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Fault Diagnose Expert System Application On Weapon System

Posted on:2006-04-07Degree:MasterType:Thesis
Country:ChinaCandidate:Z L TangFull Text:PDF
GTID:2178360182977270Subject:Electronic and Information Engineering
Abstract/Summary:PDF Full Text Request
Expert System is an intelligent program system which is always built up by human interface; knowledge warehouse; data warehouse and inference engine. It is the main research direction of artificial intelligence knowledge. Many fault information and practice experience are concluded to be rules that can be used by computer, all these rules are offered to knowledge warehouse finally, so we can infer and analyze all data using these rules. With the help of expert system we can find out the final fault reason. Furthermore, expert system has the function of self-study.In order to meet the maintaining request of army, intelligent diagnosis project with the synthesis function must be used. This fault diagnosis system must be designed to adapt for field army needs. Therefore, fault diagnosis expert system (FDES) is introduced to the maintaining of weapon system.At first, we discussed the working principle and general structure of expert system, at the same time we analyzed the construct process of expert system. Secondly, we brought forward the design project which includes the system's content such as conceptual hierarchy, total framework, and particular constitution of each part. The paper shows the design thinking which includes two-knowledge representation and two-inference engine, we used this knowledge to make up of the hard core of FDES.This paper discussed the rationale of each representation. Advantage or disadvantage of each representation is found out. Finally, we chose two-knowledge representation: representation based on rule and representation based on frame. At the same time, we chose two-inference engine: front inference and reverse inference.At last, a detail instance of FDES and summarization are given.
Keywords/Search Tags:Fault Diagnosis, Expert System, Knowledge representation, Inference engine
PDF Full Text Request
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