基于PMC模型的MWOFD算法  

MWOFD algorithm based on PMC model

作　　者：宣恒农[1] 赵冬[1] 苗春玲[1] 张润驰 刘田田[1] XUAN Hengnong;ZHAO Dong;MIAO Chunling;ZHANG Runchi;LIU Tiantian(School of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210046, China)

机构地区：[1]南京财经大学信息工程学院,南京210046

出　　处：《计算机工程与应用》2017年第3期226-230,共5页Computer Engineering and Applications

基　　金：国家自然科学基金重大研究计划资助项目(No.90718008);国家自然科学基金重点项目(No.6113305);江苏省自然科学基金(No.2004119);江苏省研究生培养创新工程(No.KYLX_0995)

摘　　要：为了诊断出系统中的故障单元,首次将贝壳漫步优化算法用于解决系统级故障诊断问题,提出一种高效快速的诊断算法——MWOFD诊断(Mussels Wandering Optimization Fault Diagnosis)算法。结合系统级故障诊断的特点,设计了个体化编码及初始化的方法,并根据诊断模型所满足的方程约束重新设计了适应度函数,同时对二进制映射算法进行优化。最后将新算法与AD-FAFD算法,FAFD算法和EAFD算法进行实验对比,结果表明:MWOFD算法有效地提高了诊断正确率和诊断效率。In order to diagnose the fault units in the system,this paper firstly uses the Mussels Wandering Optimizationalgorithm to solve the system-level fault diagnosis problem,proposes an efficient fault diagnosis algorithm-the MusselsWandering Optimization Fault Diagnosis(MWOFD).Combining with the characteristics of system-level fault diagnosis itproposes the Mussels Wandering encoding and initialization,and designs the new fitness function according to equationconstraint conditions that the diagnostic model has to meet,at the same time it optimizes the existing binary mapping algorithm.Finally,the new algorithm is compared with AD-FAFD algorithm,FAFD algorithm and EAFD algorithm experimentally.Experimental results show that MWOFD algorithm improves the diagnostic accuracy and efficiency of diagnosiseffectively.

关 键 词：系统级故障诊断 方程模型 贝壳漫步算法 贝壳漫步诊断(MWOFD)算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] TP301[自动化与计算机技术—计算机科学与技术]