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螺旋桨零件的逆向建模研究

Research on Reverse Modeling of Propeller Parts
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摘要 为了减少螺旋桨零件的研发时间,降低公司成本,以螺旋桨零件为例,针对螺旋桨零件提出一种基于非接触式手持式激光扫描仪设备和三维建模软件UG的逆向建模的方法。详细介绍了使用设备扫描螺旋桨零件,以获取螺旋桨零件的数据,使用UG软件对螺旋桨零件进行逆向建模,使用Geomagic Quality软件将逆向建模完成的三维CAD模型和手持式激光扫描仪设备采集螺旋桨零件完成的STL模型进行偏差分析,根据偏差分析的结果,从设备、数据采集环境、数据采集人员、数据采集方法等方面全面考虑影响测量结果的因素,然后建立数学模型,进行不确定度评定,更加严谨地判断螺旋桨零件逆向建模完成的三维CAD模型是否合格,结果发现逆向建模完成的模型在要求范围内,验证了这种逆向建模的方法,为判断产品逆向建模提供参考。 In order to reduce the development time of propeller parts and the cost of the company, a reverse modeling method based on noncontact handheld laser scanner and 3D modeling software UG was proposed for propeller parts. The use of equipment was introduced in detail to scan propeller parts to obtain data of propeller parts, the UG software was used to reverse modeling of propeller parts, Geomagic Quality software was used to reverse modeling 3D CAD model and hand-held laser scanner equipment to collect the completed STL model of propeller parts for deviation analysis. According to the result of deviation analysis, the factors affecting the measurement results were comprehensively considered from the aspects of equipment, data acquisition environment, data acquisition personnel, data acquisition methods, etc., and then a mathematical model was established to evaluate the uncertainty. It was more rigorous to judge whether the 3D CAD model of propeller parts reverse modeling was qualified. It was found that the model of reverse modeling was within the required range, which verified this reverse modeling method and provided a reference for judging the reverse modeling of products.
作者 梁土珍 易显钦 刘华刚 Liang Tuzhen;Yi Xianqin;Liu Huagang(Guangzhou Electromechanical Technician College,Guangzhou 510435,China;Guangdong Polytechnic of Light Industry,Guangzhou 510300,China;Beijing Electronic Technology Vocational College,Beijing 100176,China)
出处 《机电工程技术》 2023年第1期67-71,共5页 Mechanical & Electrical Engineering Technology
基金 广东省普通高校青年创新人才项目(编号:2020KQNCX148) 广东省技工教育和职业培训省级教学研究课题(编号:KT2020031)。
关键词 螺旋桨 逆向建模 偏差分析 不确定度评定 数据采集 propeller reverse modeling deviation analysis uncertainty evaluation data acquisition
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