Mechanical performance analysis of two-prop shield caving hydraulic support
-
摘要: 浅埋深煤层基岩比较薄、松散层较厚，工作面易出现台阶下沉等状况，矿压展现剧烈，应用于浅埋深煤层工作面的两柱掩护式放顶煤液压支架易出现工作阻力不足，对顶板的支护效果不好，从而造成生产安全问题。针对以上问题，采用空间力学分析及结构有限元分析，对适用于浅埋深煤层的ZFY12000/25/42D型两柱掩护式放顶煤液压支架在顶梁受偏心载荷且底座两端受载、顶梁受扭转载荷且底座两端受载、顶梁受偏心载荷且底座受扭转载荷3种最危险工况下的受力状态进行了分析。分析结果表明：在不同工况下，支架各结构件的应力大小均会有所不同，分布状况也不尽相同，从支架整体应力分布来看，受顶板、立柱和底板的相互作用，顶梁和底座将承受较大的应力，而前后连杆、掩护梁作为连接过渡部件，所承受的应力明显较小；顶梁受扭转载荷且底座两端受载工况下支架承受应力最大，为712.69 MPa；支架位移变形趋势基本相同，均是从顶梁到底座变形量逐渐减小，整体变形状况良好。在保证结构可靠性的前提下，在应力集中部位选用高强度板材或者提高材料厚度，可改善支架应力分布状况，增强支架控顶能力，从而确保支架工作的可靠性和稳定性。Abstract: The bed rock of shallow-buried depth coal seam is relatively thinner and the loose layer is thicker, the working face is easy to appear step subsidence and other conditions, and mine rock pressure is severe. The two-prop shield caving hydraulic support used in the working face of shallow buried depth coal seam is prone to insufficient working resistance, poor support for the roof, so as to cause production safety problems. In view of the above problems, using space mechanics analysis and structural finite element analysis, stress state of ZFY12000/25/42D two-prop shield caving hydraulic support suitable for shallow-buried depth coal seams was analyzed under the three most dangerous working conditions of the top beam subjected to eccentric load and loaded on both ends of the base, the top beam subjected to torsional load and loaded on both ends of the base and the top beam subjected to eccentric load and the base subjected to torsional load. The analysis results show that under different working conditions, the stress of each structural member of the hydraulic support will be different, and the stress distribution will be different. From the overall stress distribution of the hydraulic support, the top beam and the base will be subjected to large stresses for interact of the top beam, the prop and the bottom plate, and the front and rear connecting rods and the shield beam as the connecting transition parts will be subjected to less stress; the largest stress of the support is at 712.69 MPa under the working condition of the top beam subjected to torsional load and loaded on both ends of the base; the displacement deformation trend of the support is basically the same, from the top beam to the base, the deformation is gradually reduced, but the overall deformation is good. Under the premise of ensuring structural reliability, high-strength plates are used in the stress concentration part or the thickness of the material is increased to improve the stress distribution of the support and enhance roof-controlling ability of the support, so as to ensure the reliability and stability of the support working.
-
-
期刊类型引用(18)
1. 李富强. 基于深度卷积神经网络与多源信号的煤岩识别研究. 煤炭技术. 2025(03): 233-238 . 
百度学术
2. 高如新，杜亚博，常嘉浩. 基于改进YOLOX-S的轻量化煤矸石检测方法研究. 河南理工大学学报(自然科学版). 2024(04): 133-140 . 百度学术
3. 陈晓杰，王亮，赵美玲，刘光伟，涂俊雄. 基于ECA-YOLOv5s的煤矿带式输送机异物检测网络模型. 采矿技术. 2024(04): 316-324 . 百度学术
4. 陈世涛，张敏，栗超. 基于YOLOv5的带式输送机煤堆异物检测. 洁净煤技术. 2024(S2): 12-18 . 百度学术
5. 涂灿. VCS智能干选机的试验研究. 煤炭加工与综合利用. 2023(06): 37-41 . 百度学术
6. 高如新，常嘉浩，杜亚博，刘群坡. 基于改进YOLOv5s的煤矸石目标检测算法. 电子测量技术. 2023(13): 95-101 . 百度学术
7. 汪岩，李自强. 基于AI图像处理的煤矸石特征提取及分类方法. 煤炭技术. 2023(11): 231-233 . 百度学术
8. 曹现刚，刘思颖，王鹏，许罡，吴旭东. 面向煤矸分拣机器人的煤矸识别定位系统研究. 煤炭科学技术. 2022(01): 237-246 . 百度学术
9. 倪云峰，封子杰，郭苹，王静. 基于卷积神经网络的煤矸石识别算法研究. 现代电子技术. 2022(10): 57-62 . 百度学术
10. 张红，李晨阳. 基于光学图像的煤矸石识别方法综述. 煤炭工程. 2022(07): 159-163 . 百度学术
11. 申利飞，田子建，白林绪. 改进纹理模糊筛选下煤矸石X射线图像处理. 激光与红外. 2022(07): 1090-1097 . 百度学术
12. 陈彪，卢兆林，代伟，邵明，于大伟，董良. 基于轻量化HPG-YOLOX-S模型的煤矸石图像精准识别. 工矿自动化. 2022(11): 33-38 . 本站查看
13. 郑新涛，苏道玉. 基于小波矩的智能手绘草图识别系统设计. 现代电子技术. 2021(12): 177-181 . 百度学术
14. 胡璟皓，高妍，张红娟，靳宝全. 基于深度学习的带式输送机非煤异物识别方法. 工矿自动化. 2021(06): 57-62+90 . 本站查看
15. 王冠军，苏婷婷，刘文博，钱智平，李佳泽. 基于EAIDK的智能煤矸分拣系统设计. 工矿自动化. 2020(01): 105-108 . 本站查看
16. 柴炳升，胡峰. 石槽村选煤厂重介质浅槽分选工艺探究. 煤炭加工与综合利用. 2020(08): 33-34+38 . 百度学术
17. 章振原，秦训鹏，李轶峰. 基于机器视觉的废旧有色金属碎料识别方法. 激光与光电子学进展. 2020(16): 194-201 . 百度学术
18. 潘卫东，李新源，员明涛，袁永康，杨克虎. 基于顶煤运移跟踪仪的自动化放煤技术原理及应用. 煤炭学报. 2020(S1): 23-30 . 百度学术
其他类型引用(31)
计量
- 文章访问数: 102
- HTML全文浏览量: 14
- PDF下载量: 14
- 被引次数: 49
下载:
