Fault diagnosis approach of dynamic system based on data driven of nonlinear spectrum

被引：0

作者：

Zhang, Jia-Liang ^{[1
]}

Cao, Jian-Fu ^{[1
]}

Gao, Feng ^{[1
]}

Han, Hai-Tao ^{[2
]}

机构：

[1] State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University

[2] Staff Office 101, The Second Artillery Engineering University

来源：

Kongzhi yu Juece/Control and Decision | 2014年 / 29卷 / 01期

关键词：

Adaptive identification; Fault diagnosis; Nonlinear spectrum; Support vector machine;

D O I：

10.13195/j.kzyjc.2012.1330

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The problem of fault diagnosis for the dynamic system is studied based on the data driven method of nonlinear spectrum. An extraction method of nonlinear frequency spectrum feature is proposed by using one dimensional nonlinear output frequency response function. In order to improve timeliness, the variable step size adaptive identification algorithm is used to solve the nonlinear output frequency response function. The step size is changed according to estimating error so that convergence rate and steady state error are both considered. After obtained nonlinear frequency spectrum feature, the least square support vector machine classifier is used to fault identification. The fault diagnosis of hoisting equipment is researched, and experiments show that the proposed algorithm has the good high recognition rate that can fulfill the demand of online diagnosis.

引用

页码：168 / 171

页数：3

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