近年来为了对煤矿各个系统进行有效的监控，煤矿行业开发了很多自动化监控系统。许多第三方厂家开发的定制化监控系统，由于技术路线不统一，产生了大量异构数据，煤矿企业需要为各定制化系统均开发一套监控软件对数据进行二次集成，但是经转换后的数据存在滞后、运维困难、系统崩溃等问题。为解决二次开发、数据异构和数据共享程度低等问题，本文在中煤科工集团常州研究院项目《智能矿山基础信息平台的研发》中，主要研究数据感知与采集问题，开发了智能矿井多元监控数据集成系统。

针对煤矿专业化系统由不同厂家开发，煤矿企业二次开发的多种上位机数据转换程序，存在转换时间滞后、数据存储格式与原系统数据不一致等问题，本文提出用一套软件平台实现对全矿井各类感知数据的集成。将不同系统设备的协议封装为数据驱动，采用多协议驱动动态加载的方式实现对全矿数据的采集，处理后的数据格式统一。在.NET平台上采用C#语言开发了文本协议驱动、OPC（OLE for Process Control）驱动和Modbus驱动，解析后数据均是统一的格式。其它第三方系统只需将数据协议封装为驱动插件(DLL，Dynamic Link Library)，输出统一的格式，即可以以驱动的方式接入到上位机软件平台，实现用一套平台对全矿各种协议数据的采集。

针对不同系统相同的业务数据，描述规范不同，造成数据束缚在子系统中、共享困难、效率低下等问题，本文提出通过梳理筛选企业各个系统频繁共享的数据，通过构建煤矿SSN（Semantic Sensor Network Ontology）模型，映射生成RDF（Resource Description Framework）模型后添加语义描述，从而形成元数据规范，实现数据在系统间自由地共享。

针对煤矿生产过程中产生的庞大的时序数据，对数据库的存储性能要求极高，本文提出采用开源的数据库，将实时数据存储到时序数据库Influx DB中，对查询性能要求高的数据，保存到关系数据库MySQL中。

最后对本文设计的智能矿井多元监控数据集成系统进行测试和验证，证明其符合设计需求。

In recent years, many automatic monitoring systems have been developed in coal mine industry in order to monitor each system effectively. The customized monitoring system developed by many third-party manufacturers has produced a large amount of heterogeneous data due to the inconsistent technical route. Coal mine enterprises need to develop a set of monitoring software for each customized system for data secondary integration, but the data after conversion has problems such as lag, operation and maintenance difficulties, system breakdown and so on. In order to solve the problems of secondary development, data heterogeneity and low degree of data sharing, this thesis mainly studies the problem of data perception and collection in the project "Research and Development of Intelligent mine Basic Information Platform" of China Coal Technology and Engineering Group Changzhou Automa- tion Research Institute, and develops an integrated system of intelligent mine multiple monitor-

ing data.

In view of the problems such as conversion time lag and data storage format inconsistency with the data of the original system in various kinds of upper computer data conversion programs developed by different manufacturers and secondary development by coal mine enterprises, this paper proposes to use a set of software platform to realize the integration of all kinds of perception data in the whole mine. The protocol of different system equipment is encapsulated as data driven, and the multi-protocol driven dynamic loading method is adopted to realize the collection of the whole mine data, and the data format after processing is unified. The text protocol driver, OPC(OLE for Process Control) driver and Modbus driver are developed using C# language on.NET platform, and the parsed data are all in the same format. Other third-party systems only need to package the data protocol as a Dynamic link library(DLL) and output a unified format, that is, it can be connected to the upper computer software platform in the way of driving, to realize the collection of all kinds of protocol data of the mine with a set of platforms.

In view of the same business data of different systems, the description specifications are different, resulting in data bound in subsystems, sharing difficulties, low efficiency and other problems. This paper proposes to sort out and screen the data frequently shared by various systems of the enterprise, build the coal mine SSN(Semantic Sensor Network Ontology) model, map to generate RDF(Resource Description Framework)model, and then add semantic descript-ion, so as to form the metadata specification. Realize data sharing freely and efficiently among all systems.

In view of the huge amount of time-series data generated during coal mining production, the storage performance of the database is extremely high. This paper proposes to use open-source databases, storing real-time data in the time-series database Influx DB, and storing data with high query performance requirements in the relational database MySQL.

Finally, the intelligent mine multi-monitoring data integration system designed in this paper is tested and verified to prove that it meets the design requirements.

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