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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/78913


    題名: 塑膠射出成型薄殼件特徵辨識、分離與規則化網格自動建構技術發展;Development of Feature Recognition, Decomposition and Automatic Mesh Generation Technology for Thin-Walled Plastic Injection Parts
    作者: 賴景義
    貢獻者: 國立中央大學機械工程學系
    關鍵詞: 特徵辨識;特徵分解;實體網格;凹陷物;凸起物;;薄殼件;Feature recognition;Feature decomposition;Solid mesh generation;Depression;Extrusion;Rib;Thin-walled parts
    日期: 2018-12-19
    上傳時間: 2018-12-20 14:03:54 (UTC+8)
    出版者: 科技部
    摘要: 塑膠射出薄殼件在許多消費性產品上都是很普遍的零件,其特點為本體為薄殼,內部有許多功 能性幾何特徵的設計。塑膠薄殼件在外表面局部區域常會發生縮水現象,主要原因為該區域內側為 特徵與本體交界處,因為肉厚不均勻所導致。模流分析已普遍應用於射出成型上,用以輔助產品設 計、模具設計與製程參數設定,以改善射出成品的品質。在模流分析中,眾所周知六面體與稜柱體 組合的實體網格,在計算精度、收斂性、與應用性上,都具有比四面體網格更佳的品質。然而,此 種實體網格較難以建構,因為需要依各區域建構的方式將CAD 模型分解,即使對有經驗的CAE 工 程師而言,此一步驟費時又費工。特徵辨識在學術上研究已有多年,一些商用型CAD 系統均已有特 徵辨識的功能,也有一些研究探討特徵辨識於CAD 模型自動分解與網格化的技術,但是,這些方法 在工業應用上仍非很可靠,主要原因為實際CAD 模型相當複雜且多變化。 為提供塑膠薄殼件較佳的網格建構,對於薄殼內部主要的幾何特徵,需要進行辨識與分解。薄 殼內部的幾何特徵常由多種特徵組合,需要針對不同種類特徵發展辨識與分解技術,對個別特徵應 用適當的網格化技術以建立網格。在網格建構中最重要的議題為在模型面上的邊規劃網格點,當某 一特徵或區域由模型中分離時,在過渡區域兩側的網格點需要一致,以便所有網格都可正確連接。 有時在過渡區域的網格點需要進行漸層分佈,以確保所有網格都可順利連接。因此,需要同時考慮 特徵辨識與特徵分離的規劃,並且也需要計算各區域網格化所需的資料。 本計畫的目的乃針對塑膠射出薄殼件常見的幾何特徵,包括肋、管、柱、軸套、凸起物、模型 本體等,發展特徵辨識與特徵分離的技術,並且分析與計算這些特徵之幾何與拓普資料。所有分解 的特徵採用混合六面體與稜柱體的方式建構網格。當某一特徵分解時,也需計算該特徵與模型本體 交界處資料,提供模型本體網格化時使用。本研究展的方法可分成以下四部分:第一、特徵辨識方法 的發展:將著重於肋、管、柱、軸套、凸起物、模型本體的辨識,也將規劃與計算各類特徵所需記錄 的資料。第二、特徵分解前處理:將著重於各類特徵分解之切割面規劃與計算,也將計算所有切割面 的資料。第三、特徵分解技術發展:將著重於每一類特徵由CAD 模型中分解的技術發展,也將計算 各特徵與模型本體交接處資料。最後,實體網格生成:本研究分析獲得的特徵資料以B-rep 模型儲存, 輸出至Moldex3D 建構實體網格,此一步驟主要用於驗證本研究所發展特徵辨識與特徵分解應用於 實際CAD 模型的實用性。 ;Thin-walled plastic injection parts are common components in many consumer products. They are usually characterized by thin shell on the main body and with many functional geometric features inside. One inherent problem of such a part in injection molding is that the outer surface tends to be shrunk locally owing to uneven thickness at the junction of the features and the main body. Mold flow analysis has been employed in injection molding for the product design, the mold design and manufacturing parameters setting, so as to improve the quality of the injection part. In mold flow analysis, it is well known that a hybrid combination of hexahedral and prism meshes are preferable to tetrahedral meshes because they are characterized by higher accuracy, convergence, and application specificity. However, they are inherently more difficult to generate because it requires the decomposition of the CAD model carefully, which is usually complex and difficult even for well-trained CAE engineers. Feature recognition has been studied for decades and several feature recognition methods are available on commercial CAD systems. Substantial efforts have been made on automatic decomposition and meshing, but, none of them is currently reliable enough for industrial applications because real CAD models are more complex and variable. To provide a better quality of meshes for thin-walled injection parts, main features on the part should be recognized and decomposed first. Since the inner face of a thin-walled part is usually composed of many types of features, it is necessary to develop specific recognition and decomposition algorithms, and then apply appropriate meshing method for each of them. The most critical issue in mesh generation is to plan nodes on all edges of a face. When a feature or a region is extracted from a model, the nodes at the transition must be consistent so that all meshes generated can be connected correctly. A gradual change of the density of nodes near the transition region might be necessary to maintain the connection of all meshes. This means that the planning of feature recognition and decomposition should be considered simultaneously, and the data used for meshing should be analyzed and computed. The purpose of this project is to develop algorithms for the recognition and decomposition of common features on thin-walled plastic parts, including rib, tube, column, boss, extrusion, and model base, and study the geometric and topological data that should be recorded for each of the features. A hybrid meshes composed of prism and hexahedron are used for all features extracted. When a feature is extracted, the transition data between this feature and the model base is also recorded, which is needed when the model base is meshed. The proposed method can be divided into four parts. First, development of feature recognition algorithms: we focus on the recognition of rib, tube, boss, column, extrusion and model base. The data required for each type of features are planned and computed. Second, preprocess of feature decomposition: we focus on the planning and computation of all slicing faces for each of the features. The data for each slicing face are computed. Third, development of feature decomposition algorithms: we focus on the decomposition of each feature form the model. The transition data between each feature and the model base is also recorded. Finally, solid mesh generation: All feature regions obtained are saved as B-rep models and exported to Moldex3D for generating solid meshes. It is used to verify the feasibility of the proposed feature recognition and decomposition method to deal with real CAD models.
    關聯: 財團法人國家實驗研究院科技政策研究與資訊中心
    顯示於類別:[機械工程學系] 研究計畫

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