Title :
Multiple failure diagnosis
Author :
Sheppard, John W. ; Simpson, William R.
Author_Institution :
ARINC Res. Corp., Annapolis, MD, USA
Abstract :
Model based diagnostic systems have generally avoided the issue of multiple failure diagnosis due to the computational complexity of covering all possible multiple faults and still providing an efficient diagnostic strategy. Optimization of decision trees is already known to be NP-complete, and the number of combinations of multiple faults just serves to exacerbate the problem. Nevertheless, model based diagnosis is becoming popular, and the need for multiple failure diagnosis is real. In this paper, we will provide a formal analysis of the multiple failure problem in the context of one model based approach. Specifically, we will discuss algorithms and their complexity for diagnosing multiple failures using the information flow model
Keywords :
automatic testing; computational complexity; diagnostic reasoning; failure analysis; fault diagnosis; algorithms complexity; computational complexity; decision trees; formal analysis; inference meta rules; information flow model; model based diagnostic systems; multiple failure diagnosis; multiple faults; optimization; Computational complexity; Context modeling; Decision trees; Electronic mail; Failure analysis; Fault detection; Fault diagnosis; Information analysis; Logic testing; System testing;
Conference_Titel :
AUTOTESTCON '94. IEEE Systems Readiness Technology Conference. 'Cost Effective Support Into the Next Century', Conference Proceedings.
Conference_Location :
Anaheim, CA
Print_ISBN :
0-7803-1910-9
DOI :
10.1109/AUTEST.1994.381594
