Method and device for diagnosing gear faults based on combination of wavelet packet and spectral kurtosis

Abstract

The invention discloses a method and a device for diagnosing gear faults based on combination of a wavelet packet and spectral kurtosis. The method comprises the steps of (1) acquiring a gearbox vibration acceleration signal as a signal to be analyzed, (2) performing wavelet packet decomposition on the signal to be analyzed to obtain acceleration signals in different frequency bands, (3) calculating the spectral kurtosis values of the acceleration signals in different frequency bands by use of a spectral kurtosis method, (4) performing Fourier operation on the acceleration signal in the frequency band having the maximum spectral kurtosis value to obtain the optimal frequency band envelope spectrogram, and (5) observing whether a fault characteristic frequency is present in the envelope spectrogram, and if so, determining that the gear of the gearbox has faults, otherwise, determining that the gear of the gearbox has no fault; the device comprises an acceleration sensor, a wavelet decomposition module and a spectral kurtosis demodulation analysis module. The method for diagnosing gear faults based on combination of the wavelet packet and the spectral kurtosis is simple in diagnosis process and high in accuracy by use of the method of combined wavelet packet analysis and spectral kurtosis analysis.

Description

technical field [0001] The invention belongs to the technical field of mechanical engineering, in particular to a gear fault diagnosis method and device based on the combination of wavelet packet and spectral kurtosis. Background technique [0002] Gears are widely used in rotating machinery, and their operating status often directly affects the accuracy, reliability and life of the machine. As one of the most commonly used transmission methods in mechanical equipment, gears transmit torque through continuous motion. Under complex working conditions such as heavy loads, impacts, and variable loads, gears are prone to pitting, gluing, wear, and even broken teeth. Phenomenon, eventually lead to gear failure, thus affecting the normal operation of the entire machine. Since most of the frequent faults of gears exist in the early stage of the gear working cycle in the form of local defects, and most of them are potential faults, early state monitoring and fault diagnosis of gear...

AI Technical Summary

Problems solved by technology

Envelope analysis needs to artificially determine the resonance demodulation frequency band and carry out corresponding bandpass filtering, and then Hilbert transform to demodulate the signal envelope of this frequency band, but the selection of filtering center frequency and bandwidth requires rich prior knowledge and history Otherwise, it is easy to cause a large analysis error; the empirical mode decomposition has a global orthogonality problem, there are different degrees of aliasing between the modes, and the error generated by the boundary processing continues to pass on, causing a large swing in the result

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