Skip to main content
SpringerLink
Log in

Monitoring of Large-Amplitude Cyclic Cable Tension via Resonance-Enhanced Magnetoelastic Effect

  • Published:
Journal of Nondestructive Evaluation Aims and scope Submit manuscript

Abstract

Cable tension is an important parameter for monitoring the health of cable-supported bridges. Live loads cause periodic changes in cable tension. Given the lack of test methods for cyclic cable tension, the resonance-enhanced magnetoelastic (REME) effect was adopted for cable tension monitoring. Combining the magnetoelastic effect and the electromagnetic induction theory, the relationship between cable tension and the REME sensor’s induced voltage was deduced. This relationship indicated the feasibility of using the REME effect to monitor cable tension. According to the variation law of cable tension, a cyclic cable tension monitoring experiment was carried out. Based on the experimental results, a cyclic cable tension monitoring method via the REME effect was proposed. When the tension variation amplitude was less than 100% of the design tension, the monitoring error was less than 5%. The proposed method could be used to accurately monitor the large-amplitude cyclic cable tension.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Data Availability

Data will be made available on request.

References

  1. Zhang, H., Li, H., Zhou, J., Tong, K., Xia, R.: A multi-dimensional evaluation of wire breakage in bridge cable based on self-magnetic flux leakage signals. J. Magn. Magn. MATER. 566, 170321 (2023). https://doi.org/10.1016/j.jmmm.2022.170321

    Article  CAS  Google Scholar 

  2. Li, H., Ou, J.: The state of the art in structural health monitoring of cable-stayed bridges. J. Civil Struct. Health Monit. 6(1), 43–67 (2016). https://doi.org/10.1007/s13349-015-0115-x

    Article  Google Scholar 

  3. Li, J., Yi, T., Qu, C., Li, H., Liu, H.: Early warning for abnormal cable forces of cable-stayed bridges considering structural temperature changes. J. Bridge Eng. 28(2), 5797 (2023). https://doi.org/10.1061/JBENF2.BEENG-5797

    Article  Google Scholar 

  4. Zhang, L., Qiu, G., Chen, Z.: Structural health monitoring methods of cables in cable-stayed bridge: a review. Measurement 168, 108343 (2021). https://doi.org/10.1016/j.measurement.2020.108343

    Article  Google Scholar 

  5. Zhang, X., Lu, Y., Cao, M., Li, S., Sumarac, D., Wang, Z.: Instantaneous identification of tension in bridge cables using synchrosqueezing wave-packet transform of acceleration responses. Struct. Infrastruct. E. 2022, 1–16 (2022). https://doi.org/10.1080/15732479.2022.2082492

    Article  Google Scholar 

  6. Weng, J., Chen, L., Sun, L., Zou, Y., Liu, Z., Guo, H.: Fully automated and non-contact force identification of bridge cables using microwave remote sensing. Measurement 209, 112508 (2023). https://doi.org/10.1016/j.measurement.2023.112508

    Article  Google Scholar 

  7. Kim, S.W., Cheung, J.H., Park, J.B., Na, S.O.: Image-based back analysis for tension estimation of suspension bridge hanger cables. Struct. Control. Health Monit. 27(4), 2508 (2020). https://doi.org/10.1002/stc.2508

    Article  Google Scholar 

  8. Wang, J., Wang, X., Fan, C., Li, Y., Huang, X.: Bridge dynamic cable-tension estimation with interferometric radar and APES-based time-frequency analysis. Electron. Switz. 10(4), 501 (2021). https://doi.org/10.3390/electronics10040501

    Article  Google Scholar 

  9. Huang, Y., Fu, J., Wang, R., Gan, Q., Liu, A.: Unified practical formulas for vibration-based method of cable tension estimation. Adv. Struct. Eng. 18(3), 405–422 (2015). https://doi.org/10.1260/1369-4332.18.3.405

    Article  Google Scholar 

  10. Wen-ming, Z., Zhi-wei, W., Feng, D., Liu, Z.: Frequency-based tension assessment of an inclined cable with complex boundary conditions using the PSO algorithm. Cornell University Library, Ithaca (2021)

    Google Scholar 

  11. Chaki, S., Bourse, G.: Guided ultrasonic waves for non-destructive monitoring of the stress levels in prestressed steel strands. Ultrasonics 49(2), 162–171 (2009). https://doi.org/10.1016/j.ultras.2008.07.009

    Article  CAS  PubMed  Google Scholar 

  12. Qian, J., Chen, X., Sun, L., Yao, G., Wang, X., Emanuele, R., et al.: Numerical and experimental identification of seven-wire strand tensions using scale energy entropy spectra of ultrasonic guided waves. Shock. Vib. 2018, 1–11 (2018). https://doi.org/10.1155/2018/6905073

    Article  Google Scholar 

  13. Dubuc, B., Ebrahimkhanlou, A., Salamone, S.: Stress monitoring of prestressing strands in corrosive environments using modulated higher-order guided ultrasonic waves. Struct. Health Monit. 19(1), 202–214 (2020). https://doi.org/10.1177/1475921719842385

    Article  Google Scholar 

  14. Liu, Z., Li, S., Liu, L.: Investigation of wave propagation path and damage source 3D localization in parallel steel wire bundle. Struct. Control. Health Monit. 29(10), 3051 (2022). https://doi.org/10.1002/stc.3051

    Article  Google Scholar 

  15. Shi, P.: Magneto-elastoplastic coupling model of ferromagnetic material with plastic deformation under applied stress and magnetic fields. J. Magn. Magn. Mater. 512, 166980 (2020). https://doi.org/10.1016/j.jmmm.2020.166980

    Article  CAS  Google Scholar 

  16. Liu, Z., Liu, S., Xie, C., Bai, G.: Non-invasive force measurement based on magneto-elastic effect for steel wire ropes. IEEE Sens. J. 21(7), 8979–8987 (2021). https://doi.org/10.1109/JSEN.2021.3054416

    Article  ADS  CAS  Google Scholar 

  17. Tang, D., Huang, S., Chen, W., Jiang, J.: Study of a steel strand tension sensor with difference single bypass excitation structure based on the magneto-elastic effect. Smart Mater. Struct. 17(2), 25019 (2008). https://doi.org/10.1088/0964-1726/17/2/025019

    Article  Google Scholar 

  18. Zhang, R., Duan, Y., Zhao, Y., He, X.: Temperature compensation of elasto-magneto-electric (EME) sensors in cable force monitoring using BP neural network. Sens. Basel. 18(7), 2176 (2018). https://doi.org/10.3390/s18072176

    Article  ADS  Google Scholar 

  19. Liu, L., Zhang, S., Zhou, J., Zhang, H., Liu, H., Tan, K., et al.: Prestress monitoring of internal steel strands using the magnetoelastic inductance method. Prog. Electromagn. Res. M. 103, 1–13 (2021). https://doi.org/10.2528/PIERM21040902

    Article  CAS  Google Scholar 

  20. Zhang, S., Zhang, H., Liu, H., Zhou, J., Yin, C., Liao, L.: Resonance enhanced magnetoelastic method with high sensitivity for steel stress measurement. Measurement 186, 110139 (2021). https://doi.org/10.1016/j.measurement.2021.110139

    Article  Google Scholar 

  21. Kim, J., Lee, J., Sohn, H.: Automatic measurement and warning of tension force reduction in a PT tendon using eddy current sensing. Ndt E Int. 87, 93–99 (2017). https://doi.org/10.1016/j.ndteint.2017.02.002

    Article  Google Scholar 

  22. Zhang, S., Zhou, J., Zhang, H., Liao, L., Liu, L.: Influence of cable tension history on the monitoring of cable tension using magnetoelastic inductance method. Struct. Health Monit. 20(6), 3392–3405 (2021). https://doi.org/10.1177/1475921720987987

    Article  Google Scholar 

  23. Wang, X.Y., Chen, M.S., Sun, H.X., Yang, Q.: Relationship of cable tension and temperature based on long-term monitoring data on the cable-stayed bridge. Appl. Mech. Mater. 405–408, 1716–1721 (2013). https://doi.org/10.4028/www.scientific.net/AMM.405-408.1716

    Article  Google Scholar 

  24. Huang, Y., Wang, Y., Fu, J., Liu, A., Gao, W.: Measurement of the real-time deflection of cable-stayed bridge based on cable tension variations. Measurement 119, 218–228 (2018). https://doi.org/10.1016/j.measurement.2018.01.070

    Article  ADS  Google Scholar 

  25. Maljaars, J., Vrouwenvelder, T.: Fatigue failure analysis of stay cables with initial defects: Ewijk bridge case study. Struct. Saf. 51, 47–56 (2014). https://doi.org/10.1016/j.strusafe.2014.05.007

    Article  Google Scholar 

  26. Yang, M., Li, Z., Zhang, M., Wan, J.: Mutual inductance calculation of circular coils sandwiched between 3-layer magnetic mediums for wireless power transfer systems. Electron. Switz. 10(23), 3043 (2021). https://doi.org/10.3390/electronics10233043

    Article  Google Scholar 

  27. Jiles, D.C., Atherton, D.L.: Theory of ferromagnetic hysteresis (invited). J. Appl. Phys. 55(6), 2115–2120 (1984). https://doi.org/10.1063/1.333582

    Article  ADS  CAS  Google Scholar 

  28. Avakian, A., Ricoeur, A.: Constitutive modeling of nonlinear reversible and irreversible ferromagnetic behaviors and application to multiferroic composites. J. Intel. Mat. Syst. Str. 27(18), 2536–2554 (2016). https://doi.org/10.1177/1045389X16634212

    Article  CAS  Google Scholar 

  29. Zhang, S., Zhou, J., Zhou, Y., Zhang, H., Chen, J.: Cable tension monitoring based on the elasto-magnetic effect and the self-induction phenomenon. Materials. 12(14), 2230 (2019). https://doi.org/10.3390/ma12142230

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. Baghel, A.P.S., Kulkarni, S.V.: Dynamic loss inclusion in the Jiles-Atherton (JA) hysteresis model using the original JA approach and the field separation approach. IEEE T Magn. 50(2), 369–372 (2014). https://doi.org/10.1109/TMAG.2013.2284381

    Article  ADS  Google Scholar 

  31. Cao, Y., Yim, J., Zhao, Y., Wang, M.L.: Temperature effects on cable stayed bridge using health monitoring system: a case study. Struct. Health Monit. 5(10), 523–537 (2011). https://doi.org/10.1177/1475921710388970

    Article  Google Scholar 

  32. Sablik, M.J., Jiles, D.C.: Modeling effects of varying torsion in magnetized steel. IEEE T Magn. 36(5), 3248–3250 (2000). https://doi.org/10.1109/20.908756

    Article  ADS  Google Scholar 

  33. Liu, X., Chen, Y., Hu, H., Feng, S., Feng, Z.: Measurement method of natural frequencies and tension forces for cables based on elasto-magnetic sensors calibrated by frequencies. AIP Adv. 12(1), 15301 (2022). https://doi.org/10.1063/5.0073818

    Article  Google Scholar 

  34. Lo, C.C.H., Kinser, E., Jiles, D.C.: Modeling the interrelating effects of plastic deformation and stress on magnetic properties of materials. J. Appl. Phys. 93(10), 6626–6628 (2003). https://doi.org/10.1063/1.1557356

    Article  ADS  CAS  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was supported by the National Natural Science Foundation of China (52308301, 52278291, U20A20314, 52278146), the Postdoctoral Fellowship Program of CPSF (GZC20233339), and the Chongqing Post-doctoral Innovative Talent Support Program (CQBX202315).

Author information

Authors and Affiliations

  1. State Key Laboratory of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing, 400074, China

    Senhua Zhang, Jianting Zhou, Junfeng Xia, Hong Zhang, Kai Tong, Xiaotian Wu & Leng Liao

  2. School of Civil Engineering, Chongqing Jiaotong University, Chongqing, 400074, China

    Senhua Zhang, Jianting Zhou, Junfeng Xia, Hong Zhang, Kai Tong & Xiaotian Wu

  3. School of Materials Science and Engineering, Chongqing Jiaotong University, Chongqing, 400074, China

    Leng Liao

Authors
  1. Senhua Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianting Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junfeng Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kai Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiaotian Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Leng Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: LL. Methodology: SZ, LL. Investigation: SZ, KT, JX. Validation: SZ, HZ, LL. Data Curation: SZ, KT, XW. Writing-Original Draft: SZ. Writing—Review and Editing: SZ, LL. Software: JX, HZ, XW. Supervision: JZ. Project administration: JZ.

Corresponding author

Correspondence to Leng Liao.

Ethics declarations

Competing interests

No, I declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper.

Ethical Approval

Not applicable.

Informed Consent

Not applicable.

Consent for Publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, S., Zhou, J., Xia, J. et al. Monitoring of Large-Amplitude Cyclic Cable Tension via Resonance-Enhanced Magnetoelastic Effect. J Nondestruct Eval 43, 25 (2024). https://doi.org/10.1007/s10921-023-01039-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10921-023-01039-4

Keywords

Search

Navigation