Coil pitch angles have an important place in the design of rotary electrical machines. Today, a significant amount of electrical energy in the sector is consumed by induction motors fed by PWM inverters. PWM inverters used in the feeding of asynchronous motors can cause the formation and increase of voltage and current harmonics. Similarly, another reason for the increase of harmonics is the stator winding structure and coil pitch. When the stator windings of induction motors are wound with shortened coil pitch, some low level harmonics can be suppressed. Therefore, determining the pitch angle of the coil can be considered an important step in induction motor design. In the design process, this stage can be handled by mathematical calculation, but the parameters of each motor can be different and therefore, current and voltage harmonics may also be different, so it is necessary to make separate calculations for each motor. In this study, in order to find a solution to this problem, the coil pitch angles of three-phase cage induction motors were estimated with support vector machines, a popular artificial intelligence method and classifier, and tested with a ten fold cross-validation technique. As a result, an SVM estimation model has been developed that can estimate the coil pitch angle with minimum error without the need for a mathematical model of an induction motor fed by a PWM inverter. The data used in the system have been obtained experimentally, all five three-phase cage asynchronous motors used in the experiment are identical, have the same coil lengths, have windings wound at different coil pitch, all have the same power, and finally all are four poles. This study is also a unique source of information and application that can be used in active filter design, motor design, and winding design.
Anahtar Kelimeler: Coil Pitches Angles, Induction Motors, Support Vector Machines
|
