Differentiating between partial discharge sources using envelope comparison of ultra-high-frequency signals

Differentiating between partial discharge sources using envelope comparison of ultra-high-frequency signals
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DOI:
10.1049/iet-smt.2009.0064
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发表时间:
2010-09-01
影响因子:
1.4
通讯作者:
Judd, M. D.
Judd, M. D.
中科院分区:
工程技术4区
文献类型:
--
作者:
Pinpart, T.;Judd, M. D.

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高压设备中的局部放电(PD)会损坏绝缘。检测它们的一种方法是超高频(UHF)方法。使用相分辨模式或飞行时间测量的后续分析可以识别PD类型或定位缺陷。这项研究提出了一种比较UHF信号包络以区分多个局部放电源的方法。进行了实验研究,以确定一种方法,该方法在最小化信号采样率的相互竞争的目标之间达成妥协,同时保留足够的能力来区分不同位置的局部放电源。包络比较法是有效的,并且有可能并入自动化系统。结果清楚地证明了区分不同位置的PD源的能力,这为确定存在的PD源的数量提供了一种手段。由于每个PD脉冲然后可以与特定的数据子集相关联,所以后续的PD解释可以被应用于单独的PD数据流,而不是混合数据。设计了射频(RF)检测电路,并通过在模型变压器油箱中进行的实验验证了该方法的有效性。该技术应适用于其他需要区分复杂暂态信号的状态监测系统。
Partial discharges (PD) in high-voltage equipment cause damage to insulation. One method for detecting them is the ultra-high-frequency (UHF) method. Subsequent analysis using phase-resolved patterns or time-of-flight measurements can identify PD type or locate the defect. This study presents a method for comparing UHF signal envelopes to differentiate between multiple PD sources. Experimental investigations are conducted to identify an approach that strikes a compromise between competing aims of minimising signal sampling rates while retaining sufficient ability to discriminate between PD sources in different locations. The envelope comparison method is efficient and has potential for incorporation within automated systems. Results clearly demonstrate the ability to distinguish between PD sources in different positions, which offers a means to determine the number of PD sources present. Since each PD pulse can then be associated with a particular subset of data, subsequent PD interpretation could be applied to separate PD date streams, rather than to mixed data. An radio frequency (RF) detector circuit was designed and used to validate the approach by means of experiments carried out in a model transformer tank. The technique should be applicable to other condition monitoring systems that are required to distinguish between complex transient signals.