using time waveform analysis to distinguish looseness from misalignment

7/29/2019 Using Time Waveform Analysis to Distinguish Looseness From Misalignment

1/5

Emerson Process Management - CSI

DoctorKnow Application PaperTitle: Using Time Waveform Analysis to Distinguish Looseness from Misalignment

Source/

Author:

Trish Whaley

Product: MasterTrend

Technology: MasterTrend

Classification:

Time waveform analysis is a very useful but often neglected diagnostic tool. It was widely used

during the 1960's, but fell out of fashion with the advent of swept-filter analyzers. Today, time

waveform analysis is increasingly used by CSI analysts to assist in routine diagnostic work.

Machinery vibration diagnostics is based on the principle that the "forcing function" causing a

machine to vibrate is found by measuring the frequencies of predominant peaks as multiples of theshaft speed. However, various machinery defects, such as misalignment and looseness, generate

similar spectral patterns, and may easily be con-fused by an inexperienced analyst.

The spectral pattern of both misalignment and looseness problems show an increase in the amplitude

levels of peaks located at one two and/or three times the shaft speed. These types of spectral patterns

present a typical situation in which examining the time waveform is often useful for determining the

specific problem actually causing the machine vibration. Experience has shown that time waveform

analysis is most useful using acceleration as the units for amplitude.

The time waveform associated with misalignment should show a regular, periodic spacing between

major peaks. These peaks generally occur two or three times per shaft rotation. In addition, the

amplitudes of these peaks typically follow a pattern as well; for example, one of three major peaks

per shaft rotation may consistently be higher in amplitude.

Characteristics which distinguish misalignment from looseness appear in the frequency domain as

well as in the time domain. The amplitude level of the time waveform peaks is normally less than

two Gs indicating relatively little impacting. In the frequency domain, impacting results in an

elevated noise floor of the spectrum; a lower noise floor (indicating negligible impacting) thereforetends to imply misalignment as the cause of vibration.

Time waveforms associated with looseness are characterized by an irregular spacing between the

major peaks. In addition, there is no pattern to the amplitude levels of these peaks they appear in ran-

dom variation. It is not uncommon to observe impacts of up to six Gs, or more in some severe cases.

These impacts produce an elevated noise floor in the spectral plot.

Distinguishing misalignment from looseness is greatly enhanced by observing these basic patterns in

both time and frequency domains. For example, the spectrum and waveform (Figures 1 and 2, respec-

tively) of a turbine generator reveal evidence of misalignment. A casual glance at the spectrum

might seem to indicate a looseness problem because of the number of visible harmonic peaks;

however, number of visible harmonic peaks; however, the noise floor is very low - a characteristic of

misalignment. The time waveform contains two major peaks per shaft revolution with a well-

http://www.compsys.com/DRKNOW/APLPAPR.NSF/ap...63FFD277AB0EC01852565A20063CFB7?OpenDocument (1 de 5)05/07/2010 18:30:09


2/5


established amplitude level pattern-also suggesting misalignment as the cause of vibration.

The spectrum of an example boiler feed pump (Figure 3), also contains a large number of harmonic

peaks, but the noise floor is highly elevated. The time waveform (Figure 4) shows irregular spacing

between peaks with random, variable amplitude levels. Both the spectral and the waveform patterns

suggest looseness as the cause of vibration for this machine.

Some spectral and time waveform plots will show evidence of both defects. In these cases,misalignment may be driving the looseness, or the looseness may be so severe as to allow

misalignment to occur. Because of these types of situations, time waveform criteria do not eliminate

spectral analysis, they simply augment the diagnostic process when misalignment or looseness is

suspected. Time waveform analysis should be used strictly in combination with spectral analysis as

an additional, valuable tool for the analyst.



3/5




4/5




5/5


All contents copyright 1998 - 2006, Computational Systems, Inc.

All Rights Reserved.

http://www compsys com/DRKNOW/APLPAPR NSF/ap 63FFD277AB0EC01852565A20063CFB7?OpenDocument (5 de 5)05/07/2010 18:30:09

using time waveform analysis to distinguish looseness from misalignment

Documents