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1.西安科技大学机械工程学院,陕西西安 710054
2.陕西省矿山机电装备智能检测与控制重点实验室,陕西西安 710054
Received:25 June 2024,
Revised:2024-11-05,
Published:25 April 2025
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董明, 田辉, 马宏伟, 等. 基于声场特征和C扫描图像的棒材缺陷定量评价[J]. 电子学报, 2025, 53(04): 1212-1220.
DONG Ming, TIAN Hui, MA Hong-wei, et al. Quantitative Evaluation Defects in Rod Workpieces Based on Acoustic Field Characteristics and C-Scan Images[J]. Acta Electronica Sinica, 2025, 53(04): 1212-1220.
董明, 田辉, 马宏伟, 等. 基于声场特征和C扫描图像的棒材缺陷定量评价[J]. 电子学报, 2025, 53(04): 1212-1220. DOI:10.12263/DZXB.20240594
DONG Ming, TIAN Hui, MA Hong-wei, et al. Quantitative Evaluation Defects in Rod Workpieces Based on Acoustic Field Characteristics and C-Scan Images[J]. Acta Electronica Sinica, 2025, 53(04): 1212-1220. DOI:10.12263/DZXB.20240594
缺陷定量评价是无损检测领域研究的重点,超声波的扩散导致C扫描图像边缘模糊,影响缺陷定量精度.为了提高棒材缺陷定量的准确性,提出了基于声场特征和C扫描图像的棒材缺陷定量评价方法.基于多元高斯声束模型,根据超声波在曲面界面的传播规律,建立了水浸条件下棒材内部的声场模型,仿真得到棒料内部的声场分布,提取缺陷所在目标平面的声场特征值.以尼龙棒为研究对象,对含有不同深度、不同直径平底孔的尼龙棒试件进行超声C扫描成像,提取C扫描图像的特征值.建立数据集并训练随机森林回归模型,利用训练后的回归模型对测试集进行预测,得到的平底孔尺寸值比6 dB下降法的结果更接近于标准值,对于1.5 mm平底孔的定量误差为19.33%,下降了27.34个百分点.对含有自然缺陷的尼龙棒试件进行定量评价,结果表明该方法能够准确得到尼龙棒自然缺陷的尺寸信息.
Flaw sizing is the focus of research in the field of non-destructive testing. The diffusion of ultrasonic waves causes edge blurring of C-scan images
which affects the accuracy of flaw sizing. A defects quantitative evaluation method for rod workpieces is proposed based on acoustic field characteristics and C-scan images. Based on the multi-Gaussian beam model
according to the propagation law of the ultrasonic wave at a curved interface
the acoustic field distribution of the spherical focusing probe under the curved surface condition is deduced
and the acoustic field characteristic values of the target plane where the defect is located are extracted. Nylon rod samples with flat-bottomed holes of different depths and diameters are scanned by ultrasonic C-scan system
and the characteristic values of the C-scan images are extracted. A dataset is created and a random forest regression model is trained. The test set is processed by the trained model
and the predicted results are closer to the standard values compared with the quantitative results of the 6 dB drop method. The quantitative error for the 1.5 mm flat-bottomed hole is 19.33%
a 27.34 percentage points reduction compared to the 6 dB drop method. The quantitative evaluation is performed on nylon rod with natural defects
the results show that the model can effectively predict the size information of natural defects in nylon rods.
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