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What is Synthetic Failure Data Methodology for PHM about?

This thesis presents a methodology for generating and validating synthetic failure data for Prognostics and Health Management (PHM) in digital twins, addressing the challenge of scarce failure data in Industry 4.0. The methodology was applied to a smart petroleum well model, demonstrating the feasibility of creating useful synthetic data that can train machine learning algorithms. Results indicate the potential for improvements in data generation processes, while also discussing limitations and alternatives

Author

carlosgttfs

Language

EN