Wavelets for the analysis and compression of partial discharge data

X. Ma, C. Zhou, I. Kemp
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引用次数: 6

Abstract

One of the major problems encountered in the on-line condition monitoring of partial discharges for high voltage plant items is the huge volume of memory required to store PD data. This paper proposes wavelet-based and wavelet packet-based compression methods for PD measurement data, which are performed through wavelet decomposition, detail coefficient thresholding and signal reconstruction. All of the compression methods associated with these strategies are treated and the compression results as applied to practical PD data are compared. Using this technique in conjunction with the transitional compression method, it has been demonstrated that data from partial discharge activity can be compressed to approximately 5% of its original volume, which is very promising for practical on-line condition monitoring.
用于局部放电数据分析和压缩的小波
高压电站局部放电在线监测中遇到的主要问题之一是需要大量的内存来存储局部放电数据。本文提出了基于小波和基于小波包的PD测量数据压缩方法,分别通过小波分解、细节系数阈值化和信号重构来实现。对与这些策略相关的所有压缩方法进行了处理,并将压缩结果应用于实际PD数据进行了比较。将该技术与过渡压缩方法结合使用,已经证明部分放电活动的数据可以压缩到原始体积的约5%,这对于实际的在线状态监测非常有希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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