Stator current modeling of an induction motor for rotor faults diagnosis

التفاصيل البيبلوغرافية
العنوان: Stator current modeling of an induction motor for rotor faults diagnosis
المؤلفون: Azeddine Bendiabdellah, Noureddine Benouzza, Mohammed Khodja, Ahmed Hamida Boudinar
المصدر: 2016 IEEE International Power Electronics and Motion Control Conference (PEMC).
بيانات النشر: IEEE, 2016.
سنة النشر: 2016
مصطلحات موضوعية: Electric motor, Engineering, Vector control, business.industry, Squirrel-cage rotor, Stator, 020208 electrical & electronic engineering, 020206 networking & telecommunications, Control engineering, 02 engineering and technology, AC motor, Wound rotor motor, law.invention, Direct torque control, law, Control theory, 0202 electrical engineering, electronic engineering, information engineering, business, Induction motor
الوصف: In recent years, the diagnosis of electric motors appealed increasingly to signal processing methods. To develop these methods, it is necessary to have a reliable mathematical model of the physical signal to be processed, in our case the signal is the stator current. Unfortunately, often this stator current can only be obtained from an expensive measurement bench, or from a complex modelling of the electric motor. The aim of this paper is to model the induction motor stator current in the presence of a rotor fault to diagnose it. This model must take into account the effects of the presence of such a fault. In fact, the presence of the rotor fault is manifested by an eccentricity of the air gap and an oscillation of the load torque, which causes amplitude and phase modulations of the current. For this purpose, the impact of the severity of the rotor fault on these two types of modulations expressed in the studied mathematical model is also demonstrated in this paper work.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::ded1608b4803a782dcffa9afdd554e3c
https://doi.org/10.1109/epepemc.2016.7752146
رقم الأكسشن: edsair.doi...........ded1608b4803a782dcffa9afdd554e3c
قاعدة البيانات: OpenAIRE