转炉煤气干法除尘系统温度控制策略研究

发布时间：2018-03-12 12:00

本文选题：干法除尘　切入点：温度控制　出处：《安徽工业大学》2016年硕士论文　论文类型：学位论文

【摘要】：转炉煤气干法除尘技术由于具有节能减排效果好、煤气回收效率高等显著优点,可大幅度降低水资源消耗和减少大气环境污染,因而成为目前钢铁行业转炉冶炼工艺大力推行的高效能源转换新技术。其关键核心问题是在保证除尘设备安全、高效和经济运行前提下,如何提高烟气除尘的工作效率。而蒸发冷却工艺的出口烟气温度控制是影响除尘效率的重要因素。烟气温度控制过程是一个复杂的时变动态过程,系统运行受到多种变量参数的影响。因此,深入开展蒸发冷却器烟气温度控制优化控制系统的研究,对于进一步提高炼钢产品产量和质量、稳定生产过程、实现节能降耗、提高企业效益都具有重要的实际意义和工程价值。本文以蒸发冷却器为对象,对其烟气温度控制系统进行了工艺分析、控制器设计、仿真验算和软硬件系统实现几个方面的研究,具体工作内容如下:(1)在了解、消化转炉煤气干法除尘工艺流程的基础上,分析了烟气温度控制过程的动态特性和相关影响参数的函数关系,总结和归纳了烟气温度控制系统的任务要求。(2)以喷水阀开度为输入量,蒸发冷却器烟气出口温度为被控量,采用RBF神经网络与PID控制器相结合的控制方法,运用RBF神经网络整定PID参数。(3)将RBF神经网络与辨识算法相结合,组成了基于RBF神经网络自适应辨识器,对烟气温度控制系统实现自适应辨识。(4)将RBF神经网络整定参数的PID控制系统和基于RBF神经网络辨识器相结合,对蒸发冷却器烟气出口温度进行控制,并采用MATLAB仿真。结果表明,与传统的控制系统相比,基于RBF神经网络的控制系统超调小、响应快,并且具有较强的抗干扰性能,满足工艺要求,达到了较为理想的控制效果。(5)针对干法除尘烟气温度控制系统的设计和实现,采用西门子自动化产品设计了DCS控制方案,并进行了有关硬件的配置和选型、PLC系统的硬件组态以及PCS7软件程序的开发。
[Abstract]:Because of its remarkable advantages such as good energy saving and emission reduction and high gas recovery efficiency, converter gas dry dust removal technology can greatly reduce the consumption of water resources and reduce atmospheric environmental pollution. Therefore, it has become a new technology of high efficiency energy conversion, which is vigorously implemented by converter smelting process in iron and steel industry. The key problem is to ensure the safety, efficiency and economic operation of dust removal equipment. How to improve the working efficiency of flue gas dedusting. The flue gas temperature control at the outlet of evaporative cooling process is an important factor affecting the dust removal efficiency. The flue gas temperature control process is a complicated time-varying dynamic process. The operation of the system is affected by a variety of variable parameters. Therefore, the research on the optimal control system of flue gas temperature control of evaporative cooler is carried out in order to further improve the output and quality of steelmaking products, stabilize the production process, and achieve energy saving and consumption reduction. It is of great practical significance and engineering value to improve the efficiency of enterprises. In this paper, the process analysis and controller design of the flue gas temperature control system of evaporative cooler are carried out. Research on several aspects of simulation checking calculation and software and hardware system implementation. The specific work contents are as follows: 1) on the basis of understanding, digestion converter gas dry dust removal process, In this paper, the dynamic characteristics of flue gas temperature control process and the functional relationship of related parameters are analyzed, and the task requirement of flue gas temperature control system is summarized. The nozzle opening is taken as the input amount, and the flue gas outlet temperature of the evaporative cooler is controlled. Using the control method of combining RBF neural network with PID controller, using RBF neural network to adjust PID parameter. 3) combining RBF neural network with identification algorithm, an adaptive identifier based on RBF neural network is constructed. The self-adaptive identification of flue gas temperature control system is realized. The PID control system based on RBF neural network is combined with the RBF neural network identifier to control the flue gas temperature of evaporative cooler, and the MATLAB simulation is used. The results show that, Compared with the traditional control system, the control system based on RBF neural network has the advantages of small overshoot, fast response, strong anti-interference performance, and meets the technological requirements. According to the design and realization of dry dust removal flue gas temperature control system, the DCS control scheme is designed with Siemens automatic products. The hardware configuration of PCS7 system and the development of PCS7 software program are also carried out.
【学位授予单位】：安徽工业大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TF345

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