电子科技2025，Vol.38Issue(6)：39-44,6.DOI:10.16180/j.cnki.issn1007-7820.2025.06.006
一种基于支持向量机的宽带声谱故障监测方法
Broadband Acoustic Spectrum Fault Monitoring Technology Based on Support Vector Machine
摘要
Abstract
In view of the problem of condition monitoring of electromechanical equipment under complex back-ground 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 voice-print 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 broad-band 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.关键词
声纹识别/声谱分析/宽带匹配/状态监测/支持向量机/机电设备/故障监测/振动分析Key words
voiceprint recognition/spectrum analysis/broadband matching/condition monitoring/SVM/electro-mechanical equipment/fault monitoring/vibration analysis分类
计算机与自动化引用本文复制引用
竹小锋,白兴宇..一种基于支持向量机的宽带声谱故障监测方法[J].电子科技,2025,38(6):39-44,6.基金项目
国家自然科学基金(LZ22F010004)National Natural Science Foundation of China(LZ22F01004) （LZ22F010004）
