Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection

In this paper, a suitable method for the on-line detection of the airgap mixed eccentricity fault in a three-phase cage induction motor has been proposed. The method is based on a Motor Current Signature Analysis (MCSA) approach, a technique that is often used for an induction motor conditi...

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Main Authors: Reljić Dejan, Tomić Josif, Kanović Željko
Format: Article
Language:English
Published: Faculty of Technical Sciences in Cacak 2015-01-01
Series:Serbian Journal of Electrical Engineering
Subjects:
Online Access:http://www.doiserbia.nb.rs/img/doi/1451-4869/2015/1451-48691501017R.pdf
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spelling doaj-1782f11e4ef24595b09a993348e06fae2020-11-24T21:03:20ZengFaculty of Technical Sciences in CacakSerbian Journal of Electrical Engineering1451-48692217-71832015-01-01121173210.2298/SJEE1501017R1451-48691501017RApplication of the Goertzel’s algorithm in the airgap mixed eccentricity fault detectionReljić Dejan0Tomić Josif1Kanović Željko2Faculty of Technical Sciences, Novi SadFaculty of Technical Sciences, Novi SadFaculty of Technical Sciences, Novi SadIn this paper, a suitable method for the on-line detection of the airgap mixed eccentricity fault in a three-phase cage induction motor has been proposed. The method is based on a Motor Current Signature Analysis (MCSA) approach, a technique that is often used for an induction motor condition monitoring and fault diagnosis. It is based on the spectral analysis of the stator line current signal and the frequency identification of specific components, which are created as a result of motor faults. The most commonly used method for the current signal spectral analysis is based on the Fast Fourier transform (FFT). However, due to the complexity and memory demands, the FFT algorithm is not always suitable for real-time systems. Instead of the whole spectrum analysis, this paper suggests only the spectral analysis on the expected airgap fault frequencies employing the Goertzel’s algorithm to predict the magnitude of these frequency components. The method is simple and can be implemented in real-time airgap mixed eccentricity monitoring systems without much computational effort. A low-cost data acquisition system, supported by the LabView software, has been used for the hardware and software implementation of the proposed method. The method has been validated by the laboratory experiments on both the line-connected and the inverter-fed three-phase fourpole cage induction motor operated at the rated frequency and under constant load at a few different values. In addition, the results of the proposed method have been verified through the motor’s vibration signal analysis. [Projekat Ministarstva nauke Republike Srbije, br. III42004]http://www.doiserbia.nb.rs/img/doi/1451-4869/2015/1451-48691501017R.pdfinduction motorAirgap mixed eccentricityMCSAGoertzel’s algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Reljić Dejan
Tomić Josif
Kanović Željko
spellingShingle Reljić Dejan
Tomić Josif
Kanović Željko
Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection
Serbian Journal of Electrical Engineering
induction motor
Airgap mixed eccentricity
MCSA
Goertzel’s algorithm
author_facet Reljić Dejan
Tomić Josif
Kanović Željko
author_sort Reljić Dejan
title Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection
title_short Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection
title_full Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection
title_fullStr Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection
title_full_unstemmed Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection
title_sort application of the goertzel’s algorithm in the airgap mixed eccentricity fault detection
publisher Faculty of Technical Sciences in Cacak
series Serbian Journal of Electrical Engineering
issn 1451-4869
2217-7183
publishDate 2015-01-01
description In this paper, a suitable method for the on-line detection of the airgap mixed eccentricity fault in a three-phase cage induction motor has been proposed. The method is based on a Motor Current Signature Analysis (MCSA) approach, a technique that is often used for an induction motor condition monitoring and fault diagnosis. It is based on the spectral analysis of the stator line current signal and the frequency identification of specific components, which are created as a result of motor faults. The most commonly used method for the current signal spectral analysis is based on the Fast Fourier transform (FFT). However, due to the complexity and memory demands, the FFT algorithm is not always suitable for real-time systems. Instead of the whole spectrum analysis, this paper suggests only the spectral analysis on the expected airgap fault frequencies employing the Goertzel’s algorithm to predict the magnitude of these frequency components. The method is simple and can be implemented in real-time airgap mixed eccentricity monitoring systems without much computational effort. A low-cost data acquisition system, supported by the LabView software, has been used for the hardware and software implementation of the proposed method. The method has been validated by the laboratory experiments on both the line-connected and the inverter-fed three-phase fourpole cage induction motor operated at the rated frequency and under constant load at a few different values. In addition, the results of the proposed method have been verified through the motor’s vibration signal analysis. [Projekat Ministarstva nauke Republike Srbije, br. III42004]
topic induction motor
Airgap mixed eccentricity
MCSA
Goertzel’s algorithm
url http://www.doiserbia.nb.rs/img/doi/1451-4869/2015/1451-48691501017R.pdf
work_keys_str_mv AT reljicdejan applicationofthegoertzelsalgorithmintheairgapmixedeccentricityfaultdetection
AT tomicjosif applicationofthegoertzelsalgorithmintheairgapmixedeccentricityfaultdetection
AT kanoviczeljko applicationofthegoertzelsalgorithmintheairgapmixedeccentricityfaultdetection
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