Project Details

Abstract

Safety is the principal concern of the railway industry, and track alignment irregularities pose risks to the safe operation of trains. According to the Federal Railroad Administration (FRA) accident database, "Track alignment irregular (buckled/sun kink)" is the most severe accident cause. include improving rail safety by developing accurate rail neutral temperature (RNT) measurement technology. The proposed research will contribute to further improvement and verification of the machine learning (ML)-RNT predictive tool, which can support nondestructive and non-disrupting RNT measurement without the need for baseline measurement. The proposed long-term data collection system and machine learning models will contribute to stress-sensitive information extraction and a better understanding of wave propagation in rails.

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