基于机器学习的螺栓连接接触状态实时预测

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摘要：螺栓连接系统界面间的接触状态是衡量其工作状态和密封性能的重要指标。由于受到较强接触非线性和过多耦合变量的影响，接触应力分布的实时预测依然是一个难题。借助机器学习的方法，将复杂的螺栓连接问题封装在后台运算里，最终呈现出一个简单的能够实时预测接触应力分布的前台操作。

关键词：螺栓连接；接触应力；机器学习；实时预测

中图分类号：TH131文献标志码：A文章编号：1671-5276（2024）06-0032-05

Abstract：The contact status of bolted joint between system interfaces is an important indicator measuring its working condition and sealing performance， the real-time prediction of contact stress distribution， however， remains a challenge due to the effects from strong contact nonlinearity and exceeding coupling variables. This article， with the help of machine learning technique， presents a simple front operation window capable of predicting the contact stress distribution in real-time by packaging the complicated bolted joints into background computational process.

Keywords：bolted joints; contact stress; machine learning; real-time prediction

0引言

螺栓作为工业装备中常见的连接单元被大量运用，紧固件间的接触情况一直是领域内的热点和难点。（剩余6730字）