基于免疫克隆优化的阴性选择算法在电机故障检测中的应用  

Application of the Negative Selection Algorithm Based on Immune Clone Optimization in Motor Fault Detection

作　　者：姜新通[1] 陈言[1] 刘钊铭 

机构地区：[1]黑龙江八一农垦大学信息技术学院,黑龙江大庆163319

出　　处：《电气自动化》2018年第1期7-9,39,共4页Electrical Automation

摘　　要：阴性选择算法(NSA)和免疫克隆选择算法是两种典型的人工免疫系统。首先介绍了阴性选择算法和免疫克隆算法的基本原理,由于阴性选择算法的检测器存在大量无法检测的黑洞。采用免疫克隆优化算法对阴性选择算法生成的检测器进行优化,以提高故障检测率。最后通过检测电机的故障轴承证明了方法的有效性。Negative selection algorithm （NSA） and immune clone selection algorithm are two typical artificial immune systems. Firstly, this paper introduces basic principles of these two algorithms. As the NSA detector has a large number of non-detectable black holes, we use immune clone optimization algorithm to optimize the detector generated by NSA to raise the fault detection rate. Finally, the effectiveness of the proposed approach is proved by detection of the faulty bearing of the motor.

关 键 词：阴性选择算法(NSA) 免疫克隆优化 黑洞 检测器 故障检测 

分 类 号：TM921.41[电气工程—电力电子与电力传动]