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

被引:10
作者
Chulkov, A. O. [1 ]
Tuschl, C. [2 ]
Nesteruk, D. A. [1 ]
Oswald-Tranta, B. [2 ]
Vavilov, V. P. [1 ]
Kuimova, M. V. [1 ]
机构
[1] Tomsk Polytech Univ, Natl Res, Lenin Ave 30, Tomsk 634050, Russia
[2] Univ Leoben, Inst Automat, Peter Tunnerstr 27, A-8700 Leoben, Austria
基金
俄罗斯科学基金会; 俄罗斯基础研究基金会;
关键词
Infrared thermography; Thermal insulation; Defect characterization; Neural network; Induction heating; Optical heating; Scanned linear heating; THERMOGRAPHY; OPTIMIZATION; INSPECTION;
D O I
10.1007/s10921-021-00772-y
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
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 flash 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 effectiveness 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 effectiveness 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 (flash) 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.
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页数:13
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