基于支持向量机集成的导弹发动机压力预测  

Prediction of Engine Pressure of Missile Based on Support Vector Machine Ensemble

作　　者：刘丙杰[1] 冀海燕[1] 杨继锋[1] 

机构地区：[1]海军潜艇学院,山东青岛266071

出　　处：《弹箭与制导学报》2017年第1期99-102,共4页Journal of Projectiles,Rockets,Missiles and Guidance

摘　　要：针对导弹发动机压力下降难以预测的问题,根据某型导弹发动机压力实测数据,首先将实测数据进行插值处理,然后利用前5组数据为输入数据,后一组数据为预测数据,采用支持向量机集成方法对导弹发动机压力进行模型辨识,实现导弹发动机压力预测。通过对3组发动机压力实测数据进行仿真分析,发现支持向量机集成预测误差最大为0.102%,满足导弹发动机压力预测要求,对导弹发动机压力预防性维修具有重要作用。Since it was difficult to predict the pressure drop of missile engine, according to the measured data of engine pressure of a certain type of missile, the measured data were interpolated, then the five sets of data were used as input data, the latter set of data as forecast data, and the model identification of missile engine pressure was carried out by using support vector machine ensemble method to realise the prediction of missile engine pressure.Through the simulation analysis of three groups of engine pressure measured data, it was found that the maximum forcast error of support vector machine ensemble was 0.102%, which met the requirements of missile engine pressure prediction, and it played an important role in preventive maintenance of missile engine pressure.

关 键 词：支持向量机集成 导弹发动机 压力 预测 

分 类 号：TJ760.33[兵器科学与技术—武器系统与运用工程]