The characteristics of the motor with rotor broken bars are introduced and the fault diagnosis method which based on wavelet packet decomposition coefficients to determine whether there has been motor rotor broken bars is proposed, while the energy method using wavelet packet frequency bands to study it. 介绍了电机发生转子断条时的特点,提出了基于小波包分解系数判断电机是否发生转子断条的故障诊断方法,同时采用小波包频带能量法对其进行研究。
With the energy analysis to wavelet packet frequency bands, the feature of relative energy of frequency bands can be extracted accurately, which provides the diagnosis of crank bearing wear fault with quantitative foundation. 利用小波包频带能量分析法实现了对信号各频带相对能量信息特征的准确提取,为曲柄轴承磨损故障的识别提供了定量的依据。
Using wavelet packet frequency band energy technology and RBF neural network to analysis the vibration signal of the disc, estimate the disc positioning accuracy and analysis the change of disc operation reliability from the perspective of disc positioning accuracy. 采用小波包频带能量技术和RBF神经网络对不同工况下的刀盘振动信号进行分析,判断刀盘的定位精度,从定位精度的角度分析不同工况下刀盘运行可靠性的变化。
On the Fault Diagnosis based on the Detecting Technology of Wavelet Packet Frequency(PF) Band Energy 基于小波包频带能量检测技术的故障诊断
The motion characteristics of the breaker electromagnet were studied by analyzing the vibration signals and the current in the closing coil in terms of the motion time, frequency spectrum, and energy distribution of the wavelet packet frequency band. 主要基于振动信号,并结合合闸线圈电流,从振动时间、频谱特性和小波包分解能量分布来分析断路器的电磁铁动特性;