PauloCareli/power-quality-disturbances-with-machine-learning
Power Quality Disturbances Classification with Machine Learning. This is my final paper project for the Electrical Engineering course at UFJF.
This project helps electrical engineers and power systems operators analyze and classify various power quality disturbances in electrical signals. It takes raw electrical signal data, processes it to extract key features, and then uses machine learning models to identify the type of disturbance present. The output is a classification of 14 different types of power quality issues, which can aid in diagnosing and resolving problems in power grids.
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Use this if you need to automatically identify and categorize different types of power quality disturbances from electrical signal measurements.
Not ideal if you are looking for a real-time monitoring and control system for power quality, as this project focuses on offline analysis and classification.
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Sep 20, 2021
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