Quantifying the value of positive transfer: An experimental case study
| Autor: | Hughes, Aidan J., Delo, Giulia, Poole, Jack, Dervilis, Nikolaos, Worden, Keith |
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| Rok vydání: | 2024 |
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| Druh dokumentu: | Working Paper |
| Popis: | In traditional approaches to structural health monitoring, challenges often arise associated with the availability of labelled data. Population-based structural health monitoring seeks to overcomes these challenges by leveraging data/information from similar structures via technologies such as transfer learning. The current paper demonstrate a methodology for quantifying the value of information transfer in the context of operation and maintenance decision-making. This demonstration, based on a population of laboratory-scale aircraft models, highlights the steps required to evaluate the expected value of information transfer including similarity assessment and prediction of transfer efficacy. Once evaluated for a given population, the value of information transfer can be used to optimise transfer-learning strategies for newly-acquired target domains. Comment: In Proceedings of the 11th European Workshop on Structural Health Monitoring (EWSHM 2024), Potsdam, Germany. July 2024. arXiv admin note: text overlap with arXiv:2311.03083 |
| Databáze: | arXiv |
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