Middendorf Philipp, Blümel Richard, Hinz Lennart, Raatz Annika, Kästner Markus, Reithmeier Eduard
Institute of Measurement and Automatic Control, An der Universität 1, 30823 Garbsen, Germany.
Institute of Assembly Technology, 30823 Garbsen, Germany.
Sensors (Basel). 2022 Jul 11;22(14):5191. doi: 10.3390/s22145191.
Inspection in confined spaces and difficult-to-access machines is a challenging quality assurance task and particularly difficult to quantify and automate. Using the example of aero engine inspection, an approach for the high-precision inspection of movable turbine blades in confined spaces will be demonstrated. To assess the condition and damages of turbine blades, a borescopic inspection approach in which the pose of the turbine blades is estimated on the basis of measured point clouds is presented. By means of a feature extraction approach, film-cooling holes are identified and used to pre-align the measured point clouds to a reference geometry. Based on the segmented features of the measurement and reference geometry a RANSAC-based feature matching is applied, and a multi-stage registration process is performed. Subsequently, an initial damage assessment of the turbine blades is derived, and engine disassembly decisions can be assisted by metric geometry deviations. During engine disassembly, the blade root is exposed to high disassembly forces, which can damage the blade root and is crucial for possible repair. To check for dismantling damage, a fast inspection of the blade root is executed using the borescopic sensor.
在受限空间和难以接近的机器中进行检查是一项具有挑战性的质量保证任务，尤其难以量化和自动化。以航空发动机检查为例，将展示一种在受限空间中对可移动涡轮叶片进行高精度检查的方法。为了评估涡轮叶片的状况和损伤情况，提出了一种基于测量点云估计涡轮叶片姿态的内窥检查方法。通过特征提取方法，识别出气膜冷却孔并用于将测量点云预对齐到参考几何形状。基于测量几何形状和参考几何形状的分割特征，应用基于随机抽样一致性（RANSAC）的特征匹配，并执行多阶段配准过程。随后，得出涡轮叶片的初始损伤评估结果，并且可以通过度量几何偏差辅助发动机拆卸决策。在发动机拆卸过程中，叶片根部会受到高拆卸力的作用，这可能会损坏叶片根部，并且对于可能的修复至关重要。为了检查拆卸损伤，使用内窥传感器对叶片根部进行快速检查。
