anamarigarzon/Predictive_and_Proactive_Maintenance_in_Power_Systems
This repository contains the analysis of predictive and proactive maintenance in power systems. It includes fault simulation, ML fault prediction, thermographic infrared images analysis from diverse power systems. The aim of the project is to detect failure in the equipment through Computer Vision and Machine Learning methods.
This project helps power system operators and maintenance engineers anticipate and prevent equipment failures. It analyzes thermographic infrared images and other power system data to predict potential faults. The output is an early warning system that allows for proactive maintenance, preventing costly outages and improving system reliability.
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Use this if you manage power distribution systems and want to shift from reactive repairs to predictive maintenance, leveraging visual and operational data to prevent equipment failures.
Not ideal if your primary concern is maintaining non-electrical or non-infrastructure assets, or if you lack access to thermographic imaging data for your equipment.
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Jupyter Notebook
License
BSL-1.0
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Last pushed
Dec 14, 2023
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