摘要
以挖掘机动臂为研究对象,通过模态分析得到动臂各阶固有频率及振型特性,确定影响挖掘机动臂动态特性的关键固有频率。将关键固有频率作为神经网络预测目标,通过拉丁超立方抽样获取动臂固有频率神经网络训练样本,建立动臂神经网络预测模型,为液压挖掘机动臂的优化设计提供了依据。
The excavator boom is taken as research object, and its natural frequency and mode characteristics are obtained through the modal analysis. The dynamic characteristics having the influence on its critical natural frequencies is determined. The key natural frequency is used as the prediction target of the neural network. The training sample of the natural frequency prediction neural network is obtained by the Latin sampling, then, the prediction model of the boom neural network is established. The basis is provided for the optimal design of hydraulic excavator boom.
作者
黄健
林述温
林航
HUANG Jian;LIN Shuwen;LIN Hang(College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China)
出处
《机械制造与自动化》
2019年第4期100-102,115,共4页
Machine Building & Automation
关键词
模态分析
挖掘机动臂
神经网络
固有频率预测
modal analysis
excavator boom
neural network
natural frequency prediction
