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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 130
Paper Published : 2388
No. of Authors : 6802
  Journal Paper


Paper Title :
Robust Features For Load Independent Machine Fault Diagnosis Using Feature Selection

Author :Anandaraj G, Anupriyanka P, Aswin Krishnan, Sri Saravanan J B, Sumangala V, Gopinath R, Santhosh Kumar C

Article Citation :Anandaraj G ,Anupriyanka P ,Aswin Krishnan ,Sri Saravanan J B ,Sumangala V ,Gopinath R ,Santhosh Kumar C , (2014 ) " Robust Features For Load Independent Machine Fault Diagnosis Using Feature Selection " , International Journal of Mechanical and Production Engineering (IJMPE) , pp. 36-39, Volume-2,Issue-9

Abstract : Machine Fault Diagnosis (MFD) is of vital importance in aerospace applications that consist of complex systems. In this paper, load independent MFD on a three phase 3kVA synchronous generator has been described. Statistical features were extracted in both time and frequency domains. Chi squared algorithm was used for feature selection and classification was done using C4.5 algorithm. Voltage and current analyses were performed in both domains, and a set of robust features were identified.

Type : Research paper

Published : Volume-2,Issue-9


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