In CNC machining, micro-line toolpaths are widely used for machining parts with free-form surfaces, which are usually fitted to smooth curves to enhance machining efficiency and quality. This paper presents a global t...
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In CNC machining, micro-line toolpaths are widely used for machining parts with free-form surfaces, which are usually fitted to smooth curves to enhance machining efficiency and quality. This paper presents a global toolpath smoothing method based on a novel edge error estimation and regional control points optimization. Firstly, some dominant points are selected according to cubic polynomial fitting error. Subsequently, an initial NURBS curve is generated iteratively. During each iteration, new dominant points are added, and the parameters of the tool tip points are updated. Finally, an edge error estimation method for NURBS curves is proposed and integrated into a regional optimization scheme to generate the resultant NURBS curve under geometric deviation constraints. Simulation and experiment results demonstrate that the proposed method can reduce the number of controlpoints and curvature extreme of the resultant NURBS curve compared with the reference method. Furthermore, our method streamlines the interpolation process, resulting in time savings ranging from 10.66 % to 17.30 %, all the while adhering to the same geometric and kinematic constraints. The method offers an efficient solution for micro-line toolpath interpolation in CNC machining, improving the machining efficiency.
In Industry 4.0 and advanced manufacturing, producing high-precision, complex products such as aero-engine blades involves sophisticated processes. Digital twin technology enables the creation of high-precision, real-...
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In Industry 4.0 and advanced manufacturing, producing high-precision, complex products such as aero-engine blades involves sophisticated processes. Digital twin technology enables the creation of high-precision, real-time 3D models, optimizing manufacturing processes and improving product qualification rates. Establishing geometric models is crucial for effective digital twins. Traditional methods often fail to meet precision and efficiency demands. This paper proposes a fitting method based on an improved sparrow search algorithm (SSA) for high-precision curve fitting with minimal controlpoints. This enhances modeling precision and efficiency, creating models suitable for digital twin environments and improving machining qualification rates. The SSA's position update function is enhanced, and an internal node vector update range prevents premature convergence and improves global search capabilities. Through automatic iterations, optimal controlpoints are calculated using the least squares method. Fitness values, based on local and global errors, are iteratively calculated to achieve target accuracy. Validation with aero-engine blade data showed fitting accuracies of 1e-3 mm and 1e-5 mm. Efficiency in searching for minimal controlpoints improved by 34.7%-49.6% compared to traditional methods. This SSA-based fitting method significantly advances geometric modeling precision and efficiency, addressing modern manufacturing challenges with high-quality, real-time production capabilities.
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