节点文献
水泥厂质量监控管理及决策支持系统的研究与设计
Research and Design of Cement Quality Control and Decision Support System
【作者】 吴庆星;
【导师】 叶思敏;
【作者基本信息】 四川大学 , 控制理论与控制工程, 2003, 硕士
【摘要】 面对日趋激烈的市场竞争,如何应用高新技术改造传统产业,既是企业十分关注而迫切需要得到解决的问题,又是控制技术应用中一个重大的研发领域。随着现代工业的飞速发展,工业生产过程的控制规模不断扩大,复杂程度不断增加。工业生产过程控制模式已由原来的局部自动化、DDC集中控制发展到先进的分布式控制系统(Distributed Control System,简称DCS)和FCS。DCS在保证一定的适应性、扩展性和可靠性的基础上,很好地解决了如何提高系统的控制能力的问题,然而目前市场推出的DCS系统通常以生产过程自动化为主要目标,优化控制仅限于生产过程的局部,对于全局性大系统的优化问题尚未得到应有的重视,影响了DCS的应用效果。 本文在DCS的基础上,提出了以水泥产品质量为直接控制目标的控制方式,将质量控制与生产过程控制结合起来,对水泥厂现有的生产工艺提供优化控制和质量管理的决策支持,对水泥的各阶段质量指标和最终质量指标—28天强度等进行动态追踪实时控制。针对水泥企业数据量巨大,控制点众多,工艺复杂等特有的生产特点,结合了当今工业应用中的前沿技术,以数据库为基础,集成了DSS、数据挖掘、面向对象技术、COM/DCOM、OPC等新兴技术以及一些优化决策算法,如线性规划、多元回归、正交试验等,将现代检测技术、自动控制技术、计算机技术、通讯技术与水泥生产工艺融为一体,在完成设备集成、信息集成的基础上实现全厂质量信息的快速采集、科学处理、工艺设计、质量调控。 本文首先简单描述了系统的结构原理以及一些主要功能模块,对水泥生产工艺进行了一定的阐述,接着重点介绍了水泥工艺优化和质量控制中行之有效的控制算法,对运用这些算法实现在线质量控制和决策支持进行了详尽的论证和说明,并给出应用实例与应用效果。最后给出与DCS实现通讯的方式。 本系统不仅能显著简化浩繁的化验室数据及其他控制点的数据,大大提高劳动生产率,降低工人劳动强度,而且能够提供一个有效的生产工艺优化平台,辅助企业质量管理人员完成质量控制决策,通过现场设备,实现质量闭环调控,优化生产工艺过程,最终达到保证水泥生产质量,提高企业经济效益的目的。
【Abstract】 Facing the more and more severe market competition, the enterprises are very concerned and want to find the way to apply advanced technology to remold traditional industries. And this is also an important research and development area in the applied control technology. With the dramatic development of modern industry, industry production process has experienced enlargement in the scale of control and increase in the degree of complexity. The control mode in the industry production process has been developed from the original partial automatic, DDC concentrated control to the advanced DCS and PCS. DCS not only has the proper adaptive, extension and liability, but also solved the problem of enhance the control ability of the system. However, the current DCS system on the market generally aims at the production process automation, which is limited to the part of the production process. The DCS system is not receiving adequate attention in the comprehensive optimization problem in large systems, and this has badly affected its application efficiency.Based on the DCS, this paper points out the control methods that are directly aimed at controlling the cement production quality. It combines the quality control with the production process control. According to the current production technologyin cement plants, I provide an optimization control and decision support for quality managers. By this control method, you can dynamically follow and real-time control the quality indexes in various stages and in the final stage, such as the 28-day intensity. Most cement plants have large amount of data and control points, and their technology are complicated. Therefore, based on database, I combine many advanced technology in the frontier of current applied industry and integrate many new technology such as DSS, data mining, oriented-object, COM/DCOM, OPC, and some optimization decision methodology such as linear programming, multiple regression. By combining the modern testing technology, automation control technology, computer sciences, communication technology and cement production technology, I have realized the fast collecting, scientifically analyzing, technology devising and quality control of the quality information in the whole plant.This paper begins with a general description of the structure principals of the system and some main function. It then introduces the cement production technology and emphasizes on the efficient control algorithms in the cement technology optimization and quality control. I give out detailed proof and demonstration for the application of these methodologies in the realization of online quality control and decision support, as well as application examples and application outcomes. At last, I present the methods to communicate with DCS.This system can significantly simplify the tedious data in the lab and other control points, and thus greatly increase the production efficiency and decrease the amount of work by the workers. Moreover, this system can also provide a flat for production technology optimization, helping the quality controllers to make quality control decisions. Quality controllers can realize the closed loop quality adjustment and improve the production technology via the on-site equipment. Finally the quality of cement can be guaranteed and the goal of increasing profits is achieved.
【Key words】 online quality control; optimize technology; linear programming; multiple regression; orthogonal experiment plan;
- 【网络出版投稿人】 四川大学 【网络出版年期】2004年 01期
- 【分类号】TP311.52
- 【被引频次】3
- 【下载频次】225