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. 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.

Automated summary

This paper introduces an analysis and classification method using infrared thermography and image processing to evaluate the working condition of angle grinders. A new method, BCAoMID-F, is proposed to extract features from thermal images of three angle grinders and achieved high recognition efficiency. The technique presented is effective for fault diagnosis of electrical devices and electric power tools.