Wear Trend Forecast of Aero-engine Based on Improved RBF Neural Network

摘要：

An improved RBF neural network is proposed in this paper, which is to solve the problem of wear trend prediction accuracy for aero-engine. The number of neurons in the input layer of this improved model is determined by the ideology of equal dimensionality vectors, obtain the optimal model, then the content of iron and silicon element in the spectral can be predicted by the trained model, finally wear trend of aero-engine is determined. The simulation results show that, comparing with other models, the improved RBF neural network has great practicability and satisfied prediction accuracy in the field of wear trend.

关键词： Aero-Engine RBF Neural Network Equal Dimensionality Vectors Wear Trend forecast Spectra

作者: Liying Jiang Lei Wang Jianhui Xi Yibo Li Yan Zhang

作者单位: College of Automation, Shenyang Institute of Aeronautical Engineering, Shenyang, 110136

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 2234-2237

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）