Evaluation of Fault Diagnosability for Dynamic Systems With Unknown Uncertainties | Zendy

Fangzhou Fu | Zendy; Dayi Wang | Zendy; Wenbo Li | Zendy; Ping Liu | Zendy

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Evaluation of Fault Diagnosability for Dynamic Systems With Unknown Uncertainties

Author(s) -

Fangzhou Fu,

Dayi Wang,

Wenbo Li,

Ping Liu

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2816167

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, the quantitative fault diagnosability problem for a stochastic dynamic system subjects to unknown uncertainties is proposed. Reliable isolability, reliable detectability, and reliable distinguishability are newly defined for the studied uncertain system. By considering model uncertainties, norm-bounded disturbances, and noises, the quantitative diagnosability problem is originally transferred to an optimization problem. A novel methodology is proposed to quantify the fault diagnosability based on a new sliding window model, which greatly alleviates the computation task. To quantify the disturbance effect on the diagnosability performance, disturbance ratio is defined. Furthermore, the reliable isolability conditions for a fault vector with a specific fault time profile is theoretically analyzed. Effectiveness of the proposed method is verified by a numerical example.

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