JOURNAL ARTICLE

Fuzzy model-based fault detection and isolation

Abstract

The model-based fault detection and diagnosis (FDI) is an interesting method, because of economical and safety related matters. However, in practice it is very difficult to achieve an accurate modeling for complex nonlinear systems. If the system structure is not precisely known, the diagnosis has to be based primarily on data or heuristic information. Fuzzy system theory is an interesting tool to handle these situations. The use of characteristics of fuzzy logic theory makes it suitable for fault diagnosis. In this paper, a simulator of an industrial servo-actuated valve is used to simulate several faults in the system. These faults are some of the possible faults in the real system. The fuzzy model-based FDI system developed in this paper was able to detect and isolate all the simulated faults.

Keywords:
Fault detection and isolation Fuzzy logic Computer science Heuristic Fault (geology) Nonlinear system Control engineering Fuzzy control system Isolation (microbiology) Data mining Artificial intelligence Engineering

Metrics

8
Cited By
2.58
FWCI (Field Weighted Citation Impact)
25
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Fault Detection and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Fuzzy Logic and Control Systems
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Control Systems Optimization
Physical Sciences →  Engineering →  Control and Systems Engineering

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