Asenkron Motor Arıza Tespitinde Akım Uzay Örüntü Tanıma Sisteminin Kullanılması

Son on yılda, karmaşık dinamik sistemlerin sürekli olarak izlenmesi, çeşitli mühendislik alanlarında giderek daha önemli bir konu haline gelmiştir. Bu çalışmada, asenkron motorların sürekli izlenmesi için görsel tabanlı verimli invaryantlar kullanan bir model tanıma tabanlı sistem sunulmaktadır. Bu makalede anlatılan aşamalar, farklı arıza tiplerinin tanımlanmasına ve ayrıca bunlara karşılık gelen arıza şiddetinin belirlenmesine izin veren 3-boyutlu durum uzay örüntülerinin görüntü kompozisyonuna dayanmaktadır. Bu otomatik arıza tespit sistemi, zamanla değişenmotor akımları ile ilgilenir ve belirtilen üç-fazlı stator akımlarının tanımlanmasına dayanır. Önerilen metodun etkinliğini doğrulamak amacıylabenzetim sonuçları da sunulmuştur

Induction Motor Fault Detection Using Current Space Pattern Recognition

Over the last decade, continuous monitoring of complex dynamic systems has become an increasingly important issue in various engineering disciplines. In this study, a model recognition based system using visual based efficient in variants is presented for continuous monitoring of induction motors. The steps described in this article are based on the image description of the 3-dimensional state space patterns, which allows identification of different types of faults and also their corresponding fault severity. This automatic fault detection system deals with time-varying motor currents and is based on the identification of the specified three-phase stator currents. Various simulations results are also presented to confirm the effectiveness of the proposed method

Keywords:

Induction Motor, Fault Diagnosis Curren tState Space Pattern Recognition,

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