Machine learning-enhanced acoustic emission technique for impact source identification and classification in steel pipes.
(2024)
Presentation / Conference Contribution
FATUKASI O.S., ABOLLE-OKOYEAGU, J., PRATHURU, A. and SOLADEMI, O. 2024. Machine learning-enhanced acoustic emission technique for impact source identification and classification in steel pipes. Presented at the 12th Annual conference of Society of structural integrity and life (DIVK12), 17-19 November 2024, Belgrade, Serbia.
External impacts represent a prevalent source of structural damage in pipes/piping systems. Detecting and identifying the nature, and the severity of these impacts would enhance the reliability and operational safety of such critical infrastructure.... Read More about Machine learning-enhanced acoustic emission technique for impact source identification and classification in steel pipes..