智能矿井多元监控数据集成关键技术研究

Research on key technologies of multi-element monitoring data integration in intelligent mine

  • 摘要: 目前大部分煤矿监控系统采用私有数据采集协议,相互之间无法兼容。针对该问题,从数据采集、数据融合、数据存储3个方面入手,探讨了智能矿井多元监控数据集成关键技术。数据采集:为了加强系统的开放性、兼容性,可将私有协议封装为驱动动态链接库(DLL),通过加载适配OPC,MQTT等协议及挂接私有协议驱动的方式实现各业务系统的数据采集,并采用多线程技术满足多通道、多协议数据传输的高效性、实时性要求。数据融合:可将各系统之间共享频率高的数据进行统一规范,形成煤矿主数据,以保证各系统之间数据的一致性。数据存储:对实时性要求高的数据可选用时序数据库,对实时性要求不高的数据可选用关系型数据库,经对比分析,InfluxDB更适用于煤矿监控数据的实时存储,MySQL Community更适用于对实时性要求不高的数据存储;可运用Redis缓存技术实现数据高效缓存,以保证煤矿监控数据的完整性。

     

    Abstract: Currently, most coal mine monitoring systems adopt private data acquisition protocols, which are incompatible with each other. In order to solve this problem, the key technologies of multi-element monitoring data integration in intelligent mine are discussed from three aspects of data acquisition, data fusion and data storage. Data acquisition: In order to strengthen the openness and compatibility of the system, the private protocol can be encapsulated into a driver dynamic link library (DLL). The data acquisition of each business system can be realized by loading and adapting OPC, MQTT and other protocols and hooking the private protocol driver. The multithreading technology can be adopted to meet the requirements of high efficiency and real-time of multi-channel and multi-protocol data transmission. Data fusion: The data with the high frequency of sharing among various systems can be unified and standardized to form the master data of the coal mine. This will ensure the consistency of data among various systems. Data storage: For data with high real-time requirements, the time series database can be selected. For data with low real-time requirements, the relational database can be selected. Through comparative analysis, InfluxDB is more suitable for real-time storage of coal mine monitoring data, and MySQL Community is more suitable for data storage with low real-time requirements. Redis cache technology can be used to achieve efficient data cache so as to ensure the integrity of coal mine monitoring data.

     

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