Fault Diagnosis Method of Marine Fans Based on MTAD and Fuzzy Entropy

被引：0

作者：

Jiang J. ^{[1
]}

Hu Y. ^{[1
]}

Fang Y. ^{[1
]}

Zhang C. ^{[1
]}

Rui X. ^{[1
]}

Wang M. ^{[1
]}

机构：

[1] Merchant Marine College, Shanghai Maritime University, Shanghai

来源：

Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2022年 / 33卷 / 10期

关键词：

Fault diagnosis; Feature extraction; Feature selection; Fuzzy entropy; Multiscale time-domain averaging decomposition(MTAD); Ship rotating machinery;

D O I：

10.3969/j.issn.1004-132X.2022.10.006

中图分类号：

学科分类号：

摘要：

Ship rotating machinery often operated in a multi-vibration source environment. How to effectively extract features and reduce noise processing of the vibration signals was a hot topic for scholars. The time-domain synchronous averaging method had good effect iveness on the noise suppression of vibration signals. However, the key phase signals required by this method were difficult to obtain, and fault information other than the specific frequency would be lost, and the waveforms of the frequency multiplication signal would be mixed with each other. The above problems limited the applicability of this method. A MTAD method was proposed to overcome the problems of the traditional time-domain averaging method effectively, and combined fuzzy entropy feature selection to perform fault diagnosis on ship wind turbines. The accuracy and calculation speed are better than that of EMD, EEMD and VMD method. The effectiveness of the proposed method is demonstrated through simulation data analysis and fault simulation experiments. © 2022, China Mechanical Engineering Magazine Office. All right reserved.

引用

页码：1178 / 1188

页数：10

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