Malek模型下的系统级故障诊断烟花算法
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  • 英文篇名:Fireworks Algorithm for System-level Fault Diagnosis Based on Malek Model
  • 作者:归伟夏 ; 蓝婷 ; 陆倩
  • 英文作者:GUI Wei-xia;LAN Ting;LU Qian;School of Computer and Electronics Information,Guangxi University;
  • 关键词:系统级故障诊断 ; Malek模型 ; 烟花算法
  • 英文关键词:system-level fault diagnosis;;malek model;;fireworks algorithm
  • 中文刊名:XXWX
  • 英文刊名:Journal of Chinese Computer Systems
  • 机构:广西大学计算机与电子信息学院;
  • 出版日期:2019-07-15
  • 出版单位:小型微型计算机系统
  • 年:2019
  • 期:v.40
  • 基金:国家自然科学基金项目(61862003,61862004)资助;; 广西研究生教育创新项目(YCSW2019036)资助
  • 语种:中文;
  • 页:XXWX201907010
  • 页数:6
  • CN:07
  • ISSN:21-1106/TP
  • 分类号:46-51
摘要
为了更高效地解决系统级故障诊断问题,首次将烟花算法应用到故障诊断Malek模型中.充分利用烟花算法在局部搜索和全局搜索方面良好的自调节能力,引入最小爆炸半径检测机制,并采用改进的爆炸算子、高斯变异操作和新的映射策略,得到一个新的系统级故障诊断算法.通过仿真实验表明,该算法能以较短的CPU运行时间判断出故障集,从而证明算法具有良好的稳定性和快速性,并能高效解决Malek模型下的系统级故障诊断问题.
        In order to solve the system-level fault diagnosis problem more efficiently,the fireworks algorithm is firstly applied to the fault diagnosis on Malek model. Make full use of the good ability of self-regulation for local search and global search of the fireworks algorithm. The minimum explosion radius detection mechanism is cited in the article. And improving explosive operator,optimizing Gaussian mutation operator,and new mapping strategy are used to build a new system-level fault diagnosis algorithm on Malek model.Simulation results show that the fireworks algorithm can work out the fault sets with a shorter CPU running time,which proves that the algorithm has good stability and rapidity,and it can effectively solve the system-level fault diagnosis problem under the Malek model.
引文
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