Blockchain-enabled Data Mining for Pre-Condition Monitoring in Railway Infrastructure
Meisam Gordan, Ramin Ghiasi, Araliya Mosleh, Diogo Rodrigo Ferreira Ribeiro, Abdollah Malekjafarian · e-Journal of Nondestructive Testing · 2024
Early detection of abnormalities in railway systems is crucial for risk mitigation and cost-effective maintenance. Damaged wheels in freight trains cause a significant threat to transport infrastructure integrity, particularly when wheel flats occur. Monitoring wheel conditions relies on sensing mechanisms, requiring robust data integrity checks. This paper proposes a data-driven approach utilising blockchain for pre-condition monitoring to enhance data reliability. To achieve this goal, a data mining procedure is developed to establish a local blockchain. The blockchain continuously expands with new blocks, with each block linked to the previous one via a hash function. Only validated data are recorded in order to enhance the reliability of train measurements.