Full Text:   <419>

Summary:  <66>

CLC number: 

On-line Access: 2024-03-13

Received: 2023-02-14

Revision Accepted: 2023-06-26

Crosschecked: 2024-03-13

Cited: 0

Clicked: 537

Citations:  Bibtex RefMan EndNote GB/T7714


Junyuan ZHENG


Duojia SHI


-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE A 2024 Vol.25 No.3 P.206-222


A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China

Author(s):  Junyuan ZHENG, Caiyou ZHAO, Duojia SHI, Ping WANG, Jian WANG, Bolong JIANG, Xi SHENG

Affiliation(s):  Key Laboratory of High-speed Railway Engineering, Ministry of Education, Southwest Jiaotong University, Chengdu 610031, China; more

Corresponding email(s):   zcy848279@163.com

Key Words:  Floating slab track, Support stiffness, Detailed analytical model, Failure identification, Monitoring system

Junyuan ZHENG, Caiyou ZHAO, Duojia SHI, Ping WANG, Jian WANG, Bolong JIANG, Xi SHENG. A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China[J]. Journal of Zhejiang University Science A, 2024, 25(3): 206-222.

@article{title="A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China",
author="Junyuan ZHENG, Caiyou ZHAO, Duojia SHI, Ping WANG, Jian WANG, Bolong JIANG, Xi SHENG",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China
%A Junyuan ZHENG
%A Caiyou ZHAO
%A Duojia SHI
%A Ping WANG
%A Jian WANG
%A Bolong JIANG
%J Journal of Zhejiang University SCIENCE A
%V 25
%N 3
%P 206-222
%@ 1673-565X
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2300085

T1 - A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China
A1 - Junyuan ZHENG
A1 - Caiyou ZHAO
A1 - Duojia SHI
A1 - Ping WANG
A1 - Jian WANG
A1 - Bolong JIANG
J0 - Journal of Zhejiang University Science A
VL - 25
IS - 3
SP - 206
EP - 222
%@ 1673-565X
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2300085

The extensive use of steel spring floating slab tracks has effectively addressed the challenge of alleviating the environmental vibrations induced by urban rail transit systems. However, under the combined action of train dynamic loads and complex environmental factors, problems, such as the fracture of steel spring vibration isolators and suspension vibrations induced by the uneven settlement of the base, often occur. The failure of isolator support stiffness is often hidden in its early stages and is challenging to identify by conventional detection methods. At the same time, it will aggravate the wheel‍–‍rail interaction, accelerate the deterioration of track structure, and even affect the driving safety. This study first establishes a detailed coupled train-floating slab track-foundation analytical model. Then the influence of the vibration isolator support stiffness failure on the dynamic indices of the floating slab track system response is analyzed. A set of defect identification methods that can detect the number of failed steel springs, severity of damage, and their location is proposed. Finally, an intelligent monitoring system for support stiffness of floating slab track is built by combining the density-based spatial clustering of applications with noise algorithm and statistical data analysis and is applied to a rail line in southern China. During a three-year monitoring campaign, a suspension failure and a fracture of a steel spring were each successfully detected and detailed failure information was obtained. Field investigation results were consistent with the damage identification results. After repair, the track structure dynamic response returned to the average pre-damage level and further deterioration had been arrested. The proposed damage identification methods and monitoring system provide an approach for intelligent identification of track structure support stiffness failures.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]AnkrahAA, KimothoJK, MuvengeiOM, 2020. Fusion of model-based and data driven based fault diagnostic methods for railway vehicle suspension. Journal of Intelligent Learning Systems and Applications, 12(3):51-81.

[2]AuerschL, 2017. Static and dynamic behaviours of isolated or unisolated ballast tracks using a fast wavenumber domain method. Archive of Applied Mechanics, 87(3):555-574.

[3]BashirS, AkhtarN, 2022. Development of low-frequency mass spring system for underground high-speed railways. Journal of Vibration Engineering & Technologies, 10(2):559-579.

[4]BerthaM, GolinvalJC, 2017. Identification of non-stationary dynamical systems using multivariate ARMA models. Mechanical Systems and Signal Processing, 88:166-179.

[5]ChandranP, ThieryF, OdeliusJ, et al., 2022. Unsupervised machine learning for missing clamp detection from an in-service train using differential eddy current sensor. Sustainability, 14(2):1035.

[6]CollierM, 2003. A micro-AGV for flexible manufacturing in small enterprises. Integrated Manufacturing Systems, 14(5):442-448.

[7]CongJL, GaoMY, WangY, et al., 2020. Subway rail transit monitoring by built-in sensor platform of smartphone. Frontiers of Information Technology & Electronic Engineering, 21(8):1226-1238.

[8]CuiXL, ChenGX, YangHG, et al., 2016. Study on rail corrugation of a metro tangential track with Cologne-egg type fasteners. Vehicle System Dynamics, 54(3):353-369.

[9]DerschMS, KhachaturianC, EdwardsJR, 2021. Methods to mitigate railway premium fastening system spike fatigue failures using finite element analysis. Engineering Failure Analysis, 121:105160.

[10]DilenaM, LimongelliMP, MorassiA, 2015. Damage localization in bridges via the FRF interpolation method. Mechanical Systems and Signal Processing, 52-53:162-180.

[11]GomesGF, GiovaniRS, 2022. An efficient two-step damage identification method using sunflower optimization algorithm and mode shape curvature (MSDBI–SFO). Engineering with Computers, 38(2):1711-1730.

[12]HongN, LiLS, YaoWR, et al., 2020. High-speed rail suspension system health monitoring using multi-location vibration data. IEEE Transactions on Intelligent Transportation Systems, 21(7):2943-2955.

[13]JamesIII GH, CarneTG, LauferJP, 1995. The natural excitation technique (NExT) for modal parameter extraction from operating structures. Modal Analysis: The International Journal of Analytical and Experimental Modal Analysis, 10(4):260-277.

[14]LamHF, WongMT, YangYB, 2012. A feasibility study on railway ballast damage detection utilizing measured vibration of in situ concrete sleeper. Engineering Structures, 45:284-298.

[15]LiSS, 2020. An improved DBSCAN algorithm based on the neighbor similarity and fast nearest neighbor query. IEEE Access, 8:47468-47476.

[16]LiZW, LiuXZ, LuHY, et al., 2020. Surface crack detection in precasted slab track in high-speed rail via infrared thermography. Materials, 13(21):4837.

[17]LovedayPW, LongCS, RamatloDA, 2020. Ultrasonic guided wave monitoring of an operational rail track. Structural Health Monitoring, 19(6):1666-1684.

[18]NelsonJT, WatryDL, AmatoMA, et al., 2018. Sound transit prototype high performance low frequency floating slab testing and evaluation. In: Anderson D, Gautier PE, Iida M, et al. (Eds.), Noise and Vibration Mitigation for Rail Transportation Systems. Springer, Heidelberg, Germany, p.607-618.

[19]RajaramS, NelsonJT, 2019. High-performance floating slab track: design and construction improvements based on lessons learned from prototype slabs. Transportation Research Record: Journal of the Transportation Research Board, 2673(1):300-309.

[20]RamosA, CorreiaAG, CalçadaR, et al., 2021. Influence of track foundation on the performance of ballast and concrete slab tracks under cyclic loading: physical modelling and numerical model calibration. Construction and Building Materials, 277:122245.

[21]RioG, SoiveA, GrolleauV, 2005. Comparative study of numerical explicit time integration algorithms. Advances in Engineering Software, 36(4):252-265.

[22]ShenZY, HedrickJK, ElkinsJA, 1983. A comparison of alternative creep force models for rail vehicle dynamic analysis. Vehicle System Dynamics, 12(1-3):79-83.

[23]SitharamTG, SebastianR, FazilF, 2018. Vibration isolation of buildings housed with sensitive equipment using open trenches–case study and numerical simulations. Soil Dynamics and Earthquake Engineering, 115:344-351.

[24]TalbotJP, 2016. Base-isolated buildings: towards performance-based design. Proceedings of the Institution of Civil Engineers-Structures and Buildings, 169(8):574-582.

[25]TamagawaS, 2021. Determination of load test conditions for rail fastenings of a floating slab track. International Journal of Computational Methods and Experimental Measurements, 9(1):14-27.

[26]VandiverJK, DunwoodyAB, CampbellRB, et al., 1982. A mathematical basis for the random decrement vibration signature analysis technique. Journal of Mechanical Design, 104(2):307-313.

[27]WangL, ZhaoYN, SangT, et al., 2022. Ultra-low frequency vibration control of urban rail transit: the general quasi-zero-stiffness vibration isolator. Vehicle System Dynamics, 60(5):1788-1805.

[28]WickramasingheWR, ThambiratnamDP, ChanTHT, 2020. Damage detection in a suspension bridge using modal flexibility method. Engineering Failure Analysis, 107:104194.

[29]WilsonGP, SaurenmanHJ, NelsonJT, 1983. Control of ground-borne noise and vibration. Journal of Sound and Vibration, 87(2):339-350.

[30]XuFZ, SongXL, YangJJ, 2020. Influence of steel spring failure of floating slab track on vibration characteristics of infrastructure. In: Tutumluer E, Chen XB, Xiao YJ (Eds.), Advances in Environmental Vibration and Transportation Geodynamics. Springer, Singapore, p.987-998.

[31]YuP, ManaloA, FerdousW, et al., 2021. Failure analysis and the effect of material properties on the screw pull-out behaviour of polymer composite sleeper materials. Engineering Failure Analysis, 128:105577.

[32]YuanXC, ZhuSY, XuL, et al., 2020. Investigation of the vibration isolation performance of floating slab track with rubber bearings using a stochastic fractional derivative model. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 234(9):992-1004.

[33]ZhaoCY, LiuDY, ZhangXM, et al., 2019. Influence of vibration isolator failure on vehicle operation performance and floating slab track structure vibration reduction effectiveness. Shock and Vibration, 2019:8385310.

[34]ZhaoCY, ZhengJY, SangT, et al., 2021. Computational analysis of phononic crystal vibration isolators via FEM coupled with the acoustic black hole effect to attenuate railway-induced vibration. Construction and Building Materials, 283:122802.

[35]ZhuSY, ZhangQL, ZhaiWM, et al., 2021. Sensor deploying for damage identification of vibration isolator in floating-slab track using deep residual network. Measurement, 183:109801.

[36]ZouJH, DuTF, ChenW, et al., 2022. Experimental study of concrete floating slab municipal road with steel spring isolators under vehicle loads. Construction and Building Materials, 315:125686.

Open peer comments: Debate/Discuss/Question/Opinion


Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE