Title:
DEEP-LEARNING-BASED METHOD FOR PREDICTING RESIDUAL LIFE OF AERO-ENGINE
Document Type and Number:
WIPO Patent Application WO/2024/045377
Kind Code:
A1
Abstract:
The present invention relates to a deep-learning-based method for predicting the residual life of an aero-engine. The method comprises: acquiring data that reflects a full life cycle of an aero-engine, and obtaining the predicted residual life of the engine by means of a trained residual-life prediction model, wherein the life prediction model is constructed on the basis of deep learning. The training process of the prediction model comprises the following steps: S1, acquiring data that reflects a full life cycle of an aero-engine; S2, preprocessing the data; S3, on the basis of a random forest model, performing feature selection on the data; S4, on the basis of a Transformer model, performing feature extraction on data which has been subjected to feature selection; and S5, training an LSTM model by using data which has been subjected to feature extraction. Compared with the prior art, the present invention has the advantages of increasing the training speed, enhancing the stability of an algorithm, etc.
Inventors:
QIAO FEI (CN)
MU HANSHUO (CN)
MU HANSHUO (CN)
Application Number:
PCT/CN2022/135013
Publication Date:
March 07, 2024
Filing Date:
November 29, 2022
Export Citation:
Assignee:
UNIV TONGJI (CN)
International Classes:
G06F30/27; G06N3/04; G06N3/08; G06F119/04
Foreign References:
| CN113139278A | 2021-07-20 | |||
| CN112712209A | 2021-04-27 | |||
| CN114297918A | 2022-04-08 | |||
| CN110807257A | 2020-02-18 |
Attorney, Agent or Firm:
SHANGHAI KESHENG INTELLECTUAL PROPERTY AGENCY LTD. (CN)
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