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提出了一个基于混合智能的电火花加工电参数学习模型 ,它模仿熟练操作者的决策过程 ,由工艺数据库、加工规则库、学习模块和推理模块组成。在学习模块中利用遗传算法从工艺数据库中抽取出反映电参数和加工结果之间关系的模糊产生式规则 ,存储在规则库中。推理模块基于这些规则利用模糊推理对新的加工要求提供合适的电参数。
A learning model of electric spark machining parameters based on hybrid intelligence is proposed, which imitates the decision-making process of skilled operators. It consists of technology database, processing rule base, learning module and reasoning module. In the learning module, genetic algorithm is used to extract the rules of fuzzy generation that reflect the relationship between electrical parameters and machining results from the process database and stored in the rule base. Based on these rules, the inference module utilizes fuzzy reasoning to provide appropriate electrical parameters for new processing requirements.