摘要
结合试验研究结果,通过对影响机油泵供油特性影响因素的分析,建立了用于分析机油泵供油特性的BP神经网络仿真模型,并利用该模型对机油泵的温度特性、转速特性和压力特性进行了预测分析,取得良好的仿真效果。通过对不同样本训练得到的神经网络模型仿真结果和试验结果的比较分析,验证了采用正交法设计该网络模型学习样本的可行性,指出利用正交法设计学习样本时,只要位级选择适当,就可以大大减少学习样本的数量,并取得满意的预测效果。
Combining the experimental results and analysis of influencing factors on oil delivery performance of oil pump, a simulation model for analyzing oil pump delivery performance was developed based on the BP neural network. Influences from oil temperature, oil pump rotation speed and delivery pressure on delivery performance of oil pump were investigated with this model. Simulation results showed the accuracy of model. By choosing different kinds of learning samples to train neural network model, comparative analysis with experimental results were given. Designing of learning samples with orthogonal method was feasible and choosing learning samples by orthogonal method can reduce the numbers of learning samples greatly with a satisfied prediction.
出处
《内燃机学报》
EI
CAS
CSCD
北大核心
2007年第3期265-270,共6页
Transactions of Csice
基金
国家自然科学基金资助项目(50575065)
关键词
机油泵
神经网络
正交设计
学习样本
建模
Oil pump
Neural network
Orthogonal design
Learning samples
Modeling
