对近两年我国及日本在机械监测诊断领域内小波技术的研究与应用进行了回顾，简述了小波技术的理论研究及其在旋转机械、往复机械、齿轮、轴承、建筑结构、疲劳损伤等方面的应用中所取得的可喜进展和特点。指出应根据小波函数的性质有针对性地应用，以取得更好的效果。

This paper proposes a fault diagnosis method for plant machinery in an unsteady operating condition using instantaneous power spectrum (IPS) and genetic programming (GP). IPS is used to extract feature frequencies of each machine state from measured vibration signals for distinguishing faults by relative crossing information. Excellent symptom parameters for detecting faults are automatically generated by the GP. The excellent symptom parameters generated by GP can sensitively reflect the characteristics of signals for precise diagnosis. The method proposed in this paper is verified by applying it to the fault diagnosis of a rolling bearing.

A new time-domain analysis method that uses second generation wavelet transform (SGWT) for weak fault feature extraction is proposed. To extrata incipient fault feature, a biorthogonal wavelet with the characteristics of impact is constructed by using SGWT. Processing detail signal of SGWT with a sliding window devised on the basis of rotating operation cycle, and extracting modulus maxi-mum from each window, fault features in time-domain are highlighted. To make fitrther analysis on the reason of the fault, wavelet package transform based on SGWT is used to process vibration data again. Calculating the energy of each frequency-band, the energy distribution features of die signal are at- tained. Then taking account of the fault features and the energy distribution, the reason of die fault is worked out. An early impact-rob fault caused by axis misalignment and rotor imbalance is successfully detected by using this method in an oil refinery.