Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier

In industrial processes electrical motors are serviced after a specific number of hours, even if there is a need for service. This led to the development of early fault diagnostic methods. Paper presents early fault diagnostic method of synchronous motor. This method uses acoustic signals generated...

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Main Author: Adam GLOWACZ
Format: Article
Language:English
Published: Institute of Fundamental Technological Research Polish Academy of Sciences 2014-06-01
Series:Archives of Acoustics
Subjects:
Online Access:https://acoustics.ippt.pan.pl/index.php/aa/article/view/817
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author Adam GLOWACZ
author_facet Adam GLOWACZ
author_sort Adam GLOWACZ
collection DOAJ
description In industrial processes electrical motors are serviced after a specific number of hours, even if there is a need for service. This led to the development of early fault diagnostic methods. Paper presents early fault diagnostic method of synchronous motor. This method uses acoustic signals generated by synchronous motor. Plan of study of acoustic signal of synchronous motor was proposed. Two conditions of synchronous motor were analyzed. Studies were carried out for methods of data processing: Line Spectral Frequencies and K-Nearest Neighbor classifier with Minkowski distance. Condition monitoring is useful to protect electric motors and mining equipment. In the future, these studies can be used in other electrical devices.
format Article
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publisher Institute of Fundamental Technological Research Polish Academy of Sciences
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series Archives of Acoustics
spelling doaj-art-1793700caf96479d8b7115f13d4e13452025-08-20T02:39:03ZengInstitute of Fundamental Technological Research Polish Academy of SciencesArchives of Acoustics0137-50752300-262X2014-06-0139210.2478/aoa-2014-0022Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor ClassifierAdam GLOWACZ0AGH University of Science and TechnologyIn industrial processes electrical motors are serviced after a specific number of hours, even if there is a need for service. This led to the development of early fault diagnostic methods. Paper presents early fault diagnostic method of synchronous motor. This method uses acoustic signals generated by synchronous motor. Plan of study of acoustic signal of synchronous motor was proposed. Two conditions of synchronous motor were analyzed. Studies were carried out for methods of data processing: Line Spectral Frequencies and K-Nearest Neighbor classifier with Minkowski distance. Condition monitoring is useful to protect electric motors and mining equipment. In the future, these studies can be used in other electrical devices.https://acoustics.ippt.pan.pl/index.php/aa/article/view/817acoustic signalpattern analysissynchronous motordiagnostics.
spellingShingle Adam GLOWACZ
Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier
Archives of Acoustics
acoustic signal
pattern analysis
synchronous motor
diagnostics.
title Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier
title_full Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier
title_fullStr Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier
title_full_unstemmed Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier
title_short Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier
title_sort diagnostics of synchronous motor based on analysis of acoustic signals with the use of line spectral frequencies and k nearest neighbor classifier
topic acoustic signal
pattern analysis
synchronous motor
diagnostics.
url https://acoustics.ippt.pan.pl/index.php/aa/article/view/817
work_keys_str_mv AT adamglowacz diagnosticsofsynchronousmotorbasedonanalysisofacousticsignalswiththeuseoflinespectralfrequenciesandknearestneighborclassifier