程慎行,陈尧,万智龙,等. 棒材周向扫查下的极坐标合成孔径聚焦成像检测[J]. 失效分析与预防,2025,20(1):25-32,72. doi: 10.3969/j.issn.1673-6214.2025.01.004
    引用本文: 程慎行,陈尧,万智龙,等. 棒材周向扫查下的极坐标合成孔径聚焦成像检测[J]. 失效分析与预防,2025,20(1):25-32,72. doi: 10.3969/j.issn.1673-6214.2025.01.004
    CHENG Shenxing,CHEN Yao,WAN Zhilong,et al. Detection of polar coordinates synthetic aperture focusing imaging for the bars under circumferential scanning[J]. Failure analysis and prevention,2025,20(1):25-32,72. doi: 10.3969/j.issn.1673-6214.2025.01.004
    Citation: CHENG Shenxing,CHEN Yao,WAN Zhilong,et al. Detection of polar coordinates synthetic aperture focusing imaging for the bars under circumferential scanning[J]. Failure analysis and prevention,2025,20(1):25-32,72. doi: 10.3969/j.issn.1673-6214.2025.01.004

    棒材周向扫查下的极坐标合成孔径聚焦成像检测

    Detection of Polar Coordinates Synthetic Aperture Focusing Imaging for the Bars Under Circumferential Scanning

    • 摘要: 为实现周向扫查下棒材截面整体内部的缺陷成像检测,提出了极坐标合成孔径聚焦(PCSAFT)成像检测方法。根据棒材内部结构和声束传播路径,推导出极坐标系下的探头−棒材周向时距曲线,算得极坐标系下的周向检测等时面,实现了棒材截面的极坐标合成孔径聚焦图像重建。针对直径40 mm棒材检测的成像结果表明:所提方法可有效呈现出棒材外表面轮廓和缺陷的实际位置,内部11个ϕ 2 mm平底孔的角度最大偏差低于3.50°,缺陷最多深度偏差低于1.1 mm。相比合成孔径聚焦技术(SAFT)成像,PCSAFT成像结果更为直观,更加适用于自动化检测过程中的缺陷检测与判定。

       

      Abstract: To realize the defect imaging of the whole interior of a bar section under circum-scanning, a polar coordinates synthetic aperture focusing technique (PCSAFT) is proposed in this paper. According to athe internal structure and propagation path of tbe beam within the bar, the circumferential time-distance curve of the probe and bar in polar coordinate system is derived, and the circumferential detection isochronous surface in polar coordinate system is calculated. Imaging results achieved from a bar with a diameter of 40 mm show that the proposed method can effectively represent the outline of the bar’s outer surface and accurately lacate the defects. For the 11 internal flat bottom holes with a diameter of 2 mm, the maximum angle deviation is less than 3.50°, and the maximum depth deviation of the defects is less than 1.1 mm. Compared with traditional SAFT imaging, the results of CSSAFT imaging proposed in this paper are more intuitive and more suitable for defect detection and determination in automatic inspection processes.

       

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