Quantitative Detection of Cracks in Steel Using Eddy Current Pulsed Thermography.
Quantitative Detection of Cracks in Steel Using Eddy Current Pulsed Thermography.
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使用涡流脉冲热成像技术定量检测钢中的裂纹
DOI：
10.3390/s18041070
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发表时间：
2018-04-02
期刊：
影响因子：
--
通讯作者：
Zhang H
中科院分区：
文献类型：
--
作者：
Shi Z;Xu X;Ma J;Zhen D;Zhang H
小裂纹是钢中常见的缺陷，在工业应用中经常导致灾难性事故。各种无损检测方法已被调查的裂纹检测，但目前大多数方法集中在定性裂纹识别和图像处理。在这项研究中，涡流脉冲热成像（ECPT）应用于定量检测裂纹的基础上导数分析的温度变化。在仿真研究中，分析了激励参数对温度变化的影响。利用Canny边缘检测算法对热图像中的裂纹轮廓和位置进行了识别。然后，通过裂纹轮廓确定一个或多个轨迹，以便通过其温度分布确定裂纹边界。得到了沿轨迹沿着的斜率曲线。最后，通过对斜率曲线特征的分析，对裂缝尺寸进行了定量分析。实验验证表明，该方法可以定量检测裂纹尺寸，误差小于1%。因此，所提出的ECPT方法被证明是一个可行的和有效的无损检测方法定量裂纹。
Small cracks are common defects in steel and often lead to catastrophic accidents in industrial applications. Various nondestructive testing methods have been investigated for crack detection; however, most current methods focus on qualitative crack identification and image processing. In this study, eddy current pulsed thermography (ECPT) was applied for quantitative crack detection based on derivative analysis of temperature variation. The effects of the incentive parameters on the temperature variation were analyzed in the simulation study. The crack profile and position are identified in the thermal image based on the Canny edge detection algorithm. Then, one or more trajectories are determined through the crack profile in order to determine the crack boundary through its temperature distribution. The slope curve along the trajectory is obtained. Finally, quantitative analysis of the crack sizes was performed by analyzing the features of the slope curves. The experimental verification showed that the crack sizes could be quantitatively detected with errors of less than 1%. Therefore, the proposed ECPT method was demonstrated to be a feasible and effective nondestructive approach for quantitative crack detection.
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影响因子：
4.2
作者：
Wilson, John;Tian, Guiyun;Almond, Darryl
通讯作者：
Almond, Darryl
用于金属材料和缺陷表征的不同激励配置的涡流脉冲热成像
DOI：
10.3390/s16060843
发表时间：
2016-06-08
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Tian GY;Gao Y;Li K;Wang Y;Gao B;He Y
通讯作者：
He Y
影响因子：
4.2
作者：
Abidin, Ilham Zainal;Tian, Gui Yun;Almond, Darryl
通讯作者：
Almond, Darryl
影响因子：
6.7
作者：
Li, Kongjing;Tian, Gui Yun;Crichton, Stuart
通讯作者：
Crichton, Stuart
DOI：
10.3390/s151025882
发表时间：
2015-10-13
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Zhou X;Zhou J;Tian G;Wang Y
通讯作者：
Wang Y