Reliability Assessment of SHM Methodologies for Damage Detection

Article Preview

Abstract:

Probability-based imaging which illustrates a distribution map of probability of damage presence in structures is a diagnostic method well established for damage detection in sensorized structures. Since the quality of the recorded signal is directly linked to the reliability of the diagnostic outcome, the assessment of robustness of the damage detection methodology is of high significance. In this paper, robustness and reliability of the current probability based imaging algorithms have been assessed for detecting BVID in a composite panel. Consequently, a proposed outlier analysis and DI probability distribution damage detection algorithm was shown to improve the reliability of the detection method.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

244-247

Citation:

Online since:

September 2016

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2016 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Kessler, S.S., S.M. Spearing, and C. Soutis, Damage detection in composite materials using Lamb wave methods. Smart Materials and Structures, 2002. 11(2): p.269.

DOI: 10.1088/0964-1726/11/2/310

Google Scholar

[2] Su, Z., et al., On selection of data fusion schemes for structural damage evaluation. Structural Health Monitoring, 2009. 8(3): pp.223-241.

DOI: 10.1177/1475921708102140

Google Scholar

[3] Sharif-Khodaei, Z., O. Bacarreza, and M. Aliabadi. Lamb-Wave Based Technique for Multi-Site Damage Detection. in Key Engineering Materials. 2014. Trans Tech Publ.

DOI: 10.4028/www.scientific.net/kem.577-578.133

Google Scholar

[4] Michaels, J.E., Detection, localization and characterization of damage in plates with an in situ array of spatially distributed ultrasonic sensors. Smart Materials and Structures, 2008. 17(3): p.035035.

DOI: 10.1088/0964-1726/17/3/035035

Google Scholar

[5] Su, Z. and L. Ye, Identification of damage using Lamb waves: from fundamentals to applications. Vol. 48. 2009: Springer Science & Business Media.

Google Scholar

[6] Sohn, H., et al., Wavelet-based active sensing for delamination detection in composite structures. Smart Materials and Structures, 2003. 13(1): p.153.

DOI: 10.1088/0964-1726/13/1/017

Google Scholar

[7] Sultan, M., et al., On impact damage detection and quantification for CFRP laminates using structural response data only. Mechanical Systems and Signal Processing, 2011. 25(8): pp.3135-3152.

DOI: 10.1016/j.ymssp.2011.05.014

Google Scholar

[8] Michaels, J.E. and T.E. Michaels, Guided wave signal processing and image fusion for in situ damage localization in plates. Wave Motion, 2007. 44(6): pp.482-492.

DOI: 10.1016/j.wavemoti.2007.02.008

Google Scholar

[9] Sharif-Khodaei, Z. and M. Aliabadi, Assessment of delay-and-sum algorithms for damage detection in aluminium and composite plates. Smart materials and structures, 2014. 23(7): p.075007.

DOI: 10.1088/0964-1726/23/7/075007

Google Scholar

[10] Flynn, E.B., et al. Maximum-likelihood estimation of damage location in guided-wave structural health monitoring. in Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences. 2011. The Royal Society.

DOI: 10.1098/rspa.2011.0095

Google Scholar