Issue 48

R. S. Y. R. C. Silva et alii, Frattura ed Integrità Strutturale, 48 (2019) 693-705; DOI: 10.3221/IGF-ESIS.48.65 704 C ONCLUSIONS n this paper a methodology based on Continuous Wavelet Transform associated with interpolation and regularization techniques for detection of damage in a real bridge using numerical and experimental data are presented. Two wavelets, Daubechies and Coiflet are applied to the mode shapes obtained. Current research of wavelet analyses for damage assessment leads to the following conclusions.  Damage is successfully localized by the wavelet coefficients that achieved large values in the damaged positions.  The proposed methodology can be implemented without the need for the dynamic data of an intact structure as a starting point for damage detection.  The proposed methodology can be applied to detect damage of small dimension.  The use of a small number of measurement points is a drawback that can be overcome by using interpolation techniques.  Signal noises at the extremities of the structure are due to discontinuities at those positions. At those points damage identification is difficult.  The methodology proposed here can help to reduce bridge inspection tasks. From the results obtained at a few points, using the proposed methodology a possible damage area can be pointed out. Therefore, with that indication, a detailed inspection could be done just in the indicated area. No examination extended to a larger area is necessary.  The proposed methodology in this paper is a reliable approach for damage detection in bridges. R EFERENCES [1] Janeliukstis, R., Rucevskis, S., Wesolowski, M., Chate, A. (2017). Experimental structural damage localization in beam structure using spatial continuous wavelet transform and mode shape curvature methods, Measurement 102, pp. 253- 270. [2] Friswell, M.I. (2007). Damage identification using inverse methods, Phil. Trans. R. Soc. A. 365, pp. 393-410. [3] Fan, W., Qiao, P. (2011). Vibration-based damage identification methods: a review and comparative study, Struct. Health Monit. 10, pp. 83–111. [4] Estrada, E. S. (2008). Damage detection methods in bridges trough vibration monitoring: evaluation and application. Guimarães, Doctoral Thesis, University of Minho, 289p. [5] Silva, R. S. Y. R C. (2015). Monitoring and numerical and experimental identification of damages in steel and concrete beams and bridges using wavelet transform. Brasília, PhD Thesis, University of Brasília, 240p (in Portuguese). [6] Weibing, H., Wei, H., Yu, Z. (2010). Wavelet analysis in damage detection for bridge structure. Key Engineering Materials 417, pp. 813-816. [7] Sun, Z., Chang, C. (2002). Structural damage assessment based on wavelet packet transform. Journal of Structural Engineering 128, pp. 1354-1361. [8] Alvandi, A., Bastien, J., Gregoire, E., Jolin, M. (2009). Bridge integrity assessment by continuous wavelet transforms. International Journal of Structural Stability and Dynamics 9, pp. 11-43. [9] Li, Z. H., Au, F. T. K. (2015). Damage detection of bridges using response of vehicle considering road surface roughness. International Journal of Structural Stability and Dynamics 3, pp. 1-23. [10] Golmohamadi, M., Badri, H., Ebrahimi, A. (2012). Damage diagnosis in bridges using wavelet. International Conference on Technological Advancements in Civil Engineering, Coimbatore, Índia. [11] Rajendran, P., Sivakumar, M. S. (2015). Rotational–mode-shape-based added mass identification using wavelet transform International. Journal for Computational Methods in Engineering Science and Mechanics 16, pp. 182-187. [12] Hester, D., González, A. (2011). A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle. Mechanical Systems and Signal Processing 28, pp. 145-166. [13] Palechor, E. U. L. (2014). Identification of damages in metallic beams using wavelets and numerical and experimental data. Brasília Master Thesis – University of Brasília, 299p (in Portuguese). [14] Tikhonov, A. N., Arsenin, V. Y. (1977). Solutions of Ill-posed Problems. John Wiley, New York. [15] Ovanesova, A. V., Suárez, L. E. (2004). Applications of wavelet transforms to damage detection in frame structures. Journal Engineering Structures 26, pp. 39-49. [16] ARTeMIS. ARTeMIS Extractor pro. Academic license. User’s manual (2009). In:ApS SVS, editor. Aalborg, Denmark. I