复合材料科学与工程Issue(4)：125-134,10.DOI:10.19936/j.cnki.2096-8000.20250428.016
CFRP基材矿用安全头盔轻量化设计与优化
Lightweight design and optimization of CFRP material mining helmet
摘要
Abstract
In order to solve the problem of excessive weight of the mining helmet,carbon fiber reinforced com-posite(CFRP)material was devised to substitute for the conventional ABS plastic to realize the lightweight design of the mining helmet.The finite element model of steel ball-helmet for collision simulation was established.The me-chanical properties of ABS and CFRP helmet shell were compared and analyzed in simulation.The strength and stiff-ness of CFRP helmet shell are superior to ABS casings,and have better protective properties.The input-output re-lationship between CFRP lamination parameters and helmet mechanical properties was simulated by BP neural net-work.And the global optimization of helmet mechanical properties was realized by particle swarm optimization algo-rithm.The optimization results indicate that the optimal lamination parameters consist ofa total number of 6 layers of CFRP,with each layer having a thickness of 0.2 mm and arranged in the following angle sequence[0/45/60/45/0/90].The collision simulation results show that the optimized CFRP helmet's top experiences a maximum deform-ation of 19.601 mm,while the headform endures a maximum force of 4.891 kN.The optimization configuration can meet the requirements of relevant national standards and achieve a lightweight design with 49.3%weight reduction compared with the ABS helmet shell.关键词
碳纤维增强复合材料/有限元分析/BP神经网络/粒子群优化/轻量化设计Key words
carbon fiber reinforced plastics/finite element analysis/BP neural network/particle swarm opti-mization/lightweight design引用本文复制引用
石林鑫,王海军,王洪磊..CFRP基材矿用安全头盔轻量化设计与优化[J].复合材料科学与工程,2025,(4):125-134,10.基金项目
煤炭科学研究总院创新创业科技专项(2021-JSYF-003) （2021-JSYF-003）
