"Tekhnichna Diahnostyka ta Neruinivnyi Kontrol" (Technical Diagnostics and Non-Destructive Testing) #2, 2025, pp. 18-22
Application of wavelet analysis and differential-integral graphical methods for thermograms processing in thermal nondestructive testing
V.O. Storozhenko, O.V. Miahkyi, S.M. Meshkov, R.P. Orel
RTC «Thermocontrol» of Kharkiv National University of Radio Electronics. 14 Nauky Ave., 61166, Kharkiv,
Ukraine. E-mail: roman.orel@nure.ua
The problem of increasing the informativeness and reliability of the results of non-destructive testing of high-tech objects of
complex structures by the active thermal method is considered. To solve this, we suggest combining the developed integral-differential
signal processing method with existing information processing methods based on the formalization of the description of
temperature fields. The stages of this transformation are considered: the formation of an operator that characterizes the temperature
field that arises on the surface of the control object due to the action of thermal influence and boundary conditions associated
with its state and structure. The relations between the stages were analyzed, based on which obstacles and noises were identified
that might arise at each of them and thus limit the informativeness and probability of detecting continuity violations. The following
sources of interference were considered: non-uniform heating of the surface of the control object and non-uniformity
of the adhesive layer under the honeycomb structure cladding. A set of methods for reducing the impact of these interferences
is proposed, including wavelet analysis, joint and differential filtering methods, integral analysis methods, decision-making
criteria, and classical image processing methods adapted to the infrared range. It has been shown that the use of these methods
reduces the interference level to 0.6 °C (instead of 2 °C). The temperature contrast caused by the different thicknesses of the
adhesive layer can be reduced to 0.4 °C (instead of 1.2 °C). Statistics obtained during thermal non-destructive testing of a batch
of honeycomb samples showed that the probability of detecting suprathreshold defects can reach 90%. 9 Ref., 3 Fig.
Keywords: thermal control, composite structures, interference, wavelet, image processing, method sensitivity
Received: 29.03.25
Received in revised form: 18.04.25
Accepted: 12.05.25
References
1. Storozhenko, V.A., Maslova, V.A. (2004) Thermography in diagnostics
and nondestructive testing. Kharkov: Smith [in Russian].
2. Maldague, Xavier P.V. (2001) Theory and practice of infrared
technology for nondestructive testing. John Wiley & Sons, Inc.
3. Miahkyi, A.V., Lazorenko, O.V., Storozhenko, V.A. (2013)
Processing the results of thermal defectoscopy of honeycomb
structures in order to reduce the level of obstacle. Vіsnik NTU
«HPІ», serіja «Elektroenergetika ta peretvorjuval’na tehnіka», 34, 108–122 [in Russian].
4. Chernogor, L.F., Lazorenko, O.V., Potapov, A.A. (2012)
Wavelet analysis of model fractal ultra-wideband signals.
Proceeding of 6th International Conference on Ultrawideband
and Ultrashort Impulse Signals, Sevastopol,
Ukraine, 291–293. DOI: https://doi.org/10.1109/UWBUSIS.2012.6379809
5. Bathe, K.J., Wilson, E.L. (1976) Numerical methods in finite
element analysis. Prentice-Hall, Englewood Cliffs, N.J.
6. Storozhenko, V., Orel, R., Miahkyi, A. (2016) Optimization
of the procedure of thermal flaw detection of the honeycomb
constructions by improving the accuracy of interference function.
Eastern-European J. of Enterprise Technologies, 5(5),
12–18. DOI: https://doi.org/10.15587/1729-4061.2016.79563
7. Mallat, S.A. (2008) Wavelet tour of signal processing. The
Sparse Way, Academic Press, N.Y.
8. Lazorenko, O.V., Chernogor, L.F. (2009) Ultra-wideband
signals and processes. Kharkiv: V.N. Karazin Kharkіv National
University [in Russian].
9. Storozhenko, V.O., Meshkov, S.M., Orel, R.P., Miahkyi, O.V.
(2022) Reducing the level of interference at thermal non-destructive
testing considering the specific thermal physical
and morphological characteristics of the object. Tekh. Diahnost.
ta Neruiniv. Kontrol, 4, 47–51 [in Ukrainian]. DOI:
https://doi.org/10.37434/tdnk2022.04.04
Advertising in this issue: