The amplitude modulation bispectrum: A weak modulation features extracting method for bearing fault diagnosis

Abstract

As a key component of the industrial equipment, the failure of rolling bearings could cause equipment to malfunction, resulting in serious losses. However, the bearing fault information is often disturbed by the operation of other parts in the industrial equipment. A key issue is the recognition of weak information in the fault diagnosis of rolling bearings. The amplitude modulation bispectrum proposed in this paper is a rolling bearing fault diagnosis method for weak modulation feature extraction. Aiming at the problem that the bearing fault information is weak and difficult to extract, the method reconfigures the amplitude of the signal in the frequency domain to adjust the proportions of different components in the signal effectively and highlight the fault characteristic information. Based on the use of advanced demodulation tool to deal with the complex modulation components in the signal, an index, named bispectrum signal-to-noise ratio, to evaluate the fault information quantitatively for two-dimensional data is also proposed. The index helps to optimize the bispectrum demodulation results and make the valid information clearer. The effectiveness of this method in rolling bearing fault diagnosis is confirmed using simulation and experimental signals, and comparison with other methods has demonstrated the superiority of this method.