Geodesic
Modeling of a thermal response of cast-iron concrete system under active thermal non-destructive testing
Matematičeskoe modelirovanie, Tome 31 (2019) no. 3, pp. 23-40.

Voir la notice de l'article provenant de la source Math-Net.Ru

The article is devoted to mathematical modeling of the thermophysical experiment related to diagnostics of a space under a cast-iron tubbing of a shaft lining by the optical lock-in thermography. In the article it is presented a numerical solution of the twodimensional boundary value problem that describes heat transfer processes by conduction, convection and radiation. Detection of a defect placed within the space under the tubbing is carried out by analyzing of phase characteristics of temperature oscillations on the tubbing surface that is available for observing. To compute the phase characteristics, the digital lock-in correlation method is used. In the article an influence on the phase characteristics of heating frequency, heating time and noise is investigated. For mathematical processing of noisy data, the algorithm, based on using the reference temperature distribution on the tubbing surface covering the defect-free lining, is developed. This algorithm consists of the Kalman filter, the Rauch-Tung-Striebel smoothing procedure and the smoothing spline method with criterial choosing of the smoothing parameter. An efficiency of the proposed approach is illustrated by results of numerical experiments.
Keywords: infrared thermography, thermal non-destructive testing, optical lock-in thermography, signal processing, numerical modeling. 
@article{MM_2019_31_3_a1,
     author = {M. S. Zhelnin and O. A. Plekhov and L. Yu. Levin},
     title = {Modeling of a thermal response of cast-iron concrete system under active thermal non-destructive testing},
     journal = {Matemati\v{c}eskoe modelirovanie},
     pages = {23--40},
     publisher = {mathdoc},
     volume = {31},
     number = {3},
     year = {2019},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MM_2019_31_3_a1/}
}
TY  - JOUR
AU  - M. S. Zhelnin
AU  - O. A. Plekhov
AU  - L. Yu. Levin
TI  - Modeling of a thermal response of cast-iron concrete system under active thermal non-destructive testing
JO  - Matematičeskoe modelirovanie
PY  - 2019
SP  - 23
EP  - 40
VL  - 31
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/MM_2019_31_3_a1/
LA  - ru
ID  - MM_2019_31_3_a1
ER  - 
%0 Journal Article
%A M. S. Zhelnin
%A O. A. Plekhov
%A L. Yu. Levin
%T Modeling of a thermal response of cast-iron concrete system under active thermal non-destructive testing
%J Matematičeskoe modelirovanie
%D 2019
%P 23-40
%V 31
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/MM_2019_31_3_a1/
%G ru
%F MM_2019_31_3_a1
M. S. Zhelnin; O. A. Plekhov; L. Yu. Levin. Modeling of a thermal response of cast-iron concrete system under active thermal non-destructive testing. Matematičeskoe modelirovanie, Tome 31 (2019) no. 3, pp. 23-40. http://geodesic.mathdoc.fr/item/MM_2019_31_3_a1/

[1] Ju.P. Olhovikov, Krep kapitalnykh vyrabotok kaliinykh i solianykh rudnikov, Ugletekhizdat, M.; Nedra, M., 1984, 283 pp.

[2] GOST R 57054-2016 «Tiubingi chugunnye. Komplekty tiubingovykh kolets»

[3] Pravila bezopasnosti pri vedenii gornykh rabot i pererabotke tverdykh poleznykh iskopaemykh: federalnye normy i pravila v oblasti promyshlennoi bezopasnosti, ZAO NTC PB, M., 2015, 276 pp.

[4] A.A. Zhukov, “Razrabotka i adaptatsiia tekhnologii diagnostiki betonnoi krepi shakhtnykh stvolov kaliinykh rudnikov”, Gornyi informatsionno-analiticheskii biulleten (nauchno-tekhnicheskii zhurnal), 2016, no. 8, 245–254

[5] A.I. Babkin, I.G. Sanfirov, “Geofizicheskii monitoring zatiubingovogo prostranstva”, Gornyi informatsionno-analiticheskii biulleten (nauchno-tekhnicheskii zhurnal), 2011, no. 1, 213–218

[6] A.I. Babkin, I.A. Sanfirov, “Prakticheskie primery resheniia gornotekhnicheskih zadach metodami shakhtnoi seismoakustiki”, Gornyi informacionno-analiticheskii bjulleten (nauchno-tehnicheskii zhurnal), 2011, no. 4, 152–159

[7] V.P. Vavilov, Infrakrasnaia termografiia i teplovoi kontrol, ID Spektr, M., 2009, 544 pp.

[8] V.V. Kliuev (red.), Nerazrushaiushchii kontrol i diagnostika, Spravochnik, 2-e izd., Mashinostroenie, M., 2003, 656 pp.

[9] O. Breitenstein, W. Warta, M. Langenkamp, Lock-in thermography: Basics and use for evaluating electronic devices and materials, Springer Science Business Media, 2010, 208 pp.

[10] J. Liu, W. Yang, J. Dai, “Research on thermal wave processing of lock-in thermography based on analyzing image sequences for NDT”, Infrared Physics Technology, 53:5 (2010), 348–357 | DOI

[11] D. Peng, R. Jones, “Modelling of the lock-in thermography process through finite element method for estimating the rail squat defects”, Engineering Failure Analysis, 28 (2013), 275–288 | DOI

[12] S. Ranjit, K. Kang, W. Kim, “Investigation of lock-in infrared thermography for evaluation of subsurface defects size and depth”, International Journal of Precision Engineering and Manufacturing, 16:11 (2015), 2255–2264 | DOI

[13] R. Shrestha, W. Kim, “Evaluation of coating thickness by thermal wave imaging: A comparative study of pulsed and lock-in infrared thermography-Part I: Simulation”, Infrared Physics Technology, 83 (2017), 124–131 | DOI

[14] T. Sakagami, S. Kubo, “Development of a new non-destructive testing technique for quantitative evaluations of delamination defects in concrete structures based on phase delay measurement using lock-in thermography”, Infrared Physics Technology, 43:3 (2002), 311–316 | DOI

[15] M. Yuan, H. Wu, Z. Tang, H.J. Kim, S.J. Song, J. Zhang, “Prediction of the effect of defect parameters on the thermal contrast evolution during flash thermography by finite element method”, Journal of the Korean Society for Nondestructive Testing, 34:1 (2014), 10–17 | DOI

[16] G. Busse, D. Wu, W. Karpen, “Thermal wave imaging with phase sensitive modulated thermography”, Journal of Applied Physics, 71:8 (1992), 3962–3965 | DOI

[17] D. Wu, G. Busse, “Lock-in thermography for nondestructive evaluation of materials”, Revue generale de thermique, 37:8 (1998), 693–703 | DOI

[18] C. Zöcke, A. Langmeier, R. Stößel, W. Arnold, “Reconstruction of the defect shape from lock-in thermography phase images”, Quantitative InfraRed Thermography Journal, 6:1 (2009), 63–78 | DOI

[19] L. Junyan, T. Qingju, L. Xun, W. Yang, “Research on the quantitative analysis of subsurface defects for non-destructive testing by lock-in thermography”, NDT E International, 45:1 (2012), 104–110 | DOI

[20] G. Jinlong, L. Junyan, W. Fei, W. Yang, “Inverse heat transfer approach for nondestructive estimation the size and depth of subsurface defects of CFRP composite using lock-in thermography”, Infrared Physics Technology, 71 (2015), 439–447 | DOI

[21] R. Gupta, O. Breitenstein, “Unsteady-state lock-in thermography — Application to shunts in solar cells”, Quantitative InfraRed Thermography Journal, 4:1 (2007), 85–105 | DOI

[22] A.A. Degtjarev, Sh. Tajl, “Elementy teorii adaptivnogo rasshirennogo filtra Kalmana”, Keldysh Institute preprints, 2003, 026, 35 pp. | Zbl

[23] S.S. Haykin, Kalman filtering and neural networks, Wiley, New York, 2001, 304 pp.

[24] T.C.M. Lee, “Smoothing parameter selection for smoothing splines: a simulation study”, Computational statistics Data analysis, 42:1 (2003), 139–148 | DOI | MR | Zbl

[25] A.G. Bloh, Ju.A. Zhuravlev, L.N. Ryzhkov, Teploobmen izlucheniem, Spravochnik, Energoatomizdat, M., 1991, 432 pp.

[26] A.A. Samarskii, P.N. Vabishchevich, Computational Heat Transfer, Wiley, 1996, 418 pp.

[27] P.J. Green, B.W. Silverman, Nonparametric regression and generalized linear models: a roughness penalty approach, CRC Press, 1993, 182 pp. | MR

[28] N.B. Vargaftik, Spravochnik po teplofizicheskim svoistvam gazov i zhidkostei, Nauka, M., 1972, 720 pp.

[29] GOST 1412-85 «Chugun s plastinchatym grafitom dlia otlivok»

[30] A.I. Eremkin, T.I. Koroleva, Teplovoi rezhim zdanii, uchebnoe posobie, Izdatelstvo ASV, M., 2000, 368 pp.