Abstract: To address the engineering challenge of reduced accuracy in dynamic load identification under the thermal-vibration coupled envi-ronment of high-speed aircraft due to environmental interference, this study has, for the first time, established a test platform for random load identification that considers thermal-vibration coupling effects. This platform integrates a shaker and a quartz lamp array to achieve precise application of random and thermal loads, respectively, and combines high-temperature accelerometers to measure dynamic responses under ground-based thermal conditions. To account for temperature effects, a random load identification method under thermal environments based on Tikhonov regularization is proposed. By incorporating model corrections that consider thermal effects and introducing a frequency response function deformation matrix into Tikhonov regularization to account for the application conditions of random loads, the method is used to perform inversion analysis on structural dynamic response data. Finally, compara-tive experiments were conducted under normal temperature (20°C) and high temperature (500°C) conditions. The results indicate that the platform can effectively simulate the thermal-vibration coupled test conditions of an aircraft and meet the requirements of load inversion under thermal-vibration coupling states. Based on load inversion results, it was concluded that the effects of thermal envi-ronment on structural parameters and thermal disturbance noise are key factors affecting load identification accuracy, providing a theoretical foundation and experimental support for the development of random load identification technology in complex thermal-vibration coupled environments.

Key words: thermal vibration coupling test, load identification, model correction, inverse virtual excitation method, regu-larization