屈力刚,孙晨,杨野光.风洞试验模型曲面快速处理系统开发[J].精密成形工程,2024,16(9):217-224.
QU Ligang,SUN Chen,YANG Yeguang.Development of a Fast Surface Processing System for Wind Tunnel Test Models[J].Journal of Netshape Forming Engineering,2024,16(9):217-224. |
| 风洞试验模型曲面快速处理系统开发 |
| Development of a Fast Surface Processing System for Wind Tunnel Test Models |
| 投稿时间：2023-10-18 |
| DOI：10.3969/j.issn.1674-6457.2024.09.023 |
| 中文关键词: CAA二次开发 CATIA 特征识别 邻接矩阵 边界表示法 |
| 英文关键词: CAA secondary development CATIA feature recognition adjacent matrix boundary representation |
| 基金项目:辽宁省兴辽人才基金(XLYC2002086) |
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| 摘要点击次数: 162 |
| 全文下载次数: 34 |
| 中文摘要: |
| 目的 结合风洞试验模型曲面处理方法与CATIA CAA二次开发技术，开发曲面快速处理系统，以解决目前风洞试验模型曲面处理自动化程度低、重叠与搭接曲面检查困难及孔洞填充效率低等问题，提高设计效率、规范设计流程。方法 提出一种基于边界表示法的特征智能识别算法，该方法基于边界表示法提取曲面的拓扑边界，通过拓扑分析和构建加权的邻接矩阵计算目标特征，实现待处理目标的快速识别和提取。基于该算法与CAA接口开发风洞试验模型曲面快速处理系统，以交互式形式进行发布，以某导弹风洞试验模型的曲面处理作为应用实例，验证该算法和曲面快速处理系统的适用性。结果 通过实例演示，验证了该系统在重叠与搭接曲面检查、复杂孔洞填充以及批量化模型缩放的处理方面效果显著，相比于传统设计时手动曲面处理，效率提高了30倍。结论 基于边界表示法的特征智能识别算法可以快速进行目标特征的识别，曲面快速处理系统可以有效地提高设计效率，实现了风洞试验模型曲面处理的快速化和智能化。 |
| 英文摘要: |
| Combined with the surface processing method of wind tunnel test model and CATIA CAA secondary development technology, the work aims to develop a fast surface processing system to solve the problems of low automation degree of surface processing, difficult inspection of overlap and lap surfaces, and low filling efficiency of holes in current wind tunnel test models, so as to improve design efficiency and standardize design flow. An intelligent feature recognition algorithm based on boundary representation was proposed. The topological boundary of a surface was extracted based on boundary representation, and the target features were calculated by topological analysis and construction of weighted adjacency matrix to realize rapid recognition and extraction of the target. Based on this algorithm and CAA interface, the fast surface processing system of wind tunnel test model was developed and published in interactive form. The surface processing of a missile wind tunnel test model was taken as an application example to verify the applicability of the algorithm and fast surface processing system. Through the example demonstration, it was verified that the system was effective in the processing of overlap and lap surface inspection, complex hole filling and mass model scaling, and the efficiency was 30 times higher than that of manual processing in traditional design. The feature intelligent recognition algorithm based on boundary representation can quickly identify the target features, and the fast surface processing system can effectively improve the design efficiency, and realize the fast and intelligent surface processing of the wind tunnel test model. |
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