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通过对机械设备中存在的因果诊断知识故障树模型的分析，提出了一种基于解释学习的产生规则的方法．在对诊断对象进行深入分析其知识表示的基础上，给出了知识编辑细化的框架．在此框架的基础上，得出了基于解释学习的知识归纳方法．还对解释学习中存在的效用问题进行了探讨，并提出提高其效用的策略．
Based on the analysis of the fault tree model of causal diagnosis in mechanical equipment, a method of generating rules based on interpretation learning is proposed. On the basis of deeply analyzing the knowledge object of the diagnosis object, this paper gives a framework of detailed knowledge editing. Based on this framework, a method of knowledge induction based on interpretation learning is derived. It also explores the utility problems existing in the explanation of learning and puts forward some strategies to improve its effectiveness.