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

基于多模型简化CDKF的故障诊断方法

邱岳恒 章卫国 赵鹏轩 刘小雄

邱岳恒, 章卫国, 赵鹏轩, 等 . 基于多模型简化CDKF的故障诊断方法[J]. 北京航空航天大学学报, 2013, 39(7): 968-972.
引用本文: 邱岳恒, 章卫国, 赵鹏轩, 等 . 基于多模型简化CDKF的故障诊断方法[J]. 北京航空航天大学学报, 2013, 39(7): 968-972.
Qiu Yueheng, Zhang Weiguo, Zhao Pengxuan, et al. Fault diagnosis approach based on multiple model estimator with simplified CDKF[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(7): 968-972. (in Chinese)
Citation: Qiu Yueheng, Zhang Weiguo, Zhao Pengxuan, et al. Fault diagnosis approach based on multiple model estimator with simplified CDKF[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(7): 968-972. (in Chinese)

基于多模型简化CDKF的故障诊断方法

基金项目: 航空科学基金资助项目(20100753009)
详细信息
  • 中图分类号: TP 273

Fault diagnosis approach based on multiple model estimator with simplified CDKF

  • 摘要: 针对使用传统卡尔曼滤波器对非线性系统进行故障诊断,估计精度低的问题,提出了一种新的故障诊断方法.该方法结合多模型自适应估计和简化中央差分卡尔曼滤波器的优点,能在线快速地检测出故障,利用中央差分代替了雅可比矩阵的求解,使系统状态估计准确收敛到真实值附近,而且避免了反复求解量测预测方差等一系列繁杂过程.在执行机构不同故障的情况下,通过与其他算法进行诊断对比,结果表明提出的算法在精度上和运行速度上具有明显的优势.

     

  • [1] Liu Z J,Li Q,Liu X H,et al.An expected-mode augmentation based approach for multiple-fault detection and diagnosis in flight control systems[J].Proceedings of the Institution of Mechanical Engineers,Part G,Journal of Aerospace Engineering,2012,226(10):1202-1213
    [2] Ducard G,Geering H P.A reconfigurable flight control system based on the EMMAE method //Proceedings of the 2006 American Control Conference.Piscatway,NJ:IEEE,2006:14-16
    [3] Rupp D,Ducard G,Shafai E,et al.Extended multiple model adaptive estimation for the detection of sensor and actuator faults //44th IEEE Conference on Decision and Control.Piscataway,NJ:IEEE Computer Society,2005:3079-3084
    [4] Qiu Yueheng,Zhang Weiguo.EMMAE failure detection system and failure evaluation over flight performance[J].International Journal of Intelligent Computing and Cybernetics,2012,3(5):401-420
    [5] 杨晓华,邵宗战,侯宝娥,等.基于采样的非线性滤波方法[J].指挥控制与仿真,2009,31(5):1-5 Yang Xiaohua,Shao Zongzhan,Hou Baoe,et al.Nonlinear filtering methods based on sampling[J].Command Control & Simulation,2009,31(5):1-5(in Chinese)
    [6] van der Merwe R.Sigma-point Kalman filters for probabilistic inference in dynamic state-space models .Eugune,USA:Oregon Health and Science University,2004
    [7] Kim C,Sakthivel R,Chung W K.Unscented fast SLAM:a robust and efficient solution to the SLAM problem[J].IEEE Transactions on Robotics,2008,24(4):808-820
    [8] Kazufumi Ito,Xiong Kaiqi.Gaussian filters for nonlinear filtering problems [J].IEEE Transactions on Automatic Control,2000,45(5):910- 927
    [9] Norgaard M,Poulsen N K,Ravn O.Advances in derivative free state estimation for nonlinear systems .IMM-Technical Report-1998-15,1998
    [10] 严恭敏,严卫生,徐德民.简化UKF滤波在SINS大失准角初始对准中的应用[J].中国惯性技术学报,2008,20(3):253-264 Yan Gongmin,Yan Weisheng,Xu Demin.Application of simplified UKF in SINS initial alignment for large misalignment angles[J].Journal of Chinese Inertial Technology,2008,20(3):253-264(in Chinese)
    [11] 鲁道夫·布罗克豪斯.飞行控制[M].北京:国防工业出版社,1999 Rudolf Brockhaus.Flight control[M].Beijing:National Defense Industry Press,1999
  • 加载中
计量
  • 文章访问数:  1662
  • HTML全文浏览量:  256
  • PDF下载量:  462
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-07-30
  • 网络出版日期:  2013-07-30

目录

    /

    返回文章
    返回
    常见问答