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A Damage Detection Approach for Cable-Stayed Bridges Using Displacement Responses and Mahalanobis Distance | ||
| Journal of Rehabilitation in Civil Engineering | ||
| مقاله 3، دوره 13، شماره 2 - شماره پیاپی 38، مرداد 2025، صفحه 47-63 اصل مقاله (2.02 M) | ||
| نوع مقاله: Regular Paper | ||
| شناسه دیجیتال (DOI): 10.22075/jrce.2024.33273.1995 | ||
| نویسندگان | ||
| Mahtab Mohseni Moghaddam1؛ Ehsan Dehghani* 2؛ Maryam Bitaraf3 | ||
| 1Ph.D. Candidate, Department of Civil Engineering, University of Qom, Qom, Iran | ||
| 2Associate Professor, Faculty of Civil Engineering, University of Qom, Qom, Iran | ||
| 3Assistant Professor, Faculty of Civil Engineering, University of Tehran, Tehran, Iran | ||
| تاریخ دریافت: 23 بهمن 1402، تاریخ بازنگری: 06 خرداد 1403، تاریخ پذیرش: 11 مرداد 1403 | ||
| چکیده | ||
| Given the crucial role of cable-stayed bridges in infrastructure, continuous health monitoring throughout their lifespan is imperative. To achieve this purpose, a damage detection approach for cable-stayed bridges under loading was presented. This method aimed to assess the condition of cable-stayed bridges through phase space analysis of time domain responses. Displacement responses were utilized to minimize the need for extensive sensor deployment. Damage was identified by analyzing variations in the Mahalanobis distance index curve between intact and damaged models. This method was evaluated for effectiveness through a numerical case study. The case study involved damage design in the deck and cables of the Puqian cable-stayed bridge. The results demonstrated that this method can efficiently detect the damage location in the cable-stayed bridge and exhibited anti-noise capability in identifying the location of damage, especially for cables. Its accuracy at a noise level of 30 dB was 76.5%, 5.56%, and 75% for cable, deck, and combined cable and deck scenarios, respectively. This method can serve as a rapid and continuous monitoring tool for damage detection in cable-stayed bridges, with minimal traffic disruption and relying solely on deck displacement responses. | ||
تازه های تحقیق | ||
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| کلیدواژه‌ها | ||
| Cable-stayed bridges؛ Damage detection؛ Displacement response؛ Mahalanobis distance؛ Structural health monitoring | ||
| مراجع | ||
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[1] Zhang L, Qiu G, Chen Z. Structural health monitoring methods of cables in cable-stayed bridge: A review. Measurement 2021;168:108343. https://doi.org/10.1016/j.measurement.2020.108343.
[2] Zhang Y-M, Wang H, Bai Y, Mao J-X, Chang X-Y, Wang L-B. Switching Bayesian dynamic linear model for condition assessment of bridge expansion joints using structural health monitoring data. Mechanical Systems and Signal Processing 2021;160:107879. https://doi.org/10.1016/j.ymssp.2021.107879.
[3] Li S, Niu J, Li Z. Novelty detection of cable-stayed bridges based on cable force correlation exploration using spatiotemporal graph convolutional networks. Structural Health Monitoring 2021;20:2216–28. https://doi.org/10.1177/1475921720988666.
[4] Wang F, Ning S, Sun Z. Experimental investigation on wear resistance of bushing in bridge suspenders. Journal of Performance of Constructed Facilities 2020;34:06020001. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001429.
[5] Zhou Y, Sun L. Insights into temperature effects on structural deformation of a cable-stayed bridge based on structural health monitoring. Structural Health Monitoring 2019;18:778–91. https://doi.org/10.1177/1475921718773954.
[6] Lei X, Siringoringo DM, Dong Y, Sun Z. Interpretable machine learning methods for clarification of load-displacement effects on cable-stayed bridge. Measurement 2023;220:113390. https://doi.org/10.1016/j.measurement.2023.113390.
[7] Jesus A, Brommer P, Westgate R, Koo K, Brownjohn J, Laory I. Bayesian structural identification of a long suspension bridge considering temperature and traffic load effects. Structural Health Monitoring 2019;18:1310–23. https://doi.org/10.1177/1475921718794299.
[8] Lei X, Siringoringo DM, Sun Z, Fujino Y. Displacement response estimation of a cable-stayed bridge subjected to various loading conditions with one-dimensional residual convolutional autoencoder method. Structural Health Monitoring 2023;22:1790–806. https://doi.org/10.1177/14759217221116637.
[9] Wangchuk S, Siringoringo DM, Fujino Y. Modal analysis and tension estimation of stay cables using noncontact vision‐based motion magnification method. Structural Control and Health Monitoring 2022;29:e2957. https://doi.org/10.1002/stc.2957.
[10] Nazarian E, Ansari F, Azari H. Recursive optimization method for monitoring of tension loss in cables of cable-stayed bridges. Journal of Intelligent Material Systems and Structures 2016;27:2091–101. https://doi.org/10.1177/1045389X15620043.
[11] Saidin SS, Kudus SA, Jamadin A, Anuar MA, Amin NM, Ya ABZ, et al. Vibration-based approach for structural health monitoring of ultra-high-performance concrete bridge. Case Studies in Construction Materials 2023;18:e01752. https://doi.org/https://doi.org/10.1016/j.cscm.2022.e01752.
[12] Pan H, Azimi M, Yan F, Lin Z. Time-Frequency-Based Data-Driven Structural Diagnosis and Damage Detection for Cable-Stayed Bridges. Journal of Bridge Engineering 2018;23:04018033. https://doi.org/10.1061/(asce)be.1943-5592.0001199.
[13] Zarbaf SEHAM, Norouzi M, Allemang RJ, Hunt VJ, Helmicki A, Venkatesh C. Ironton-Russell Bridge: Application of Vibration-Based Cable Tension Estimation. Journal of Structural Engineering 2018;144:04018066. https://doi.org/10.1061/(asce)st.1943-541x.0002054.
[14] Wu B, Wu G, Lu H, Feng DC. Stiffness monitoring and damage assessment of bridges under moving vehicular loads using spatially-distributed optical fiber sensors. Smart Materials and Structures 2017;26:1–21. https://doi.org/10.1088/1361-665X/aa5c6f.
[15] Hong W, Wu Z, Yang C, Wan C, Wu G. Investigation on the damage identification of bridges using distributed long-gauge dynamic macrostrain response under ambient excitation. Journal of Intelligent Material Systems and Structures 2012;23:85–103. https://doi.org/10.1177/1045389X11430743.
[16] Le HT, Thammarak P. Damage detection of a reinforced concrete beam using the modal strain approach. International Journal of Dynamics and Control 2023;11:2774–85. https://doi.org/10.1007/s40435-023-01160-2.
[17] Wu B, Wu G, Yang C. Parametric study of a rapid bridge assessment method using distributed macro-strain influence envelope line. Mechanical Systems and Signal Processing 2019;120:642–63. https://doi.org/10.1016/j.ymssp.2018.10.039.
[18] He WY, Ren WX, Zhu S. Baseline-free damage localization method for statically determinate beam structures using dual-type response induced by quasi-static moving load. Journal of Sound and Vibration 2017;400:58–70. https://doi.org/10.1016/j.jsv.2017.03.049.
[19] Zhang L, Wu G, Cheng X. A rapid output-only damage detection method for highway bridges under a moving vehicle using long-gauge strain sensing and the fractal dimension. Measurement: Journal of the International Measurement Confederation 2020;158:107711. https://doi.org/10.1016/j.measurement.2020.107711.
[20] Sarwar MZ, Cantero D. Deep autoencoder architecture for bridge damage assessment using responses from several vehicles. Engineering Structures 2021;246:113064. https://doi.org/10.1016/j.engstruct.2021.113064.
[21] Zhang W, Li J, Hao H, Ma H. Damage detection in bridge structures under moving loads with phase trajectory change of multi-type vibration measurements. Mechanical Systems and Signal Processing 2017;87:410–25. https://doi.org/10.1016/j.ymssp.2016.10.035.
[22] Nie Z, Hao H, Ma H. Structural damage detection based on the reconstructed phase space for reinforced concrete slab: Experimental study. Journal of Sound and Vibration 2013;332:1061–78. https://doi.org/https://doi.org/10.1016/j.jsv.2012.08.024.
[23] Nie Z, Hao H, Ma H. Using vibration phase space topology changes for structural damage detection. Structural Health Monitoring 2012;11:538–57. https://doi.org/10.1177/1475921712447590.
[24] Peng Z, Li J, Hao H, Nie Z. Improving identifiability of structural damage using higher order responses and phase space technique. Structural Control and Health Monitoring 2021;28:e2808. https://doi.org/10.1002/stc.2808.
[25] De Maesschalck R, Jouan-Rimbaud D, Massart DL. The mahalanobis distance. Chemometrics and Intelligent Laboratory Systems 2000;50:1–18. https://doi.org/10.1016/S0169-7439(99)00047-7.
[26] Pamwani L, Shelke A. Damage Detection Using Dissimilarity in Phase Space Topology of Dynamic Response of Structure Subjected to Shock Wave Loading. Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems 2018;1:1–13. https://doi.org/10.1115/1.4040472.
[27] Tuttipongsawat P, Sasaki E, Suzuki K, Fukuda M, Kawada N, Hamaoka K. PC tendon damage detection based on phase space topology changes in different frequency ranges. Journal of Advanced Concrete Technology 2019;17:474–88. https://doi.org/10.3151/jact.17.474.
[28] Paul B, George RC, Mishra SK. Phase space interrogation of the empirical response modes for seismically excited structures. Mechanical Systems and Signal Processing 2017;91:250–65. https://doi.org/10.1016/j.ymssp.2016.12.008.
[29] Peng Z, Li J, Hao H. Data driven structural damage assessment using phase space embedding and Koopman operator under stochastic excitations. Engineering Structures 2022;255:113906. https://doi.org/10.1016/j.engstruct.2022.113906.
[30] Peng Z, Li J, Hao H. Structural damage detection via phase space based manifold learning under changing environmental and operational conditions. Engineering Structures 2022;263:114420. https://doi.org/10.1016/j.engstruct.2022.114420.
[31] Abarbanel H. Analysis of observed chaotic data. New York (NY): Springer; 2012.
[32] Jiang A-H, Huang X-C, Zhang Z-H, Li J, Zhang Z-Y, Hua H-X. Mutual information algorithms. Mechanical Systems and Signal Processing 2010;24:2947–60. https://doi.org/10.1016/j.ymssp.2010.05.015.
[33] Broomhead DS, King GP. Extracting qualitative dynamics from experimental data. Physica D: Nonlinear Phenomena 1986;20:217–36. https://doi.org/10.1016/0167-2789(86)90031-X.
[34] Rhodes C, Morari M. The false nearest neighbors algorithm: An overview. Computers & Chemical Engineering 1997;21:S1149–54. https://doi.org/10.1016/S0098-1354(97)87657-0.
[35] George RC, Mishra SK, Dwivedi M. Mahalanobis distance among the phase portraits as damage feature. Structural Health Monitoring 2018;17:869–87. https://doi.org/10.1177/1475921717722743.
[36] Yi J, Yu D. Longitudinal damage of cable-stayed bridges subjected to near-fault ground motion pulses. Advances in Bridge Engineering 2021;2:1–22. https://doi.org/10.1186/s43251-021-00034-x.
[37] Yi J, Li J. Longitudinal Seismic Behavior of a Single-Tower Cable-Stayed Bridge Subjected to Near-Field Earthquakes. Shock and Vibration 2017;2017. https://doi.org/10.1155/2017/1675982.
[38] Zhu L, Zhou Q, Ding Q, Xu Z. Identification and application of six-component aerodynamic admittance functions of a closed-box bridge deck. Journal of Wind Engineering and Industrial Aerodynamics 2018;172:268–79. https://doi.org/10.1016/j.jweia.2017.11.002.
[39] Jaramilla B, Huo S. Looking to load and resistance factor rating. Public Roads 2005;69.
[40] Australasian Railway Association. Bridge Design Code. Sydney, Australia: Austroads; 1992. | ||
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