自动化学报2017，Vol.43Issue(9)：1580-1587,8.DOI:10.16383/j.aas.2017.c160676
基于D-S融合的混合专家知识系统故障诊断方法
A Fault Diagnosis Approach by D-S Fusion Theory and Hybrid Expert Knowledge System
摘要
Abstract
There are various types of process knowledge and multiple uncertainties in complex process industry.To address these issues,a fault diagnosis approach which employs D-S knowledge fusion and hybrid knowledge system is proposed.Based on the types of available information,we establish different expert knowledge systems and present uncertainty reasoning respectively.By analyzing the characteristics of the current available data,adaptive weights are calculated for different expert knowledge systems.Then D-S evidence theory is utilized for conclusion fusion.Not only the expert experience knowledge but also a large amount of accumulated data is utilized in this method,which improves the utilization rate of information.The fault diagnosis accuracy for uncertainty systems are increased by the use of D-S conclusion fusion.The proposed method is then applied to fault diagnosis of a thickener in a hydrometallurgy process and satisfactory diagnosis results are achieved.关键词
混合知识系统/自适应权重/D-S证据理论/信息融合/浓密过程Key words
Hybrid expert knowledge system/adaptive weight/D-S evidence theory/information fusion/thickener引用本文复制引用
袁杰,王福利,王姝,赵露平..基于D-S融合的混合专家知识系统故障诊断方法[J].自动化学报,2017,43(9):1580-1587,8.基金项目
国家自然科学基金(61533007),辽宁省科学技术计划项目(2015020051),中央高校基础科研业务费(N160404007)资助 Supported by National Natural Science Foundation of China (61533007),Liaoning Science and Technology Project (2015020051),and Fundamental Research Funds for the Central Universities (N160404007) （61533007）
