Research on Prediction Method of Bolt Tightening for Aviation Components Based on Neural Network

Abstract

Aviation components play an important role in national defense and aviation development. Bolt connections are widely used in the assembly of aviation components, due to their simple structure and convenient disassembly. In addition to the impact of elastic interaction, the gap between the tightened parts also makes it very difficult to obtain a uniform bolt load, to achieve the required tightness during the tightening process. However, the impact of elastic interaction can be reduced by selecting the best tightening sequence, and the optimal tightening sequence of aviation components under different gaps can be predicted by constructing a neural network surrogate model. Based on the predicted optimal sequence, the elastic interaction matrix corresponding to the sequence can be obtained. In order to obtain a uniform preload, the initial load of each bolt is calculated according to an elastic interaction matrix. This research has improved the tightness of aviation components and the real-life efficiency of tightening process planning.