空军工程大学学报2023，Vol.24Issue(6)：42-49,8.DOI:10.3969/j.issn.2097-1915.2023.06.006
基于双通道模型的航空发动机剩余寿命预测
Remaining Life Prediction of Aero-Engine Based on Dual-Channel Model
摘要
Abstract
Aiming at the problem of insufficient data mining depth of the Remaining Useful Life prediction model of aero-engine at this stage,a prediction method of dual-channel model is proposed.First,a dual channel network structure is constructed:channel one uses time convolutional networks,which enables the network to have a larger receptive field and computing speed through residual structure and hole convo-lution;channel 2 uses convolutional long short-term memory network to extract multidimensional spatio-temporal features and capture long-term dependencies of data.Then,the multi head attention mechanism is used to reassign weights to the features of the dual channel network.Finally,the dual channel network is used for feature fusion output to achieve prediction of the remaining life of aircraft engines.Experimen-tal validation was conducted using the turbofan engine degradation dataset and compared with other CNN-biLSTM models,multi feature attention models,multi head attention models,and CNN-GRU models mentioned in literature.The results indicate that the proposed model performs better on all three evalua-tion indicators,providing a new approach for predicting the remaining life of aircraft engines.关键词
航空发动机/寿命预测/时间卷积网络/卷积长短时间记忆网络/多头注意力机制Key words
aero engines/life prediction/temporal convolutional networks/convolutional long short-term memory network/multihead attention mechanism分类
航空航天引用本文复制引用
车鲁阳,高军伟,付惠琛..基于双通道模型的航空发动机剩余寿命预测[J].空军工程大学学报,2023,24(6):42-49,8.基金项目
山东省自然科学基金(ZR2019MF063) （ZR2019MF063）
