Real-time Prediction of Bolted Joint Contact State Based on Machine Learning
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.
万方数据
维普
