Data Fusion Algorithm Based on D-S Evidential Theory and Its Application for Circuit Fault Diagnosis

ZHU Da-qi; YU Sheng-lin

您当前的位置：

首页 >

文章列表页 >

Data Fusion Algorithm Based on D-S Evidential Theory and Its Application for Circuit Fault Diagnosis

更新时间：2025-07-16

- Data Fusion Algorithm Based on D-S Evidential Theory and Its Application for Circuit Fault Diagnosis
- Acta Electronica Sinica Vol. 30, Issue 2, Pages: 221-223(2002)
- 作者机构：
  
  1. 南京航空航天大学测试工程系,江苏,南京,210016
  2. 安徽工业大学工业自动化系,安徽,马鞍山,243002
  3. 南京航空航天大学测试工程系江苏南京,210016
  4. 安徽工业大学工业自动化系安徽马鞍山,243002
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18TP274
- Published：2002
- 稿件说明：
移动端阅览
ZHU Da-qi, YU Sheng-lin. Data Fusion Algorithm Based on D-S Evidential Theory and Its Application for Circuit Fault Diagnosis[J]. Acta Electronica Sinica, 2002, 30(2): 221-223.
DOI：

ZHU Da-qi, YU Sheng-lin. Data Fusion Algorithm Based on D-S Evidential Theory and Its Application for Circuit Fault Diagnosis[J]. Acta Electronica Sinica, 2002, 30(2): 221-223. DOI：

摘要

本文在D-S证据理论的基础上

结合模糊集合论

给出了电子电路故障定位的多传感器数据融合方法.通过测试电路中的被诊断元件的工作温度和工作电压两个物理量

得出D-S证据理论中两传感器对各待诊断元件的信度函数分配

再利用D-S联合规则得到融合后的信度函数分配

从而确定故障元件

并通过单传感器诊断结果与融合诊断结果比较

说明多传感器融合的优越性.

Abstract

A data fusion method for circuit fault diagnosis based on D-S evidential theory and fuzzy logical theory is presented.By measuring the temperature and voltage of circuit component

the belief function assignment of two sensors to circuit component is gotten

and the fusion belief function assignment is gotten by using D-S rule

and fault component is found.By comparing the diagnosis results based on separate original data and fused data respectively

it is shown that the latter is more accurate than the former in the circuit fault recognition.

关键词

Keywords

references

Views

3135

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Multiple Classifier Fault Diagnosis System Based on Dynamic Weight

A CatBoost Optimization-Based Fault Diagnosis Model for Photovoltaic Arrays

Multi-Dimensional Dynamic Topology Learning Graph Convolution for Skeleton-Based Action Recognition

Zero Sample Fault Diagnosis Based on Transfer Learning

Fault Diagnosis of Laminar Cooling Roller Motor Based on Morphological Combination Patterns Mining of Multi-Current Features

Related Author

HUANG Jiang-tao

WANG Ming-hui

LI Wu-jing

GU Bo

PENG Zi-ran

XU Huai-shun

XIAO Shen-ping

LUO Hui-lan

Related Institution

College of Computer and Information Engineering,Guangxi Teachers Education University

Key Lab of Scientific Computing and Intelligent Information Processing in Universities of Guangxi

College of Computer Science, Sichuan University

College of Computer and Information EngineeringGuangxi Teachers Education UniversityNanningGuangxi 530023China

Key Lab of Scientific Computing and Intelligent Information Processing in Universities of GuangxiNanningGuangxi 530023China

⁰