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    面向岩体结构自动识别的钻孔图像修复方法研究

    Study on Borehole Image Restoration Method for Automatic Recognition of Rock Structure

    • 摘要: 钻孔摄像技术是岩体结构精细探测的重要手段,测试过程中不可避免的探头偏心问题显著降低了钻孔图像的质量,进而制约了岩体结构信息的精准自动识别.为此,提出一种基于灰度特征分析的钻孔图像修复方法,以优化岩体结构识别效果和几何参数测量精度.首先,基于钻孔摄像工作原理,开展了探头偏心在钻孔图像中的响应特征分析,建立了图像灰度特征模型,形成了全景成像探头三维定位分析方法.然后,基于探头空间轨迹计算图像灰度误差矩阵,实现了探头偏心引起的图像灰度误差校正及修复.并定量分析了探头偏心导致的钻孔图像方位角误差,建立了基于探头空间定位校正的图像透视误差修复方法.最后,开展了典型钻孔图像的应用分析.研究结果表明,基于图像灰度特征分析获取探头空间位置信息,进而开展灰度误差和透视误差校正,能够对钻孔图像效果和测量精度有较大的提升,二值化处理结果也验证了修复后图像可更好地显现岩体结构关键信息,降低其他因素的干扰,为岩体结构自动识别提供了良好的图像数据基础.

       

      Abstract: Borehole imaging technology is a crucial method for detailed rock mass structure detection.The unavoidable probe eccentricity issue during testing significantly decreases the quality of borehole images,thereby limiting the precise automatic identification of rock mass structure information.To address this challenge,a borehole image restoration method based on grayscale feature analysis is proposed to enhance the identification of rock mass structure and the accuracy of geometric parameter measurements.Initially,the response characteristics of probe eccentricity in borehole images are analyzed based on the operating principle of borehole imaging.An image grayscale feature model is formulated,and a method for three-dimensional positioning analysis of the panoramic imaging probe is established.Subsequently,by calculating the grayscale error matrix based on spatial trajectory of the probe,the correction and restoration of image grayscale errors caused by probe eccentricity are achieved.A quantitative analysis of the azimuth error in borehole images induced by probe eccentricity is conducted,and a method for image perspective error restoration based on probe spatial positioning correction is developed.Application analysis of typical borehole images demonstrates that,by acquiring spatial position information of the probe based on grayscale feature analysis and conducting grayscale and perspective error corrections,the effectiveness and measurement accuracy of borehole images are significantly enhanced.The binarization processing results also validate that the restored images can more effectively reveal crucial rock mass structure information and minimize interference from external factors,thus providing image data foundation for automatic identification of rock mass structure.

       

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