Learning Machine Design for Mechanic Fault Diagnosis Expert System

被引：0

作者：

Yu, YiFan ^{[1
]}

Liu, XiaoLing ^{[1
]}

Chen, WenBin ^{[1
]}

机构：

[1] Southwest Petr Univ, Sch Comp Sci, Chengdu, Peoples R China

来源：

ADVANCED RESEARCH ON ENGINEERING MATERIALS, ENERGY, MANAGEMENT AND CONTROL, PTS 1 AND 2 | 2012年 / 424-425卷

关键词：

fault diagnosis; expert system; rule; machine learning;

D O I：

10.4028/www.scientific.net/AMR.424-425.81

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

According to the features of fault diagnosis expert system, knowledge was expressed by applying production rule and certainty factor. What lead to incorrect knowledge was analyzed, and a certainty correction algorithm and rule discovery algorithm was proposed based on case studies. A learning machine of mechanic fault diagnosis expert system was designed and implemented by using C++ BUILDER 6.0. That provides technical support for noise control in substation.

引用

页码：81 / +

页数：2