Artificial neural network model for prediction of tool tip temperature and analysis

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Tarih

2018

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Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Technological improvements put computer systems in the center of our life and various scientific disciplines. These can range from controlling a device in our home to public institutions and the industry. One of these disciplines is a sub-area in mechanical engineering called machining is concerned with not only mechanical systems but also computer aided systems. Artificial Neural Networks -an area of artificial intelligence- which is concerned with learning and decision making of computers is a field that scientists are very interested in. In this study, an Artificial Neural Network system was designed for predicting the temperature at the tool tip in the machining process. In the metal cutting process, tool tip temperature is one of the conditions that must be identified, analyzed and monitored. For this purpose, an ANN model was developed to determine the tool tip temperature in the turning process. In the designed ANN model, parameters consisting of three inputs and one output were used. The three input variables were rake angle (?-o), approaching angle (-o), feedrate (fmm/rev) respectively. The output parameter was the tool tip temperature (T-0C). The most appropriate model was determined according to Mean Squared Error ratio. In the test phase of the Artificial Neural Network, the smallest Mean Squared Error was obtained with the Artificial Neural Network topology formed as 3-4-1. In this Artificial Neural Network model, calculations were Mean Squared Error0.00144, R20.9956 (absolute fraction of variance) in the training phase and Mean Squared Error0.00231, R20.9954 in the test phase. The results show that the designed Artificial Neural Network model can be used for predicting and analyzing tool tip temperature

Açıklama

Anahtar Kelimeler

Bilgisayar Bilimleri, Yapay Zeka, Artificial Neural Network, Prediction Mode

Kaynak

International Journal of Intelligent Systems and Applications in Engineering

WoS Q Değeri

Scopus Q Değeri

Cilt

6

Sayı

1

Künye

Tasdemir, S. (2018). Artificial Neural Network Model for Prediction of tool Tip Temperature and Analysis. International Journal of Intelligent Systems and Applications in Engineering, 6(1), 92-96.