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基于EMD-LSTM模型的APU排气温度预测

王晓燕 白贤明 宋辞 毛子荐

王晓燕, 白贤明, 宋辞, 等. 基于EMD-LSTM模型的APU排气温度预测[J]. 航空动力学报, 2024, 39(8):20220076 doi: 10.13224/j.cnki.jasp.20220076
引用本文: 王晓燕, 白贤明, 宋辞, 等. 基于EMD-LSTM模型的APU排气温度预测[J]. 航空动力学报, 2024, 39(8):20220076 doi: 10.13224/j.cnki.jasp.20220076
WANG Xiaoyan, BAI Xianming, SONG Ci, et al. APU exhaust temperature prediction based on EMD-LSTM model[J]. Journal of Aerospace Power, 2024, 39(8):20220076 doi: 10.13224/j.cnki.jasp.20220076
Citation: WANG Xiaoyan, BAI Xianming, SONG Ci, et al. APU exhaust temperature prediction based on EMD-LSTM model[J]. Journal of Aerospace Power, 2024, 39(8):20220076 doi: 10.13224/j.cnki.jasp.20220076

基于EMD-LSTM模型的APU排气温度预测

doi: 10.13224/j.cnki.jasp.20220076
详细信息
    作者简介:

    王晓燕(1975-),女,副教授,博士,主要从事机械可靠性工程及精益管理方面的研究

  • 中图分类号: V267

APU exhaust temperature prediction based on EMD-LSTM model

  • 摘要:

    为了提高排气温度(EGT)的预测精度需要减少数据的复杂性。提出一种经验模态分解(EMD)和长短期记忆神经网络(LSTM)组合方法来预测EGT。将具有时间序列特征的EGT数据,利用EMD分解成含有相同特征的本征模态函数(IMF)和残差(RES);利用LSTM模型对分量进行预测;将所有分量预测出来的结果进行叠加得到EGT的预测值。并对EMD-LSTM模型与单一的LSTM模型的预测结果进行对比分析。结果表明:前者比后者的方均根误差和平均相对误差分别降低了35%和42%。说明此模型在预测APU的EGT值上具有更好的预测精度。

     

  • 图 1  LSTM结构图

    Figure 1.  LSTM structure diagram

    图 2  EGT预测流程图

    Figure 2.  EGT prediction flow chart

    图 3  EGT数据序列

    Figure 3.  EGT data sequence

    图 4  EMD分解结果

    Figure 4.  EMD decomposition results

    图 5  各个分量LSTM预测结果

    Figure 5.  LSTM prediction results of each component

    图 6  EGT预测结果对比

    Figure 6.  Comparison of EGT prediction effect

    表  1  两种模型的评价结果

    Table  1.   Evaluation results of two models

    预测模型 RMSE MAPE/%
    LSTM 5.291 0.7
    EMD-LSTM 3.414 0.4
    下载: 导出CSV
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  • 收稿日期:  2022-02-21
  • 网络出版日期:  2024-03-20

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