基于机理和数据驱动的气流床气化炉耐火砖状态在线监测研究

The entrained flow gasification technology is the main direction of the development of coal gasification technology. The gasifier is the key and core equipment of the whole gasification process. However, due to the complexity of the multivariable in the furnace, there is no technique or method to monitor the corrosion rate or state of the refractory bricks in the gasifier. This project aims to develop an on-line refractory monitoring technology of entrained flow gasifier and achieve the intelligent optimization control of gasifier operation process. The on-line refractory monitoring method of entrained flow gasifier based on the mechanism and data driven is to be proposed in this project. In order to develop the refractory monitoring technology, two key scientific issues should be solved. The first is to build a mathematical model of dynamic mechanism of temperature field in gasifier, which is based on the temperature of the outer wall of the gasifier and the thickness of the refractory brick. The second is to propose the refractory brick corrosion rate model and regulation mechanism of under multi parameters. Three mechanism models are mainly studied, including the rate of the refractory brick erosion, the dynamic distribution of the temperature field in the furnace and the distribution of the dynamic deposition of the wall slag. Then the high precision fast algorithm and adaptive relaxation factor stable iterative method is developed. Through the above research, the on-line monitoring technology for thickness and state of refractory bricks in gasifier will be proposed, form the control method between the key operating parameters of gasifier and corrosion damage rate of refractories. This study would enhance the monitoring and intelligent level of the existing CWS entrained flow gasifier, providing support for the intelligent manufacturing of the entrained flow coal gasification system.

气流床气化技术是煤气化技术发展的主要方向，气化炉是整个技术的关键与核心装备。由于炉内多变量复杂性，迄今没有一种技术或方法对炉内耐火砖蚀损速率或状态进行监测。本项目以气化炉耐火砖状态在线监测为对象，实现气化炉操作过程智能优化控制为需求，创新性提出了基于数据驱动和机理模型相结合的气化炉耐火砖厚度与状态在线监控技术。围绕构建基于气化炉外壁温度、耐火砖蚀损厚度的炉内温度场动态机理数学模型和多参数耦合作用下的耐火砖蚀损速率模型与调控机理两个关键科学问题，重点研究并掌握耐火砖蚀损速率、炉内温度场动态分布、壁面熔渣动态沉积分布三个机理模型，开发高精度快速算法和自适应松弛因子稳定迭代方法。通过以上研究，形成气化炉耐火砖厚度与状态在线监控技术，构建气化炉关键操作参数与耐火砖蚀损速率调控方法，进而提升现有气流床水煤浆气化炉的监控与智能化水平，为气流床煤气化装置智能制造提供支撑。

气流床气化技术是煤气化技术发展的主要方向，气化炉是整个技术的关键与核心装备。本项目以耐火砖气化炉为对象，研究了气化炉内多相湍流流动过程，揭示了气化炉内耐火砖蚀损速率与参数关系，得出温度及低频脉动温度对耐火砖蚀损起决定性作用，建立基于扩散的耐火砖的蚀损速率模型，掌握了基于操作参数减缓耐火砖蚀损速率的控制方法。采用多种模型对气化炉出口合成气温度进行预测，提出了基于激冷室热平衡过程的气化炉出口温度数据驱动预测方法，并结合CFD计算构建的数据库，开发了基于数据驱动和机理模型相结合的气化炉内温度实时在线监控技术；在煤质已知和煤质未知情况下，预测的炉内温度整体误差为19.8K和50K，计算时间约为1s。提出了用灰熔化程度、碳转化率作为描述颗粒表面特征的模型，以动能参数作为颗粒黏附的临界条件，综合渣层特性，提出了颗粒黏附综合模型；分析了不同工况颗粒Saffman升力、热泳力、布朗力对沉积的影响，得出气速的增大使沉积速度出现先增大后减少的趋势，大颗粒限制因素为黏附判据，小颗粒则受沉积机理影响。建立基于数据驱动和机理模型相结合的气化炉耐火砖厚度与状态监控技术，并以千吨级SE水煤浆气化炉内为对象，开发了SE气化炉耐火砖厚度与状态监控软件，实现SE水煤浆气化炉状态实时监控反馈。在本项目支持下，已在AIChE Journal、Fuel 和Chemical Engineering Science 等重要刊物发表论文15 篇，其中SCI 论文12 篇；获省部级科技奖励4项；申请、获得发明专利6 项，培养研究生6名。主要研究成果应用于多喷嘴对置式水煤浆气化炉、SE水煤浆气化炉耐火衬里设计与优化；开发的软件已应用SE水煤浆气化炉装置，建立包含装置运行周期、性能指标的气化炉操作优化建议和智能化分析，提高整个装置的在线率与经济效益。