Abstract：In order to detect a mechanical type of structural failure of the circuit breaker, the characteristics of the circuit breaker mechanical vibration signal is analyzed in this paper. A combination of medium voltage circuit breaker based on empirical mode decomposition(EMD) amount of energy and support vector machine(SVM) theory vibration signal feature vector extraction and analysis of fault classification method is proposed. First, the vibration signal of the circuit breaker is decomposed by EMD, and then intrinsic mode function(IMF) is obtained. The total energy of each failure intrinsic mode function component obtained the method of discrete sampling points information which contains the main features. Using the amount of energy of IMF component as a feature vector, SVM and kernel function parameters and genetic algorithm optimization,the failure of the test sample signal as input feature vector into trained "BT-SVM" support vector machine classification mechanism for fault classification. The difference and fault type of vibration signals can be identified by this method through the experimental analysis.
孙一航, 武建文, 廉世军, 张路明. 结合经验模态分解能量总量法的断路器振动信号特征向量提取[J]. 电工技术学报, 2014, 29(3): 228-236.
Sun Yihang, Wu Jianwen, Lian Shijun, Zhang Luming. Extraction of Vibration Signal Feature Vector of Circuit Breaker Based on Empirical Mode Decomposition Amount of Energy. Transactions of China Electrotechnical Society, 2014, 29(3): 228-236.
[1] 蔡月明, 李惠宇, 何胜利. 智能开关控制装置关键技术研究[J]. 电力系统保护与控制, 2011, 39(11): 129-132. Cai Yueming, Li Huiyu, He Shengli. Key technology research of intelligent switchgear's control device[J]. Power System Protection and Control, 2011, 39(11): 129-132. [2] 施婕, 艾芊. 智能电网实现的若干关键技术问题研究[J]. 电力系统保护与控制, 2009, 37(19): 1-4. Shi Jie, Ai Qian. Research on several key technical problems in realization of smart grid[J]. Power System Protection and Control, 2009, 37(19): 1-4. [3] 沈力, 黄瑜珑, 钱家骊. 断路器振动信号的相频特性及在监测中的应用[J]. 电工技术学报, 1997, 12(3): 42-45. Shen Li, Huang Yulong, Qian Jiali. Phase-frequency characteristic of vibration signal in circuit breaker and its application in condition monitoring[J]. Transactions of China Electrotechnical Society, 1997, 12(3): 42-45. [4] 武建文, 孙一航, 张路明, 等. 一种具有故障区间隔离的断路器控制器: 中国, 201110104084. X[P]. 2013-09-18. [5] 李兴源, 魏巍, 王渝红, 等. 坚强智能电网发展技术的研究[J]. 电力系统保护与控制, 2009, 37(17): 1-7. Li Xingyuan, Wei Wei, Wang Yuhong, et al. Study on the development and technology of strong smart grid[J]. Power System Protection and Control, 2009, 37(17): 1-7. [6] Huang N E, et a1. The empirical mode decomposition and the Hilbert spectrum for nonlinearand non— stationary time serie analysis[J]. Proc. R. Soc. Lond. A, 1998, 45(4): 903-995. [7] 李天云, 赵妍, 季小慧. HHT 方法在电力系统故障信号分析中的应用[J]. 电工技术学报, 2005, 20(6): 87-91. Li Tianyun, Zhao Yan, Ji Xiaohui. Application of HHT method for analysis of fault signal in electric power system[J]. Transactions of China Electrotechnical Society, 2005, 20(6): 87-91. [8] Loh C H, et a1. Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motioncharacteristics and structural nssdonses[J]. Bulletin of Theseism Gical Society of America, 2001(91): 1339-1357. [9] 程军圣. 基于Hilbert-Huang变换的旋转机械故障诊断方法研究[D]. 长沙: 湖南大学, 2005. [10] Polycarpou A A, Soom A, Poter J W, et al. Event timing and shape analysis of vibration bursts from power circuit breakers[J]. IEEE Trans. on Power Delivery, 1996, 11(2): 848-857. [11] Runde M, Skyberg B, Ohlen M. Vibration analysis for periodic diagnostic testing of circuit breakers[C]. High Voltage Engineering Symposium, Conference Publication, London, 1999: 98-101. [12] 王天金, 冯志鹏, 郝如江, 等. 基于Teager能量算子的滚动轴承故障诊断研究[J]. 振动与冲击, 2012, 31(2): 1-5. Wang Tianjin, Feng Zhipeng, Hao Rujiang, et al. Fault diagnosis of rolling element bearings based on Teager energy operator[J]. Journal of Vibration and Shock, 2012, 31(2): 1-5. [13] 董文智, 张超, 基于EEMD能量熵和支持向量机的轴承故障诊断[J]. 机械设计与研究, 2011, 27(5): 53-57. Dong Wenzhi, Zhang Chao. A bearing fault diagnosis method based on EEMD energy entropy and SVM[J]. Machine Design and Research, 2011, 27(5): 53-57. [14] 陈朋永, 赵书涛, 李建鹏, 等. 基于EMD和SVM的高压断路器机械故障诊断方法研究[J]. 华北电力大学学报, 2012, 39(6): 23-28. Chen Pengyong, Zhao Shutao, Li Jianpeng, et al. Research machinery fault diagnosis of high voltage circuit breaker based on EMD and SVM[J]. Journal of North China Electric Power University, 2012, 39(6): 23-28. [15] 程军圣, 于德杰, 杨宇. 基于内禀模态奇异值分解和支持向量机的故障诊断方法[J]. 自动化学报, 2006, 32(3): 475-480. Cheng Junsheng, Yu Dejie, Yang Yu. Fault diagnosis approach based on intrinsic mode singular value decomposition and support vector machines[J]. 2006, 32(3): 475-480. [16] 于徳介, 程军圣, 杨宇. 机械故障诊断的Hilbert- huang变换方法[M]. 北京: 科学出版社, 2006. [17] 陈忠, 郑时雄. 基于经验模式分解(EMD)的齿轮箱齿轮故障诊断技术研究[J]. 振动工程学报, 2003, 16(2): 229-231. Chen Zhong, Zheng Shixong. Study on fault diagnosis of gears using empirical mode decomposition[J]. Journal of Vibration Engineering, 2003, 16(2): 229-231. [18] 王子汉. 基于支持向量机的故障诊断方法的研究[D]. 太原: 太原理工大学, 2009. [19] 孙来军, 胡晓光, 纪延超. 基于支持向量机的高压断路器机械状态分类[J]. 电工技术学报, 2006, 21(8): 53-57. Sun Laijun, Hu Xiaoguang, Ji Yanchao. Mechanical fault classification of high voltage circuit breakers based on support vector machine[J]. Transactions of China Electrotechnical Society, 2006, 21 (8): 53-57. [20] 陈伟根, 邓帮飞, 杨彬. 基于振动信号经验模态分解及能量熵的高压断路器故障识别[J]. 高压电器, 2009, 45(2): 90-96. Chen Weigen, Deng Bangfei, Yang Bin. Fault recognition for high voltage circuit breaker based on EMD of vibration signal and energy entropy characteristic[J]. High Voltage Apparatus, 2009, 45(2): 90-96. [21] 黄健, 胡晓光, 巩玉楠. 基于经验模态分解的高压断路器机械故障诊断方法[J]. 中国电机工程学报, 2011, 31(12): 108-113. Huang jian, Hu Xiaoguang , Gong Yunan. Machinery fault diagnosis of high voltage cicuit breaker based on empirical mode decomposition[J]. Proceedings of the CSEE, 2011, 31(12): 108-113. [22] 周将坤, 陆森林. 基于EMD平均能量法的滚动轴承故障诊断[J]. 轻工机械, 2010, 28(2): 35-40. Zhou Jiangkun, Lu Senlin. Fault diagnosis of rolling bearing based on EMD average energy method[J]. Light Industry Machinery, 2010, 28(2): 35-40.
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