document: Fusion of qualitative bond graph and genetic algorithms : A fault diagnosis application In this paper , the problem of fault diagnosis via integration of genetic algorithms -LRB- GA 's -RRB- and qualitative bond graphs -LRB- QBG 's -RRB- 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
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