涡轮叶片气膜孔几何特征识别方法OA
Identification Method for Extracting the Geometric Features of Film Cooling Holes on Turbine Blades
为了提升高热负荷涡轮叶片的服役可靠性与冷却系统设计精度,亟须构建具备高分辨率与高效率的气膜孔几何参数检测方法.针对现有检测手段在复杂孔群形貌识别与三维特征重建方面的技术瓶颈,本文提出一种针对涡轮叶片气膜孔三维点云的几何特征参数识别方法,以及针对粗糙的气膜孔提取最小圆通道的方法.基于本文提出的算法,利用不完整的气膜孔点云数据获取轴线和孔径参数,并得到粗糙圆孔内的最小圆通道的直径.通过与圆柱模拟气膜孔的设计值进行比较,验证了本文算法的精度和鲁棒性.结果表明,本文对圆柱孔轴线特征识别误差为0.1255°,孔径识别误差为1.317％,较现有算法在复杂工况下的检测精度有显著提升,为气膜孔数字化检测技术的工程应用提供了有效的解决方案.
The geometric accuracy of the film cooling holes directly determines the cooling efficiency of the turbine blades.The current digital inspection methods for the film cooling holes still need to be further improved in terms of accuracy and efficiency.To address this issue,this paper proposes a geometric feature parameter identification method for the 3D point cloud of turbine blade film cooling holes and a method to extract the minimum circular channel for rough film cooling holes.The proposed algorithm facilitates the utilization of incomplete film cooling hole point cloud data to derive the axis and hole diameter parameters,in addition to the diameter of the smallest circular channel within the rough circular hole.The efficacy of the proposed algorithm is substantiated through a comparative analysis with design values of cylindrical simulated film cooling holes.The findings indicate that the error of the proposed algorithm is 0.1255° for the recognition of the axial features of cylindrical holes and 1.317％for the recognition of the hole diameter.This represents a substantial enhancement in detection accuracy under complex working conditions when compared with existing algorithms.The algorithm provides an effective solution for the engineering application of digital detection technology for film cooling holes.
张霄昕;董一巍;徐微雨;李迪;庞长涛;刘松
厦门大学,福建厦门 361005||四川天府新区厦大创新研究院,四川成都 610213厦门大学,福建厦门 361005||四川天府新区厦大创新研究院,四川成都 610213||华中科技大学智能制造装备与技术全国重点实验室,湖北武汉 430074北京航空精密机械研究所精密制造技术航空科技重点实验室,北京 100076北京航空精密机械研究所精密制造技术航空科技重点实验室,北京 100076北京航空精密机械研究所精密制造技术航空科技重点实验室,北京 100076中国航发四川涡轮燃气研究院,四川成都 610213
航空航天
涡轮叶片气膜孔测量三维点云几何特征识别
turbine bladefilm cooling holemeasurement3D point cloudgeometric feature recognition
《航空科学技术》 2026 (2)
42-50,9
国家自然科学基金(52475491,51705440)福建省自然科学基金(2019J01044)航空科学基金(20170368001,20230003068002,20240003068001)华中科技大学智能制造装备与技术全国重点实验室开放基金(IMETKF2024013)中国科学院-福建省STS项目(2022T3071)厦门大学四川研究院开放课题(202401YB002)四川省科技计划项目(2025YFHZ0039,2026YFHZ0284) National Natural Science Foundation of China(52475491,51705440)Natural Science Foundation of Fujian Prov-ince,China(2019J01044)Aeronautical Science Foundation of China(20170368001,20230003068002,20240003068001)Founda-tion of State Key Laboratory of Intelligent Manufacturing Equipment and Technology(IMETKF2024013)CAS-Fujian STS Project(2022T3071)Open Project of Sichuan Institute of Xiamen University(202401YB002)Sichuan Science and Technology Program(2025YFHZ0039,2026YFHZ0284)
评论