刘永梅;杜松怀;盛万兴;

• 1:中国农业大学信息与电气工程学院
• 2:中国电力科学研究院有限公司

摘要(Abstract)：

在低压配电网剩余电流中检测出生物体触电电流信号并还原是一个典型的回归预测问题,然而单纯采用典型的回归预测方法如支持向量机(support vector machine,SVM)、神经网络(neural network,NN),效果并不理想。该文提出一种基于SVM-神经网络融合反馈的触电电流检测方法,该方法在标准SVM及神经网络的基础上进行融合判定,有效利用各个模型的优点进行融合分析。针对上述方法,该论文通过对实际动物、植物的触电实验获得相关训练数据和测试数据,实验表明基于SVM与神经网络的融合反馈方法可较大的提升生物体触电电流信号检测的准确性。

关键词(KeyWords)： SVM算法;神经网络算法;触电电流;剩余电流;检测方法;融合算法

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 刘永梅;杜松怀;盛万兴;

Email:

DOI: 10.13335/j.1000-3673.pst.2018.2977

参考文献(References)：

• [1]杜松怀，张筱慧．电流系统接地技术[M]．北京：中国电力出版社，2011:39-58.
• [2] Massimo Mitolo. Shock hazard in the presence of protective residual-current devices[J]. IEEE Transactions on Industry Applications,2010,46(4):1552-558.
• [3]吴慎山，苏本庆，谢鸿凤，等．漏电检测与智能鉴相漏电保护器的研究[J]．河南师范大学学报(自然科学版)，2005,33(1):53-55.Wu Shenshan,Su Benqing,Xie Hongfeng,et al.Study on electric leakage and electric leakage protective instrument[J].Journal of Henan Normal University(Natural Science),2005,33(1):53-55(in Chinese).
• [4]蔡志远，庞佳，陈廷辉．基于剩余电流和漏电阻抗的漏电保护方法的研究[J]．电力系统保护与控制，2011,39(12):61-64.Cai Zhiyuan,Pang Jia,Chen Tinghui.Research on method of leakage current protection based on residual current and leakage impedance[J].Power System Protection and Control,2011,39(12):61-64(in Chinese).
• [5]张冠英．基于A型的剩余电流智能保护技术研究[D]．天津：河北工业大学，2011.
• [6]李春兰，杜松怀，苏娟，等．一种新的基于小波变换和混沌理论的触电信号检测方法[J]．电力系统保护与控制，2011,39(10):47-54.Li Chunlan,Du Songhuai,Su Juan,et al.A novel detecting method of electric shock signal based on wavelet transform and chaotic theory[J].Power System Protection and Control,2011,39(10):47-54(in Chinese).
• [7]李春兰，苏娟，杜松怀，等．基于小波分析和BP神经网络的触电信号检测模型[J]．农业工程学报，2010,26(2):130-134.Li Chunlan,Su Juan,Du Songhuai,et al.Detecting model of electric shock signal based on wavelet analysis and BP neural network[J].Transactions of the Chinese Society of Agricultural Engineering,2010,26(2):130-134(in Chinese).
• [8]熊晓祎，肖先勇，赵恒．基于自适应算法的触电事故电流检测[J]．电力系统保护与控制，2017,45(4):139-144.Xiong Xiaoyi,Xiao Xianyong,Zhao Heng.Adaptive algorithm based electrical shock current detection method[J].Power System Protection and Control,2017,45(4):139-144(in Chinese).
• [9]韩晓慧，杜松怀，苏娟，等．基于参数优化的最小二乘支持向量机触电电流检测方法[J]．农业工程学报，2014,30(23):238-245.Han Xiaohui,Du Songhuai,Su Juan,et al.Determination method of electric shock current based on parameter-optimized least squares support vector machine[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(23):238-245(in Chinese).
• [10]关海鸥，杜松怀，苏娟，等．一种触电信号的自动快速检测模型[J]．电网技术，2013,37(8):2328-2335.Guan Haiou,Du Songhuai,Su Juan,et al.An automatic and quick detection model of electric shock signals[J]. Power System Technology,2013,37(8):2328-2335(in Chinese).
• [11]刘永梅，盛万兴，杜松怀．一种面向剩余电流保护装置的触电阻抗建模方法[J]．河北工业大学学报，2017,46(4):15-23.Liu Yongmei,Sheng Wanxing,Du Songhuai.An electric shock impedance modeling method of living organisms in low-voltage distribution network[J].Journal of Hebei University of Technology,2017,46(4):15-23(in Chinese).
• [12] Suykens J A K,Vandewale J,Least squares support vector machine classifiers[J].Neural Processing Letters,1999,9(3):293-300.
• [13] Van Gestel T,Suykens J A K,Baesens B,et al.Benchmarking least squares support vector machine classifiers[J].Mach Learn,2004,54(1):5-32.
• [14]丁世飞，齐丙娟，谭红艳．支持向量机理论与算法研究综述[J]．电子科技大学学报，2011,40(1):2-10.Ding Shifei,Qi Bingjuan,Tan Hongyan.An overview on theory and algorithm of support vector machines[J].Journal of University of Electronic Science and Technology of China,2011,40(1):2-10(in Chinese).
• [15]杨跃，刘俊勇，黄媛，等．基于特征椭球和支持向量机复合映射的暂态稳定预测模型[J]．电网技术，2017,41(8):2514-2520.Yang Yue,Liu Junyong,Huang Yuan,et al.Transient stability prediction model based on CELL-SVM composite projection[J].Power System Technology,2017,41(8):2514-2520(in Chinese).
• [16]王勇，付志红，张淮清，等．基于前馈神经网络的电网基波高精度检测[J]．电网技术，2011,35(8):124-128.Wang Yong,Fu Zhihong,Zhang Huaiqing.High precision detection of fundamental of power grid based on back propagation neural network[J].Power System Technology,2011,35(8):124-128(in Chinese).
• [17]王元章，李智华，吴春华，等．基于BP神经网络的光伏组件在线故障诊断[J]．电网技术，2013,37(8):2094-2100.Wang Yuanzhang,Li Zhihua,Wu Chunhua,et al.A survey of online fault diagnosis for PV module based on BP neural network[J].Power System Technology,2013,37(8):2094-2100(in Chinese).
• [18]项文强，张华，王姮，等．基于L-M算法的BP网络在变压器故障诊断中的应用[J]．电力系统保护与控制，2011,39(8):100-103.Xiang Wenqiang,Zhang Hua,Wang Heng,et al.Application of BP neural network with L-M algorithm in power transformer fault diagnosis[J].Power System Protection and Control,2011,39(8):100-103(in Chinese).
• [19]刘永梅，杜松怀，盛万兴．基于AdaBoost算法的剩余电流分类方法[J]．电子技术应用，2018,44(12):147-150.Liu Yongmei,Du Songhuai,Sheng Wanxing.A residual current classify algorithm based on adaboost[J].Application of Electronic Technique,2018,44(12):147-150(in Chinese).
• [20]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.Fault transient feature extraction and fault type identification for electrical shock signals[J].Power System Technology,2016,40(11):3591-3596(in Chinese).