An Approach to Damage Detection in the Aircraft Structure with the Use of Integrated Sensors – The Symost Project

• Autorzy: Dragan K. , Dziendzikowski M. , Leski A. , Dworakowski Z. , Uhl T.

Identyfikatory

DOI

10.2478/v10164-012-0052-7

• Języki publikacji: EN

Abstrakty

EN

This paper presents an approach to damage growth monitoring and early damage detection in the structure of PZL – 130 ORLIK TC II turbo-prop military trainer aft using the statistical models elaborated by the Polish Air Force Institute of Technology (AFIT) and the network of the sensors attached to the structure. Drawing on the previous experiences of the AFIT and AGH in structural health monitoring, the present research will deploy an array of the PZT sensors in the structure of the PZL -130 Orlik TC II aircraft. The aircraft has just started Full Scale Fatigue Test (FSFT) that will continue up to 2013. The FSFT of the structure is necessary as a consequence of the structure modification and the change of the maintenance system - the transition to Condition Based Maintenance. In this paper, a novel approach to the monitoring of the aircraft hot-spots will be presented. Special attention will be paid to the preliminary results of the statistical models that provide an automated tool to infer about the presence of damage and its size. In particular, the effectiveness of the selected signal characteristics will be assessed using dimensional reduction methods (PCA) and the so-called averaged damage indices will be delivered. Moreover, the results of the signal classification based on the neural network will be presented alongside the numerical model of the wave propagation. The work contains selected information about the project scope and the results achieved at the preliminary stage of the project.

Słowa kluczowe

EN

averaged damage index; full scale fatigue test; damage growth monitoring

• Wydawca: Wydawnictwa Naukowe Sieci Badawczej Łukasiewicz - Instytutu Lotnictwa
• Czasopismo: Fatigue of Aircraft Structures
• Rocznik: 2012
• Tom: Iss. 4
• Strony: 10--16
• Opis fizyczny: Bibliogr. 19 poz., rys., tab., wykr., wzory

Twórcy

autor

Dragan K.

• Air Force Institute of Technology, Warsaw, Poland
• AGH University of Technology, Krakow, Poland

autor

Dziendzikowski M.

• Air Force Institute of Technology, Warsaw, Poland

autor

Leski A.

• Air Force Institute of Technology, Warsaw, Poland

autor

Dworakowski Z.

• Air Force Institute of Technology, Warsaw, Poland

autor

Uhl T.

• AGH University of Technology, Krakow, Poland

Bibliografia

• [1] Worden, K. & Barton, J.M. (2004). An Overview of Intelligent Fault Detection in Systems and Structures. Structural Health Monitoring. Vol. 3(1), p. 85.
• [2] Medina, E.A. & Aldrin, J.C. (2011). Probabilistic Reliability Assessment Protocol for Structural Health Monitoring (SHM) Systems. In AA&S 2011 Conference, April 18-21 2011, San Diego.
• [3] Su, Z. & Ye, L. (2009). Identification of Damage Using Lamb Waves. London: Springer-Verlag GmbH & Co.
• [4] Alleyne, D.N. & Cawley, P. (1996). The excitation of Lamb waves in pipes using drycoupled piezoelectric transducers. J. Nondestruct. Eval. Vol. 15(1), p. 11.
• [5] Tua, P.S., Quek, S.T. & Wang, Q. (2005). Detection of cracks in cylindrical pipes and plates using piezo-actuated Lamb waves. Smart Mater. Struct. Vol. 14, p. 1325.
• [6] Kim Y.H., Kim D.H., Han J.H. & Kim C.G. (2007). Damage assessment in layered composites using spectral analysis and Lamb wave. Compos. Part B-Eng. Vol. 38, p. 800.
• [7] Su, Z., Ye, L. & Lu, Y. (2006). Guided Lamb waves for identification of damage in composite structures: a review. J. Sound Vib. Vol. 295, p. 753.
• [8] Wang, Q.W. & Sun, B.X. (2010). Structural damage localization and quantification using static test data. Struct. Health Monit. Vol. 10(4), p. 381.
• [9] Hay T.R., Royer R.L., Gao H. , Zhao X. & Rose J.L. (2006). A comparison of embedded sensor Lamb wave ultrasonic tomography approaches for material loss detection. Smart Mater. Struct. Vol. 15(4), p. 946.
• [10] Wang D., Ye L., Lu Y. & Su Z. (2009). Probability of the presence of damage estimated from an active sensor network in a composite panel of multiple stiffeners. Compos. Sci. Technol. Vol. 69(13), p. 2054.
• [11] Clarke, T. & Cawley, P. (2010). Enhancing the defect localization capability of a guided wave SHM system applied to a complex structure. Struct. Health Monit. Vol. 10(3), p. 247.
• [12] Dragan K., Klimaszewski S., Salacinski M., Synaszko P. & Dziendzikowski M. (2011), Structural Health Monitoring of the Helicopter Main Rotor. In AA&S 2011 Conference, April 18-21 2011, San Diego.
• [13] Dragan K., Dziendzikowski M. & Uhl T. (2011). The development of the non-parametric classification models for the damage monitoring on the ex ample of the ORLIK aircraft structure. In Second International Workshope on Smart Diagnostic of Structures, Krakow, November 2011.
• [14] Sohn, H., Czarnecki, J.A. & Farrar, C.R. (2000). Structural health monitoring using statistical process control. J. Struct. Eng. Vol. 126(1), p. 1356.
• [15] De Boe, P. & Golinval, J.C. (2003). Principal component analysis of a piezosensor array for damage localization. Struct. Health Monit. Vol. 2(2), p. 137.
• [16] Mustapha F., Worden K., Pierce S.G. & Manson G. (2007). Damage detection using stress waves and multivariate statistics: an experimental case study of an aircraft component. Strain, Vol. 43(1), p. 47.
• [17] Trendafilova, I., Cartmell, M.P. and Ostachowicz, W. (2008). Vibration-based damage detection in an aircraft wing scaled model using principal component analysis and pattern recognition. J. Sound Vib. Vol. 313(3), p. 560.
• [18] Mujica L.E., Rodellar J., Fernandez A. & Guemes A. (2010). Q-statistic and T2 statistic PCA-based measures for damage assessment in structures. Struct. Health Monit. Vol. 10(5), p. 539.
• [19] Hastie, T. Tibshirani, R. & Friedman, J. (2009). The Elements of Staistical Learning: Data Mining, Inference, and Prediction, second ed. New York: Springer Science+Business Media.

Uwagi

EN

The financial support from the National Centre for Research and Development for the work realized under the LIDER project LIDER/25/43/L-2/10/NCBiR/2011 is gratefully acknowledged.

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.