Life Prediction of Relay Based on Wavelet Packet Transform and RBF Neural Network
Li Zhigang,Liu Boying,Li Lingling,Sun Dongwang
Hebei Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin 300130 China
Abstract：The performance parameters sequential values of relay is non-stationary time series,In order to predict the working life of relay accurately, this paper improves the wavelet packet transform theory and using the improved wavelet packet transform theory to decompose relay overtravel time runoff of non-stationary characteristics, so that the smooth item and random item separation, for the smooth item ,using traditional AR model to predict; for random item, the RBF(radial basis function) neural network prediction model which is based on phase space reconstruction is established to predict. Finally, the results of two predict models were reconstructed through the wavelet packet reconstruction method to predict the original non-stationary runoff series. Through an example verified that this method has higher accuracy and it is an feasible method.
李志刚,刘伯颖,李玲玲,孙东旺. 基于小波包变换及RBF神经网络的继电器寿命预测[J]. 电工技术学报, 2015, 30(14): 233-240.
Li Zhigang,Liu Boying,Li Lingling,Sun Dongwang. Life Prediction of Relay Based on Wavelet Packet Transform and RBF Neural Network. Transactions of China Electrotechnical Society, 2015, 30(14): 233-240.
[1] Kristin hollung, Eva Veiseth, Terje Froystein, et al. Variation in the response to manipulation of post- mortem glycolysis in beef muscles by low-voltage electrical stimulation and conditioning temperature[J]. Science Direct, 2007, (77): 372-383. [2] 林近山, 陈前. 基于非平稳时间序列双标度指数特征的齿轮箱故障诊断[J]. 机械工程学报, 2012, 48(13): 108-114. Lin Jinshan, Chen Qian. Fault Diagnosis of gearboxes based on the double-scaling-exponent characteristic of nonstationary time series[J]. Journal of Mechanical Engineering. 2012, 48(13): 108-114. [3] Lin Jinshan, Chen Qian. Fault Diagnosis of Gearboxes Based on the Double-scaling-exponent Characteristic of Nonstationary Time Series[J]. Chinese Journal of Mechanical Engineering, 2012, 48(13): 108-114. [4] 翟国富, 赵新民, 刘茂凯, 等. 采用超程时间建模的航空航天继电器寿命预测方法的研究[J]. 航空学报, 1998, 19(5): 617-620. Zhai Guofu, Zhao Xinmin, Liu Maokai, et al. Research on reliability life forecasting based on model-building of super-path time for aerospace relays[J]. Acta aeronauticaet astronautica sinica, 1998, 19(5): 617- 620. [5] Zhang Hua, Ren Ruoen. Non-stationary time series prediction based on wavelet decomposition and remanet GM(1, 1)-AR[J]. Systems Engineering-Theory and Practice, 2010, 30(6): 1016-1020. [6] 任立, 余琼, 翟国富. 航天继电器可靠性寿命试验分析系统的研究[J]. 机电元件, 2009, 29(2): 3-7. Ren Li, Yu Qiong, Zhai Guofu. Study of reliability life test system for aerospace relay[J]. Electrome- chanical components, 2009, 29(2): 3-7. [7] 李国宾, 关德林, 李廷举. 基于小波包变换和奇异值分解的柴油机振动信号特征提取研究[J]. 振动与提取, 2011, 30(8): 149-152. Li Guobin, Guan Delin, Li Tingju. Feature extraction of diesel engine vibration signal based on wavelet- packet transform and singularity value decomposi- tion[J]. Journal of vibration and shock, 2011, 30(8): 149-152. [8] 唐炬, 谢颜斌, 周倩. 基于最优小波包变换与核主分量分析的局部放电信号特征提取[J]. 电工技术学报, 2010, 25(9): 35-40. Tang Ju, Xie Yanbin, Zhou Qian. et al. Feature extraction for partial discharge signals based on the optimal wavelet packet basis transform and kernel principal component analysis[J]. Transactions of China Electrotechnical Society, 2010, 25(9): 35-40. [9] 房国志, 杨超, 赵洪. 基于FFT和小波包变换的电力系统谐波检测方法[J]. 电力系统保护与控制, 2012, 40(5): 75-79. Fang Guo zhi, Yang Chao, Zhao Hong. Detection of harmonic in power system based on FFT and wavelet packet[J]. Power System Protection and Control, 2012, 40(5): 75-79. [10] 张闯, 刘素贞, 杨庆新, 等. 基于FFT和小波包变换的电磁声发射信号处理[J]. 电工技术学报, 2010, 25(4): 24-28. Zhang Chuang, Liu Suzhen, Yang Qingxin. etal. Signal processing of electromagnetically induced acoustic emission based on FFT and wavelet packet transform [J]. Transactions of China Electrotechnical Society, 2010, 25(4): 24-28. [11] 彭磊, 刘莉, 龙腾. 基于动态径向基函数代理模型的优化策略[J]. 机械工程学报, 2011, 47(7): 164-170. Peng Lei, Liu Li, Long Teng. Optimization strategy using dynamic radial basis function metamodel[J]. Journal of mechanical engineering, 2011, 47(7): 164- 170. [12] Wei Yongqiang, Guo Hong, Xie Zhanming. Neural network adaptive sliding mode control for direct- drive servo system[J]. Transactions of China Elec- trotechnical Society, 2009, 24(3): 74-85. [13] 尹建川, 胡江强, 何庆华. 变结构径向基函数网络及其在混沌序列在线预测中的应用[J]. 模式识别与人工智能, 2010, 23(6): 874-879. Yin Jianchuan, Hu Jiangqing, He Qinghua. Variable structure radial basis function network and its applica- tion to on-line chaotic time series prediction[J]. Pattern recognition and artificial intelligence, 2010, 23(6): 874-879. [14] 杨胡萍, 王承飞, 朱开成, 等. 基于相空间重构和Chebyshev正交基神经网络的短期负荷预测[J]. 电力系统保护与控制, 2012, 40(24): 95-99. Yang Huping, Wang Chengfei, Zhu Kaicheng. et al. Short-term load forecasting based on phase space reconstruction and Chebyshev orthogonal basis neural network[J]. Power System Protection and Control, 2012, 40(24): 95-99. [15] Liu Ronghui, Yang Erbin, Yang Xiu. Analysis of Transient harmonics in power systems based on wavelet packet transform[C]. Advances in Biomedical Engineering——2012 International Conference on Mechanical Engineering and Automation, 2012, (10): 213-218. [16] Rong Mingxing. Wavelet transform and neural networks in fault diagnosis of a motor rotor[J]. International Journal of Plant Engineering and Management, 2012, 17(2): 104-111. [17] Guo Huiyong, Lin Jianrong, Li Zhengliang. Structural damage localization of steel arch bridge based on wavelet packet transform[C]. Proceedings of 2010 International Conference on Broadcast Technology and Multimedia Communication, 2010, (3): 26-29.
2015, Vol. 30 
