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
Link To Document :
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