DocumentCode
314350
Title
A knowledge-based approach for fault detection and isolation in analog circuits
Author
El-Gamal, Mohamed A.
Author_Institution
Dept. of Math. & Comput. Sci., United Arab Emirates Univ., Al-Ain, United Arab Emirates
Volume
3
fYear
1997
fDate
9-12 Jun 1997
Firstpage
1580
Abstract
A new knowledge-based analog fault detection and isolation technique is proposed. It is based on utilizing the domain knowledge in order to design a training set which characterizes the behavior of the circuit under test in both fault-free and fault situations. The training set expressed as a set of rules is then mapped into a rule-based connectionist neural network. This network is trained to perform the desired fault isolation. The effectiveness of the technique is demonstrated through a testing example
Keywords
analogue circuits; circuit analysis computing; circuit testing; fault diagnosis; knowledge based systems; learning (artificial intelligence); neural nets; analog circuits; domain knowledge; fault detection and isolation; knowledge-based approach; rule-based connectionist neural network; training set; Analog circuits; Circuit faults; Circuit simulation; Circuit testing; Dictionaries; Electrical fault detection; Fault detection; Fault diagnosis; Mathematics; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.614129
Filename
614129
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