Randomized trial shows improved energy efficiency in agro-industrial facilities with integrated diagnostics.
Key Points
This study aims to demonstrate the effectiveness of an intelligent system that automates the design of energy-efficient facilities while providing diagnostics for electric drives.
Experimental testing of 1.5-7.5 kW asynchronous electric motors.
Numerical modelling using finite element and finite difference methods.
Optimization through a genetic algorithm and particle swarm methodology.
Faulty electric motors showed a 20% increase in current and a drop in power factor from 0.87 to 0.74.
Numerical modelling indicated a 9% reduction in energy consumption and a 16% increase in power factor.
The classification model achieved an accuracy with an area under the curve of 0.94, confirming reliable diagnostics.