Xukai Ren

TL;DR: In this paper, the authors conducted a comprehensive study on the cracking behavior by using optical microscope (OM), scanning electron microscopy (SEM), energy dispersion spectrum (EDS), electron backscatter diffraction (EBSD), X-ray diffraction(XRD), and differential scanning calorimetry (DSC).

TL;DR: It can be concluded that the proposed method based on acoustic signal and the ensemble learning model is effective in predicting the material removal despite the complicated grinding environment.

TL;DR: In this paper, the authors developed a grinding force model and material removal rate model based on single grain force for robotic belt grinding, which divides the whole grinding process into three stages: initial stage, steady stage and accelerated stage, and analyses the grinding force of rubbing, ploughing and cutting effects and MRR at each stage.

TL;DR: In this work, a fast and accurate robotic grinding path planning method is proposed for automatic removal of irregular weldments on a free form surface by adding the weld seam to the parent surface by the proposed superposition method.

TL;DR: In this article, the authors analyzed the grinding energy partition from the perspective of grinding effects and thermal aspects in robotic belt grinding and provided a new venue for studying abrasive belt grinding.