基于改进LMS自适应滤波的局部放电噪声抑制方法

为了解决局部放电测量现场中信号淹没在周期性窄带干扰中的问题,文中提出一种应用于变压器局部放电在线监测系统的改进变步长最小均方(least mean square,LMS)自适应滤波算法,通过构造一个新型滤波函数结合实际情况中AD芯片量程自适应调整步长,解决了传统LMS算法需要阶数和步长匹配、收敛性差、容易发散的缺点.通...

Partial discharge noise suppression method based on improved LMS adaptive filtering

In order to solve the problem that the signal is submerged in periodic narrow-band interference in the partial discharge measurement site, an improved variable step size least mean square (LMS) adaptive filter algo-rithm applied to the transformer partial discharge online monitoring system is proposed in this paper. By constructing a new filter function combined with the actual situation of the AD chip range adaptive ad-justment step size, it solves the traditional The LMS algorithm needs to match the order and step size, and has the disadvantages of poor convergence and easy divergence. The special case where the delay is found to be zero in the test is discussed and analyzed, which provides a high signal-to-noise ratio adaptive filter design. For reference. The change of the initial iteration step length of the new method is compared with the iter-ation process of the traditional fixed-step LMS algorithm, which proves that the new method has the ad-vantages of fast convergence and not easy to diverge. Finally, through the transformer partial line moni-toring device built in the laboratory, the different effects of the traditional LMS algorithm and the algorithm in this paper under the measured data are compared and analyzed, and the signal-to-noise ratio (SNR), mean square error (MSE) and waveform similarity coefficient (NCC) verifies the superiority of the new method.