Subspace-based Fault Detection - Multiplicative and Additive Fault

被引:0
|
作者
Kim, Young-Man [1 ]
机构
[1] Saginaw Valley State Univ, Univ Ctr, 7400 Bay Rd, Saginaw, MI 48710 USA
关键词
D O I
暂无
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
In this research, a technique is developed to separate an additive fault from a multiplicative fault of a system which is disturbed by integrated white noise. First, Predictor-based System Identification (PBSID) is formulated in a differenced form (DPBSID) in order to filter out the integrated white noise. Second, the differenced PBSID is reformulated in a recursive form (DRPBSID) which is for separating an additive fault from a multiplicative fault. If the fault type is multiplicative, the Frobenius norm of the difference between the identified system matrix and a changed one becomes greater than a threshold. By recursively updating the system matrix, the difference goes below the threshold hence, a multiplicative fault is separated from an additive one. This technique is applied to a complex system and its effectiveness is demonstrated using Matlab simulation.
引用
收藏
页数:6
相关论文
共 50 条
  • [21] Robust detection of intermittent multiplicative sensor fault
    Zhang, Junfeng
    Christofides, Panagiotis D.
    He, Xiao
    Zhao, Yinghong
    Zhang, Zhihao
    Zhou, Donghua
    [J]. ASIAN JOURNAL OF CONTROL, 2021, 23 (01) : 463 - 473
  • [22] Fault detection of multimodal processes based on local entropy double subspace
    Guo, Jin-Yu
    Liu, Yu-Chao
    Li, Yuan
    [J]. Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2020, 37 (09): : 2020 - 2028
  • [23] Fault detection in multimodal processes based on the local entropy double subspace
    Guo, Jinyu
    Zhao, Wenjun
    Li, Yuan
    [J]. TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2023, 45 (07) : 1323 - 1336
  • [24] Subspace identification based scheme for Fault Detection in drive train system
    Chouiref, H.
    Boussaid, B.
    Abdelkrim, M. N.
    Puig, V.
    Abrun, C.
    [J]. 2015 4TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC), 2015, : 199 - 205
  • [25] Fault subspace decomposition and reconstruction theory based online fault prognosis
    Han, Min
    Li, Jinbing
    Han, Bing
    Zhong, Kai
    [J]. CONTROL ENGINEERING PRACTICE, 2019, 85 : 121 - 131
  • [26] KERNEL SUBSPACE-BASED ANOMALY DETECTION FOR HYPERSPECTRAL IMAGERY
    Nasrabadi, Nasser M.
    [J]. 2009 FIRST WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING, 2009, : 83 - 86
  • [27] Subspace-Based Detection and Localization in Distributed MIMO Radars
    Lai, Yangming
    Venturino, Luca
    Grossi, Emanuele
    Yi, Wei
    [J]. 2022 IEEE 12TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), 2022, : 365 - 369
  • [28] Local subspace-based denoising for shot boundary detection
    Pan, Xuefeng
    Zhang, Yongdong
    Li, Jintao
    Cao, Xiaoyuan
    Tang, Sheng
    [J]. NEW FRONTIERS IN APPLIED ARTIFICIAL INTELLIGENCE, 2008, 5027 : 32 - 41
  • [29] Subspace-based adaptive generalized likelihood ratio detection
    Burgess, KA
    VanVeen, BD
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1996, 44 (04) : 912 - 927
  • [30] An invariance property of some subspace-based detection algorithms
    Basseville, M
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1999, 47 (12) : 3398 - 3400