Comparative Analysis of Wavelet and Hilbert Transforms for Vehicle-Based Identification of Bridge Damping Ratios

Much of the research has focused on identifying bridge frequencies for health monitoring, while the bridge damping ratio also serves as an important factor in damage detection. This study presents an enhanced method for identifying bridge damping ratios using a two-axle, three-mass test vehicle, relying on wheel responses captured by only two mounted sensors. Damping ratio estimation formulas are derived using both the Hilbert Transform (HT) and Wavelet Transform (WT), with a consistent formulation that confirms accurate estimation is achievable with minimal instrumentation, particularly when addressing the support effect. A comparative analysis of the two signal processing techniques reveals the superior performance of WT in identifying bridge damping ratios. The effectiveness of the proposed procedure and formulas is validated through a detailed parametric study, demonstrating robustness across bridges with varying modal damping ratios and different spans using minimal sensors. Moreover, the present study shows that responses from only the first two spans of a multi-span bridge are sufficient for reliable damping estimation, underscoring the practicality and scalability of the procedure for structural health monitoring applications.

Authors

Publication Details

Journal
Computer Modeling in Engineering & Sciences
Published
2025-01-01
DOI
https://doi.org/10.32604/cmes.2025.068945
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Analysis of Wavelet and Hilbert Transforms for Vehicle-Based Identification of Bridge Damping Ratios

Yuan-Jun Zhang, Judy P. Yang
Computer Modeling in Engineering & Sciences
Structural Health Monitoring Techniques
article

Comparative Analysis of Wavelet and Hilbert Transforms for Vehicle-Based Identification of Bridge Damping Ratios

Yuan-Jun Zhang, Judy P. Yang
article en

Abstract

Much of the research has focused on identifying bridge frequencies for health monitoring, while the bridge damping ratio also serves as an important factor in damage detection. This study presents an enhanced method for identifying bridge damping ratios using a two-axle, three-mass test vehicle, relying on wheel responses captured by only two mounted sensors. Damping ratio estimation formulas are derived using both the Hilbert Transform (HT) and Wavelet Transform (WT), with a consistent formulation that confirms accurate estimation is achievable with minimal instrumentation, particularly when addressing the support effect. A comparative analysis of the two signal processing techniques reveals the superior performance of WT in identifying bridge damping ratios. The effectiveness of the proposed procedure and formulas is validated through a detailed parametric study, demonstrating robustness across bridges with varying modal damping ratios and different spans using minimal sensors. Moreover, the present study shows that responses from only the first two spans of a multi-span bridge are sufficient for reliable damping estimation, underscoring the practicality and scalability of the procedure for structural health monitoring applications.

Computer Modeling in Engineering & SciencesVol. 144(1)
Openalex Percentile: Top 81%
Structural Health Monitoring Techniques
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.