Abstract
The identification of changes in the dynamic characteristics which are related to structural damage is the core principle of the vibration-based structural health monitoring (VBSHM). By addressing these changes, engineers can acquire valuable information about the condition of structures. Eigenfrequencies are influenced by environmental factors and this influence can be high enough to completely mask the effect of damage while they are also global structural characteristics and they cannot asses the location of the damage. A promising alternative is the monitoring of modal strains which offers the benefit of high sensitivity to local damage. However, current measurement techniques encounter difficulties in capturing the very small strain (sub-microstrain) levels that occur during ambient or operational excitation with sufficient accuracy and precision.
This research aims to accurately identify the modal strains of a steel I-beam from sub-microstrain data using Fiber-optic Bragg Grating (FBG) sensors. For this purpose, two measurement techniques are compared. In the first, an interrogator that measures all sensors simultaneously and saves the wavelength spectra for further processing is used. A novel signal processing algorithm that identifies the Bragg wavelength shift from low-resolution data with high accuracy and precision is used for processing the spectral data into strain values. In the second, an interrogator that scans each sensor individually with a high-speed sweep and therefore offers a high wavelength resolution is used. The peak-shifts from the reflected wavelength are identified with a built-in peak detection algorithm and subsequently converted into strains. The phase shift that is created between the various FBG sensors due to the sweep is resolved by implementing a novel synchronization technique.
The accuracy of both techniques in identifying the beam’s dynamic characteristics is investigated through an experimental modal analysis. Two chains of multiplexed FBGs directly glued to the flanges of the beam are used as sensors. The beam is excited at low force amplitudes to explore the ability to identify dynamic characteristics from very low Signal-to-Noise-Ratio (SNR) data. Finally, the accuracy of the identified strain mode shapes from the two techniques is assessed by comparison with a validated finite element model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Farrar, C.R., Worden, K.: Structural health monitoring: a machine learning perspective. Wiley, West Sussex (2013)
Rodrigues, C., Félix, C., Lage, A., Figueiras, J.: Development of a long-term monitoring system based on FBG sensors applied to concrete bridges. J. Eng. Struct. 32(8), 1993–2002 (2010)
Brownjohn, J.M.W., Stefano, A., Xu, Y.L., Wenzel, H., Aktan, E.: Vibration-based monitoring of civil infrastructure: challenges and successes. J. Civil Struct. Health Monit. 1(3–4), 79–95 (2011)
Deraemaeker, A., Reynders, E., De Roeck, G., Kullaa, J.: Vibration-based structural health monitoring using output-only measurements under changing environment. J. Mech. Syst. Signal Process. 22(1), 34–56 (2008)
Peeters, B., De Roeck, G.: One-year monitoring of the Z24-Bridge: environmental effects versus damage events. J. Earthquake Eng. Struct. Dynam. 30(2), 149–171 (2001)
Unger, J.F., Teughels, A., De Roeck, G.: Damage detection of a prestressed concrete beam using modal strains. J. Struct. Eng. 131(9), 1456–1463 (2005)
Glisic, B., Inaudi, D.: Fibre Optic Methods for Structural Health Monitoring. Willey, Chichester (2007)
Glisic, B.: Performance and health monitoring of civil structures and infrastructure using long-gauge and distributed fiber optic sensors. In: Proceedings of the 18th International Conference on Transparent Optical Networks (ICTON), Trento, Italy (2016)
Roveri, N., Carcaterra, A., Sestieri, A.: Real-time monitoring of railway infrastructures using fibre Bragg grating sensors. J. Mech. Syst. Sign. Process. 60–61, 14–28 (2015)
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. J. Mech. Syst. Sign. Process. 86, 58–74 (2017)
Lamberti, A., Vanlanduit, S., De Pauw, B., Berghmans, F.: A novel fast phase correlation algorithm for peak wavelenght detection of fiber Bragg grating sensors. J. Optics Exp. 22(6), 7099–7112 (2014)
Maes, K., Reynders, E., Rezayat, A., De Roeck, G., Lombaert, G.: Offine synchronization of data acquisition systems using system identification. J. Sound Vib. 381, 264–272 (2016)
Reynders, E., Houbrechts, J., De Roeck, G.: Fully automated (operational) modal analysis. J. Mech. Syst. Signal Process. 29, 228–250 (2012)
Reynders, E., Schevenels, M., De Roeck, G.: MACEC 3.3: A Matlab toolbox for experimental and operational modal analysis, User’s manual, Report BWM-2014-06. Department of Civil Engineering, KU Leuven, Leuven, Belgium (2014)
Reynders, E., de Roeck, G.: Reference-based combined deterministic–stochastic subspace identification for experimental and operational modal analysis. J. Mech. Syst. Signal Process. 22(3), 617–637 (2008)
Acknowledgements
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. Kristof Maes is a postdoctoral fellow of KU Leuven. The financial support of FWO and KU Leuven is gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Anastasopoulos, D., Maes, K., De Roeck, G., Reynders, E. (2018). A Comparison of Two Data Acquisition Techniques for Modal Strain Identification from Sub-microstrain FBG Data. 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_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-67443-8_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67442-1
Online ISBN: 978-3-319-67443-8
eBook Packages: EngineeringEngineering (R0)