| Citation: | ZHANG Xinsheng, ZANG Chaoping, WANG Xin, et al. Nonlinear parameter identification method for clamps based on neural network proxy model[J]. Journal of Aerospace Power, 2025, 40（9）：20230761 doi: 10.13224/j.cnki.jasp.20230761
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A method for nonlinear parameter identification of pipeline clamp system based on fixed frequency testing and neural network proxy model was proposed. Firstly, modal testing under low excitation amplitudes was conducted, and a bottom level linear model of the pipeline clamp system based on the test data was established. Secondly, fixed frequency tests under different excitation amplitudes and frequencies were performed, the constant displacement and constant velocity response surfaces of the system were constructed, and nonlinear parameter characterization and identification of the dynamic parameters of the clamp based on the equivalent linearization theory were performed. Then, in response to the problem of insufficient response prediction accuracy in the equivalent linearization model, nonlinear dynamic characteristics analysis of the clamp structure under different nonlinear parameters was carried out. Neural network technology was used to quantitatively describe the influence of nonlinear parameters on its response characteristics, and its proxy model was constructed. Finally, based on the proxy model and its sensitivity characteristics, the nonlinear stiffness and damping coefficients of the clamp were identified in reverse, thereby obtaining the nonlinear dynamic model of the system. The response prediction results based on this model were highly consistent with the measured results. The maximum frequency difference at the resonance peak was less than 0.007%, and the response amplitude error was less than 1.53%, indicating that the nonlinear dynamic model obtained based on the identification results can accurately predict its nonlinear vibration behavior, verifying the reliability of the identification results.
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