Dynamic Impedance Analysis of Live Electrocution Based on Least Squares Method

doi:10.11985/2023.03.029

Abstract

Abstract:

In response to the lack of an accurate human impedance model, the inability of residual current protection equipment in low-voltage distribution networks to identify electrocution characteristics, and the inability to use humans as electrocution test objects, a human electrocution dynamic impedance model based on animal electrocution test data and fitted with the least squares method is established. The dynamic impedance model is improved by the electrocution channel composition based on the high similarity of electrical characteristics and anatomy between humans and animals such as pigs and sheep. Compared with the existing human impedance model, the human electrocution dynamic impedance model is more accurate in describing the impedance change within a short time of electrocution, and can highlight the time-varying characteristics of human impedance within a short time of electrocution. Physical simulations show that the human dynamic impedance model is able to characterize the human impedance trend both within a short period of time and over a long period of time. It is a reference value for the development of a new generation of residual current protection devices for the human body and other living organisms.

Key words: Least squares method, electrocution current, dynamic resistance model, biological electrocution characteristics

CLC Number:

TM771

XU Hao, WANG Xinyang, WEI Yunbing, ZHAO Qicheng. Dynamic Impedance Analysis of Live Electrocution Based on Least Squares Method[J]. Journal of Electrical Engineering, 2023, 18(3): 268-276.

Figures/Tables 20

References 21

[1]	李春兰, 叶豪, 王成斌, 等. 基于猪触电试验的人体触电规律研究[J]. 江苏大学学报, 2019, 40(5):553-558,565.
	LI Chunlan, YE Hao, WANG Chengbin, et al. Research on the law of human electrocution based on pig electrocution test[J]. Journal of Jiangsu University, 2019, 40(5):553-558,565.
[2]	刘永梅, 杜松怀, 盛万兴. 基于SVM-神经网络融合反馈的触电电流检测方法[J]. 电网技术, 2020, 44(5):1972-1977.
	LIU Yongmei, DU Songhuai, SHENG Wanxing. A method for electrocution current detection based on SVM-neural network fusion feedback[J]. Power System Technology, 2020, 44(5):1972-1977.
[3]	刘晨, 沈介明. 基于LABVIEW的泄漏电流人体阻抗计算模型[J]. 电子产品可靠性与环境试验, 2021, 39(2):18-21.
	LIU Chen, SHEN Jieming. The leakage current human impedance calculation model based on LABVIEW[J]. Electronic Product Reliability and Environmental Testing, 2021, 39(2):18-21.
[4]	叶豪, 李春兰, 高阁, 等. 基于多因素的动物触电电流特征试验与分析[J]. 江苏大学学报, 2020, 41(1):39-45.
	YE Hao, LI Chunlan, GAO Ge, et al. Multi-factor-based experiments and analysis of animal electrocution current characteristics[J]. Journal of Jiangsu University, 2020, 41(1):39-45.
[5]	王文艇, 钟季康, 马骏, 等. 人体阻抗模型分析[J]. 中国医学物理学杂志, 2005(6):736-738,713.
	WANG Wenting, ZHONG Jikang, MA Jun, et al. Model analysis of human body impedance[J]. Chinese Journal of Medical Physics, 2005(6):736-738,713.
[6]	BORA D J, DASGUPTA R. Estimation of skin impedance models with experimental data and a proposed model for human skin impedance[J]. IET Systems Biology, 2020, 14(5):39-46. doi: 10.1049/syb2.v14.1
[7]	蔡智萍, 郭谋发, 魏正峰. 基于BP神经网络的低压配电网生命体触电识别方法研究[J]. 电网技术, 2022, 46(4):1614-1623.
	CAI Zhiping, GUO Moufa, WEI Zhengfeng. Research on the recognition method of living body shock in low-voltage distribution network based on BP neural network[J]. Power System Technology, 2022, 46(4):1614-1623.
[8]	任龙霞. 活体触电识别研究[D]. 杭州: 浙江大学, 2012.
	REN Longxia. Research on in vivo electrocution identification[D]. Hangzhou: Zhejiang University, 2012.
[9]	杜卓, 吴建华, 张少华, 等. 非线性最小二乘法在离心泵特性曲线拟合的应用[J]. 水电能源科学, 2021, 39(3):152-154.
	DU Zhuo, WU Jianhua, ZHANG Shaohua, et al. Application of nonlinear least squares method to centrifugal pump characteristic curve fitting[J]. Hydropower Energy Science, 2021, 39(3):152-154.
[10]	郭峰, 李天友, 叶荣, 等. 基于滑动去趋势波动分析的触电特征检测方法[J]. 供用电, 2020, 37(4):65-70.
	GUO Feng, LI Tianyou, YE Rong, et al. Electrocution feature detection method based on sliding de-trend fluctuation analysis[J]. Power Supply, 2020, 37(4):65-70.
[11]	高阁, 李春兰, 张亚飞, 等. 基于正交试验触电试验平台参数优化及触电信号分析[J]. 中国农机化学报, 2019, 40(9):181-188. doi: 10.13733/j.jcam.issn.2095-5553.2019.09.31
	GAO Ge, LI Chunlan, ZHANG Yafei, et al. Parameter optimization and electrocution signal analysis of electrocution test platform based on orthogonal test[J]. Chinese Journal of Agricultural Chemistry, 2019, 40(9):181-188.
[12]	滕松林. 浅析一种新型触电漏电保护器[J]. 农村电气化, 1999(7):41.
	TENG Songlin. Analysis of a new type of electric shock leakage protector[J]. Rural Electrification, 1999(7):41.
[13]	中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. GB/T 13870.1—2022 电流对人和家畜的效应第1部分:通用部分[S]. 北京: 中国标准出版社, 2008.
	General Administration of Quality Supervision,Inspection and Quarantine of the People’s Republic of China, National Standardization Administration of the People’s Republic of China. GB/T 13870.1—2022 Effects of current on human beings and livestock—Part 1:General aspects[S]. Beijing: China Standard Publishing House, 2008.
[14]	滕松林, 杨校生. 触电漏电保护器及其应用[M]. 北京: 机械工业出版社,1994.
	TENG Songlin, YANG Xiaosheng. Electrocution leakage protector and its application[M]. Beijing: China Machine Press,1994.
[15]	阮方鸣, Tomasz DLUGOSZ, 高攸纲. 计算人体生物电阻抗的柱体模型算法[J]. 电子学报, 2010, 38(2):469-472.
	RUAN Fangming, DLUGOSZ T, GAO Yougang. Column model algorithm for computing human bioelectrical impedance[J]. Journal of Electronics, 2010, 38(2):469-472.
[16]	熊卫红, 毛兴华, 李景禄, 等. 小电阻接地方式对人身安全的影响及智能电阻接地方式研究[J]. 电力系统保护与控制, 2019, 47(14):166-172.
	XIONG Weihong, MAO Xinghua, LI Jinglu, et al. Impact of small resistance grounding method on personal safety and research on intelligent resistance grounding method[J]. Power System Protection and Control, 2019, 47(14):166-172.
[17]	韩晓慧, 杜松怀, 苏娟, 等. 触电信号暂态特征提取及故障类型识别方法[J]. 电网技术, 2016, 40(11):3591-3596.
	HAN Xiaohui, DU Songhuai, SU Juan, et al. Transient feature extraction of contact signal and fault type identification method[J]. Power System Technology, 2016, 40(11):3591-3596.
[18]	马波. 高压触电防护措施的研究与应用[D]. 北京: 华北电力大学, 2014.
	MA Bo. Research and application of high-voltage electric shock protection measures[D]. Beijing: North China Electric Power University, 2014.
[19]	赵秋生. 从人体电流效应解读人体触电的安全阈值[J]. 安全, 2012, 33(5):10-13.
	ZHAO Qiusheng. Interpreting the safety threshold of human electrocution from human current effect[J]. Safety, 2012, 33(5):10-13.
[20]	朱文艳. 泄漏电流测试仪人体阻抗模拟电路的探讨[J]. 电子产品可靠性与环境试验, 2019, 37(5):77-80.
	ZHU Wenyan. Exploration of human impedance simulation circuit of leakage current tester[J]. Electronic Product Reliability and Environmental Testing, 2019, 37(5):77-80.
[21]	潘永长, 李紫莲, 凌军, 等. 基于谐波特征的活体触电判据研究[J]. 浙江电力, 2021, 40(1):56-60.
	PAN Yongchang, LI Zilian, LING Jun, et al. Research on live electrocution criterion based on harmonic characteristics[J]. Zhejiang Electric Power, 2021, 40(1):56-60.

组织种类		电导率/(Ω·cm)
血液	142.85
肌肉	429.18
骨骼	62 500.00
腱	371.74
脂肪	5 263.15

仿真参数	数值
三相电源线电压/V	380
电源频率/Hz	50
负载功率/W	30 000
线路电阻/(Ω/km)	1.273×10^-2
线路电感/(H/km)	0.933 7×10^-3
线路电容/(F/km)	12.74×10^-9
断路器切换时间/s	0.22~0.8

阻抗模型	阻抗网络
弗莱贝加尔人体阻抗模型
毕格麦亚阻抗模型
电灼伤电流人体阻抗模型
感知与反应电流人体阻抗模型
摆脱电流人体阻抗模型