Wavelet Transform and Autoregressive Model Parameter Features based Engine Fault Diagnosis System

Öz

Örüntü tanıma ve makine öğrenmesi başarılı sonuçlar sağlamasından dolayı popülerliğini giderek arttırmakta ve birçok alanda kullanılmaktadır. Bu çalışmada marka ve model farkı gözetmeksizin zamanlama kayışı ve vuruntu arızası ile normal çalışma durumlarına ait otomobil motor sesleri sınıflandırılmıştır. Önerilen yöntem iki saniyelik motor seslerinden sürekli dalgacık dönüşümü ve özbağlanım parametresi özniteliklerin k-en yakın komşuluk algoritması ile sınıflandırarak %91.8 oranında sınıflandırma doğruluğu elde etmiştir. Elde edilen sonuçlar önerilen yöntemin otomobil motor sesleri kullanılarak araçlarda meydana gelebilecek arızaları büyük oranda tespit edilebileceğini göstermiştir. Böylece, otomobil motorlarındaki arızanın erken tespiti mümkün olmakta, bu da olası kazaların ve büyük arızaların ortaya çıkmasının önüne geçmektedir. Ayrıca, önerilen yöntemin araç yetkili servislerine ve motor ustalarına rehberlik etmek ve zaman kazandırmak amaçlı da kullanılabileceği düşünülmektedir.

Anahtar Kelimeler

• Motor arızası
• Ses tanıma
• Öznitelik Çıkarma

Dalgacık Dönüşümü ve Özbağlanım Model Parametreleri Öznitelikleri ile Otomobil Motor Seslerinden Arıza Tespiti

Öz

Anahtar Kelimeler

• Motor arızası

Kaynakça

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