Paper
5 March 2018 Planetary gearbox fault diagnosis based on PSO-VMD and PMMSE
Dawei Yang, Yongdong Zhao, Fuzhou Feng, Pengcheng Jiang
Author Affiliations +
Proceedings Volume 10710, Young Scientists Forum 2017; 107101B (2018) https://doi.org/10.1117/12.2317065
Event: Young Scientists Forum 2017, 2017, Shanghai, China
Abstract
Aiming at the difficulty in planetary gearbox fault diagnosis, a method combining Particle Swarm OptimizationVariational Mode Decomposition (PSO-VMD) and Partial Mean of Multi-scale Entropy (PMMSE) was proposed. First, to reduce the drawback of subjectively selecting the parameters of VMD, PSO is used to optimize the decomposition scale and secondary penalty factor. Then, the signal is processed by VMD into several components and the valid components are selected by mutual information method to reconstruct signal. Multi-scale entropy can analyze the complexity of signal under different scale factors, and PMMSE based on multi-scale entropy can reflect the mean value and variation trend of multi-scale entropy. Finally, the PMMSE of reconstructed signal is applied to describe the state of planetary gearbox, and thereby to diagnose planetary gearbox faults. By analyzing the experimental signal of planetary gearbox, the results indicated the proposed method could primely distinguish different faults of planetary gearbox.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dawei Yang, Yongdong Zhao, Fuzhou Feng, and Pengcheng Jiang "Planetary gearbox fault diagnosis based on PSO-VMD and PMMSE", Proc. SPIE 10710, Young Scientists Forum 2017, 107101B (5 March 2018); https://doi.org/10.1117/12.2317065
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KEYWORDS
Signal processing

Particle swarm optimization

Diagnostics

Sensors

Signal analysis

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