摘要
电机是一种复杂的旋转机械,故障种类多而且难以辨别。为了对电机的常见故障进行正确、快速地检测,在分析电机故障特征的基础上,对采集来的电机振动信号的时域和频域进行了小波包分解;利用分解的小波系数,在各个频段上进行小波系数重构,诊断故障发生的类型。仿真试验结果表明:小波包分析是对电机故障进行检测的有效方法,同时也给出了一种思路,为电机故障实时检测提供了理论依据。
It is difficult to identify various faults of electric motors. To make the common electrical fault detection correct and quick, on basis of analyzing the motor fault characters, the vibration signal is decomposed by wavelet packet which indicates signal character both in time domain and frequency domain. With the use of the wavelet coeffi- cient, in each frequency branch reconstructed coefficient is calculated so as to diagnose the fault type. The simulation results show that the proposed method has a better performance in rapidity and validity. It also provides a new way and theory promotion on further electric motors fault detection research.
出处
《电机与控制应用》
北大核心
2008年第7期53-56,共4页
Electric machines & control application
关键词
故障检测
振动信号
小波包分析
重构系数
malfunction detection
vibrant signal
wavelet packet analysis
reconstructed coefficient
