Development of a Machine Learning Model for Analysis of An Deep Groove Ball Bearing

Ball Bearing is the most important mechanical element in many industries. The bearing has to work reliably under uncertain working conditions with high load. Hence it is necessary to design an equipment which has maximum reliability and minimum weight, keeping the design safe under all loading conditions. The project work deals with the development of machine learning model for analysis of Deep groove ball bearing with different speeds and loading conditions. The data bank for alternating stress and deformation of bearing is developed by using static structural analysis. Python programming language is used to develop machine learning model. Three machine learning models Linear Regression Algorithm, Support Vector Machine Algorithm and Random Forest Algorithm are used and the score for each model is determined.