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A Novel Approach for Acoustic Signal Processing of a Drum Shearer Based on Improved Variational Mode Decomposition and Cluster Analysis

School of Mechanical Engineering, Anhui University of Science & Technology, No168 Taifeng Road, Huainan 232001, China
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Sensors 2020, 20(10), 2949; https://doi.org/10.3390/s20102949
Received: 8 April 2020 / Revised: 2 May 2020 / Accepted: 11 May 2020 / Published: 22 May 2020
(This article belongs to the Special Issue Sensors for Fault Diagnosis and Prognostics)
During operation, the acoustic signal of the drum shearer contains a wealth of information. The monitoring or diagnosis system based on acoustic signal has obvious advantages. However, the signal is challenging to extract and recognize. Therefore, this paper proposes an approach for acoustic signal processing of a shearer based on the parameter optimized variational mode decomposition (VMD) method and a clustering algorithm. First, the particle swarm optimization (PSO) algorithm searched for the best parameter combination of the VMD. According to the results, the approach determined the number of modes and penalty parameters for VMD. Then the improved VMD algorithm decomposed the acoustic signal. It selected the ideal component through the minimum envelope entropy. The PSO was designed to optimize the clustering analysis, and the minimum envelope entropy of the acoustic signal was regarded as the feature for classification. We then use a shearer simulation platform to collect the acoustic signal and use the approach proposed in this paper to process and classify the signal. The experimental results show that the approach proposed can effectively extract the features of the acoustic signal of the shearer. The recognition accuracy of the acoustic signal was high, which has practical application value. View Full-Text
Keywords: drum shearer; acoustic signal; variational mode decomposition; parameter optimization; particle swarm optimization; cluster analysis drum shearer; acoustic signal; variational mode decomposition; parameter optimization; particle swarm optimization; cluster analysis
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Li, C.; Peng, T.; Zhu, Y. A Novel Approach for Acoustic Signal Processing of a Drum Shearer Based on Improved Variational Mode Decomposition and Cluster Analysis. Sensors 2020, 20, 2949.

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