研究论文
Trend attention fully convolutional network for remaining useful life estimation
Linchuan Fan, Yi Chai, Xiaolong Chen
Ministry of Education of the People's Republic of China Chongqing University
来源Reliability Engineering & System Safety
年份2022
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计算机 / AIAnomaly Detection Techniques and Applications
Time Series Analysis and Forecasting · Machine Fault Diagnosis Techniques
参考文献 36
Review of Hybrid Prognostics Approaches for Remaining Useful Life Prediction of Engineered Systems, and an Application to Battery Life Prediction
被引 545Linxia Liao, Felix Köttig · IEEE Transactions on Reliability · 2014
Learning Deep Features for Discriminative Localization
被引 10,978Bolei Zhou, Aditya Khosla, Àgata Lapedriza · 2016
Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics
被引 873Chong Zhang, Pin Lim, A. K. Qin · IEEE Transactions on Neural Networks and Learning Systems · 2016
此处列出前 3 条
引用本文 89
Meta-learning with elastic prototypical network for fault transfer diagnosis of bearings under unstable speeds
被引 206Jingjie Luo, Haidong Shao, Jian Lin · Reliability Engineering & System Safety · 2024
Transformer-based hierarchical latent space VAE for interpretable remaining useful life prediction
被引 86Jing Tao, Pai Zheng, Liqiao Xia · Advanced Engineering Informatics · 2022
An attention-based multi-scale temporal convolutional network for remaining useful life prediction
被引 82Zhiqiang Xu, Yujie Zhang, Qiang Miao · Reliability Engineering & System Safety · 2024
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