measurement and instrumentation_lecture2
TRANSCRIPT
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MEASUREMENT AND INSTRUMENTATION
BMCC 4743
LECTURE 2: PERFORMANCE OF STATICCHARACTERISTICS IN MEASUREMENT
AND INSTRUMENTATION
Mochamad Safarudin
Faculty of Mechanical Engineering, UTeM
2008
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Contents
Definition of static
Requirement of static characteristicspreservation
Static calibration
Passive & active sensors
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Definition of Static
The steady staterelationship between input
and output of an instrument
Measurement of quantities that are constantor vary quite slowly with respect to time.
It does not involve differential equations.
All the static performance characteristics areobtained by one form or another via a
process called static calibration.
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Contents
Definition of static
Requirement of staticcharacteristics preservation
Static calibration
Passive & active sensors
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Requirement of static characteristics
preservation Precise & Accurate
Measurements that are close to each other
are precise Measurements that are close to the correct
value are accurate
Measurements can be: Precise but inaccurate Neither precise nor accurate
Precise and accurate
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Requirement of static characteristics
preservation Repeatability
The ability of an instrument to register readings accuratelyrepeatedly
Linearity The input and output relationship of a linear transducer canbe represented by the following equation:
wherey is theoutput of transducer,xis the input oftransducer, m is theslope of curve (transfer function), c isthe offset.
Often, the straight line approach is used for certain range ofoperation for a non-linear system.
y= mx+ c
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Requirement of static characteristics
preservation Hysteresis
Hysteresis results in predictable error. May be dueto internal friction, freeplay or looseness in the
mechanism of an instrument.
Also in electrical phenomena (relation between theoutput voltage and the input field current in a d.c.generator) - the effect is due to magnetic
hysteresis of the iron in the field coils. The transfer functions differ with the increase and
decrease of inputs as shown in the followingfigure.
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Generalized
graph
ofo
utput/inputrelationship
wherehysteresisispresent.(FromP.
H.Sydenham,
Han
dboo
k
of
Measuremen
t
Sc
ience,
Vol.
2,
Chichester,
U.K.,
JohnWiley&Sons,198
3)
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Linearity
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It is highly desirable that the measurement system has a
linier relationship between input and output means that
the change in output is proportional to the change in the
value of the measurandDeviation from true linearity is called linearity error
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Sensitivity
Sensitivity is the ratio of change in
magnitude of the output to the change
in magnitude of the measurand
Sensitivity=D(output)/D(input)
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Sensitivity and Non Linearity
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Contents
Definition of static
Requirement of static characteristics
preservation
Static calibration
Passive & active sensors
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Static Calibration
Imagine a situation in which all inputs (desired,interfering or modifying) except one are kept at someconstant values.
The one input under study is varied over some rangeof constant values which causes the output(s) to varyover some range of constant values.
The input/output relationships developed in this waycomprise a static calibration valid under the statedconstant conditions of all other inputs.
The procedure may be repeated for other inputs foroverall instrument static behaviour
Ultimate objective is to define measurement accuracy
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Contents
Definition of static
Requirement of static characteristics
preservation
Static calibration
Passive & active sensors
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EXERCISE
What is the meaning of the followingwords:
Measurand
Physical quantity
Data
Parameter
Transducer
Actuator
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ANSWER TO EXERCISE
Measurand: Physical quantity being measured
Physical quantity: Variable such as pressure,temperature, mass, length, etc
Data: Information obtained from theinstrumentation/measurement system as a result of themeasurements made of the physical quantities
Parameter: Physical quantity within defined (numeric)limits.
Transducer:A device that converts one form of energy toanother
Actuator: Electronic transducer that converts electrical energyinto mechanical energy
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Next Lecture
Analysis on Experimental Data
End of Lecture 2