Application of Fourier Sensing Strategies for Monitoring Velocity Changes in Coda Waves

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.

Authors

Publication Details

Journal
e-Journal of Nondestructive Testing
Published
2025-09-18
DOI
https://doi.org/10.58286/31724
Primary Topic
Flow Measurement and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application of Fourier Sensing Strategies for Monitoring Velocity Changes in Coda Waves

Eduardo Pérez, Odile Abraham, Pierric Mora, Florian Römer et al.
e-Journal of Nondestructive Testing
Flow Measurement and Analysis
article

Application of Fourier Sensing Strategies for Monitoring Velocity Changes in Coda Waves

Eduardo Pérez, Odile Abraham, Pierric Mora, Florian Römer, Jasmien Hassanin, Shilan Shaabani
article en

Abstract

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.

e-Journal of Nondestructive TestingVol. 30(10)
Openalex Percentile: Top 71%
Flow Measurement and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.