研究目的
To develop a novel vision-oriented open CNC system for profile grinding machines to enable visual detection and compensation of profile errors during machining, improving precision and efficiency.
研究成果
The developed vision-oriented open CNC system effectively integrates image processing with motion control, meets efficiency requirements for profile grinding, and significantly improves machining precision by enabling real-time error detection and compensation. It provides a reference for developing other intelligent machine tools.
研究不足
The system's efficiency is dependent on the selected software platforms and hardware capabilities; image processing is time-consuming, and accuracy is limited by the vision system's resolution. Future work could optimize algorithms and integrate more advanced sensors.
1:Experimental Design and Method Selection:
The study designed a vision-oriented open CNC system with Ethernet-based hardware and multi-thread software architecture. It included image processing for error detection and virtual-axis-based compensation.
2:Sample Selection and Data Sources:
A high-speed steel specimen with a specific contour profile was used for grinding experiments.
3:List of Experimental Equipment and Materials:
Equipment included a self-developed profile grinding machine, IPC upper computer, Trio MC664-X motion controller, CCD camera (GC2441M), telecentric lens, LED backlight, vitrified bond grinding wheel, and calibration template.
4:Experimental Procedures:
The experiment involved profile grinding without and with error compensation, using in-situ vision for image capture and processing, and offline measurement with a profiler. Machining parameters included spindle speed, feed rate, and depth of cut.
5:Data Analysis Methods:
Time consumption was measured for image processing tasks, and contour errors were analyzed using optimization models and subpixel algorithms.
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