Literature DB >> 33919618

Ventilation Diagnosis of Angle Grinder Using Thermal Imaging.

Adam Glowacz1.   

Abstract

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 (TRAG) was in the range of 98.5-100%. The presented technique is efficient for fault diagnosis of electrical devices and electric power tools.

Entities:  

Keywords:  angle grinder; diagnosis; fault detection; image processing; power tool; thermal images

Year:  2021        PMID: 33919618     DOI: 10.3390/s21082853

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  11 in total

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Journal:  Sensors (Basel)       Date:  2022-05-20       Impact factor: 3.847

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Authors:  Juncheng Guo; Yuyan Wu; Lizhi Chen; Shangbin Long; Daqi Chen; Haibing Ouyang; Chunliang Zhang; Yadong Tang; Wenlong Wang
Journal:  Biomed Eng Online       Date:  2022-06-15       Impact factor: 3.903

3.  Non-GDANets: Sports small object detection of thermal images with Non-Glodal decoupled Attention.

Authors:  Jia Zhao; Bingfei Mao; Hengran Meng; Liping Wu; Jingpeng Li
Journal:  PLoS One       Date:  2022-07-06       Impact factor: 3.752

4.  Computer-Aided Detection of COVID-19 from CT Images Based on Gaussian Mixture Model and Kernel Support Vector Machines Classifier.

Authors:  Ahmet Saygılı
Journal:  Arab J Sci Eng       Date:  2021-10-07       Impact factor: 2.807

5.  Artificial Intelligence for Classifying and Archiving Orthodontic Images.

Authors:  Shihao Li; Zizhao Guo; Jiao Lin; Sancong Ying
Journal:  Biomed Res Int       Date:  2022-01-27       Impact factor: 3.411

6.  Deploying Machine Learning Techniques for Human Emotion Detection.

Authors:  Ali I Siam; Naglaa F Soliman; Abeer D Algarni; Fathi E Abd El-Samie; Ahmed Sedik
Journal:  Comput Intell Neurosci       Date:  2022-02-02

7.  Micro Learning Support Vector Machine for Pattern Classification: A High-Speed Algorithm.

Authors:  Yu Yan; Yiming Wang; Yiming Lei
Journal:  Comput Intell Neurosci       Date:  2022-08-03

8.  E-GCS: Detection of COVID-19 through classification by attention bottleneck residual network.

Authors:  T Ahila; A C Subhajini
Journal:  Eng Appl Artif Intell       Date:  2022-09-20       Impact factor: 7.802

9.  Improved Support Vector Machine Enabled Radial Basis Function and Linear Variants for Remote Sensing Image Classification.

Authors:  Abdul Razaque; Mohamed Ben Haj Frej; Muder Almi'ani; Munif Alotaibi; Bandar Alotaibi
Journal:  Sensors (Basel)       Date:  2021-06-28       Impact factor: 3.576

10.  Experimental Investigation and Fault Diagnosis for Buckled Wet Clutch Based on Multi-Speed Hilbert Spectrum Entropy.

Authors:  Jiaqi Xue; Biao Ma; Man Chen; Qianqian Zhang; Liangjie Zheng
Journal:  Entropy (Basel)       Date:  2021-12-20       Impact factor: 2.524

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