基于BP神经网络的装甲车辆发动机使用状态评价  

Armored Vehicle Engine Service Condition Evaluation Based on BP Neural Network

作　　者：张会奇[1] 陈春良[2] 刘峻岩[1] 张咏清[1] 

机构地区：[1]装甲兵工程学院装备试用与培训大队,北京100072 [2]装甲兵工程学院技术保障工程系,北京100072

出　　处：《兵工自动化》2014年第1期32-34,共3页Ordnance Industry Automation

摘　　要：为综合预测装甲车辆发动机使用寿命,应用相关性分析优化发动机使用影响因素指标体系,定义发动机使用条件修正系数,对发动机使用状态样本数据进行分析与处理,构建BP神经网络评价模型,并利用获得的样本数据对网络进行训练和检验。结果表明:该方法能定量评价装甲车辆发动机使用状态,为预测装甲车辆发动机使用寿命提供一种新方法。In order to forecast the service life of the armored vehicle engine synthetically, the index system of the armored vehicle engine using influence factors was established and optimized by means of the relativity analysis method, define engine service condition correction coefficient, analyzed and processed engine service state sample data, established BP neural network evaluation model, and use acquired sample data to train and test network. The results show that the method can carry out quantization evaluation armored vehicle engine service state and provide a new method for forecasting the armored vehicle engine service life.

关 键 词：BP神经网络 装甲车辆发动机 使用状态 评价 

分 类 号：TJ811[兵器科学与技术—武器系统与运用工程]