Research on gross error detection of enhanced reference points for aircraft assembly tooling based on topological structure

Aiming to address the technical issue that gross errors in the measured data of enhanced reference points on aircraft assembly fixtures can reduce the accuracy of measurement field construction, this paper proposes a topology based method for gross error detection in such reference points. First, a topological model that incorporates neighborhood relationships and distance constraints among the enhanced reference points is established using both initial calibrated data and actual measured data. Using the topological information of the initially calibrated datum points as a reference, a topological model of the measured data is constructed, and the relative error distribution between the measured data and the standard data is analyzed in terms of topological information. This enables rapid and accurate identification of gross error points. Subsequently, a comparative experimental analysis of the registration of enhanced reference points is carried out to evaluate the variations in the stability of the fitted coordinate system and the registration errors before and after gross error removal. Experimental results show that gross error points increase the overall registration error of enhanced reference points through error propagation. The proposed method effectively limits the fluctuation range of registration errors after gross error points are removed and significantly improves the accuracy of coordinate system construction. This method offers reliable technical support for high precision aircraft assembly and has strong potential for engineering application.