| Summary: | 碩士 === 國立虎尾科技大學 === 機械與電腦輔助工程系碩士班 === 106 === Owing to introduce the concept of industry 4.0 from Germany. The various country began to invest in manufacturing intelligent technology research and development. United States proposed Advanced Manufacturing Partnership (ASP), China proposed Made in China 2025, Japanese proposed Industry 4.1J. The Taiwan government also currently introduction of Smart Manufacturing and Taiwan Productivity 4.0 Initiative. In the machine tool section, the unmanned production line has become the current trend. Although the machine tool manufacturing production line has been able to achieve automatic loading and unloading for the workpiece. However, if replace the workpiece that has not been set in advance. It still required to manually perform alignment for the workpiece. This will result in higher time and cost. Development for automated workpiece alignment system can reduce alignment time, and achieve the purpose of the unmanned factory. In the automated workpiece alignment section, Germany DATRON[3] develops the neo measurement system, which automatically aligns the workpiece by its self-developed 2D vision system. However, it still needs the manual operation.
Therefore, this study develops a 3D scanning system using the structured light of gray code for aiding the workpiece position of CNC machine tool online. The 3D scanning system automatically aids the machine tool probes for component setting and inspection. A 3D scanning system consisting of one camera and one projector with structural light has been set up in order to acquire the images representing the scanned object with projected light patterns. These images are then decoded and analyzed in order to obtain the depth information for each point representing the workpiece. The research is mainly divided into four parts. First, the workpiece is reconstructed 3D model points based on the structured light of gray code using C++ programming. Second, the noise filtering, edge detection, and other post-processing can obtain 3D model points using the Point Cloud Library (PCL). The 3D model points are large data sets composed of 3D physical point data. Third, to automate the workpiece alignment with the self-developed detection equipment and the reconstructed processing workpiece edge model. Fourth, we established a human-machine Interface to connect the CNC controller and the 3D scanning system for uploading data. Resulted showed that the dimensional accuracy error of the 3D scanning system after reconstructing 3D model points is about ±0.1mm for each axis. The repeated precision error of the 3D model edge points is about 0.05 mm. The time delay of Bluetooth communication between the edge-finding device is about 11 milliseconds, resulting average movement error is about 0.0005mm. The running time of the 3D scanning system with automatic workpiece position is about 99~103 seconds, including, structured light scanning, 3D model points processing, edge detection, and automatic positioning. Experiments show that this study can achieve the online fast automatic workpiece positioning on CNC machine tool.
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