OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Online diagnosis of accidental faults for real-time embedded systems using a hidden Markov model

Ge, Ning and Nakajima, Shin and Pantel, Marc Online diagnosis of accidental faults for real-time embedded systems using a hidden Markov model. (2015) Simulation, vol. 91 (n° 10). pp. 851-868. ISSN 0037-5497

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
3MB

Official URL: http://dx.doi.org/10.1177/0037549715590598

Abstract

This article proposes an approach for the online analysis of accidental faults for real-time embedded systems using hidden Markov models (HMMs). By introducing reasonable and appropriate abstraction of complex systems, HMMs are used to describe the healthy or faulty states of system’s hardware components. They are parametrized to statistically simulate the real system’s behavior. As it is not easy to obtain rich accidental fault data from a system, the Baum–Welch algorithm cannot be employed here to train the parameters in HMMs. Inspired by the principles of fault tree analysis and the maximum entropy in Bayesian probability theory, we propose to compute the failure propagation distribution to estimate the parameters in HMMs and to adapt the parameters using a backward algorithm. The parameterized HMMs are then used to online diagnose accidental faults using a vote algorithm integrated with a low-pass filter. We design a specific test bed to analyze the sensitivity, specificity, precision, accuracy and F1-score measures by generating a large amount of test cases. The test results show that the proposed approach is robust, efficient and accurate.

Item Type:Article
Additional Information:http://sim.sagepub.com/content/early/2015/07/01/0037549715590598
HAL Id:hal-01316834
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Paul Sabatier-Toulouse III - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université de Toulouse I-Sciences Sociales - UT1 (FRANCE)
Other partners > National Institute of Informatics - NII (JAPAN)
Laboratory name:
Statistics:download
Deposited By: IRIT IRIT
Deposited On:20 Apr 2016 09:01

Repository Staff Only: item control page