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Time Series Multiple Channel Convolutional Neural Network with Attention-Based Long Short-Term Memory for Predicting Bearing Remaining Useful Life

机译：时间序列多通道卷积神经网络，具有基于关注的长短期记忆，用于预测轴承剩余的使用寿命

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Jehn-Ruey Jiang; Juei-En Lee; Yi-Ming Zeng;
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1. Predicting remaining useful life of rolling bearings based on deep feature representation and long short-term memory neural network: [J] . Wentao Mao, Jianliang He, Jiamei Tang, Advances in Mechanical Engineering . 2018,第12期

机译：基于深度特征表示和长短期记忆神经网络预测滚动轴承的剩余使用寿命：
2. Convolution and Long Short-Term Memory Hybrid Deep Neural Networks for Remaining Useful Life Prognostics [J] . Zhengmin Kong?, Yande Cui, Zhou Xia?, Applied Sciences . 2019,第19期

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3. TIME SERIES LAND COVER CLASSIFICATION BASED ON SEMI-SUPERVISED CONVOLUTIONAL LONG SHORT-TERM MEMORY NEURAL NETWORKS [J] . S. Jing, T. Chao International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences . 2020,第4期

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4. Remaining Useful Life Estimation With Parallel Convolutional Neural Networks On Predictive Maintenance Applications [C] . Adem Avci, Nurettin Acir Signal Processing and Communications Applications Conference . 2020

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5. A study of neural networks and multiple neural networks in making short-term and long-term time-series prediction of petroleum production and gas consumption. [D] . Nguyen, Hanh Hong. 2003

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6. Time Series Multiple Channel Convolutional Neural Network with Attention-Based Long Short-Term Memory for Predicting Bearing Remaining Useful Life [O] . Jehn-Ruey Jiang, Juei-En Lee, Yi-Ming Zeng 2020

机译：时间序列多通道卷积神经网络具有基于注意力的长短期记忆可预测轴承剩余使用寿命
7. Real-Time Bearing Remaining Useful Life Estimation Based on the Frozen Convolutional and Activated Memory Neural Network [O] . Zesheng Chen, Xiaotong Tu, Yue Hu, 2019

机译：基于冷冻卷积和激活内存神经网络的实时轴承剩余使用寿命估计

Time Series Multiple Channel Convolutional Neural Network with Attention-Based Long Short-Term Memory for Predicting Bearing Remaining Useful Life

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