Simulation Research of Cable Insulation Defect Detection Based on Electrical Capacitance Tomography

doi:10.11985/2023.03.006

Abstract

Abstract:

Power cables have excellent insulation performance and are widely used in rail transit systems and power systems, but they may suffer from insulation faults under the long-term action of external insulation degradation factors, which affect the stability of the system power supply. In order to accurately determine the status of cable insulation and ensure the safe and stable operation of the system, a simulation study is conducted on the detection of insulation defects in power cables based on electrical capacitance tomography. A model of power cable with eight-electrode capacitive sensor is constructed. The geometry of the capacitive sensor is optimized in terms of signal output strength, and the sensitivity field distribution is optimized using the median filtering algorithm. By integrating the optimized capacitive sensor and sensitivity field, employing Landweber image reconstruction algorithm, the reconstruction of images representing four typical cable insulation defects: air gap, water tree, wedge-shaped scratch, and composite defects, is facilitated, thus enabling the detection of power cable insulation defects.

Key words: Power cables, insulation defects, electrical capacitance tomography, simulation

CLC Number:

TM561

LIN Yibin, CHEN She, JIN Yuxiao, ZHONG Lipeng, SUN Qiuqin, WANG Feng. Simulation Research of Cable Insulation Defect Detection Based on Electrical Capacitance Tomography[J]. Journal of Electrical Engineering, 2023, 18(3): 54-62.

Figures/Tables 13

References 23

[1]	刘刚, 刘斯亮, 金尚儿, 等. 基于理、化、电特性的110 kV XLPE绝缘电缆剩余寿命的综合评估[J]. 电工技术学报, 2016, 31(12):72-79,107.
	LIU Gang, LIU Siliang, JIN Shanger, et al. Comprehensive evaluation of remaining life of 110 kV XLPE insulated cable based on physical,chemical and electrical properties[J]. Transactions of China Electrotechnical Society, 2016, 31(12):72-79,107.
[2]	刘刚, 吴亮, 金尚儿, 等. 基于电特性的110 kV交联聚乙烯电缆剩余寿命评估[J]. 高电压技术, 2017, 43(8):2718-2723.
	LIU Gang, WU Liang, JIN Shanger, et al. Assessment of 110 kV XLPE cables remaining life based on electrical characteristics[J]. High Voltage Engineering, 2017, 43(8):2718-2723.
[3]	邓旭. 长沙地区配网电缆附件选型与电缆运行分析[J]. 湖南电力, 2004(6):36-37,62.
	DENG Xu. Selection of cable accessories and analysis of cable operation in Changsha distribution network[J]. Hunan Electric Power, 2004(6):36-37,62.
[4]	慕世友, 刘民, 冯玉柱, 等. 高压交联电缆现场交流耐压试验[J]. 高电压技术, 2001, 27(104):42-43.
	MU Shiyou, LIU Min, FENG Yuzhu, et al. On-site AC voltage withstand test of high voltage XLPE power cable[J]. High Voltage Engineering, 2001, 27(104):42-43.
[5]	于海, 刘威, 李清. 110 kV交联聚乙烯绝缘电缆耐压试验[J]. 黑龙江电力, 2020, 42(4):334-338.
	YU Hai, LIU Wei, LI Qing. Voltage withstand test of 110 kV XLPE insulated cable[J]. Heilongjiang Electric Power, 2020, 42(4):334-338.
[6]	杜言. 交联聚乙烯电缆局部放电在线监测及定位研究[D]. 重庆: 重庆大学, 2006.
	DU Yan. Study on partial discharge on-line monitoring and location of XLPE cable[D]. Chongqing: Chongqing University, 2006.
[7]	赵中原, 吕征宇, 段乃欣, 等. 交联聚乙烯电缆局部放电在线监测系统研制[J]. 电力系统自动化, 2004, 28(5):59-62,84.
	ZHAO Zhongyuan, LÜ Zhengyu, DUAN Naixin, et al. Development of on-line monitoring system for partial discharge of crosslinked polyethylene cable[J]. Automomation of Electric Power Systems, 2004, 28(5):59-62,84.
[8]	胡卫. 换流变介质损耗角正切值测量与分析[J]. 电工技术, 2017, 455(9):125-126,131.
	HU Wei. Measurement and analysis of loss angle tangent of rheological medium[J]. Electric Engineering, 2017, 455(9):125-126,131.
[9]	黄光磊, 李喆, 杨丰源, 等. 直流交联聚乙烯电缆泄漏电流试验特性研究[J]. 电工技术学报, 2019, 34(1):192-201.
	HUANG Guanglei, LI Zhe, YANG Fengyuan, et al. Experimental research on leakage current of DC cross linked polyethylene cable[J]. Transactions of China Electrotechnical Society, 2019, 34(1):192-201.
[10]	方针, 陆佳政, 张红先, 等. 高压交联聚乙烯电力电缆水树枝缺陷在线监测系统的研制[J]. 湖南电力, 2007(6):1-3,8.
	FANG Zhen, LU Jiazheng, ZHANG Hongxian, et al. Development of an online monitoring system for water tree defects in high-voltage cross-linked polyethylene power cables[J]. Hunan Electric Power, 2007(6):1-3,8.
[11]	ZHANG W, WANG C, YANG W, et al. Application of electrical capacitance tomography in particulate process measurement:A review[J]. Advanced Powder Technology, 2014, 25(1):174-188. doi: 10.1016/j.apt.2013.12.003
[12]	WANG H, YANG W. Application of electrical capacitance tomography in circulating fluidised beds:A review[J]. Applied Thermal Engineering, 2020, 176:115311. doi: 10.1016/j.applthermaleng.2020.115311
[13]	CHAPLIN G, PUGSLEY T. Application of electrical capacitance tomography to the fluidized bed drying of pharmaceutical granule[J]. Chemical Engineering Science, 2005, 60(24):7022-7033. doi: 10.1016/j.ces.2005.06.029
[14]	HOSSEINI M, KAASINEN A, LINK G, et al. Electrical capacitance tomography to measure moisture distribution of polymer foam in a microwave drying process[J]. IEEE Sensors Journal, 2021, 21(16):18101-18114. doi: 10.1109/JSEN.2021.3085762
[15]	LI C, WANG H, WANG M, et al. Experimental study of XLPE power cable insulation detection based on the electrical capacitance tomography sensor[C]// 2021 IEEE 4th International Electrical and Energy Conference (CIEEC), May 28-30,2021,Wuhan,China. IEEE, 2021:1-4.
[16]	LIU X, FAN X, ZHAO Y, et al. Particles movement behavior and apparent density in gas-solid fluidized bed as determined by an electronic dynamometer and electrical capacitance tomography[J]. Chemical Engineering Journal, 2022, 429:132463. doi: 10.1016/j.cej.2021.132463
[17]	Al HOSANI E, ZHANG M, SOLEIMANI M. A limited region electrical capacitance tomography for detection of deposits in pipelines[J]. IEEE Sensors Journal, 2015, 15(11):6089-6099. doi: 10.1109/JSEN.2015.2453361
[18]	CUI Z, WANG Q, XUE Q, et al. A review on image reconstruction algorithms for electrical capacitance/ resistance tomography[J]. Sensor Review, 2016, 36(4):429-445. doi: 10.1108/SR-01-2016-0027
[19]	YANG W Q, SPINK D M, YORK T A, et al. An image-reconstruction algorithm based on Landweber’s iteration method for electrical-capacitance tomography[J]. Measurement Science and Technology, 1999, 10(11):1065. doi: 10.1088/0957-0233/10/11/315
[20]	牟昌华, 彭黎辉, 姚丹亚, 等. 一种基于电势分布的电容成像敏感分布计算方法[J]. 计算物理, 2006(1):87-92.
	MOU Changhua, PENG Lihui, YAO Danya, et al. A calculation method of sensitivity distribution with electrical capacitance tomography[J]. Chinese Journal of Computational Physics, 2006(1):87-92.
[21]	孙宏琦, 施维颖, 巨永锋. 利用中值滤波进行图像处理[J]. 长安大学学报, 2003(2):104-106.
	SUN Hongqi, SHI Weiying, JU Yongfeng. Image processing with medium value filter[J]. Journal of Chang’an University, 2003(2):104-106.
[22]	宋洋. 图像处理的中值滤波算法优化与实现[D]. 北京: 北京邮电大学, 2011.
	SONG Yang. Optimization and implementation of median filtering algorithm for image processing[D]. Beijing: Beijing University of Posts and Telecommunications, 2011.
[23]	周湶, 王鑫源, 欧阳希, 等. 基于反射系数谱的XLPE电缆水树缺陷定位方法[J]. 电工电能新技术, 2021, 40(7):28-39. doi: 10.12067/ATEEE2103012
	ZHOU Quan, WANG Xinyuan, OUYANG Xi, et al. Method for locating water tree defects in XLPE cables based on reflection coefficient spectrum[J]. New Technology of Electrical Engineering and Energy, 2021, 40(7):28-39.

参数	数值
电缆导体直径/mm	29.9
电缆绝缘层厚度/mm	10.5
电缆绝缘层相对介电常数	2.5
传感器基底相对介电常数	4
传感器电极数	8
传感器基底厚度/mm	0.1
传感器屏蔽层厚度/mm	0.1
传感器电极厚度/mm	0.1