Abstract
Vibration based Structural Health Monitoring was and is still a hot topic in research. Much progress has been made both from the theoretical as well as the practical side. Vibration-based SHM traditionally makes use of uniaxial/triaxial accelerometers or velocity meters. Also sometimes inclinometers are installed. Recent trends in SHM are the use of high-rate GPS receivers [1], wave propagation-based piezoelectric ceramic sensing technology and optical fiber sensors for dynamic strain and temperature measurements [2].
A particular challenge for structural health assessment is the discovery of small local damage. It is well known that for small damages, the changes in natural frequencies remain very low. Moreover, they are considerably influenced by environmental conditions (mainly temperature) [3], which influence has to be eliminated on beforehand [4, 5]. Also modal displacements are rather insensitive to small stiffness perturbations. On the contrary, modal strains (or curvatures) are very receptive to small stiffness changes. Additionally, they immediately spot the damage location. Some authors have tried to derive curvatures from modal displacements but this procedure is very prone to even slight measurement and/or identification errors. Therefore, the key issue is the direct measurement of (modal) strains. However, the development of a distributed strain sensor network able to cope with the very low strain intensities during ambient excitation is still a challenge. In this paper by recent experiments on steel and concrete beams the extreme accuracy of dynamic measurements with optical FBG strain sensors is demonstrated.
Another possibility to obtain precise modal strains would be the development of a transducer that amplifies the strains. In a recent research project, by using Topology Optimization [6], a transducer was developed that measures differential axial displacements over a sufficient long distance and at the same time is upscaling the strains. Results obtained with this transducer are reported.
In this context, a new challenge for Optimal Sensor Placement [7] is to deal with different sensor types, e.g. displacement transducers, accelerometers and strain sensors.
For localization and quantification of damage, the most powerful method is FE-model updating based on minimizing differences between measured and calculated modal parameters [8]. The addition of modal strains to the objective function of the minimization problem will improve the damage identification process.
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Yi, T.H., Li, H.N., Gu, M.: Experimental assessment of high-rate GPS receivers for deformation monitoring of bridge. Measurement 46(1), 420–432 (2013)
Lopez-Higuera, J.M., Cobo, L.R., Incera, A.Q., Cobo, A.: Fiber optic sensors in structural health monitoring. J. Lightwave Technol. 29(4), 587–608 (2011)
Deraemaeker, A., Reynders, E., De Roeck, G., Kullaa, J.: Vibration based structural health monitoring using output-only measurements under changing environment. Mech. Syst. Signal Process. 22(1), 34–56 (2008)
Reynders, E., Wursten, G., De Roeck, G.: Output-only structural health monitoring in changing environmental conditions by means of nonlinear system identification. Struct. Health Monit. 13(1), 82–93 (2014)
Reynders, E., De Roeck, G.: Robust structural health monitoring in changing environmental conditions with uncertain data. In: Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR, 2003, New York, NY, USA, 16–20 June 2013 (2013)
Bendsoe, M.P., Sigmund, O.: Topology Optimization: Theory Methods and Applications. Springer, New York (2003)
Bui, T.T., Reynders E., Lombaert G., De Roeck, G.: Ambient vibration testing of a large truss bridge with optimal sensor placement. In: Gao, G., Tutumluer, E., Chen, Y. (eds.) Recent Advances in Environmental Vibration; Proceedings of the 6th International Symposium on Environmental Vibration. China Scientific Book Services (2013)
Teughels, A., De Roeck, G.: Damage detection and parameter identification by finite element model updating. Arch. Comput. Methods Eng. 12(2), 123–164 (2005)
Peeters, B., De Roeck, G.: Reference-based stochastic subspace identification for output-only modal analysis. Mech. Syst. Signal Process. 13(5), 855–878 (1999)
Reynders, E., De Roeck, G.: Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis. Mech. Syst. Signal Process. 22(3), 617–637 (2008)
Araujo, A., García-Palacios, J., Blesa, J., Tirado, F., Romero, E., Samartín, A., Nieto-Taladriz, O.: Wireless measurement system for structural health monitoring with high time-synchronization accuracy. IEEE Trans. Instrum. Meas. 61(3), 801–810 (2012)
Lourens, E., Papadimitriou, C., Gillijns, S., Reynders, E., De Roeck, G., Lombaert, G.: Joint input-response estimation for structural systems based on reduced-order models and vibration data from a limited number of sensors. Mech. Syst. Signal Process. 29, 310–327 (2012)
Cunha, A., Caetano, E., Magalhães, F., Moutinho, C.: Recent perspectives in dynamic testing and monitoring of bridges. Struct. Control Health Monit. 20(6), 853–877 (2013)
Jonckers, T.: Development of High-accuracy Strain Sensors using Topology Optimization, MSc Thesis, KU Leuven (2016)
Anastasopoulos, D., Moretti, P., Geernaert, T., De Pauw, B., Nawrot, U., De Roeck, G., Berghmans, F., Reynders, E.: Modal strain identification from low-amplitude FBG data using an improved wavelength detection algorithm. In: Bakker, J., Frangopol, D.M., van Breugel, K. (eds.) Proceedings of the 5th International Symposium on Life-Cycle Civil Engineering, IALCCE 2016, pp. 319–326. Delft, The Netherlands, Taylor & Francis (2016)
Anastasopoulos, D., Moretti, P., Geernaert, T., De Pauw, B., Nawrot, U., De Roeck, G., Berghmans, F., Reynders, E.: Identification of modal strains using sub-microstrain FBG data and a novel wavelength-shift detection algorithm. Mech. Syst. Signal Process. 86, 58–74 (2017)
Lamberti, A., Vanlanduit, S., De Pauw, B., Berghmans, F.: A novel fast phase correlation algorithm for peak wavelength detection of fiber bragg grating sensors. Opt. Express 22(6), 7099–7112 (2014)
Reynders, E., Schevenels, M., De Roeck, G.: MACEC 3.3: a Matlab toolbox for experimental and operational modal analysis, BWM-2014-06, KU Leuven, internal report (2014)
Wang, F., Lazarov, B.S., Sigmund, O.: On projection methods, convergence and robust formulations in topology optimization. Struct. Multidisciplinary Optim. 43, 767–784 (2011)
Acknowledgments
The research presented in this paper has been performed within the framework of the project G099014N “Identification and modeling of structural damage”, funded by the Research Foundation Flanders (FWO), Belgium. Their financial support is gratefully acknowledged.
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De Roeck, G., Reynders, E., Anastasopoulos, D. (2018). Assessment of Small Damage by Direct Modal Strain Measurements. In: Conte, J., Astroza, R., Benzoni, G., Feltrin, G., Loh, K., Moaveni, B. (eds) Experimental Vibration Analysis for Civil Structures. EVACES 2017. Lecture Notes in Civil Engineering , vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-67443-8_1
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DOI: https://doi.org/10.1007/978-3-319-67443-8_1
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