| Summary: | 碩士 === 中原大學 === 電機工程學系 === 85 ===
The Massive Transit System in Taipei started the planning phase about ten years ago. Two lines of systems have been constructed since then. Both of them, Mu-Cha Line and Dan-Shui line, are now commerically operated. But the Dan-Shui line is a type of high capacity transportation system. The train is operated by an operator in the train together with operators in the control center. Thus, the human operators involve a lot of decision making during the train operation. During an emergency condition, the system operators in the control center have to handle the abnormal situation, resolve the problems and guide the operator in the train to remedy the problems. In order to understand the operating state of the system, the number of measurements installed along the rail-way is large. Thus, it is very difficult for system operators to identify the problems and propose an adequate remedial control action during a short period of time. In order to solve the problem, many researchers had worked on the alarm processor issue and accomplished some achievement, e.g., Intelligent Alarm Processor (I.A.P.). However, most of the work on the I.A.P. is based on the rules of expert systems. One of the drawbacks of using rule-based expert systems is that the completeness of the knowledge base can not be guaranteed. Model-based approach, on the other hand, can be used to solve this problem. In this thesis, a model-based intelligent alarm processor is modified to handle analog change alarms generated by the SCADA of the Power Supply System of the Massive Rapid Transit System of Taipei. The test results show that the proposed model-based expert system can identify the cause of the alarms correctly.
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