Multiple features extraction and selection for detection and classification of stator winding faults-Reference-Cited by-同舟云学术

Multiple features extraction and selection for detection and classification of stator winding faults

Published:2017-12-06 Issue:3 Volume:12 Page:339-346
ISSN:1751-8660
Container-title:IET Electric Power Applications
language:en
Short-container-title:IET Electric Power Applications

Author:

Haroun Smail¹,Seghir Amirouche Nait¹,Touati Said²

Affiliation:

1. Laboratory of Electrical and Industrial Systems (LSEI)Department of Electrical EngineeringU.S.T.H.B El AliaBP. 32, Bab Ezzouar, 16111AlgiersAlgeria

2. Electrical Engineering Department (DGE)Nuclear Research Center of Birine (CRNB) Bp 180Ain OusseraAlgeria

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-epa.2017.0457

Reference32 articles.

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2. Feature‐based fault diagnosis system of induction motors using vibration signal

3. Fault induction dynamic model, suitable for computer simulation: simulation results and experimental validation;Baccarini L.M.R.;Mech. Syst. Signal Process.,2010

4. Advance current monitoring techniques to detect and diagnosis the inter‐turn stator fault in three phase induction motor;Khalaf F.M.;Int. J. Eng. Sci.,2017

5. Review of condition monitoring of rotating electrical machines

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