Fault Diagnosis Expert System of Continuous Miner Hydraulic System

被引：3

作者：

Li, Xiaohuo ^{[1
]}

Tang, Renpeng ^{[1
]}

Sha, Yongdong ^{[1
]}

Bai, Shuaiwi ^{[1
]}

Zhang, Jinghui ^{[2
]}

机构：

[1] Liaoning Tech Univ, Mech Engn Coll, Fuxin 123000, Peoples R China

[2] Sany Heavy Equipment Co Ltd, Shenyang 110027, Peoples R China

来源：

HYDRAULIC EQUIPMENT AND SUPPORT SYSTEMS FOR MINING | 2013年 / 619卷

关键词：

Continuous miner; hydraulic system; neural network; fault diagnosis; expert system;

D O I：

10.4028/www.scientific.net/AMR.619.463

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In order to fine working states of a continuous miner hydraulic system, diagnose quickly and effectively its faults, reduce failure rate, save maintenance time and improve the reliability and productivity of a continuous miner, the GA-PSO hybrid optimization method of fuzzy neural network is used in fault diagnosis of a continuous miner hydraulic system in the paper, a intelligent fault diagnosis expert system of a hydraulic system is designed by means of taking VC 6.0 as the programming platform, using SQL SERVER 2000 as database, embedding MATLAB7.1 in the internal. The system is simple in man-machine interface and good in man-machine conversation, capable of analyzing accurately and judging properly failures of a continuous miner hydraulic system.

引用

页码：463 / +

页数：2