基于声音信号的核主元故障诊断法

Research on KPCA Fault Diagnosis Method Based on Sound Signal

针对振动诊断法的局限性,提出了基于声音信号KPCA的故障诊断方法。介绍了核主元分析法的基本原理及其用于故障检测的基本步骤,给出了声音信号详细预处理过程,提取了由时域、频域和时频域参量共同构成的多域特征向量,利用核主元分析法进行了故障诊断。对轴向柱塞泵进行了试验,结果表明:利用声音信号KPCA的故障诊断法是有效的,能克服基于振动信号故障诊断法的不足。

To resolve the deficiency of vibration fault diagnosis method,it was proposed that kernel principal component analysis( KPCA) fault diagnosis method based on sound signal. The basic theory of KPCA and its basic procedures for fault detection were introduced and sound signal pre-processing was depicted,multi-domain feature vector was extracted from time,time-frequency and frequency domain,faults were diagnosed with KPCA method. The new KPCA fault diagnosis method based on sound signal processing was tested on axial piston pump,the result shows that this method is effective and it can overcome the deficiencies of fault diagnosis method based on vibration signal.