神经网络技术用于渐开线少齿差减速器效率的研究  

Research on the Efficiency of a Retarder with Involute Gearing of Less Tooth Difference Using Neural Network

作　　者：张申林[1] 

机构地区：[1]西安公路交通大学,西安710064

出　　处：《机械科学与技术》1999年第6期991-992,共2页Mechanical Science and Technology for Aerospace Engineering

摘　　要：利用神经网络理论建立了渐开线少齿差减速器效率预测模型，通过对本模型的数据处理和试验数据的比较，证实了本模型的正确性，并就渐开线少齿差减速器的效率随输入功率的变化得出了结论。This paper successfully makes a model of artificial neural network for forecasting the efficiency of a retarder with involute gearing of less tooth diffierence. Comparison between the calculation results with experimental data shows that the forecasting values provided is accurate. On the other hand, the conclusion that the retarder efficiency varies with the input power is given in this paper.

关 键 词：神经网络 少齿差 减速器 效率 

分 类 号：TH132.46[机械工程—机械制造及自动化]