基于神经网络的重型柴油机机油品质监测方法  

Means of Luboil Quality Monitoring of Heavy-duty Diesel Engine Based on Neural Network

作　　者：赵文柱[1] 赵永东[1] 王宪成[1] 和穆[1] 罗晋 

机构地区：[1]装甲兵工程学院机械工程系 [2]95830 部队

出　　处：《装甲兵工程学院学报》2013年第6期31-35,共5页Journal of Academy of Armored Force Engineering

基　　金：军队科研计划项目

摘　　要：针对某重型柴油机机油品质劣化快、规律不清的问题,通过4组含有不同体积分数柴油的机油黏温特性的测量,分析了机油中不同体积分数的柴油对机油品质劣化的影响规律,采用指数函数拟合出相应的黏温公式,利用径向基神经网络建立了机油品质实车监测模型,通过实车验证表明:该模型能够准确计算出机油中混入柴油的体积分数,实时反映机油品质状况,为机油按质换油提供了一种有效的监测手段。At the present time,the fast degradation and unclear changing law of luboil quality of some heavy-duty diesel engine is an urgent problem.In this paper,the effect law of diesel content on the engine luboil quality is analyzed by measuring four groups of engine luboil viscosity-temperature data including different volume percentage of diesel.And the corresponding viscosity-temperature formula is deduced using exponential function.What's more,the monitoring model of real vehicles is built with radialbasis function neural network.Real vehicle experiments prove that,the model established in this paper can not only calculate the volume percentage of diesel mixed in engine luboil,but also reflect the engine luboil quality in real time,which can provide an effective monitoring means for the replacement of luboil in accordance with the quality.

关 键 词：机油品质 监测 神经网络 

分 类 号：TK428.9[动力工程及工程热物理—动力机械及工程]