基于软测量的自支撑钢化真空玻璃性能预测与结构优化研究

This project considered the intensive quenching process of the glass with upheaval boundary condition as the research object, the material structure optimization of the tempered vacuum glazing with self-supporting pillars as the goal, the statistical thermodynamics, materials and structural chemistry,soft sensor intelligent modeling， etc as the theoretical basis, applied the quenching modified information and the cooling performance controlling means of the metal materials to the modeling of the heat transferring process for the tempered vacuum glazing with self-supporting pillars.With the concept of the catastrophe theory, the key scientific problems were catched that the micro-natures of the inorganic non-metallic materials determines its macro performance and the macro performance reflects its micro-natures. The quenching mechanism of the glass, the key parameters' influence on the quenching quality, intelligent modeling combined the mathematical model with RBFNN model of the quenching process will be studied, then the prediction model revealing the inherent relations among the quenching process, the work piece, the micro-natures of the materials and it's macro performance will be established, and the unique theory system and scientific method for the interdicipline produced by the quenching process and materials will come into being. The research will provide one new way for the selection, preparation and application of the piece materials for the vacuum glazing and simultaneously make contributions to promoting the cross development of the inorganic nonmetallic materials science and the soft sensor intelligent modeling theory.

以界面条件剧变的玻璃淬火过程与真空玻璃传热过程为研究对象，以自支撑钢化真空玻璃基片支撑点结构优化为目标，以统计热力学、材料和软测量智能建模等为理论基础，将金属材料热处理改性信息和冷却性能调控手段应用于钢化玻璃冷却过程传热机理模型和自支撑真空玻璃结构及性能调控中，结合突变论与选择透过性思想，紧紧抓住无机非金属材料的微观性质决定其宏观性能、宏观性能体现其微观性质这个关键科学问题，研究玻璃材料淬火过程机制，研究淬火过程关键参数对淬火工件硬度分布的影响，提出机理数学模型与RBF神经网络混合的自支撑钢化玻璃基片淬火过程与真空玻璃传热过程智能建模方法，在非常规玻璃淬火过程、淬火工件、材料微观性质与宏观性能之间架起理论桥梁，建立起能揭示其内在联系的理论预测模型，形成该交叉学科独有的理论体系和科学方法，为真空玻璃基片材料的选择、制备与应用提供新思路指导，推动无机非金属材料科学与软测量智能建模理论交叉发展。

针对建筑围护结构保温性能提升对真空玻璃这一透明高保温节能材料的重大需求，研究了真空玻璃的传热过程的基于数据的软测量智能建模方法及基于机理模型的非稳态算法，研究了基于退化轨迹分析的真空寿命预测方法；为提高真空玻璃的安全性能及生产效率，发明了自支撑、随机支撑、无支撑等真空玻璃支撑点支撑方法，发明了基于激光微加工的真空玻璃前处理及焊接方法，使真空玻璃的结构得以优化；基于水基淬火介质的冷却特性曲线，研究了金属材料淬火过程中关键参数对工件硬度的影响，可实现在水与油冷却特性之间任意调控。本研究为实现服役中真空玻璃保温性能的动态监测与真空寿命的在线预测奠定了理论基础，为实现淬火介质的“水代油”技术及高端金属材料的热处理质量奠定数据基础。提出了基于非稳态真空玻璃传热过程软测量智能建模方法与基于退化轨迹分析的真空玻璃真空寿命预测方法；起草了《真空玻璃保温性能检测方法与真空寿命预测方法 非稳态法》国家标准；研制真空玻璃性能检测仪器系统与基于真空水淬的高端金属材料热处理系统。获得了真空玻璃非热源侧温度变化速率及加速率数据可代替难以直接检测的真空度衰减率数据，宏观关联真空玻璃的保温性能及真空寿命；基于有机无机复合的水基淬火介质的冷却特性曲线数据，长程关联金属材料热处理质量。在玻璃淬火过程、淬火工件、材料微观性质与宏观性能之间架起了理论桥梁，建立起能揭示其内在联系的理论预测模型，形成该交叉学科独有的理论体系和科学方法，为真空玻璃基片材料的选择、制备与应用提供新思路指导，推动了无机非金属材料科学与软测量智能建模理论交叉发展。