This study introduces a simple and novel partial discharge (PD) detection method for generator condition monitoring applications. The proposed method uses statistical operator ‘Variance’ which is proportional to the power of an electrical signal. It was validated by field measurement conducted at four in service hydro-generators: two having heavily aged windings and the other two having identical new. First, accuracy of detecting PD pulses was verified by comparing with wavelet-based method. The proposed method detected all the PD pulses with a ‘Precision’ higher than 90% and recall of 100%. As the second step phase resolved PD (PRPD) patterns generated using the proposed method were compared with commercial PD monitoring systems. It was found that the overall similarity was above 0.75. Finally, extracted PD pulses were used to calculate the polarity wise dissipated PD energies. The calculated energies were correlated with identified PD sources through series of off-line tests and visual inspections. It was observed that discharges due to loosen windings and corona activity were well correlated with estimated PD energies. All these validation processes indicated that the proposed method effectively and accurately detect PD pulses and can be used as a diagnostic tool for generator applications.

中文翻译：

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一种新颖，简单的发电机局部放电检测方法的现场验证

本研究介绍了一种用于发电机状态监测应用的简单新颖的局部放电（PD）检测方法。所提出的方法使用与电信号的功率成比例的统计算子“方差”。通过对四台使用中的水轮发电机进行的现场测量得到了验证：两台发电机的绕组严重老化，另外两台具有相同的新发电机。首先，通过与基于小波的方法进行比较，验证了PD脉冲检测的准确性。所提出的方法检测到所有的PD脉冲，其“精度”均高于90％，召回率达100％。作为第二步阶段，将使用建议的方法生成的已分解PD（PRPD）模式与商用PD监控系统进行了比较。发现总体相似度高于0.75。最后，提取的PD脉冲用于计算按极性计算的PD能量。通过一系列离线测试和目视检查，将计算出的能量与确定的局部放电源相关联。据观察，由于绕组松动和电晕活动而引起的放电与估计的PD能量有很好的相关性。所有这些验证过程表明，所提出的方法有效，准确地检测了PD脉冲，可以用作发电机应用的诊断工具。