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姓名 邱裕凱(Yu-kai Chiu) 查詢紙本館藏 畢業系所 機械工程學系 論文名稱 以B-rep為基礎之孔洞特徵辨識技術發展 相關論文 檔案 [Endnote RIS 格式] [Bibtex 格式] [相關文章] [文章引用] [完整記錄] [館藏目錄] [檢視] [下載]
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摘要(中) 特徵辨識的用途之一在於協助CAE分析之前置處理,事先辨識出特徵所在,方能針對不同特徵進行網格加密或簡化的動作,以便建構出合適的網格,而幾何特徵(Hole、Fillet、Rib、Chamfer等)是影響網格品質的重要因素之一,本研究將以孔洞特徵為主要辨識對象,加入混接面辨識技術,發展出過去鮮少針對具有混接面的孔洞特徵辨識技術,同時將孔洞的外形進行有系統的歸類,記錄孔洞相關資訊。本研究提出一基於B-rep模型之孔洞特徵辨識技術,期望以自動化取代傳統以肉眼辨識的方式,大幅降低數值分析上所需花費的時間。此外,將以多組實際案例來驗證孔洞辨識技術的準確性與可行性,驗證本研究的可信度。 摘要(英) The purpose of feature recognition is for the pre-processing of the CAE analysis. In the beginning of the analysis, various types of features must be recognized, in order to it can generate meshes of high density. The feature recognition can also be used to simplify the features, so as to build high quality meshes. Some geometric features, such as holes, fillets, ribs and chamfers are one of the key factors affecting the quality and accuracy in finite element analysis. This study focuses on the recognition of various kinds of holes. Particularly, a blend face recognition algorithm is added to deal with the cases with fillets at the boundary. Meanwhile, various kinds of holes are classified and the associated data for each of them are recorded. This research presents an approach based on the B-rep model for the recognition of holes. It can replace traditional manual work significantly, and hence improve the efficiency of meshes generation in the CAE analysis. Several realistic CAD models are employed to verify the feasibility of the proposed algorithm. 關鍵字(中) ★ 混接面
★ B-rep
★ 孔洞特徵辨識關鍵字(英) ★ Blend face
★ B-rep
★ Hole feature recognition論文目次 摘要 I
Abstract II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 IX
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 2
1.3 研究目的與方法 5
1.3.1 研究目的 5
1.3.2 研究方法 8
1.4 論文架構 15
第二章 孔洞外形分類與複雜度探討 16
2.1 前言 16
2.2 孔洞外形分類 17
2.2.1 盲孔與穿透孔的差異 19
2.2.2 圓孔與非圓孔的差異 19
2.2.3 是否具有混接面 19
2.2.4 典型混接面孔洞 20
2.3 特徵複雜度 20
2.4 孔洞特徵辨識架構 21
第三章 孔洞辨識演算法 23
3.1前言 23
3.2 B-rep基本結構 23
3.3 孔洞辨識流程規劃 28
3.3.1 邊屬性定義 28
3.3.2 孔洞辨識方法 30
第四章 案例驗證與討論 44
4.1 前言 44
4.2 本研究辨識結果與商用軟體CADdoctor比較 44
4.3 問題討論 53
第五章 結論與未來展望 60
5.1 結論 60
5.2未來展望 61
參考文獻 63
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指導教授 賴景義(Jiing-yih Lai) 審核日期 2014-7-24 推文 facebook plurk twitter funp google live udn HD myshare reddit netvibes friend youpush delicious baidu 網路書籤 Google bookmarks del.icio.us hemidemi myshare