A Coaxial Alignment Method for Large Flange Parts Assembly Using Multiple Local Images

The large flange parts in aero-engines are usually manually assembled. Collision damage caused by assembly alignment error often occurs in the assembly process, which affects the assembly accuracy and product reliability. The machine vision-based alignment methods usually achieve the high-precision measurement of the parts by obtaining the high-resolution images of the whole parts with a combination of laser distance sensors. Hence, existing methods are high costly and inefficient. In this paper, a new alignment method based on the principle of coaxial alignment for large flange parts is proposed. The proposed method first obtains multiple high-precision image pairs from the local field of views at the fitting surfaces of flanges. The clearance and bolt holes in each image pair are then extracted via edge recognition and Hough Transformation. Two optimization models are built to calculate the translation adjustment and rotation adjustment. The optimization model 1 is built with the translation adjustments of the flange as the variables and the consistency of the clearances as the objective function. The algorithm to solve the model based on the gradient-descent method is proposed. The positions of the bolt holes in the images are subsequently adjusted based on the translation adjustment, and the rotation adjustment is calculated by solving the built optimization model 2. The experiments show that the proposed method can be applied to the assembly process of large flange parts, and the visual servo control model based on this method also has good stability.