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| Vibration Characteristic Analysis and Closing Synchronization Research of Low Voltage Circuit Breakers |
| Miao Xiren,Wang Yan |
| Fuzhou University Fuzhou 350108 China |
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Abstract Wavelet decomposition method is used to analysis the low voltage circuit breaker mechanical properties with its vibration signals. According to the electric operating mechanism of low voltage circuit breaker and its closing action sequence relations,driving motor current signal as a time stamp is applied to effectively extract closing vibration signal. A novel low voltage circuit breaker closing synchronous research is proposed with wavelet energy spectrum analysis in this paper. Based on refine decomposition to closing vibration signal and feature extraction from its main frequency band with wavelet packet reconstruction,the feature vector of closing synchronous is constructed. Three phases closing asynchronous fault identification model is established by back propagation neural network with above feature vector. The vibration signals of a DW15#x02014;1600 low-voltage circuit breaker under four specific closing synchronous status simultaneities are recorded from a single acceleration sensor mounted on a cross beam of breaker base. The simulation results show that the combination method of wavelet packet energy spectrum and neural network can effectively analysis the closing synchronism of a low voltage circuit breaker.
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Received: 09 October 2012
Published: 11 December 2013
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[1] 杨飞, 王小华, 荣命哲, 等. 一种新的中压真空断路器三相同期在线监测方法[J]. 中国电机工程学报, 2008, 28(12): 139-144.
[2] 孙来军, 胡晓光, 纪延超. 改进的小波包-特征熵在高压断路器[J]. 中国电机工程学报, 2007, 27(12): 103-108.
[3] 胡晓光, 戴景民, 纪延超, 等. 基于小波奇异性检测的高压断路器故障诊断[J]. 中国电机工程学报, 2001, 21(5): 67-70．
[4] 马强, 荣命哲, 贾申利. 基于振动信号小波包提取和短时能量分析的高压断路器合闸同期性的研究[J]. 中国电机工程学报, 2005, 25(13): 150-154.
short time analysis method[J]. Proceedings of the CSEE, 2005, 25(13): 150-154.
[5] Runde M, Skyberg B, Ohlen M. Vibration analysis for periodic diagnostic testing of circuit breakers[C]. High Voltage Engineering Symposium, London, UK, 1999: 98-101.
[6] Pan Hongxia, Men Jifang. Fault diagnosis of diesel engine based on energy spectrum analysis[C]. Proceedings of the International Conference on Control, 2012: 697-701.
[7] 赵志宏, 杨绍普. 基于小波包变换与样本熵的滚动轴承故障诊断[J]. 振动、测试与诊断, 2012, 32(4): 640-644, 692.
[8] 徐建源, 张彬, 林莘, 等. 能谱熵向量法及粒子群优化的RBF神经网络在高压断路器机械故障诊断中的应用[J].高电压技术, 2012, 38(6): 1299-1306.
[9] Shariatinasab Reza, Akbari Mohsen, Aghaebrahimi M R. A novel wavelet-neural network method for fault location analysis on transmission lines[C]. Proceedin- gs of the Mediterranean Electrotechnical Conference, 2012: 963-966.
[10] 程正兴. 小波分析算法与应用[M]. 西安:西安交通大学出版社, 1998.
[11] 李舜铭, 李香莲. 振动信号的现代分析技术与应用[M]. 北京: 国防工业出版社, 2008. |
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2013, Vol. 28 
