Bearing Fault Diagnosis Based on CEMDAN Energy Weighting Method

Rong-qun HU, Yi-ren ZHOU, Lan ZHANG, Zhi-qiang GUO, Chao ZHOU

Abstract


Bearing fault diagnosis is an important way to ensure the safe operation of equipment. However, the impact caused by some faults in the industrial field is often covered by environmental noise, the weak feature extraction method of vibration signal under strong noise interference is particularly important. In order to solve the problem that weak fault features can’t be extracted by single noise reduction or feature enhancement method under strong noise interference, an energy weighting method based on time-frequency spectrum analysis is proposed in this paper, which combines noise elimination and feature enhancement methods to extract weak impact features under strong noise background. Through the test verification of bearing inner ring fault, the method proposed in this paper has certain practical value in practical application.

Keywords


Time-frequency analysis method, Binary conversion, Feature extraction, Fault diagnosis.


DOI
10.12783/dtcse/ica2019/30752

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