Multi-cutter optimization combination selection method for triangular grid model numerical control processing

Abstract

The invention discloses a multi-cutter optimization combination selection method for triangular grid model numerical control processing, and the method comprises the steps: reading in a triangular grid model and building topological information; enabling the model to be segmented into a plurality of feature subregions based on a patch normal vector and a patch principal curvature; carrying out thequick cutter interference inspection of the feature regions which may generate interference, and obtaining a cutter interference region; employing different cutter track generation strategies for different types of feature subregions, and estimating the lengths of tracks based on a corresponding line spacing calculation formula through cutter track length estimation models of all feature regions;determining the smallest cutter according to the maximum principal curvature of a triangular patch and a standard cutter size, and employing a genetic algorithm to optimize other cutters. The methodcan obtain a high-efficiency processing cutter combination of a complex triangular grid model more effectively and precisely.

Description

technical field [0001] The invention belongs to the technical field of numerical control machining, and in particular relates to a multi-cutter optimal combination selection method for numerical control machining of a triangular grid model. Background technique [0002] In NC machining, in order to improve the machining efficiency, large-size tools are generally used as much as possible. However, for complex geometric models, there are often interference areas that cannot be processed by large-size tools. Therefore, small-size tools are required to process the interference areas. For complex geometric models, there may be a large gap in the processing efficiency of different tool combinations, so the optimal combination selection of tools is also an important research content in the field of CNC machining. [0003] At present, in terms of tool combination optimization, a lot of research has been done on the 2.5D cavity of the mold at home and abroad and relatively mature res...

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Problems solved by technology

However, this method uses a single estimation model for the entire model when estimating the trajectory length, and does not consider the influence of different surface features on the tool trajectory length, and the trajectory length estimation is not accurate.

The academic paper "Cutting Tool Combination and Machining Strategy Affectation Based on the Determination of Local Shapes for Freeform Surfaces" published by BeyM et al. at the academic conference "International Conference on Smart Manufacturing Application, 2008" considered the influence of different types of regions on the processing time, but the processing strategy only considered the parallel section method and the contour method, and the simulation method was used to obtain the processing time. It is necessary to generate the tool path when the time is high, which will affect the efficiency

[0004] In short, in the existing methods of tool combination optimization for surface models, the influence of model geometry on machining is not fully considered, but the result of low precision is used as the criterion for optimization selection to select the optimal tool combination, resulting in the accuracy of the algorithm. The performance needs to be further improved; at the same time, it is also necessary to adopt a suitable tool optimization combination method to further enhance the adaptability

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