Autonomous Bearing Fault Diagnosis Based on Fault-Induced Envelope Spectrum and Moving Peaks-Over-Threshold Approach

Although the envelope-spectrum-based methods for bearing fault diagnosis have been widespread in the scientific community, their application to autonomous diagnosis is hindered by the specified selection of informative frequency bands and the threshold calculation. This article, therefore, proposes a novel autonomous diagnosis method via fault-induced envelope spectrum (FIES) and moving peaks-over-threshold (MPOT) approach. A fault-induced filter is first designed to reveal all the informative bands of the spectral coherence (SCoh) rather than only a specified band. Then, the FIES is used to extract each fault signature, which weights and integrates along the spectral frequency axis of the SCoh. Subsequently, the MPOT is proposed to calculate a frequency-dependent threshold for the FIES, which not only concentrates the heavy-tailed statistical characteristics of faults but also removes the influence of the nonstationary statistical characteristics for the threshold. Finally, the healthy indicator and suspected fault indicator are compared with warn users of the possible risks, meanwhile, making a decision for autonomous diagnosis. The effectiveness of the proposed method is verified by the experimental data. Results are found superior to two existing envelope-spectrum-based methods, which are more practical in terms of autonomous fault diagnosis and health monitoring.