2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

含缺失数据的小波-卡尔曼滤波故障预测方法

杜党波 张伟 胡昌华 周志杰 司小胜 张建勋

杜党波, 张伟, 胡昌华, 周志杰, 司小胜, 张建勋. 含缺失数据的小波-卡尔曼滤波故障预测方法. 自动化学报, 2014, 40(10): 2115-2125. doi: 10.3724/SP.J.1004.2014.02115
引用本文: 杜党波, 张伟, 胡昌华, 周志杰, 司小胜, 张建勋. 含缺失数据的小波-卡尔曼滤波故障预测方法. 自动化学报, 2014, 40(10): 2115-2125. doi: 10.3724/SP.J.1004.2014.02115
DU Dang-Bo, ZHANG Wei, HU Chang-Hua, ZHOU Zhi-Jie, SI Xiao-Sheng, ZHANG Jian-Xun. A Failure Prognosis Method Based on Wavelet-Kalman Filtering with Missing Data. ACTA AUTOMATICA SINICA, 2014, 40(10): 2115-2125. doi: 10.3724/SP.J.1004.2014.02115
Citation: DU Dang-Bo, ZHANG Wei, HU Chang-Hua, ZHOU Zhi-Jie, SI Xiao-Sheng, ZHANG Jian-Xun. A Failure Prognosis Method Based on Wavelet-Kalman Filtering with Missing Data. ACTA AUTOMATICA SINICA, 2014, 40(10): 2115-2125. doi: 10.3724/SP.J.1004.2014.02115

含缺失数据的小波-卡尔曼滤波故障预测方法

doi: 10.3724/SP.J.1004.2014.02115
基金项目: 

国家自然科学基金(61174030,61374126,61370031),国家杰出青年基金(61025014)资助

详细信息
    作者简介:

    杜党波 第二炮兵工程大学博士研究生.主要研究方向为预测与健康管理.E-mail: ddb effort@126.com

A Failure Prognosis Method Based on Wavelet-Kalman Filtering with Missing Data

Funds: 

Supported by National Natural Science Foundation of China (61174030,61374126,61370031), and National Science Fund for Distinguished Young Scholars of China (61025014)

  • 摘要: 研究了复杂系统存在缺失数据时的故障预测问题.首先,针对测试数据的非平稳性,在小波-卡尔曼滤波预测模型的基础上进行了改进,并 利用期望最大化算法对模型参数进行了在线更新,提高其对非平稳时间序列的预测能力;其次,将数据缺失通过一个满足伯努利分布的随机变量描 述,实现了缺失数据情况下小波-卡尔曼滤波状态估计.基于此,提出了缺失数据下的故 障预测算法;最后,通过数值仿真和实例验证,说明了所提算法的有效性和可行性.
  • [1] Hu Chang-Hua, Wang Zhao-Qiang, Zhou Zhi-Jie, Si Xiao-Sheng. An RVM fuzzy model identification method and its application to fault prediction. Acta Automatica Sinica, 2011, 37(4): 503-512(胡昌华, 王兆强, 周志杰, 司小胜. 一种RVM模糊模型辨识方法及在故障预报中的应用. 自动化学报, 2011, 37(4): 503-512)
    [2] [2] Si X S, Wang W, Hu C H, Zhou D H, Pecht M G. Remaining useful life estimation based on a nonlinear diffusion degradation process. IEEE Transactions on Reliability, 2012, 61(1): 50-67
    [3] [3] Si X S, Wang W, Hu C H, Zhou D H. Remaining useful life estimation-a review on the statistical data driven approaches. European Journal of Operational Research, 2011, 213(1): 1-14
    [4] Si Xiao-Sheng, Hu Chang-Hua, Zhou Dong-Hua. Nonlinear degradation process modeling and remaining useful life estimation subject to measurement error. Acta Automatica Sinica, 2013, 39(5): 530-541(司小胜, 胡昌华, 周东华. 带测量误差的非线性退化过程建模与剩余寿命估计. 自动化学报, 2013, 39(5): 530-541)
    [5] Zhou Dong-Hua, Wei Mu-Heng, Si Xiao-Sheng. A survey on anomaly detection, life prediction and maintenance decision for industrial processes. Acta Automatica Sinica, 2013, 39(6): 711-722(周东华, 魏慕恒, 司小胜. 工业过程异常检测、寿命预测与维修决策的研究进展. 自动化学报, 2013, 39(6): 711-722)
    [6] [6] Zhou Z J, Hu C H. An effective hybrid approach based on grey and ARMA for forecasting gyro drift. Chaos, Solitons Fractals, 2008, 35(3): 525-529
    [7] [7] Zheng T X, Girgis A A, Makram E B. A hybrid wavelet-Kalman filter method for load forecasting. Electric Power Systems Research, 2000, 54(1): 11-17
    [8] [8] You K Y, Xie L H. Minimum data rate for mean square stabilization of discrete LTI systems over lossy channels. IEEE Transactions on Automatic Control, 2010, 55(10): 2373-2378
    [9] [9] Xie L, Xie L H. Stability analysis of networked sampled-data linear systems with Markovian packet losses. IEEE Transactions on Automatic Control, 2009, 54(6): 1375-1381
    [10] Sinopoli B, Schenato L, Franceschetti M, Poolla K, Jordan M I, Sastry S S. Kalman filtering with intermittent observations. IEEE Transactions on Automatic Control, 2004, 49(9): 1453-1464
    [11] Nahi N. Optimal recursive estimation with uncertain observation. IEEE Transactions on Information Theory, 1969, 15(4): 457-462
    [12] Li Yue-Yang, Zhong Mai-Ying. On designing robust H_ fault detection filter for linear discrete time-varying systems with multiple packet dropouts. Acta Automatica Sinica, 2010, 36(12): 1788-1796(李岳炀, 钟麦英. 存在多步测量数据丢失的线性离散时变系统鲁棒H_故障检测滤波器设计. 自动化学报, 2010, 36(12): 1788-1796)
    [13] Chen Bo, Yu Li, Zhang Wen-An. Robust Kalman filtering for uncertain discrete time-delay systems with missing measurement. Acta Automatica Sinica, 2010, 37(1): 123-128(陈博, 俞立, 张文安. 具有测量数据丢失的离散不确定时滞系统鲁棒Kalman滤波. 自动化学报, 2010, 37(1): 123-128)
    [14] Ibrahim J G, Chen M H, Lipsitz S R, Herring A H. Missing-data methods for generalized linear models: a comparative review. Journal of the American Statistical Association, 2005, 100(469): 332-346
    [15] Jaffer A, Gupta S. Optimal sequential estimation of discrete processes with Markov interrupted observations. IEEE Transactions on Automatic Control, 1971, 16(5): 471-475
    [16] Liu X H, Goldsmith A. Kalman filtering with partial observation losses. In: Proceedings of the 43Mrd IEEE Conference on Decision and Control. Bahamas, USA: IEEE, 2004. 4180-4186
    [17] Hu J, Wang Z D, Gao H J, Stergioulas L K. Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements. Automatica, 2012, 48(9): 2007-2015
    [18] Shen Qi-Xia, Liu Xin-Sheng. The restricted EM algorithm for regression coefficients of the linear model with missing data. Journal of Nanjing University (Mathematical Biquarterly), 2007, 24(1): 122-131(沈启霞, 刘心声. 含缺失数据线性模型回归系数的约束EM算法. 南京大学学报(数学半年刊), 2007, 24(1): 122-131)
    [19] Zhou Dong-Hua, Xi Yu-Geng, Zhang Zhong-Jun. A suboptimal multiple fading extended Kalman filter. Acta Automatica Sinica, 1991, 17(6): 689-695(周东华, 席裕庚, 张钟俊. 一种带多重次优渐消因子的扩展卡尔曼滤波器. 自动化学报, 1991, 17(6): 689-695)
    [20] Zhou Zhi-Jie, Hu Chang-Hua, Han Xiao-Xia. Study on the methods for modeling and forecasting gyro's drift performance based on non-stationary time series. Electronics Optics Control, 2005, 12(3): 23-26(周志杰, 胡昌华, 韩晓霞. 基于非平稳时间序列的陀螺漂移性能建模与预测方法研究. 电光与控制, 2005, 12(3): 23-26)
    [21] Gibson S, Ninness B. Robust maximum-likelihood estimation of multi-variable dynamic systems. Automatica, 2005, 41(10): 1667-1682
    [22] Gibson S, Wills A, Ninness B. Maximum-likelihood parameter estimation of bilinear systems. IEEE Transactions on Automatic Control, 2005, 50(10): 1581-1596
    [23] Dong H, Wang Z, Gao H. Robust H filtering for a class of nonlinear networked systems with multiple stochastic communication delays and packet dropouts. IEEE Transactions on Signal Processing, 2010, 58(4): 1957-1966
    [24] Zhou Z J, Hu C H, Yang J B, Xu D L, Zhou D H. A model for real-time failure prognosis based on hidden Markov model and belief rule base. European Journal of Operational Research, 2010, 207(1): 269-283
    [25] Khan M E, Dutt D N. An expectation-maximization algorithm based Kalman smoother approach for event-related desynchronization (ERD) estimation from EEG. IEEE Transactions on Biomedical Engineering, 2007, 54(7): 1191-1198
  • 加载中
计量
  • 文章访问数:  1980
  • HTML全文浏览量:  103
  • PDF下载量:  1534
  • 被引次数: 0
出版历程
  • 收稿日期:  2013-08-27
  • 修回日期:  2014-03-28
  • 刊出日期:  2014-10-20

目录

    /

    返回文章
    返回