基于深度学习和限幅模糊的变转速液压动力源恒流量预测方法  

Constant flow prediction method of variable speed hydraulic power source based on deep learning and limitation fuzzy

作　　者：宋震 李俊良 刘贵强 SONG Zhen;LI Jun-liang;LIU Gui-qiang(School of Mechanical Engineering,Southwest Petroleum University,Chengdu 610500,China)

机构地区：[1]西南石油大学机电工程学院,成都610500

出　　处：《吉林大学学报（工学版）》2021年第3期1106-1110,共5页Journal of Jilin University:Engineering and Technology Edition

基　　金：中国博士后科学基金项目(2017M623061)。

摘　　要：针对变转速液压动力源恒流量传统预测方法耗时长、预测误差大以及准确率低等问题,提出了基于深度学习和限幅模糊的变转速液压动力源恒流量预测方法。利用永磁同步电机数学模型、伺服控制器数学模型、齿轮泵数学模型和比例溢流阀数学模型,在深度学习的基础上,使用限幅模糊控制技术,对变转速液压动力源恒流量进行预测。结果显示:相对于传统预测方法,本文方法的预测效率和准确率得到了大幅度提高。When the conventional method is used to predict the constant flow rate of the variable speed hydraulic power source,the time used to predict the flow rate is long,the error between the predicted result and the real rate is large,and the prediction accuracy is poor.To overcome the above drawbacks,based on the deep learning and limited amplitude fuzzy,a constant flow prediction method of variable speed hydraulic power source is proposed.Using the mathematical models of permanent magnet synchronous motor,servo controller,gear pump and proportional relief valve,with the principle of deep learning,the constant flow of variable speed hydraulic power source is predicted by the limited amplitude fuzzy control technique.The experimental results show that the proposed method has higher prediction efficiency and accuracy.

关 键 词：深度学习 限幅模糊 变转速液压 流量预测 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]