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Ventilation Diagnosis of Angle Grinder Using Thermal Imaging

The paper presents an analysis and classification method to evaluate the working condition of angle grinders by means of infrared (IR) thermography and IR image processing. An innovative method called BCAoMID-F (Binarized Common Areas of Maximum Image Differences—Fusion) is proposed in this paper. T...

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Detalles Bibliográficos
Autor principal: Glowacz, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072699/
https://www.ncbi.nlm.nih.gov/pubmed/33919618
http://dx.doi.org/10.3390/s21082853
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author Glowacz, Adam
author_facet Glowacz, Adam
author_sort Glowacz, Adam
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description The paper presents an analysis and classification method to evaluate the working condition of angle grinders by means of infrared (IR) thermography and IR image processing. An innovative method called BCAoMID-F (Binarized Common Areas of Maximum Image Differences—Fusion) is proposed in this paper. This method is used to extract features of thermal images of three angle grinders. The computed features are 1-element or 256-element vectors. Feature vectors are the sum of pixels of matrix V or PCA of matrix V or histogram of matrix V. Three different cases of thermal images were considered: healthy angle grinder, angle grinder with 1 blocked air inlet, angle grinder with 2 blocked air inlets. The classification of feature vectors was carried out using two classifiers: Support Vector Machine and Nearest Neighbor. Total recognition efficiency for 3 classes (TR(AG)) was in the range of 98.5–100%. The presented technique is efficient for fault diagnosis of electrical devices and electric power tools.
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spelling pubmed-80726992021-04-27 Ventilation Diagnosis of Angle Grinder Using Thermal Imaging Glowacz, Adam Sensors (Basel) Article The paper presents an analysis and classification method to evaluate the working condition of angle grinders by means of infrared (IR) thermography and IR image processing. An innovative method called BCAoMID-F (Binarized Common Areas of Maximum Image Differences—Fusion) is proposed in this paper. This method is used to extract features of thermal images of three angle grinders. The computed features are 1-element or 256-element vectors. Feature vectors are the sum of pixels of matrix V or PCA of matrix V or histogram of matrix V. Three different cases of thermal images were considered: healthy angle grinder, angle grinder with 1 blocked air inlet, angle grinder with 2 blocked air inlets. The classification of feature vectors was carried out using two classifiers: Support Vector Machine and Nearest Neighbor. Total recognition efficiency for 3 classes (TR(AG)) was in the range of 98.5–100%. The presented technique is efficient for fault diagnosis of electrical devices and electric power tools. MDPI 2021-04-18 /pmc/articles/PMC8072699/ /pubmed/33919618 http://dx.doi.org/10.3390/s21082853 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Glowacz, Adam
Ventilation Diagnosis of Angle Grinder Using Thermal Imaging
title Ventilation Diagnosis of Angle Grinder Using Thermal Imaging
title_full Ventilation Diagnosis of Angle Grinder Using Thermal Imaging
title_fullStr Ventilation Diagnosis of Angle Grinder Using Thermal Imaging
title_full_unstemmed Ventilation Diagnosis of Angle Grinder Using Thermal Imaging
title_short Ventilation Diagnosis of Angle Grinder Using Thermal Imaging
title_sort ventilation diagnosis of angle grinder using thermal imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072699/
https://www.ncbi.nlm.nih.gov/pubmed/33919618
http://dx.doi.org/10.3390/s21082853
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