Application of non-stationary analysis to machinery monitoring

The author discusses how nonstationary signal processes, such as the wavelet transform and the Wigner-Ville distribution, can be applied to machinery monitoring and diagnostics in industry. One major area of application is incipient failure detection in mechanical and electrical devices. It is argued that optimum incipient failure detection requires nonstationary analysis because failure signals: (a) are nonstationary; (b) are not repetitive in the earliest stages; (c) consist of several active frequency components; and (d) often occur over several scales. Some conventional methods used for machinery diagnostics are described, and their shortcomings are noted. These techniques include natural frequency envelope monitoring, cepstral analysis, and kurtosis. The opportunity for applying nonstationary techniques is indicated.<>