激活规则多目标优化算法在任务分解中的应用

针对工业生产中计算量大、故障原因复杂的故障诊断任务,提出一种基于MPSO/D的激活规则多目标优化算法。采用置信规则库系统(EBRB)实现任务分解,以激活规则的不一致性与激活权重和作为多目标优化问题的目标函数,利用MPSO/D算法获取不一致性最小的激活规则集合,提高推理准确性。标准测试函数和三元复合驱采出井卡泵故障诊断实例中的测试结果表明,该算法能够有效提高EBRB系统的推理能力和虚拟导诊的任务分解准确性。

Application of Rule Activation Multi-Objective Optimization Algorithm in Task Decomposition

To address fault diagnosis tasks with large amounts of computation and complex fault causes in industrial production,this paper proposes a rule activation multi-objective optimization algorithm based on MPSO/D.First,Extended Belief Rule Base(EBRB)system is used to implement task decomposition.Next,the objective functions of the problems are optimized with inconsistency of activation rules and sum of activation weights taken as multiple objectives.Then MPSO/D algorithm is used to obtain a set of activation rules with minimal inconsistency,so as to improve inference accuracy.Experimental results on the standard test functions and the fault diagnosis example of the well pump for ternary compound flooding show that the proposed algorithm can effectively improve the reasoning ability of the EBRB system and the accuracy of task decomposition of virtual guidance.