Print Email Facebook Twitter A novel approach towards fatigue damage prognostics of composite materials utilizing SHM data and stochastic degradation modeling Title A novel approach towards fatigue damage prognostics of composite materials utilizing SHM data and stochastic degradation modeling Author Loutas, T. (University of Patras) Eleftheroglou, N. (TU Delft Structural Integrity & Composites) Date 2016 Abstract A prognostic framework is proposed in order to estimate the remaining useful life of composite materials under fatigue loading based on acoustic emission data and a sophisticated Non Homogenous Hidden Semi Markov Model. Bayesian neural networks are also utilized as an alternative machine learning technique for the non-linear regression task. A comparison between the two algorithms operation, input, output and performance highlights their ability to tackle the prognostic task. Subject SHMremaining useful lifemachine learning techniquescomposite materialsacoustic emission To reference this document use: http://resolver.tudelft.nl/uuid:8ae30ce5-74bf-405f-815a-bc7be67a1281 Publisher NDT.net ISBN 9781510827936 Source 8th European Workshop on Structural Health Monitoring: Bilbao, Spain, 2 Event 8th European Workshop on Structural Health Monitoring, 2016-07-05 → 2016-07-08, Bilbao, Spain Part of collection Institutional Repository Document type conference paper Rights © 2016 T. Loutas, N. Eleftheroglou Files PDF EWSHM2016.pdf 778.83 KB Close viewer /islandora/object/uuid:8ae30ce5-74bf-405f-815a-bc7be67a1281/datastream/OBJ/view