一种基于支持向量机的宽带声谱故障监测方法

doi:10.16180/j.cnki.issn1007-7820.2025.06.006

Abstract

Abstract:

In view of the problem of condition monitoring of electromechanical equipment under complex background noise, a wideband sound spectrum fault monitoring method based on SVM (Supported Vector Machine) is proposed in this study. Different from the traditional narrowband fault monitoring method based on acceleration sensor and vibration analysis, the proposed method uses a broadband acoustic sensor to collect the sound spectrum signal. Power spectral entropy and multiscale entropy computations are employed for background noise suppression and voiceprint extraction. Based on SVM, the pattern recognition capability of SVM is combined with the background noise suppression capability of power spectrum entropy and multi-scale entropy. The proposed method has strong broadband fault information picking ability, strong interference noise suppression ability, high equipment status information utilization rate, accurate voiceprint tracking and matching, and can accurately monitor and identify the operation faults of electromechanical equipment under complex background noise environment, which is verified by simulation and experimental results.

Key words: voiceprint recognition, spectrum analysis, broadband matching, condition monitoring, SVM, electromechanical equipment, fault monitoring, vibration analysis

CLC Number:

TP181

ZHU Xiaofeng, BAI Xingyu. Broadband Acoustic Spectrum Fault Monitoring Technology Based on Support Vector Machine[J].Electronic Science and Technology, 2025, 38(6): 39-44.

Figures/Tables 9

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References 19

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信号状态	标签	多尺度熵均值	功率谱熵值
正常信号S(t)	A	0.523 1	0.891 3
正常信号S(t)	A	0.531 8	0.904 2
正常信号S(t)	A	0.491 2	0.920 2
正常信号S(t)	A	0.501 1	0.884 0
正常信号S(t)	A	0.510 2	0.914 5
故障信号S₁(t)	B	0.822 3	1.210 3
故障信号S₁(t)	B	0.819 8	1.205 4
故障信号S₁(t)	B	0.782 3	1.209 7
故障信号S₁(t)	B	0.793 4	1.183 4
故障信号S₁(t)	B	0.784 2	1.194 2
故障信号S₂(t)	C	1.210 2	1.402 3
故障信号S₂(t)	C	1.182 4	1.523 1
故障信号S₂(t)	C	1.191 4	1.518 2
故障信号S₂(t)	C	1.217 8	1.492 4
故障信号S₂(t)	C	1.198 4	1.490 2

Broadband Acoustic Spectrum Fault Monitoring Technology Based on Support Vector Machine

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