DocumentCode :
3446720
Title :
Importance analysis on components in railway rolling stock based on fuzzy weighted logarithmic least square method
Author :
Wang, Lingzhi ; Xu, Yugong ; Zhang, Jiadong
Author_Institution :
Sch. of Mech., Electron. & Control Eng., Beijing Jiaotong Univ., Beijing, China
Volume :
1
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
175
Lastpage :
179
Abstract :
Aiming at the problems that the components in railway rolling stock are complex, highly correlated and difficult to make importance evaluation by traditional method, the importance evaluation index of components in railway rolling stock is established on the basis of the decision of the main factors which influence the importance. A model based on the triangular fuzzy number (TFN) weighted logarithmic least square method is given and corresponding evaluation process is described. The weight of the main factors is determined and the importance analysis on components in railway rolling stock is done with the importance evaluation index. The result indicates that the model can synthesize expert group opinions adequately and combine subjective analysis with quantitative analysis effectively. The calculation program for common use has been developed. It is shown by the instance that this method is convenient and effective. Based on the research the proposed method is given for deciding the concrete maintenance mode according to the components importance.
Keywords :
fuzzy set theory; least squares approximations; number theory; principal component analysis; railway rolling stock; components importance analysis; fuzzy weighted logarithmic least square method; quantitative analysis; railway rolling stock; triangular fuzzy number; Couplers; Maintenance engineering; Vehicles; importance analysis; influencing factor; least square method; triangular fuzzy number (TFN);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658651
Filename :
5658651
Link To Document :
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