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改善气体绝缘开关设备中局部放电测量的时差误差。

Improving the Error of Time Differences of Arrival on Partial Discharges Measurement in Gas-Insulated Switchgear.

机构信息

Jiangsu Key Laboratory of New Energy Generation and Power Conversion, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

State Grid Zhejiang Electric Power Co. Ltd. Research Institute, Hangzhou 310014, China.

出版信息

Sensors (Basel). 2018 Nov 21;18(11):4078. doi: 10.3390/s18114078.

DOI:10.3390/s18114078
PMID:30469445
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6263400/
Abstract

Partial Discharge (PD) detection based on Ultra-High-Frequency (UHF) measurements in Gas-Insulated Switchgear (GIS) is often used for fault location based on extraction of Time Differences of Arrival (TDoA), and the core technique is to obtain the precise time difference of each UHF signal. Usually, TDoA extraction algorithms can be categorized as cross-correlation function method (CCF), minimum energy method (ME), and threshold value method (TV) are not qualified to analyze the time difference with high accuracy and efficiency, especially the complicated UHF PD signals in the field. In this paper, multiple tests were carried out based on the real GIS UHF signals. Three typical algorithms (CCF, ME, and TV) were used to extract and calculate the TDoA of UHF signals. Afterwards, depending on the disassembly of equipment, the accuracy and effective range of the algorithms are analyzed by means of error and variance. To minimize the error and the variance, an average method with the combination (CA) and portfolio of traditional algorithms is proposed and verified in different situations. The results demonstrate that the improved algorithm could increase the accuracy of time difference extraction, less than 4.0%.

摘要

基于超高频（UHF）测量的局部放电（PD）检测在气体绝缘开关设备（GIS）中常用于根据到达时间差（TDoA）提取进行故障定位，其核心技术是获得每个 UHF 信号的精确时间差。通常，TDoA 提取算法可以分为互相关函数法（CCF）、最小能量法（ME）和阈值法（TV）。但是，这些算法不能高效、准确地分析时间差，尤其是现场复杂的 UHF PD 信号。在本文中，基于真实的 GIS UHF 信号进行了多项测试。使用三种典型算法（CCF、ME 和 TV）提取和计算 UHF 信号的 TDoA。之后，通过设备拆卸，通过误差和方差分析算法的准确性和有效范围。为了最小化误差和方差，提出了一种组合（CA）和传统算法组合的平均方法，并在不同情况下进行了验证。结果表明，改进后的算法可以提高时间差提取的准确性，误差小于 4.0%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/566f2ffa3023/sensors-18-04078-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/ccaf4f31fca4/sensors-18-04078-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/27b12ffe12a2/sensors-18-04078-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/0fb2b885d53f/sensors-18-04078-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/bab705985a8c/sensors-18-04078-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/89f575aeb79d/sensors-18-04078-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/ff8c5f310e81/sensors-18-04078-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/566f2ffa3023/sensors-18-04078-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/2bac59ee702d/sensors-18-04078-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/7fb73fbb40fb/sensors-18-04078-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/06864b2c9525/sensors-18-04078-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/b444402993f2/sensors-18-04078-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/ccaf4f31fca4/sensors-18-04078-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/27b12ffe12a2/sensors-18-04078-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/0fb2b885d53f/sensors-18-04078-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/bab705985a8c/sensors-18-04078-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/89f575aeb79d/sensors-18-04078-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/31e9dc363dcf/sensors-18-04078-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/ff8c5f310e81/sensors-18-04078-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6f0/6263400/566f2ffa3023/sensors-18-04078-g012.jpg

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