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A Wavelet Transform Technique for De-noising Partial Discharge Signals

机译:小波变换技术在局部放电信号降噪中的应用

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Partial discharge (PD) diagnosis is essential to identify the nature of insulation defects causing discharge. The problem of PD signal recognition has been approached in a number of ways. Most of the approaches are based on laboratory experiments or on signals acquired during off-line tests of industrial apparatus. On-line testing is vastly preferable as the equipment can remain in service, and the operators can monitor the insulation condition continuously. Interferences from noise sources have been a persistent problem, which have increased with the advent of solid-state power switching electronics. Use of wavelet transform technique offers many advantages over conventional digital filters and is ideally suited to process nonstationary signals (transients) often encountered in high voltage testing and measurements. In this paper, an empirical waveletbased method is proposed to recover PD pulses mixed with excessive noise/interference. A critical assessment of the proposed method is carried out by processing simulated PD signals along with noise signals using MAT LAB software.
机译:诊断局部放电(PD)对于识别导致放电的绝缘缺陷的性质至关重要。 PD信号识别的问题已经以多种方式解决。大多数方法基于实验室实验或工业设备离线测试期间获得的信号。在线测试是非常可取的,因为设备可以保持运行状态,并且操作员可以连续监控绝缘状况。噪声源的干扰一直是一个长期存在的问题,随着固态功率开关电子器件的出现,噪声问题日益严重。小波变换技术的使用提供了优于常规数字滤波器的许多优点,非常适合处理高压测试和测量中经常遇到的非平稳信号(瞬态)。本文提出了一种基于经验小波的方法来恢复混合了过多噪声/干扰的局部放电脉冲。通过使用MAT LAB软件处理模拟的PD信号以及噪声信号,可以对所提出的方法进行严格的评估。

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