Fault Identification based on Condition Monitoring for Motor using MATLAB

Pavan Kumar BK¹* and Yadavalli Basavaraj^2
1Asst. Prof, Mechanical Department, Ballari Institute of Technology and Management, Ballari, Karnataka, India
²Principal, Mechanical Department, Ballari Institute of Technology and Management, Ballari, Karnataka, India
*Corresponding Author: Pavan Kumar BK, Asst. Prof, Mechanical Department, Ballari Institute of Technology and Management, Ballari, Karnataka, India.

Published: July 25, 2025

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Abstract  

Rotating machines are commonly employed in a wide range of industrial applications. To minimise failures, boost dependability, and reduce maintenance costs, condition-based maintenance must be implemented for spinning machinery. It is very critical to identify the fault and predict the life of any machines. Henceforth, present study is focused on reliability of machines using neural network by the aid of statistical tool named MATLAB which ensures the proper validation which has 99% accuracy for the obtained data. 

Keywords: Condition monitoring; FFT Analyzer; Neural Network; ISO severity chart

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