基于基因算法的加工质量故障诊断研究与实现

 以基于节约覆盖集理论的概率因果诊断模型为理论基础,以基因算法为该模型的求解策略,两者结合起来解决质量管理界的难点问题之一——机械加工过程质量故障诊断问题,其中又以构造一个合理有效的基因算法个体适合度评价函数为重点,同时引入了故障树分析方法,来提高诊断模型的准确性和可解释性。应用研究表明,该方法将有效地解决加工质量的诊断与改进问题。

RESEARCH ON QUALITY FAULT DIAGNOSIS IN MECHANICAL MACHINING PROCESS BASED ON GENETIC ALGORITHM

The probabilistic causal model, based on the parsimonious covering theory, is a universal fault diagnosis model and its shortcomings and some improvements are firstly described. And then a new improved model based on a genetic algorithm is put forward to solve the quality fault diagnosis problem in mechanical machining process, in which some steps are introduced in detail,and an individual fitness evaluation function is developed by analyzing the relationship between the machining error and error resource and using fault tree analysis. Finally, some implementation techniques are described and the feasibility of the method is demonstrated by means of CASE.