Data-Driven Structural Health Monitoring Approach Using Guided Lamb Wave Responses
Publication: Journal of Aerospace Engineering
Volume 33, Issue 4
Abstract
In this paper, a data-driven structural health monitoring (SHM) approach is proposed to conduct in situ evaluation of the structural health state, i.e., damage location and extent, in which guided Lamb wave responses at selected locations are employed. The proposed approach is composed of an offline and an online phase. The objectives of the offline phase are to carry out data dimensionality reduction and to establish the mapping relationship between sensor data and damage status. First, a comprehensive database is established via high-fidelity finite element method (FEM) simulations (ABAQUS software) to determine guided Lamb wave responses (e.g., displacement and acceleration) under various prescribed structural damage conditions. Then, the proper orthogonal decomposition (POD) method is applied to extract key features from these responses under each simulated case. Finally, a neural network-based surrogate model is developed to relate the damage status with modal coefficients of the POD. The goal of the online phase is to quantify the damage location and extent using limited sensor measurements. The gappy proper orthogonal decomposition (GPOD) is employed to reconstruct the full field information based on limited sensor data. Subsequently, the associated damage extent and location are derived by applying the surrogate model developed in the offline phase. The proposed data-driven SHM approach is comprehensively validated using simulation data harvested from both beam and plate examples. The maximum error between evaluated and actual damage values is within 10%. Parametric studies are conducted as well to investigate the effects on damage detection using different sensor placement and sensor types. In summary, the proposed approach could lead to an efficient damage detection technique for aerospace structures.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, and code generated or used during the study appear in the pubished article.
References
Abdeljaber, O., and O. Avci. 2016. “Nonparametric structural damage detection algorithm for ambient vibration response: Utilizing artificial neural networks and self-organizing maps.” J. Archit. Eng. 22 (2): 04016004. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000205.
Allaire, D., D. Kordonowy, M. Lecerf, L. Mainini, and K. Willcox. 2014. “Multifidelity DDDAS methods with application to a self-aware aerospace vehicle.” In Proc., 14th Int. Conf. on Computational Science. Amsterdam, Netherlands: Elsevier.
Amezquita-Sanchez, J. P., and H. Adeli. 2016. “Signal processing techniques for vibration-based health monitoring of smart structures.” Arch. Comput. Methods Eng. 23 (1): 1–15. https://doi.org/10.1007/s11831-014-9135-7.
Amouzgar, K., and N. Strömberg. 2016. “Radial basis functions as surrogate models with a priori bias in comparison with a posteriori bias.” Struct. Multidiscip. Optim. 55 (4): 1453–1469. https://doi.org/10.1007/s00158-016-1569-0.
Arora, V., Y. H. Wijnant, and A. D. Boer. 2014. “Acoustic-based damage detection method.” Appl. Acoust. 80 (Jun): 23–27. https://doi.org/10.1016/j.apacoust.2014.01.003.
Aydin, K., and O. Kisi. 2015. “Damage diagnosis in beam-like structures by artificial neural networks.” J. Civ. Eng. Manage. 21 (5): 591–604. https://doi.org/10.3846/13923730.2014.890663.
Benkedjouh, T., K. Medjaher, N. Zerhouni, and S. Rechak. 2015. “Health assessment and life prediction of cutting tools based on support vector regression.” J. Intell. Manuf. 26 (2): 213–223. https://doi.org/10.1007/s10845-013-0774-6.
Burrows, B. J., and D. L. Allaire. 2017. “A comparison of naive bayes classifiers with applications to self-aware aerospace vehicles.” In Proc., 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conf., 2017–3819. Denver: American Institute of Aeronautics and Astronautics.
Capriotti, M., H. E. Kim, F. L. D. Scalea, and H. Kim. 2017. “Non-destructive inspection of impact damage in composite aircraft panels by ultrasonic guided waves and statistical processing.” Materials 10 (6): 616. https://doi.org/10.3390/ma10060616.
Contreras Cortés, F., M. Farjas, and F. J. Melero. eds. 2013. “CAA2010: Fusion of cultures.” In Proc., 38th Annual Conf. on Computer Applications and Quantitative Methods in Archaeology Granada, Spain. Oxford: Archaeopress.
Dao, P. B., and W. J. Staszewski. 2014. “Lamb wave based structural damage detection using cointegration and fractal signal processing.” Mech. Syst. Sig. Process. 49 (1–2): 285–301. https://doi.org/10.1016/j.ymssp.2014.04.011.
Das, S., P. Saha, and S. K. Patro. 2014. “Vibration-based damage detection techniques used for health monitoring of structures: A review.” J. Civ. Struct. Health Monit. 6 (3): 477–507. https://doi.org/10.1007/s13349-016-0168-5.
Dimitriu, G., R. Ştefănescu, and I. Navon. 2017. “Comparative numerical analysis using reduced-order modeling strategies for nonlinear large-scale systems.” J. Comput. Appl. Math. 310 (Jan): 32–43. https://doi.org/10.1016/j.cam.2016.07.002.
Du, G., Z. Li, and G. Song. 2018. “A PVDF-based sensor for internal stress monitoring of a concrete-filled steel tubular (CFST) column subject to impact loads.” Sensors 18 (6): 1682. https://doi.org/10.3390/s18061682.
Ebrahimkhanlou, A., B. Dubuc, and S. Salamone. 2016. “Damage localization in metallic plate structures using edge-reflected lamb waves.” Smart Mater. Struct. 25 (8): 085035. https://doi.org/10.1088/0964-1726/25/8/085035.
Everson, R., and L. Sirovich. 1995. “Karhunen–Loève procedure for gappy data.” J. Opt. Soc. Am. 12 (8): 1657. https://doi.org/10.1364/JOSAA.12.001657.
Gaspar, B., A. P. Teixeira, and C. Soares Guedes. 2014. “Assessment of the efficiency of Kriging surrogate models for structural reliability analysis.” In Probabilistic engineering mechanics, 24–34. Boca Raton, FL: CRC Press.
Giurgiutiu, V., and A. Zagrai. 2005. “Damage detection in thin plates and aerospace structures with the electro-mechanical impedance method.” Struct. Health Monit. 4 (2): 99–118. https://doi.org/10.1177/1475921705049752.
Holford, K., R. Pullin, S. Evans, M. Eaton, J. Hensman, and K. Worden. 2009. “Acoustic emission for monitoring aircraft structures.” Proc. Inst. Mech. Eng. Part G: J. Aerosp. Eng. 223 (5): 525–532. https://doi.org/10.1243/09544100JAERO404.
Huang, Z., C. Wang, J. Chen, and H. Tian. 2011. “Optimal design of aeroengine turbine disc based on kriging surrogate models.” Comput. Struct. 89 (1–2): 27–37. https://doi.org/10.1016/j.compstruc.2010.07.010.
Jiang, C., Y. Soh, and H. Li. 2016. “Sensor placement by maximal projection on minimum eigenspace for linear inverse problems.” IEEE Trans. Signal Process. 64 (21): 5595–5610. https://doi.org/10.1109/TSP.2016.2573767.
Kohonen, T. 1990. “The self-organizing map.” Proc. IEEE 78 (9): 1464–1480. https://doi.org/10.1109/5.58325.
Kohonen, T., E. Oja, O. Simula, A. Visa, and J. Kangas. 1996. “Engineering applications of the self-organizing map.” Proc. IEEE 84 (10): 1358–1384. https://doi.org/10.1109/5.537105.
Kong, Q., S. Fan, X. Bai, Y. L. Mo, and G. Song. 2017. “A novel embeddable spherical smart aggregate for structural health monitoring: Part I. Fabrication and electrical characterization.” Smart Mater. Struct. 26 (9): 095050. https://doi.org/10.1088/1361-665X/aa80bc.
Kromanis, R., and P. Kripakaran. 2014. “Predicting thermal response of bridges using regression models derived from measurement histories.” Comput. Struct. 136 (May): 64–77. https://doi.org/10.1016/j.compstruc.2014.01.026.
Lee, K., and D. Mavris. 2010. “Unifying perspective for gappy proper orthogonal decomposition and probabilistic principal component analysis.” AIAA J. 48 (6): 1117–1129. https://doi.org/10.2514/1.45750.
Li, J., and W. Zhang. 2016. “The performance of proper orthogonal decomposition in discontinuous flows.” Theor. Appl. Mech. Lett. 6 (5): 236–243. https://doi.org/10.1016/j.taml.2016.08.008.
Lim, Y. Y., and C. K. Soh. 2014. “Electro-mechanical impedance (EMI)-based incipient crack monitoring and critical crack identification of beam structures.” Res. Nondestr. Eval. 25 (2): 82–98. https://doi.org/10.1080/09349847.2013.848311.
Lu, G., Y. Li, M. Zhou, Q. Feng, and G. Song. 2018. “Detecting damage size and shape in a plate structure using PZT transducer array.” J. Aerosp. Eng. 31 (5): 04018075. https://doi.org/10.1061/(ASCE)AS.1943-5525.0000904.
Mainini, L., and K. Willcox. 2015. “Surrogate modeling approach to support real-time structural assessment and decision making.” AIAA J. 53 (6): 1612–1626. https://doi.org/10.2514/1.J053464.
Mohebi, E., and A. Bagirov. 2015. “Modified self-organising maps with a new topology and initialisation algorithm.” J. Exp. Theor. Artif. Intell. 27 (3): 351–372. https://doi.org/10.1080/0952813X.2014.954278.
Mousas, C., P. Newbury, and C. N. Anagnostopoulos. 2014. “Data-driven motion reconstruction using local regression models.” In Artificial intelligence applications and innovations, edited by L. Iliadis, I. Maglogiannis, and H. Papadopoulos. Berlin: Springer.
Platon, L., F. Zehraoui, and F. Tahi. 2017. “Self-organizing maps with supervised layer.” In Proc., 12th Int. Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM), 1–8. New York: IEEE.
Qiu, H., Y. Xu, L. Gao, X. Li, and L. Chi. 2016. “Multi-stage design space reduction and metamodeling optimization method based on self-organizing maps and fuzzy clustering.” Expert Syst. Appl. 46 (Mar): 180–195. https://doi.org/10.1016/j.eswa.2015.10.033.
Raben, S., J. Charonko, and P. Vlachos. 2012. “Adaptive gappy proper orthogonal decomposition for particle image velocimetry data reconstruction.” Meas. Sci. Technol. 23 (2): 025303. https://doi.org/10.1088/0957-0233/23/2/025303.
Rauter, N., and R. Lammering. 2014. “Impact damage detection in composite structures considering nonlinear lamb wave propagation.” Mech. Adv. Mater. Struct. 22 (1–2): 44–51. https://doi.org/10.1080/15376494.2014.907950.
Rosiek, M., A. Martowicz, and T. Uhl. 2010. “Uncertainty and sensitivity analysis of electro-mechanical impedance based SHM system.” IOP Conf. Ser.: Mater. Sci. Eng. 10 (1): 012207. https://doi.org/10.1088/1757-899X/10/1/012207/pdf.
Rumpfkeil, M. P., and P. Beran. 2016. “Construction of multi-fidelity surrogate models for aerodynamic databases.” In Proc., 9th Int. Conf. on Computational Fluid Dynamics (ICCFD9). Istanbul, Turkey: International Conference on Computational Fluid Dynamics.
Saeidi, F., S. A. Shevchik, and K. Wasmer. 2016. “Automatic detection of scuffing using acoustic emission.” Tribol. Int. 94 (Feb): 112–117. https://doi.org/10.1016/j.triboint.2015.08.021.
Saini, P., C. M. Arndt, and A. M. Steinberg. 2016. “Development and evaluation of gappy-POD as a data reconstruction technique for noisy PIV measurements in gas turbine combustors.” Exp. Fluids 57 (7): 122. https://doi.org/10.1007/s00348-016-2208-7.
Sanayei, M., and M. Saletnik. 1996a. “Parameter estimation of structures from static strain measurements. I: Formulation.” J. Struct. Eng. 122 (5): 555–562. https://doi.org/10.1061/(ASCE)0733-9445(1996)122:5(555).
Sanayei, M., and M. Saletnik. 1996b. “Parameter estimation of structures from static strain measurements. II: Error sensitivity analysis.” J. Struct. Eng. 122 (5): 563–572. https://doi.org/10.1061/(ASCE)0733-9445(1996)122:5(563).
Schwankl, M., Z. S. Khodaei, M. H. Aliabadi, and C. Weimer. 2013. “Electro-mechanical impedance technique for structural health monitoring of composite panels.” In Vol. 525–526 of Key engineering materials, 569–572. Istanbul, Turkey: Trans Tech Publications. https://doi.org/10.4028/www.scientific.net/KEM.525-526.569.
Senyurek, V. Y. 2015. “Detection of cuts and impact damage at the aircraft wing slat by using Lamb wave method.” Measurement 67 (May): 10–23. https://doi.org/10.1016/j.measurement.2015.02.007.
Shateri, M., M. Ghaib, D. Svecova, and D. Thomson. 2017. “On acoustic emission for damage detection and failure prediction in fiber reinforced polymer rods using pattern recognition analysis.” Smart Mater. Struct. 26 (6): 065023. https://doi.org/10.1088/1361-665X/aa6e43.
Su, Z., and L. Ye. 2009. Identification of damage using lamb waves: From fundamentals to applications. Berlin: Springer.
Taddei, T., J. D. Penn, M. Yano, and A. T. Patera. 2016. “Simulation-based classification; a model-order-reduction approach for structural health monitoring.” Arch. Comput. Methods Eng. 25 (1): 23–45. https://doi.org/10.1007/s11831-016-9185-0.
Tiwari, M., K. Song, C. Chatterjee, and M. Gupta. 2012. “Improving reliability of river flow forecasting using neural networks, wavelets and self-organizing maps.” J. Hydroinf. 15 (2): 486–502. https://doi.org/10.2166/hydro.2012.130.
Venugopal, V., and G. Wang. 2014. “Modeling and analysis of Lamb wave propagation in a beam under lead zirconate titanate actuation and sensing.” J. Intell. Mater. Syst. Struct. 26 (13): 1679–1698. https://doi.org/10.1177/1045389X14536010.
Wang, M., D. Dutta, K. Kim, and J. Brigham. 2015. “A computationally efficient approach for inverse material characterization combining Gappy POD with direct inversion.” Comput. Methods Appl. Mech. Eng. 286 (Apr): 373–393. https://doi.org/10.1016/j.cma.2015.01.001.
Willcox, K. 2006. “Unsteady flow sensing and estimation via the gappy proper orthogonal decomposition.” Comput. Fluids 35 (2): 208–226. https://doi.org/10.1016/j.compfluid.2004.11.006.
Wu, Q., F. Yu, Y. Okabe, and S. Kobayashi. 2014. “Application of a novel optical fiber sensor to detection of acoustic emissions by various damages in CFRP laminates.” Smart Mater. Struct. 24 (1): 015011. https://doi.org/10.1088/0964-1726/24/1/015011.
Xu, K., C. Ren, Q. Deng, Q. Jin, and X. Chen. 2018. “Real-time monitoring of bond slip between GFRP bar and concrete structure using piezoceramic transducer-enabled active sensing.” Sensors 18 (8): 2653. https://doi.org/10.3390/s18082653.
Xue, P., C. Chen, R. Beardsley, and R. Limeburner. 2011. “Observing system simulation experiments with ensemble Kalman filters in Nantucket Sound, Massachusetts.” J. Geophys. Res. 116 (C1): C01011. https://doi.org/10.1029/2010JC006428.
Yan, Y., L. Cheng, Z. Wu, and L. Yam. 2007. “Development in vibration-based structural damage detection technique” Mech. Syst. Sig. Process. 21 (5): 2198–2211. https://doi.org/10.1016/j.ymssp.2006.10.002.
Yondo, R., E. Andres, and E. Valero. 2018. “A review on design of experiments and surrogate models in aircraft real-time and many query aerodynamic analyses.” In Progress in aerospace sciences, 23–61. Amsterdam, Netherlands: Elsevier.
Information & Authors
Information
Published In
Journal of Aerospace Engineering
Volume 33 • Issue 4 • July 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Apr 16, 2019
Accepted: Jan 21, 2020
Published online: Apr 23, 2020
Published in print: Jul 1, 2020
Discussion open until: Sep 23, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.