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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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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 |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-8072699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT glowaczadam ventilationdiagnosisofanglegrinderusingthermalimaging |