| Literature DB >> 33919618 |
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