Research On Vacuum Glass Insulation Testing And Vacuum Life Prediction Algorithm

In recent years,the problem of environmental protection and energy conservation has become more and more obvious.The state has invested a lot of money in the environmental protection and energy conservation projects.Vacuum glass which is good for building materials as doors and windows,can effectively reduce the overall energy consumption of buildings.The heat insulation performance parameters(U value)and life detection process that are the main indicators of vacuum glass are difficult to test,the testing process is tedious,the result of the testing is not very good.This problems can not be applied to the problem of vacuum glass online detection,and is not conducive to the promotion of industrialization of vacuum glass.In view of the above problems,this paper combines the current research hot spot:the soft measurement of complex industrial product performance parameters and intelligent modeling to achieve data prediction and data analysis.First of all,based on the specific process of vacuum glass heat transfer,the Principal Component Analysis method(PCA)was used to extract the main parameters of the vacuum glass,and presents a method of vacuum glass insulation performance test.In this method,the rate of temperature change on the side of vacuum glass without heat source is used to measure the performance of vacuum glass;Then,according to the thermal insulation performance test data which set as the vacuum glass insulation performance degradation data to make intelligent modeling and prediction,analysis and prediction of the degradation path of vacuum glass insulation,and get life prediction data of vacuum glass on line and off line.The main research contents include:extraction of main parameters of heat transfer coefficient of vacuum glass based on Principal Component Analysis(PCA)method;Experimental design and data analysis of vacuum glass insulation,building the thermal insulation performance data system;Fitting analysis of degradation model based on performance degradation data,getting the degenerate and degenerate functions,getting the life prediction data of vacuum glass;Modeling and prediction of thermal degradation data of vacuum glass base on Wavelet Neural Network.In this paper,based on the research status of vacuum glass,I designed and realized the experimental equipment and experimental process.The temperature of the vacuum glass which without heat source can be used as a quantitative standard for the thermal insulation performance of vacuum glass.At the same time,combined with the MATLAB software platform and the relevant software warehouse,we can get the performance model of the vacuum glass insulation performance data and the vacuum glass lifetime.The performance degradation model can be used to detect the remaining life of vacuum glass in the process of manufacture and using.The quantitative standard of thermal insulation performance and the degradation model of vacuum glass have laid a good foundation for the preparation of detection equipment and industrial popularization of vacuum glass.