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冲击试验机波形预测方法研究.

Authors :
刘 博
闫 明
李朕均
雷 蕾
Source :
Journal of Mechanical & Electrical Engineering. Sep2024, Vol. 41 Issue 9, p1715-1722. 8p.
Publication Year :
2024

Abstract

When using impact testing machine to evaluate products, it often fails to reach the peak acceleration and pulse width of the specified pulse waveform, and it needs to be adjusted by the experience of testers and repeated experiments. Therefore, in order to accurately predict the shock waveform before the shock test and save debugging time and resources, a method was proposed to predict the peak acceleration and pulse width of the waveform using a nonlinear regression model. First, the Mooney-Rivlin model was used to fit the hyper elastic intrinsic parameters of the waveform generator, a finite element model of the shock system was established, and shock tests were conducted to verify the accuracy of the finite element model. Then, the finite element and orthogonal experimental methods were used to study the effects of parameters such as hardness, thickness, diameter and shock table drop height of the waveform generator on the shock waveform. Finally, the power function was chosen as the functional form of multivariate nonlinear regression and the less significant factor terms were eliminated to establish the prediction model of peak acceleration and pulse width of the shock waveform, and the accuracy of the prediction model was verified by the shock test. The research results show that the thickness and diameter of the waveform generator and their interaction are the main factors affecting the shock waveforms. Comparing the predicted values of the regression model with the shock test data, it is found that the error between the two is not more than 10%, which indicates that the established regression prediction model of impact waveform is effective. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
10014551
Volume :
41
Issue :
9
Database :
Academic Search Index
Journal :
Journal of Mechanical & Electrical Engineering
Publication Type :
Academic Journal
Accession number :
180222426
Full Text :
https://doi.org/10.3969/j.issn.1001-4551.2024.09.020