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Title: Model-based fault diagnosis in continuous dynamic systems
Authors: Lo, CH
Wong, YK 
Rad, AB
Keywords: Artificial intelligence
Genetic algorithms
Fault detection
Fault diagnosis
Qualitative bond graph
Issue Date: 2004
Publisher: Elsevier
Source: ISA transactions, 2004, v. 43, no. 3, p. 459-475 How to cite?
Journal: ISA transactions 
Abstract: Traditional fault detection and isolation methods are based on quantitative models which are sometimes difficult and costly to obtain. In this paper, qualitative bond graph (QBG) reasoning is adopted as the modeling scheme to generate a set of qualitative equations. The QBG method provides a unified approach for modeling engineering systems, in particular, mechatronic systems. An input-output qualitative equation derived from QBG formalism performs continuous system monitoring. Fault diagnosis is activated when a discrepancy is observed between measured abnormal behavior and predicted system behavior. Genetic algorithms (GA's) are then used to search for possible faulty components among a system of qualitative equations. In order to demonstrate the performance of the proposed algorithm, we have tested it on a laboratory scale servo-tank liquid process rig. Results of the proposed model-based fault detection and diagnosis algorithm for the process rig are presented and discussed.
ISSN: 0019-0578
DOI: 10.1016/S0019-0578(07)60161-X
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