Applications of Time-Frequency Analysis Techniques
on Machinery Fault Diagnosis
ZhuangLi, Lin
Liu,
Suri
Ganeriwala
SpectraQuest Inc., 8201 Hermitage Road, Richmond, VA 23228
Published: August 2006
Abstract
Generally speaking the sound and vibration
signals obtained from a rotating machine are time-variant since they
are strongly related to the rotational speed which is not constant
even in the macro steady state. Since the mostly used signal
processing method, the Fourier analysis, is only suitable for
stationary signals, the development of the joint time-frequency
analysis is demanded. Both the linear and quadratic time-frequency
analysis approaches have been introduced. The performances of these
algorithms were compared. Several tips were then summarized for you
to pick an appropriate method for your application. Several
successful applications of the time-frequency analysis methods on
the machinery fault diagnosis were presented in detail.
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Introduction
For scientists and engineers, a system under
study is usually considered as a black-box. In general cases people
only can obtain useful information by analyzing the measured signals
acquired from the system. Therefore, the signal processing
techniques are helpful and indispensable tools for us to extract
useful information and features associated with the system. The last
several decades have seen many innovative signal processing
approaches developed, and some of them have already found successful
applications in machinery fault diagnostics. Wavelet transform,
short-time Fourier transform, Gabor expansion, Wigner-Ville
distribution (WVD), cepstrum, bispectrum, correlation method,
high-resolution spectral analysis, statistical analysis, etc. are
all hot topics nowadays. How to select an appropriate method for a
particular problem is then an interesting question. Spectra Quest,
Inc. is planning to publish a series of tech notes on the
applications of advanced signal processing techniques on machinery
fault diagnosis. For the purpose of simplicity, we will try to avoid
presenting theories behind these techniques. These tech notes are
going to focus on the industrial applications with plenty of
examples. Advantages, disadvantages, and suitable applications will
be discussed for each technique. The performance of some related
techniques will be further compared.
Fig 1. Zoomed Gabor spectrogram of the oil whip
component
Fig 2. Gabor transform of a shut-down test on MFS
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