Published May 2011 | Version v1
Journal article

Dynamic eccentricity fault diagnosis in round rotor synchronous motors

  • 1. Center of Excellence on Applied Electromagnetic Systems, School of Electrical and Computer Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

Description

Research highlights: → We have presented a novel approach to detect dynamic eccentricity in round rotor synchronous motors. → We have introduced an efficient index based on processing torque using time series data mining method. → The stator current spectrum of the motor under different levels of fault and load are computed. → Winding function method has been employed to model healthy and faulty synchronous motors. -- Abstract: In this paper, a novel approach is presented to detect dynamic eccentricity in round rotor synchronous motors. For this, an efficient index is introduced based on processing developed torque using time series data mining (TSDM) method. This index can be utilized to diagnose eccentricity fault and its degree. The capability of this index to predict dynamic eccentricity is illustrated by investigation of load variation impacts on the nominated index. Stator current spectrum of the faulty synchronous motor under different loads and dynamic eccentricity degrees are computed. Effects of the dynamic eccentricity and load variation simultaneously are scrutinized on the magnitude of 17th and 19th harmonic components as traditional indices for eccentricity fault diagnosis in synchronous motors. Necessity signals and parameters for processing and feature extraction are evaluated by winding function method which is employed to model healthy and faulty synchronous motors.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2010.12.017

Additional details

Identifiers

DOI
10.1016/j.enconman.2010.12.017;
PII
S0196-8904(10)00561-3;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
52
Journal Issue
5
Journal Page Range
p. 2092-2097
ISSN
0196-8904
CODEN
ECMADL

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
42073876
Subject category
S42: ENGINEERING;
Descriptors DEI
ELECTRIC CURRENTS; FAULT TREE ANALYSIS; MOTORS; ROTORS; SIGNALS; STATORS; TIME-SERIES ANALYSIS; TORQUE; VARIATIONS
Descriptors DEC
CURRENTS; ENGINES; MATHEMATICS; STATISTICS; SYSTEM FAILURE ANALYSIS; SYSTEMS ANALYSIS

Optional Information

Copyright
Copyright (c) 2010 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.