Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34727
Title: Fusion of qualitative bond graph and genetic algorithms : a fault diagnosis application
Authors: Lo, CH
Wong, YK 
Rad, AB
Chow, KM
Keywords: Artificial intelligence
Genetic algorithms
Fault diagnosis
Qualitative bond graph
Issue Date: 2002
Publisher: Elsevier
Source: ISA transactions, 2002, v. 41, no. 4, p. 445-456 How to cite?
Journal: ISA transactions
Abstract: In this paper, the problem of fault diagnosis via integration of genetic algorithms (GA's) and qualitative bond graphs (QBG's) is addressed. We suggest that GA's can be used to search for possible fault components among a system of qualitative equations. The QBG is adopted as the modeling scheme to generate a set of qualitative equations. The qualitative bond graph provides a unified approach for modeling engineering systems, in particular, mechatronic systems. In order to demonstrate the performance of the proposed algorithm, we have tested the proposed algorithm on an in-house designed and built floating disc experimental setup. Results from fault diagnosis in the floating disc system are presented and discussed. Additional measurements will be required to localize the fault when more than one fault candidate is inferred. Fault diagnosis is activated by a fault detection mechanism when a discrepancy between measured abnormal behavior and predicted system behavior is observed. The fault detection mechanism is not presented here.
URI: http://hdl.handle.net/10397/34727
ISSN: 0019-0578
DOI: 10.1016/S0019-0578(07)60101-3
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