This paper proposed a CNC interpolator based on block overlap, capable of changing acceleration and deceleration time constants during continuous machining. The time constant can be set individually for each block through G-code commands. A velocity profile generation algorithm is proposed to set different time constants for both acceleration and deceleration phases. This algorithm can be applied to short blocks. The block overlap algorithm can be used for corner smoothing. A simulation model of the CNC interpolator was constructed to evaluate the proposed interpolation algorithm. Simulation results demonstrated that the proposed algorithm increased precision in areas with significant angular changes by adjusting time constants while simultaneously reducing machining time.
This paper proposes a cycle time estimation algorithm of a CNC machine tool, using a block overlap based tool path generation algorithm. Velocity profile generation algorithm of CNC interpolator is proposed to compute the cycle time of the G-Code block. Because the CNC blends adjacent velocity profiles to reduce the cycle time and smooth the tool path, the cycle time is adjusted considering the block overlap. The in-position time of rapid traverse is compensated to improve the cycle time estimation accuracy. The simulation model was designed to estimate the cycle time of the CNC machine tool. A three-axis feed drive testbed was used to evaluate the cycle time estimation accuracy of the proposed algorithm.
The study focused on the development of the CAM system restricted to the fabrication of variable pitch screws by using turning centers. To develop the dedicated CAM system at a low cost, open source programming language was used as much as possible. A commercially available 3D-CAD system was used to model variable pitch screws. The edge data of the variable pitch screw was extracted from 3D-CAD data of the variable pitch screw, and then a number of the edge data were copied by the amount of feed in the longitudinal direction of the screw to make a cutter path. The successive cutter path was repeatedly generated by reducing the size of the edge data. The advantage of this method of generating the cutter path is very simple and easy to use, compared with the conventional CAM systems. During the cutter path generation, the system can detect the collision between the cutting tool and the workpiece. As a result, the validity of the developed CAM system for variable pitch screws fabrication was confirmed from several examples of the cutter path generation.
In CNC machining, NC data created by CAM software is usually linearly interpolated. This linearly interpolated tool path, however, may degrade the dynamic motion performance of the machine tool and the geometric accuracy in comparison with the reference CAD data. Tool path smoothing can be an effective way to address these problems. In this paper, a five-axis tool path smoothing method is proposed based on dual cubic B-spline curves. The proposed smoothing method includes two steps. First, the tool orientation is adjusted to reduce drastic changes in tool orientation movement. Then, dual B-spline curves are generated for smooth interpolation of tool position and orientation, wherein their control points are created by using modified internal division points between the top and bottom points of the tool defined by given tool position and orientation vectors. The B-spline curves pass through the junctions of straight line segments comprising the top and bottom points, respectively. Smooth tool position and orientation vectors are finally obtained by simultaneous interpolation of the B-spline curves. The proposed method is implemented in a PC-based five-axis control system and experimentally demonstrated to show improvements in the dynamic motion performance and the geometric accuracy compared with the conventional linear interpolation.
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Research on three-section type tool path planning algorithm for tooth hot pressing model cutting Lijun Zhang, Shaowei Fang, Jiayi Xu, Ning Yang, Weijian Guo, Hang Wang, Changliang Li Computers & Industrial Engineering.2022; 163: 107817. CrossRef