A study of the method of the thermal conductivity measurement for VIPs with improved RBF neural networks

Thermal conductivity is an important physical quantity which is the token of the heat-conducting property of VIPs. The measurement of thermal conductivity is invaluable for VIPs can be widely used. This paper presented a fast and high precision measuring method of VIP's thermal conductivity, and proved its feasibility by simulation. New methods use improved neutral networks to fit the relationship between VIP's thermal conductivity and characteristic value of frequency change, and verified the superiority of this method by experiment compared with the least squares. The presented methods are very valuable for the widespread use of vacuum insulation panels.