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煤岩体裂隙结构形态和力学属性的可视化数据库构筑初探

王宏伟, 张翠敏, 宋嘉祺, 王泽亮, 潘艳

王宏伟,张翠敏,宋嘉祺,等. 煤岩体裂隙结构形态和力学属性的可视化数据库构筑初探[J]. 煤炭科学技术,2023,51(S1):27−39

. DOI: 10.13199/j.cnki.cst.2022-1328
引用本文:

王宏伟,张翠敏,宋嘉祺,等. 煤岩体裂隙结构形态和力学属性的可视化数据库构筑初探[J]. 煤炭科学技术,2023,51(S1):27−39

. DOI: 10.13199/j.cnki.cst.2022-1328

WANG Hongwei,ZHANG Cuimin,SONG Jiaqi,et al. Preliminary study on construction of visual database for structural morphology and mechanical properties of coal and rock cracks[J]. Coal Science and Technology,2023,51(S1):27−39

. DOI: 10.13199/j.cnki.cst.2022-1328
Citation:

WANG Hongwei,ZHANG Cuimin,SONG Jiaqi,et al. Preliminary study on construction of visual database for structural morphology and mechanical properties of coal and rock cracks[J]. Coal Science and Technology,2023,51(S1):27−39

. DOI: 10.13199/j.cnki.cst.2022-1328

煤岩体裂隙结构形态和力学属性的可视化数据库构筑初探

基金项目: 

煤炭安全精准开采国家地方联合工程研究中心(安徽理工大学)开放基金资助项目(EC2022001);北京市自然科学基金资助项目(8202041);国家自然科学基金资助项目(41872205)

详细信息
    作者简介:

    王宏伟: (1981—),男,山西朔州人,教授,博士生导师。E-mail:whw@cumtb.edu.cn

  • 中图分类号: TD67

Preliminary study on construction of visual database for structural morphology and mechanical properties of coal and rock cracks

Funds: 

Open Fund Project of National and Local Joint Engineering Research Center for Safe and Accurate Coal Mining (Anhui University of Science and Technology) (EC2022001); Beijing Natural Science Foundation Project (8202041); National Natural Science Foundation of China (41872205)

  • 摘要:

    煤岩体中裂隙赋存状态、结构形态和力学属性等对其材料强度、变形能力和抗冲击性能等具有显著的影响,确定裂隙的空间几何结构、空间展布形态和力学属性对于研究煤岩力学性能具有重要的理论意义和工程应用价值,构筑煤岩体裂隙结构形态和力学属性可视化数据库可为研究裂隙形态多样性识别提供一个新的思路和方向。从数据库概念和建立数据库基本方法出发,设计了裂隙可视化数据库构筑的基本思路,建立了煤岩实体和裂隙实体间一对多的映射关系,构建了裂隙多源数据智能获取、裂隙属性智能分类与存储、形态可视化分析与实现3个方面的数据库基本框架,实现了可视化数据库的裂隙结构形态智能识别、基于结构形态和断裂力学的分类属性多角度判别、几何展布形态可视化、基于条形码与二维码扫描的裂隙属性智能传输等特色功能。以北京昊华能源股份有限公司大安山煤矿为工程背景,获取了逆冲断层和倒转褶皱等复杂地质构造中的煤岩样品。运用CT扫描、图像分析处理与三维重构等技术手段构建了若干裂隙的三维数字化模型。结合不同属性分类标准,基于智能识别算法分类了裂隙的形态特征、分布位置和几何特征等数据,初步建立了煤岩体裂隙可视化数据库的基本模块,开展了裂隙检索与数据入库,展示了裂隙结构的结合形态,为可视化数据库的建立打下基础。

    Abstract:

    The occurrence status, structural morphology and mechanical properties of cracks in coal and rock have a significant impact on its material strength, deformability and impact resistance. Determining the spatial geometry, spreading form and mechanical properties of cracks are of great important both in theory and engineering application for studying the mechanical properties of coal and rock, and the construction of visual database of cracks morphology and mechanical properties of coal and rock mass can provide new idea and research direction for study the identification of crack morphology diversity. Starting from the concept of database and the basic method of establishing a database, the basic idea of the construction of visual database of cracks is designed, a one-to-many mapping relationship between coal-rock mass and crack entities is established, and the basic database framework including the intelligent acquisition of crack multi-source data, intelligent classification and storage of crack properties and visual analysis and implementation of morphological structure is constructed. The features such as intelligent identification of cracks morphology in visual database, multi-angle discrimination based on classification properties of structural morphology and crack mechanics, visualization of the distribution form of geometric structures and intelligent transmission of crack properties based on bar code and QR-code is realized. The project background is Da’anshan coal mine of Beijing Haohua Energy Resource Co., Ltd. Coal rock samples in complex geological formations such as thrust faults and reversed folds were obtained. The 3D digital model of several cracks was extracted by CT scanning, image analysis processing and 3D reconstruction. Combined with different attribute classification standards, the morphological characteristics, distribution location and geometric characteristics of cracks are calculated and classified based on the intelligent recognition algorithm. In addition, the basic module of visualized database of coal and rock crack is established, the crack retrieval and data entry are carried out, and the binding morphology of the crack structure is demonstrated, laying a foundation for the establishment of visual database.

  • 图  1   煤岩样品与裂隙实体关系映射图

    Figure  1.   Mapping diagram of relationship between coal and rock mass and cracks entities

    图  2   裂隙结构形态和力学属性可视化数据库的构筑流程

    Figure  2.   Logical graph of visual database construction of cracks structure morphology

    图  3   数据库智能识别流程

    Figure  3.   Logic graph of intelligent database identification

    图  4   裂隙智能分类算法流程

    Figure  4.   Logical graph of the intelligent classification algorithm of cracks

    图  5   裂隙属性及分类标准

    Figure  5.   Diagram of properties and classification criteria for cracks

    图  6   裂隙几何结构形态可视化

    Figure  6.   Visualization of cracks geometric structure and distribution

    图  7   裂隙条形码和二维码生成流程

    Figure  7.   Logical graph for the generation of crack barcodes and QR codes

    图  8   大安山井田构造示意

    Figure  8.   Geological structure outline map of Da'anshan Coal Mine

    图  9   数据库登录界面

    Figure  9.   Index interface of the database login

    图  10   数据库内部模块示意

    Figure  10.   Schematic diagram of database internal module

    表  1   不同裂隙的参数及分类

    Table  1   Parameters and classification of different cracks

    裂隙编号体积/mm3角度/(°)按平整度分单/多裂隙埋深/m
    构造倾角/(°)
    构造类型裂隙二维码
    DA-M13-001196.700平面型单裂隙400
    10~90
    倒转背斜
    DT-M20-00181.6260曲面型单裂隙800
    70~90
    向斜
    DT-M37-001118.2968平面型单裂隙800
    70~90
    向斜
    CJ-M01-001162.430曲面型单裂隙680
    8~15
    背斜
    CJ-M01-00240.0528平面型单裂隙680
    8~15
    背斜
    CJ-M01-00347.6550平面型单裂隙680
    8~15
    背斜
    DA-M01-004506.63平面型多裂隙400
    50~90
    倒转向斜
    CJ-M02-0011704.93曲面型多裂隙680
    8~15
    背斜
    CJ-M03-001687.79曲面型多裂隙680
    8~15
    背斜
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-08-16
  • 网络出版日期:  2023-05-17
  • 刊出日期:  2023-05-31

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