随着煤炭行业智能化建设进程的不断推进，煤矿井下钻探系统的数字化、智能化水平已成为提升煤矿安全生产与效率的关键。然而，即使现阶段已建成的智能矿山，依然存在井下钻探数据实时采集与传输能力不足、数据集成困难、数据利用率低等现象，亟待通过构建钻探监测通信系统予以解决。

本文针对煤矿智能钻探监测通信系统（包含硬件设备与软件系统），首先从设备可靠性与数据集成两个方面分析了系统构建前存在的问题。基于课题组研发的ZZJT127矿用钻孔参数监测与图像监视装置，分析硬件设备的技术基础并进行设备测试与测量数据的标定工作，完成对系统硬件部分的研究；其次，通过对矿井钻探数字化建设需求的深入分析，提出构建智能钻探监测通信系统的必要性和紧迫性。基于分层架构理论，从总体架构、网络架构及功能架构三个维度进行系统架构设计，完成系统功能的设计与实现，最终构建了软硬一体化的煤矿智能钻探监测通信系统；第三，为了解系统在工程应用中的可靠性和适用性，从硬件、软件和人为因素三个方面，建立系统运行可靠性评价指标体系，通过现场调研与问卷调查来筛选出合理指标，调研数据经过信度与效度检验，以确保评价指标的科学性与有效性。在权重计算方面，主观权重采用G1序关系分析法量化专家经验，客观权重则通过改进的CRITIC法计算，引入信息熵进行数据离散性与冲突性处理，对标准差采用变异系数进行替代来消除量纲的影响，然后利用基于博弈论的组合赋权法确定各指标的最终权重，使权重结果更接近客观，通过建立综合评价云模型来直观反映系统的最终评价结果；最后，结合Z煤矿工程应用案例，计算出各评价指标权重，并结合云图法和云相似度法，得出系统可靠性综合评价结果，再分别从硬件、软件和人为因素三个方面提出了系统的改进与优化措施，为系统的进一步完善指明了方向。

本文的研究通过对智能钻探监测通信系统的构建，有效解决了井下钻探过程中数据集成困难、处理效率低等问题，实现了对钻探过程的实时监测与数据管理，丰富了煤矿井下钻探的数字化管理手段。本文的研究还可为后续自动化钻机的升级改造工作提供一定的实践价值与理论指导意义。

With the continuous advancement of intelligent construction in the coal industry, the digitalization and intelligence level of underground drilling systems in coal mines have become key factors in enhancing the safety and efficiency of coal mine production. However, even in the intelligent mines that have been built at present, there are still problems such as insufficient real-time data collection and transmission capabilities in underground drilling, difficulties in data integration, and low data utilization rates. These issues urgently need to be addressed by constructing a drilling monitoring and communication system.

This paper focuses on the intelligent drilling monitoring and communication system in coal mines (including hardware equipment and software systems). Firstly, it analyzes the problems existing before the system construction from the aspects of equipment reliability and data integration. Based on the ZZJT127 mining hole parameter monitoring and image surveillance device developed by the research group, it analyzes the technical basis of the hardware equipment and conducts equipment testing and calibration of measurement data to complete the research on the hardware part of the system. Secondly, through in-depth analysis of the digital construction requirements of underground drilling in mines, it proposes the necessity and urgency of constructing an intelligent drilling monitoring and communication system. Based on the theory of layered architecture, it designs the system architecture from three dimensions: overall architecture, network architecture, and functional architecture, completes the design and implementation of system functions, and ultimately builds a soft and hard integrated intelligent drilling monitoring and communication system for coal mines. Thirdly, in order to understand the reliability and applicability of the system in engineering applications, it establishes a system operation reliability evaluation index system from three aspects: hardware, software, and human factors. Through on-site investigations and questionnaires, it screens out reasonable indicators. The survey data undergoes reliability and validity tests to ensure the scientificity and effectiveness of the evaluation indicators. In terms of weight calculation, the subjective weight is quantified by the G1 order relation analysis method to reflect expert experience, while the objective weight is calculated by the improved CRITIC method, introducing information entropy for data dispersion and conflict processing, and using the coefficient of variation to replace the standard deviation to eliminate the influence of dimensions. Then, the combination weighting method based on game theory is used to determine the final weight of each indicator, making the weight results closer to objectivity. A comprehensive evaluation cloud model is established to visually reflect the final evaluation results of the system. Finally, combined with the engineering application case of Z coal mine, the weights of each evaluation indicator are calculated, and the comprehensive reliability evaluation results of the system are obtained through the cloud diagram method and cloud similarity method. Improvement and optimization measures are proposed respectively from the aspects of hardware, software, and human factors to provide a direction for the further improvement of the system.

The research in this paper effectively solves the problems of difficult data integration and low processing efficiency in underground drilling through the construction of an intelligent drilling monitoring and communication system, realizes real-time monitoring and data management of the drilling process, and enriches the digital management means of underground drilling in coal mines. The research in this paper can also provide certain practical value and theoretical guidance significance for the subsequent upgrading and transformation of automated drilling machines.

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