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
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;
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.614129
