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On ultrasonic guided wave tomography using a decoder architecture for sparse sensor array data

Year: 2025
Type: conference-paper
Abstract: We address defect mapping from sparse guided-wave measurements by learning to reconstruct 2-D velocity fields from eight travel-time paths. Our geometry-conditioned model is trained on a large synthetic dataset matched to a specific experimental setup. In simulation, reconstruction quality is highest when thinning overlaps the transmitter. On the experiment, the model recovers two corrosion regions; depth agrees (< 1mm), while x-y localisation is centre-biased. A fundamental limitation is the sim-to-real gap. Overall, eight paths suffice for coarse, depth-consistent maps with approximate estimation of x-y location.
Authors: Ioannis Matthaiou, Katy Tant, Gordon Dobie, Matthew McInnes, Cameron Dick, Praveen Ashok, Dave Allan Hughes
Language: English
Open Access status: green
OpenAlex ID: W4415367178
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Cites: 10
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