0; //'data' vector index for(n=0;n<logind;n++){ scanbacklog = backlog[n]; for(i=0;i<scanbacklog;i++){ cap[l] = data[j]; tach[l] = data[(j+(2*scanbacklog))]; stage[l] = data[(j+(1*scanbacklog))]; l++; j++;} j=j+(2*scanbacklog);} //Put data in surface array for(i=0;i<points;i++){ surfacecap[i][step] = cap[i]; surfacestage[i][step] = stage[i]; surfacetach[i][step] = tach[i]; } //find once-around vector indicies MaxMin1D (tach, points, &tachmax, &imax, &min, &imin); j=0; n=0; for(i=0;i<points;i++){ if(tach[i] > .5){ mark[j][step] = i; j++; tach[i+1] = 0; tach[i+2] = 0; tach[i+3] = 0; tach[i+4] = 0; tach[i+5] = 0; if(j>999){ break;} } } j = j-1; //No tach pulse error if(j<0){ MessagePopup("DAQ Error", "The last test could not resolve a\n" "once-per-rev pulse. Please change\n" "direction of rotation or side of\n"
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"square wave logic."); live = 0; datapresent = 0; break; } //point per rev check n = 0; for(i=0;i<j;i++){ sqcount[i] = mark[i+1][step] - mark[i][step]; if(sqcount[i] != encct){ n = 1; k = sqcount[i]; } } step++; SetCtrlVal(panelHandle, PANEL_SHOWSTEP, step); } // end else if(done==1){ //Was that the final ring? If not, acquire again if(step < totalsteps){ nextstep(); } //If that was last pass, clean up screen and start analysis if (step==totalsteps) analyze(); } //end 'done' if break; } return 0; } //PLOTSTEP //create polar plot & FFT and diplay measurements for one step int CVICALLBACK plotstep (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: //Pick which layer to plot GetCtrlVal(panelHandle, PANEL_SHOWSTEP, &showstep); if(showstep>totalsteps){ showstep=totalsteps; SetCtrlVal (panelHandle, PANEL_SHOWSTEP, showstep); } datastep=showstep-1;
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if(datapresent==0)break; //Delete old plots DeleteGraphPlot (panelHandle, PANEL_ROUNDPLOT, -1, VAL_IMMEDIATE_DRAW); DeleteGraphPlot (panelHandle, PANEL_FFTPLOT, -1, VAL_IMMEDIATE_DRAW); //Read in values for the chosen step from matrix testTIR = testTIRstore[step]; lsc = lscstore[datastep]; asymax = asymaxstore[datastep]; deg = degstore[datastep]; maxfft = maxfftstore[datastep]; ifftmax = ifftmaxstore[datastep]; rpm = rpmstore[datastep]; var = varstore[datastep]; a = astore[datastep]; b = bstore[datastep]; for(i=0;i<encct;i++){ capmean[i] = capmeanstore[i][datastep]; R[i] = Rstore[i][datastep]; } points=datapoints-(2*encct); for(i=0;i<points;i++){ fftx[i] = fftxstore[i][datastep]; } points=points-(2*encct); for(i=0;i<points;i++){ cap[i] = capsurfclean[i][datastep]; } //Show Calculations SetCtrlVal (panelHandle, PANEL_ESYNCH, lsc); SetCtrlVal (panelHandle, PANEL_FIM, testTIR); SetCtrlVal (panelHandle, PANEL_MAXASYNCH, asymax); SetCtrlVal (panelHandle, PANEL_ASYANGLE, deg); SetCtrlVal (panelHandle, PANEL_MAXFFT, maxfft); SetCtrlVal (panelHandle, PANEL_UPRBOX, ifftmax); //Plot Error Motion GetCtrlVal(panelHandle, PANEL_PLOTCONTROL, &n); if(n == 0){ if(lsc>1.0)circleval = ceil (lsc/2); if(lsc<1.0)circleval = (ceil (lsc*10/2))/10; } if(n == 1)circleval = 1; if(n == 2)circleval = 2; if(n == 3)circleval = 5; if(n == 4)circleval = 10; if(n == 5)circleval = 25;
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if(n == 6)circleval = 50; if(n == 7)circleval = 100; if(n == 8)circleval = 150; if(n == 9)circleval = 200; if(n == 10)circleval = 500; bcircle = 3*circleval; MaxMin1D (cap, points, &capmax, &imax, &capmin, &imin); Mean (capmean, encct, &mean); mean = mean + bcircle + fabs(capmin); //mean error circle radius //Set Axes if(capmax>circleval)max = capmax + bcircle + fabs(capmin); if(circleval>capmax)max = circleval + bcircle + fabs(capmin); SetAxisScalingMode (panelHandle, PANEL_ROUNDPLOT, VAL_XAXIS, VAL_MANUAL, -max , max); SetAxisScalingMode (panelHandle, PANEL_ROUNDPLOT, VAL_LEFT_YAXIS, VAL_MANUAL, -max, max); //Plot Total Error Motion for(i=0;i<points;i++)capplot[i] = cap[i] + fabs(capmin) + bcircle; ToRect1D (capplot, angle, points, &vecx[0], &vecy[0]); rgb = MakeColor (57, 201, 232); PlotXY (panelHandle, PANEL_ROUNDPLOT, vecx, vecy, points, VAL_DOUBLE,VAL_DOUBLE, VAL_THIN_LINE, VAL_EMPTY_SQUARE, VAL_SOLID, 1,rgb); //Synchronous Error Motion circles MaxMin1D (capmean, encct, &capmax, &imax, &min, &imin); capmax = capmax + fabs(capmin) + bcircle; //new 'capmax' min = min + fabs(capmin) + bcircle; //new 'min' ovalcolor = MakeColor(0, 130, 0); PlotOval (panelHandle, PANEL_ROUNDPLOT, mean, mean, -mean, -mean, VAL_LT_GRAY, VAL_TRANSPARENT);//mean x = circleval + mean; PlotOval (panelHandle, PANEL_ROUNDPLOT, x, x, -x, -x, ovalcolor, VAL_TRANSPARENT); //outer x = mean - circleval; PlotOval (panelHandle, PANEL_ROUNDPLOT, x, x, -x, -x, ovalcolor, VAL_TRANSPARENT); //inner PlotPoint (panelHandle, PANEL_ROUNDPLOT, 0.0, 0.0, VAL_CROSS, VAL_BLACK); //center cross PlotPoint (panelHandle, PANEL_ROUNDPLOT, a, b, VAL_CROSS, VAL_GREEN); //lsc center cross dcoffset=fabs(capmin) + bcircle; if (dcoffset>dcoffset_prev)dcoffset_max=dcoffset; //Plot Synchronous; for(i=0;i<encct;i++){ capplot[i] = capmean[i] + fabs(capmin) + bcircle; capplotstore[i][datastep] = capplot[i]; }
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ToRect1D (capplot, angle, encct, &vecx[0], &vecy[0]); PlotXY (panelHandle, PANEL_ROUNDPLOT, vecx, vecy, encct, VAL_DOUBLE, VAL_DOUBLE, VAL_THIN_LINE, VAL_EMPTY_SQUARE, VAL_SOLID, 1, VAL_BLACK); if(lsc>1.0)sprintf (tempchar, "-%.0f", circleval); if(lsc<1.0)sprintf (tempchar, "-%.1f", circleval); x = (mean - circleval)*cos(pi/4); y = (mean - circleval)*sin(pi/4); PlotText (panelHandle, PANEL_ROUNDPLOT, x, y, tempchar, VAL_APP_META_FONT, VAL_BLACK, VAL_TRANSPARENT); if(lsc>1.0)sprintf (tempchar, "%.0f", circleval); if(lsc<1.0)sprintf (tempchar, "%.1f", circleval); x = (mean + circleval)*cos(pi/4); y = (mean + circleval)*sin(pi/4); PlotText (panelHandle, PANEL_ROUNDPLOT, x, y, tempchar, VAL_APP_META_FONT, VAL_BLACK, VAL_TRANSPARENT); //Plot FFT GetCtrlVal (panelHandle, PANEL_FFTPLOTSCALE, &fftscale); if(fftscale == 0){if(cutoff == 0){xpts = encct/2*inc;} else{xpts = cutoff*inc;} } if(fftscale == 1){xpts = cpr*revs*0.01/2;} //1% if(fftscale == 2){xpts = cpr*revs*0.05/2;} //5% if(fftscale == 3){xpts = cpr*revs*0.1/2;} //10% if(fftscale == 4){xpts = cpr*revs*0.15/2;} //15% if(fftscale == 5){xpts = cpr*revs*0.25/2;} //25% if(fftscale == 6){xpts = cpr*revs*0.5/2;} //50% if(fftscale == 7){xpts = cpr*revs*0.75/2;} //75% if(fftscale == 8){xpts = encct*inc/2;} //Full Scale xupr = xpts/revs; SetCtrlVal(panelHandle, PANEL_FFTPLOTXSCALE, xupr); //FFT Plot GetCtrlVal(panelHandle, PANEL_FFTYMAX, &max); if(max < 1.00){MaxMin1D (capfft, points, &max, &imax, &min, &imin);} fftcolor = MakeColor (255, 100, 100); FFTPlot2(panelHandle,PANEL_FFTPLOT,capfft,fftx,xtemp,max,points,xpts,fftcolor); //Date and Time SetCtrlVal (panelHandle, PANEL_MONTHBOX, month); SetCtrlVal (panelHandle, PANEL_DAYBOX, day); SetCtrlVal (panelHandle, PANEL_YEARBOX, year); SetCtrlVal (panelHandle, PANEL_HOURBOX, hour); SetCtrlVal (panelHandle, PANEL_MINUTEBOX_2, minutetens); SetCtrlVal (panelHandle, PANEL_MINUTEBOX, minute); //Done With Acq. live = 0; datapresent = 1;
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//RPM Task/Scan Clock/Buffer nidaqAICreateTask ("daq::1!(0,3)", kNidaqWaveformCapture, &channum, &rpmID); nidaqAIConfigBuffer (rpmID, buffersize, kNidaqContinuous); nidaqAIConfigExternalScanClock (rpmID, "daq::1!(PFILowtoHigh1)"); // Ch B, High to Low nidaqAIStart (rpmID); t1 = Timer(); ResumeTimerCallbacks(); break; } return 0; } //STOP //stop acquisition when stop button is pressed int CVICALLBACK stop (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: if(live == 1 | liverev == 1 ){ SuspendTimerCallbacks(); nidaqAIStop(taskID); nidaqAIDestroyTask(taskID); live = 0; datapresent = 0; liverev = 0; revdatapresent = 0; wait = 0; SetCtrlVal(panelHandle, PANEL_WAITBAR, wait); ResetTextBox (panelHandle, PANEL_STATUSBOX, " "); if(test == 1)test = 0; if(test == 2)test = 1; step=0; } break; } return 0; } //---------------------------------------------------------------------------- // SetControlAttributes For 3d plot //---------------------------------------------------------------------------- static int SetControlAttributes(void) { int error = 0;
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OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_LIGHTING_ENABLE, 1); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_LIGHT_SELECT, 1); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_LIGHT_ENABLE, 1); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_LIGHT_DISTANCE, 3.0); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_VIEW_DISTANCE,2.0); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_PROJECTION_TYPE,OGLVAL_PERSPECTIVE); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_BGCOLOR,OGLVAL_WHITE); // Setup Axis Labels OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_XNAME_VISIBLE,1); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_YNAME_VISIBLE,1); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_ZNAME_VISIBLE,1); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_XNAME,"Form error"); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_YNAME," "); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_ZNAME,"Height"); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_XLABEL_VISIBLE,0); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_YLABEL_VISIBLE,0); OGLSetCtrlAttribute(panelHandle,surfaceControl,OGLATTR_ZLABEL_VISIBLE,0); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_XLABEL_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_YLABEL_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_ZLABEL_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_XNAME_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_YNAME_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_ZNAME_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_XY_GRID_VISIBLE, 1); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_YZ_GRID_VISIBLE, 1); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_XZ_GRID_VISIBLE, 1); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_XY_GRID_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_YZ_GRID_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_XZ_GRID_COLOR, OGLVAL_LT_GRAY); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_XPRECISION,0); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_YPRECISION,0); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_ZPRECISION,0); Error : return error; } //---------------------------------------------------------------------------- // CreatePlot 3d plot //----------------------------------------------------------------------------
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static int CreatePlot(void) { int error = 0; int plotTypeIs3D = 1; int numPlots; double radxStep; double radyStep; int plot; register int i,j; double x,y; double xStep,yStep; void * pts; double *pts3DPtr; OGLVertexD *pts2DPtr; // Setup control OGLSetCtrlAttribute (panelHandle,surfaceControl,OGLATTR_PLOTAREA_ZSTART, 0.0); OGLSetCtrlAttribute (panelHandle,surfaceControl,OGLATTR_PLOTAREA_ZSIZE, 0.6); OGLSetCtrlAttribute (panelHandle,surfaceControl,OGLATTR_VIEW_AUTO_DISTANCE, 0); OGLSetCtrlAttribute (panelHandle,surfaceControl,OGLATTR_VIEW_DISTANCE, 2.0); OGLGetCtrlAttribute (panelHandle,surfaceControl,OGLATTR_NUM_PLOTHANDLES,&numPlots); // Delete any existing plots for (i=0;i<numPlots;i++) { OGLGetCtrlAttribute(panelHandle,surfaceControl, OGLATTR_FIRST_PLOTHANDLE, &plot); OGLDeletePlot(panelHandle,surfaceControl,plot,0); } plot = OGLPlot3DScatter (panelHandle, surfaceControl, bobert, 1, 30719, OGLVAL_DOUBLE); // Setup plot attributes OGLSetPlotAttribute(panelHandle,surfaceControl,plot,OGLATTR_SURFACE_STYLE,OGLVAL_SMOOTH); OGLSetPlotAttribute(panelHandle,surfaceControl,plot,OGLATTR_SURFACE_COLOR,OGLVAL_RED); OGLSetPlotAttribute(panelHandle,surfaceControl,plot,OGLATTR_SURFACE_SPECULAR_FACTOR,1.0); OGLSetPlotAttribute(panelHandle,surfaceControl,plot,OGLATTR_SURFACE_SHININESS,50); OGLSetPlotAttribute(panelHandle,surfaceControl,plot,OGLATTR_WIRE_STYLE,OGLVAL_SOLID); OGLSetPlotAttribute (panelHandle, surfaceControl, plot, OGLATTR_WIRE_COLOR, OGLVAL_DK_GRAY); //} // Display plot OGLRefreshGraph(panelHandle,surfaceControl);
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Error : return error; } //---------------------------------------------------------------------------- // 3d plot control properties //---------------------------------------------------------------------------- int CVICALLBACK properties (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: OGLPropertiesPopup(panelHandle,surfaceControl); break; } return 0; } //---------------------------------------------------------------------------- // DemoPanelCallback - Since CVI does not know about CVIOGL control, we must // manually resize the CVIOGL control whenever the picture control is resized. //---------------------------------------------------------------------------- int CVICALLBACK DemoPanelCallback (int panel, int event, void *callbackData, int eventData1, int eventData2) { int width, height, top, left; switch (event) { case EVENT_PANEL_SIZE: GetCtrlAttribute(panelHandle, PANEL_PICTURE, ATTR_TOP, &top); GetCtrlAttribute(panelHandle, PANEL_PICTURE, ATTR_LEFT, &left); GetCtrlAttribute(panelHandle, PANEL_PICTURE, ATTR_WIDTH, &width); GetCtrlAttribute(panelHandle, PANEL_PICTURE, ATTR_HEIGHT, &height); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_TOP, top); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_LEFT, left); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_WIDTH, width); OGLSetCtrlAttribute (panelHandle, surfaceControl, OGLATTR_HEIGHT, height); OGLRefreshGraph(panelHandle, surfaceControl); break; } return 0; } //---------------------------------------------------------------------------- // Change 3d Plot Type //---------------------------------------------------------------------------- int CVICALLBACK ChangePlotType (int panel, int control, int event,
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void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: CreatePlot(); break; } return 0; } //Plot FFT int CVICALLBACK fftplotxscale (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: //if no data, then break if(datapresent == 0){break;} //Clear FFT plot DeleteGraphPlot (panelHandle, PANEL_FFTPLOT, -1, VAL_IMMEDIATE_DRAW); //Plot FFT GetCtrlVal (panelHandle, PANEL_FFTPLOTXSCALE, &xupr); if(xupr > cpr/2)xupr = cpr/2; xpts = xupr*revs; //FFT Plot GetCtrlVal(panelHandle, PANEL_FFTYMAX, &max); if(max < 1.00){MaxMin1D (capfft, points, &max, &imax, &min, &imin);} fftcolor = MakeColor (255, 100, 100); FFTPlot2(panelHandle,PANEL_FFTPLOT,capfft,fftx,xtemp,max,points,xpts,fftcolor); break; } return 0; } //Plot FFT int CVICALLBACK fftplotscale (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: //if no data, then break if(datapresent == 0){break;} //Clear FFT plot
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DeleteGraphPlot (panelHandle, PANEL_FFTPLOT, -1, VAL_IMMEDIATE_DRAW); //Plot FFT GetCtrlVal (panelHandle, PANEL_FFTPLOTSCALE, &fftscale); if(fftscale == 0){if(cutoff == 0){xpts = encct/2*inc;} else{xpts = cutoff*inc;} } if(fftscale == 1){xpts = cpr*revs*0.01/2;} //1% if(fftscale == 2){xpts = cpr*revs*0.05/2;} //5% if(fftscale == 3){xpts = cpr*revs*0.1/2;} //5% if(fftscale == 4){xpts = cpr*revs*0.15/2;} //5% if(fftscale == 5){xpts = cpr*revs*0.25/2;} //25% if(fftscale == 6){xpts = cpr*revs*0.5/2;} //50% if(fftscale == 7){xpts = cpr*revs*0.75/2;} //75% if(fftscale == 8){xpts = encct*inc/2;} //Full Scale xupr = xpts/revs; SetCtrlVal(panelHandle, PANEL_FFTPLOTXSCALE, xupr); //FFT Plot GetCtrlVal(panelHandle, PANEL_FFTYMAX, &max); if(max < 1.00){MaxMin1D (capfft, points, &max, &imax, &min, &imin);} fftcolor = MakeColor (255, 100, 100); FFTPlot2(panelHandle,PANEL_FFTPLOT,capfft,fftx,xtemp,max,points,xpts,fftcolor); break; } return 0; } //indicator timer int CVICALLBACK timer2 (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_TIMER_TICK: if(livebar == 0){break;} if (livebar == 1){ SuspendTimerCallbacks(); nidaqAIRead (taskIDtir, "daq::1!(0)", 1, -1.0, &datum); GetCtrlVal (panelHandle, PANEL_BARSCALE, &tirdiv); if(tirdiv == 0){tirscl = 100; SetCtrlAttribute (panelHandle, PANEL_BARIND, ATTR_MIN_VALUE, -1000.0); SetCtrlAttribute (panelHandle, PANEL_BARIND, ATTR_MAX_VALUE, 1000.0);} //2000 div if(tirdiv == 1){tirscl = 10;
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SetCtrlAttribute (panelHandle, PANEL_BARIND, ATTR_MIN_VALUE, -100.0); SetCtrlAttribute (panelHandle, PANEL_BARIND, ATTR_MAX_VALUE, 100.0);} //200 div if(tirdiv == 2){ tirscl = 1; SetCtrlAttribute (panelHandle, PANEL_BARIND, ATTR_MIN_VALUE, -10.0); SetCtrlAttribute (panelHandle, PANEL_BARIND, ATTR_MAX_VALUE, 10.0);} //20 div GetCtrlVal(options, OPTIONS_GAGESENSE, &sense); vcap = datum*sense/tirscl; //scaled vcapin = datum*sense; //microinches SetCtrlVal (panelHandle, PANEL_LEDR, 0); SetCtrlVal (panelHandle, PANEL_LEDL, 0); if(vcap > 10 | vcap == 10){ vcap = 10; SetCtrlVal (panelHandle, PANEL_LEDR, 1); } if(vcap < -10 | vcap == -10){ vcap = -10; SetCtrlVal (panelHandle, PANEL_LEDL, 1); } SetCtrlVal (panelHandle, PANEL_BARIND, vcapin); } if (livebar == 1){ ResumeTimerCallbacks();} break; } return 0; } //Polar plot scale int CVICALLBACK plotscale (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: if(datapresent == 0)break; DeleteGraphPlot (panelHandle, PANEL_ROUNDPLOT, -1, VAL_IMMEDIATE_DRAW); //Plot Error Motion
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GetCtrlVal(panelHandle, PANEL_PLOTCONTROL, &n); if(n == 0){ if(lsc>1.0)circleval = ceil (lsc/2); if(lsc<1.0)circleval = (ceil (lsc*10/2))/10; } if(n == 1)circleval = 1; if(n == 2)circleval = 2; if(n == 3)circleval = 5; if(n == 4)circleval = 10; if(n == 5)circleval = 25; if(n == 6)circleval = 50; if(n == 7)circleval = 100; if(n == 8)circleval = 150; if(n == 9)circleval = 200; if(n == 10)circleval = 500; bcircle = 3*circleval; MaxMin1D (cap, points, &capmax, &imax, &capmin, &imin); Mean (capmean, encct, &mean); mean = mean + bcircle + fabs(capmin); //mean error circle radius //Set Axes if(capmax>circleval)max = capmax + bcircle + fabs(capmin); if(circleval>capmax)max = circleval + bcircle + fabs(capmin); SetAxisScalingMode (panelHandle, PANEL_ROUNDPLOT, VAL_XAXIS, VAL_MANUAL, -max , max); SetAxisScalingMode (panelHandle, PANEL_ROUNDPLOT, VAL_LEFT_YAXIS, VAL_MANUAL, -max, max); //Plot Total Error Motion for(i=0;i<points;i++)capplot[i] = cap[i] + fabs(capmin) + bcircle; ToRect1D (capplot, angle, points, &vecx[0], &vecy[0]); rgb = MakeColor (57, 201, 232); PlotXY (panelHandle, PANEL_ROUNDPLOT, vecx, vecy, points, VAL_DOUBLE,VAL_DOUBLE, VAL_THIN_LINE, VAL_EMPTY_SQUARE, VAL_SOLID, 1, rgb); //Synchronous Error Motion circles MaxMin1D (capmean, encct, &capmax, &imax, &min, &imin); capmax = capmax + fabs(capmin) + bcircle; //new 'capmax' min = min + fabs(capmin) + bcircle; //new 'min' ovalcolor = MakeColor(0, 130, 0); PlotOval (panelHandle, PANEL_ROUNDPLOT, mean, mean, -mean, -mean, VAL_LT_GRAY, VAL_TRANSPARENT);//mean x = circleval + mean; PlotOval (panelHandle, PANEL_ROUNDPLOT, x, x, -x, -x, ovalcolor, VAL_TRANSPARENT); //outer x = mean - circleval; PlotOval (panelHandle, PANEL_ROUNDPLOT, x, x, -x, -x, ovalcolor, VAL_TRANSPARENT); //inner
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PlotPoint (panelHandle, PANEL_ROUNDPLOT, 0.0, 0.0, VAL_CROSS, VAL_BLACK); //center cross PlotPoint (panelHandle, PANEL_ROUNDPLOT, a, b, VAL_CROSS, VAL_GREEN); //lsc center cross //Plot Synchronous; for(i=0;i<encct;i++)capplot[i] = capmean[i] + fabs(capmin) + bcircle; ToRect1D (capplot, angle, encct, &vecx[0], &vecy[0]); PlotXY (panelHandle, PANEL_ROUNDPLOT, vecx, vecy, encct, VAL_DOUBLE, VAL_DOUBLE, VAL_THIN_LINE, VAL_EMPTY_SQUARE, VAL_SOLID, 1, VAL_BLACK); if(lsc>1.0)sprintf (tempchar, "-%.0f", circleval); if(lsc<1.0)sprintf (tempchar, "-%.1f", circleval); x = (mean - circleval)*cos(pi/4); y = (mean - circleval)*sin(pi/4); PlotText (panelHandle, PANEL_ROUNDPLOT, x, y, tempchar, VAL_APP_META_FONT, VAL_BLACK, VAL_TRANSPARENT); if(lsc>1.0)sprintf (tempchar, "%.0f", circleval); if(lsc<1.0)sprintf (tempchar, "%.1f", circleval); x = (mean + circleval)*cos(pi/4); y = (mean + circleval)*sin(pi/4); PlotText (panelHandle, PANEL_ROUNDPLOT, x, y, tempchar, VAL_APP_META_FONT, VAL_BLACK, VAL_TRANSPARENT); break; } return 0; } //Change units on display int CVICALLBACK units (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: GetCtrlVal(panelHandle, PANEL_UNITS, &n); //metric units if(n == 1){ ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_6, 0, "nm"); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_8, 0, "nm"); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_10, 0, "nm"); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_14, 0, "nm"); ReplaceTextBoxLine (options, OPTIONS_TEXTBOX_2, 0, "nm"); } //english units else{ ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_6, 0, "µin."); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_8, 0, "µin."); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_10, 0, "µin.");
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ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_14, 0, "µin."); ReplaceTextBoxLine (options, OPTIONS_TEXTBOX_2, 0, "µin."); } break; } return 0; } //Change units on display int CVICALLBACK revunits (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: SetCtrlVal(panelHandle, PANEL_UNITS, n); //metric units if(n == 1){ ReplaceTextBoxLine (options, OPTIONS_TEXTBOX_2, 0, "nm"); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_6, 0, "nm"); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_8, 0, "nm"); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_10, 0, "nm"); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_14, 0, "nm"); } //english units else{ ReplaceTextBoxLine (options, OPTIONS_TEXTBOX_2, 0, "µin."); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_6, 0, "µin."); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_8, 0, "µin."); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_10, 0, "µin."); ReplaceTextBoxLine (panelHandle, PANEL_TEXTBOX_14, 0, "µin."); } break; } return 0; } //Load Picture int CVICALLBACK picture (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_LEFT_CLICK: err = FileSelectPopup ("", "*.bmp","*.pcx;*.bmp;*.dib;*.rle;*.ico;*.wmf;*.emf", "", VAL_OK_BUTTON, 0, 0, 1, 0, &path[0]);
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err = strlen (path); if(err == 0){break;} DisplayImageFile (panelHandle, PANEL_PICTURE, path); break; } return 0; } //Turn filter on/off int CVICALLBACK filttoggle (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: GetCtrlVal(panelHandle, PANEL_FILTTOGGLE, &n); //on, turn off if(n == 0){ SetCtrlAttribute (panelHandle, PANEL_FILTCUTOFF, ATTR_DIMMED, 1); break;} //off, turn on if(n == 1){ SetCtrlAttribute (panelHandle, PANEL_FILTCUTOFF, ATTR_DIMMED, 0); break;} break; } return 0; } //Precision of numbers shown int CVICALLBACK precision (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: GetCtrlVal(options, OPTIONS_PRECISION, &n); SetCtrlAttribute (panelHandle, PANEL_ESYNCH, ATTR_PRECISION, n); SetCtrlAttribute (panelHandle, PANEL_FIM, ATTR_PRECISION, n); SetCtrlAttribute (panelHandle, PANEL_MAXASYNCH, ATTR_PRECISION, n); SetCtrlAttribute (panelHandle, PANEL_MAXFFT, ATTR_PRECISION, n); SetCtrlAttribute (panelHandle, PANEL_UPRBOX, ATTR_PRECISION, n); break; } return 0; } //Quit Program
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//triggers U500 to stop spindle, disable axes int CVICALLBACK quit (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: AOUpdateChannel (1, "1", 5.0); Delay(pulse); AOUpdateChannel (1, "1", 0.0); QuitUserInterface (0); break; } return 0; } //** //***********************MENU BARS ****************************** //** //MeasureMenu Bar void CVICALLBACK measure (int menuBar, int menuItem, void *callbackData, int panel) { switch(menuItem){ case ROUNDMENU_MEASUREMENT_SAVE: Clear1D (capsave, 2000000); Clear1D (stagesave, 2000000); Clear1D (tachsave, 2000000); if(datapresent == 0)break; //Write surfacecap and surfacestage matrices to vectors points = datapoints; // revert to stored value for(m=0;m<totalsteps;m++){ for(n=0;n<points;n++){ capsave[(m*points)+n] = surfacecap[n][m]; stagesave[(m*points)+n] = surfacestage[n][m]; tachsave[(m*points)+n] = surfacetach[n][m]; } } for(n=0;n<points;n++){ filtcap[n] = capsurfclean[n][1]; } //Put settings into vector settings[0]=encct; settings[1]=sense; settings[2]=totalsteps; settings[3]=stepsize; settings[4]=revnum; settings[5]=datapoints; err = DirSelectPopup ("", "Select Directory", 1, 1, &path[0]);
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if(err < 1){break;} err = SetDir (path); //Long vectors from matrices ArrayToFile ("capsave", capsave, VAL_DOUBLE, (points*totalsteps), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_CONST_WIDTH, 10, VAL_ASCII, VAL_OPEN_AS_IS); ArrayToFile ("stagesave", stagesave, VAL_DOUBLE, (points*totalsteps), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_CONST_WIDTH, 10, VAL_ASCII, VAL_OPEN_AS_IS); ArrayToFile ("tachsave", tachsave, VAL_DOUBLE, (points*totalsteps), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_CONST_WIDTH, 10, VAL_ASCII, VAL_OPEN_AS_IS); ArrayToFile ("settings", settings, VAL_DOUBLE, (6), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_CONST_WIDTH, 10, VAL_ASCII, VAL_OPEN_AS_IS); ArrayToFile ("astore", astore, VAL_DOUBLE, (100), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_CONST_WIDTH, 10, VAL_ASCII, VAL_OPEN_AS_IS); ArrayToFile ("bstore", bstore, VAL_DOUBLE, (100), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_CONST_WIDTH, 10, VAL_ASCII, VAL_OPEN_AS_IS); ArrayToFile ("filtcap", filtcap, VAL_DOUBLE, (points), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_CONST_WIDTH, 10, VAL_ASCII, VAL_OPEN_AS_IS); MessagePopup ("Save Complete", "Save has completed. Vectors\n" "have been created in the selected directory.\n" "\n"); break; case ROUNDMENU_MEASUREMENT_PRINT: SetPrintAttribute (ATTR_ORIENTATION, VAL_LANDSCAPE); SetPrintAttribute (ATTR_COLOR_MODE, VAL_GRAYSCALE); SetPrintAttribute (ATTR_PRINT_AREA_HEIGHT, VAL_USE_ENTIRE_PAPER); SetPrintAttribute (ATTR_PRINT_AREA_WIDTH, VAL_INTEGRAL_SCALE); SetPrintAttribute (ATTR_BITMAP_PRINTING, 1); PrintPanel (panelHandle, "", 1, VAL_FULL_PANEL, 1);
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break; case ROUNDMENU_MEASUREMENT_LOAD: //Set Path err = DirSelectPopup ("", "Select Directory", 1, 1, &path[0]); if(err < 1){break;} err = SetDir (path); err = FileToArray ("settings", settings, VAL_DOUBLE, 6, 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_ASCII); //Put settings into vector encct = settings[0]; sense = settings[1]; totalsteps = settings[2]; stepsize = settings[3]; revnum = settings[4]; datapoints = settings[5]; points = datapoints; //Get Encoder Value perrev = encct; SetCtrlVal (panelHandle, PANEL_REVNUM, revnum); SetCtrlVal(options, OPTIONS_ENCCOUNT, encct); SetCtrlVal(options, OPTIONS_GAGESENSE, sense); SetCtrlVal(options, OPTIONS_TOTALSTEPS, totalsteps); SetCtrlVal(options, OPTIONS_STEPSIZE, stepsize); err = FileToArray ("capsave", capsave, VAL_DOUBLE, (points*totalsteps), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_ASCII); err = FileToArray ("stagesave", stagesave, VAL_DOUBLE, (points*totalsteps), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_ASCII); err = FileToArray ("tachsave", tachsave, VAL_DOUBLE, (points*totalsteps), 1, VAL_GROUPS_TOGETHER, VAL_GROUPS_AS_COLUMNS, VAL_ASCII); if(err<0){break;} //Stored settings recovery for(m=0;m<totalsteps;m++){ for(n=0;n<points;n++){ surfacecap[n][m] = capsave[(m*points)+n]; surfacestage[n][m] = stagesave[(m*points)+n]; surfacetach[n][m] = tachsave[(m*points)+n]; tach[n] = surfacetach[n][m]; }
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//find once-around vector indicies MaxMin1D (tach, points, &tachmax, &imax, &min, &imin); j=0; for(n=0;n<points;n++){ if(tach[n] > .5){ mark[j][m] = n; j++; tach[n+1] = 0; tach[n+2] = 0; tach[n+3] = 0; tach[n+4] = 0; tach[n+5] = 0; if(j>999){ break;} } } j = j-1; //No tach pulse error if(j<0){ MessagePopup("DAQ Error", "The last test could not resolve a\n" "once-per-rev pulse. Please change\n" "direction of rotation or side of\n" "square wave logic."); live = 0; datapresent = 0; break; } //point per rev check n = 0; for(i=0;i<j;i++){ sqcount[i] = mark[i+1][step] - mark[i][step]; if(sqcount[i] != encct){ n = 1; k = sqcount[i]; } } } datapoints = points; // revert to stored value loaded = 1; //indicates that data is from file: bypasses some operations later //Use "Reload" button MessagePopup ("Load Complete", "Load has completed. Select 'MEASUREMENT>Reload'\n"
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"to view data.\n" "\n"); //points = points - 2 revs datapresent = 1; break; case ROUNDMENU_MEASUREMENT_RELOAD: //if no data, break if(datapresent == 0){break;} //revert to 'analyze' function call up top analyze(); break; case ROUNDMENU_WINDOW_OPTIONS: InstallPopup (options); SetPanelAttribute (panelHandle, ATTR_DIMMED, 1); break; case ROUNDMENU_WINDOW_REVERSAL: GetCtrlVal(options, OPTIONS_ENCCOUNT, &encct); break; case ROUNDMENU_WINDOW_TIR_IND: SuspendTimerCallbacks(); //Initialize Board Init_DA_Brds (1, &brdcode); indon = 1; liverev = 0; live = 0; InstallPopup(tirpanel); SetPanelAttribute (panelHandle, ATTR_DIMMED, 1); nidaqAICreateTask ("daq::1!(0,2)", kNidaqPointByPoint, &channum, &taskIDtir); nidaqAIStart (taskIDtir); ResumeTimerCallbacks(); break; case ROUNDMENU_MEASUREMENT_MENUQUIT: QuitUserInterface (0); break; }
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} /******************************************************/ /* TIR INDICATOR */ /******************************************************/ int tirdiv; double datum, vcap, vcapin, tirscl; //Timer int CVICALLBACK timetick (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_TIMER_TICK: if (indon == 0){ break;} if (indon == 1){ SuspendTimerCallbacks(); GetCtrlVal (tirpanel, TIRPANEL_CAPSWITCH, &capswitch); if(capswitch==1){ nidaqAIRead (taskIDtir, "daq::1!(2)", 1, -1.0, &datum);} if(capswitch==0){ nidaqAIRead (taskIDtir, "daq::1!(0)", 1, -1.0, &datum);} GetCtrlVal (tirpanel, TIRPANEL_TIRSCALE, &tirdiv); if(tirdiv == 0){tirscl = 100; SetCtrlAttribute (tirpanel, TIRPANEL_DIAL_IND, ATTR_MIN_VALUE, -1000.0); SetCtrlAttribute (tirpanel, TIRPANEL_DIAL_IND, ATTR_MAX_VALUE, 1000.0);} //2000 div if(tirdiv == 1){tirscl = 10; SetCtrlAttribute (tirpanel, TIRPANEL_DIAL_IND, ATTR_MIN_VALUE, -100.0); SetCtrlAttribute (tirpanel, TIRPANEL_DIAL_IND, ATTR_MAX_VALUE, 100.0);} //200 div if(tirdiv == 2){ tirscl = 1; SetCtrlAttribute (tirpanel, TIRPANEL_DIAL_IND, ATTR_MIN_VALUE, -10.0); SetCtrlAttribute (tirpanel, TIRPANEL_DIAL_IND, ATTR_MAX_VALUE, 10.0);} //20 div GetCtrlVal(options, OPTIONS_GAGESENSE, &sense); vcap = datum*sense/tirscl; //scaled vcapin = datum*sense; //microinches SetCtrlVal (tirpanel, TIRPANEL_LEDR, 0); SetCtrlVal (tirpanel, TIRPANEL_LEDL, 0); if(vcap > 10 | vcap == 10){ vcap = 10;
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SetCtrlVal (tirpanel, TIRPANEL_LEDR, 1); } if(vcap < -10 | vcap == -10){ vcap = -10; SetCtrlVal (tirpanel, TIRPANEL_LEDL, 1); } SetCtrlVal (tirpanel, TIRPANEL_DIAL_IND, vcapin); SetCtrlVal (tirpanel, TIRPANEL_DIGIT_IND, vcapin); } if (indon == 1){ ResumeTimerCallbacks();} break; } return 0; } //TIR Close int CVICALLBACK close_tir (int panel, int control, int event, void *callbackData, int eventData1, int eventData2) { switch (event) { case EVENT_COMMIT: SuspendTimerCallbacks(); indon = 0; nidaqAIStop (taskIDtir); nidaqAIDestroyTask (taskIDtir); RemovePopup(0); SetPanelAttribute (panelHandle, ATTR_DIMMED, 0); //RPM Task/Scan Clock/Buffer nidaqAICreateTask ("daq::1!(0,3)", kNidaqWaveformCapture, &channum, &rpmID); nidaqAIConfigBuffer (rpmID, buffersize, kNidaqContinuous); nidaqAIConfigExternalScanClock (rpmID, "daq::1!(PFILowtoHigh1)"); // Ch B, High to Low nidaqAIStart (rpmID); t1 = Timer(); ResumeTimerCallbacks(); break; } return 0; } int CVICALLBACK clear (int panel, int control, int event, void *callbackData, int eventData1, int eventData2)
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{ switch (event) { case EVENT_COMMIT: Clear1D(cap, points); Clear1D(tach, points); Clear1D(stage, points); Clear1D(dddzarray, 200000); Clear1D(dddmag, 200000); Clear1D(dddphase, 200000); for(step=0;step<totalsteps;step++){ for(i=0;i<points;i++){ surfacecap[i][step] = cap[i]; surfacestage[i][step] = stage[i]; surfacetach[i][step] = tach[i]; } } step=0; nextstep(); break; } return 0; }