日前，河南晋控天庆煤化工有限责任公司加气站智慧管网建设项目竣工投用。

Recently, the intelligent pipeline network construction project of the gas filling station of Henan Jin Kong Tianqing Coal Chemical Co., Ltd. was completed and put into use.

此前，管网日常运行主要依赖人工巡检和经验判断，不仅劳动强度大，更存在诸多难以规避的风险隐患。为破解难题，公司在项目筹备阶段，成立专项工作小组，深入调研管网运行现状，广泛走访上下游用气单位，全面梳理生产运营中的痛点、难点问题。

Previously, the daily operation of the pipeline network mainly relied on manual inspections and experience-based judgments. This not only involved high labor intensity but also presented numerous risks and potential hazards that were difficult to avoid. To solve these problems, during the project preparation stage, the company established a special working group, conducted in-depth research on the current operation status of the pipeline network, extensively visited upstream and downstream gas-consuming units, and comprehensively sorted out the pain points and difficult issues in the production and operation process.

在硬件部署环节，公司秉持“精准覆盖、全面感知”的原则，在管网沿线关键节点、重点设备区域累计安装了十几套智能监测终端。这些终端集成了压力、温度、流量、泄漏检测等多维度传感器，能够对管网运行状态进行24小时不间断监测。与传统监测方式相比，智能监测终端的响应速度显著提升，其中泄漏检测精度达到PPM级，即便管网出现微小的泄漏异常，也能被精准捕捉并实时上传数据。

In the hardware deployment stage, the company adhered to the principle of "precise coverage and comprehensive perception", and installed more than ten sets of intelligent monitoring terminals along the pipeline network at key nodes and in key equipment areas. These terminals integrate multiple-dimensional sensors such as pressure, temperature, flow, and leakage detection, enabling 24-hour uninterrupted monitoring of the pipeline network's operating status. Compared with traditional monitoring methods, the response speed of the intelligent monitoring terminals has significantly improved. The leakage detection accuracy reaches the PPM level, and even minor leakage abnormalities in the pipeline network can be accurately detected and real-time data uploaded.

为打破数据壁垒，项目团队搭建专属的智慧管网云平台，实现加气站内部气量输送数据、设备运行状态信息、环境监测数据与上下游用户用气数据的实时汇聚、互联互通。该平台搭载的智能分析模型，能够对海量数据进行深度挖掘和实时分析，实现从“事后补救”向“事前预防”转变。

To break through the data barriers, the project team has built an exclusive smart pipeline network cloud platform, enabling the real-time aggregation and interconnection of gas volume transmission data within the gas filling station, equipment operation status information, environmental monitoring data, and gas usage data from upstream and downstream users. The intelligent analysis models installed on this platform can conduct in-depth data mining and real-time analysis of massive data, achieving a transformation from "post-event remediation" to "pre-event prevention".

在运维管控层面，中控操作人员无需抵达现场，即可全面掌握管网运行动态，并根据用气需求变化一键下达调度指令，实现气量的精准调配。针对设备维护工作，系统能够根据设备运行年限、累计运行时长、实时工况等数据，实现预防性维护，开展针对性检修，有效降低设备故障率。

At the operation and control level, the central control operators do not need to go to the site. They can comprehensively grasp the operation status of the pipeline network and issue dispatching instructions with a single click based on changes in gas usage demands, achieving precise allocation of gas volume. Regarding equipment maintenance work, the system can implement preventive maintenance based on data such as the operating years, cumulative operating hours, and real-time conditions of the equipment, and carry out targeted repairs, effectively reducing the failure rate of the equipment.