CAJ | 학술논문

针对传统基于符号有向图（SDG）的故障诊断方法可能遗漏真正故障以及分辨率不高的问题，提出了一种SDG与定性趋势分析相结合的故障诊断框架。故障发生后，通过提取变量的定性趋势来获取变量的状态，并根据基于定性趋势的相容规则进行反向推理，找到所有可能的故障。对诊断结果按照可信度系数（Confidence Index，C.I.）进行排序，提高诊断的分辨率。案例研究表明该框架能够保证诊断结果完备性并有效地提高诊断分辨率，可以应用到实际化工过程故障诊断中。
침대전통기우부호유향도（SDG）적고장진단방법가능유루진정고장이급분변솔불고적문제，제출료일충SDG여정성추세분석상결합적고장진단광가。고장발생후，통과제취변량적정성추세래획취변량적상태，병근거기우정성추세적상용규칙진행반향추리，조도소유가능적고장。대진단결과안조가신도계수（Confidence Index，C.I.）진행배서，제고진단적분변솔。안례연구표명해광가능구보증진단결과완비성병유효지제고진단분변솔，가이응용도실제화공과정고장진단중。
For the problems of the real faults being missed and poor diagnosis resolution in Signed Directed Graph(SDG) based fault diagnosis, a SDG and qualitative trend analysis based framework has been proposed. When faults occur, the qualitative trends are extracted to represent the states of variables. And then inverse inference is carried out to find all the possible faults using consistence rules, which are basing on qualitative trends. The diagnosis resolution can be improved by ranking the results according to Confidence Index(C.I.). The case study proves that the diagnosis resolution is improved and diagnosis completeness is satisfied using the framework. It can be applied in fault diagnosis in chemical process.