Abstract
It is difficult to accurately predict the change of clamping force in bolt loosening state. Aiming at the this problem, based on the data-driven method guided by bolt loosening mechanism, a prediction method for bolt loosening characteristics was proposed. The mechanism model of the loosening process was established in combination with the mechanical state of bolt. The sensitivity analysis of each feature in the mechanism model was carried out through the parameter test method, and the evaluation index was proposed to obtain the crucial features of the loosening process. Furthermore, considering the nonlinear and uncertain characteristics of bolt loosening, a prediction model of bolt loosening characteristics based on Gaussian Process Regression (GPR) was proposed and verified. The results showed that compared with the traditional regression model, the proposed model could not only obtain the change of the mean value of preload but also describe the confidence interval of preload change in the sense of probability synchronously, which provided a guarantee for the accurate prediction of bolt loosening characteristics; the model proved to be reasonable by the excellent consistency of bolt loosening test data and prediction data.
| Translated title of the contribution | Prediction of bolt connection loosening based on mechanism and data fusion |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 692-700 |
| Number of pages | 9 |
| Journal | Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS |
| Volume | 27 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 2021 |