Smart Asset Management System with Health Degradation Identification and Remaining Useful Lifetime Estimation in Electrical Distribution System

The goal of this project is to develop and implement a smart asset management solution for the existing assets in the actual grid as well as for the industry plants by utilizing machine-learning technologies combined with advanced control system algorithms applied on actual and historical collected data. The developed strategy aims to analyze and identify the asset behavior, state of health identification, health degradation process, and remaining useful lifetime estimation. The proposed solutions will assist the preventive maintenance activities, the optimization of equipment uptime, and improvement of the overall assets and system reliability. The reliability will be assessed and predicted based on the collected historical data. The research activities within this project will be coordinated with, and the results will be adopted by, the industry partner (Shell- Qatar).