Probabilistic delamination diagnosis of composite materials using a novel Bayesian Imaging Method

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Oct 14, 2013
Tishun Peng Abhinav Saxena Kai Goebel Shankar Sankararaman Yibing Xiang Yongming Liu

Abstract

In this paper, a framework for probabilistic delamination location and size detection is proposed. A delamination probability image using Lamb wave-based damage detection is constructed using the Bayesian updating technique. First, the algorithm for the probabilistic delamination detection framework using Bayesian updating (Bayesian Imaging Method - BIM) is presented. Following this, a fatigue testing setup for carbon-carbon composite coupons is introduced and the corresponding lamb wave based diagnostic signal is collected and interpreted. Next, the obtained signal features are incorporated in the Bayesian Imaging Method to detect delamination size and location, as along with corresponding uncertainty bounds. The damage detection results using the proposed methodology are compared with X-ray images for verification and validation. Finally, some conclusions and future works are drawn based on the proposed study.

How to Cite

Peng, T. ., Saxena, A. ., Goebel, K. ., Sankararaman, S., Xiang, Y. ., & Liu, Y. . (2013). Probabilistic delamination diagnosis of composite materials using a novel Bayesian Imaging Method. Annual Conference of the PHM Society, 5(1). https://doi.org/10.36001/phmconf.2013.v5i1.2234
Abstract 663 | PDF Downloads 164

##plugins.themes.bootstrap3.article.details##

Keywords

diagnosis, composite materials, Bayesian Imaging Method

References
Adam, M. T. (2002). "G104-A2L Guide for estimation of measurement uncertainty in testing." American Association of Laboratory Accreditation Manual: 10- 18.

Bell, S. (2001). "A Beginner’s Guide to Uncertainty of Measurement." The National Physical Laboratory 2: 9- 16.

Cheng, L. and Tian, G. Y. (2012). "Comparison of Nondestructive TestingMethods on Detection of Delaminations in Composites." Journal of Sensors 2012(2012): 7.

Constantin, N., Sorohan, S. and Gavan, M. (2011). "Efficient and low cost PZT network for detection and localizaiton of damage in low curvature panels." Journal of Theoretical and Applied Mehanics 49(3): 685-704.

Cowles, M. K. and Carlin, B. P. (1996). "Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review." Journal of the American Statistical Association 91(434).

Fort, G., Moulines, E. and Priouret, P. (2012). "Convergence of adaptive and interacting Markov chain Monte Carlo algorithms." Annals of Statistics 39(6): 3262-3289.

Giurgiutiu, V., Zagrai, A. and Bao, J. J. (2002). "Piezoelectric wafer embedded active sensors for aging aircraft structural health monitoring." Structural Health Monitoring 1(1): 41-61.

Grimberg, R., Premel, D., Savin, A., Le Bihan, Y. and Placko, D. (2001). "Eddy current hologaphy evaluation of delamination in carbon-epoxy composites." Insight 43(4): 260-264.

Hasting, W. K. (1970). "Monte Carlo sampling methods using Markov Chain and their applications." Biometrika 57: 97-109.

Ji, S., Xue, Y. and Carin, L. (2008). "Bayesian Compressive Sensing." IEEE transaction on signal processing 56(6).

Kazys, R. and Svilainis, L. (1997). "Ultrasonic detection and characterization of delaminations in thin composite plates using signal processing technique." Ultrasonics 35: 367-383.

Koruk, M. and Kilic, M. (2009). "The usage of IR thermography for the temprature measurements inside an automobile cabin." International Communication in Heat and Mass Tansfer 36: 872-877.

Lemistre, M. and Balageas, D. (2001). "Structural health monitoring system based on diffracted Lamb wave analysis by multiresolution processing." Smart materials and structures 10: 504.

Li, Y.-l., Dong, L.-y., Guan, W.-z., Li, Z. and Zhou, L.-y. (2007). "The Application of Bayesian Method in Image Segmentation." ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control 490.

Mielozyk, M., Krawczuk, M., Malinowski, P., Wandowski, T. and Ostachowicz, W. (2012). "Active therography method for delamination detection and localisation in composite structures." 6th European Workshop on Structural Health Monitoring

Nicolleto, A. and Hola, K. (2010). "X-ray computed tomography vs. metallography for pore sizing and fatigue of cast Al-alloys." Pocedia Engineering 2(1): 8.

Peng, T., He, J., Liu, Y., Saxena, A., Celaya, J. and Goebel, K. (2012). "Integrated fatigue damage diagnosis and prognosis under uncertainties." Annual Conference of Prognostics and Health Management Society.

Peskun, P. H. (1973). "Aptimum Monte Carlo sampling using Markov chains." Biometrika 57: 97-109.

Pickup, L. C., Capel, D. P., Roberts, S. J. and Zisserman, A. (2009). "Bayesian Methods for Image Super-Resolution." The computer Journal 52(1): 101-113.

Raghavan, A. and Cesnik, C. E. S. (2007). "Review of guided-wave structural health monitoring." Shock and Vibration Digest 39(2): 91-116.

Saxena, A., Goebel, K., Larrosa, C. C., Janapati, V., Roy, S. and Chang, F.-K. (2011). "Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials." Proceedings of the 8th International Workshop on Structural Health Monitoring 1: 1139-1149.

Scalea, d., Francesco, L., Robinson, J. S., Tuzzeo, D. and Bonomo, M. (2002). "Guided wave ultrasonics for NDE of aging aircraft components " Proc. SPIE 4704: 123-132.

Sophian, A., Tian, G. Y., Taylor, D. and Rudlin, J. (2001). "Electromagnetic and eddy current NDT: a review." Insight 43(5): 302-306.

Su, Z. and Ye, L. (2009). "Identification of damage using Lamb waves: From fundamentals to applications." London: Springer-Verlag GmbH & Co.: 346.

Wang, C. H., Rose, J. T. and Chang, F.-K. (2004). "A synthetic time-reversal imaging method for structural health monitoring." J. of smart mater. Struct. 13: 413- 423.

Zhao, X., Gao, H., zhang, G. f., Ayhan, B., Yan, F., Chiman, K. and Joseph, L. R. (2007). "Active health monitoring of an aircraft wing with embedded piezoelctric sensor/actuator network:I.Defect detection, localization and growth monitoring " Smart MATER. STRUCT. 16: 1208-1217.

Zhou, C., Su, Z. and Cheng, L. (2011). "Probability-based diagnostic imaging using hybrid features extracted from ultrasonic Lamb wave signals." Smart materials and structures 20(12): 125005.
Section
Technical Research Papers

Most read articles by the same author(s)

<< < 1 2 3 4 5 6 7 8 > >>