A Visual Analytics Tool for the Structural Health Monitoring of an Aircraft Panel
Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 680
 A. Guemes, Fiber Optic Strain Sensors. NATO-STO Lecture Series. Retrieved from https://www.sto.nato.int/publications/STO%20Educational%20Notes/STO-EN-AVT-220/EN-AVT-220-03.pdf, 2014. Accessed on: 19/11/2020
 A. Güemes, et al., “Methodologies for the Damage Detection Based on Fiber-Optic Sensors. Applications to the Fuselage Panel and Lower Wing Panel”, in Smart Intelligent Aircraft Structures (SARISTU), P.C. Wölcken, M. Papadopoulos, Eds., Switzerland: Springer International Publishing, 2016, pp 407-431.
 I.T. Jolliffe, Principal Component Analysis, New York, NY: Springer-Verlag, 2002, pp-10-28.
 F.M. Pisano, M. Ciminello, “Preliminary robustness analysis of a Structural Health Monitoring PCA-based algorithm”, in Proc. 9th European Workshop on Structural Health Monitoring, Manchester, 2018.
 J.W. Tukey, Exploratory Data Analysis, Boston, MA: Addison-Wesley Publishing Company, 1977, pp.29-43.
 https://www.r-project.org/ Accessed on: 19/11/2020
 F.M. Pisano, M. Ciminello, F. Romano, U. Mercurio, “Visual Analysis for PCA-based skin-stringer debonding of composite stiffened panels”, in Proc. 12th International Workshop on Structural Health Monitoring, Stanford, 2019, DOI 10.12783/shm2019/32480
 https://www.tableau.com. Accessed on: 19/11/2020
 P. Hanrahan, C. Stolte, J. Mackinlay, “Selecting a Visual Analytics Application”, Tableau whitepaper, https://www.tableau.com/whitepapers/selecting-visual-analytics-application. Accessed on: 19/11/2020
 J. Thomas, K. Cook. Illuminating the Path: Research and Development Agenda for Visual Analytics, United States: Department of Homeland Security, 2005.
 P.C. Wong, J. Thomas, “Visual Analytics”, Computer Graphics and Applications, IEEE, 24 (5), 2004, pp. 20-21. doi: 10.1109/MCG.2004.39
 D.A. Keim, F. Mansmann, J. Schneidewind, H. Ziegler, “Visual Analytics: Scope and Challenges”, Lecture Notes in Computer Science, No.4404, 2008, pp. 76-90.
 D.A. Keim, F. Mansmann, J. Schneidewind, A. Stoffel, H. Ziegler, “Visual Analytics”, Encyclopedia of Database Systems, Springer, 2009.
 Mastering the Information Age Solving Problems with Visual Analytics, VisMaster - European Coordination Action Project, D. Keim, J. Kohlhammer, G. Ellis., F. Mansmann, Eds., Eurographics Association, 2010.
 http://www.va-sa.net. Accessed on: 19/11/2020
 Extreme weather events and their consequences for civil protection, R. Heinz, N. vom Scheidt, E. Behm E. (Eds.), 2012.
 www.vis-sense.eu. Accessed on: 19/11/2020
 J. Dill, R. Earnshaw, D. Kasik, J. Vince, P.C. Wong, Expanding the frontiers of Visual Analytics and Visualization, Springer, 2012.
 J. J. Caban, D. Gotz, “Visual analytics in healthcare – opportunities and research challenges”, Journal of the American Medical Informatics Association, Vol. 22(2), March 2015, pp. 260–262, https://doi.org/10.1093/jamia/ocv006
 Y. Chung, N. Bagheri, J. A. Salinas-Perez, K. Smurthwaite, E. Walsh, M. A. Furst, S. Rosenberg, L. Salvador-Carull, “Role of visual analytics in supporting mental healthcare systems research and policy: A systematic scoping review”, International Journal of Information Management 50, 2020, pp. 17–27. https://doi.org/10.1016/j.ijinfomgt.2019.04.012
 https://researcher.watson.ibm.com/researcher/view_group.php?id=9297. Accessed on: 19/11/2020
 https://www.tableau.com/it-it/solutions/healthcare-provider-analytics. Accessed on: 19/11/2020
 https://www.sas.com/it_it/industry/health-care.html. Accessed on: 19/11/2020
 D. Kasik, “Visual Analyics at Boeing”, Boeing Information Technology 2012.
 D. Kasik, C. Senesac, “Visualization: Past, Present, and Future at Boeing”, Boeing Information Technology, 2012.
 M. Varga, A. de Hoon, R. May, C. Varga, H. van Gasteren, “Application of visual analytics to aviation safety - Wildlife strikes - The '5 W Questions”, IEEE Conference on Visual Analytics Science and Technology (VAST), Paris, 2014, pp. 283-284. doi: 10.1109/VAST.2014.7042531
 P. P. Giangarra, B. Metrovich, M. M. Schwitters, B. P. Semple, “Smarter bridges through advanced structural health monitoring”, IBM J. RES. & DEV., VOL. 55 NO. 1&2, 2011.
 B. Raphael, A. Harichandran, “Sensor Data Interpretation in Bridge Monitoring—A Case Study”, Front. Built Environ., 2020 https://doi.org/10.3389/fbuil.2019.00148
 https://www.globvision.com/index.php/. Accessed on: 19/11/2020
 https://rmarkdown.rstudio.com/. Accessed on: 19/11/2020
 “Visual Analysis Best Practices”, Tableau whitepaper, https://www.tableau.com/learn/whitepapers/tableau-visual-guidebook. Accessed on: 19/11/2020
 M. Hardin, D. Hom, R. Perez, L. Williams, “Which chart or graph is right for you?”, Tableau whitepaper, https://www.tableau.com/learn/whitepapers/which-chart-or-graph-is-right-for-you. Accessed on: 19/11/2020
 http://powertoolsfortableau.com/tools/drawing-tool. Accessed on: 19/11/2020
 https://www.gartner.com/en/documents/3980852/magic-quadrant-for-analytics-and-business-intelligence-p. Accessed on: 19/11/2020