Detection of short-circuits of dc motor using thermographic images, binarization and k-nn classifier

2Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Glowacz, A., Glowacz, A., & Glowacz, Z. (2017). Detection of short-circuits of dc motor using thermographic images, binarization and k-nn classifier. Tehnicki Vjesnik, 24(4), 1013–1018. https://doi.org/10.17559/TV-20150924194102

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free