【摘要】 为了克服叶片液压静力加载系统调试范围窄、响应速度慢等问题,减少各个节点的牵引力耦合,设计了基于伺服驱动技术的叶片静力加载系统,提出BP神经网络变积分PID控制算法。试验结果表明:系统加载过程中加载点牵引力能保持平稳、协调变化,具备更强的抗干扰适应性,满足风电叶片静力加载试验要求。更多还原

【Abstract】 In order to overcome the problems of narrow debugging range and slow response speed of blade static loading system based on hydraulic technology and reduce the traction coupling of each node,a blade static loading system based on servo control technology was designed,and a BP neural network variable integral PID control algorithm was proposed. The test results show that the traction force at the loading point can keep stable and coordinated changes during the loading process,and has stronger anti-interference adaptability,which meets the static loading test requirements of wind turbine blade.更多还原