Abstract
This paper deals with investigations on structural health monitoring algorithms for an optimal false calls management. These false calls are caused, in the current study, by several environmental and operational factors. These factors and their effects are broken down in this paper. To demystify these effects and so reach more reliable monitoring with the best possible trade-off between probability of detection and false alarm rate, some techniques either analytical or statistical could be used. A comparative discussion between these methods is given. An example of a study using an unsupervised method is shown.
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Sohn H (2007) Effects of environmental and operational variability on structural health monitoring. Philos Transac Ser A Math Phys Eng Sci 365:539–560
Croxford AJ, Wilcox PD, Drinkwater BW, Konstantinidis G (2007) Strategies for guided-wave structural health monitoring. Proc R Soc A Math Phys Eng Sci 463:2961–2981
Croxford AJ, Moll J, Wilcox PD, Michaels JE (2010) Efficient temperature compensation strategies for guided wave structural health monitoring. Ultrasonics 50:517–528
Putkis O, Dalton RP, Croxford AJ (2015) The influence of temperature variations on ultrasonic guided waves in anisotropic CFRP plates. Ultrasonics 60:109–116
Eybpoosh M, Berges M, Nah YN (2014) Investigation on the effects of environmental and operational conditions (EOC) on diffuse-field ultrasonic guided-waves in pipes. In: Proceedings of international conference on computing in civil and building engineering, pp 1198–1205. Orlando, Florida, United States
Chen F, Wilcox PD (2007) The effect of load on guided wave propagation. Ultrasonics 47:111–122
Michaels JE, Lee SJ, Chen X, Shi F, Michaels TE (2011) Understanding and exploiting applied loads for guided wave structural health monitoring. In: Aircraft airworthiness & sustainment conference. San Diego, CA, 18–21 April 2011
Schubert KJ, Brauner C, Herrmann AS (2013) Non-damage-related influences on Lamb wave-based structural health monitoring of carbon fiber-reinforced plastic structures. Structural Health Monitoring 13:158–176
Schubert KJ, Herrmann AS (2013) A Compensation Method for Environmental Influences on passive lamb wave based Impact evaluation for CFRP. Key Eng Mater 569:1265–1272
Cicero T, Cawley P, Lowe MJS, Simonetti F (2009) Effects of liquid loading and change of properties of adhesive joints on subtraction techniques for structural health monitoring. In: Proceedings of the Review of Progress in QNDE, American Institute of Physics, vol. 28, pp 1006–1013. New York
Lu Y, Michaels JE (2008) Discriminating damage from surface wetting via feature analysis for ultrasonic structural health monitoring systems. Rev Prog QNDE 27:1420–1427
Rizzo P, Sorrivi E, Lanza di Scalea F, Viola E (2007) Wavelet-based outlier analysis for guided wave structural monitoring: application to multi-wire strands. J Sound Vibr 307: 52–68
Rizzo P, Cammarata M, Bartoli I, di Scalea FL, Salamone S, Coccia S, et al (2010) Ultrasonic guided waves-based monitoring of rail head: laboratory and field tests. Adv Civil Eng
Worden K, Farrar CR, Manson G, Park G (2007) The fundamental axioms of structural health monitoring. Proc R Soc London A Math Phys Eng Sci 463:1639–1664
Clifton DA, Hugueny S, Tarassenko L (2011) Novelty detection with multivariate extreme value statistics. J Signal Process Syst 65:371–389
Xiang S, Nie F, Zhang C (2008) Learning a Mahalanobis distance metric for data clustering and classification. Pattern Recogn 41:3600–3612
Barnett V, Lewis T (1994) Outliers in statistical data, 3rd edn. Wiley, New York, NY
El Mountassir M, Yaacoubi S, and Dahmene F (2015) Detection of structural damage using an unsupervised learning algorithm under variational environmental and operational conditions. In: 11th International conference on damage assessment of structures, DAMAS 2015. Ghent University, Belgium, August 24–26 2015
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El Mountassir, M., Yaacoubi, S., Dahmene, F., Chauveau, D. (2018). Algorithms for an Optimal False Calls Management. In: Chapuis, B., Sjerve, E. (eds) Sensors, Algorithms and Applications for Structural Health Monitoring. IIW Collection. Springer, Cham. https://doi.org/10.1007/978-3-319-69233-3_9
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DOI: https://doi.org/10.1007/978-3-319-69233-3_9
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