基于图像识别的原始地质编录矢量化三维建模方法

    3D modeling method based on the pattern recognition of vectorized original geological logging data

    • 摘要: 针对传统原始地质编录建模未考虑图件污染、矢量化效率低、模型精确度不高等问题,提出了一种基于图像识别的原始地质编录矢量化三维建模方法,该方法主要包括:①读取并裁剪原始地质编录图纸;②采用Rosenfeld算法降噪细化图形;③采用Douglas-Peucker算法提取并抽稀分离地质素描界线;④三维化地质编录界线;⑤采用Coons曲面精准构建三维地质体模型。该方法成功应用于个旧矿区高松矿田的三维地质建模中,数值模拟实验结果表明:相比于传统原始地质编录三维建模,使用该方法的建模结果更能真实反映矿体形态变化,建模速度从20 min缩短至30 s内,极大提高了地质编录建模效率,进而降低了井下生产勘探和采掘作业工作的风险。

       

      Abstract: Aiming at the problems of traditional original geological logging modeling, such as map pollution, low vectorization efficiency and low model accuracy, this paper proposes a vectorization 3D modeling method of original geological logging based on pattern recognition. This method mainly includes reading and cutting the original geological logging drawings, and Rosenfeld algorithm is used to reduce noise and refine graphics, and adopt Douglas-Pucker algorithm to extract and dilute the geological sketch boundary, and three-dimensional geological logging boundary, and the Coons surface is used to accurately build the 3D geological body model. This method has been successfully applied to the 3D geological modeling of Gejiu Mining Area. The numerical simulation results show that compared with the traditional original geological logging 3D modeling, the modeling results using this method can more truly reflect the change of ore body shape, and the modeling speed is reduced from 20 min to 30 s, which greatly improves the efficiency of geological logging modeling, and further reduces the risk of underground production exploration and mining operations.

       

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