Inspection of interface debonding in thermal barrier coatings using pulsed thermography

被引：0
|
作者：
Dong L. [1 ]
Guo W. [1 ]
Wang H. [1 ]
Xing Z. [1 ]
Feng F. [2 ]
Wang B. [3 ]
Gao Z. [4 ]
机构：
[1] Science and Technology on Remanufacturing Laboratory, Army Academy of Armored Forces, Beijing
[2] Department of Vehicle Engineering, Army Academy of Armored Forces, Beijing
[3] School of Engineering and Technology, China University of Geosciences, Beijing
[4] School of Material Science and Engineering, Xi'an University of Technology, Xi'an
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2019年 / 40卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Interface debonding; Pulsed thermography; Thermal barrier coating; Thermal image reconstruction; Thermal signal reconstruction;
D O I：
10.7527/S1000-6893.2019.22895
中图分类号：
学科分类号：
摘要：
This paper aims at soloving the nondestructive testing problem of interface debonding defect of thermal barrier coatings. Firstly, a preparing method for specimen with artificial debonding defects is proposed, providing more realistic thermal conduction process and controllable defect size. On this basis, pulsed thermography is employed to detect the coating specimen with artificial debonding defect, and the transient response process of the surface temperatures in debonding region and sound region of coating interface is analyzed. Standard Deviation (SD) and Normalized Contrast (NC) are used as evaluation criteria to quantitatively compare the effects of three typical thermal image reconstruction methods, which are PPT, PCA, and TSR, in the identification of debonding defects. The results indicate that, for YSZ thermal barrier coatings with a thickness of 400 μm, the debonding defects with a minimum diameter of 4 mm can be identified in raw thermal image sequency, while the debonding defects with a minimum diameter of 2 mm can be identified in all three reconstructed image sequences. The identificating ability of debonding defects have significantly improved by three reconstruction algorithms, among which the TSR reconstruction algorithm provided the best noise suppression ability for thermal image sequence. © 2019, Press of Chinese Journal of Aeronautics. All right reserved.
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