Investigation of cross-sensitivities of the potential drop method for structural health monitoring of civil structures
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Erik Schneegans
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Joachim Hug
Abstract
Currently, structural health monitoring (SHM) systems are not in widespread use for monitoring civil structures because of low defect sensitivity and high cross-sensitivities of most SHM techniques available. The potential drop method (PDM), commonly used in material testing, is a possible method for SHM of large metallic civil structures combining high defect sensitivity and high area monitoring capability. The current state of the art lacks experimental evidence of the applicability to large specimens under the demanding operating conditions of SHM. Here, we investigated the PDM as an SHM system experimentally by analyzing the cross-sensitivity to temperature changes and performed a temperature compensation. We present an optimized method for suppressing the unwanted influence of mechanical loads and increasing the defect sensitivity. The temperature influence was separated from the defect-induced impedance change and effectively suppressed by compensation. Thus, cross-sensitivity does not limit PDM in SHM for large metallic civil structures with temperature compensation. PDM is a promising technique for SHM which could facilitate the widespread use of SHM of conductive civil structures.
Zusammenfassung
Die Zustandsüberwachung von Baustrukturen wird aktuell aufgrund der geringen Sensitivität für strukturelle Defekte und hoher Querempfindlichkeiten der verfügbaren Messsysteme nur an einzelnen Bauwerken eingesetzt. Das Potentialsondenverfahren (PSV), welches fast ausschließlich in der Materialprüfung eingesetzt wird, ist eine für die Zustandsüberwachung von großen Metallstrukturen möglicherweise geeignete Methode, da es eine hohe Empfindlichkeit für strukturelle Defekte mit der Fähigkeit, Messobjekte über große Strecken zu überwachen, kombiniert. Nach aktuellem Stand der Technik fehlt jedoch der experimentelle Nachweis der Anwendbarkeit des PSV auf große Messobjekte unter den Betriebsbedingungen des SHM. In diesem Beitrag haben wir das PSV als SHM-System experimentell untersucht und insbesondere die Querempfindlichkeit gegenüber Temperaturänderungen analysiert. Wir stellen einen optimierten Messaufbau zur Unterdrückung des unerwünschten Einflusses mechanischer Belastungen vor und demonstrieren Methoden zur Erhöhung der Defektsensitivität. Die temperaturbedingte Impedanzänderung konnte von einer defektinduzierten Änderung getrennt und durch eine Temperaturkompensation erfolgreich minimiert werden. Bei Anwendung einer Temperaturkompensation stellt die Querempfindlichkeit gegenüber der Temperatur keine grundsätzliche Limitation für den Einsatz des PSV im SHM dar. Das PSV ist somit eine vielversprechende Methode für das SHM, mit der eine weitere Verbreitung von SHM-Systemen für leitfähige Baustrukturen möglich werden könnte.
Funding source: AiF Projekt
Award Identifier / Grant number: KK5403201DB1
About the authors
M. Sc. Erik Schneegans is a research assistant with the Institute for Electrical Information Technology of the Technical University Clausthal. He studied industrial engineering at the University of Kassel until 2021. He is working in the research field of structural health monitoring for metallic structures.
Christian Rembe received the diploma in Physics from the University of Hanover, Germany, in 1994. From 1994 to 1999, he was a doctoral student at the University of Ulm in Germany where he received a doctor degree in Engineering (Dr.-Ing.). In 1999, he joined the Berkeley Sensor & Actuator Center at the University of California, Berkeley as postdoctoral fellow, supported by a Feodor-Lynen-Scholarship of the Alexander von Humboldt-Foundation and a MacKay Lecturer Fellowship from UC Berkeley. From 2001-2014 he was the department head for Development Optics at Polytec GmbH in Waldbronn, Germany. Since 2015, he has been a professor for Applied Metrology at the Clausthal University of Technology in Germany. In 2017, he became head of the Institute for Electrical Information Technology at the TU Clausthal. Since 2020 he has been subject advisor for the Bachelor’s degree program in Electrical Engineering and the Master’s degree program in Electrical Engineering and Information Technology. He is currently chairman of the board of the Arbeitskreis der Hochschullehrer für Messtechnik (AHMT). His main research interests are in the fields of optical metrology and photonic sensors.
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Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This project is funded by the Central Innovation Program for SMEs of the German Federal Ministry for Economic Affairs and Energy (funding code KK5403201DB1).
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
[1] C. R. Farrar and K. Worden, “An introduction to structural health monitoring,” Phil. Trans. Math. Phys. Eng. Sci., vol. 365, no. 1851, pp. 303–315, 2007. https://doi.org/10.1098/rsta.2006.1928.Search in Google Scholar PubMed
[2] P. Cawley, “A development strategy for structural health monitoring applications,” J. Nondestruct. Eval. Diagn. Progn. Eng. Syst., vol. 4, no. 4, 2021. https://doi.org/10.1115/1.4051974.Search in Google Scholar
[3] H. Sohn, “Effects of environmental and operational variability on structural health monitoring,” Phil. Trans. Math. Phys. Eng. Sci., vol. 365, no. 1851, pp. 539–560, 2007. https://doi.org/10.1098/rsta.2006.1935.Search in Google Scholar PubMed
[4] J. Brownjohn, “Structural health monitoring of civil infrastructure,” Phil. Trans. Math. Phys. Eng. Sci., vol. 365, no. 1851, pp. 589–622, 2007. https://doi.org/10.1098/rsta.2006.1925.Search in Google Scholar PubMed
[5] P. Cawley, “Structural health monitoring: closing the gap between research and industrial deployment,” Struct. Health Monit., vol. 17, no. 5, pp. 1225–1244, 2018. https://doi.org/10.1177/1475921717750047.Search in Google Scholar
[6] E. P. Carden and P. Fanning, “Vibration based condition monitoring: a review,” Struct. Health Monit., vol. 3, no. 4, pp. 355–377, 2004. https://doi.org/10.1177/1475921704047500.Search in Google Scholar
[7] A. F. G. Tenreiro, A. M. Lopes, and L. F. M. Da Silva, “A review of structural health monitoring of bonded structures using electromechanical impedance spectroscopy,” Struct. Health Monit., vol. 21, no. 2, pp. 228–249, 2022. https://doi.org/10.1177/1475921721993419.Search in Google Scholar
[8] K. M. Holford, “Acoustic emission in structural health monitoring,” Key Eng. Mater., vols. 413–414, pp. 15–28, 2009. https://doi.org/10.4028/www.scientific.net/kem.413-414.15.Search in Google Scholar
[9] P. Cawley, F. Cegla, and A. Galvagni, “Guided waves for ndt and permanently-installed monitoring,” Insight: Non-Destr. Test. Cond. Monit., vol. 54, no. 11, pp. 594–601, 2012. https://doi.org/10.1784/insi.2012.54.11.594.Search in Google Scholar
[10] J. Corcoran, “Creep monitoring using permanently installed potential drop sensors,” Dissertation, Imperial College London, London, 2015.Search in Google Scholar
[11] J. Corcoran, C. M. Davies, P. Cawley, and P. B. Nagy, “A quasi-dc potential drop measurement system for material testing,” IEEE Trans. Instrum. Meas., vol. 69, no. 4, pp. 1313–1326, 2020. https://doi.org/10.1109/tim.2019.2908509.Search in Google Scholar
[12] D. M. Farrell, B. J. Robbins, J. Stallings, S. Cardoso, and W. Bakker, “Crack growth monitoring on industrial plant using established electrical resistance ‘scanner’ technology,” Insight: Non-Destr. Test. Cond. Monit., vol. 50, no. 12, pp. 690–694, 2008. https://doi.org/10.1784/insi.2008.50.12.690.Search in Google Scholar
[13] W. Oppermann, P. Hofstötter, and H. Keller, “Long-term installations of the dc-potential drop method in four nuclear power plants and the accuracies thereby obtained for monitoring of crack initiation and crack growth,” Nucl. Eng. Des., vol. 174, no. 3, pp. 287–292, 1997. https://doi.org/10.1016/s0029-5493(97)00127-1.Search in Google Scholar
[14] K. H. Ryu, I. S. Hwang, and J. H. Kim, “Development of wall thinning screening system and its application to a commercial nuclear power plant,” Nucl. Eng. Des., vol. 265, no. 2, pp. 591–598, 2013. https://doi.org/10.1016/j.nucengdes.2013.09.021.Search in Google Scholar
[15] J. Y. Yoon, Y. Kim, S. Choi, et al.., “On-line monitoring of environment-assisted cracking in nuclear piping using array probe direct current potential drop,” J. Nondestr. Eval., vol. 35, no. 1, p. 1059, 2016. https://doi.org/10.1007/s10921-015-0330-8.Search in Google Scholar
[16] M. S. Leung and J. Corcoran, “A probabilistic method for structural integrity assurance based on damage detection structural health monitoring data,” Struct. Health Monit., vol. 21, no. 4, pp. 1608–1625, 2022. https://doi.org/10.1177/14759217211038881.Search in Google Scholar
[17] G. Sposito, “Advances in potential drop techniques for non-destructive testing,” Dissertation, Imperial College London, London, 2009.Search in Google Scholar
[18] E. Schneegans, J. Hug, and C. Rembe, “Temperaturkompensation des Potentialsondenverfahrens für die Zustandsüberwachung von Baustrukturen,” TM - Tech. Mess., vol. 89, no. s1, pp. 95–100, 2022. https://doi.org/10.1515/teme-2022-0064.Search in Google Scholar
[19] P. B. Nagy, “Ndt techniques: electrical,” in Reference Module in Materials Science and Materials Engineering, vol. 64, Amsterdam, Elsevier, 2016, p. 2638.10.1016/B978-0-12-803581-8.03470-6Search in Google Scholar
[20] T. V. Venkatsubramanian and B. A. Unvala, “An ac potential drop system for monitoring crack length,” J. Phys. E: Sci. Instrum., vol. 17, no. 9, pp. 765–771, 1984. https://doi.org/10.1088/0022-3735/17/9/012.Search in Google Scholar
[21] G. S. Smith, “Proximity effect in systems of parallel conductors,” J. Appl. Phys., vol. 43, no. 5, pp. 2196–2203, 1972. https://doi.org/10.1063/1.1661474.Search in Google Scholar
[22] Zurich Instruments, Mfli User Manual: Manual, 2023.Search in Google Scholar
[23] E. Schneegans, J. Hug, and C. Rembe, “Eignung des Potentialsondenverfahrens für die Zustandsüberwachung von Brücken,” in Sensoren und Messysteme, L. Reindl, Ed., Berlin, VDE Verlag GmbH, 2022.10.1515/teme-2022-0064Search in Google Scholar
[24] J. Corcoran and P. B. Nagy, “Compensation of the skin effect in low-frequency potential drop measurements,” J. Nondestr. Eval., vol. 35, no. 4, p. 741, 2016. https://doi.org/10.1007/s10921-016-0374-4.Search in Google Scholar
[25] L. J. Giacoletto, “Frequency- and time-domain analysis of skin effects,” IEEE Trans. Magn., vol. 32, no. 1, pp. 220–229, 1996. https://doi.org/10.1109/20.477574.Search in Google Scholar
[26] N. Bowler, “Frequency-dependence of relative permeability in steel,” AIP Conf. Proc., vol. 820, pp. 1269–1276, 2005.10.1063/1.2184670Search in Google Scholar
[27] S. Kasap, Principles of Electronic Materials and Devices, 4th edn. New York, NY, McGraw-Hill, a business unit of The McGraw-Hill Companies, Inc, 2018.Search in Google Scholar
[28] D. R. Lide. CRC Handbook of Chemistry and Physics: A Ready-Reference Book of Chemical and Physical Data, 84th ed. editor-in-chief, D. R. Lide, Ed., Boca Raton, Fla. London, CRC, 2003.Search in Google Scholar
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Articles in the same Issue
- Frontmatter
- Editorial
- XXXVI. Messtechnisches Symposium des AHMT in Magdeburg
- Research Articles
- Studying the effects of siloxane poisoning on a SnO2 metal oxide semiconductor gas sensor in temperature cycled operation enabling self-monitoring and self-compensation
- Investigations on terthiophene as an electrically conductive polymer for UV laser lithography
- Properties and special phenomena of strain sensors made of carbon particle-filled elastomers
- Machine learning approach for impedance locus uncertainties
- Investigation of cross-sensitivities of the potential drop method for structural health monitoring of civil structures
- Modular Direct Laser Writing setup for high precision nanostructuring
Articles in the same Issue
- Frontmatter
- Editorial
- XXXVI. Messtechnisches Symposium des AHMT in Magdeburg
- Research Articles
- Studying the effects of siloxane poisoning on a SnO2 metal oxide semiconductor gas sensor in temperature cycled operation enabling self-monitoring and self-compensation
- Investigations on terthiophene as an electrically conductive polymer for UV laser lithography
- Properties and special phenomena of strain sensors made of carbon particle-filled elastomers
- Machine learning approach for impedance locus uncertainties
- Investigation of cross-sensitivities of the potential drop method for structural health monitoring of civil structures
- Modular Direct Laser Writing setup for high precision nanostructuring
