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作 者:杨敬伟 陈亚峰 辛向军 YANG Jingwei;CHEN Yafeng;XIN Xiangjun(Department of Computer,Henan Vocational College of Light Industry,Zhengzhou 450000,China;School of Software,Zhengzhou University of Light Industry,Zhengzhou 450002,China)
机构地区:[1]河南轻工职业学院计算机系,河南郑州450000 [2]郑州轻工业大学软件学院,河南郑州450002
出 处:《金属矿山》2025年第2期161-166,共6页Metal Mine
基 金:河南省高校重点科研项目(编号:22A413010);2024年度河南省高等教育教学改革研究与实践项目(编号:2024SJGLX0799)。
摘 要:为实现矿井高效率巡检,确保井下安全生产,融合5G通信技术研发了矿井智能巡检机器人系统。通过分析矿井智能巡检机器人的工作原理和应用场景,构建了基于5G通信技术的多模块协同系统框架,包含环境感知层、网络传输层、边缘计算层和决策应用层4层架构,并对通信技术进行了优化,包括通信时延优化、可靠性保障机制设计、带宽资源优化及抗干扰设计等,确保系统在矿井复杂环境中稳定运行和高效巡检。为验证系统性能,设计了包含仿真测试、井下试验和对比试验的综合验证方案,采用端到端时延、数据传输速率、图像识别准确率、路径规划精度等指标进行了评价。试验结果表明:该系统在5G信道质量动态优化方面,相比TCP协议,信号强度提升了4 dB、信噪比提升了10 dB、数据传输率提升了66.7%、机器人移动速度提升了87.5%,有助于实现矿井安全状态的实时监测、智能分析和多级预警等功能。To achieve high-efficiency inspection in mines and ensure safe underground production,an intelligent mine inspection robot system integrating 5G communication technology has been developed.By analyzing the working principle and application scenarios of the intelligent mine inspection robot,a multi-module collaborative system framework based on 5G was constructed,which consists of four layers:the environmental perception layer,network transmission layer,edge computing layer,and decision-making application layer.Additionally,optimizations were made to the communication technology,including communication latency optimization,reliability assurance mechanism design,bandwidth resource optimization,and anti-interference design,to ensure the stable operation and efficient inspection of the system in the complex mining environment.To verify the system's performance,a comprehensive validation plan was designed,including simulation tests,underground field trials,and comparative experiments.Evaluation metrics such as end-to-end latency,data transmission rate,image recognition accuracy,and path planning accuracy were used.The experimental results show that:in terms of dynamic optimization of 5G channel quality,compared to the TCP protocol,the signal strength improved by 4 dB,the signal-to-noise ratio increased by 10 dB,the data transmission rate increased by 66.7%,and the robot's movement speed increased by 87.5%.These improvements contribute to the real-time monitoring,intelligent analysis and multi-level early warning functions of the mine's internal safety status.
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