Articles | Volume 16, issue 2
https://doi.org/10.5194/ms-16-431-2025
https://doi.org/10.5194/ms-16-431-2025
Research article
 | 
09 Sep 2025
Research article |  | 09 Sep 2025

Bearing fault diagnosis method based on an improved particle swarm optimization–variational mode decomposition (PSO–VMD) multidimensional index and its application in a crane amplitude-changing mechanism

Zhao Tian, Zeyang Ke, Hanzhong Liu, Bin Zhao, XiaoChun Zhu, Yudong Tang, and Chuan Zhu

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Short summary
In this paper, kurtosis-based improved particle swarm optimization (IPSO) is proposed to optimize the number of penalty factors and decomposition levels in variational mode decomposition (VMD). A method for fusing time domain metrics with entropy features and extracting their streamline features by principal component analysis (PCA) is also proposed. Experimental data validation shows that the method not only reduces the training time of the classification model but also improves the classification accuracy.
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