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Title: Discrimination of Electrical Motor Faults in Thermal Images by using First-order Statistics and Classifiers
Authors: Sakallı, Gönül
Koyuncu, Hasan
Keywords: electrical fault
fault classification
first-order statistics
image analysis
induction motor
thermal image
Fault detection
Image classification
Induction motors
Infrared devices
Nearest neighbor search
Support vector machines
Camera images
Electrical equipment
Electrical faults
Fault classification
First-order statistics
Inductions motors
Random forests
Thermal camera
Thermal images
Decision trees
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Fault detection and classification of an electrical equipment is a significant subject concerning the continuity of efficient working and necessary tasks. The heat concept creates a stimulating effect in case of failure among the electrical equipment. For this reason, thermal camera images can be functional and are used to detect the malfunctions. In this paper, thermal camera images are utilized to detect 11 different conditions of induction motors that are 8 different short-circuit faults of stator windings, rotor failure, cooling fan failure, and no-load. First-order statistics (FOS) are considered to obtain the discriminative information among the thermal images. The classification unit of model is specified examining five efficient algorithms that are neural networks (NN), k-nearest neighbors (k-NN), random forest (RF), logistic regression (LR), and support vector machines (SVM). In the experiments, 10-fold cross validation is chosen as the test method, and four metrics (accuracy, specificity, sensitivity, AUC) are considered to evaluate the performance. Consequently, the best accuracy of 97.29% is observed by k-NN and RF techniques. In a detailed examination, it is revealed that the most qualified technique rises as RF for the proposed model by considering the accuracy and AUC rates. © 2022 IEEE.
Description: 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022 -- 9 June 2022 through 11 June 2022 -- 180434
ISBN: 9781665468350
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections

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