Abstract

In the digital assembly of modern aircraft, to meet the higher requirements of aircraft assembly quality, the measurement data of geometric characteristics are used to replace the actual model of the parts for assembly calculation and analysis. However, when analyzing the assembly deviation of parts with complex assembly features, it is difficult to express the non-ideal model clearly by using traditional methods. At the same time, the amount of measured data is large, and the calculation efficiency is low. We propose methods to build geometric feature models based on measurement data to extract and optimize non-ideal features and reduce the data of discrete point sets to address this problem. The experimental results reveal the accuracy and computational efficiency of the geometric feature expression of the model and verify the feasibility of the proposed method.

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