This study demonstrates a compressed-sensing approach to improve monitoring of velocity changes using coda wave interferometry, highlighting its efficiency.
In Structural Health Monitoring (SHM) and Non-Destructive Evaluation (NDE), Coda Wave Interferometry (CWI) is used to monitor temporal velocity changes in different media, caused by temperature, stress, cracks, or defects. However, the traditional data acquisition methods result in huge amounts of data, challenging storage and transmission, requiring more efficient data acquisition techniques. This study proposes a compressed-sensing-based approach using Fourier sensing strategies to reduce the amount of data collected by the acquisition system while maintaining high accuracy. The approach is benchmarked using the traditional time-stretching (TS) technique applied to a real data set collected from a lab experiment on concrete specimens. The results show that Fourier sensing can effectively reduce the amount of data to be collected without compromising accurate velocity variation (dv/v) detection. To evaluate the accuracy of our proposed method, the Root Mean Square Error (RMSE) in the estimated velocity is used as a performance metric.
No takes yet. Share an insight, caveat, or question.
Hassanin et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: