Remaining life prediction of pinch rolls based on Yu parametric deep migration metric learning
To address the problems of little historical data of pinch rolls and the lack of relevant life prediction methods,a method for predicting the remaining life of pinch rolls based on Yu parametric deep migration metric learning was proposed.Firstly,Yu parametric depth metric learning(DMN-Yu)was used to extract deep features from vibration signals,and the features were combined with principal component analysis(PCA)and self-organizing mapping neural network(SOM)to construct a one-dimensional health factor(HI)by reduction.Then,the target pinch rolls were predicted and analyzed by a migration strategy using a shared hidden layer approach in combination with a long and short term memory network(LSTM)model.The experiment verified that the LSTM model with deep migration learning had a better prediction effect,which was a guideline for the health state assessment and remaining service life prediction of pinch rolls equipment.
NETL
NSTL
万方数据
维普
