Original scientific paper

https://doi.org/10.17559/TV-20210413082734

Diagnosis of Bearing Damage in Mechanical Equipment Combining Fuzzy Logic Variable Phase Layered Algorithm

Yao Chen ; ShangLuo University, Shannxi, ShangLuo, 726000, China

Abstract

The paper aims at the problem that the bearing of mechanical equipment affects the safe, stable and efficient operation of mechanical equipment. In this paper, a fuzzy logic variable phase layered algorithm (flvpla) is proposed. The dimension reduction is realized by calculating the vibration signal. The vibration signal is effectively used to diagnose bearing fault, and the signal value is reduced to conduction fault classification. Finally, the experimental results show that the dimension reduction effect based on flvpla is better than that based on principal component analysis (PCA) algorithm and LTSA. The fault recognition rate of ba-svm is significantly higher than that of genetic algorithm optimized support vector machine (GA-SVM) and particle swarm optimization support vector machine (PSO-SVM). Therefore, the combination of flvpla and ba-svm can obtain higher recognition accuracy.

Keywords

fault diagnosis; fuzzy logic variable phase layered algorithm (flvpla); multiscale permutation entropy; rolling bearing

Hrčak ID:

272469

URI

https://hrcak.srce.hr/272469

Publication date:

15.4.2022.

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