Research on intelligent assembly method of aero-engine deep-cavity nuts based on torque-angle control

The assembly quality of high-torque nuts in the deep cavity (95mm-diameter, 800mm-deep) of aero-engine low-pressure rotors directly determines engine operational reliability. Key technical challenges include meeting the 1900–2100 N m torque requirement, ± 0.2^∘ angular accuracy demand, and stable preload control under thermal-centrifugal coupling conditions. To address these issues, this study proposes an optimization method integrating fractal contact mechanics and multi-physics coupling, and develops a visual tightening system that combines visual monitoring with servo control. Utilizing the W-M (Weierstrass-Mandelbrot) fractal function and Hertz theory, the research reveals that a surface roughness of Ra=1.6 m limits the real contact area to 12%–18% of the nominal area. A thread stiffness model is established, with the calculated overall stiffness of 5.06× 10⁵ N/mm showing a relative error of less than 1% compared to experimental results. ANSYS simulations quantify preload attenuation under thermal-centrifugal coupling conditions. The developed system achieves an angular positioning accuracy of ± 0.18^∘. Experimental verification on 20 aero-engines test dummy shows that the developed system achieves an angular positioning accuracy of ± 0.18^∘, controls preload error within ± 8% (relative to the 200 kN design preload), reduces single assembly time from 4 to 2.6 h (35% efficiency improvement), and effectively avoids part collisions during the assembly process. These results fully meet the high-reliability assembly requirements of aero-engines.