基于ANSYS和神经网络的液压挖掘机动臂轻量化设计方法研究

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。

Research Method for Lightweight Design on Arm of Hydraulic Excavator Based on ANSYS and Neural Network

By taking a structure of the moving arm of hydraulic excavator as the research object, the mathematical model of optimal 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 optimization 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.