Statistical pattern analysis of partial discharge measurements for quality assessment of insulation systems in high-voltage electrical machinery
Statistical pattern analysis of partial discharge measurements for quality assessment of insulation systems in high-voltage electrical machinery
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DOI：
10.1109/tia.2004.836174
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发表时间：
2004-11
影响因子：
4.4
通讯作者：
B. Yazici
中科院分区：
文献类型：
--
作者：
B. Yazici
本文提出了一种新的局部放电相位分辨测量统计分析方法，用于高压机械电气绝缘质量评估。该方法是基于监督分类方法，利用直方图相似性分析。选择直方图相似性分析的动机有两个方面。首先，相位分辨PD测量本身实际上是二维直方图。因此，基于直方图匹配的方法适合数据的性质。其次，直方图相似性分析结合了典型的统计参数，用于PD分析，在统计上强大和严格的方式。在我们的研究中，我们利用各种直方图类型和相似性分析，包括相关性，卡方和Kolmogorov-Smirnov检验。此外，我们提出了一个后处理方法来量化的准确性，使用户能够做出软决策的分类结果。我们的实验室样品的实验研究表明，该方法在绝缘缺陷的检测和分类显示出强大的潜力。从我们的研究结果表明，所提出的方法提供了一个强大的，一般的，数学上简单的方法来分析相位分辨PD测量。
In this paper, we present a new statistical analysis method of phase-resolved partial discharge (PD) measurements for the quality assessment of electrical insulation in high-voltage machinery. The method is based on a supervised classification approach which utilizes histogram similarity analysis. The motivation for choosing histogram similarity analysis is twofold. First, the phase-resolved PD measurement itself is, in fact, a two-dimensional histogram. Therefore, a histogram-matching-based approach suits the very nature of the data. Second, histogram similarity analysis combines the typical statistical parameters, used in PD analysis, in a statistically powerful and rigorous way. In our study, we utilize various histogram types and similarity analysis, including correlation, chi-square, and Kolmogorov-Smirnov tests. Further, we propose a postprocessing method to quantify the accuracy of classification results which enables the user to make soft decisions. Our experimental study on laboratory samples demonstrates that the method shows strong potential in detection and classification of insulation defects. The results from our study suggest that the proposed method provides a powerful, general, and mathematically simple approach to the analysis of phase-resolved PD measurements.