Application of artificial intelligence in electronic circuit diagnosis

Miscellaneous · Sun Jan 01 00:00:00 EST 1989

OSTI ID:5896740

Sabour, F

This dissertation has examined the field of Artificial Intelligence (AI) in general and the sub-field of Expert-System (ES) in particular. Research in automatic fault diagnosis dates back to the 1950's; but until recent times, it had been neglected by the AI community except for the diagnosis of very small and relatively simple low-level electronic circuits (e.g., (Brown and Sussman, 1974), (Brown and Burton, 1975) and (Brown, 1977)). With increasing complexity of modern electronic systems, the cost of performing any diagnosis can be very high. The historical approach for a human trouble-shooter to detect, isolate and repair faults is no longer practical in general situation. The explosive growth of new technologies has quickened the pace of new product introductions. The skill levels required to maintain and diagnose today's electronic circuits are increasingly demanding. Skilled technicians must undergo long periods of basic classroom education and many years of on the job training before becoming productive. Knowledge is perishable. Knowledge of technicians can easily be lost, as one leaves his or her job. Furthermore, knowledge generally is not easily sharable among technicians across vast geographical space. Finally, today's technicians are finding it hard to keep up with technological progress and new product proliferations. On line expert guidance will be very helpful. The research presented in this dissertation was prompted by need for a system which can preserve, organize, distribute and present expert knowledge to technicians or engineers. Expert system technology, a subset of modern AI research, has been implemented to fulfill these sets of objectives. This research has demonstrated that artificially intelligence can model human thinking process. An expert system was built as a part of total contribution to the field.

• Research Organization: Union for Experimenting Coll. and Univ., Cincinnati, OH (USA)
• OSTI ID: 5896740
• Resource Relation: Other Information: Thesis (Ph.D)
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
DIAGNOSTIC TECHNIQUES
AUTOMATION
ELECTRONIC CIRCUITS
FAILURE MODE ANALYSIS
ARTIFICIAL INTELLIGENCE
DIAGNOSTIC USES
EXPERT SYSTEMS
KNOWLEDGE BASE
SYSTEM FAILURE ANALYSIS
SYSTEMS ANALYSIS
USES
990200* - Mathematics & Computers