电机生产线噪声故障自动识别

电机振声信号蕴涵着丰富的电机状态信息,因此提出利用电机振声信号实现电机生产线噪声出厂检测。考虑工业现场环境的影响,系统首先采用小波分析对振声信号进行消噪,提取有用信号;再利用小波技术多分辨率的特点,从能量分布角度出发,结合概率论参数区间估计法获得各频段能量区间,对故障电机进行自动识别。系统基于LabVIEW软件平台,实现电机振声信号的实时采集、分析和后处理。现场应用表明,该系统效果良好。

Automatic Identification of Vibrating Sound Fault in Motors Applied to Production Line Reality

The vibrating sound signal, which contains abundant state information of the motor, was used to perform on-line inspection of finished motors. Due to noisy conditions in industrial environments, a preprocessor based on wavelet analysis to suppress undesired noise was described. Moreover, with multi-resolution characteristics of wavelet technique, the method of energy spectrum and inter-zone estimate was used to identify defect motor automatically. This system based on LabVIEW programming language can detect, analyze and process vibrating sound signal. And the system has been supplied successfully.