基于改进GWO-BP神经网络的电磁线圈温升预测  

Temperature rise prediction of electromagnetic coil based on improved GWO-BP neural network

作　　者：刘文超[1,2] 刘远航 游达章 潘传林[3] LIU Wenchao;LIU Yuanhang;YOU Dazhang;PAN Chuanlin(School of Mechanical Engineering,Hubei University of Technology,Wuhan 430068,CHN;Modern Manufacturing Quality Engineering Hubei Key Laboratory,Wuhan 430068,CHN;Hubei Beichen Transmission System Technology Co.,Ltd.,Xianning 437000,CHN)

机构地区：[1]湖北工业大学机械工程学院,湖北武汉430068 [2]现代制造质量工程湖北省重点实验室,湖北武汉430068 [3]湖北北辰传动系统技术有限公司,湖北咸宁437000

出　　处：《制造技术与机床》2024年第10期73-79,共7页Manufacturing Technology & Machine Tool

基　　金：国家自然科学基金项目(51875180)。

摘　　要：针对差速器运转时电磁线圈温升的非线性与复杂性以及传统BP神经网络在预测中存在的问题,采用改进后的灰狼算法(gray wolf optimization,GWO)对BP神经网络进行优化,并根据室温环境下现场跟踪试验的数据建立以运行时间、直流电流、运转功率为输入,以某型电子锁式差速器电磁线圈连续工作8 h后的实时温度与初始环境温度间的温升差值为输出的网络预测模型。选取平均绝对误差(mean absolute error,MAE)、平均绝对百分比误差(mean absolute percentage error,MAPE)、均方误差(mean square error,MSE)作为系统评价指标,分别与传统BP网络模型、粒子群算法优化后的网络模型(PSO-BP)进行对比,结果表明GWO-BP神经网络模型具有更好的预测能力和更小的误差精度。为实现汽车轴间差速器上电磁线圈温升变化的精准预测提供了方法和思路。Aiming at the non-linearity and complexity of electromagnetic coil temperature rise during differential operation and the problems existing in the prediction of the traditional BP neural network,the improved grey wolf optimization(GWO)was adopted to optimize the BP neural network.According to the data of the field tracking experiment in a room temperature environment,a network prediction model is established,which takes running time,DC current and running power as input and the temperature rise difference between the real-time temperature and the initial ambient temperature after eight hours continuous operation of the electromagnetic coil of an electronic lock differential as output.MAE,MAPE and MSE were selected as system evaluation indexes,and compared with the traditional BP network model and the network model optimized by particle swarm optimization algorithm(PSO-BP),the results showed that GWO-BP neural network model had better prediction ability and smaller error accuracy.It provides a method and idea for realizing the accurate prediction of the temperature rise of the electromagnetic coil on the automobile axle differential.

关 键 词：灰狼算法 BP神经网络 电磁线圈 温升 

分 类 号：U463.218.4[机械工程—车辆工程]