论文部分内容阅读
针对因挖掘机动臂结构尺寸变量表达形式而导致的神经网络应力模型预测精度较低、模型结构复杂、通用性和泛化能力较差等问题,分析了结构尺寸变量表达形式对神经网络应力预测模型的影响,在此基础上研究基于新的结构尺寸变量表达形式下的动臂结构应力预测神经网络模型的建模方法及预测精度.研究结果表明:新的动臂结构尺寸表达形式,不仅可简化预测模型,同时还可使它获得较高的预测精度.
In view of the problems such as low accuracy of neural network stress model, complicated model structure and poor generalization and generalization ability caused by the expression of dimensional structure of excavator boom structure, this paper analyzes the effect of structural dimension variable expression on neural network stress prediction Model based on which the modeling method and prediction accuracy of the neural network model of the boom structure stress prediction based on the new structure size variable expression are studied.The results show that the new boom structure size expression form not only Simplify the prediction model, while still allowing it to obtain a higher prediction accuracy.