Fault Diagnosis by Using Selective EnsembleLearning Based on Fisher criterion

摘要：

Faolt diagnosis on diesel engine is a difficult prroblem due t0 the complex structure of the engines and the presence of multi-excite sources．There have been previous attempts to solve this problem by using antifieial nenral networks and others methods．In this paper,a norel algorithm named FCSEN (Fisher Criteflon based Selective Ensemble)is proposed to improve diagnosis accuracy and efficiency． FCSEN is compared with the general case of bagging and GASEN,a baseline method,namely Genetic Algorithm Based Selective ENsemble,on UCl data sets．Then,FCSEN is used Io dial,nose the dieseI engine．Computational results show that FCSEN obtains higher accuracy than other several methods like bagging of neural neVvorks and GASEN．

关键词： Fault diagnosis Fisher criterion Selective ensemble learning Bagging Support vector machines component

作者: Liu Tianyu Zhang Xiangfeng Jiang Bin

作者单位: School of Electric Shanghai Dianji University Shanghai,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 351-354

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）