摘要
提出一种基于人工免疫模型的故障诊断方法。根据免疫系统机理构建模型框架,模拟T细胞和B细胞功用,分别设计模型中的T模块和B模块。T模块采用实向量阴性选择算法生成异常检测器,完成系统的异常状态检测;B模块响应系统实际状态,运用聚类原理动态进化,形成告警信息反馈至T模块。2个模块相互作用,共同实现系统状态的在线实时检测。应用结果表明,该模型具有正确性和有效性。
This paper presents a fault diagnosis method using artificial immune model.Using immunological principles,the frame of model is created.The T-module and B-module of the model are designed by simulating functions of T-cells and B-cells.The T-module discriminates anomaly states from the states of the system.The B-module responds the actual states of system and dynamically evolves using clustering principle.The alert information is fed back to the T-module.The interaction of these two modules made the system to achieve on-line detection.This model is successfully applied to rudder fault diagnosis of a certain pilotless.Results confirm the feasibility and effectiveness of this method.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第16期5-7,共3页
Computer Engineering
基金
国家部委基金资助项目
关键词
人工免疫模型
故障诊断
阴性选择
聚类
artificial immune model
fault diagnosis
negative selection
clustering
