Application of big data monitoring system in intelligentization of factory
HAN Chengyu1, LU Zheng1, XU Mingyang2, MA Fangyuan1, WANG Jingde1, SUN Wei1
1. College of Chemical Engineering, Beijing university of chemical technology, Beijing 100029, China;
2. Sinochem Quanzhou Petrochemical Co., Ltd, Fujian Quanzhou 362103, China
摘要 针对化工企业现有信息化系统存在的一些普遍性问题，基于现有的信息化架构设计开发了大数据监测系统。大数据监测系统对原有相对孤立的多个信息系统进行了整合，并引入先进的大数据分析算法及策略为生产操作提供指导，将成为工厂智能化的重要组成部分。系统中的智能数据网关，可统一访问DCS （Distributed Control System）实时数据、历史数据、实验室检测数据等各种数据源；数据调度中心规范了子系统间交互的方式，增强了业务拓展及数据应用的灵活性；知识融合库结合了数据驱动技术，能够不断积累工程师的操作经验；系统还提供了开放的二次开发接口，支持算法模块的客户化开发。上述系统已在某石化企业上线投产，运行稳定，持续为现场工程师提供及时、准确的操作指导，得到了用户的充分认可。
Abstract：
In view of some common problems existing in the existing information systems of chemical enterprises, a big data monitoring system was designed and developed on the basis of the existing information architecture. The big data monitoring system integrates many relatively isolated information systems, introduces advanced big data analysis algorithms and strategies, provides guidance for production and operations, and will become an important part of intelligentization of the factory. The intelligent data gateway in the system can access DCS (Distributed Control System) real-time data, historical data, laboratory test data and other data sources in a unified way; The data dispatching center standardizes the interaction between subsystems, and enhances the flexibility of business expansion and data application. Knowledge fusion library combines data-driven technology, and can accumulate the operation experience of engineers. The system also provides an open secondary development interface, which supports the customized development of algorithm modules. The above-mentioned system has been put into production in a petrochemical enterprise, running stably, providing timely and accurate operation guidance for field engineers, and being fully recognized by users.
HAN Chengyu, LU Zheng, XU Mingyang, MA Fangyuan, WANG Jingde, SUN Wei.Application of big data monitoring system in intelligentization of factory[J]. Chemcial Industry and Engineering, 2022,39(2): 37-40,49
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2022, Vol. 39 
