Dual-Layer Characteristic Temperature Model for AWES Dynamic Thermal Detection Based on IR

Abstract

AbstractWith the increasing application of the AWES, the dynamic thermal detection of the electrolyzer inspires great interest. The dimension of dynamic thermal detection of the AWES is currently limited to only the inlet and outlet temperatures. This study proposes a dual-layer characteristics temperature model for AWES temperature monitoring. The DLCT model deals with the difficulty of extracting characteristic temperature with its first layer of multi gaussian distribution regression. The second layer model can clarify the disturbing signal using linear regression and provide a quantized temperature distribution pattern of the surface temperature. This DLCT model does not require additional modifications to the AWES, nor any temperature sensor inside or on its surface. With the DLCT model implemented during dynamic operation, the AWES can be more comprehensive monitored, and more insights can be gathered regarding the DLCT for better thermal uniformity.