Measurement of defect depth by peak second derivative method in pulse thermography

被引:0
|
作者
Feng Lichun [1 ]
He Ruigang [1 ]
Zhang Yan [1 ]
机构
[1] Capital Normal Univ, Dept Phys, Beijing 100048, Peoples R China
关键词
NDE; pulsed thermography; second derivative method;
D O I
10.1117/12.900701
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In pulse thermography, pulsed flash energy is applied to the surface and the temperature of the surface is recorded and analysed. Generally the the flash duration is short and the heating could be taken as impulse function. After the surface is heated instantaneously, heat goes down by conduction. If an area has defect below, the temprature of this area will be different from the temprature of defect free area. Analytic solution indicates that the time at which the temperature descending curve of the area with defect below separate from the curve of the defect free area is proportional to the square of the defect depth. Thus, if the deviation time is determined, the defect depth could be calculated. In real inspection, different from theoretical model, the temperature decay curve may be noisy and sometimes fluctuating. And due to the effect of three-dimentional conduction and different boundary conditions the temperature decay curve is different from the theoretical solution under ideal conditions. All these affect the identification of the deviation time and then affect the accurary of the depth measurement. Peak temperature contrast and peak slope of temperature contrast methods are popularly used in depth measurement, but all these two methods require the prior determination of a reference point that is known to be on sound material. Peak second derivative method in log scale is a reference free method which can somehow decrease the influence of noisy data and three-dimentioanl conduction. To reduce the noise induced by derivation, fitted data instead of raw data is offten used. Hower, the global data fitting is not suitable in some situation. In this paper, peak second derivative method based on patial data fitting is proposed and results are discussed. The results show that this method could improve the accuracy of depth measurement for CFRP specimen.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Rectification of depth measurement using pulsed thermography with logarithmic peak second derivative method
    Li, Xiaoli
    Zeng, Zhi
    Shen, Jingling
    Zhang, Cunlin
    Zhao, Yuejin
    INFRARED PHYSICS & TECHNOLOGY, 2018, 89 : 1 - 7
  • [2] Impact of Pulse Length on the Accuracy of Defect Depth Measurements in Pulse Thermography
    Pierce, James
    Crane, Nathan B.
    JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME, 2019, 141 (04):
  • [3] Evaluation of defect depth in CFRP composites by long pulse thermography
    Wang, Zijun
    Wan, Litao
    Zhu, Junzhen
    Ciampa, Francesco
    NDT & E INTERNATIONAL, 2022, 129
  • [4] Defect depth measurement of carbon fiber reinforced polymers by thermography
    Chen, Terry Yuan-Fang
    Chen, Jian-Lun
    SEVENTH INTERNATIONAL SYMPOSIUM ON PRECISION MECHANICAL MEASUREMENTS, 2016, 9903
  • [5] Quantitative Measurement of Defect Depth Using Pulsed Thermography: A Comparative Study
    Leksir, Yazid Laib Dit
    Amouri, Ammar
    Guerfi, Kadour
    Moussaoui, Abdelkrim
    RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING, 2023, 59 (06) : 724 - 735
  • [6] Quantitative Measurement of Defect Depth Using Pulsed Thermography: A Comparative Study
    Yazid Laib Dit Leksir
    Ammar Amouri
    Kadour Guerfi
    Abdelkrim Moussaoui
    Russian Journal of Nondestructive Testing, 2023, 59 : 724 - 735
  • [7] Logarithmic minus peak second derivative time based depth prediction
    Zeng Zhi
    Tao Ning
    Feng Li-Chun
    Zhang Cun-Lin
    ACTA PHYSICA SINICA, 2013, 62 (13)
  • [8] Analysis of long-pulse thermography methods for defect depth prediction in transmission mode
    Kalyanavalli, V
    Mithun, P. M.
    Sastikumar, D.
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2020, 31 (01)
  • [9] THE ORGAN DEPTH MEASUREMENT BY A PEAK COMPTON RATIO AND A DOUBLE PEAK METHOD
    NOSIL, J
    KLOIBER, R
    MEDICAL PHYSICS, 1984, 11 (03) : 373 - 373
  • [10] A Method of Defect Depth Estimation for Simulated Infrared Thermography Data with Deep Learning
    Fang, Qiang
    Maldague, Xavier
    APPLIED SCIENCES-BASEL, 2020, 10 (19):