Deterministic Learning and Fault Diagnosis for Nonlinear Oscillation System

被引：1

作者：

Chen, Tianrui ^{[1
]}

Wang, Cong ^{[1
]}

机构：

[1] S China Univ Technol, Coll Automat, Guangzhou 510640, Guangdong, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

Fault detection and isolation; dynamic pattern recognition; deterministic learning; nonlinear oscillation systems;

D O I：

10.1109/WCICA.2008.4593508

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 diagnosis of faults is one of the important tasks in engineering systems. In this paper, based on the recent results on deterministic learning (DL) theory and rapid dynamical pattern recognition, a rapid fault diagnosis scheme is proposed for nonlinear oscillation systems. Firstly, a neural network bank for fault detection and isolation (FDI) is established through DL. Secondly, a mechanism for rapid FDI is presented, by which a fault occurred can be detected and isolated by patten recognition. Simulation studies are included to demonstrate the effectiveness of the proposed approach.

引用

页码：3654 / +

页数：2

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