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局部放电在线监测对保证电力变压器安全运行有重要意义，实现在线监测的关键是从强干扰中监测出微弱的放电信号。针对怎样抑制周期性干扰，文献中报道较多的是LMS自适应滤波方法，但该方法需调整参数多，对脉冲型干扰表现出不稳定性。为此，文中分别论述并比较了LMS算法和基于鲁棒RLS算法的自适应滤波方法的基本原理及实现方法。实验结果表明：鲁棒RLS算法较好地解决了LMS算法存在的问题，且能获得更高的信噪比，基本适用于局部放电在线监测。
Partial discharge on-line monitoring to ensure the safe operation of power transformers is of great significance to achieve online monitoring is the strong interference from the monitoring of a weak discharge signal. For how to restrain periodic interference, LMS adaptive filtering method is reported in the literature, but this method needs to adjust many parameters and shows instability to impulsive interference. Therefore, the paper discusses and compares the basic principles and implementation methods of LMS algorithm and adaptive filtering method based on robust RLS algorithm respectively. The experimental results show that the robust RLS algorithm solves the existing problems of LMS algorithm and achieves higher signal-to-noise ratio, which is suitable for on-line partial discharge monitoring.