CAE應用之混接面辨識技術發展

陳星佑(Hsing-yu Chen)

指導教授 ： 賴景義

國立中央大學/工學院/機械工程學系/碩士(2015年)

摘要

自動化特徵辨識在工業上的應用廣泛，特別是CAM以及CAE相關的應用。在CAE應用方面，為了提昇網格的品質，在建立網格時特定的幾何特徵(Hole、Fillet、Rib、Chamfer等)時常需要以人工的方式對網格進行調整，因而浪費大量時間。其中，混接面(Blend face)特徵在複雜網格建構中容易產生品質不良的狹長網格，更會造成在特徵辨識上使拓樸結構複雜化導致其他特徵辨識的困難。因此，本研究以B-rep資料結構為基礎，針對實際CAD模型中的混接面特徵，開發一自動化混接面辨識技術，並改善過去辨識中所會碰到的問題，最後提供相關資訊給相關特徵辨識與CAE分析進行後續應用。程序當中，使用者可修改閾值條件，藉由判斷各面的平滑連續性等條件篩選出混接面，並將結果加以分類。最後將以多組實際案例與商用軟體CADdoctor進行互相驗證，以證明本研究的正確性與嚴謹性。

關鍵字

CAE ； 特徵辨識 ； 混接面

並列摘要

Automatic feature recognition can be used extensively in industry both in CAE and CAM application. For CAE analysis, we always waste a lot of time to modify the mesh manually at specific features (Hole, Fillet, Rib Chamfer…) to improve the quality of meshes. Especially, blend features always cause the narrow and long mesh in mesh generating, leading to the complexity of the topology structure and the difficulty to recognize other features. Therefore, this research uses the B-rep (Boundary representation) data structure in CAD models to develop automatic blend recognition technology, for improving the identification in the parts, and for providing the interrelated information for other feature recognition and CAE analysis to conduct the follow-up uses. In this program, users are able to modify the threshold, based on determining the smooth continuity or other conditions to recognize blend feature and classify the results. Finally, several real cases are presented and compared with those by CADdoctor, commercial software, to verify the accuracy of the proposed method.

並列關鍵字

CAE ； feature recognition ； blend face

參考文獻

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