As a crucial substrate material for optoelectronic materials, sapphire has important applications in both military and civilian fields. In order to achieve the final processing quality of sapphire substrate materials, double-sided chemical mechanical polishing (DS-CMP) is a necessary process, which is also a guarantee for the preparation of high-end LED chips. Here, the sapphire DS-CMP processing plan based on the Box-Behnken design is obtained and experimented, then a hybrid approach of response surface method (RSM) and support vector machines (SVM) algorithm is established as the material removal rate (MRR) prediction model for sapphire DS-CMP. Furthermore, the material removal process of sapphire DS-CMP, the influence of response variables on the MRR of sapphire DS-CMP, and the prediction results of RSM-SVM on sapphire DS-CMP are analyzed respectively. From the experimental results, the maximum MRR obtained is 387.59 nm/min, which is more than six times the reported MRR of single-sided CMP under similar process parameters. The mean square error of predicted value through RSM-SVM is basically around ±10% of the experimental value, which possess satisfied validity for the MRR prediction of sapphire DS-CMP. Finally, both top and bottom surface quality of sapphire wafers after DS-CMP processing was investigated.
Uneven surface quality often occurs when butt welds are manually grinding, so robotic weld grinding automation has become a fast-developing trend. Weld seam extraction and trajectory planning are important for automatic control of grinding process. However, most of the research on weld extraction is focused on before welding. Due to the irregular shape of the weld after welding, and too little work has been devoted to the weld identification after welding. Consequently, in this paper, a novel simple and efficient weld extraction algorithm is proposed, and the robot grinding path is planned. Firstly, a new flexible bracket structure for welding seam extraction is designed. Secondly, the weld seam section profile model is established, and the processing of spatial point cloud problem is transformed into the processing of two-dimensional point cloud problem. The least square method (LSM) based on threshold comparison is used to segment the weld seam, which greatly improved the processing speed and accuracy. Then the grinding path and pose are obtained according to the extracted weld space structure. Finally, a robotic welding seam automatic grinding system is built. Experiments show that the proposed method could well extract the irregular weld contour after welding and the grinding system built is reliable, which greatly improves the grinding efficiency. Key words Robot; weld seam extraction; model segmentation; automatic grinding system 1. Introduction1The welding technology plays an irreplaceable role in shipbuilding, automobile, aerospace and other fields [1,2]. However, welding stress will be generated in the weld area after welding, which greatly reduces the connection strength between the workpiece. The welding stress can be reduced and the fatigue strength of the workpiece can be improved by grinding the weld seam [3,4]. Therefore, it has very important practical value and significance to grind the weld after welding. At present, the grinding process for weld seam is usually done by workers, who have to endure the Zhaohui Deng ()
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