A comprehensive method of a defect map forming based on thermal response patterns
DOI:
https://doi.org/10.15276/opu.2.68.2023.12Keywords:
thermogram, thermal response, defect map, statistical analysis, probability distribution, threshold value, signal-to-noise ratioAbstract
The study considers contemporary approaches used in the analysis of infrared thermography results of a test object aimed at identifying structural features for defect map formation. Emphasis is placed on the advantages of employing statistical analysis methods in thermogram analysis, involving the quantitative assessment of signal-to-noise ratio and optimizing the thermographic analysis procedure through global extremum search of the objective function. According to the developed methodology, a set of four possible outcomes resulting from the thermographic analysis of a test object is examined, including true positive, false positive, true negative, and false negative results. The analysis of thermographic procedure results for the detection of a potential defect in an individual thermogram element is determined through the probability distribution function of temperature, which is compared with a similar function for a homogeneous section of the test object. In the basic methodology, probability distribution parameters for a homogeneous section of the test object and a section with structural features differ in terms of mean and variance. By dividing the temperature probability distribution area with a threshold value, four zones are formed: a zone where a defect is guaranteed to be absent, a zone where a defect is not detected according to the chosen threshold value, a zone where a defect is detected according to the chosen threshold value, and a zone where a defect is guaranteed to be present. The basic approach, based on statistical methods, allows determining the accuracy of thermographic analysis for an individual thermogram element by calculating the signal-to-noise ratio based on the fundamental indicators of mean and variance of the temperature probability distribution. Within the extended scheme of statistical analysis of thermographic investigation results, a z-value is determined, based on the number of neighboring thermogram elements corresponding to a homogeneous section and a section with potential structural features.
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Saffiudeen M.F., Syed A., Mohammed F.T. Failure analysis of heat Exchanger using Internal Rotary inspection System (IRIS). Journal of Failure Analysis and Prevention. 2021. Vol. 21(2). P. 494–498. DOI: https://doi.org/10.1007/ s11668-020-01093-4.
Cryogenic solutions for IR detectors – a guideline for selection / Griot R., Vasse Ch., Arts R., Ivanov R., Höglund L., Costard E. Opto-Electronics Review. 2023. P. 45–66. DOI: https://doi.org/10.24425/ opelre.2023.144566.
Billaha M.A., Das M.K. Performance analysis of AlGaAs/GaAs/InGaAs-based asymmetric long-wavelength QWIP. Applied Physics A. 2019. Vol. 125(7). P. 19–27. DOI: https://doi.org/10.1007/ s00339-019-2750-2.
High-performance MCT and QWIP IR detectors at Sofradir / Reibel Y., Rubaldo L., Manissadjian A., Billon-Lanfrey D., Rothman J., de Borniol E., Destéfanis G., Costard E. SPIE Proceedings. 2012. P. 11 17. DOI: https://doi.org/10.1117/ 12.975671.
Sengar S. Power Quality Improvement in hybrid power system integration using FPA and IC Controller. International Journal of Intelligent Engineering and Systems. 2022. Vol. 15(2). P. 89–98. DOI: https://doi.org/10.22266/ijies2022. 0430.09.
Bias-free operational monolithic symmetric-connected Photodiode Array / Yang D., Huang Y., Liu T., Ma X., Duan X., Liu K., Ren X. Chinese Optics Letters. 2021. Vol. 18(1). P. 25–31. DOI: https://doi.org/10.3788/ col202018.012501.
Vavilov V., Burleigh D. Equipment for active TNDT. Infrared Thermography and Thermal Nondestructive Testing. 2022. P. 331–339. DOI: https://doi.org/10.1007/978-3-030-48002-8_8.
Mirzabeigi S., Razkenari M. Automated vision-based building inspection using drone thermography. Construction Research Congress. 2022. 39–44. DOI: https://doi.org/10.1061/9780784483961.077.
Domin J., Kielan P., Lamkowski K. Robotic Measurement System dedicated for inspection and diagnostics of building structures using thermography techniques. 2019 Applications of Electromagnetics in Modern Engineering and Medicine (PTZE). 2019. P. 17–25. DOI: https://doi.org/10.23919/ptze.2019.8781725.
Yumnam M., Gupta H., Ghosh D., Jaganathan J. Inspection of Concrete Structures externally reinforced with FRP composites using active infrared thermography: A Review. Construction and Building Materials. 2021. Vol. 310. P. 52–65. DOI: https://doi.org/10.1016/j.conbuildmat.2021.125265.
Lozanov Y., Tzvetkova S., Petleshkov A. Determination of the periodicity for thermographic tests of the electrical equipment. 2021 17th Conference on Electrical Machines, Drives and Power Systems (ELMA). 2021. P. 84–90. DOI: https://doi.org/10.1109/elma52514.2021.9502984.
Haraszti F. Thermographic inspection in the electric industry. Acta Materialia Transilvanica. 2018. Vol. 1(2). P. 77–80. DOI: https://doi.org/10.2478/amt-2018-0026.
Berg A., Ahlberg J., Felsberg M. Enhanced analysis of thermographic images for monitoring of District Heat Pipe Networks. Pattern Recognition Letters. 2016. Vol 83. P. 215–223. DOI: https://doi.org/ 10.1016/j.patrec.2016.07.002.
Marinetti S., Vavilov V. IR thermographic detection and characterization of hidden corrosion in metals: General analysis. Corrosion Science. 2010. Vol. 52(3). P. 865–872. DOI: https://doi.org/ 10.1016/j.corsci.2009. 11.005.
Thermographic investigation on fluid oscillations and transverse interactions in a fully metallic flat-plate pulsating heat pipe / Pagliarini L., Cattani L., Ayel V., Slobodeniuk M., Romestant C., Bozzoli F. Applied Sciences. 2023. Vol. 13(10). P. 51–63. DOI: https://doi.org/10.3390/app13106351.
Strutz T., Specht O., Muller E., Wild W. Compression of thermographic images in Welding Engineering: A comparative study. 2000 5th International Conference on Actual Problems of Electronic Instrument Engineering Proceedings. APEIE-2000. Devoted to the 50th Anniversary of Novosibirsk State Technical University. 2019. Vol. 1. (Cat. No.00EX383). P. 91–113. DOI: https://doi.org/ 10.1109/apeie.2000.913130.
Álvarez-Tey G., García-López C. Strategy based on two stages for IR thermographic inspections of photovoltaic plants. Applied Sciences. 2022. Vol. 12(13). P. 6331–6343. DOI: https://doi.org/ 10.3390/app12136331.
Vavilov V.P., Chulkov A.O. 1D and 3D defect characterization in IR thermographic NDT. Proceedings of QIRT Asia. 2019. P. 11–16. DOI: https://doi.org/10. 21611/qirt.2019.032.
