油库多源设备数据采集和处理系统设计研究

Research on Design of Oil Depot Multi-Source Equipment Data Acquisition and Processing System

为解决大规模成品油库异构设备的数据采集和实时处理问题,创新性地设计了一种针对成品油库的通用化、高可用性的工业实时数据采集和处理系统,以定义异构数据采集的四层架构,并规范油库设备设计的四层级编码和数据格式化处理规则。按照开放平台通信统一架构(OPC UA)标准协议,对油库多源异构设备进行数据采集和协议转换。利用消息队列遥测传输(MQTT)协议与云平台进行数据转发和传输,同步提出采集的高可用性策略,实现多源异构设备设施与平台端大规模数据的实时采集和交互。云平台端利用Kafka、Storm、MySQL和Redis实现大规模实时数据的高速处理。该系统在多座大型成品油库试点应用,实现对油库安全生产的实时数据采集、处理和预警推送,采集监控点超过5000个,测试数据采集和处理最大时延低于1.5 s。应用结果证实了该系统的有效性。

To solve the problem of data acquisition and real-time processing of heterogeneous devices in large-scale refined oil depots,a generalized,high-availability industrial real-time data acquisition and processing system for refined oil depots is innovatively designed to define the four-layer architecture of heterogeneous data acquisition and standardize the four-layer level of coding and data formatting and processing rules for the design of oil depot devices.Data acquisition and protocol conversion of oil depot multi-source heterogeneous equipment is performed in accordance with the standard protocol of open platform communication unified architecture(OPC UA).Data forwarding and transmission with the cloud platform is performed using message queuing telemetry transport(MQTT)protocol,and the high availability strategy for acquisition is proposed synchronously to realize real-time acquisition and interaction of large-scale data between the multi-source heterogeneous equipment and facilities and the platform side.At the cloud platform end,Kafka,Storm,MySQL and Redis are used to realize high-speed processing of large-scale real-time data.The system is piloted in several large-scale refined oil depots to realize real-time data collection,processing,and early warning push for oil depot safety production,with more than 5000 collection and monitoring points,and the maximum latency of test data collection and processing is less than 1.5 s.The application results confirm the effectiveness of the system.