Please wait a minute...
J4  2010, Vol. 44 Issue (7): 1251-1254    DOI: 10.3785/j.issn.1008-973X.2010.07.003
徐贵斌, 周东华
清华大学 自动化系, 北京 100084
Fault prediction for state-dependent fault based on online learning neural network
XU Gui-bin, ZHOU Dong-hua
(Department of Automation, Tsinghua University, Beijing 100084, China
 全文: PDF  HTML



The concept of external and internal stimulated faults was proposed, and the fault prediction problem of nonlinear system with statedependent fault was investigated. The fault model of nonlinear system was formulated as a general nonlinear function with external and internal stimulated faults coupled together, and the structure of the function was unknown. The back propogation (BP) neural network was applied to learn the fault function online in order to approximate the fault model, and an online neural network based statedependent fault prediction algorithm was given. The algorithm can detect the fault online, and iteratively estimate and predict the fault and the system state. The failure time of the system was predicted online by using the predicted value of the system state. The generalization of fault model showed the effect of the system state on the fault, which made the algorithm more applicable. Simulation results demonstrated the effectiveness of the method.

出版日期: 2010-07-01
:  TP 277  
通讯作者: 周东华,男,教授,博导.     E-mail:
作者简介: 徐贵斌(1983—),男,黑龙江齐齐哈尔人,博士生,从事动态系统故障诊断及预测的研究.E-mail:
E-mail Alert


徐贵斌, 周东华. 基于在线学习神经网络的状态依赖型故障预测[J]. J4, 2010, 44(7): 1251-1254.

XU Gui-Bin, ZHOU Dong-Hua. Fault prediction for state-dependent fault based on online learning neural network. J4, 2010, 44(7): 1251-1254.


[1] BARRY R F. Failure prediction for preventive maintenance [C]∥ Proceedings of the Joint Conference on Automatic Test Systems. London: IERE, 1970: 549568.

[2] CHELIDZE D, CUSUMANO J P. A dynamical systems approach to failure prognosis [J]. Journal of Vibration and Acoustics Transactions of the ASME, 2004, 126(1): 28.

[3] WANG X H, RONG M Z, QIU J, et al. Research on mechanical fault prediction algorithm for circuit breaker based on sliding time window and ANN [J]. IEICE Transactions on Electronics, 2008, E91C(8): 12991305.

[4] XU Z, JI Y, ZHOU D. Realtime reliability prediction for a dynamic system based on the hidden degradation process identification [J]. IEEE Transactions on Reliability, 2008, 57(2): 230242.

[5] ORCHARD M E, VACHTSEVANOS G J. A particlefiltering approach for online fault diagnosis and failure prognosis [J]. Transactions of the Institute of Measurement and Control, 2009, 31(3/4): 221246.
[6] ZHANG L B, WANG Z H, ZHAO S X. Shortterm fault prediction of mechanical rotating parts on the basis of fuzzygrey optimizing method [J]. Mechanical Systems and Signal Processing, 2007, 21(2): 856865.
[7] ZHANG Z D, HU S S. A new method for fault prediction of modelunknown nonlinear system [J]. Journal of the Franklin InstituteEngineering and Applied Mathematics, 2008, 345(2): 136153.
[8] XU G, ZHOU D. Fault prediction for dynamic systems with statedependent faults [C]∥ Proceedings of the 4th International Conference on Innovative Computing, Information and Control. Piscataway, NJ, USA: IEEE, 2009: 207210.
[9] XIA R, MENG K, QIAN F, et al. Online wavelet denoising via a moving window [J]. /Acta Automatica Sinica, 2007, 33(9): 897901.
[10] WERBOS P J. Beyond regression: new tools for prediction and analysis in the behavioral sciences [D]. Massachusetts: Harvard University, 1975.
[11] WERBOS P J. Building and understanding adaptive systems: a statistical/numerical approach to factory automation and brain research [J]. IEEE Transactions on Systems, Man and Cybernetics, 1987, 17(1): 720.
[12] WERBOS P J. Backpropagation: past and future [C]∥ IEEE International Conference on Neural Networks. New York: IEEE, 1988: 343353.
[13] 周东华, 叶银忠. 现代故障诊断与容错控制[M]. 北京: 清华大学出版社, 2000: 137139.
[14] XIE X Q, ZHOU D H, JIN Y H. Strong tracking filter based adaptive generic model control [J]. Journal of Process Control, 1999, 9(4): 337350.

[1] 段斌, 梁军, 费正顺, 杨敏, 胡斌. 基于GA-ANN的非线性半参数建模方法[J]. J4, 2011, 45(6): 977-983.
[2] 杜文莉, 王坤, 钱锋. 基于特征空间降维的溶剂脱水分离过程监控[J]. J4, 2010, 44(7): 1255-1259.
[3] 林勇, 周晓军, 杨先勇, 等. 基于双谱识别和人工免疫网络的智能故障检测[J]. J4, 2009, 43(10): 1777-1782.