真空玻璃保温性能检测和真空寿命预测算法研究

发布时间：2018-04-26 23:28

本文选题：真空玻璃保温性能 + 主元分析(PCA)　；参考：《海南大学》2017年硕士论文

【摘要】：近年来,环保节能问题越来越显著,国家投入大量的资金到环保节能项目中。真空玻璃作为良好的建筑和门窗节能材料,能够有效的降低建筑物整体的能耗。而真空玻璃保温性能参数(U值)和真空玻璃真空寿命作为真空玻璃性能的主要指标,检测过程繁琐、困难、结果一致性较低,不能应用于真空玻璃在线检测等问题,使得真空玻璃的产业化推广和实际使用遇到很大的困难。针对上述问题,本论文结合当前研究热点:复杂工业产品性能参数的软测量检测方式和智能建模实现数据预测和数据分析。首先结合真空玻璃传热具体过程,通过主元分析方法(PCA)提取对真空玻璃保温性能影响最大的主元变量,提出一种真空玻璃保温性能实验检测方法,该检测方法以真空玻璃非热源侧的温度变化率作为指标衡量真空玻璃保温性能:然后针对保温性能检测实验检测数据作为真空玻璃保温性能退化数据进行智能建模预测,分析预测真空玻璃保温性能的退化轨迹,对在线和非在线的真空玻璃进行真空寿命预测。主要的研究内容包括:基于主元分析方法(PCA)对真空玻璃传热系数检测参数的主元变量提取;真空玻璃保温性能实验设计和检测数据分析,建立真空玻璃保温性能指标数据体系;基于性能退化数据的退化模型拟合分析,得到退化曲线和退化函数,对真空玻璃真空寿命预测;小波神经网络(WNN)针对真空玻璃保温性能退化数据的建模和真空寿命预测。本文结合本人专业和真空玻璃研究现状,设计和实现了真空玻璃保温性能实验。检测得到的真空玻璃非热源侧温度可以作为真空玻璃保温性能的一个定量指标,同时结合MATLAB软件平台和相关软件仓库对检测得到真空玻璃保温性能数据和真空玻璃使用时间进行智能建模,得到性能退化模型,通过模型预测和判断真空玻璃的真空寿命数据。该性能退化模型能够良好的检测出厂和使用过程中的真空玻璃真空剩余寿命。保温性能定量标准和真空玻璃性能退化模型为真空玻璃相关检测设备制备和真空玻璃产业化推广奠定良好的基础。
[Abstract]:In recent years, the problem of environmental energy conservation has become more and more prominent, and the state has invested a lot of funds into environmental energy conservation projects. Vacuum glass as a good building and door-window energy-saving materials can effectively reduce the overall energy consumption of buildings. But the vacuum glass insulation property parameter (U value) and the vacuum life of the vacuum glass are the main indexes of the vacuum glass performance. The testing process is tedious, difficult, the result is low consistency, and can not be applied to the vacuum glass on-line detection and so on. So that the industrialization of vacuum glass promotion and practical use encountered great difficulties. In view of the above problems, this paper combines the current research focus: soft sensor detection of complex industrial product performance parameters and intelligent modeling to achieve data prediction and data analysis. According to the specific process of vacuum glass heat transfer, the principal component variables which have the greatest influence on the thermal insulation performance of vacuum glass are extracted by principal component analysis (PCA) method, and an experimental test method for vacuum glass thermal insulation performance is proposed. In this method, the temperature change rate of the non-heat source side of the vacuum glass is taken as the index to evaluate the thermal insulation performance of the vacuum glass. Then, the test data of the thermal insulation property are used as the degradation data of the thermal insulation property of the vacuum glass for intelligent modeling and prediction. The degradation trajectory of vacuum glass thermal insulation performance is analyzed and the vacuum life of vacuum glass is predicted for both online and off-line vacuum glass. The main research contents include: extracting the principal component variables of the testing parameters of vacuum glass heat transfer coefficient based on the principal component analysis method, designing the experimental design of vacuum glass thermal insulation performance and analyzing the test data, establishing the vacuum glass thermal insulation performance index data system; The degradation curve and function are obtained to predict the vacuum life of the vacuum glass, and the wavelet neural network (WNN) is used to model the degradation data and predict the vacuum life of the vacuum glass. In this paper, we design and implement the experiment of vacuum glass insulation performance according to my professional and vacuum glass research status. The measured non-heat source side temperature of vacuum glass can be used as a quantitative index of thermal insulation performance of vacuum glass. At the same time, combined with MATLAB software platform and related software warehouse, the vacuum glass thermal insulation performance data and the vacuum glass usage time are modeled intelligently, and the performance degradation model is obtained. The vacuum life data of vacuum glass are predicted and judged by the model. The performance degradation model can detect the vacuum residual life of vacuum glass in the process of production and use. The quantitative standard of thermal insulation and the degradation model of vacuum glass properties lay a good foundation for the preparation of vacuum glass related testing equipment and the industrialization and popularization of vacuum glass.
【学位授予单位】：海南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TQ171.72

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