A method for optimizing assembly preload and fractal parameters driven by normal contact stiffness of a bolted joint

CN122365769APending Publication Date: 2026-07-10NORTH CHINA INST OF AEROSPACE ENG
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NORTH CHINA INST OF AEROSPACE ENG
Filing Date
2026-05-19
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing technologies suffer from high trial-and-error costs and low efficiency when improving the normal contact stiffness of bolted joints in CNC machine tools, and it is difficult to effectively control and optimize assembly preload and fractal parameters.

Method used

By establishing a mapping relationship model between the normal contact stiffness of the bolted joint and the normal force, the fractal dimension of the joint surface and the surface roughness parameters, considering the lateral contact and sliding displacement of the micro-protrusions, the assembly preload and fractal parameters are optimized, the cutting parameters are optimized using neural networks, and the bolt preload is optimized by combining the safety factor and the elastic interaction coefficient.

Benefits of technology

This technology effectively improves the normal contact stiffness of bolted joints in CNC machine tools, reduces trial-and-error costs, and enhances the connection stiffness and dynamic performance of the overall machine structure.

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Abstract

The application discloses a bolted joint normal contact stiffness driven assembly preload and fractal parameter optimization method, and belongs to the field of dynamic characteristic analysis of numerical control machine tools. The method comprises the following steps: a mapping relationship model of the normal contact stiffness of the bolted joint, the normal force, the fractal dimension of the joint surface and the surface roughness parameter is established; the normal contact stiffness under the steady state is taken as the target, and the inflection point is defined as the optimization result of the normal force, the fractal dimension of the joint surface and the surface roughness parameter; a normal force and assembly preload relationship model is established, and an assembly preload optimization method considering the safety factor is proposed; a cutting parameter and joint surface fractal dimension and surface roughness parameter relationship model based on a neural network is constructed, and the cutting parameter is optimized reversely. The application not only optimizes the assembly preload and the surface characteristic parameter from the assembly dimension, but also controls the surface characteristic parameter from the manufacturing angle, and has important engineering value for improving the normal contact stiffness of the bolted joint and the dynamic characteristics of the whole machine.
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