【作者】 邰伟鹏；

【导师】 岳建华；

【作者基本信息】 中国矿业大学 ， 地球探测与信息技术， 2021， 博士

【摘要】 煤矿突水、冲击地压及煤与瓦斯突出等动力灾害具有偶发性高、危险性大等特点,井下电法勘探可对其进行有效的预测预报。直流电法和瞬变电磁法是矿井探测的主力方法,而针对张量电阻率的研究则为井下实时监测方法提供了理论依据。一方面,探测数据采集、处理过程和解释结果要求高度的可靠性,而我国从事矿井电法勘探的专业人员数量不足、水平参差不齐;另一方面,张量电阻率实时监测方法急需开发专用仪器设备、数据采集传输控制系统。随着我国煤矿开采深度的增加,兼之新冠疫情的叠加影响,对开发煤矿井下电法探测协同处理与解释系统提出了更为迫切的需求。本文对井下电法勘探的资料数据采集和处理云技术进行了系统性研究,在感知矿山物联网理论的指导下,提出了基于云技术的井下电法探测数据采集、处理与资料解释的整体解决方案。利用云端分布式软件开发技术,实现了基于Web的矿井电法勘探工程项目全流程管理,基于云计算的井下电法探测数据处理算法和云端数据可视化方法,设计了张量电阻率实时监测的数据采集、传输远程控制系统。本文的主要贡献为:(1)基于工程管理ERP(Enterprise Resource Planning)概念和互联网架构演进理论,整合人力物力资源、基础数据资源,优化业务流程,提出了井下电法勘探线上协同工作方法,实现了协同工作Web系统,建立了地质资料汇编库,线上工作流程贯穿地质任务发布、物探方案设计与审核、数据采集与质量控制、数据处理、报告编制与审核、交付验收的全过程。系统对接微信消息推送服务,实现工作任务流转的实时提醒。(2)张量电阻率实时监测方法急需开发专用仪器设备和软件系统,提出了张量电阻率数据采集站的智能远程控制方法,实现了其子站设备工作状态的自主巡检,开发了主站设备与工控机的控制、数据采集程序,并定义了数据传输协议和云存储结构。最终实现了矿井地质条件的实时监测。(3)基于云计算理论,提出了基于云端分布式架构的井下电法探测数据处理及可视化方法。研究分析了多种瞬变电磁仪器的多源异构数据时空属性,给出了其统一的结构,并实现了云存储;实现了基于云计算的瞬变电磁法探测数据的单测点滤波和截取算法、多测道曲线生成算法、视电阻率算法;建立了云端地学等值面生成方法,视电阻率数据通过RESTful接口发送至Web前端页面程序,再通过互联网传输到用户浏览器上利用Web GL技术进行插值计算后实现等值面可视化。基于云技术的井下电法资料数据采集、处理及解释系统采用分布式架构,支持Java、Python、.Net Core C#语言程序,通过网关与用户终端的浏览器交互数据,以Nginx实现负载均衡。张量电法仪采集传输和远程控制程序采用C语言实现,通过TCP/IP协议向工控机传输实时监测数据并同步到云服务器上。工控机调试和监控软件的Windows Form窗体应用程序采用C#语言编程实现。更多还原

【Abstract】 A coal mine dynamic disaster such as a water inrush,rock burst,coal or gas explosion has both high frequency and high-risk characteristics.Underground electrical and electromagnetic methods detection can be used to predict and forecast these events.For this job,two methods are typically used: Direct Current Method(DCM)and Transient Electromagnetic Method(TEM).The research on the tensor resistivity provides the theoretical basis for the mine fixed-point real-time monitoring method.On the one hand,the detection data collection,processing,and interpretation results require high reliability.There are,however,insufficient professionals,and their skills levels differ greatly.On the other hand,the real-time monitoring method of tensor resistivity lacks special equipment and data collection transmission control systems.With the increasing coal mining depth in China,the goal-setting of carbon neutrality and the peak of carbon dioxide emissions,and the impact of COVID-19,it is urgent to develop a cooperative processing and interpretation system of underground electrical and electromagnetic methods in coal mines.In this paper,we present a systematic analysis of the data collection and processing of underground electromagnetic and electrical methods.Guided by sensory mine internet of things theory.An overall solution based on cloud technology is presented for the acquisition,processing,and interpretation of underground electrical data.We design a remote-control system for real-time monitoring’s data collection and transmission of the tensor resistance using the cloud distributed system,which implements the online workflow of the mine’s electrical advanced detection,multiple data processing algorithms,and data visualization methods.The main contributions of this paper are as follows:(1)The co-operative work mode of underground electrical lead survey method is introduced according to the evolution theory of the internet software architecture and Enterprise Resource Planning(ERP)concept of project management after deeply investigating the personnel organizational form,the task division,and the workflow.Human resources,material resources,and basic data resources can be integrated.The work flow can be optimized.It runs the entire process of detection task release,design,and audit of the geophysical prospecting project,data collection,and quality control,data processing,report preparation,and audit,delivery,and acceptance.A geologic information database is set up.Using the We Chat push notification service,the system realizes the function of data changes notifications within the workflow.(2)The underground tensor resistivity monitoring system is urgent to develop special instrument and software.The intelligent remote-control method of the tensor resistivity data acquisition equipment is presented.The independent inspection of the working status of the tensor electrical instrument sub-station equipment is implemented.The control and data acquisition program of the master station equipment and the Industrial PC are developed.The data transmission protocol and cloud storage structure are defined.The intelligent remote-control system of the tensor resistivity method instrument is completed and the real-time monitoring method of the underground coal mine is implemented.(3)Based on cloud computing theory,a method for underground electrical data processing and visualization using a cloud-based distributed architecture is presented.Statistical properties of heterogeneous data from different transient electromagnetic instruments are analyzed,and their normalized structures are presented.On cloud systems,we implement algorithms for single-point filtering and interception,multichannel curve generation,and apparent resistivity calculation.We also develop an isosurface generation method for cloud systems.A distributed application program is used to process the data,then the data is transmitted to the web front end program,then the web URL code with the data is transmitted to the client Web browser through the Internet,where the apparent resistivity isosurface can be displayed using Web GL.Cloud-based underground electrical data collection,processing,and interpretation are supported using Java,Python,and Net Core C#.Through the gateway,data can be exchanged,and Nginx implements load balancing.Tensor’s acquisition,transmission,and control programs are written in C.Real-time monitoring data are transmitted using the TCP/IP protocol to the Industrial PC and then synchronized with the cloud servers.Windows Form,the application for debugging and monitoring software on industrial PCs,is written in C#.更多还原