The Detection and Characterization of Defects in Metal/Non-metal Sandwich Structures by Thermal NDT, and a Comparison of Areal Heating and Scanned Linear Heating by Optical and Inductive Methods; Journal of Nondestructive Evaluation; Vol. 40, iss. 2
| Parent link: | Journal of Nondestructive Evaluation Vol. 40, iss. 2.— 2021.— [44, 13 p.] |
|---|---|
| Korporace: | , |
| Další autoři: | , , , , , |
| Shrnutí: | Title screen It is common on space vehicles to have thermal insulation adhesively bonded to a metal structure. A typical defect in such structures is an interlayer disbond, which may occur either between the insulation and the metal substructure or between the layers of multilayer thermal insulation. One-sided thermal nondestructive testing (TNDT) using surface optical heating, such as Xenon fash or quartz tube, may detect disbonds if the thermal insulation thickness does not exceed a few millimeters and disbonds are not very small. In thicker insulation, the efectiveness of the inspection can be improved by using electrical induction to heat the metal base. In both cases, thermal excitation can be areal heating, which is heat projected over an area by a stationary heat source, or scanned linear heating (SLH), which is a linear heater scanned across the test subject. In the latter, either the linear heater is moved across a stationary test subject, or the linear heater is stationary and the test subject is moved. The SLH method usually provides a higher inspection rate (inspected area unit time). In this research, both the theoretical and experimental features of both optical and induction heating have been investigated and compared in the application to non-metallic insulation adhesively bonded to a metal structure. The efectiveness of using neural networks (NN) for characterizing defects has also been studied to demonstrate that optimal NN training should involve 4-5 points selected in defect areas close to non-defect areas, and the NN input data should be prepared by applying the known technique of Thermographic Signal Reconstruction (TSR). Since SLH provides more uniform heating, it provides higher quality IR thermograms than those obtained from areal (fash) heating and this improves the detectability of defects in thermal insulation to a depth of 4-6 mm. Other advantages of SLH for TNDT testing are (1) an inspection rate that is twice as high as an area heating technique and (2) a better potential for fully automated (robotic) testing. Режим доступа: по договору с организацией-держателем ресурса |
| Jazyk: | angličtina |
| Vydáno: |
2021
|
| Témata: | |
| On-line přístup: | https://doi.org/10.1007/s10921-021-00772-y |
| Médium: | Elektronický zdroj Kapitola |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=665319 |
MARC
| LEADER | 00000naa0a2200000 4500 | ||
|---|---|---|---|
| 001 | 665319 | ||
| 005 | 20250129164344.0 | ||
| 035 | |a (RuTPU)RU\TPU\network\36518 | ||
| 035 | |a RU\TPU\network\34206 | ||
| 090 | |a 665319 | ||
| 100 | |a 20210913d2021 k||y0rusy50 ba | ||
| 101 | 0 | |a eng | |
| 102 | |a US | ||
| 135 | |a drcn ---uucaa | ||
| 181 | 0 | |a i | |
| 182 | 0 | |a b | |
| 200 | 1 | |a The Detection and Characterization of Defects in Metal/Non-metal Sandwich Structures by Thermal NDT, and a Comparison of Areal Heating and Scanned Linear Heating by Optical and Inductive Methods |f A. O. Chulkov, C. Tuschl, D. A. Nesteruk [et al.] | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 36 tit.] | ||
| 330 | |a It is common on space vehicles to have thermal insulation adhesively bonded to a metal structure. A typical defect in such structures is an interlayer disbond, which may occur either between the insulation and the metal substructure or between the layers of multilayer thermal insulation. One-sided thermal nondestructive testing (TNDT) using surface optical heating, such as Xenon fash or quartz tube, may detect disbonds if the thermal insulation thickness does not exceed a few millimeters and disbonds are not very small. In thicker insulation, the efectiveness of the inspection can be improved by using electrical induction to heat the metal base. In both cases, thermal excitation can be areal heating, which is heat projected over an area by a stationary heat source, or scanned linear heating (SLH), which is a linear heater scanned across the test subject. In the latter, either the linear heater is moved across a stationary test subject, or the linear heater is stationary and the test subject is moved. | ||
| 330 | |a The SLH method usually provides a higher inspection rate (inspected area unit time). In this research, both the theoretical and experimental features of both optical and induction heating have been investigated and compared in the application to non-metallic insulation adhesively bonded to a metal structure. The efectiveness of using neural networks (NN) for characterizing defects has also been studied to demonstrate that optimal NN training should involve 4-5 points selected in defect areas close to non-defect areas, and the NN input data should be prepared by applying the known technique of Thermographic Signal Reconstruction (TSR). Since SLH provides more uniform heating, it provides higher quality IR thermograms than those obtained from areal (fash) heating and this improves the detectability of defects in thermal insulation to a depth of 4-6 mm. Other advantages of SLH for TNDT testing are (1) an inspection rate that is twice as high as an area heating technique and (2) a better potential for fully automated (robotic) testing. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 461 | |t Journal of Nondestructive Evaluation | ||
| 463 | |t Vol. 40, iss. 2 |v [44, 13 p.] |d 2021 | ||
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a infrared thermography | |
| 610 | 1 | |a thermal insulation | |
| 610 | 1 | |a defect characterization | |
| 610 | 1 | |a neural network | |
| 610 | 1 | |a induction heating | |
| 610 | 1 | |a optical heating | |
| 610 | 1 | |a scanned linear heating | |
| 610 | 1 | |a инфракрасная термография | |
| 610 | 1 | |a теплоизоляция | |
| 610 | 1 | |a дефекты | |
| 610 | 1 | |a нейронные сети | |
| 610 | 1 | |a индукционный нагрев | |
| 610 | 1 | |a многослойные структуры | |
| 610 | 1 | |a неразрушающий контроль | |
| 610 | 1 | |a оптические методы | |
| 610 | 1 | |a индуктивные методы | |
| 701 | 1 | |a Chulkov |b A. O. |c specialist in the field of non-destructive testing |c Deputy Director for Scientific and Educational Activities; acting manager; Senior Researcher, Tomsk Polytechnic University, Candidate of Technical Sciences |f 1989- |g Arseniy Olegovich |3 (RuTPU)RU\TPU\pers\32220 |9 16220 | |
| 701 | 1 | |a Tuschl |b C. | |
| 701 | 1 | |a Nesteruk |b D. A. |c specialist in the field of descriptive geometry |c Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences |f 1979- |g Denis Alekseevich |3 (RuTPU)RU\TPU\pers\31502 |9 15663 | |
| 701 | 1 | |a Oswald-Tranta |b B. | |
| 701 | 1 | |a Vavilov |b V. P. |c Specialist in the field of dosimetry and methodology of nondestructive testing (NDT) |c Doctor of technical sciences (DSc), Professor of Tomsk Polytechnic University (TPU) |f 1949- |g Vladimir Platonovich |3 (RuTPU)RU\TPU\pers\32161 |9 16163 | |
| 701 | 1 | |a Kuimova |b M. V. |c linguist |c Head of the Department of Tomsk Polytechnic University, Candidate of pedagogical sciences |f 1976- |g Marina Valerievna |3 (RuTPU)RU\TPU\pers\32753 |9 16631 | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа неразрушающего контроля и безопасности |b Центр промышленной томографии |b Научно-производственная лаборатория "Тепловой контроль" |3 (RuTPU)RU\TPU\col\23838 |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Школа базовой инженерной подготовки |b Отделение иностранных языков |3 (RuTPU)RU\TPU\col\23510 |
| 801 | 2 | |a RU |b 63413507 |c 20210913 |g RCR | |
| 856 | 4 | |u https://doi.org/10.1007/s10921-021-00772-y | |
| 942 | |c CF | ||