基于多层感知机的航空发动机压气机盘应力和温度预测
Stress and temperature prediction of aero-engine compressor disk based on multilayer perceptron
王学民 1徐敬沛 1何云1
作者信息
- 1. 中国航发四川燃气涡轮研究院,成都 610500
- 折叠
摘要
将发动机可测参数作为初始特征,利用人工神经网络技术建立航空发动机压气机盘应力和温度预测的MLP(multilayer perceptron)模型,采用BP(back propagation)神经网络算法进行训练.结果表明:该方法预测结果与传统有限元计算结果吻合较好,相对偏差均在1％以内,判定系数达到0.95以上,方均根误差均在5以内,且计算速度由小时级提升为分秒级,可为后续工程应用提供依据.
Abstract
Taking the measures parameters of the engine as the initial characteristics,the MLP(multilayer perceptron)model of aero-engine compressor disk stress and temperature prediction was established by using artificial neural network technology,and BP(back propagation)neural network algorithm was used for training.The results showed that the prediction results of this method were in good agreement with the traditional finite element calculation results.The relative deviations were all within 1％,the determination coefficients were above 0.95,and the root mean squared error was within 5.Moreover,the calculation speed increased from hour level to minute second level,providing a basis for subsequent engineering applications.
关键词
压气机轮盘/神经网络/多层感知机/应力/温度/寿命管理Key words
compressor disk/neural network/multilayer perceptron/stress/temperature/life management引用本文复制引用
出版年
2024
NETL
NSTL
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