@article{YUAN2026, 
author = {Ye YUAN and Qixiao ZHU and Rui ZHU and Xiaochen HANG and Pan LI and Qingguo FEI},
title = {Random load identification method and verification in thermal environment based on Tikhonov regularization},
year = {2026},
journal = {Acta Aeronautica et Astronautica Sinica},
volume = {47},
number = {11},
keywords = {regularization, high-speed vehicle, load identification, thermal vibration coupling test, inverse virtual excitation method},
url = {https://www.sciopen.com/article/10.7527/S1000-6893.2025.32325},
doi = {10.7527/S1000-6893.2025.32325},
abstract = {To address the engineering challenge of reduced accuracy in dynamic load identification in the thermal-vibration coupled environment of high-speed vehicle due to environmental interference, this study establishes 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 in 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, comparative experiments were conducted under normal temperature (20 ℃) and high temperature (500 ℃) 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 in thermal-vibration coupling states. Based on load inversion results, it is concluded that the effects of thermal environment 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.}
}