NDLI: A factorial hidden markov model (FHMM)-based reasoner for diagnosing multiple intermittent faults

Content Provider	IEEE Xplore Digital Library
Author	Singh, S. Kodali, A. Pattipati, K.
Copyright Year	2009
Description	Author affiliation: General Motors India Science Lab, Bangalore, Karnataka 560066, India (Singh, S.) \|\| Department of Electrical and Computer Engineering, University of Connecticut, Storrs, 06226, USA (Kodali, A.; Pattipati, K.)
Abstract	This paper presents a factorial hidden Markov model (FHMM)-based diagnostic reasoner to handle multiple intermittent faults. The dynamic multiple fault diagnosis (DMFD) problem is to determine the most likely evolution of fault states, the one that best explains the observed test outcomes over time. In our previous research work [1], we have shown that the problem of diagnosing dynamic multiple faults in the presence of imperfect test outcomes, is an NP-hard problem. Here, we combine a Gauss-Seidel coordinate ascent optimization method with a Soft Viterbi decoding algorithm for solving the DMFD problem. We demonstrated the algorithm on small-scale and medium-scale systems and the simulation results shows that this approach improves primal function value (1.4%∼8.3%) and correct isolation rate (1.7%∼11.4%) as compared to a Lagrangian relaxation method discussed in our previous work [1].
Starting Page	146
Ending Page	151
File Size	388201
Page Count	6
File Format	PDF
ISBN	9781424445783
DOI	10.1109/COASE.2009.5234134
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Testing Fault diagnosis NP-hard problem Gaussian processes Optimization methods Viterbi algorithm Decoding Lagrangian functions Relaxation methods imperfect tests Inermittent faults multiple fault diagnosis hidden Markov models dynamic faults
Content Type	Text
Resource Type	Article

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