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Recognition and classification of protrusion features on thin-wall parts for mold flow analysis

机译:模具流动分析薄壁零件突起特征的识别与分类

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摘要

Thin-wall plastic parts exist in many products and are frequently manufactured by injection molding. The inner surface of a thin-wall part has many functional and structural features, typically divided into depressions and protrusions. While recognition of protrusion features is important in mold flow analysis, this recognition is difficult owing to the complexity and variety of the designed shapes. The purpose of this study was to develop a method for the detection and classification of protrusion features on thin-wall plastic parts. In the proposed algorithm, the inner and outer faces of a part model were detected first. Auxiliary faces, including translational, wall, and bottom faces, were recognized next. With auxiliary faces available, protrusion faces can thus be recognized and grouped in accordance with their neighboring relationship. A feature classification algorithm was finally implemented to classify five types of protrusions, namely tubes, ribs, columns, polygon blocks, and irregular extrusions. A detailed description of the procedures in each step of the proposed algorithm is provided. Twelve CAD models and analysis results are also presented to demonstrate the feasibility of the proposed protrusion recognition algorithm.
机译:薄壁塑料部件存在于许多产品中,经常通过注塑制造。薄壁部分的内表面具有许多功能性和结构特征,通常分为凹陷和突起。虽然突出特征的识别在模具流动分析中很重要,但由于设计形状的复杂性和各种各样,这种识别难以。本研究的目的是开发一种用于薄壁塑料部件上的突起特征的检测和分类方法。在所提出的算法中,首先检测零件模型的内面和外面。接下来识别辅助面,包括平移,墙壁和底面。使用可用辅助面,因此可以根据其邻近的关系来识别和分组突出面。最终实现了一个特征分类算法以对五种类型的突起,即管,肋,列,多边形块和不规则挤出进行分类。提供了所提出的算法的每个步骤中的过程的详细描述。还提出了十二个CAD模型和分析结果,以证明所提出的突出识别算法的可行性。

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