TY - JOUR
T1 - Small Fault Diagnosis With Gap Metric
AU - Jin, Hailang
AU - Zuo, Zhiqiang
AU - Wang, Yijing
AU - Cui, Lei
AU - Zhao, Zhengen
AU - Li, Linlin
AU - Gao, Zhiwei
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61933014, Grant 62173243, Grant 62273250, Grant 62003161, Grant 62233009, and Grant 62073029; and in part by the Tianjin Research Innovation Project for Postgraduate Students under Grant 2021YJSB142.
Publisher Copyright:
© 2013 IEEE.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - This article proposes a novel data-driven gap metric fault detection and isolation (FDI) approach for small multiplicative fault. First, the scheme of model-based fault classification and gradation is developed by means of the gap metric. Subsequently, the data-driven gap metric is utilized to detect a small fault via the mechanism model. Furthermore, fault detectability criterion is derived with the help of the developed fault detectability indicator. The relationship between fault detectability indicator and fault detection index is then investigated to analyze fault detection performance. To enhance fault isolability, a solution of appropriate fault cluster center model and radius is provided under the condition of fault isolation. Third, a gap metric fault-tolerant control strategy is exploited to guarantee system stability when a large fault is diagnosed by the developed FDI approach. The speed regulation of dc-motor and dc–dc converter are used for simulation and experiment verifications. Moreover, the comparison results and Monte Carlo simulation demonstrate the superiority and reliability of the proposed method.
AB - This article proposes a novel data-driven gap metric fault detection and isolation (FDI) approach for small multiplicative fault. First, the scheme of model-based fault classification and gradation is developed by means of the gap metric. Subsequently, the data-driven gap metric is utilized to detect a small fault via the mechanism model. Furthermore, fault detectability criterion is derived with the help of the developed fault detectability indicator. The relationship between fault detectability indicator and fault detection index is then investigated to analyze fault detection performance. To enhance fault isolability, a solution of appropriate fault cluster center model and radius is provided under the condition of fault isolation. Third, a gap metric fault-tolerant control strategy is exploited to guarantee system stability when a large fault is diagnosed by the developed FDI approach. The speed regulation of dc-motor and dc–dc converter are used for simulation and experiment verifications. Moreover, the comparison results and Monte Carlo simulation demonstrate the superiority and reliability of the proposed method.
KW - Data-driven
KW - fault detection and isolation (FDI)
KW - fault-tolerant control (FTC)
KW - gap metric
KW - model-based
KW - small fault
UR - http://www.scopus.com/inward/record.url?scp=85161057930&partnerID=8YFLogxK
U2 - 10.1109/tsmc.2023.3276060
DO - 10.1109/tsmc.2023.3276060
M3 - Article
VL - 53
SP - 5715
EP - 5728
JO - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
JF - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
SN - 1083-4427
IS - 9
ER -