Fault diagnosis of machines based on D-S evidence theory. Part 1: D-S evidence theory and its improvement
Fault diagnosis of machines based on D-S evidence theory. Part 1: D-S evidence theory and its improvement
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DOI：
10.1016/j.patrec.2005.08.025
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发表时间：
2006-04-01
影响因子：
5.1
通讯作者：
Zuo, MJ
中科院分区：
文献类型：
--
作者：
Fan, XF;Zuo, MJ
本文通过引入模糊隶属度函数、重要性指标对传统D-S证据理论进行改进。和冲突因子，以解决D-S证据理论在实际应用中的证据充分性、证据重要性和证据冲突等问题。提出了基于改进D-S证据理论的新决策规则。实例表明，改进的D-S证据理论比传统的D-S证据理论能更好地融合多源信息进行故障诊断。(c)2005 Elsevier B. V.保留所有权利。
In this paper, conventional D-S evidence theory is improved through the introduction of fuzzy membership function, importance index. and conflict factor in order to address the issues of evidence sufficiency, evidence importance, and conflicting evidences in the practical application of D-S evidence theory. New decision rules based on the improved D-S evidence theory are proposed. Examples are given to illustrate that the improved D-S evidence theory is better able to perform fault diagnosis through fusing multi-source information than conventional D-S evidence theory. (c) 2005 Elsevier B.V. All rights reserved.