The environmental wind tunnel of high-speed railway trains serves as a crucial experimental facility for the research and development of high-speed railway technology. The refrigeration system within the wind tunnel is an important subsystem. However, the design of the wind tunnel refrigeration system management program presents significant scientific challenges and limitations. Traditional management approaches in wind tunnel refrigeration systems suffer from prolonged decision-making times and reliance on experiential knowledge, necessitating the need for intelligent transformation. This paper aims to address these issues by exploring existing intelligent management methodologies and defining the concept of a wind tunnel intelligent laboratory along with its primary modules. Furthermore, we propose a water cooler failure prediction model based on the existing equipment model of the wind tunnel’s refrigeration system. This model effectively predicts the Remaining Useful Life (RUL) of the water cooler in the case of fouling failure, contributing to enhanced efficiency, cost reduction, and safety improvements in laboratories.