盲信号处理在机电声学监测与诊断中的应用

机械噪声信号和振动信号一样,蕴含了机械设备运行状态的重要信息,当设备状态发生改变时,其声学特性同样会发生改变。但是,待识别的目标信号和其它设备的信号以及噪声信号混杂在一起,一般很难直接从测量的声信号中获得有用的信息。因此,排除或抑制干扰信号或背景噪声,准确地从低信噪比的混合信号中提取出待识别的目标信号,对声学监测与诊断方法十分关键,而盲信号处理技术为机械声学信号的分离提供了一个有力的解决手段。该文对盲信号技术在机械装置声学监测与诊断中的研究现状进行了概述,为盲信号进一步应用于机械中的声学分析打下基础。

Application of Blind Signal Processing in the Electromechanical Acoustic Monitoring and Diagnosis

Acoustical signals,similar to mechanical vibration signals,indicate a lot about the mechanical system,because the acoustical features will change along with the working condition of equipments.But it is too difficult to extract useful information from measured mixtures directly,since the target signal is usually corrupted by other equipments’ signals or noise.Consequently,in acoustic-based diagnosis,it is crucial to remove or restrain interference signals or background noise,and accurately extract the target signal from the mixed signals of low signal-noise ratio.While blind signal processing(BSP) technology becomes a powerful tool in the field of separation of mechanical acoustical signals.This paper gave a general explanation of the use of BSP in detection and diagnosis of faults in rotating machinery,and can be the foundation for BSP to apply to the analysis of machinery noise.