Zhang Huanbao, Gao Tao, Wang Fulin, Lin Qibin, Zhang Shenchen, Zou Changhui, Yang Shijiao, He Haiyang
School of Resources Environment and Safety Engineering, University of South China, Hengyang, 421001, China.
Jiangxi Xiushui Xianglushan Tungsten Industry Co., Ltd, Jiujiang, 332000, China.
Sci Rep. 2025 Mar 28;15(1):10698. doi: 10.1038/s41598-025-94992-1.
In the field of mining engineering, ensuring the safe operation of mines is of utmost importance, and the stability of the backfill materials plays a pivotal role. This research comprehensively analyzes the strain field evolution and crack development in cemented paste backfill (CPB) specimens made from whole tailings under various backfill mix designs by using uniaxial compressive strength (UCS) testing, digital image correlation, and computer vision recognition (CVR) technology. The experimental outcomes reveal that the UCS of the CPB decreases with reductions in cement-to-tailings ratio, filling concentration, and curing age, while the rate of principal strain field evolution significantly accelerates. The developed computer vision recognition model (HSV-CVR), based on hue, saturation, and value color patterns, processes strain field data to quantify the proportions of various strain regions. By applying the first derivative of these proportions, the model enables early crack prediction. This approach overcomes the limitations and subjectivity of traditional artificial vision methods for crack identification, providing precise quantification of CPB strain evolution. The research enhances understanding of mining backfill materials behavior and provides a strong scientific basis for design, monitoring, and risk management, crucial for improving mining safety and efficiency.
在采矿工程领域，确保矿山的安全运营至关重要，而回填材料的稳定性起着关键作用。本研究通过单轴抗压强度（UCS）测试、数字图像相关以及计算机视觉识别（CVR）技术，全面分析了不同回填配合比下全尾砂制成的胶结充填料浆（CPB）试件中的应变场演变和裂纹发展情况。实验结果表明，CPB的UCS随着水泥与尾砂比、充填浓度和养护龄期的降低而减小，而主应变场的演变速率显著加快。基于色调、饱和度和明度颜色模式开发的计算机视觉识别模型（HSV-CVR）对应变场数据进行处理，以量化不同应变区域的比例。通过应用这些比例的一阶导数，该模型能够实现裂纹的早期预测。这种方法克服了传统人工视觉裂纹识别方法的局限性和主观性，实现了对CPB应变演变的精确量化。该研究加深了对采矿回填材料性能的理解，为设计、监测和风险管理提供了有力的科学依据，这对提高采矿安全性和效率至关重要。
