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YAPAY SİNİR AĞI (YSA) KULLANARAK TİTREŞİM TABANLI MAKİNA DURUM İZLEMESİ VE HATA TEŞHİSİ

VIBRATION BASED MACHINERY HEALTH MONITORING AND FAULT DETECTION USING ARTIFICIAL NEURAL NETWORK (ANN)

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Abstract (2. Language): 
In this study, training set was composed using ISO-10816 which is the evaluation standards of medium-size machines and was applied for training of Artificial Neural Networks (ANN). ANN consist three layers which are an input layer, a hidden layer and an output layer. First data matrix which size is 720x9 was composed the table of ISO-10816 for the network training. Nevertheless a test matrix which is 200x5 sizes was composed. Training was tested by changing different types of hidden layers which were consisting of 5, 10, 15, 25, 50 and 75 neurons. Test results were compared with each others and the best performance was found. Back-Propagation was used in training. Suitability was determined with comparing result values and real table values.
Abstract (Original Language): 
Bu çalışmada titreşim analizi için “Orta Ölçekli Makinaların Titreşim Değerlendirme Standartları ISO-10816” tablosu kullanılarak oluşturulan eğitim seti, Yapay Sinir Ağını (YSA) eğitmek için kullanılmıştır. Üç katmanlı oluşturulan YSA ağını eğitmek için ISO-10816 tablosundan 720x9’luk veri matrisi, test için 200x5’lik veriye sahip bir matris kullanılmıştır. Eğitim, gizli katman hücre sayısı 5, 10, 15, 25, 50 ve 75 olan ağların her biri için ayrı ayrı gerçekleştirilmiştir. Birbirleriyle karşılaştırılarak en iyi sonucu veren ağ yapısı bulunmuştur. Eğitim için geri yayılım algoritması kullanılmıştır. Eğitimden sonra elde edilen çıkış değerleri gerçek tablo değerleriyle karşılaştırılarak, titreşim analizinde kullanılabilirliği saptanmıştır.

REFERENCES

References: 

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