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Heterogeneous data fusion for the improved non-destructive detection of steel-reinforcement defects using echo state networks (2022)
Journal Article
Wootton, A. J., Day, C., & Haycock, P. W. (2022). Heterogeneous data fusion for the improved non-destructive detection of steel-reinforcement defects using echo state networks. Structural Health Monitoring, 21(6), 2910-2921. https://doi.org/10.1177/14759217221080718

The degradation of roads is an expensive problem: in the United Kingdom alone, £27 billion was spent on road repairs between 2013 and 2019. One potential cost-saver is the early, non-destructive detection of faults. There are many available technique... Read More about Heterogeneous data fusion for the improved non-destructive detection of steel-reinforcement defects using echo state networks.

Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX (2017)
Journal Article
Wootton, A. J., Butcher, J. B., Kyriacou, T., Day, C. R., & Haycock, P. W. (2017). Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX. Engineering Applications of Artificial Intelligence, 64, 152-163. https://doi.org/10.1016/j.engappai.2017.05.014

Echo State Networks (ESNs) and a Nonlinear Auto-Regressive Moving Average model with eXogenous inputs (NARMAX) have been applied to multi-sensor time-series data arising from a test footbridge which has been subjected to multiple potentially damaging... Read More about Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX.