Knowledge compilation and refinement for fault diagnosis
Knowledge compilation and refinement for fault diagnosis
复制标题
故障诊断知识整理与细化
DOI：
10.1109/64.97790
复制
发表时间：
1991
期刊：
影响因子：
--
通讯作者：
Kotaro Nakamura
中科院分区：
文献类型：
--
作者：
S. Kobayashi;Kotaro Nakamura
描述了一个基于基于解释的学习的知识汇编框架，该框架使用案例、因果模型以及用于诊断的测量和测试知识。通过故障诊断案例和可操作性标准，将因果诊断知识编译为可操作性诊断知识。然后对该操作知识进行差异分析，将其细化为启发式诊断知识。讨论了该系统的实现及其在卷烟厂故障诊断中的实际应用
A knowledge-compilation framework that is based on explanation-based learning and that uses cases, causal models, and measurement and testing knowledge for diagnosis is described. Fault diagnostic cases as well as operationality criteria are used to compile causal diagnostic knowledge into operational diagnostic knowledge. A difference analysis is then performed on that operational knowledge to refine it into heuristic diagnostic knowledge. The implementation of the system and its application to a practical problem involving fault diagnosis in cigarette factories are discussed.<<ETX>>