DocumentCode
3216780
Title
A novel analytical framework for qualitative Model-Based Fault Diagnosis
Author
Baniardalani, Sobhi ; Askari, Javad ; Afzalian, Ali A.
Author_Institution
Electr. & Comput. Eng. Dept., Isfahan Univ. of Technol., Isfahan, Iran
fYear
2010
fDate
9-11 June 2010
Firstpage
1929
Lastpage
1934
Abstract
This paper presents a unified analytical framework for qualitative Model-Based Fault Diagnosis (MBFD), similar to the quantitative MBFD. Dioid Algebra is used in addition to ordinary Algebra for simulation qualitative models. The framework is illustrated and adapted in details for three main qualitative diagnostic methods which employ Stochastic, Non-Deterministic, and Timed Automata, respectively. Using the proposed methodology, we are able to compute quantitative residuals for qualitative models. Therefore some useful and practical computational tasks can be carried out on the obtained residuals. One of the main contributions of the paper is introducing a new approach to qualitative structured residual generation, which is applied to timed automata models.
Keywords
Algebra; Automata; Automatic control; Automation; Fault diagnosis; Filters; Java; Pattern recognition; Robustness; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation (ICCA), 2010 8th IEEE International Conference on
Conference_Location
Xiamen, China
ISSN
1948-3449
Print_ISBN
978-1-4244-5195-1
Electronic_ISBN
1948-3449
Type
conf
DOI
10.1109/ICCA.2010.5524167
Filename
5524167
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