Intelligent Fault Detection and Diagnostics System on Rule-based Neural Network Approach

被引：3

作者：

Arseniev, Dmitry G. ^{[1
]}

Lyubimov, Boris E. ^{[2
]}

Shkodyrev, Viacheslav P. ^{[2
]}

机构：

[1] State Polytech Univ, St Petersburg, Russia

[2] Dis Int Sys Dept, State Polytech Univ, St Petersburg, Russia

来源：

2009 IEEE CONTROL APPLICATIONS CCA & INTELLIGENT CONTROL (ISIC), VOLS 1-3 | 2009年

关键词：

D O I：

10.1109/CCA.2009.5281003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Modern industrial systems can't exist without fault detection and diagnostics subsystem. Creation of such subsystem becomes a challenging task. Often it's more difficult than creation of the rest system's parts. This paper provides an approach for building fault detection and diagnostics system based on artificial neural networks, automatic training method for such systems and investigates different aspects of this method.

引用

页码：1815 / +

页数：2