Reliability evaluation and optimization design of cutter head structure of shield machine based on algorithm

View at publisher
Authors: Bo Ning
Cited by: 0

Abstract

In this paper, the reliability evaluation and optimization design of cutter head structure of shield machine are studied, aiming at improving the construction efficiency and safety of shield machine under complex working conditions. By introducing advanced algorithms such as finite element analysis (FEA) and genetic algorithm (GA), the stress distribution, deformation and fatigue life of the cutter head of shield machine are accurately evaluated. Taking a tunnel project as the background, the finite element model is established by using C3D10 tetrahedral element, and the fatigue life of the tool is predicted by combining the modified Miner linear cumulative damage criterion. The results show that there is stress concentration at the root of tool installation, and the service life of some tools fails to meet expectations. Based on the evaluation results, the optimization design scheme is put forward, including measures such as increasing the radius of the fillet at the root of the tool, optimizing the layout of the tool and adopting gradient materials. Multi-objective optimization of cutter structure of cutterhead is carried out by GA. The optimized cutterhead is significantly improved in structural strength, deformation control, lightweight and fatigue life, and the maximum equivalent stress is reduced by 7.7%, the total weight of cutterhead is reduced by 9.4%, and the tool life is increased by 40.2%. The verification results of the optimization scheme show that this method can effectively improve the structural reliability and comprehensive performance of the cutter head of the shield machine, and provide scientific guidance for the practical engineering application of the shield machine.

Fields of Study & Subjects

Tunneling and Rock Mechanics Geotechnical Engineering and Analysis Rock Mechanics and Modeling

Publication details

Journal / source
IET conference proceedings.
Volume
2025
Issue
34
Pages
105–109
Publication date
1 January 2026
Language
EN