沙梁煤矿井筒支护质量智能监测试验研究

Intelligent monitoring test of shaft support quality in Shaliang Coal Mine

  • 摘要:
    目的 针对煤矿深部开采中井筒支护监测实时性不足、数据精度低、预测难度大等难题,提出基于光纤光栅传感的井筒支护质量智能监测技术体系,并开展了一系列技术试验。
    方法 通过钻孔窥视法获取围岩松动圈特性,构建分布式光纤传感网络实现应变、温度、位移多参量同步监测,开发数据集成统一的井筒支护质量光纤智能监测平台,确定符合功能要求的硬件设备关键技术参数,能够实现井筒支护质量的实时监测,推进了煤矿井筒支护质量智能监测技术的落地应用。
    结果及结论 研究结果表明,系统可实时监测井筒变形量,实现了井筒多参量融合监测,为支护方案的动态优化提供了指导,为煤矿智能化建设提供了技术支撑。

     

    Abstract: Aiming at the problems such as insufficient real-time performance, low data accuracy and high prediction difficulty of wellbore support monitoring in deep coal mining, an intelligent monitoring technology system for wellbore support quality based on fiber Bragg grating sensing was proposed, and a series of technical experiments were carried out. The characteristics of the loose ring of the surrounding rock were obtained through the borehole peeking method. A distributed optical fiber sensing network was constructed to achieve synchronous monitoring of multiple parameters such as strain, temperature and displacement. A data integrated and unified optical fiber intelligent monitoring platform for wellbore support quality was developed. The key technical parameters of the hardware equipment that meet the functional requirements were determined, enabling real-time monitoring of wellbore support quality. It has promoted the practical application of intelligent monitoring technology for the support quality of coal mine shafts. The research results show that the system can monitor the deformation of the wellbore in real time, achieve multi-parameter fusion monitoring of the wellbore, and provide guidance for the dynamic optimization of the support scheme.

     

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