On a defect identification method based on monitoring the structure and peculiarities of surface wave fields
Source abstract
Abstract
A special technique is proposed for processing detected signals. The technique uses an adjustable orthonormal basis and makes it possible to effectively identify defects by monitoring the structure and peculiarities of surface wave fields.
Only a short abstract or summary was supplied by the source.
Source: openalex_inverted_index · Quality: short
Research context
OpenAlex topics: Ultrasonics and Acoustic Wave Propagation · Structural Health Monitoring Techniques · Non-Destructive Testing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (16)
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1. Dervilis, N., Choi, M., Barthorpe, R.J., Park, G., Farrar, C.R., and Worden, K., On damage diagnosis for a wind turbine blade using pattern recognition, J. Sound Vib., 2014, vol. 333, no. 6, pp. 1833–1850.10.1016/j.jsv.2013.11.015 ↗
2. Salazar, A., Vargara, L., and Llinares, R., Learning material defect patterns by separating mixtures of independent component analyzers from NDT sonic signals, Mech. Syst. Signal Process., 2010, vol. 24, no. 6, pp. 1870–1886.10.1016/j.ymssp.2010.01.007 ↗
3. Tsui, P.C. and Basir, O.A., Wavelet basis selection and feature extraction for shift invariant ultrasound foreign body classification, Ultrasonics, 2006, vol. 45, nos. 1–4, pp. 1–14.10.1016/j.ultras.2006.05.214 ↗
4. Tondreau, G. and Deraemaeker, A., Local modal filters for automated data-based damage localization using ambient vibrations, Mech. Syst. Signal Process, 2013, vol. 39, nos. 1–2, pp. 162–180.10.1016/j.ymssp.2013.03.020 ↗
5. Ismagilov, I.R., Golenishchev-Kutuzov, V.A., Kalimullin, R.I., Migachev, S.A., and Khasanov, A.A., Detecting surface and volume defects in metals by the laser-acoustic method, Russ. J. Nondestr. Test., 2014, vol. 50, no. 6, pp. 318–324.10.1134/S1061830914060060 ↗
6. Korkh, Yu.V., Perov, D., and Rinkevich, A.B., Detection of subsurface microflaws using the high-frequency acoustic microscopy method, Russ. J. Nondestr. Test., 2015, vol. 51, no. 4, pp. 198–209.10.1134/S1061830915040051 ↗
7. Sedel'nikov, Yu.E. and Fadeeva, L.Yu., The synthesized video-signal method in nondestructive-testing problems, Russ. J. Nondestr. Test., 2015, vol. 51, no. 5, pp. 320–328.10.1134/S1061830915050083 ↗
8. Ogorodnikova, O.M. and Martynenko, S.V., Application of the Levenberg-Marquardt algorithm in computer simulation of cast defects, Russ. J. Nondestr. Test., 2015, vol. 51, no. 5, pp. 315–319.10.1134/S1061830915050058 ↗
9. Vatul'yan, A.O. and Dudarev, V.V., On determining internal pressure in a cylinder based on acoustic-probing data, Defektoskopiya, 2014, no. 10, pp. 52–60.
10. Bocharova, O.V., On inverse problems of identification the cavity in the elastic cylinder, J. Phys.: Conf. Ser., 2014, vol. 490, no. 1, p. 012057. doi 10.1088/1742-6596/490/1/012057
11. Mallat, S.A., Wavelet Tour of Signal Processing, New York: Academic, 1999.
12. Gonzales, R.C. and Woods, E.W., Digital Image Processing, Upper Saddle River, NJ: Prentice Hall, 2002.
13. Sedov, A.V., Modelirovanie ob”ektov s diskretno-raspredelennymi parametrami: dekompozitsionnyi podkhod (Modeling Objects with Discrete-Distributed Parameters: a Decomposition Approach), Moscow: Nauka, 2010.
14. Cogranne, R. and Retraint, F., Statistical detection of defects in radiographic images using an adaptive parametric model, Signal Process., 2014, vol. 96, pp. 173–189.10.1016/j.sigpro.2013.09.016 ↗
15. Bocharova, O.V., Lyzhov, V.A., and Andzhikovich, I.E., Some features of wave fields on the surface of bodies weakened by flaws, Yuzh. Nauch. Tsentra, Ross. Akad. Nauk, 2013, vol. 9, no. 2, pp. 11–15.
16. Bocharova, O.V., Andzhikovich, I.E., and Vorovich, E.I., On the problem of studying surface wave fields with thin-film ferroelectric sensors, Yuzh. Nauch. Tsentra, Ross. Akad. Nauk, 2015, vol. 11, no. 1, pp. 30–35.