Transmissibility performance of highly damped stationary vehicle and its contact-point response for indirect bridge health monitoring: Theory and experiment
Restricted accessResearch articleFirst published online May, 2026
Transmissibility performance of highly damped stationary vehicle and its contact-point response for indirect bridge health monitoring: Theory and experiment
Indirect bridge health monitoring is a promising measurement technique which has several advantages over the conventional direct method. However, the indirect method still encounters some challenges such as the effect of road roughness and vehicle’s own frequency. Utilizing the scanning vehicle in a stationary state has been proposed to overcome the effects of road roughness. Also, the contact-point response (CPR) has been developed to eliminate the vehicle’s own frequency. However, CPR has been developed for undamped vehicle. Therefore, the first part of this study develops CPR calculation method for a damped vehicle model. The CPR is calculated for a damped stationary vehicle (considering various vehicle frequencies) using the proposed equations. The transmissibility of the CPR is tested by comparing the time and frequency domains between the indirect (vehicle) and bridge direct response (reference). The transmissibility of the vehicle significantly improved by computing CPR, especially for low vehicle frequencies. In the second part of the paper, a frequency-free vehicle is developed in a laboratory set-up. The response of the vehicle does not contain the frequency of the vehicle due to using polyurethane (PU) wheels. Dynamic responses, damping ratios, and mode shapes are compared between the direct and indirect method. Accordingly, the results show that the designed vehicle has high transmissibility of the bridge vibration.
MalekjafarianACorballyRGongW. A review of mobile sensing of bridges using moving vehicles: progress to date, challenges and future trends. Structures2022; 44: 1466–1489.
2.
MalekjafarianAMcGetrickPJObrienEJ. A review of indirect bridge monitoring using passing vehicles. Shock Vib2015; 2015: 286139.
3.
YangYBYangJP. State-of-the-art review on modal identification and damage detection of bridges by moving test vehicles. Int J Struct Stabil Dynam2018; 18(02): 1850025.
4.
ZhangCMousaviAAMasriSF, et al.Vibration feature extraction using signal processing techniques for structural health monitoring: a review. Mech Syst Signal Process2022; 177: 109175.
5.
YangYBYangJPWuYt., et al.Vehicle scanning method for bridges. John Wiley & Sons, 2019.
6.
WangZLYangJPShiK, et al.Recent advances in researches on vehicle scanning method for bridges. Int J Struct Stabil Dynam2022; 22(15): 2230005.
7.
YangYBLinCWYauJD. Extracting bridge frequencies from the dynamic response of a passing vehicle. J Sound Vib2004; 272(3-5): 471–493.
8.
YangYBZhangBQianY, et al.Contact-point response for modal identification of bridges by a moving test vehicle. Int J Struct Stabil Dynam2018; 18(05): 1850073.
9.
WangHNagayamaTZhaoB, et al.Identification of moving vehicle parameters using bridge responses and estimated bridge pavement roughness. Eng Struct2017; 153: 57–70.
10.
YangYBLeeYCChangKC. Effect of road surface roughness on extraction of bridge frequencies by moving vehicle. In: Mechanics and model-based control of advanced engineering systems. Springer, 2014, pp. 295–305.
11.
YangYBLiYCChangKC. Using two connected vehicles to measure the frequencies of bridges with rough surface: a theoretical study. Acta Mech2012; 223(8): 1851–1861.
12.
ZhanYAuF. A double-pass method for bridge assessment considering surface roughness using normalized contact point responses. Smart Monitoring. Assessment Rehabilitation of Civil Structures2019; 9.
13.
YangYBXuHZhangB, et al.Measuring bridge frequencies by a test vehicle in non-moving and moving states. Eng Struct2020; 203: 109859.
14.
YangYBLiZWangZ, et al.A novel frequency-free movable test vehicle for retrieving modal parameters of bridges: theory and experiment. Mech Syst Signal Process2022; 170: 108854.
15.
HashlamonINikbakhtETopaA, et al.Numerical parametric study on the effectiveness of the contact-point response of a stationary vehicle for bridge health monitoring. Appl Sci2021; 11(15): 7028.
16.
YangYBXiongFWangZL, et al.Extraction of bridge frequencies inclusive of the higher modes by the ESMD using the contact-point response. Int J Struct Stabil Dynam2020; 20(04): 2050045.
17.
YangYXuHWangZ, et al.Refined detection technique for bridge frequencies using rocking motion of single-axle moving vehicle. Mech Syst Signal Process2022; 162: 107992.
18.
YangYXuHMoX, et al.An effective procedure for extracting the first few bridge frequencies from a test vehicle. Acta Mech2021; 232(3): 1227–1251.
19.
LiJZhuXGuoJ. Enhanced drive-by bridge modal identification via dual Kalman filter and singular spectrum analysis. Struct Control Health Monit2022; 29(5): e2927.
20.
ZhanYAuFZhangJ. Bridge identification and damage detection using contact point response difference of moving vehicle. Struct Control Health Monit2021; 28(12): e2837.
21.
YangYBXuHWangZL, et al.Using vehicle–bridge contact spectra and residue to scan bridge’s modal properties with vehicle frequencies and road roughness eliminated. Struct Control Health Monit2022; 29(8): e2968.
22.
ZhangBQianYWuY, et al.An effective means for damage detection of bridges using the contact-point response of a moving test vehicle. J Sound Vib2018; 419: 158–172.
23.
YangYZhangBQianY, et al.Further revelation on damage detection by IAS computed from the contact-point response of a moving vehicle. Int J Struct Stabil Dynam2018; 18(11): 1850137.
24.
CorballyRMalekjafarianA. Examining changes in bridge frequency due to damage using the contact-point response of a passing vehicle. Journal of Structural Integrity Maintenance2021; 6(3): 148–158.
25.
HashlamonINikbakhtETopaA. Indirect bridge health monitoring employing contact-point response of instrumented stationary vehicle. In: Proceedings of the International Conference on Civil, Offshore and Environmental Engineering. Springer, 2021.
26.
HashlamonINikbakhtEJAS. The use of a movable vehicle in a stationary condition for indirect bridge damage detection using baseline-free methodology. Appl Sci (Basel)2022; 12(22): 11625.
27.
HashlamonINikbakhtE. Theoretical and numerical investigation of bridge frequency identification employing an instrumented vehicle in stationary and moving states. Structures2023; 51: 1684–1693.
28.
NayekRNarasimhanS. Extraction of contact-point response in indirect bridge health monitoring using an input estimation approach. J Civ Struct Health Monit2020; 10(5): 815–831.
29.
XiaoFMaoYTianG, et al.Partial-model-based damage identification of long-span steel truss bridge based on stiffness separation method. Struct Control Health Monit2024; 2024(1): 5530300.
30.
XiaoFMaoYSunH, et al.Stiffness separation method for reducing calculation time of truss structure damage identification. Struct Control Health Monit2024; 2024(1): 5171542.
31.
LiuJChenSBergésM, et al.Diagnosis algorithms for indirect structural health monitoring of a bridge model via dimensionality reduction. Mech Syst Signal Process2020; 136: 106454.
32.
CerdaFChenSBielakJ, et al.Indirect structural health monitoring of a simplified laboratory-scale bridge model. Smart Struct Syst2014; 13(5): 849–868.
33.
LiuJBergésMBielakJ, et al.A damage localization and quantification algorithm for indirect structural health monitoring of bridges using multi-task learning. In: AIP Conference Proceedings. AIP Publishing LLC, 2019.
34.
CerdaFGarrettJHBielakJ, et al.Indirect structural health monitoring in bridges: scale experiments. In: Proceedings of the Sixth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2012), Lago di Como, Italy, July 8-12, 2012.
35.
LedermanGWangZBielakJ, et al.Damage quantification and localization algorithms for indirect SHM of bridges. In: Proceedings of the International Conference on Bridge Maintenance, Safety and Management, Shanghai, China, Jul 9, 2014.
36.
AlamdariMChangKKimC, et al.Transmissibility performance assessment for drive-by bridge inspection. Eng Struct2021; 242: 112485.
37.
CanteroDMcGetrickPKimC, et al.Experimental monitoring of bridge frequency evolution during the passage of vehicles with different suspension properties. Eng Struct2019; 187: 209–219.
38.
KimCChangKMcGetrickPJ, et al.Utilizing moving vehicles as sensors for bridge condition screening-A laboratory verification. Sensors2017; 29(2): 153–163.
39.
ChangKKimCKawataniM. Feasibility investigation for a bridge damage identification method through moving vehicle laboratory experiment. Structure Infrastructure Engineering2014; 10(3): 328–345.
40.
KimCIsemotoRMcGetrickP, et al.Drive-by bridge inspection from three different approaches. Smart Struct Syst2014; 13(5): 775–796.
41.
McGetrickPKimCGonzálezA, et al.Experimental validation of a drive-by stiffness identification method for bridge monitoring. Struct Health Monit2015; 14(4): 317–331.
42.
SinghPSadhuA. A hybrid time-frequency method for robust drive-by modal identification of bridges. Eng Struct2022; 266: 114624.
43.
LanYLinWZhangY. Bridge frequency identification using vibration responses from sensors on a passing vehicle. In: Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability. CRC Press, 2022, pp. 956–963.
44.
LiJZhuXLawS, et al.Drive-by blind modal identification with singular spectrum analysis. J Aero Eng2019; 32: 1030.
45.
LiJZhuXLawS, et al.Indirect bridge modal parameters identification with one stationary and one moving sensors and stochastic subspace identification. J Sound Vib2019; 446: 1–21.
46.
LiJZhuXLawS, et al.A two-step drive-by bridge damage detection using dual Kalman filter. Int J Struct Stabil Dynam2020; 20(10): 2042006.
47.
LiJZhuXLawS, et al.Time-varying characteristics of bridges under the passage of vehicles using synchroextracting transform. Mech Syst Signal Process2020; 140: 106727.
48.
PourzeynaliSZhuXGhariA, et al.Comprehensive study of moving load identification on bridge structures using the explicit form of newmark-β method: numerical and experimental studies. Remote Sens2021; 13(12): 2291.
49.
LinCWYangYB. Use of a passing vehicle to scan the fundamental bridge frequencies: an experimental verification. Eng Struct2005; 27(13): 1865–1878.
50.
YangYChenWYuH, et al.Experimental study of a hand-drawn cart for measuring the bridge frequencies. Eng Struct2013; 57: 222–231.
