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

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

Transactions of Tianjin University ›› 2018, Vol. 24 ›› Issue (6) : 587 -601.

PDF
Transactions of Tianjin University ›› 2018, Vol. 24 ›› Issue (6) : 587 -601. DOI: 10.1007/s12209-018-0135-9
Research Article

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

Author information +
History +
PDF

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.

Keywords

Rotational-angle influence lines / Damage identification / Simply supported bridge / Curvature / Moving load / Anti-noise property

Cite this article

Download citation ▾
Yu Zhou, Shengkui Di, Changsheng Xiang, Wanrun Li, Lixian Wang. Damage Identification in Simply Supported Bridge Based on Rotational-Angle Influence Lines Method. Transactions of Tianjin University, 2018, 24(6): 587-601 DOI:10.1007/s12209-018-0135-9

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

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

[2]

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

[3]

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

[4]

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

[5]

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

[6]

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

[7]

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

[8]

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

[9]

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

[10]

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

[11]

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

[12]

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

[13]

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

[14]

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

[15]

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

[16]

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

[17]

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

[18]

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

[19]

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

[20]

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

[21]

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

[22]

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

[23]

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

[24]

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

[25]

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

[26]

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

[27]

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

[28]

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

[29]

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

[30]

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

[31]

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

[32]

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

[33]

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

[34]

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

[35]

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

[36]

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

AI Summary AI Mindmap
PDF

142

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/