摘要
为了快速、准确的识别电站风机的故障类型,基于克隆选择算法和免疫网络算法,提出一种免疫群体网络算法,该算法能对多个抗原群体同时进行局部和全局搜索,从而形成2层搜索机制,保证了算法的局部和全局搜索能力,有效克服了未成熟收敛现象,提高了群体的多样性,仿真结果表明,免疫群体网络算法能有效识别电站风机故障。
Aiming at identifying the fault types of plant fans rapidly and correctly, a new immune population network algorithm was proposed in this paper, which combined clone selection algorithm and immune network algorithm. The immune population network algorithm can execute both local and global search to multiantigen population, and form two-layer searching mechanism. It improves the capability of global and local search, effectively eliminates the premature convergence and increases the diversity of antigen population. The simulation results indicats that the immune population network algorithm can recognize the plant fans＇ faults efficiently.
出处
《北京工业大学学报》
EI
CAS
CSCD
北大核心
2008年第11期1207-1210,共4页
Journal of Beijing University of Technology
基金
国家自然科学基金项目资助(60374029)
高等学校博士学科点专项科研基金项目资助(20060112005)
山西省青年科学基金项目资助(2007021018)
关键词
人工免疫系统
免疫群体网络算法
电站风机
故障诊断
artificial immune system
immune population network algorithm
plant fan
fault diagnosis
