张博科技论文写作.ppt
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1、Engine fault diagnosis based on multi-sensor information fusion using DempsterShafer evidence theory,2班 张,期刊名称:INFORMATION FUSION,作者单位:加拿大安大略省滑铁卢大学,ScienceDirect: 荷兰Elsevier Science公司出版的期刊,是世界上公认的高品位学术期刊,影响因子,Engine fault diagnosis based on multi-sensor information fusion using DempsterShafer eviden
2、ce theory 基于Dempster-Shafer证据理论的多传感器信息融合的发动机故障诊断 Abstract: Engine diagnostics is a typical multi-sensor fusion problem. 发动机诊断是一种典型的多传感器融合的问题。 It involves the use of multi-sensor information such as vibration,sound, pressure and temperature, to detect and identify engine faults. 它涉及到使用多传感器信息如振动、声音、压力
3、和温度用以检测和识别发动机故障。,From the viewpoint of evidence theory, information obtained from each sensor can be considered as a piece of evidence, and as such, multi-sensor based engine diagnosis can be viewed as a problem of evidence fusion. 从证据理论的观点来看,从每个传感器获得的信息可以被视为一项证据,正因为如此,基于发动机诊断的多传感器可以被看作是证据融合的问题。 In
4、this paper we investigate the use of DempsterShafer evidence theory as a tool for modeling and fusing multi-sensory pieces of evidence pertinent to engine quality. 在本文中,我们讨论使用D-S证据理论作为建模工具并且融合多传感器证据和发动机质量。,We present a preliminary review of Evidence Theory and explain how the multi-sensor engine dia
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