Skip to main content
SpringerLink
Log in

Damage Identification in Simply Supported Bridge Based on Rotational-Angle Influence Lines Method

  • Research Article
  • Published:
Transactions of Tianjin University Aims and scope Submit manuscript

Abstract

To locate and quantify local damage in a simply supported bridge, in this study, we derived a rotational-angle influence line equation of a simply supported beam model with local damage. Using the diagram multiplication method, we introduce an analytical formula for a novel damage-identification indicator, namely the difference of rotational-angle influence lines-curvature (DRAIL-C). If the initial stiffness of the simply supported beam is known, the analytical formula can be effectively used to determine the extent of damage under certain circumstances. We determined the effectiveness and anti-noise performance of this new damage-identification method using numerical examples of a simply supported beam, a simply supported hollow-slab bridge, and a simply supported truss bridge. The results show that the DRAIL-C is directly proportional to the moving concentrated load and inversely proportional to the distance between the bridge support and the concentrated load and the distance between the damaged truss girder and the angle measuring points. The DRAIL-C indicator is more sensitive to the damage in a steel-truss-bridge bottom chord than it is to the other elements.

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
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23

Similar content being viewed by others

References

  1. Li Y, Zhang JQ, Chen YJ et al (2017) Ultimate flexural capacity of a severely damaged reinforced concrete T-girder bridge. J Bridge Eng 22(5):05017003

    Article  Google Scholar 

  2. Tian L, Huang F (2014) Numerical simulation for progressive collapse of continuous girder bridge subjected to ship impact. Trans Tianjin Univ 20(4):250–256

    Article  Google Scholar 

  3. Yang M, Zhong H, Telste M (2016) Bridge damage localization through modified curvature method. J Civ Struct Health Monit 6(2):175–188

    Article  Google Scholar 

  4. Zhen S, Tomonori N, Yozo F (2016) Minimizing noise effect in curvature-based damage detection. J Civ Struct Health Monit 6(2):255–264

    Article  Google Scholar 

  5. Sun GS, Liu CG, Zhang SB et al (2014) Three-step damage identification method based on dynamic characteristics. Trans Tianjin Univ 20(5):379–384

    Article  Google Scholar 

  6. Chang K, Kim C (2016) Modal-parameter identification and vibration-based damage detection of a damaged steel truss bridge. Eng Struct 122:156–173

    Article  Google Scholar 

  7. Xu ZD, Zeng X, Li S (2015) Damage detection strategy using strain-mode residual trends for long-span bridges. J Comput Civ Eng 29(5):04014064

    Article  Google Scholar 

  8. Tatar A, Niousha A, Rofooei FR (2017) Damage detection in existing reinforced concrete building using forced vibration test based on mode shape data. J Civ Struct Health Monit 7(1):1–13

    Article  Google Scholar 

  9. Feng DM, Feng MQ (2016) Output-only damage detection using vehicle-induced displacement response and mode shape curvature index. Struct Control Health Monit 23(8):1088–1107

    Article  Google Scholar 

  10. Xiang CS, Zhou Y, Di SK et al (2014) Detection indicator of structural nondestructive damage based on flexibility curvature difference rate. Appl Mech Mater 744–746(5):46–52

    Google Scholar 

  11. Laory I, Ali NB, Trinh TN et al (2012) Measurement system configuration for damage identification of continuously monitored structures. J Bridge Eng 17(6):857–866

    Article  Google Scholar 

  12. Lee ET, Eun HC (2008) Damage detection of damaged beam by constrained displacement curvature. J Mech Sci Technol 22(6):1111–1120

    Article  Google Scholar 

  13. Chen H, He W, He R (2012) Damage identification for suspender of through and half-through arch bridges based on displacement differences of monitoring points. China J Highw Trans 25(1):83–88 (in Chinese)

    Google Scholar 

  14. Link M, Weiland M (2009) Damage identification by multi-model updating in the modal and in the time domain. Mech Syst Signal Process 23(6):1734–1746

    Article  Google Scholar 

  15. Hiller JE, Roesler JR (2005) Determination of critical concrete pavement fatigue damage locations using influence lines. J Transp Eng 131(8):599–607

    Article  Google Scholar 

  16. Štimac I, Kožar I, Mihanović A (2007) Beam damage detection by deflection influence lines. Gradevinar 59(12):1053–1066

    Google Scholar 

  17. Chen JH, Zhao SB, Yao JT (2014) Superstructure damage identification of existed simply-supported slab bridge based on influence line of symmetrical deflection differential. J Basic Sci Eng 22(2):283–293

    Google Scholar 

  18. Wang YL, Zhang P, An XM (2014) Two-span continuous bridge damage localization method based on vertical support reaction. China J Highw Transp 27(4):79–84

    Google Scholar 

  19. Wang YL, Zhang X, An XM (2015) Damage localization method for simply supported bridge with flexural stiffness uncertainty considered. China J Highw Transp 28(3):82–87

    Google Scholar 

  20. Chen ZW, Cai QL, Lei Y et al (2014) Damage detection of long-span bridges using stress influence lines incorporated control charts. Sci China Technol Sci 57(9):1689–1697

    Article  Google Scholar 

  21. Chen ZW, Zhu SY, Xu YL et al (2015) Damage detection in long suspension bridges using stress influence lines. J Bridge Eng 20(3):05014013

    Article  Google Scholar 

  22. Zhu SY, Chen ZW, Cai QL et al (2014) Locate damage in long-span bridges based on stress influence lines and information fusion technique. Adv Struct Eng 17(8):1089–1102

    Article  Google Scholar 

  23. Sun SW, Sun LM, Chen L (2016) Damage detection based on structural responses induced by traffic load: methodology and application. Int J Struct Stab Dyn 16(4):1640026

    Article  MathSciNet  Google Scholar 

  24. Du YF, Liu YS, Wang XQ (2009) Damage identification of simply-supported beam bridges based on influence line curvature of deflection differential values. Bridge Contract 31(4):80–83

    Google Scholar 

  25. Zhang YQ, Sun K (2016) Analysis of displacement influence line for railway bridge with rotatable elastic support and local damage. J China Railw Soc 38(2):124–130 (in Chinese)

    Google Scholar 

  26. Zhong H, Yang MJ (2016) Damage detection for plate-like structures using generalized curvature mode shape method. J Civ Struct Health Monit 6(1):141–152

    Article  Google Scholar 

  27. Chandrashekhar M, Ganguli R (2009) Damage assessment of structures with uncertainty by using mode shape curvatures and fuzzy logic. J Sound Vib 326:939–957

    Article  Google Scholar 

  28. Law SS, Zhu XQ (2005) Nonlinear characteristics of damaged concrete structures under vehicular load. J Struct Eng 131(8):1277–1285

    Article  Google Scholar 

  29. Pawletko R (2015) Analysing applicability of selected methods to smooth indicator diagrams of marine medium-speed engine. Pol Marit Res 22(2):55–61

    Article  Google Scholar 

  30. Navabian N, Bozorgnasab M, Taghipour R et al (2016) Damage identification in plate-like structure using mode shape derivatives. Arch Appl Mech 86(5):819–830

    Article  Google Scholar 

  31. Nie JG, Zhu L (2014) Beam-truss model of steel-concrete composite box-girder bridges. J Bridge Eng 19(7):04014023

    Article  Google Scholar 

  32. Théoret P, Massicotte B, Conciatori D (2012) Analysis and design of straight and skewed slab bridges. J Bridge Eng 17(2):289–301

    Article  Google Scholar 

  33. Yuan AM, Qian SL, He Y et al (2015) Capacity evaluation of a prestressed concrete adjacent box girder with longitudinal cracks in the web. J Perform Constr Facil 29(1):04014028

    Article  Google Scholar 

  34. Wang J, Chen C, Xiang H et al (2017) Performance of the transverse connectivity in simply supported girder bridges and its strengthening strategy. J Perform Constr Facil 31(5):04017081

    Article  Google Scholar 

  35. Liu J (2012) Shannon wavelet spectrum analysis on truncated vibration signals for machine incipient fault detection. Meas Sci Technol 23(5):055604

    Article  Google Scholar 

  36. Zhu X, Rizzo P (2014) Sensor array for the health monitoring of truss structures by means of guided ultrasonic waves. J Civ Struct Health Monit 4(3):221–234

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Natural Science Foundation of China (Nos. 51608245 and 51568041) and Natural Science Foundation of Gansu Province (Nos. 148RJZA026 and 2014GS02269).

Author information

Authors and Affiliations

  1. School of Civil Engineering, Lanzhou University of Technology, Lanzhou, 730050, China

    Yu Zhou, Shengkui Di, Changsheng Xiang, Wanrun Li & Lixian Wang

  2. Northwest Center for Disaster Mitigation in Civil Engineering, Ministry of Education, Lanzhou, 730050, China

    Yu Zhou, Changsheng Xiang & Wanrun Li

Authors
  1. Yu Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shengkui Di
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Changsheng Xiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wanrun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lixian Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yu Zhou.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, Y., Di, S., Xiang, C. et al. Damage Identification in Simply Supported Bridge Based on Rotational-Angle Influence Lines Method. Trans. Tianjin Univ. 24, 587–601 (2018). https://doi.org/10.1007/s12209-018-0135-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12209-018-0135-9

Keywords

Search

Navigation