电子学报2025，Vol.53Issue(4)：1212-1220,9.DOI:10.12263/DZXB.20240594
基于声场特征和C扫描图像的棒材缺陷定量评价
Quantitative Evaluation Defects in Rod Workpieces Based on Acoustic Field Characteristics and C-Scan Images
摘要
Abstract
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-Gauss-ian 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 pre-dicted results are closer to the standard values compared with the quantitative results of the 6 dB drop method.The quantita-tive error for the 1.5 mm flat-bottomed hole is 19.33%,a 27.34 percentage points reduction compared to the 6 dB drop meth-od.The quantitative evaluation is performed on nylon rod with natural defects,the results show that the model can effective-ly predict the size information of natural defects in nylon rods.关键词
多元高斯声束模型/缺陷定量/C扫描成像/随机森林回归/棒料Key words
multi-gaussian beam model/flaw sizing/C-scan image/random forest regression/rod workpieces分类
信息技术与安全科学引用本文复制引用
董明,田辉,马宏伟,陈渊,曹现刚,万翔..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(4):1212-1220,9.基金项目
国家自然科学基金(No.51705418) （No.51705418）
陕西省自然科学基础研究计划—陕煤联合基金项目(No.2021JLM-07) National Natural Science Foundation of China(No.51705418) （No.2021JLM-07）
Shannxi Coal Joint Fund of Natural Science Basic Research Program(No.2021JLM-07) （No.2021JLM-07）
