【作者】 张军；

【导师】 李景银；

【作者基本信息】 东北大学 ， 计算机软件与理论， 2005， 硕士

【摘要】 本文论述了炉型智能检测系统的研究和实现。针对炉前操作人员对炉型管理的新需求,提出了采用基于十字测温边缘温度、炉墙温度和理论燃烧温度计算炉墙粘结厚度的理论和方法。使用回归分析数学方法建立炉墙温度模型,再利用传热学的公式,根据炉墙温度的变化,计算高炉内部粘结的厚度。本文提供了独立的数据提取、回归模型优化、回归模型评价的算法,使整个炉型智能检测系统得到了改进和完善。 本系统按照面向对象的思想,运用了部分设计模式,采用了分布式设计的方法,使系统的可扩展性和可维护性得到了明显的增强。更多还原

【Abstract】 The topic of the papers is the Research and Achievement of Artificial Intelligence Examine and Measure of Blast Furnace Inner Profile.It is completely discussed that new system theory, architecture, implementation with comparing the old system. It is said that the old system character and improvement of new system. A new idea is using Cross wise Temperature, Theory Burning Temperature to predict the Blast Furnace Wall Temperature by Regressing Analysis method. Based on the expressions of Heat Transfer, we get the thick of Blast Furnace Wall. The papers offer independent data-filtered, regressing model-optimized and regressing model-appraised arithmetic, which make Artificial Intelligence Examine and Measure of Blast Furnace Inner Profile improve and consummate.The whole system is modeled by Distributed Design method based on Object-Oriented idea. Use some Design Patterns. It especially improves the expansibility and maintainability of the system更多还原