Dissertation
Dissertation > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Expert systems, knowledge engineering

Space Camera Fault Diagnosis Expert System Research and Implementation

Author LiuXuYue
Tutor HuJun
School Graduate Schoo,Chinese Academy of Sciences
Course Applied Computer Technology
Keywords Expert System Fault Tree Analysis Neural Network Frame
CLC TP182
Type Master's thesis
Year 2010
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In order to improve the efficiency of space camera troubleshooting and shorten troubleshooting time, reduce troubleshooting human and material resources, the design can be more than a collection of the best experience of experts to achieve human space camera combined diagnosis of fault diagnosis expert system . Elaborate fault diagnosis technology research status at home and abroad to introduce expert systems , fault tree analysis and neural network fault diagnosis technology features and basic methods . For their advantages and disadvantages , will take reasonable combination of the three fault diagnosis method for fault diagnosis. In the comparative analysis , based on the fault tree has established itself as one of the means of knowledge acquisition , rule -based framework and knowledge base construction scheme . Using neural network self- learning ability , BP neural network model and network model set up systems Bayes learning machine . Since the main source of failure data FMEA table , according to the characteristics of knowledge acquisition , build space camera fault tree . Failure is mainly expressed in production rules . Then introduced the fault diagnosis inference mechanism . Reasoning using forward and reverse hybrid reasoning . Object-oriented language java and SQL Server as a development tool . Knowledge creation, inference engine and other experts explain procedures to implement parts of the system using java , knowledge of storage using SQL Server database to complete. For space camera for fault simulation , using the expert system for fault diagnosis , the results show that expert systems can quickly analyze the fault phenomena , proposed diagnostic results are consistent with reality.

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