Tehnički vjesnik, Vol. 24 No. 4, 2017.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20150924194102
Detection of short-circuits of dc motor using thermographic images, binarization and K-NN classifier
Adam Glowacz
orcid.org/0000-0003-0546-7083
; AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering, al. A. Mickiewicza 30, 30-059 Krakow, Poland
Andrzej Glowacz
; AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering, al. A. Mickiewicza 30, 30-059 Krakow, Poland
Zygfryd Glowacz
; AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering, al. A. Mickiewicza 30, 30-059 Krakow, Poland
Sažetak
Many fault diagnostic methods have been developed in recent years. One of them is thermography. It is a safe and non-invasive method of diagnostic. Fault diagnostic method of incipient states of Direct Current motor was described in the article. Thermographic images of the commutator of Direct Current motor were used in an analysis. Two kinds of thermographic images were analysed: thermographic image of commutator of healthy DC motor, thermographic image of commutator of DC motor with shorted rotor coils. The analysis was carried out for image processing methods such as: extraction of magenta colour, binarization, sum of vertical pixels and sum of all pixels in the image. Classification was conducted for K-Nearest Neighbour classifier. The results of analysis show that the proposed method is efficient. It can be also used for diagnostic purposes in industrial plants.
Ključne riječi
diagnostics; DC motor; K-NN classifier; maintenance; thermographic images
Hrčak ID:
185441
URI
Datum izdavanja:
31.7.2017.
Posjeta: 1.929 *