Abstract
Introduction
Structural damage and its extent can be detected by vibration-based techniques to avoid failure or to minimize maintenance. Among different damage identification techniques, modal curvature approaches are widely researched and applied one. On the contrary, wavelet transformation (WT) methods are gaining popularity in damage identification of real life buildings because of their suitability for non-stationary signals and non-dependency on baseline data. This paper presents a novel approach utilizing complex continuous wavelet to effectively locate change in physical properties of reinforced concrete (RC) buildings by virtue of variation in frequency and mode shapes due to small change in mass and stiffness.
Methods
In this paper, the effect of variation of mass and stiffness of a building on the modal parameters is established analytically using theequation of motion for a multi-degree freedom system under forced vibration condition. A 3-D finite element model was developed for predicting the modal frequencies and mode shapes of the scaled down six storey RC building and the effect of addition of mass on a particular level of structure on the modal parameters was studied. Further, acceleration time histories were recorded with variation in mass on 3rd story of building using wireless tri-axial accelerometers and the time histories were processed to arrive at Curvature Damage Factor and wavelet coefficients for identification of the additional load on the particular floor.
Results
Vibration responses from all floors of RC building in ambient and loaded conditions were analyzed for frequency response spectra (FRS). Mode shapes were drawn for unloaded case and loaded cases. It was observed that the modal frequency of building decreases with the increase in mass at floors. It is observed that CDF approach could detect the change in mass in both numerical and experimental results. However, CDF algorithm could not detect the addition of load in case 1, 2 and 3, i.e. when load was less than 25 kg, i.e. only 2.6% of floor mass (960 kg). The acquired data for the above stated load cases were analyzed using complex Gaussian ‘cgau5’ wavelet in MATLAB toolbox to determine the singularity in the signal in terms of wavelet coefficient modulus. It is observed that the WT approach is able to precisely locate the change in physical parameters of the RC model building. However, it is seen that additional load could not be detected in case where only 9 kg, i.e. 0.93% of the total floor mass, was placed on 3rd floor.
Conclusions
From the research work, it is observed that CDF technique is inefficient in damage detection and always demand prior baseline information, which is usually difficult to obtain in practice. However, the wavelet transform-based approach more accurately detects the location of change without relying on intact state vibration data.
Similar content being viewed by others
References
Koohdaragh M, Lotfollahi-Yaghin MA, Ettefagh MM, Mojtehedi A, Beyghbabaye B (2011) Damage detection in beam-like structure based on wavelet packet. Sci Resa Essays 6(7):1537–1545
Rytter A (1993) Vibration based inspection of civil engineering structures. Ph.D. dissertation, Department of Building Technology and Structural Engineering, Aalborg University, Denmark, vol R9314, no 44
Cawley P, Adams RD (1979) The location of defects in structures from measurements of natural frequencies. J Strain Anal 14(2):49–57
Fan W, Qiao P (2011) Vibration-based damage identification methods: a review and comparative study. Struct Health Monit 10(1):83–111
Patel SS, Chourasia AP, Panigrahi SK, Parashar J, Parvez N, Kumar M (2016) Damage identification of RC structures using wavelet transformation. Procedia Eng 144:336–342
Amiri GG, Asadi A (2009) Comparison of different methods of wavelet and wavelet packet transform in processing ground motion records. Int J Civil Eng 7(4):248–257
Staszewski WJ, Tomlinson GR (1994) Application of the wavelet transform to fault detection in a spur gear. J Mech Syst Signal Process 8(3):289–307
Wang WJ, McFadden PD (1996) Application of wavelets to gearbox vibration signals for fault detection. J Sound Vib 192(5):927–939
Hou Z, Noori M, Amand RS (2000) Wavelet-based approach for structural damage detection. J Eng Mech 126(7):677–683
Mallat S (2001) A wavelet tour of signal processing. Academic Press, San Diego
Moyo P, Brownjohn JMW (2002) Detection of anomalous structural behavior using wavelet analysis. Mech Syst Signal Process 16(2–3):429–445
Sun Z, Chang CC (2002) Structural damage assessment based on wavelet packet transform. J Struct Eng 128(10):1354–1361
Amaravadi V, Rao V, Koval LR, Derriso MM (2011) Structural health monitoring using wavelet transforms. In: Proceedings of SPIE, smart structures and materials 2001: smart structures and integrated systems, vol 4327, pp 258–269
Gurley K, Kijewski T, Kareem A (2003) First and higher order correlation detection using wavelet transforms. J Eng Mech 129(2):188–201
Jaya Prakash G, Swarnamani S (2008) Damage identification in composite beams using continuous wavelet transform applied to mode shape and strain energy data. Adv Vib Eng 7(2):127–141
Gentile A, Messina A (2003) On the continuous wavelet transforms applied to discrete vibrational data for detecting open cracks in damaged beams. Int J Solids Struct 40:95–315
Panigrahi SK, Chakraverty S, Mishra BK (2013) Damage assessment in beam with sparse modal information. Adv Vib Eng 12(4):343–348
Melhem H, Kim H (2003) Damage detection in concrete by Fourier and wavelet analyses. J Eng Mech 129(5):571–577
Kim H, Melhem H (2004) Damage detection of structures by wavelet analysis. J Eng Struct 26:347–362
Ovanesova AV, Suarez LE (2004) Applications of wavelet transforms to damage in frame structures. Eng Struct 26:39–49
Basu B (2005) Identification of stiffness degradation in structures using wavelet analysis. Constr Build Mater 19:713–721
Goggins J, Broderick BM, Basu B, Elghazouli AY (2007) Investigation of seismic response of braced frames using wavelet analysis. Struct Control Health Monit 14:627–648
Radzienski M, Krawczuk M (2009) Experimental verification and comparison of mode shape-based damage detection methods. In: 7th International conference on modern practice in stress and vibration analysis. J Phys Conf Ser, vol 181
Asaee ZS, Anvar SA, Sherafat Z (2011) Comparison of modal parameters of multi-story buildings obtained by different wavelet functions. In: Proceedings of IOMAC11-4th international operational modal analysis conference
Miao XY, Wang SL, Fan YJ (2011) Study on damage identification for reinforced concrete structures based on wavelet transform. Appl Mech Mater 94–96:1505–1510
Noh HY, Nair KK, Lignos DG, Kiremidjian AS (2011) Use of wavelet-based damage-sensitive features for structural damage diagnosis using strong motion data. J Struct Eng 137(10):1215–1228
Xue G (2012) Damage detection of reinforced concrete beams by wavelet analysis. Appl Mech Mater 166–169:1416–1421
Chen B, Chen ZW, Wang GJ, Xie WP (2014) Damage detection on sudden stiffness reduction based on discrete wavelet transform. Sci World J 2014:807620. https://doi.org/10.1155/2014/807620
Buyukozturk O, Yu T (2003) Structural health monitoring and seismic impact assessment. In: Proceedings of fifth national conference on earthquake engineering, Istanbul, Turkey, 26–30 May 2003
Pandey AK, Biswas M, Samman MM (1991) Damage detection from changes in curvature mode shapes. J Sound Vib 145(2):321–332
Wahab MMA, Roeck GD (1999) Damage detection in bridges using modal curvatures: application to a real damage scenario. J Sound Vib 226(2):217–235
Harry HG, Gajanan MS (1999) Structural modeling and experimental techniques, 2nd edn. CRC Press, Washington, DC
Kanwar VS, Kwatra N, Aggarwal P, Gambir ML (2008) Health monitoring of RCC building model experimentally and its analytical validation. Eng Comput Int J Comput Aided Eng Softw 25(7):677–693
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Patel, S.S., Chourasia, A., Panigrahi, S.K. et al. A Study on Efficacy of Wavelet Transform for Damage Identification in Reinforced Concrete Buildings. J. Vib. Eng. Technol. 6, 127–138 (2018). https://doi.org/10.1007/s42417-018-0023-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42417-018-0023-6