Review on Intelligent Fault Diagnosis of Wind Tunnel Test System

Under the background of the country 's vigorous promotion of intelligent manufacturing, all kinds of test equipment in the wind tunnel test system tend to be large-scale and complicated. The multi-source, high-dimensional and unstructured massive operation data bring great challenges to the management and monitoring of the wind tunnel test system. Therefore, it is of great significance and value to study the intelligent fault diagnosis technology of wind tunnel test system. According to the time line of technology development, this paper analyzes and summarizes the application status and constraints of traditional signal analysis theory and fault diagnosis method based on traditional machine learning technology. The network structure and model idea of five classical deep learning models are introduced in detail. The research status of the above models in the field of fault diagnosis and prediction of wind tunnel test system is combed, and the advantages and disadvantages of this technology in the field of fault diagnosis of wind tunnel test system are put forward. Finally, according to the possible limitations of the wind tunnel test system, the future prospects in this field are put forward, which provides a reference for the further research of intelligent wind tunnel operation and maintenance technology.