A data-driven approach to RUL prediction of tools

An effective and reliable prediction of the remaining useful life(RUL)of a tool is important to a metal forming process because it can significantly reduce unexpected maintenance,avoid machine shutdowns and increase system stability.This study proposes a new data-driven approach to the RUL prediction for metal forming processes under multiple contact sliding conditions.The data-driven approach took advantage of bidirectional long short-term memory(BLSTM)and convolutional neural networks(CNN).A pre-trained lightweight CNN-based network,WearNet,was re-trained to classify the wear states of workpiece surfaces with a high accuracy,then the classification results were passed into a BLSTM-based regression model as inputs for RUL estimation.The experimental results demonstrated that this approach was able to predict the RUL values with a small error(below 5%)and a low root mean square error(RMSE)(around 1.5),which was more superior and robust than the other state-of-the-art methods.

Debris effect on the surface wear and damage evolution of counterpart materials subjected to contact sliding

This paper aims to explore the debris effect on surface wear and damage evolution of counterpart materials during contact sliding.A cylinder-on-flat testing configuration is used to investigate the wear behaviours of the contact pair.To explore the roles of wear debris,compressed air is applied to remove the debris in sliding zones.The comparative study demonstrates that the influence of debris removal is related to the surface properties of contact pairs.When substantial wear debris accumulates on the tool surface,debris removal can considerably alter surface damage evolution,resulting in different friction transitions,distinct surface morphology of contact pair,as well as different rates of material removal.It has been found that the surface damage evolution will not reach a stable stage unless the increase of wear particle number ceases or the average size of wear particles becomes lower than a specific threshold.However,the influence of debris removal reduces when the adhesion between the contact pair materials gets smaller.