A comparison between MLP NN and RBF NN techniques for the detection of stator inter-turn fault of an induction motor

Author

Dash, Rudra Narayan ; Subudhi, Bidyadhar ; Das, Susmita

Author_Institution

Dept. of Electr. Eng., Nat. Inst. of Technol., Rourkela, India

fYear

2010

fDate

27-29 Dec. 2010

Firstpage

251

Lastpage

256

Abstract

This paper presents a comparison between multilayer perceptron neural network (MLP NN) and Radial basis feedforward neural network (RBF NN) techniques for the detection of inter-turn short circuit fault in stator winding of an induction motor. The fault location process is based on the monitoring the three phase shifts between the line current and the phase voltage of the induction machine.

Keywords

induction motors; multilayer perceptrons; power engineering computing; stators; MLP NN; RBF NN techniques; circuit fault; induction motor; stator inter turn fault; stator winding; Artificial neural networks; Conferences; Induction motors; Industrial electronics; Service robots; Stators; Fault Diagnosis; Induction Motor; Interturn short circuit fault; Multilayer Perceptron Neural Network; Radial Basis Function Neural Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, Control & Robotics (IECR), 2010 International Conference on

Conference_Location

Orissa

Print_ISBN

978-1-4244-8544-4

Type

conf

DOI

10.1109/IECR.2010.5720163

Filename

5720163

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2609114