High-fidelity modeling method for closing self-locking nuts and study of structural parameter optimization

Abstract

The Closing self-locking nut (CSLN) has better anti-vibration and anti-loosening properties compared with the plain nut, and is widely used in the aerospace field and other industries. However, because the nut has the closing area, it is difficult to accurately build the thread model. Much of the research on the CSLN has focused on experiments. The high-fidelity modeling method of the CSLN is needed. In this study, the thread expression of the closing area is derived. The model is established by MATLAB and HYPERMESH, combined with the standard thread modeling method. Before modeling, the thread expression of the closing area is derived. The accuracy of the high-fidelity model is verified by loosening characteristics experiments. Finally, the response surface method is used to analyze the effect on the anti-loosening property of the CSLN. The influencing parameters are the closing length, the nut thickness, the nut diameter and the closing amount. And the optimal structure parameters of the CSLN is obtained. The results show that the simulation of the high-fidelity model matches the reality. The errors between simulation and experiment are less than 4.69%. The residual preload is positively correlated with four influencing factors. The closing area length has the greatest effect on the residual preload. The optimum structural parameters are 6 mm the closing area length, 1 mm the nut thickness, 5 mm the nut diameter, and 0.06 mm the closing amount. The residual preload at this point is 9127 N, which is 20.6% higher than the original. The research provides an accurate and convenient modeling method for the study of the CSLN, and provide the reference for model optimization design.