摘要
对平煤四矿煤巷智能掘进关键技术进行了研究,从裂隙智能识别算法、多切片结构面图像三维重构、图像分割技术的裂隙检测、巷道可掘性判定等方面进行了论述,提出了基于光学影像传感器的数据采集、二维伽马函数自适应校正、Hough变换边缘拟合等方法,建立了巷道掘进多切片结构面模型,并进行了工程实践应用。结果表明,该技术实现了裂隙智能识别与三维重构,准确判定了巷道可掘性与空顶自稳时间,达到了提高施工效率、降低安全风险、减少人力成本的效果,解决了煤巷掘进中围岩稳定性评估及安全支护难题。
A study was conducted on the key technologies for intelligent driving in coal roadways at Pingmei No.4 Mine.The research covered intelligent recognition algorithms for fractures,three-dimensional reconstruction of multi-chamber structural surfaces,fracture detection using image segmentation techniques,and the determination of roadway excavability.The methods were proposed such as data acquisition based on optical imaging sensors,adaptive correction of two-dimensional gamma functions,and edge fitting using Hough transform.A multi slice structural surface model for roadway driving was established and the engineering practice application was carried out.The results showed that this technology achieved intelligent recognition and three-dimensional reconstruction of fractures,accurately determined the excavability of the roadway and the time required for roof self-stabilization.It improved construction efficiency,reduced safety risks,and lowered labor costs,effectively addressing the challenges of surrounding rock stability assessment and safe support in coal roadway driving.
作者
庞锦彪
Pang Jinbiao(China Pingmei Shenma Group No.4 Mine,Pingdingshan 467000,China)
出处
《能源与环保》
2025年第8期268-274,共7页
CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基金
国家重点研发计划资助项目(2017YFC0804209)。
关键词
智能掘进
裂隙识别
块体识别
工程实践
intelligent driving
fracture identification
block identification
engineering practice
