Smart Energy Management System: SCIM Diagnosis and Failure Classification and Prediction Using Energy Consumption Data

2021 
This paper represents the impact of smart energy management system in industrial microgrid on improving the key performance indicators of the maintenance, the case study will be on the squirrel cage induction motors, the idea is to finding correlations between energy consumption data and mechanical failures of these machines, this work shows a first version of a test bench acquiring vibration, voltage, current and speed while the eccentricity fault is present, after test bench preparation, installation, configuration, gathering the data, monitoring it, and see the harmonics of current and vibration in frequential domain and see the first results, the idea is to store the data and trying to implement machine learning algorithms, which gives an accuracy between 0.71 and 0.96 between model features which are current voltage and vibration, this work is a primary work of a big idea that is already developed and mention by a lot of scientists and researchers, that can be implemented in a real case of study in mining industry.
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