Cluster Analysis of Partial Discharge Based on Image Edge Detection

被引：1
|
作者：
Lin Jianhua [1 ]
Gui Junfeng [2 ]
Gao Shengyou [3 ]
Chen Xiyang [1 ]
Xia Yunfeng [1 ]
Huang Jianhua [1 ]
机构：
[1] Dongguan Power Breuse Guangdong Grid, Dongguan 523008, Peoples R China
[2] Beijing Jiaotong Univ, Sch Elect Engn, Beijing 100044, Peoples R China
[3] Tsinghua Univ, Dept Elect Engn, State Key Lab Control & Simulat Power Syst & Gene, Beijing 100084, Peoples R China
来源：
PROCEEDINGS OF 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION (ICICTA 2015) | 2015年
关键词：
partial discharge; image processing; recognition; cluster analysis; edge detection; MATHEMATICAL MORPHOLOGY FILTERS; RECOGNITION;
D O I：
10.1109/ICICTA.2015.81
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Partial discharge (PD) measurement is one of the most important diagnostic methods to detect local faults in high voltage cable. This requires effective means of PD detection and recognition. The paper describes a method of PD recognition by image processing. Three kinds of cable-joint fault models are made for PD test with high voltage. Large amounts of test data are got for drawing scatter map or spectrum that can reflect the characteristic of PD. There is a certain extent difference in various types of PD spectrum. Spectrums of F-q and TF are converted to grayscale. The edge detection by mathematical morphology is used for cluster analysis. Different types of PD signal and interference signal are separated. Higher recognition accuracy rate is obtained when judging the separated signal.
引用
收藏
页码：290 / 294
页数：5
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