文献类型：期刊文献

中文题名：基于动态扫描涡流热成像技术的碳钢结构损伤检测

英文题名：Structural Damage Evaluation of Carbon Steel Based on Dynamic Scanning Eddy Current Infrared Thermography

作者：涂彦昕[1];梅红伟[1];刘立帅[2];沈泽锴[1];王黎明[1]

机构：[1]清华大学深圳国际研究生院广东省复杂滨海环境电力装备可靠性工程技术研究中心,深圳518055;[2]承压系统与安全教育部重点实验室(华东理工大学),上海200237

年份：2023

卷号：38

期号：11

起止页码：2999

中文期刊名：电工技术学报

外文期刊名：Transactions of China Electrotechnical Society

收录：CSTPCD;;EI(收录号：20232814379227);Scopus;北大核心:【北大核心2020】；CSCD:【CSCD2023_2024】；

基金：国家自然科学基金面上资助项目(51977117)。

语种：中文

中文关键词：动态扫描涡流热成像;热波信号重构;无损检测;最小相频

外文关键词：Dynamic scanning eddy current infrared thermography;thermographic signal reconstruction;nondestructive detection;the frequency of minimum phase

摘要：针对工业系统中碳钢结构损伤检测的实际需求,该文采用动态扫描涡流热成像(DSECT)技术对人工制备缺陷碳钢试件进行检测,提出了针对DSECT的热图序列重建算法,并利用最小相频特征实现了缺陷深度的定量检测。该文推导建立了DSECT热波传播模型,并在对数坐标下实现了热波信号的拟合,消除了热波信号的噪声;提出了基于热波信号重构的热图序列重建算法,在视场中剔除了线圈,实现了视场中被检试件的均匀加热;对人工制备的缺陷试件进行检测研究,验证了重建算法的有效性;通过快速傅里叶变换提取了最小相频特征,利用缺陷深度与最小相频平方根倒数的线性关系,实现了对缺陷深度的定量估计。研究表明,DSCET解决了传统涡流热成像方法的不足,该文提出的重建算法改善了成像视场,便于对碳钢缺陷进行定量检测。
As a common metal,carbon steel has been utilized widely in the power industry.Nevertheless,faults such as fatigue,cracks,and delamination are unavoidable in carbon steel during the process of manufacture and use,and these defects can even lead to the fracture failure of equipment.Detecting structural defects in carbon steel in a timely manner is crucial for ensuring the safety of power industrial systems.Compared to traditional non-destructive testing techniques,dynamic scanning eddy current infrared thermography(DSECT)has application potential for the inspection of carbon steel materials in the power industry.For the practical needs of structural damage detection,the principle of DSECT and related algorithms are explored,as well as the applicability of the technology for detecting faults in carbon steel.Firstly,the thermal wave propagation model of DSECT is derived based on Fourier heat conduction.Secondly,an algorithm for thermographic signal reconstruction(TSR)is proposed,in which the thermal wave signal is fitted in the logarithmic coordinate system to eliminate the noise of the thermal wave signal.Thirdly,an experimental study is carried out to verify the effectiveness of the TSR algorithm by detecting artificial defective carbon steel specimens using DSECT.Finally,the frequency of the minimum phase is extracted by the fast Fourier transform for the purpose of quantitatively detecting the defect depth,and the defect depth is estimated quantitatively by using the linear relationship between the defect depth and the inverse of the square root of the frequency of the minimum phase.In a word,DSCET overcomes the drawbacks of traditional non-destructive testing,and the related algorithm enhances imaging and defect depth measurement.Experimental test results on artificial defect samples show that the coil arrival order matches the peak temperature arrival order.The temperature at the detection point remains largely constant while the coil does not reach the detection point,increases rapidly as the coil leaves the detection point,and peaks as the coil leaves the effective heating region.The TSR-based thermogram sequence algorithm is used to reconstruct the original experimental data and the results show that,the thermophysical change process in the reconstructed thermogram sequence conforms to the thermal wave propagation law;the reconstruction algorithm can eliminate coils from the field of view and achieve uniform heating of the tested specimen.In addition,the minimum phase in the reconstructed thermogram is linearly proportional to the frequency,and the frequency domain properties are correlated with defect depth.The defect depth can be fitted with the square root inverse of the frequency of the minimum phase as a linear relationship,and the goodness of fit is 0.9912.Results show that the DSECT approach and related algorithms proposed can depict faults in two-dimensional imaging more simply and clearly,and also offer quantitative measures of defect depth.The key conclusions are as follows.(1)DSECT's dynamic coil scanning allows for a single,wide-range specimen detection,overcoming the single-coil excitation method's limitations.(2)By using TSR algorithm,a smooth reconstruction of the thermal wave signal can be accomplished and the thermal wave signal noise is eliminated.(3)The TSR-based reconstruction method of the thermogram sequence eliminates the coils in the thermogram field of view and achieves uniform heating of the specimen in the thermogram.(4)Minimum phase is the effective feature for quantitative detection,and the defect depth can be quantitatively estimated using the linear relationship between the defect depth and the inverse of the square root of the minimum phase frequency.