摘要
以挖掘机的动臂结构为研究对象,构建考虑静态强度、刚度、轻量化等性能的优化设计数学模型,以ANSYS软件为工具,对挖掘机动臂进行了轻量化设计计算,针对轻量化设计过程中设计变量非线性的特点,建立了人工神经网络的模型,对ANSYS软件优化设计的结果进行了验证,有效地降低了动臂的质量。结果表明,用两种方法结合起来进行轻量化设计的方法合理可行,对其他的机械进行轻量化设计具有一定的指导意义。
By taking a structure of the moving arm of hydraulic excavator as the research object, the mathematical model of opti-mal design taking performance into consideration of static strength, stiffness and lightweight was built. Based on the software ANSYS software as tools, the design and calculation for lightweight on the moving arm of hydraulic excavator were completed. The model of the neural network was built by aiming at the nonlinearity characteristics of the lightweight design variable in process, so as to verify the op-timization results by ANSYS software, and the weight of the moving arm is significantly reduced. Results indicate that, this method combined with ANSYS and neural network is reasonable and feasible for lightweight design, and it has a certain guiding significance for lightweight design on other machineries.
出处
《机床与液压》
北大核心
2015年第1期136-140,共5页
Machine Tool & Hydraulics
基金
国家科技支撑计划(2012BAF02B00
2011BAF11B01)
关键词
液压挖掘机
动臂
轻量化
有限元分析
人工神经网络
Hydraulic excavator
Moving arm
Lightweight design
Finite element analysis
Artificial neural network
