http://www.lw23.com/lunwen_376718487/
论文标题:基于测量数据的叶片截面特征参数提取技术研究
Research of Cross-Sectional Feature Parameter Extraction of Blade Based on Measurement Data
论文作者
论文导师 张定华,论文学位 硕士,论文专业 航空宇航制造工程
论文单位 西北工业大学,点击次数 11,论文页数 65页File Size6557K
2007-03-01
论文网 http://www.lw23.com/lunwen_376718487/
Measurement Data; Blade; Cross-Sectional Feature Parameter; Parameter Extraction; Reverse Engineering
航空发动机涡轮叶片需要承受高温、高压等恶劣的工作环境。在叶片生产过程中必须使用严格的检测手段，作全面系统的检测以确保叶片合格。航空发动机叶片的型面质量对发动机性能有着决定性的影响。由于叶片型面复杂且参数繁多，因此如何检测和评估叶片的型面质量越来越受到人们的关注。 对叶片型面质量的评估大部分着重于对特征参数的评估，叶片型面的特征参数包括：缘头半径、弦长、最大厚度等。 针对这一问题，本文研究了基于测量数据的叶片截面特征参数提取方法。根据各个特征参数的定义，详细研究了各个特征参数的提取方法。主要体现在以下几个方面： 1) 在数据预处理阶段，提供了排气孔的判断和解决方法。该方法基于数据点的单调性，自动判断出截面轮廓是否包含排气孔。根据多边形凸包的方法，确定排气孔的位置并进行处理。 2) 采用了基于多边形凸包的方法提取弦线。该方法利用叶片自身的特点，认为叶盆部分是截面轮廓中最大的凹陷部分。因而在提取凸包的过程中记录每一段凹陷部分，取首尾距离最大的凹陷部分为叶盆部分。相连凹陷部分的首尾点得到弦线，进而得到弦长和弦倾角参数。 3) 采用基于最大半径误差的方法提取缘头。由于叶片缘头半径非常小，一般的方法非常难以确定缘头的精确范围。本文提出了一种基于最大半径误差的方法，具有很好的鲁棒性。 4) 提出了一种简化的最大厚度提取方法。该方法可以在将轮廓粗略分割出叶盆叶背数据以后，快速提取出合适精度的最大厚度。 最后，基于VTK(visualization toolkit)可视化开发工具软件包和动态库技术，将上述算法开发成参数提取软件模块，并添加和完善了已有的中弧线提取功能，形成一个较为完善的叶片特征参数提取模块，并与叶片三维偏差分析、壁厚分析等模块集成了一个涡轮叶片尺寸测量软件，以满足算法验证和实际检测的需要。
Aero-engine turbine blade always works under poor environment with high temperature and high pressure. During the production process, complete detection with strict standard must be executed in order to satisfy the quality requirement. The blade profile quality has a decisive impact on the aero-engine performance. However, the complexity and variety of the blade make it difficult to inspect and evaluate the profile, so how to realize the inspection turns to be more and more important.Most of current study focuses on the evaluating of blade feature parameters, such as leading edge, trailing edge, chord line length, max thickness and so on.In this dissertation, a new method for cross-sectional feature parameter extraction of blade from the measurement data is presented. For each feature parameter, the extraction approach is detailed in the paper according to the feature definition. The main contents and contributions of this dissertation are as follows:1) At the stage of the data pre-process, the method for identifying casting vent is proposed based on the monotonicity of the profile data. The method can identify whether the vent exist or not automatically. According to the method of polygon convex, the position of vent is determined and further processing will be adopted.2) Based on polygon convex hull method, the chord line is extracted. The method depends on the geometric character of the blade, consider the pressure surface as the concavest part of the blade surface. During the extract process of convex hull, each concave section is recorded then the pressure surface is picked up which has a maximum distance of first and last point of the concave. The chord line can be got by linking those two points, the length and the angle of chord line are obtained correspondingly.3) The leading and trailing edge is extracted based on the method of maximum radius error. Because the radius of leading and trailing edge is very small, common methods can not satisfy the required precision and robustness.4) A simplification method for computing the maximum thickness of the blade is developed. This method can compute the maximum thickness quickly with proper precision when the blade is divided into convex and concave part roughly.Finally, the software model for feature parameters extraction is developed by using dynamic library technology and visualization tool kit (VTK) based on methods presented in the dissertation. Then, blade 3-deminsional deviation analysis model, thickness analysis model and mean-line extraction function are also well integrated in the software in order to satisfy the requirement of algorithm certification and fulfill the real inspect.
2009-11-27, 03:30 PM
【转帖】基于测量数据的叶片截面特征参数提取技术研究
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