一种PMC模型下的系统级故障诊断烟花算法  

System-level Fault Diagnosis Fireworks Algorithm Based on PMC Model

作　　者：归伟夏[1] 陆倩 GUI Wei-xia;LU Qian(School of Computer and Electronics Information,Guangxi University,Nanning 530004,China)

机构地区：[1]广西大学计算机与电子信息学院,南宁530004

出　　处：《小型微型计算机系统》2018年第9期1944-1950,共7页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(61363002)资助

摘　　要：为了快速和有效地诊断出大规模多处理器系统中的故障结点,首次将烟花算法应用于系统级故障诊断中.充分利用烟花算法具有很好的全局搜索能力和局部搜索能力的自调节机制特点,结合PMC模型的故障诊断模式特点设计约束方程,提出新的适应度函数,并优化了变异算子以及选择策略,得到系统级故障诊断优化算法.仿真实验表明该算法具有很好的稳定性和收敛性,并证明了算法的有效性.To solve the problem that the fault nodes can be diagnosed quickly and effectively in large-scale multiprocessor systems，fireworks algorithm is applied to solving the systemlevel fault diagnosis problem for the first time as an effective diagnosis algorithm.Fireworks algorithm has a good global search ability and local search ability of self-regulation mechanism.Taking the most of this advantage of fireworks algorithm，the constraint equations are designed according to the characteristics of the PMC model，and a new fitness function is proposed.At the same time，the mutation operator and the selection strategy are optimized.The simulation result shows that the algorithm has good stability and convergence.Finally，the validity of the algorithm is proved.

关 键 词：系统级故障诊断 烟花算法 PMC模型 t-可诊断性 

分 类 号：TP306[自动化与计算机技术—计算机系统结构]