浮式风机动态缆防弯器优化设计

Optimization Design of Dynamic Cable Bending Stiffener for Floating Wind Turbine

针对防弯器设计时几何结构参数多,需同时考虑刚度、寿命及质量,设计过程复杂,难以快速获得最优结构方案等问题,建立动态缆整体动力响应分析模型及防弯器有限元分析模型,以质量和疲劳寿命为优化目标,将其主要几何参数作为变量,利用BP神经网络算法实现几何参数与疲劳寿命之间的全局化映射,建立防弯器疲劳寿命预测模型,并通过多目标粒子群优化算法得到考虑寿命与质量的最优结构方案。结果表明,优化后防弯器质量和疲劳寿命有一定的提升,形成了浮式风机动态缆防弯器快速优化设计方法。研究成果可为海洋工程结构与装备的优化设计提供理论指导。

There are many geometric structure parameters in the design of bending stiffeners.It is necessary to consider the stiffness,life and quality at the same time.The design process is complicated and it is difficult to obtain the optimal structural scheme quickly.The overall dynamic response analysis model of dynamic cable and the finite element analysis model of bending stiffener are established.The quality and fatigue life are taken as the optimization objectives,and the main geometric parameters are taken as variables.The BP neural network algorithm is used to realize the global mapping between geometric parameters and fatigue life.The fatigue life prediction model of bending stiffener is established,and the optimal structural scheme considering life and quality is obtained by multi-objective particle swarm optimization algorithm.The results show that the quality and fatigue life of bending stiffener are improved after optimization,and a rapid optimization design method for dynamic cable bending stiffener of floating wind turbine is formed.The research results can provide theoretical guidance for the optimization design of ocean engineering structures and equipment.