Application of Contourlet Transform in Damage Localization and Severity Assessment of Prestressed Concrete Slabs

Document Type : Regular Article


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


In this paper, the location and severity of damages in prestressed concrete slabs are assessed using the contourlet transform as a novel signal processing method. To achieve this goal, the numerical models of prestressed concrete slabs were built based on the experimental specimens reported in the previous research works. Then, the single, double, and triple damage scenarios with various geometric shapes (transverse, longitudinal, inclined, and curved slots) at different positions (middle and corners) were created in the models. To assess the severity of damages, the depth of slots was taken constant in the single and double damage scenarios and assumed variable in the triple ones. The vibration mode shapes together with their corresponding curvatures were obtained using the modal analysis. The contourlet transform coefficients of modal curvatures in two states of damaged and undamaged models were taken as the inputs for the proposed damage index. The results show that the proposed damage index has well identified the severity of triple damage scenarios in addition to detecting the location of different single and double damages at the middle and in the vicinity of corner and supports of the prestressed concrete slab models. Furthermore, the proposed damage index has the highest sensitivity rate to damage scenarios with geometric shapes of inclined, curved, transverse, and longitudinal slot, respectively.

Graphical Abstract

Application of Contourlet Transform in Damage Localization and Severity Assessment of Prestressed Concrete Slabs


  • Damage detection of pre-stressed concrete slab conducted by Contourlet transform.
  • Single, double and triple damage scenarios at middle and corners of slab were analyzed.
  • Various transverse, longitudinal, inclined, and curved slots were investigated.
  • Modal curvatures of damaged and undamaged concrete slab were taken as the inputs.
  • Proposed method performs well in damage localization and severity estimation.


Main Subjects

[1]       Yan R, Chen X, Mukhopadhyay SC. Structural Health Monitoring. vol. 26. Cham: Springer International Publishing; 2017. doi:10.1007/978-3-319-56126-4.
[2]       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. doi:10.3390/app10238647.
[3]       Ghalehnovi M, Karimipour A, de Brito J, Chaboki HR. Crack Width and Propagation in Recycled Coarse Aggregate Concrete Beams Reinforced with Steel Fibres. Appl Sci 2020;10:7587. doi:10.3390/app10217587.
[4]       Karimipour A, Rakhshanimehr M, Ghalehnovi M, de Brito J. Effect of different fibre types on the structural performance of recycled aggregate concrete beams with spliced bars. J Build Eng 2021;38:102090. doi:10.1016/j.jobe.2020.102090.
[5]       Karimipour A, de Brito J. Influence of polypropylene fibres and silica fume on the mechanical and fracture properties of ultra-high-performance geopolymer concrete. Constr Build Mater 2021;283:122753. doi:10.1016/j.conbuildmat.2021.122753.
[6]       Rezaiee-Pajand M, Karimipour A, Abad JMN. Crack Spacing Prediction of Fibre-Reinforced Concrete Beams with Lap-Spliced Bars by Machine Learning Models. Iran J Sci Technol Trans Civ Eng 2020. doi:10.1007/s40996-020-00441-6.
[7]       Jahangir H, Bagheri M. Evaluation of Seismic Response of Concrete Structures Reinforced by Shape Memory Alloys (Technical Note). Int J Eng 2020;33. doi:10.5829/ije.2020.33.03c.05.
[8]       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 2020. doi:10.1007/s40996-020-00497-4.
[9]       Santandrea M, Imohamed IAO, Jahangir H, Carloni C, Mazzotti C, De Miranda S, et al. An investigation of the debonding mechanism in steel FRP- and FRCM-concrete joints. 4th Work. New Boundaries Struct. Concr., Capri Island, Italy: 2016, p. 289–98.
[10]     Jahangir H, Esfahani MR. Numerical Study of Bond – Slip Mechanism in Advanced Externally Bonded Strengthening Composites. KSCE J Civ Eng 2018;22:4509–18. doi:10.1007/s12205-018-1662-6.
[11]     Jahangir H, Esfahani MR. Strain of Newly – Developed Composites Relationship in Flexural Tests (In Persian). J Struct Constr Eng 2018;5:92–107. doi:10.22065/jsce.2017.91828.1255.
[12]     Bagheri M, Chahkandi A, Jahangir H. Seismic Reliability Analysis of RC Frames Rehabilitated by Glass Fiber-Reinforced Polymers. Int J Civ Eng 2019. doi:10.1007/s40999-019-00438-x.
[13]     Jahangir H, Esfahani MR. Investigating loading rate and fibre densities influence on SRG - concrete bond behaviour. Steel Compos Struct 2020;34:877–89. doi:10.12989/scs.2020.34.6.877.
[14]     Jahangir H, Esfahani MR. Experimental analysis on tensile strengthening properties of steel and glass fiber reinforced inorganic matrix composites. Sci Iran 2020. doi:10.24200/SCI.2020.54787.3921.
[15]     Seyedpoor SM, Ahmadi A, Pahnabi N. Structural damage detection using time domain responses and an optimization method. Inverse Probl Sci Eng 2019;27:669–88. doi:10.1080/17415977.2018.1505884.
[16]     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. doi:10.24200/sci.2018.5663.1408.
[17]     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. doi:10.1016/j.jestch.2019.05.013.
[18]     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;44:219–29. doi:10.1007/s40996-019-00263-1.
[19]     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. doi:10.1016/j.compstruct.2020.113160.
[20]     Heidari A, Raeisi J. Optimum design of structures against earthquake by simulated annealing using wavelet transform. J Soft Comput Civ Eng 2018;2:23–33. doi:10.22115/SCCE.2018.125682.1055.
[21]     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. doi:10.1007/s12205-016-0523-4.
[22]     Jahangir H, Esfahani MR. Structural Damage Identification Based on Modal Data and Wavelet Analysis. 3rd Natl. Conf. Earthq. Struct., Kerman, Iran: 2012.
[23]     Shah M, Mevada S, of VP-IJ, 2016 undefined. Comparative Study of Diagrid Structures with Conventional Frame Structures. IngentaconnectCom n.d.
[24]     Jiang T, Kong Q, Patil D, Luo Z, Huo L, Song G. Detection of Debonding Between Fiber Reinforced Polymer Bar and Concrete Structure Using Piezoceramic Transducers and Wavelet Packet Analysis. IEEE Sens J 2017;17:1992–8. doi:10.1109/JSEN.2017.2660301.
[25]     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. doi:10.1177/1475921718776200.
[26]     Naito H, Bolander JE. Damage detection method for RC members using local vibration testing. Eng Struct 2019;178:361–74. doi:10.1016/j.engstruct.2018.10.031.
[27]     Mokhtari Masinaei M, Jahangir H, Khatibinia M. Damage Detection in Prestressed Concrete Slabs Using Vibrational Responses in Time Domain. 5th Natl. Conf. Recent Adv. Civ. Eng. Archit. Urban Dev., Shahid Beheshti University, Tehran, Iran: 2019.
[28]     Jahangir H, Esfahani MR. Assessment of structural damage severity using the energy due to dynamic response (In Persian). 2nd Int. Conf. Acoust. Vib., Tehran, Iran: 2012.
[29]     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.
[30]     Moughty JJ, Casas JR. A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions. Appl Sci 2017;7:510. doi:10.3390/app7050510.
[31]     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. doi:10.1142/S0219455418500256.
[32]     Wang S, Xu M. Modal Strain Energy-based Structural Damage Identification: A Review and Comparative Study. Struct Eng Int 2019;29:234–48. doi:10.1080/10168664.2018.1507607.
[33]     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.
[34]     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.
[35]     Daneshvar MH, Gharighoran A, Zareei SA, Karamodin A. Damage Detection of Bridge by Rayleigh-Ritz Method. J Rehabil Civ Eng 2020;8:111–20. doi:10.22075/JRCE.2019.17603.1337.
[36]     Do MN, Vetterli M. Contourlets: a directional multiresolution image representation. Proceedings. Int. Conf. Image Process., vol. 1, IEEE; 2002, p. I-357-I–360. doi:10.1109/ICIP.2002.1038034.
[37]     Shahrokhinasab E, Hosseinzadeh N, Monirabbasi A, Torkaman S. Performance of Image-Based Crack Detection Systems in Concrete Structures. J Soft Comput Civ Eng 2020;4:127–39. doi:10.22115/SCCE.2020.218984.1174.
[38]     Ma C-X, Zhao C-X, Hou Y. Pavement Distress Detection Based on Nonsubsampled Contourlet Transform. 2008 Int. Conf. Comput. Sci. Softw. Eng., IEEE; 2008, p. 28–31. doi:10.1109/CSSE.2008.1027.
[39]     Zhibiao S, Yanqing G. Algorithm on Contourlet Domain in Detection of Road Cracks for Pavement Images. J Algorithm Comput Technol 2013;7:15–25. doi:10.1260/1748-3018.7.1.15.
[40]     Fan Y. A Pavement Cracks Detection Algorithm Based on NSCT Domain. J Inf Comput Sci 2015;12:4791–8. doi:10.12733/jics20106356.
[41]     Qian Q, Dang Q, Zhao C, He J. Recognition of pavement damage types based on features fusion. 2018 Tenth Int. Conf. Adv. Comput. Intell., IEEE; 2018, p. 239–42. doi:10.1109/ICACI.2018.8377613.
[42]     Ai Y, Xu K. Feature extraction based on contourlet transform and its application to surface inspection of metals. Opt Eng 2012;51:113605. doi:10.1117/1.OE.51.11.113605.
[43]     Hajizadeh AR, Salajegheh J, Salajegheh E. Performance evaluation of wavelet and curvelet transforms based-damage detection of defect types in plate structures. Struct Eng Mech 2016;60:667–91. doi:10.12989/sem.2016.60.4.667.
[44]     Li J, Cao B, Nie F, Zhu M. Feature Extraction of Foam Nickel Surface Based on Multi-Scale Texture Analysis. J Adv Comput Intell Intell Informatics 2019;23:175–82. doi:10.20965/jaciii.2019.p0175.
[45]     Vafaie S, Salajegheh E. Comparisons of wavelets and contourlets for vibration-based damage identification in the plate structures. Adv Struct Eng 2019;22:1672–84. doi:10.1177/1369433218824903.
[46]     Mallat S. A wavelet tour of signal processing. London, UK: Academic Press; 1999.
[47]     Burt P, Adelson E. The Laplacian Pyramid as a Compact Image Code. IEEE Trans Commun 1983;31:532–40. doi:10.1109/TCOM.1983.1095851.
[48]     Bamberger RH, Smith MJT. A filter bank for the directional decomposition of images: theory and design. IEEE Trans Signal Process 1992;40:882–93. doi:10.1109/78.127960.
[49]     Po DD-Y, Do MN. Directional multiscale modeling of images using the contourlet transform. IEEE Trans Image Process 2006;15:1610–20. doi:10.1109/TIP.2006.873450.
[50]     Do MN, Vetterli M. The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans Image Process 2005;14:2091–106. doi:10.1109/TIP.2005.859376.
[51]     Pahlevan Mosavari M. Damage detection on slabs using modal analysis. Ferdowsi University of Mashhad, 2014.
[52]     Lubliner J, Oliver J, Oller S, Oñate E. A plastic-damage model for concrete. Int J Solids Struct 1989;25:299–326. doi:10.1016/0020-7683(89)90050-4.
[53]     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. doi:10.1108/eb023750.
[54]     Oller S, Oñate E, Miquel J, Botello S. A plastic damage constitutive model for composite materials. Int J Solids Struct 1996;33:2501–18. doi:10.1016/0020-7683(95)00161-1.
[55]     Pandey AK, Biswas M, Samman MM. Damage detection from changes in curvature mode shapes. J Sound Vib 1991;145:321–32. doi:10.1016/0022-460X(91)90595-B.
[56]     Qiao P, Lu K, Lestari W, Wang J. Curvature mode shape-based damage detection in composite laminated plates. Compos Struct 2007;80:409–28. doi:10.1016/j.compstruct.2006.05.026.