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现场监测设备所采集到的过电压/雷电流信号中,蕴含有非常丰富的故障类型信息。但是,现场记录到的实际波形不可避免存在大量白噪声干扰,其在各个频段都占据了部分能量。为了保证和提高监控设备对实测信号分类识别的准确性,需进行预处理以消除过电压/雷电流信号中对分类识别系统无用甚至是有干扰影响的噪声部分。本文将小波阈值去噪算法应用于过电压/雷电流信号领域,应用Matlab软件编写基于该方法的算法程序,并对加噪后的模拟信号进行去噪处理,然后通过评估系数反映各种情况下的去噪效果和还原效果,提出了适合110kV及35kV电压等级的过电压/雷电流信号最优去噪处理方案,并结合某地区35kV、110kV变电站及云南110kV输电线路实测波形证明其去噪效果的有效性。
Over-voltage / lightning current signals collected by on-site monitoring equipment contain very rich fault type information. However, the actual waveform recorded in the field inevitably has a lot of white noise interference, which occupies a part of energy in all frequency bands. In order to ensure and improve the accuracy of the classification of the measured signal by the monitoring equipment, pre-processing is needed to eliminate the noise part of the overvoltage / lightning current signal which is useless or even interfering with the classification and identification system. In this paper, the wavelet threshold denoising algorithm is applied in the field of over-voltage / lightning current signal. The algorithm program based on the method is programmed by Matlab software, and the noise-added analog signal is denoised, and then the coefficient is reflected to reflect the various situations , The optimal de-noising scheme of overvoltage / lightning current signal suitable for 110kV and 35kV voltage levels is proposed, and the de-noising effect is proved with the actual measured waveforms of 35kV and 110kV substations in a certain area and Yunnan 110kV transmission line Effectiveness.