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Electric Locomotive Electrical Part Of The Fault Diagnosis Expert System

Posted on:2010-02-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y B LiuFull Text:PDF
GTID:2192360278969073Subject:Traffic Information Engineering & Control
Abstract/Summary:PDF Full Text Request
The fault diagnosis study of electrical system in Electric locomotive is an urgent solution to ensure the safe operations of locomotive and reduce the machine-breaking incidents. This paper take SS9 electric locomotive as an example, take electrical equipment of electric locomotive as a study object. The composition of electrical system in electric locomotive is introduced. Locomotive operation and relevant information is obtained from locomotive manufacturer. The common fault of electrical system in electric locomotive is summarized. The shortages of existed vehicle-carried monitoring equipment and microcomputer diagnosis system is analyzed.Based on the analysis of electrical system in electric locomotive, a fault diagnosis system of electrical system is designed, which can be divided into two parts: data collection module and vehicle-carried fault diagnosis expert system module.Data collection module take CPCI industrial control machine as a platform, which involve a variety of bus types, including the MVB, CAN, RS485, GSM-R and so on. Meanwhile, the entire network architecture of fault diagnosis and GSM-R communication protocol is designed here.The design of expert system is the core of the entire study of fault diagnosis system. The establishment of fault knowledge database and the design of fault reasoning machine are very important. According to the fault characteristics of electrical system in electric locomotive, a double mode reasoning based on accurate knowledge reasoning together with neural network is advanced and the expert system model is set up respectively.Finally, the development and implementation of fault diagnosis expert system is studied based on the design. And the software of fault diagnosis expert system is demonstrated.
Keywords/Search Tags:electrical system, fault diagnosis, neural network, precise reasoning, expert system
PDF Full Text Request
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