基于CCFHTLS算法的异步电动机转子故障检测

定子电流经低通滤波器处理后产生高斯有色噪声,限制了异步电机转子故障检测算法的辨识精度。针对该问题,提出一种抑制高斯有色噪声的异步电机故障检测技术。首先对采集到的定子电流进行预处理,利用逆同步旋转变换剔除基波,避免了直接检测时基波对故障辨识精度的影响。然后利用互相关函数(CCF)处理技术对高斯有色噪声的抑制作用,提出基于CCFHTLS算法的电机转子故障诊断技术。针对异步电机转子断条和偏心故障的识别进行试验,结果表明CCFHTLS算法可以有效抑制高斯有色噪声,并保留故障有用信息,显著地提高了故障检测的分辨率。

Detection Method of Rotor Fault in Asynchronous Motors Based on CCFHTLS

In asynchronous motors, colored Gaussian noises will be produced in stator current after lowpass filter. For this reason, the precision of rotor fault detection methods was restricted. In order to solve this problem, a method for the rotor fault detection in asynchronous motors which could restrain colored Gaussian noises was proposed. Firstly, inverse rotation transform was used to pretreat the sampling stator current and eliminate the fundamental frequency, with which the estimation error of direct detection without pretreatment could be avoided. Then, considering that crosscorrelation function (CCF) could restrain colored Gaussian noises, crosscorrelation function Hankel total least squares (CCFHTLS) algorithm was proposed to detect motor rotor fault. The experimental result of broken rotor bars and eccentric fault detection indicated that CCFHTLS algorithm remarkably restrained colored Gaussian noises and accurately preserved available information of faults, significantly promoting the detection precision.