Abstract：The basic concepts and highlights of self-organization map (SOM) neural network which is suitable for small samples are given. The relationship between mechanical characteristics of vacuum circuit breaker and the corresponding mechanical failure was analyzed. On this basis, a method of mechanical fault diagnosis of vacuum circuit breaker that mechanical characteristics parameters were taken as training and identification samples of SOM neural network is proposed. The whole process of applying this method to conduct the mechanical fault classification of circuit breakers is emphasized: the fault differentiation is carried out by extracting the mechanical characteristics of circuit breaker under the normal and fault states as inputs of SOM network. The experimental results show that the fault diagnosis scheme achieves high accuracy of mechanical fault classification for vacuum circuit breakers.
刘艳,陈丽安. 基于SOM的真空断路器机械故障诊断[J]. 电工技术学报, 2017, 32(5): 49-54.
Liu Yan,Chen Li’an. Mechanical Fault Diagnosis of Vacuum Circuit Breaker Based on SOM. Transactions of China Electrotechnical Society, 2017, 32(5): 49-54.
[1] 王季梅.真空开关技术与应用[M].北京:机械工业出版社,2007:1-3. [2] Heising C R,Janssen A L J,Lanz W,et al.Summary of CIGRE 13.06 working group world wide reliablity data and maintenance cost data on high voltage circuit breakers above 63 kV[C]//Conference Record of IEEE Industry Applications Society Annual Meeting,1994:2226-2234. [3] 黄建,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 circuit breaker based on empirical mode decomposition[J].Proceedings of the CSEE,2011,31(12):108-113. [4] 常广,王毅,王玮.采用振动信号零相位滤波时频熵的高压断路器机械故障诊断[J].中国电机工程学报,2013,33(3):155-162. Chang Guang,Wang Yi,Wang Wei.Mechanical fault diagnosis of high voltage circuit breakers utilizing zero-phase filter time-frequency entropy of vibration signal[J].Proceedings of the CSEE,2013,33(3):155-162. [5] 孙一航,武建文,廉世军,等.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):228-235. Sun Yihang,Wu Jianwen,Lian Shijun,et al.Extraction of vibration signal feature vector of circuit breaker based on empirical mode decomposition amount of energy[J].Transactions of China Electrotechnical Society,2014,29(3):228-235. [6] 梅飞,梅军,郑建勇,等.基于KPCA-SVM的断路器故障稳健诊断方法[J].电工技术学报,2014,29(1):50-58. Mei Fei,Mei Jun,Zheng Jianyong,et al.Fault robust diagnosis method of circuit breaker based on KPCA-SVM [J].Transactions of China Electrotechnical Society,2014,29(1):50-58. [7] 齐郑,张惠汐,饶志,等.基于极限学习机的多信息融合区段定位方法[J].电力系统保护与控制,2014,42(19):74-80. Qi Zheng,Zhang Huixi,Rao Zhi,et al.Multi-information fusion fault location based on extreme learning machine[J].Power System Protection and Control,2014,42(19):74-80. [8] 程声烽,程小华,杨露.基于改进粒子群算法的小波神经网络在变压器故障诊断中的应用[J].电力系统保护与控制,2014,42(19):37-42. Cheng Shengfeng,Cheng Xiaohua,Yang Lu.Application of wavelet neural network with improved particle swarm optimization algorithm in power transformer fault diagnosis[J].Power System Protection and Control,2014,42(19):37-42. [9] 杨凌霄,朱亚丽.基于概率神经网络的高压断路器故障诊断[J].电力系统保护与控制,2015,43(10):62-67. Yang Lingxiao,Zhu Yali.Fault diagnosis of high voltage circuit breakers based on probabilistic neural network[J].Power System Protection and Control,2015,43(10):62-67. [10]程序,关永刚,张文鹏,等.基于因子分析和支持向量机算法的高压断路器机械故障诊断方法[J].电工技术学报,2014,29(7):209-215. Cheng Xu,Guan Yonggang,Zhang Wenpeng,et al.Diagnosis method on the mechanical failure of high voltage circuit breakers based on factor analysis and SVM[J].Transactions of China Electrotechnical Society,2014,29(7):209-215. [11]史丽萍,汤家升,王攀攀,等.采用最优小波树和改进BP神经网络的感应电动机定子故障诊断[J].电工技术学报,2015,30(24):38-46. Shi Liping,Tang Jiasheng,Wang Panpan,et al.Stator fault diagnosis of induction motors using the optimal wavelet tree and improved BP neural network[J].Transactions of China Electrotechnical Society,2015,30(24):38-46. [12]李赢,舒乃秋.基于模糊聚类和完全二叉树支持向量机的变压器故障诊断[J].电工技术学报,2016,31(4):64-71. Li Ying,Shu Naiqiu.Transformer fault diagnosis based on fuzzy clustering and complete binary tree support vector machine[J].Transactions of China Electrotechnical Society,2016,31(4):64-71. [13]于生宝,何建龙,王睿家,等.基于小波包分析和概率神经网络的电磁法三电平变换器故障诊断方法[J].电工技术学报,2016,31(17):102-112. Yu Shengbao,He Jianlong,Wang Ruijia,et al.Fault diagnosis of electromagnetic three-level inverter based on wavelet packet analysis and probabilistic neural networks[J].Transactions of China Electrotechnical Society,2016,31(17):102-112. [14]张静.基于SOM的变压器故障诊断研究[J].电力学报,2014,29(4):318-321. Zhang Jing.Transformer fault diagnosis based on SOM[J].Journal of Electric Power,2014,29(4):318-321. [15]徐国政,张节容,钱家骊.高压电器原理和应用[M].北京:清华大学出版社,2000. [16]舒少龙.基于力信号处理的断路器机械特性研究[D].杭州:浙江大学,2014. [17]邹云峰,吴为麟,李智勇.基于自组织神经网络的低压故障电弧聚类分析[J].仪器仪表学报,2010,31(3):573-576. Zou Yunfeng,Wu Weilin,Li Zhiyong.Cluster analysis of arc fault in low-voltage based on SOM neural network[J].Chinese Journal of Scientific Instrument,2010,31(3):573-576. [18]史峰,王小川.Matlab神经网络30个案例分析[M].北京:北京航空航天大学出版社,2010. [19]史晓霞,陈一民,李军治.神经网络在应用科学和工程中的应用:从基本原理到复杂模式识别[M].北京:机械工业出版社,2010.
2017, Vol. 32 
