基于AOA-MSVM的控制集群故障检测方法  

Fault Detection Method of Control Cluster Based on AOA-MSVM

作　　者：杨博 庄毅[1] YANG Bo;ZHUANG Yi(College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学计算机科学与技术学院,江苏南京211106

出　　处：《计算机与现代化》2023年第12期112-117,共6页Computer and Modernization

基　　金：国家自然科学基金资助项目(61572253);“十三五”装备预研领域基金资助项目(61402420101HK02001);航空科学基金资助项目(2016ZC52030)。

摘　　要：控制集群系统的复杂性和多样性导致集群系统易发生故障,从而降低集群系统的可用性。针对现有的故障检测方法存在的检测效率和准确度较低、故障类型难以有效自动识别等问题,本文提出一种基于改进的自适应算术优化的多类支持向量机(Arithmetic Optimization Algorithm-Multi-class SVM,AOA-MSVM)的控制集群故障检测方法来检测集群中的故障,以提高集群系统的可用性。首先,运用局部线性嵌入算法对集群系统中监测到的系统信息进行降维;然后,针对集群系统中故障种类多的特点,运用一对多支持向量机的方法构建故障检测模型,提升检测故障的能力;最后,使用改进的自适应算术优化算法对模型参数求最优解。搭建高可用控制集群系统进行对比实验,实验结果表明,本文提出的故障检测方法具有更高的检测效率和准确度并可有效识别故障类型。The complexity and diversity of the control cluster system lead to the easy failure of the cluster system,which reduces the availability of the cluster system.In view of the problems in the existing fault detection methods,such as low detection efficiency and accuracy,and difficulty in effective automatic identification of fault types,in this paper,a control cluster fault detection method based on an improved adaptive Arithmetic Optimization Algorithm-Multi-class SVM(AOA-MSVM)is proposed to detect cluster faults in order to improve the availability of the cluster system.Firstly,the local linear embedding algorithm is used to reduce the dimensionality of the system information detected in the cluster system.Then,according to the characteristics of multiple kinds of faults in the cluster system,the method of one-to-many support vector machine is used to build a fault detection model to improve the ability of fault detection.Finally,the improved adaptive arithmetic optimization algorithm is used to obtain the optimal solution of the model parameters.A high availability control cluster system is set up for comparative experiments.The experimental results show that the proposed fault detection method has higher detection efficiency and accuracy and can effectively identify the fault type.

关 键 词：故障检测 集群 多类支持向量机 算术优化算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]