Planetary gear box early fault diagnosis method based on APEWT and IMOMEDA

Abstract

The invention provides a planetary gear box early fault diagnosis method based on APEWT and IMOMEDA. The method comprises the following steps: firstly, calculating a discrete scale space spectrum of aplanetary gear box fault vibration signal, and adaptively determining a frequency band division boundary on the scale space spectrum; then, APEWT is adopted to automatically decompose the fault signal into a series of modal components, and sensitive components are selected from the modal components; secondly, carrying out deconvolution processing on the sensitive component by adopting IMOMEDA, and carrying out waveform extension on the deconvolved component to obtain a lifting signal; and finally, extracting a fault characteristic frequency from the envelope spectrum of the lifting signal, and comparing the fault characteristic frequency with a theoretical fault characteristic frequency value of the gearbox so as to identify the type of a fault. According to the method, the early fault feature information of the planetary gear box can be extracted clearly and accurately, the problem that parameters in EWT cannot be determined adaptively is solved, the problem that MOMEDA has a seriousedge effect is also solved, and the fault diagnosis accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis and vibration signal analysis of rotating machinery, and relates to a method for early fault diagnosis of rotating machinery, in particular to a multi-point optimization based on Adaptive Parameterless Empirical Wavelet Transform (APEWT) and lifting The improved Multipoint Optimal Minimum Entropy Deconvolution Adjusted (IMOMEDA) planetary gearbox early fault diagnosis method can be used for fault diagnosis of gears and rolling bearings in planetary gearboxes. Background technique [0002] Planetary gearboxes have the advantages of small size, large transmission ratio, strong bearing capacity, stable operation and high work efficiency, and have been widely used in large and complex mechanical equipment such as helicopters, wind power, heavy trucks and ships. However, the working environment of planetary gearboxes is usually relatively harsh. Long-term operation under high-load, strong impac...

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Problems solved by technology

[0005] In view of the above problems, the object of the present invention is to provide a planetary gearbox early fault diagnosis method based on adaptive non-parametric empirical wavelet transform and lifting multi-point optimization minimum entropy deconvolution correction (APEWT-IMOMEDA), aiming at strong background noise The early fault features of the planetary gearbox are weak and difficult to extract, the signal spectrum cannot be adaptively divided in the traditional EWT algorithm, and there are serious edge effects in the MOMEDA algorithm.

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