Deep separable convolutional network for remaining useful life prediction of machinery

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2019.106330 ◽

2019 ◽

Vol 134 ◽

pp. 106330 ◽

Author(s):

Biao Wang ◽

Yaguo Lei ◽

Naipeng Li ◽

Tao Yan

Keyword(s):

Life Prediction ◽

Remaining Useful Life ◽

Convolutional Network ◽

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Remaining Useful Life Prediction of Mechanical Equipment Based on Temporal Convolutional Network and Asymmetric Loss Function

10.1109/phm-nanjing52125.2021.9613038 ◽

2021 ◽

Author(s):

Xudong Guo ◽

Pengxin Wang ◽

Huaqing Wang ◽

Jiangtao Xiao ◽

Song Liuyang

Keyword(s):

Loss Function ◽

Life Prediction ◽

Remaining Useful Life ◽

Mechanical Equipment ◽

Convolutional Network ◽

Asymmetric Loss ◽

Useful Life ◽

Asymmetric Loss Function

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Distributed Attention-Based Temporal Convolutional Network for Remaining Useful Life Prediction

IEEE Internet of Things Journal ◽

10.1109/jiot.2020.3004452 ◽

2020 ◽

pp. 1-1 ◽

Author(s):

Yan Song ◽

Shengyao Gao ◽

Yibin Li ◽

Lei Jia ◽

Qiqiang Li ◽

...

Keyword(s):

Life Prediction ◽

Remaining Useful Life ◽

Convolutional Network ◽

Distributed Attention ◽

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Remaining Useful Life Prediction Based on Improved Temporal Convolutional Network for Nuclear Power Plant Valves

Frontiers in Energy Research ◽

10.3389/fenrg.2020.584463 ◽

2020 ◽

Vol 8 ◽

Author(s):

Hang Wang ◽

Minjun Peng ◽

Renyi Xu ◽

Abiodun Ayodeji ◽

Hong Xia

Keyword(s):

Power Plant ◽

Nuclear Power Plant ◽

Life Prediction ◽

Nuclear Power ◽

Remaining Useful Life ◽

Convolutional Network ◽

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State of Health Monitoring and Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Temporal Convolutional Network

IEEE Access ◽

10.1109/access.2020.2981261 ◽

2020 ◽

Vol 8 ◽

pp. 53307-53320

Author(s):

Danhua Zhou ◽

Zhanying Li ◽

Jiali Zhu ◽

Haichuan Zhang ◽

Lin Hou

Keyword(s):

Lithium Ion Batteries ◽

Health Monitoring ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

State Of Health ◽

Convolutional Network ◽

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Hierarchical Attention Graph Convolutional Network to Fuse Multi-sensor Signals for Remaining Useful Life Prediction

Reliability Engineering & System Safety ◽

10.1016/j.ress.2021.107878 ◽

2021 ◽

pp. 107878

Author(s):

Tianfu Li ◽

Zhibin Zhao ◽

Chuang Sun ◽

Ruqiang Yan ◽

Xuefeng Chen

Keyword(s):

Life Prediction ◽

Remaining Useful Life ◽

Convolutional Network ◽

Sensor Signals ◽

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A new sorting feature-based temporal convolutional network for remaining useful life prediction of rotating machinery

Computers & Electrical Engineering ◽

10.1016/j.compeleceng.2021.107413 ◽

2021 ◽

Vol 95 ◽

pp. 107413

Author(s):

Heng Sun ◽

Min Xia ◽

Yawei Hu ◽

Siliang Lu ◽

Yongbin Liu ◽

...

Keyword(s):

Life Prediction ◽

Rotating Machinery ◽

Remaining Useful Life ◽

Convolutional Network ◽

Feature Based ◽

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Remaining Useful Life Prediction Based on Multi-scale Residual Convolutional Network for Aero-engine

2021 IEEE International Conference on Prognostics and Health Management (ICPHM) ◽

10.1109/icphm51084.2021.9486524 ◽

2021 ◽

Author(s):

Jinhui Yu ◽

Yuhuai Peng ◽

Qingxu Deng

Keyword(s):

Life Prediction ◽

Remaining Useful Life ◽

Convolutional Network ◽

Multi Scale ◽

Aero Engine ◽

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A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings

Reliability Engineering & System Safety ◽

10.1016/j.ress.2021.107813 ◽

2021 ◽

pp. 107813

Author(s):

Yudong Cao ◽

Yifei Ding ◽

Minping Jia ◽

Rushuai Tian

Keyword(s):

Life Prediction ◽

Attention Mechanism ◽

Remaining Useful Life ◽

Rolling Bearings ◽

Convolutional Network ◽

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Remaining useful life prediction for mechanical equipment based on Temporal convolutional network

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) ◽

10.1109/icemi46757.2019.9101706 ◽

2019 ◽

Author(s):

Ji Wenqiang ◽

Cheng Jian ◽

Chen Yi

Keyword(s):

Life Prediction ◽

Remaining Useful Life ◽

Mechanical Equipment ◽

Convolutional Network ◽

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Dynamic Modeling and Wear-Based Remaining Useful Life Prediction of High Power Clutch Systems

Tribology Transactions ◽

10.1080/05698190590927451 ◽

2005 ◽

Vol 48 (2) ◽

pp. 208-217 ◽

Author(s):

Matthew Watson ◽

Carl Byington ◽

Douglas Edwards ◽

Sanket Amin

Keyword(s):

Dynamic Modeling ◽

Life Prediction ◽

Remaining Useful Life ◽

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