Equipment Condition Monitoring and Diagnosis System Based on Evidence Weight

被引：4

作者：

Yao, Xuemei ^{[1
]}

Li, Shaobo ^{[2
]}

Zhang, Ansi ^{[1
]}

机构：

[1] Guizhou Univ, Minist Educ, Key Lab Adv Mfg Technol, Guiyang 550025, Guizhou, Peoples R China

[2] Guizhou Univ, Sch Mech Engineer, Guiyang 550025, Guizhou, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ONLINE ENGINEERING | 2018年 / 14卷 / 02期

基金：

中国国家自然科学基金;

关键词：

data fusion; monitoring; evidence theory; intelligent diagnosis;

D O I：

10.3991/ijoe.v14i02.7731

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A system for monitoring and diagnosing the working conditions of equipment is developed in this study to ensure equipment safety and reliability. First, a perceptual model with four layers is designed. Original data are collected by sensors, and analyses are performed with intelligent algorithms. Decisions are then made and displayed on a screen in real time. Second, a method for monitoring equipment conditions is developed based on evidence weights. Basic probability assignment of evidence is corrected according to evidence and sensor weights, and an optimal fusion algorithm is selected by comparing an introduced threshold and a conflict factor. Third, the effectiveness and practicability of the algorithm are tested by simulating the monitoring and diagnosis of centrifugal pumps. Finally, the system is implemented to verify its validity.

引用

页码：143 / 154

页数：12

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