Abstract
In recent years the interest in permanent monitoring of civil structures has raised because of the needs of controlling the ageing of a huge number of existing infrastructures. The recent advances in sensing technologies and data processing have made the installation and operation of permanent monitoring systems more and more attractive. Vibration-based monitoring is based on the analysis of the evolution in time of damage features. A lot of these features are obtained from experimental estimates of the modal parameters. However, these estimates are usually influenced by environmental and operational factors. The variations they induce in the estimates may hide the small changes due to damage, so their influence has to be appropriately considered in practical applications.
Using a large number of experimental data, models relating modal properties and environmental and operational factors can be set. However, the selection of the factors to be measured is typically not straightforward. As an alternative, statistical tools can be used to correct the estimates without the need to measure those factors.
In the present paper, after a review of the available approaches to quantify the influence of environmental and operational factors, the opportunity of applying robust blind source separation techniques in this field is assessed.
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References
Rainieri C, Fabbrocino G (2010) Automated output-only dynamic identification of civil engineering structures. Mech Syst Signal Process 24(3):678–695
Rainieri C, Fabbrocino G, Cosenza E (2011) Near real-time tracking of dynamic properties for standalone structural health monitoring systems. Mech Syst Signal Process 25(8):3010–3026
Doebling SW, Farrar CR, Prime MB, Shevitz DW (1996) Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review, technical report LA-13070-MS, UC-900, Los Alamos National Laboratory, New Mexico 87545
Rainieri C, Fabbrocino G, Cosenza E (2008) Integrated systems for structural health monitoring: worldwide applications and perspectives. In: Proceedings of the fourth European workshop on structural health monitoring, Cracow
Magalhaes F, Cunha A, Caetano E (2012) Vibration based structural health monitoring of an arch bridge: from automated OMA to damage detection. Mech Syst Signal Process 28:212–228
Rainieri C, Fabbrocino G, Manfredi G, Dolce M (2012) Robust output-only modal identification and monitoring of buildings in the presence of dynamic interactions for rapid post-earthquake emergency management. Eng Struct 34:436–446
Rainieri C, Fabbrocino G, Cosenza E (2010) Integrated seismic early warning and structural health monitoring of critical civil infrastructures in seismically prone areas. Struct Health Monit Int J 10(3):291–308
Fabbrocino G, Laorenza C, Rainieri C, Santucci De Magistris F (2009) Seismic monitoring of structural and geotechnical integrated systems. Mater Forum 33:404–419
Rainieri C, Fabbrocino G, Santucci de Magistris F (2013) An integrated seismic monitoring system for a full-scale embedded retaining Wall. Geotech Test J 36(1):1–14
Rainieri C, Fabbrocino G (2011) Operational modal analysis for the characterization of heritage structures. Geofizika 28:127–143
Conte C, Rainieri C, Aiello MA, Fabbrocino G (2011) On-site assessment of masonry vaults: dynamic tests and numerical analysis. Geofizika 28:109–126
Sohn H, Farrar CR, Hemez FM, Shunk DD, Stinemates DW, Nadler BR (2003) A review of structural health monitoring literature: 1996–2001. Technical report LA-13976-MS, UC-900, Los Alamos National Laboratory, New Mexico 87545
Farrar CR, Worden K (2012) Structural health monitoring: a machine learning perspective. Wiley, Chichester, p 631
Farrar CR, Doebling SW, Cornwell PJ, Straser EG (1997) Variability of modal parameters measured on the Alamosa Canyon Bridge. In: Proceedings of IMAC 15, international modal analysis conference, Orlando
Peeters B, De Roeck G (2001) One-year monitoring of the Z24-Bridge: environmental effects versus damage events. Earthq Eng Struct Dyn 30:149–171
Yan A-M, Kerschen G, De Boe P, Golinval J-C (2005) Structural damage diagnosis under varying environmental conditions – Part I: a linear analysis. Mech Syst Signal Process 19:847–864
Deraemaeker A, Reynders E, De Roeck G, Kullaa J (2008) Vibration-based structural health monitoring using output-only measurements under changing environment. Mech Syst Signal Process 22:34–56
Johnson RA, Wichern DW (1992) Applied multivariate statistical analysis. Prentice Hall, Upper Saddle River
Zang C, Friswell MI, Imregun M (2004) Structural damage detection using independent component analysis. Struct Health Monit 3:69–83
Kerschen G, Poncelet F, Golinval JC (2007) Physical interpretation of independent component analysis in structural dynamics. Mech Syst Signal Process 21:1561–1575
Ans B, Herault J, Jutten C (1985) Adaptive neural architectures: detection of primitives. In: Proceedings of COGNITIVA ’85, Paris, pp 593–597
Rainieri C (2014) Perspectives of second-order blind identification for operational modal analysis of civil structures. Shock Vib, Article ID 845106, p 9
Belouchrani A, Abed-Meraim K, Cardoso JF, Moulines E (1997) A blind source separation technique using second-order statistics. IEEE Trans Signal Process 45:434–444
Rainieri C, Gargaro D, Cieri L, Fabbrocino G (2014) Vibration-based continuous monitoring of tensile loads in cables and rods: system development and application. In: Proceedings of IMAC XXXII, Orlando
Rainieri C, Fabbrocino G (2013) Accurate damping estimation by automated OMA procedures. Conf Proc Soc Exp Mech Ser 39(4):1–9
Acknowledgments
The present work has been supported by the ReLuis-DPC Executive Project 2014-2016, Special Project ``Monitoring'', whose contribution is gratefully acknowledged.
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© 2015 The Society for Experimental Mechanics, Inc.
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Rainieri, C., Gargaro, D., Fabbrocino, G. (2015). Statistical Tools for the Characterization of Environmental and Operational Factors in Vibration-Based SHM. In: Niezrecki, C. (eds) Structural Health Monitoring and Damage Detection, Volume 7. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-15230-1_16
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DOI: https://doi.org/10.1007/978-3-319-15230-1_16
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