Enhanced adaptive high-frequency resonance technology for bearing fault detection

Abstract

The traditional high-frequency resonance technology has two disadvantages: (1) The resonance frequency (RF) is obtained by using Fourier spectrum (FS) and the bandwidth is obtained based on experience, and the effect is often poor due to severe noise interference; (2) the separation of compound faults is not considered. After systematic research, a feasible fault detection methodology named enhanced adaptive high-frequency resonance technology is summarized and introduced, which is on the basis of power spectrum (PS) analysis, abbreviated as enhanced adaptive high-frequency resonance technique based on power spectrum (PS-EAHFRT), to realize the single fault detection and compound fault separation of bearing. Firstly, the theoretical values of various bearing fault modes are calculated to establish a database. Then, a series of spectral peaks are obtained by performing PS analysis, and each prominent spectral peak is considered as an alternative RF, that is, an alternative central frequency. Then, the bandwidth calculation formula of the bandpass filter is given, and the optimal bandwidth parameter is calculated by using the signal envelope kurtosis as a sparse measure. Finally, the original signal is denoised by the optimized band-pass filter, and then the filtered signal is demodulated by envelope PS analysis, and compared with the theoretical value in the library, and then the fault category is obtained. Simulated and real-world bearing cases are used to demonstrate the effectiveness and advantages of PS-EAHFRT. It is demonstrated that the PS-EAHFRT can effectively realize the bearing single fault detection and the compound fault separation. Moreover, the lower bound of the frequency interval in which this method can achieve bearing composite fault separation is explored.

Keywords

Enhanced adaptive high-frequency resonance technology resonance frequency power spectrum analysis optimal bandpass filter rolling bearing compound fault separation

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