BP神经网络在涡轴发动机参数换算中的应用
投稿时间:2020-09-11  修订日期:2020-09-18  点此下载全文
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作者单位E-mail
陈江明 中国航发湖南动力机械研究所 jiangming_chen@126.com 
贾锐 中国航发湖南动力机械研究所 jiarui71@163.com 
段辉 中国航发湖南动力机械研究所  
中文摘要:带自由涡轮的涡轴发动机的参数换算关系难以表达为具体的函数形式。将神经网络应用于发动机参数换算,针对功率、燃气温度、燃油流量和空气流量换算分别建立四个BP神经网络模型。使用经过预处理的试验数据,对四个BP神经网络进行了训练。将训练后的神经网络应用于两台发动机的性能参数换算,与传统换算公式相比:BP神经网络换算模型的精度和稳定性都远高于传统换算公式。该方法拓展了神经网络的应用范围,有良好的工程价值,可供其它型号航空发动机研制参考。
中文关键词:BP神经网络  航空发动机  参数换算  精度  稳定性
 
Application of BP Neural Network in Performance Parameter Correction of Turboshaft Engine
Abstract:The correction function for a turboshaft engine with free turbine is difficult to be given directly with specific form. The neural network is applied to engine parameter correction and four BP neural network models for the correction of power, gas temperature, fuel flow and air flow were established. Then these BP neural networks were trained using pre-processed data. Finally, trained neural networks were applied to two engines. The results show that, the precision and stability of BP neural network models were much higher than that of traditional correction formulas. The method is proved to expand the application scope of neural network and have a bright prospect in engineering practice, which can give references for other aero engines development.
keywords:BP neural network  aero engine  parameter correction  precision  stability
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