### ASA 125th Meeting Ottawa 1993 May

## 1pNS5. Application of wavelet analysis to machinery diagnosis.

**Gary R. Wilson
**

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Mark D. Ladd
**

**
Russell D. Priebe
**

**
Kevin W. Baugh
**

**
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*Appl. Res. Labs., Univ. of Texas at Austin, P.O. Box 8029, Austin, TX
78713-8029
*

*
*
Conventional time-frequency spectral analysis, typically conducted with
discrete Fourier transforms (DFTs), represents a signal as the sum of complex
harmonic exponentials, and results in an analysis that has the same time and
frequency resolution at all frequencies represented in the DFT. However, some
processes are better represented as the sum of functions at different time
scales rather than at different frequencies. Wavelet analysis provides such a
representation, and under certain conditions can be interpreted as an analysis
whose time and frequency resolutions change with frequency, as opposed to the
constant time and frequency resolution of the DFT. Two different types of
processes associated with rotating machinery, bearing vibrations, and periodic
mechanical transients, are shown from physical considerations to have time
scale properties that are appropriate for wavelet analysis. Measurements of
bearing vibrations and mechanical transients were made and both Fourier and
wavelet analyses were applied to each of the measurements to demonstrate their
associated time-scale properties and the potential benefits of wavelet analysis
for machinery diagnostics. [Work supported by ONR.]