摘要
自动纤维铺放能有效地提高复材构件的制造效率和质量。为满足复材构件的力学性能要求及铺放质量要求,在给定曲面目标域内生成铺放轨迹时需要同时考虑转弯半径、纤维角偏差以及轨迹间距等工艺指标。现有铺放轨迹规划方法大多在对基准轨迹进行优化后,通过路径密化生成铺放轨迹。这仅能保证所生成的轨迹满足单一要求,难以整体满足多个优化目标。为实现多优化目标下的复合材料自动铺放轨迹整体规划,本文将轨迹规划问题转换成为目标域内的泛函优化问题,利用内嵌物理知识神经网络(Physics-informed neural network,PINN)实现目标函数的求解,并提取目标函数的等值线作为轨迹规划的结果。相较于现有策略,本文提出的方法能整体兼顾轨迹的方向性、可铺性以及间隙质量,为实现先进复合材料自动铺放轨迹整体规划提供新思路。
Automated fiber placement(AFP)can effectively improve the manufacturing efficiency and quality of composite components.To meet the mechanical and placement requirements,the tow paths need to be optimized in terms of turn radius,fiber angle deviations and fiber coverage in the target domain.Most of the existing planning methods are generally divided into two steps:Initial path generation and path offset,which can hardly to compromise the contradictive requirements and to satisfy multiple optimization objectives as a whole.To solve this trade-off issue,this paper defines the global metric of paths for each requirement,converts the path planning problem into a generalized function problem in the parameter domain,uses physicsinformed neural network(PINN)to solve the objective function,and finally extracts the objective function contour as the result of path planning.Compared with exiting path planning strategy,the proposed method finds global optimal tow paths with greatly improved alignment while maintaining small ply thickness variation and large turning radius,providing new paradigm for AFP path planning on complex part.
作者
林静明
许可
LIN Jingming;XU Ke(College of Mechanical&Electrical Engineering,Nanjing University of Aeronautics&Astronautics,Nanjing 210016,China)
出处
《南京航空航天大学学报》
CAS
CSCD
北大核心
2023年第5期914-923,共10页
Journal of Nanjing University of Aeronautics & Astronautics
基金
国家自然科学面上基金(52175466)。
关键词
复合材料自动铺放
轨迹规划
全局度量
内嵌物理知识神经网络
曲面参数化
automatic fiber placement
path planning
global metrics
physics-informed neural network(PINN)
surface parameterization
