most citedAn optimal baseline selection methodology for data-driven damage detection and temperature compensation in acousto-ultrasonics

16 citations · 16 across the 1 of their papers we have counts for

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eess.SP2025★ 16 cited

An optimal baseline selection methodology for data-driven damage detection and temperature compensation in acousto-ultrasonics

M-A Torres-Arredondo, Julián Sierra-Pérez, Guénaël Cabanes

The global trends in the construction of modern structures require the integration of sensors together with data recording and analysis modules so that their integrity can be conti…