Damage Detection in Prestressed Concrete Slabs Using Wavelet Analysis of Vibration Responses in the Time Domain

Document Type : Regular Paper

Authors

1 Assistant Professor, Department of Civil Engineering, University of Birjand, Birjand, Iran

2 Associate Professor, Department of Civil Engineering, University of Birjand, Birjand, Iran

3 M.Sc. in Structural Engineering, Civil Engineering Department, Hormozan University of Birjand, Birjand, Iran

Abstract

Detection of damages in structures during their service life is of vital importance and under attention of researchers. In this paper, it is attempted to identify damages in prestressed concrete slabs using vibration responses obtained from modal testing in the time domain. For this purpose, first some damage scenarios with various geometric shapes and at different locations of numerical models, corresponding to a prestressed concrete slab, were created. Next, the impact hammer force in the modal test was simulated and the accelerations time histories at different degrees of freedom corresponding to the numerical models per two states of damaged and undamaged structure were selected as the inputs for a number of damage indices to identify the damage locations. Some of these damage scenarios have been located at the middle of prestressed concrete slabs and some at the corners. The proposed damage indices in this research are obtained based on the area under the diagram of acceleration time histories, maximum and also the area under diagram of detail coefficients of the wavelet transform using the three wavelet families of Daubechies, Biorthogonal and Reverse Biorthogonal. The results showed that using damage index obtained from the area under diagram of detail coefficients of wavelet transform with the mother wavelet db2 could detect the damage scenarios at the middle and corners of the slab with a well precision. Furthermore, the damage scenarios at the corners of numerical models could be detected properly by using the mother wavelet rbio2.2 in the proposed damage index.

Keywords

Main Subjects

References

[1]      Jahangir H, Esfahani MR. Damage localization of Structures Using Adaptive Neuro-Fuzzy Inference System. 7th Natl. Congr. Civ. Eng., Zahedan, Iran: 2013.
[2]      Daneshvar MH, Gharighoran A, Zareei SA, Karamodin A. Early damage detection under massive data via innovative hybrid methods: application to a large-scale cable-stayed bridge. Struct Infrastruct Eng 2020:1–19. https://doi.org/10.1080/15732479.2020.1777572.
[3]      Jahangir H, Khatibinia M, Kavousi M. Application of Contourlet Transform in Damage Localization and Severity Assessment of Prestressed Concrete Slabs. Soft Comput Civ Eng 2021;5:39–67. https://doi.org/10.22115/SCCE.2021.282138.1301.
[4]      Jahangir H, Karamodin A. Structural Behavior Investigation Based on Adaptive Pushover Procedure. 10th Natl. Congr. Civ. Eng., Tehran, Iran: 2015.
[5]      Jahangir H, Bagheri M. Evaluation of Seismic Response of Concrete Structures Reinforced by Shape Memory Alloys (Technical Note). Int J Eng 2020;33. https://doi.org/10.5829/ije.2020.33.03c.05.
[6]      Jahangir H, Esfahani MR. Numerical Study of Bond – Slip Mechanism in Advanced Externally Bonded Strengthening Composites. KSCE J Civ Eng 2018;22:4509–18. https://doi.org/10.1007/s12205-018-1662-6.
[7]      Jahangir H, Esfahani MR. Investigating loading rate and fibre densities influence on SRG - concrete bond behaviour. Steel Compos Struct 2020;34:877–89. https://doi.org/10.12989/scs.2020.34.6.877.
[8]      Jahangir H, Esfahani MR. Experimental analysis on tensile strengthening properties of steel and glass fiber reinforced inorganic matrix composites. Sci Iran 2020. https://doi.org/10.24200/SCI.2020.54787.3921.
[9]      Bagheri M, Chahkandi A, Jahangir H. Seismic Reliability Analysis of RC Frames Rehabilitated by Glass Fiber-Reinforced Polymers. Int J Civ Eng 2019. https://doi.org/10.1007/s40999-019-00438-x.
[10]     Jahangir H, Daneshvar Khoram MH, Esfahani MR. Application of vibration modal data in gradually detecting structural damage (In Persian). 4th Int. Conf. Acoust. Vib., Tehran, Iran: 2014.
[11]     Arefzade T, Hosseini Vaez S, Naderpour H, Ezzodin A. Identifying location and severity of multiple cracks in reinforced concrete cantilever beams using modal and wavelet analysis. J Struct Constr Eng 2016;3:72–83.
[12]     Altunışık AC, Okur FY, Karaca S, Kahya V. Vibration-based damage detection in beam structures with multiple cracks: modal curvature vs. modal flexibility methods. Nondestruct Test Eval 2019;34:33–53. https://doi.org/10.1080/10589759.2018.1518445.
[13]     Daneshvar MH, Gharighoran A, Zareei SA, Karamodin A. Damage Detection of Bridge by Rayleigh-Ritz Method. J Rehabil Civ Eng 2020;8:111–20. https://doi.org/10.22075/JRCE.2019.17603.1337.
[14]     Singh J, Roy AK. Wind Pressure Coefficients on Pyramidal Roof of Square Plan Low Rise Double Storey Building. Comput Eng Phys Model 2019;2:1–16. https://doi.org/10.22115/cepm.2019.144599.1043.
[15]     Seyedi SR, Keyhani A, Jahangir H. An Energy-Based Damage Detection Algorithm Based on Modal Data. 7th Int. Conf. Seismol. Earthq. Eng., International Institute of Earthquake Engineering and Seismology (IIEES); 2015, p. 335–6.
[16]     Pahlevan Mosavari, A. Jahangir H, Esfahani MR. The Effect of Sensor Weight on Obtained Data from Modal Tests (In Persian). 9th Natl. Congr. Civ. Eng., Mashhad, Iran: Ferdowsi University of Mashhad; 2016.
[17]     Yang YB, Yang JP. State-of-the-Art Review on Modal Identification and Damage Detection of Bridges by Moving Test Vehicles. Int J Struct Stab Dyn 2018;18:1850025. https://doi.org/10.1142/S0219455418500256.
[18]     Naderpour H, Fakharian P. A synthesis of peak picking method and wavelet packet transform for structural modal identification. KSCE J Civ Eng 2016;20:2859–67. https://doi.org/10.1007/s12205-016-0523-4.
[19]     Jahangir H, Esfahani MR. Structural Damage Identification Based on Modal Data and Wavelet Analysis. 3rd Natl. Conf. Earthq. Struct., Kerman, Iran: 2012.
[20]     Avci O. Amplitude-Dependent Damping in Vibration Serviceability: Case of a Laboratory Footbridge. J Archit Eng 2016;22:04016005. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000211.
[21]     Amabili M. Nonlinear damping in large-amplitude vibrations: modelling and experiments. Nonlinear Dyn 2018;93:5–18. https://doi.org/10.1007/s11071-017-3889-z.
[22]     Li W, Vu V-H, Liu Z, Thomas M, Hazel B. Extraction of modal parameters for identification of time-varying systems using data-driven stochastic subspace identification. J Vib Control 2018;24:4781–96. https://doi.org/10.1177/1077546317734670.
[23]     Lu L, Song H, Huang C. Effects of random damages on dynamic behavior of metallic sandwich panel with truss core. Compos Part B Eng 2017;116:278–90. https://doi.org/10.1016/j.compositesb.2016.10.051.
[24]     Rezazadeh Eidgahee D, Rafiean AH, Haddad A. A Novel Formulation for the Compressive Strength of IBP-Based Geopolymer Stabilized Clayey Soils Using ANN and GMDH-NN Approaches. Iran J Sci Technol Trans Civ Eng 2019. https://doi.org/10.1007/s40996-019-00263-1.
[25]     Rezazadeh Eidgahee D, Haddad A, Naderpour H. Evaluation of shear strength parameters of granulated waste rubber using artificial neural networks and group method of data handling. Sci Iran 2019;26:3233–44. https://doi.org/10.24200/sci.2018.5663.1408.
[26]     Naderpour H, Rezazadeh Eidgahee D, Fakharian P, Rafiean AH, Kalantari SM. A new proposed approach for moment capacity estimation of ferrocement members using Group Method of Data Handling. Eng Sci Technol an Int J 2020;23:382–91. https://doi.org/10.1016/j.jestch.2019.05.013.
[27]     Jahangir H, Rezazadeh Eidgahee D. A new and robust hybrid artificial bee colony algorithm – ANN model for FRP-concrete bond strength evaluation. Compos Struct 2021;257:113160. https://doi.org/10.1016/J.COMPSTRUCT.2020.113160.
[28]     Ghorbani B, Arulrajah A, Narsilio G, Horpibulsuk S, Leong M. Resilient moduli of demolition wastes in geothermal pavements: Experimental testing and ANFIS modelling. Transp Geotech 2021;29:100592. https://doi.org/10.1016/j.trgeo.2021.100592.
[29]     Ghorbani B, Arulrajah A, Narsilio G, Horpibulsuk S. Experimental investigation and modelling the deformation properties of demolition wastes subjected to freeze–thaw cycles using ANN and SVR. Constr Build Mater 2020;258:119688. https://doi.org/10.1016/j.conbuildmat.2020.119688.
[30]     Sadrossadat E, Ghorbani B, Hamooni M, Moradpoor Sheikhkanloo MH. Numerical formulation of confined compressive strength and strain of circular reinforced concrete columns using gene expression programming approach. Struct Concr 2018;19:783–94. https://doi.org/10.1002/suco.201700131.
[31]     Kiran KKH, Kori JG. Controlling Blast Loading of the Structural System by Cladding Material. Comput Eng Phys Model 2018;1:79–99. https://doi.org/10.22115/cepm.2018.141294.1038.
[32]     Law SS, Li XY, Zhu XQ, Chan SL. Structural damage detection from wavelet packet sensitivity. Eng Struct 2005;27:1339–48. https://doi.org/10.1016/j.engstruct.2005.03.014.
[33]     Li F, Meng G, Ye L, Lu Y, Kageyama K. Dispersion analysis of Lamb waves and damage detection for aluminum structures using ridge in the time-scale domain. Meas Sci Technol 2009;20:095704. https://doi.org/10.1088/0957-0233/20/9/095704.
[34]     Vieira Filho J, Baptista FG, Inman DJ. Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition. Mech Syst Signal Process 2011;25:1550–8. https://doi.org/10.1016/j.ymssp.2010.12.003.
[35]     Rauter N, Lammering R. Impact Damage Detection in Composite Structures Considering Nonlinear Lamb Wave Propagation. Mech Adv Mater Struct 2015;22:44–51. https://doi.org/10.1080/15376494.2014.907950.
[36]     Patel SS, Chourasia AP, Panigrahi SK, Parashar J, Parvez N, Kumar M. Damage Identification of RC Structures Using Wavelet Transformation. Procedia Eng 2016;144:336–42. https://doi.org/10.1016/j.proeng.2016.05.141.
[37]     Qu H, Li T, Chen G. Adaptive wavelet transform: Definition, parameter optimization algorithms, and application for concrete delamination detection from impact echo responses. Struct Heal Monit 2018:147592171877620. https://doi.org/10.1177/1475921718776200.
[38]     Naito H, Bolander JE. Damage detection method for RC members using local vibration testing. Eng Struct 2019;178:361–74. https://doi.org/10.1016/j.engstruct.2018.10.031.
[39]     Jahangir H, Esfahani MR. Strain of Newly – Developed Composites Relationship in Flexural Tests (In Persian). J Struct Constr Eng 2018;5:92–107. https://doi.org/10.22065/jsce.2017.91828.1255.
[40]     Ghalehnovi M, Yousefi M, Karimipour A, de Brito J, Norooziyan M. Investigation of the Behaviour of Steel-Concrete-Steel Sandwich Slabs with Bi-Directional Corrugated-Strip Connectors. Appl Sci 2020;10:8647. https://doi.org/10.3390/app10238647.
[41]     Chaboki HR, Ghalehnovi M, Karimipour A, de Brito J, Khatibinia M. Shear behaviour of concrete beams with recycled aggregate and steel fibres. Constr Build Mater 2019;204:809–27. https://doi.org/10.1016/j.conbuildmat.2019.01.130.
[42]     Karimipour A, Edalati M. Shear and flexural performance of low, normal and high-strength concrete beams reinforced with longitudinal SMA, GFRP and steel rebars. Eng Struct 2020;221:111086. https://doi.org/10.1016/j.engstruct.2020.111086.
[43]     Karimipour A, Ghalehnovi M. Comparison of the effect of the steel and polypropylene fibres on the flexural behaviour of recycled aggregate concrete beams. Structures 2021;29:129–46. https://doi.org/10.1016/j.istruc.2020.11.013.
[44]     Ghalehnovi M, Karimipour A, Anvari A, de Brito J. Flexural strength enhancement of recycled aggregate concrete beams with steel fibre-reinforced concrete jacket. Eng Struct 2021;240:112325. https://doi.org/10.1016/j.engstruct.2021.112325.
[45]     Jahangir H, Bagheri M, Delavari SMJ. Cyclic Behavior Assessment of Steel Bar Hysteretic Dampers Using Multiple Nonlinear Regression Approach. Iran J Sci Technol Trans Civ Eng 2021;45:1227–51. https://doi.org/10.1007/s40996-020-00497-4.
[46]     Mallat S. A wavelet tour of signal processing. London, UK: Academic Press; 1999.
[47]     Hanteh M, Rezaifar O, Gholhaki M. Selecting the appropriate wavelet function in the damage detection of precast panel building based on experimental results and numerical method. Sharif J Civ Eng 2021. https://doi.org/10.24200/J30.2020.56237.2812.
[48]     Hanteh M, Rezaifar O, Gholhaki M. Selecting the appropriate wavelet function in the damage detection of precast full panel building based on experimental results and wavelet analysis. J Civ Struct Heal Monit 2021;11:1013–36. https://doi.org/10.1007/s13349-021-00497-6.
[49]     Ovanesova AV, Suárez LE. Applications of wavelet transforms to damage detection in frame structures. Eng Struct 2004;26:39–49. https://doi.org/10.1016/j.engstruct.2003.08.009.
[50]     Fakharian P. Structural Damage Detection Using Wavelet Packet Transform and Improved Peak-Picking Method. Semnan University, 2014.
[51]     Fakharian P, Naderpour H. Damage Severity Quantification Using Wavelet Packet Transform and Peak Picking Method. Pract Period Struct Des Constr 2022;27. https://doi.org/10.1061/(ASCE)SC.1943-5576.0000639.
[52]     Hanteh M, Rezaifar O, Gholhaki M. Damage Detection in Precast Full Panel Building Based on Experimental Results and Continuous Wavelet Analysis Analytical Method. Modares Civ Eng J 2021;21.
[53]     Rasouli A, Kourehli SS, Ghodrati Amiri G, Kheyroddin A. A Two-Stage Method for Structural Damage Prognosis in Shear Frames Based on Story Displacement Index and Modal Residual Force. Adv Civ Eng 2015;2015:1–15. https://doi.org/10.1155/2015/527537.
[54]     Gao RX, Yan R. Wavelets: Theory and applications for manufacturing. Boston, MA: Springer US; 2011. https://doi.org/10.1007/978-1-4419-1545-0.
[55]     Hanteh M, Rezaifar O. Damage detection in precast full panel building by continuous wavelet analysis analytical method. Structures 2021;29:701–13. https://doi.org/10.1016/j.istruc.2020.12.002.
[56]     Pahlevan Mosavari M. Damage detection on slabs using modal analysis. Ferdowsi University of Mashhad, 2014.
[57]     Lubliner J, Oliver J, Oller S, Oñate E. A plastic-damage model for concrete. Int J Solids Struct 1989;25:299–326. https://doi.org/10.1016/0020-7683(89)90050-4.
[58]     Oñate E, Oller S, Oliver J, Lubliner J. A constitutive model for cracking of concrete based on the incremental theory of plasticity. Eng Comput 1988;5:309–19. https://doi.org/10.1108/eb023750.
[59]     Oller S, Oñate E, Miquel J, Botello S. A plastic damage constitutive model for composite materials. Int J Solids Struct 1996;33:2501–18. https://doi.org/10.1016/0020-7683(95)00161-1.
[60]     Pappalardo CM, Guida D. Adjoint-based optimization procedure for active vibration control of nonlinear mechanical systems. J Dyn Syst Meas Control 2017;139:081010. https://doi.org/10.1115/1.4035609.
[61]     Sohn H, Czarnecki JA, Farrar CR. Structural Health Monitoring Using Statistical Process Control. J Struct Eng 2000;126:1356–63. https://doi.org/10.1061/(ASCE)0733-9445(2000)126:11(1356).
[62]     Sun Z, Chang CC. Statistical Wavelet-Based Method for Structural Health Monitoring. J Struct Eng 2004;130:1055–62. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:7(1055).
[63]     Han J-G, Ren W-X, Sun Z-S. Wavelet packet based damage identification of beam structures. Int J Solids Struct 2005;42:6610–27. https://doi.org/10.1016/j.ijsolstr.2005.04.031.

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  • Receive Date: 09 May 2021
  • Revise Date: 08 September 2021
  • Accept Date: 16 October 2021

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