计算机与数字工程2019，Vol.47Issue(3)：543-549,7.DOI:10.3969/j.issn.1672-9722.2019.03.012
基于粗糙集和改进D-S证据理论的故障诊断方法
A Fault Diagnosis Method Based on Rough Set and Improved D-S Evidence Theory
摘要
Abstract
In order to solve data problems with redundant,conflict and uncertainty in monitoring large equipment,a data fu?sion equipment monitoring method is proposed through the combination of rough set and improved D-S evidence theory. According to the decision table after the attribute reduction using rough set,the rule strength of attributes can be calculated,thus the basic probability assignment values are objectively determined. Meanwhile,the relative weights of evidences are extracted from the deci?sion importance of attributes,the Dempster's combination rules is then modified in the light of the determined weights. The proposed method remedies the deficiencies of D-S theory in evidence conflict and subjective determination of the basic probability assign?ment. A simulation of fault diagnosing method with application to the ozone generator is carried out using the proposed method,the results show that the accuracy of the proposed method is proved,and the uncertainty of the results is obviously reduced comparing with classic analyzing methods,which concludes that the proposed method has a practical significance in fault diagnosis.关键词
粗糙集/D-S证据理论/数据融合/故障诊断/多传感器/臭氧发生器Key words
rough sets/D-S evidence theory/data fusion/fault diagnosis/multisensor/ozone generator分类
信息技术与安全科学引用本文复制引用
丁晗,侯瑞春,丁香乾..基于粗糙集和改进D-S证据理论的故障诊断方法[J].计算机与数字工程,2019,47(3):543-549,7.基金项目
国家科技支撑计划基金项目(编号:2015BAF04B02)资助. （编号:2015BAF04B02）
