Akademik Veri Yönetim Sistemi
7 th INTERNATIONAL CONGRESS ON ENGINEERING AND TECHNOLOGY MANAGEMENT, 16 Nisan 2022, ss.488-495
Abstract: Rotary electric machines are widely used in industry, energy production, renewable energy
sources and factories, mainly alternating current (AC) machines and direct current (DC) machines. Therefore, any scientific study that can be done on rotating electrical machines will contribute to industrialization. Although the rotating electric machines vary according to the manufacturers, the ones with the
same power are very similar to each other in terms of external appearance. In systems that require remote
control or monitoring with a screen, it is sometimes necessary to determine the type of rotating electrical
machine immediately. Label values may not be read on the screens or the label may remain outside the
camera dial while it is in operation. In this study, a deep learning (DL) method, a convolutional neural
network (CNN) model, was implemented in order to classify and detect rotating electrical machines
with only external appearance for such special cases. In the test results after the training of the model,
success was achieved with an accuracy rate of 87.5%. It has been observed that the use of the proposed
DL model in the classification and species detection of rotating electrical machines gives very successful
results.
Keywords: Rotary Electrical Machines, CNN, TL, DL, TL, Induction, DC, Synchronous