基于红外与紫外图像信息融合的绝缘子污秽状态识别

摘要
图/表
参考文献
相关文章 (8)

全文: PDF (826 KB)
输出: BibTeX | EndNote (RIS)

摘要为了实现绝缘子污秽状态的非接触检测,提出了一种基于红外与紫外图像信息决策级融合的污秽等级识别方法。分别计算不同污秽等级绝缘子红外与紫外图像特征,根据Fisher准则进行特征选择,得到可以有效表征污秽状态的特征量,为了提高分类器的运算速度和准确性,利用核主元分析（KPCA）进行特征提取,分别得到红外与紫外特征的三维核主元向量,使用径向基神经网络（RBFNN）分别进行污秽等级识别,利用D-S证据理论对识别结果进行决策级融合,实现绝缘子污秽等级的识别。实验结果表明,该方法的正确率显著优于单独使用红外或紫外特征进行识别,为绝缘子污秽状态的非接触检测提供了新的方法。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	金立军
	张达
	段绍辉
	姚森敬

关键词 ：污秽状态, 决策级融合, Fisher准则, 核主元分析, 径向基神经网络

Abstract：In order to realize the non-contact measurement of insulator pollution severity, a method based on decision level fusion of IR and UV image information is proposed. Features of IR and UV images are calculated separately. Meanwhile, feature selection based on Fisher criterion is carried out to obtain features which have the ability to represent the contamination grades efficiently. In order to improve the calculation speed and precision of classifier, Kernel principal component analysis (KPCA) is adopted to extract three-dimensional Kernel principal features of IR and UV images. Radial basis function neural network(RBFNN) is used to identify the contamination grades using IR and UV features separately. And then, D-S theory is adopted to achieve the decision fusion and realize the high accuracy identification of contamination grades. Results of the experiments indicate that the precision of proposed method is significantly superior to recognition using IR or UV features separately. This paper provides a new method for the prevention of pollution flashover.

Key words： Contamination grades decision fusion Fisher criterion Kernel principal component analysis radial basis function neural network

收稿日期: 2013-09-16 出版日期: 2014-11-05

PACS:

TP391.4

基金资助:国家自然科学基金资助项目（51177109）

作者简介: 金立军男,1964年生,教授,博士生导师,研究方向为电气设备在线检测与故障诊断；张达男,1985年生,博士研究生,研究方向为电气设备故障诊断。

引用本文:

金立军, 张达, 段绍辉, 姚森敬. 基于红外与紫外图像信息融合的绝缘子污秽状态识别[J]. 电工技术学报, 2014, 29(8): 309-318. Jin Lijun, Zhang Da, Duan Shaohui, Yao Senjing. Recognition of Contamination Grades of Insulators Based on IR and UV Image Information Fusion. Transactions of China Electrotechnical Society, 2014, 29(8): 309-318.

链接本文:

http://dgjsxb.ces-transaction.com/CN/Y2014/V29/I8/309

[1] Krystian L Chrzan, Wallace L Vosloo, Jacobus P Holtzhausen. Leakage current on porcelain and silicone insulators under sea or light industrial pollution[J]. IEEE Transactions on Power Delivery, 2011, 26(3): 2051-2252.
[2] Joon Young Park, Jae Kyung Lee, Byung Hak Cho, et al. Development of insulator diagnosis algorithm using least-square approximation[J]. IEEE Transactions on Power Delivery, 2012, 27(1): 3-12.
[3] Yao Chenguo, Wang Jian, Li Chengxiang, et al. The syntactical pattern recognition for the leakage current of transmission-line insulators[J]. IEEE Transactions on Power Delivery, 2011, 26(4): 2244-2250.
[4] 陈伟根, 夏青, 孙才新, 等. 绝缘子放电区段划分及污秽预测的泄漏电流分形维数研究[J]. 中国电机工程学报, 2011, 31(13): 121-127. Chen Weigen, Xia Qing, Sun Caixin, et al. Research on fractal dimension of leakage current for discharge zones dividing and contamination forecasting of insulators[J]. Proceedings of the CSEE, 2011, 31(13): 121-127.
[5] 姚陈果, 李璟延, 米彦, 等. 绝缘子安全区泄漏电流频谱特征提取及污秽状态预测[J]. 中国电机工程学报, 2007, 27(30): 1-8. Yao Chenguo, Li Jingyan, Mi Yan, et al. Abstracting frequency spectrum characteristics of insulators leakage current in safety zone to forecast the contamination condition[J]. Proceedings of the CSEE, 2007, 27(30): 1-8.
[6] 焦尚彬, 刘丁, 郑岗, 等. 基于最小二乘支持向量机的绝缘子等值附盐密度预测[J]. 中国电机工程学报, 2006, 26(2): 149-153. Jiao Shangbin, Liu Ding, Zheng Gang, et al. Forecasting the ESDD of insulator based on least squares support vector machine[J]. Proceedings of the CSEE, 2006, 26(2): 149-153.
[7] 陈伟根, 汪万平, 夏青. 绝缘子污秽放电泄漏电流的多重分形特征研究[J]. 电工技术学报, 2013, 28(1): 50-56. Chen Weigen, Wang Wanping, Xia Qing. Research on Multi-fractal characteristics of leakage current for contamination discharge of insulators[J]. Transactions of China Electrotechnical Society, 2013, 28(1): 50-56.
[8] 毛颖科, 关志成, 王黎明, 等. 基于泄漏电流脉冲主成分分析的外绝缘污秽状态评估方法[J]. 电工技术学报, 2009, 24(8): 39-45. Mao Yingke, Guan Zhicheng, Wang Liming, et al. Evaluation of contamination levels of outdoor insulators based on the principal component analysis of leakage current pulses[J]. Transactions of China Electrotechnical Society, 2009, 24(8): 39-45.
[9] 周兴韬, 王玮, 倪平浩, 等. 高压绝缘子污秽泄漏电流采集装置的设计与实现[J]. 电力系统保护与控制, 2010, 38(6): 100-103. Zhou Xingtao, Wang Wei, Ni Pinghao, et al. Design and implementation of a device for acquiring leakage current on polluted high voltage insulator[J]. Power System Protection and Control, 2010, 38(6): 100-103.
[10] 范莉, 夏非, 苏浩益, 等. 基于云理论的高压绝缘子污秽状态风险评估[J]. 电力系统保护与控制, 2012, 40(15): 57-62. Fan Li, Xia Fei, Su Haoyi, et al. Risk assessment of high voltage insulator contamination condition by cloud theory[J]. Power System Protection and Control, 2012, 40(15): 57-62.
[11] 何洪英, 姚建刚, 蒋正龙, 等. 利用红外图像特征和RBPNN识别不同湿度条件下绝缘子的污秽等级[J]. 中国电机工程学报, 2006, 26(8): 117-123. He Hongying, Yao Jiangang, Jiang Zhenglong, et al. Contamination grades recognition of insulators under different humidity using infrared image features and RBPNN[J]. Proceedings of the CSEE, 2006, 26(8): 117-123.
[12] 李佐胜, 李文利, 姚建刚, 等. 应用绝缘子红外热像处理的现场污秽等级检测方法[J]. 中国电机工程学报, 2010, 30(4): 132-138. Li Zuosheng, Li Wenli, Yao Jiangang, et al. On-site detection of pollution level of insulators based on infrared-thermal-image processing[J]. Proceedings of the CSEE, 2010, 30(4): 132-138.
[13] 李和明, 王胜辉, 律方成, 等. 基于放电紫外成像参量的绝缘子污秽状态评估[J]. 电工技术学报, 2010, 25(12): 22-29. Li Heming, Wang Shenghui, Lü Fangcheng, et al. Contamination condition evaluation insulators based on discharge ultraviolet imaging parameters[J]. Transactions of China Electrotechnical Society, 2010, 25(12): 22-29.
[14] Edson G da Costa, Tarso V Ferreira, Max G G Neri, et al. Characterization of polymeric insulators using thermal and UV imaging under laboratory conditions [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2009, 16(4): 985-992.
[15] Vitelli M, Tucci V, Petrarca C. Temperature distribution along an outdoor insulator subjected to different pollution levels[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2000, 7(3): 416-423.
[16] B Subba Reddy, G R Nagabhushana. Study of temperature distribution along an artificially polluted insulator string[J]. Plasma Science & Technology, 2003, 5(2): 1715-1720.
[17] 熊兰, 刘钰, 姚树友, 等. 污秽绝缘子紫外在线监测系统[J]. 电工技术学报, 2010, 25(7): 186-191. Xiong Lan, Liu Yu, Yao Shuyou, et al. Ultraviolet on-line monitoring system for contamination insulators [J]. Transactions of China Electrotechnical Society, 2010, 25(7): 186-191.
[18] 汪金刚, 林伟, 何为, 等. 基于紫外脉冲法与SMS的绝缘子污秽实时监测系统[J]. 电力系统保护与控制, 2011, 39(3): 95-99. Wang Jingang, Lin Wei, He Wei, et al. Real-time monitoring system for insulator surface based on ultra-violet pulse detection and SMS[J]. Power System Protection and Control, 2011, 39(3): 95-99.
[19] 杨建, 杨静宁, 叶晖. Fisher线性鉴别分析的理论研究及其应用[J]. 自动化学报, 2003, 29(4): 481-493. Yang Jian, Yang Jingning, Ye Hui. Theory of Fisher linear discriminant analysis and its application[J]. Acta Automatica Sinica, 2003, 29(4): 481-493.
[20] 李楠, 张云燕, 李言俊, 等. 基于KPCA冗余检测的故障识别算法[J]. 系统仿真学报, 2011, 23(10): 2079-2088. Li Nan, Zhang Yunyan, Li Yanjun, et al. Fault identifica- tion algorithm by redundancy supervision based on KPCA method[J]. Journal of System Simulation, 2011, 23(10): 2079-2088.
[21] 徐春梅, 张浩, 彭道刚. 基于改进D-S的汽轮机组继承故障诊断研究[J]. 系统仿真学报, 2011, 23(10): 2190-2199. Xu Chunmei, Zhang Hao, Peng Daogang. Fault diagnosis method based on improved D-S evidential theory for turbine generator unit[J]. Journal of System Simulation, 2011, 23(10): 2190-2199.
[22] 李先锋, 朱伟兴, 花小朋, 等. 基于D-S证据理论的决策级多特征融合苹果分级方法[J]. 农业机械学报, 2011, 42(6): 188-192. Li Xianfeng, Zhu Weixing, Hua Xiaopeng, et al. Multi-feature decision fusion method based on D-S evidence theory for apple grading[J]. Transactions of the Chinese Society for Agricultural Machinery, 2011, 42(6): 188-192.