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基于炉体表面温度测量的AOD炉炉衬厚度与寿命预估

Forecast of AOD Converter Lining Thickness and Longevity Based on the Surface Temperature of AOD Convert

【作者】 冯洁

【导师】 李培玉;

【作者基本信息】 浙江大学 , 机械工程(专业学位), 2016, 硕士

【摘要】 目前,在钢铁精炼中,氩氧脱碳转炉(Argon Oxygen Decarburization,简称AOD转炉)是不锈钢冶炼的主流承载及冶炼容器。随着不锈钢产品在人们生产生活中需求量的不断地加大,AOD转炉的作用也日益突显。但与传统的炼钢转炉相比,AOD转炉的冶炼寿命周期要低很多,且目前国内尚无成熟的应用于AOD转炉的炉衬厚度检测技术,炉衬使用寿命基本凭借技术工人的经验判断。因而,对于如何准确预估AOD转炉炉衬厚度及寿命,降低炉衬材料的浪费,节省生产成本的问题也备受各大冶金企业关注。本文针对这一实际性需求,对国内某钢厂进行实地调研,提出以红外热像仪捕获的炉表温度来预估AOD转炉炉衬厚度与寿命的方案。全文按如下几个章节的内容展开叙述:第一章主要介绍了课题的研究背景及企业的需求,简要介绍了若干常用的冶金炉炉衬厚度检测技术,并结合AOD转炉的实际生产情况,在经过若干方案的可行性分析及对比后,提出了本文使用的AOD转炉炉衬厚度及寿命预估的方案。第二章介绍了AOD转炉的基本组成,影响其寿命的几个主要因素,并就其在不同部位、不同冶炼时期的侵蚀特征展开了相关的叙述。第三章主要讲述某钢厂AOD转炉的热仿真过程,通过实物仿真,得出炉衬厚度与炉表温度的定性关系,从实验角度为后续研究提供依据及参考。第四章主要介绍了AOD转炉炉衬厚度及寿命预估模型建立过程中用到的一个重要算法,对该算法技术的基本概念、结构作了必要的阐述。第五章在第三章仿真分析的基础上,首先提出了炉衬均匀化蚀损这一假设前提,并基于该假设建立了AOD转炉炉衬厚度及寿命预估模型。接着以红外热像仪在现场采集到的炉表温度数据及炉衬厚度数据对该模型进行可靠性验证。在该关系模型的可靠性得到确认后,本文最后又提出了归一化处理这一概念,通过归一化处理得方式扩展了该预估模型的适用范围,使之在某些非正常的生产状况下也能呈现较好的可靠性,较为准确的预估炉衬厚度及寿命。第六章是对全文的一个总结,简要的回顾了本文主要内容与不足,并就该课题后续的进一步深入研究提供了建议。

【Abstract】 Argon Oxygen Decarburization (AOD converter for short) converter is the most popular container for stainless steelmaking when in the refining of steel at present. As the increasing demand for stainless steel products, the AOD converter also become more and more important. Compared with the traditional steelmaking converter, AOD converter life cycle is much lower, and now there is no mature detection technology for AOD converter lining thickness detection at home, the lining life of AOD converter is mostly judged on experience of workers. Therefore, the problem of estimating the lining life of AOD converter accurately, reducing the waste of lining material, saving the production cost also receives a lot of attention of metallurgical enterprises. Based on the actual demand and site investigation, we mean to estimate the lining life of AOD converter and lining thickness of AOD converter through the furnace surface temperature captured by infrared thermal imager. The full text is composed of the following several parts:The first chapter mainly narrates the research background and enterprise requirements, and in this part, several commonly used techniques which is used to detect the lining thickness of the metallurgical furnace are briefly introduced. After the considering the actual production condition of AOD converter and feasibility analysis of several scheme, we puts forward the lining thickness and lining life forecast scheme of AOD converter.The second chapter recommends the basic composition of AOD converter, several key factors that affecting the lining life, and the lining erosion characteristics of AOD converter for different parts and different smelting period.The third chapter mainly narrates the thermal simulation process of a concrete AOD converter, and through the simulation we get the qualitative relationship between the lining thickness and furnace surface temperature. The simulation result provides experimental basis for further research.The fourth chapter is mainly about an important algorithm used in the forecast model for the prediction of AOD converter lining thickness and lining life. Meanwhile, it expounds the basic concepts and structure of the algorithm technology.On the basis of the simulation analysis shown in the third chapter, the fifth chapter assumes that the pitting of lining is linear and homogeneous. Then, it establishes the prediction model for AOD converter lining thickness and lining life prediction through the homogenization assumption. With furnace surface temperature data captured by infrared thermal imager, we validate the reliability of the model. When the reliability of prediction model is confirmed, then we put forward the concept of normalization processing, which expanding the scope of the forecast model and making it work well in some abnormal production conditions.The sixth chapter is a summary of full text, briefly reviewing the main content of the paper, and providing some advice on the further research of the subject.

  • 【网络出版投稿人】 浙江大学
  • 【网络出版年期】2016年 07期
  • 【分类号】TF748.2
  • 【被引频次】1
  • 【下载频次】227
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