Diagnosis of an automotive emission control system using fuzzy inference

Fault diagnosis of a physical plant is crucial for its healthy performance, as it could ultimately prevent catastrophic failure, help comply with envi ronmental regulations, and enhance customer satisfaction. There exist sever al methods to detect and isolate incipient faults that might cause a plant' s performance to deviate from the nominal, which can be either subjective o r objective. A scheme and methodology for integrating subjective (heuristic ) and objective (analytical) knowledge for fault diagnosis and decision-mak ing using fuzzy logic is demonstrated in this paper. Furthermore, the struc ture, challenges, and benefits of such integration are explored. Also, expe rimental results of the work carried out are presented. (C) 1999 Elsevier S cience Ltd. All rights reserved.