Prediction of Vibrations & Cutting Force of Single Point Cutting Tool in Turning by Using Artificial Neural Network

Professorial Dissertation from the year 2015 in the subject Engineering - Artificial Intelligence, language: English, abstract: The objective of this work is to develop a model to simulate the vibrational effects of rotating machine parts on the single point cutting tool. In this paper experimental studies were performed on turning process & vibration is measured with the help of accelerometer along with a device called as Fast Fourier Transformer (FFT) Analyzer. The vibration of single point cutting tool is sensed by accelerometer located on the tool-post of lathe machine. The accelerometer will send the sensed vibration to FFT Analyzer which can be convert the sensed data by using accelerometer shown in PC such as frequency, Amplitude, displacement & so on. The obtained experimental data given to an Artificial Neural Network (ANN) in Matlab, with the help of experimental data ANN is to be trained. And by using ANN can predict the vibrations by changing parameters of turning such as spindle speed, feed & depth of cut. This model of ANN can be predict vibrations of single point cutting tool to avoid the failure of cutting tool.