Automated equipment monitoring and diagnosis based on a generic symptom-fault source definition framework

• Main Authors: Kuan_hsien Lee, 李冠賢
• Other Authors: Yuan-Chen Yu
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/554hxg

碩士 === 國立高雄第一科技大學 === 系統資訊與控制研究所 === 96 === For equipment diagnosis, phenomenon or signals are the information that we can observe or measure from the equipment directly. However, to determine the fault source of the equipment, from those observed phenomenon or measured signals is usually not that straight forward. It also quite often dependents on the operation state that the equipment was in when the fault happened. How to properly organize and correlate those observed phenomenon, measured signals, and system states to find out the fault sources is an important issue in automated equipment diagnosis. Thus, the purpose of this research is mainly to propose a generic symptom-fault source definition framework, Based on this framework, the measured signals, system logic states, system numerical states, fault symptoms, and fault sources can be explicitly defined on a sub system, a module or even a device of the equipment. The relationship among those inference chunks of diagnosis can also then be explicitly defined through diagnosis rules. The format for those diagnosis rules were proposed in this research as well.