Analysis and control method for track irregularity on kilometer-level span high-speed railway bridges based on multivariate empirical wavelet transform

Ruifeng Han , Junhua Xiao , Yuxiao Zhang , Shehui Tan , Ruoyu Han

Railway Engineering Science ›› : 1 -23.

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Railway Engineering Science ›› :1 -23. DOI: 10.1007/s40534-026-00453-4
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Analysis and control method for track irregularity on kilometer-level span high-speed railway bridges based on multivariate empirical wavelet transform
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Abstract

To address the challenge that track irregularity on kilometer-level span high-speed railway bridges exhibits significant temperature-dependent time-varying characteristics, while traditional methods are insufficient to achieve modal consistency in decomposition and long-term effective regulation, this paper proposes a multi-dimensional analysis and differential regulation method based on the multivariate empirical wavelet transform (MEWT). An averaged normalized spectrum is constructed from multi-period track vertical deviation data to enable simultaneous decomposition and wavelength alignment of irregularity modes under different temperatures. The optimal unit length of 84 m is determined using weighted joint Shannon entropy, and a feature matrix is established from three dimensions: temperature correlation, historical chord measurement extreme value, and relative energy fluctuation intensity. The HDBSCAN (hierarchical density-based spatial clustering of applications with noise) method classifies bridge units into four categories. Then, a differential regulation strategy and adjustment optimization algorithm is developed for temperature-sensitive modes. Validation using 26 periods of measured data from the Wufengshan Yangtze River Bridge demonstrates that MEWT achieves a coefficient of variation for modal wavelengths below 0.09. Under the reference temperature of 17 °C, the maximum 60-m mid-chord offset is reduced from 10.93 to 1.73 mm, a reduction of 84.17%. Within the extreme temperature range of 0.2–31.5 °C, all regulated chord values are maintained within 2 mm, demonstrating enhanced regularity retention capability. By reasonably retaining long-wave thermal deformation components, invalid adjustments are effectively avoided, reducing engineering complexity and maintenance costs.

Keywords

Kilometer-level span bridge / High-speed railway / Track irregularity / Multivariate empirical wavelet transform / Differential regulation / Modal consistency / Shannon entropy

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Ruifeng Han, Junhua Xiao, Yuxiao Zhang, Shehui Tan, Ruoyu Han. Analysis and control method for track irregularity on kilometer-level span high-speed railway bridges based on multivariate empirical wavelet transform. Railway Engineering Science 1-23 DOI:10.1007/s40534-026-00453-4

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References

[1]

de Miranda M, Marinini L, Affonso R et al (2022) The Design of the new Storstrøm Bridge: design philosophy, structural concepts, fundamental design and innovative construction methods. In: IABSE Reports. May 25–27, 2022. Prague, pp 686–693

[2]

Yang X, Zhou Y, Li X, et al.. Effect of temperature changes on bearing motion of long-span steel truss continuous girder bridge. Constr Build Mater, 2024, 430 136440

[3]

Wang M, Wang X, Li X, et al.. Influence of spatial track alignment of long-span arch bridge on train operational stability. Veh Syst Dyn, 2023, 61(12): 3161-3180

[4]

Sun H, Li C, Zhao L, et al.. High-speed railway track maintenance and irregularity rectification with coupling physical constraint of adjacent fasteners. Constr Build Mater, 2023, 382 131281

[5]

Hwang SH, Kim S, Lee K-C, et al.. Effects of long-wavelength track irregularities due to thermal deformations of railway bridge on dynamic response of running train. Appl Sci, 2018, 8(12): 2549

[6]

Xiao J, Han R, Sun S et al (2025) Analysis and characterization of track vertical deviation in kilometer-level span high-speed railway bridge. Int J Rail Transp 14(4):829–854

[7]

Zhu Z, Ren Z, Zheng W, et al.. Mechanical behavior and track geometry evaluation of long-span cable-stayed bridges with ballastless tracks. Struct Infrastruct Eng, 2026, 22(2): 279-292

[8]

Li R, He Q, Wang X, et al.. An improved chord measurement method for determining track irregularity thresholds on long-span high-speed railway bridges. Mech Syst Signal Process, 2025, 229 112510

[9]

Pu H, Zhao L, Li W, et al.. A global iterations method for recreating railway vertical alignment considering multiple constraints. IEEE Access, 2019, 7: 121199-121211

[10]

Li Y, Wang P, He Q. A rapid optimization method for ballastless track irregularity based on dynamic chord constraints in track maintenance. Comput Aided Civ Infrastruct Eng, 2026, 41 100012

[11]

Shi J, Zhang Y, Chen Y, et al.. A smoothness optimization method for horizontal alignment considering ballasted track maintenance. Comput Aided Civ Infrastruct Eng, 2023, 38(6): 739-761

[12]

Tan S, Wang J, Chen R et al (2025) Evolution and smoothness evaluation of the precise adjustment of track vertical alignment on kilometer-scale railway bridge under multiple influences. Intell Transp Infrastruct 4:liaf024

[13]

Zhang Y, Shi J, Tan S, et al.. A smoothness control method for kilometer-span railway bridges with analysis of track characteristics. Comput Aided Civ Infrastruct Eng, 2025, 40(2): 215-242

[14]

Haigermoser A, Luber B, Rauh J, et al.. Road and track irregularities: measurement, assessment and simulation. Veh Syst Dyn, 2015, 53(7): 878-957

[15]

Li C, He Q, Wang P. Estimation of railway track longitudinal irregularity using vehicle response with information compression and Bayesian deep learning. Comput Aided Civ Infrastruct Eng, 2022, 37(10): 1260-1276

[16]

Lu T, Chen J, Sun X, et al.. The stochastic characteristics of wideband-wavelength track irregularity on Chinese HSRs and its application to dynamic wheel–rail interaction. Veh Syst Dyn, 2025, 63(3): 494-517

[17]

Xin L, Xu L, Zhang J, et al.. Research on characterization methods for track irregularities. Railw Eng Sci, 2026, 34(1): 25-39

[18]

Yun DY, Park HS. Noise-robust structural response estimation method using short-time Fourier transform and long short-term memory. Comput Aided Civ Infrastruct Eng, 2025, 40(7): 859-878

[19]

Lou P, Chen Y, Li Z. A combined method to identify the rail irregularity at welded region. J Vib Control, 2024, 30(7–8): 1438-1448

[20]

Lee JS, Park J, Kim HM, et al.. Damage detection for railway bridges using time-frequency decomposition and conditional generative model. Comput Aided Civ Infrastruct Eng, 2025, 40(7): 959-977

[21]

Chen Z, Cai X, Wang T, et al.. Mapping the relationship between the temperature gradient of CRTS III slab track on bridge and rail deformation in high-speed railways. Structures, 2024, 59 105777

[22]

Zu L, Zhou W, Jiang L, et al.. Time-frequency characteristics investigation and numerical reconstruction of seismic-induced track irregularity for high-speed railway bridge. Structures, 2023, 58 105359

[23]

Wang H, Núñez A, Liu Z, et al.. Analysis of the evolvement of contact wire wear irregularity in railway catenary based on historical data. Veh Syst Dyn, 2018, 56(8): 1207-1232

[24]

Wu W-H, Chen C-C, Jhou J-W, et al.. A rapidly convergent empirical mode decomposition method for analyzing the environmental temperature effects on stay cable force. Comput Aided Civ Infrastruct Eng, 2018, 33(8): 672-690

[25]

Zhou Z, Adeli H. Time-frequency signal analysis of earthquake records using Mexican hat wavelets. Comput Aided Civ Infrastruct Eng, 2003, 18(5): 379-389

[26]

Tanaka T, Mandic DP. Complex empirical mode decomposition. IEEE Signal Process Lett, 2007, 14(2): 101-104

[27]

Rehman N, Mandic DP. Multivariate empirical mode decomposition. Proc R Soc A Math Phys Eng Sci, 2010, 466(2117): 1291-1302

[28]

Wang Z, Wong CM, Rosa A, et al.. Adaptive Fourier decomposition for multi-channel signal analysis. IEEE Trans Signal Process, 2022, 70: 903-918

[29]

Rehman NU, Aftab H. Multivariate variational mode decomposition. IEEE Trans Signal Process, 2019, 67(23): 6039-6052

[30]

Chen Q, Xie L, Su H. Multivariate nonlinear chirp mode decomposition. Signal Process, 2020, 176 107667

[31]

Yang Y, Liu G, Wang X. Time–frequency characteristic analysis method for track geometry irregularities based on multivariate empirical mode decomposition and Hilbert spectral analysis. Veh Syst Dyn, 2021, 59(5): 719-742

[32]

Wang M, Yang C, Ning B, et al.. Influence mechanism of vertical dynamic track irregularity on train operation stability of long-span suspension bridge. Proc Inst Mech Eng Part F J Rail Rapid Transit, 2023, 237(8): 1037-1049

[33]

Costa MA, Costa JN, Andrade AR, et al.. Combining wavelet analysis of track irregularities and vehicle dynamics simulations to assess derailment risks. Veh Syst Dyn, 2023, 61(1): 150-176

[34]

Huang G, Su Y, Kareem A, et al.. Time-frequency analysis of nonstationary process based on multivariate empirical mode decomposition. J Eng Mech, 2016, 14204015065

[35]

Gilles J. Empirical wavelet transform. IEEE Trans Signal Process, 2013, 61(16): 3999-4010

[36]

Sawant SS, Manoharan P. Unsupervised band selection based on weighted information entropy and 3D discrete cosine transform for hyperspectral image classification. Int J Remote Sens, 2020, 41(10): 3948-3969

[37]

Stewart G, Al-Khassaweneh M. An implementation of the HDBSCAN* clustering algorithm. Appl Sci, 2022, 12(5): 2405

[38]

Xin T, Wang P, Ding Y. Effect of long-wavelength track irregularities on vehicle dynamic responses. Shock Vib, 2019, 2019: 4178065

[39]

Xin T, Dai C, Wang J, et al.. Study on control limits for track longitudinal irregularities measured by 60 m chord on high-speed railway. J Vib Control, 2024, 30(21–22): 5097-5109

[40]

Li X, He H, Wang M, et al.. Influence of long-span bridge deformation on driving quality of high-speed trains. Int J Rail Transp, 2024, 12(4): 690-708

[41]

Pang Z, Gao M, Li G, et al.. The wavelength characteristics of vertical deformation and a train dynamics simulation of long-span, cable-stayed bridges under complex loads. Appl Sci, 2025, 15(1): 133

[42]

Wang S, Luo J, Zhu S, et al.. Random dynamic analysis on a high-speed train moving over a long-span cable-stayed bridge. Int J Rail Transp, 2022, 10(3): 331-351

[43]

Dai P, Li H, Wang F, et al.. Key technologies of China high-speed comprehensive inspection train: CIT450. Railw Eng Sci, 2025, 33(3): 414-440

[44]

Chacón JE, Rastrojo AI. Minimum adjusted Rand index for two clusterings of a given size. Adv Data Anal Classif, 2023, 17(1): 125-133

[45]

Xiao J, Han R, Wan H, et al.. Multi-dimensional characteristics investigation of track geometry on kilometer-level span high-speed railway suspension bridge. Structures, 2024, 70 107808

[46]

Zhou Y, Xia Y, Chen B, et al.. Analytical solution to temperature-induced deformation of suspension bridges. Mech Syst Signal Process, 2020, 139 106568

[47]

Wang L, Pan Q, Hu Q, et al.. Experimental and finite element study on seismic performance of steel tube confined concrete columns considering ambient temperature. Eng Struct, 2026, 348 121779

Funding

Key Technologies Research and Development Program(2022YFB2602900)

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