Open AccessInter‐turn short‐circuit assessment of DC motor used in railway locomotive
Author(s) -
Kar Ray Debopoma,
Chattopadhyay Surajit,
DasSharma Kaushik,
Sengupta Samarjit
Publication year - 2018
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/iet-epa.2018.0047
Subject(s) - kurtosis , traction (geology) , electromagnetic coil , dc motor , fault (geology) , control theory (sociology) , traction motor , engineering , short circuit , rectifier (neural networks) , root mean square , skewness , mathematics , automotive engineering , algorithm , computer science , electrical engineering , voltage , statistics , mechanical engineering , artificial intelligence , stochastic neural network , control (management) , seismology , recurrent neural network , artificial neural network , geology
This study deals with inter‐turn short‐circuit assessment of DC traction motors used in railway locomotives. This has been done by analysing input current spectra of rectifier unit feeding the traction motor. The analysis includes multi‐resolution analysis and discrete wavelet transform (DWT) of current spectra to calculate approximate and detailed coefficients and then to evaluate the skewness, kurtosis and root mean square values. Variation of those values with respect to percentage of inter‐turn short circuit at different DWT decomposition levels has been observed. A number of curves have been chosen for fault assessment based on the observations. Deviations from normal condition have also been observed by logic matrix. Depending on the features obtained, normal and different percentages of short in the traction motor windings have been classified and an algorithm has been proposed accordingly. Case study has been carried out on Indian WAP4 locomotive, wherein the input current to the rectifiers has been analysed and efficacy of the proposed algorithm has been validated. If for the locomotives, these parameters are monitored, percentage of inter‐turn short circuit in the winding may be assessed far before massive system degradation occurs.