Fault Detection Analysis in Ball Bearings using Machine Learning Techniques

Shubham  Junghare

Authors

Shubham Junghare Department of Mechanical Engineering SIES Graduate School of Technology, Mumbai, India https://orcid.org/0009-0003-1533-9701

Keywords:

Misalignment, Fault Detection, Bearing, Machine Learning

Abstract

The Bearing element is very essential component of any rotating equipment. Any defect in the bearings lead to instable performance of the machinery. To avoid such malfunction and breakdown of the machinery equipment due to misalignment is review critically in this research paper and various machine learning techniques to tackle the issue is highlighted. This review article finds the basis for developing an effective system in order to reduce the breakdown of machinery or equipment. Conventional Machine Learning methods, like Artificial neural network, Decision Tree, Random Forest, Support Vector Machines(SVM) have been applied to detecting categorizing fault, while the application of Deep Learning methods has ignited great interest in the industry.

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