基于SVM观测器的新异类故障检测方法及应用

Novelty Faults Detection Method Based on SVM Observer and Its Application

针对目前天文望远镜驱动系统新异类故障检测遇到的先验信息不足、特征描述困难等现状,提出一种基于支持向量机状态观测器的新异类故障检测方法。首先,以望远镜驱动系统为对象,介绍该方法的基本原理,并建立通用状态观测器诊断模型;其次,以望远镜运行数据为样本对该方法进行验证。该方法新异类故障检测准确率为94%,耗时为0.047 s;同类反向传播(back propagation,简称BP)、径向基函数(radial basis function,简称RBF)观测器检测准确率为85.5%和58%,耗时为7.628和1.985 s。结果表明:基于支持向量机(support vector machine,简称SVM)状态观测器对望远镜驱动系统新异类故障检测性能明显优于误差反向传播和径向基函数观测器。将该方法实现于故障诊断及自愈半物理仿真平台,证明其工程应用的可行性。

In light of the lack of prior information and the difficulties in characterizing when detecting novelty faults of the driving systems of astronomical telescopes,the method based on the SVM observer is proposed.First,the principles of the proposed method are introduced and a diagnostic model of the general state observer is established in terms of the driving systems of astronomical telescopes. Then,the telescope’s operation data are used as samples to test the proposed method. It takes 0.047 s to detect novelty faults and the accuracy is94%. Meanwhile,the back propagation(BP)observer needs 7.628 s and finishes with a accuracy of 85.5%,and the radial basis function(RBF)observer only reaches a accuracy of 58% within 1.985 s. Compared with them,the method based the support vector machine(SVM)observer has obvious advantages. Finally,the proposed method is implemented on a fault diagnosis and self-healing semi-physical simulation platform,which proves its feasibility in engineering applications.