期刊论文

A New Method of Bearing Fault Diagnosis Based on the Combination of Time-frequency Feature Reduction and Multi-level Clustering

中文

噪声与振动控制

1006-1355

2023

43

6

123-128

10.3969/j.issn.1006-1355.2023.06.019

湖南省自然科学基金资助项目(2019JJ60076)。

本校为第一机构

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Judging whether the rolling bearing has fault according to the noisy signal,and determining the fault location and defect degree are the key problem of machine condition monitoring.Aiming at this problem,a rolling bearing fault identification method based on the combina...MORE Judging whether the rolling bearing has fault according to the noisy signal,and determining the fault location and defect degree are the key problem of machine condition monitoring.Aiming at this problem,a rolling bearing fault identification method based on the combination of wavelet frequency band subdivision,principal...