Identification method of bridge modal characteristics based on vibration response of 2-axle vehicle passing through bridge

PDF(3789 KB)

Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (13) : 78-89.

CHENG Jianting1, LIN Zikang2, WU Xiaosheng1, WANG Shenning1, ZHOU Junyong2

Author information +

History +

Abstract

To indirectly identify bridge modal parameters using the vibration responses of passing vehicles and achieve the objective of rapid health condition assessment of network bridges, this study proposed a methodology of employing a normal two-axle vehicle to synchronously identify bridge frequencies and mode shapes. Firstly, theoretical formulas were derived for the vehicle-bridge contact-point responses during the passage of a two-axle vehicle over a beam bridge under the assumption of neglecting the vehicle-bridge coupling effect. The residual contact-point responses were obtained by subtracting the time-delayed contact-point response of the front axle from that of the rear axle. A synchronous identification method of bridge frequencies and mode shapes was established by applying a dual-peak idealized spectrum filter and the Hilbert transform on the residual contact-point responses. Secondly, a numerical finite element simulation program was developed with the consideration of the vehicle-bridge coupling effect to verify the accuracy of theoretical derivations. The bridge frequency and mode shape were successfully extracted. Finally, more adverse road surface roughness conditions were analyzed to examine the effectiveness of the proposed method. The results demonstrated that the contact-point residual response is not influenced by the vehicle and road roughness when neglecting the vehicle-bridge coupling effect. This makes it possible to accurately identify bridge modal parameters. Numerical finite element simulations validated that the contact-point responses indirectly calculated through vehicle responses, interpolated by bridge node responses, and computed by theoretical derivations are highly consistent. This consistency extended to scenarios with low-grade road surface roughness. However, when road surface roughness was worse, the vehicle-bridge coupling effect led to the inclusion of vehicle frequency components in the contact-point residual responses, making it difficult for indirect identification. It is suggested that when utilizing the contact-point residual response for identifying bridge modal properties, strategies such as reducing vehicle speed or optimizing the test vehicle should be employed to mitigate the negative impact of vehicle-bridge coupling effects.

Key words

Bridge Engineering, Vehicle Scanning Method / Modal Property / Indirect Measurement / Two-axle Vehicle / Contact-point Residual Response

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

CHENG Jianting1, LIN Zikang2, WU Xiaosheng1, WANG Shenning1, ZHOU Junyong2. Identification method of bridge modal characteristics based on vibration response of 2-axle vehicle passing through bridge[J]. Journal of Vibration and Shock, 2024, 43(13): 78-89

References

[1] ZHANG C, MOUSAVI A A, MASRI S F, et al. Vibration feature extraction using signal processing techniques for structural health monitoring: a review [J]. Mechanical Systems and Signal Processing, 2022, 177: 109175. [2] HE Z, LI W, SALEHI H, et al. Integrated structural health monitoring in bridge engineering [J]. Automation in Construction, 2022, 136: 104168. [3] 王凌波, 王秋玲, 朱钊, 等. 桥梁健康监测技术研究现状及展望[J]. 中国公路学报, 2021, 34(12): 25-45. WANG Lingbo, WANG Qiuling, ZHU Zhao, et al. Current status and prospects of research on bridge health monitoring technology [J]. China Journal of Highway and Transport, 2021, 34(12): 25-45. [4] 孙利民, 尚志强, 夏烨. 大数据背景下的桥梁结构健康监测研究现状与展望[J]. 中国公路学报, 2019, 32(11): 1-20. SUN Limin, SHANG Zhiqiang, XIA Ye. Development and prospect of bridge structural health monitoring in the context of big data [J]. China Journal of Highway and Transport, 2019, 32(11): 1-20. [5] YANG Y B, LIN C W, YAU J D. Extracting bridge frequencies from the dynamic response of a passing vehicle [J]. Journal of Sound and Vibration, 2004, 272(3/4/5): 471-493. [6] 杨永斌, 王志鲁, 史康, 等. 基于车辆响应的桥梁间接测量与监测研究综述[J]. 中国公路学报, 2021, 34(10): 1-12. YANG Yongbin, WANG Zhilu, SHI Kang, et al. Research progress on bridge indirect measurement and monitoring from moving vehicle response [J]. China Journal of Highway and Transport, 2021, 34(10): 1-12. [7] WANG Z, YANG J P, SHI K, et al. Recent advances in researches on vehicle scanning method for bridges [J]. International Journal of Structural Stability and Dynamics, 2022, 22(15): 2230005. [8] YANG Y B, CHEN W F, YU H W, et al. Experimental study of a hand-drawn cart for measuring the bridge frequencies[J]. Engineering Structures, 2013, 57: 222-231. [9] NAGAYAMA T, REKSOWARDOJO A P, SU D, et al. Bridge natural frequency estimation by extracting the common vibration component from the responses of two vehicles [J]. Engineering Structures, 2017, 150: 821-829. [10] 阳洋, 梁晋秋, 袁爱鹏, 等. 基于桥梁单元刚度损伤识别的新型间接量测方法研究[J]. 中国公路学报, 2021, 34(2): 188-198. YANG Yang, LIANG Jinqiu, YUAN Aipeng, et al. Bridge element bending stiffness damage identification based on new indirect measurement method [J]. China Journal of Highway and Transport, 2021, 34(2): 188-198. [11] LIU C, ZHU Y, YE H. Bridge frequency identification based on relative displacement of axle and contact point using tire pressure monitoring [J]. Mechanical Systems and Signal Processing, 2023, 183: 109613. [12] TAN C, UDDIN N, OBRIEN E J, et al. Extraction of bridge modal parameters using passing vehicle response [J]. Journal of Bridge Engineering, 2019, 24(9): 04019087. [13] ZHANG Y, ZHAO H, LIE S T. Estimation of mode shapes of beam-like structures by a moving lumped mass [J]. Engineering Structures, 2019, 180: 654-668. [14] CORBALLY R, MALEKJAFARIAN A. Bridge damage detection using operating deflection shape ratios obtained from a passing vehicle [J]. Journal of Sound and Vibration, 2022, 537: 117225. [15] ZHOU J, LU Z, ZHOU Z, et al. Extraction of bridge mode shapes from the response of a two-axle passing vehicle using a two-peak spectrum idealized filter approach [J]. Mechanical Systems and Signal Processing, 2023, 190: 110122. [16] YANG Y B, LI Z, WANG Z L, et al. A novel frequency-free movable test vehicle for retrieving modal parameters of bridges: theory and experiment [J]. Mechanical Systems and Signal Processing, 2022, 170: 108854. [17] ZHANG B, QIAN Y, WU Y, et al. An effective means for damage detection of bridges using the contact-point response of a moving test vehicle [J]. Journal of Sound and Vibration, 2018, 419: 158-172. [18] KONG X, CAI C S, KONG B. Numerically extracting bridge modal properties from dynamic responses of moving vehicles [J]. Journal of Engineering Mechanics, 2016, 142(6): 04016025. [19] YANG Y B, XU H, WANG Z L, et al. Using vehicle–bridge contact spectra and residue to scan bridge's modal properties with vehicle frequencies and road roughness eliminated [J]. Structural Control and Health Monitoring, 2022, 29(8): e2968. [20] HU Z, LIN P, GUO H, et al. Detect the stiffness transition in beam structures by using the passive tap-scan method [J]. Mechanical Systems and Signal Processing, 2023, 192: 110211. [21] 何卫, 何珂文, 王国波. 基于频率变化的有载桥梁模态振型识别改进方法[J]. 振动与冲击, 2023, 42(9): 189-196. HE Wei, HE Kewen, WANG Guobo. An improved method for modal shape identification of loaded bridges based on frequency variation [J]. Journal of Vibration and Shock, 2023, 42(9): 189-196. [22] YANG Y B, ZHANG B, WANG T, et al. Two-axle test vehicle for bridges: Theory and applications [J]. International Journal of Mechanical Sciences, 2019, 152: 51-62. [23] YANG Y B, LI Y C, CHANG K C. Effect of road surface roughness on the response of a moving vehicle for identification of bridge frequencies [J]. Interaction and Multiscale Mechanics, 2012, 5(4): 347-368. [24] 张超东, 黎剑安, 张浩. 基于增轶Kalman滤波的移动车辆荷载在线识别[J]. 振动与冲击, 2022, 41(2): 87-95. ZHANG Chaodong, LI Jian’an, ZHANG Hao. Augmented Kalman filter based moving vehicle loads online identification [J]. Journal of Vibration and Shock, 2022, 41(2): 87-95.