Efficiency assessment of wavelet transforms and wavelets for damage localization in beams using shearography
 
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1
Silesian University of Technology
 
2
Polytechnic of Porto
 
3
Universidade de Lisboa
 
 
Submission date: 2018-07-31
 
 
Acceptance date: 2018-10-26
 
 
Online publication date: 2018-10-30
 
 
Publication date: 2018-11-05
 
 
Corresponding author
Andrzej Katunin   

Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Polska
 
 
Diagnostyka 2018;19(4):71-79
 
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ABSTRACT
Non-destructive testing of engineering structures and elements in operation is one of the crucial steps in recently introduced design philosophies: damage tolerance and condition-based maintenance. Therefore, it is important to provide effective non-destructive testing methods, which are able to detect and identify a possible damage in early stage of its development. One effective testing method, which still gains its popularity in various industrial applications, is shearography. Although, shearography is sensitive to various types of structural damage and flaws, this sensitivity can be significantly improved by applying advanced post-processing algorithms to raw data obtained from measurements. An excellent candidate for such an improvement is the wavelet analysis, due to its very high sensitivity to smallest signal disturbances. This study presents results of comparative analysis of various wavelet transforms and various wavelets in order to analyse their sensitivity to damage. The improvement in damage detectability is verified using experimental data.
 
REFERENCES (17)
1.
Vogelesang LB, Vlot A. Development of fibre metal laminates for advanced aerospace structures. Journal of Materials Processing Technology 2000; 103(1): 1-5. https://doi.org/10.1016/S0924-....
 
2.
Jardine AKS, Lin D, Banjevic D. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing 2006; 20(7): 1483-1510. https://doi.org/10.1016/j.ymss....
 
3.
Márquez FPG, Tobias AM, Pérez JMP, Papaelias M. Condition monitoring of wind turbines: Techniques and methods. Renewable Energy 2012; 46: 169-178. https://doi.org/10.1016/j.rene....
 
4.
Leendertz JA, Butters JN. An image-shearing speckle-pattern interferometer for measuring bending moments. Journal of Physics E: Scientific Instruments 1973; 6(11): 1107-1110. https://doi.org/10.1088/0022-3....
 
5.
Hung YY, Taylor CE. Speckle shearing interferometric camera – a tool for measurement of derivatives of surface displacements. Proc. SPIE 1974; 41, Developments in Laser Technology II, 169-177. https://doi.org/10.1117/12.953....
 
6.
Mininni M, Gabriele S, Lopes H, Araújo dos Santos JV. Damage identification in beams using speckle shearography and an optimal spatial sampling. Mechanical Systems and Signal Processing 2016; 79: 47-64. https://doi.org/10.1016/j.ymss....
 
7.
Steinchen W, Yang LX, Kupfer G, Mäckel P, Vössig F. Strain analysis by means of digital shearography: Potential, limitations and demonstration. Journal of Strain Analysis for Engineering Design 1998; 33(2): 171-182. https://doi.org/10.1243/030932....
 
8.
Yang LX, Hung YY. Digital shearography for nondestructive testing: Potentials, limitations, and applications. Journal of Holography and Speckle 2004; 1(2): 69-79. https://doi.org/10.1166/jhs.20....
 
9.
Hung YY. Digital shearography versus TV-holography for non-destructive evaluation. Optics and Lasers in Engineering 1997; 26(4-5): 421-436. https://doi.org/10.1016/0143-8....
 
10.
Hung YY. Shearography: A novel and practical approach for nondestructive inspection. Journal of Nondestructive Evaluation 1989; 8(2): 55-67. https://doi.org/10.1007/BF0056....
 
11.
Huang YH, Ng SP, Liu L, Chen YS, Hung YYM. Shearographic phase retrieval using one single specklegram: a clustering approach. Optical Engineering 2008; 47(5): 054301. https://doi.org/10.1117/1.2927....
 
12.
Baaran J. Visual Inspection of Composite Structures. EASA-Research Project/2007/3. Final report. Institute of Composite Structures and Adaptive Systems, DLR Braunschweig, Braunschweig; 2009.
 
13.
Kroworz A, Katunin A. Non-destructive testing of structures using optical and other methods: A review. Structural Durability & Health Monitoring 2018; 12(1): 1-17. https://doi.org/10.3970/sdhm.2....
 
14.
Reve GM, Pandarese G, Allevi G. Quantitative defect size estimation in shearography inspection by wavelet transform and shear correction. Proc. IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace), Padua, 2017; 535-540. https://doi.org/10.1109/MetroA....
 
15.
Katunin A, Lopes H, Araújo dos Santos JV. Identification of multiple damage using modal rotation obtained with shearography and undecimated wavelet transform. Mechanical Systems and Signal Processing 2019; 116: 725-740. https://doi.org/10.1016/j.ymss....
 
16.
Araújo dos Santos JV, Lopes H. Damage localization based on modal response measured with shearography. In: Nobari AS, Aliabadi MHF, eds. Vibration-Based Techniques for Damage Detection and Localization in Engineering Structures. New Jersey, World Scientific, 2018; 141-172. https://doi.org/10.1142/978178....
 
17.
Katunin A. Diagnostics of composite structures using wavelets. Specialist Monographic Series “Library of Maintenance Problems” no. 2540. Radom: The Publishing House of the Institute for Sustainable Technologies – National Research Institute; 2015.
 
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