AI Factory Railway: Prognostics and health management of catenary for climate change adaptation (AIFR-PHMCC)

Purpose and goal:

This project aims to improve the railway systems´ resilience towards micro and macro climate changes. The main objective of this project is to develop a scalable AI-based platform for the Prognostics and Health Management (PHM) of the catenary system through Digital Twin (DT) considering climate change adaptation.

The proposed project will be developed on top of the AI factory platform. The AIFactory platform is a scalable platform developed to provide connectivity, computation, and scalability both horizontally and vertically. Expected results and effects: The expected results of the project are: 1.A report on climate risks and vulnerabilities of railway catenary

2.An innovative and scalable platform for PHM of catenary through digital twin 3.A demonstrator for climate change adaption for catenary for PHM 4.Development of business models for implementation of operation and maintenance The long-term effects are: 1.Increased knowledge and awareness of climate change´s

2.Expanding innovation platform and solutions that are scalable dimensions 3.Strengthening of collaborations at national and international levels. Approach and implementation:

This project will develop and provide a set of models and algorithms for stakeholders, and additionally a platform to synchronise all the functionality. The platform is an important aspect since the project focuses on hybrid model development where the physics-based models can be a part of the algorithms. Thus, the project focuses on a holistic solution for future development, use, and integration into the existing systems within TRV and other possible railway stakeholders within and outside the consortium in the long term. T