SUPPORT VECTOR MACHINES FOR STATOR GROOVE SHAPE DETECTION IN ROTARY ELECTRIC MACHINES
7 th INTERNATIONAL CONGRESS ON ENGINEERING AND TECHNOLOGY MANAGEMENT, 16 Nisan 2022, ss.480-488, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Sayfa Sayıları: ss.480-488
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Bursa Uludağ Üniversitesi Adresli: Hayır
Özet
Abstract: Electrical machines are magnetic and electromechanical systems that work entirely with magnetism. Losses due to magnetism in rotating electrical machines affect the working performance. The
most difficult to intervene and the most neglected magnetic leakages in rotating electrical machines are
the groove leakage fields in the stator groove air gap. The stator groove shapes and the placement of the
stator coil edges in the grooves are important factors that directly affect the groove leakage fluxes and
thus the motor power and performance. Therefore, groove leakage should also be taken into account
when deciding on the stator groove shapes while designing rotating electrical machines. In this study, a
multi-classification detection study, which can be useful in deciding the groove shape by considering
the groove leaks, was carried out using the support vector machines (SVM) model. As a result of the
test with five-fold cross-validation, it was understood that the SVM method could contribute to the stator
slot selection and design of rotary electric machines.
Keywords: SVM, ML, Groove, Leakage Field