These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
140 related articles for article (PubMed ID: 38894245)
1. Remaining Useful Life Prediction Based on Deep Learning: A Survey. Wu F; Wu Q; Tan Y; Xu X Sensors (Basel); 2024 May; 24(11):. PubMed ID: 38894245 [TBL] [Abstract][Full Text] [Related]
2. Joint Learning of Failure Mode Recognition and Prognostics for Degradation Processes. Wang D; Xian X; Song C IEEE Trans Autom Sci Eng; 2024 Apr; 21(2):1421-1433. PubMed ID: 38595999 [TBL] [Abstract][Full Text] [Related]
3. Deep learning-based anomaly-onset aware remaining useful life estimation of bearings. Kamat PV; Sugandhi R; Kumar S PeerJ Comput Sci; 2021; 7():e795. PubMed ID: 34909464 [TBL] [Abstract][Full Text] [Related]
4. Degradation Alignment in Remaining Useful Life Prediction Using Deep Cycle-Consistent Learning. Li X; Zhang W; Ma H; Luo Z; Li X IEEE Trans Neural Netw Learn Syst; 2022 Oct; 33(10):5480-5491. PubMed ID: 33852404 [TBL] [Abstract][Full Text] [Related]
5. Robustness testing framework for RUL prediction Deep LSTM networks. Sayah M; Guebli D; Al Masry Z; Zerhouni N ISA Trans; 2021 Jul; 113():28-38. PubMed ID: 32646591 [TBL] [Abstract][Full Text] [Related]
6. A remaining useful life estimation method based on long short-term memory and federated learning for electric vehicles in smart cities. Chen X; Chen Z; Zhang M; Wang Z; Liu M; Fu M; Wang P PeerJ Comput Sci; 2023; 9():e1652. PubMed ID: 38077580 [TBL] [Abstract][Full Text] [Related]
7. Hybrid Degradation Equipment Remaining Useful Life Prediction Oriented Parallel Simulation considering Model Soft Switch. Ge C; Zhu Y; Di Y Comput Intell Neurosci; 2019; 2019():9179870. PubMed ID: 30992700 [TBL] [Abstract][Full Text] [Related]
8. Joint optimization of degradation assessment and remaining useful life prediction for bearings with temporal convolutional auto-encoder. Ding Y; Jia M; Zhao X; Yan X; Lee CG ISA Trans; 2024 Mar; 146():451-462. PubMed ID: 38320915 [TBL] [Abstract][Full Text] [Related]
9. Remaining Useful Life Prediction Based on Adaptive SHRINKAGE Processing and Temporal Convolutional Network. Wang H; Yang J; Shi L; Wang R Sensors (Basel); 2022 Nov; 22(23):. PubMed ID: 36501790 [TBL] [Abstract][Full Text] [Related]
10. A Double-Channel Hybrid Deep Neural Network Based on CNN and BiLSTM for Remaining Useful Life Prediction. Zhao C; Huang X; Li Y; Yousaf Iqbal M Sensors (Basel); 2020 Dec; 20(24):. PubMed ID: 33322457 [TBL] [Abstract][Full Text] [Related]
11. Adaptively Lightweight Spatiotemporal Information-Extraction-Operator-Based DL Method for Aero-Engine RUL Prediction. Shi J; Gao J; Xiang S Sensors (Basel); 2023 Jul; 23(13):. PubMed ID: 37448012 [TBL] [Abstract][Full Text] [Related]
12. Ensemble deep learning with multi-objective optimization for prognosis of rotating machinery. Ma M; Sun C; Mao Z; Chen X ISA Trans; 2020 Oct; ():. PubMed ID: 34756307 [TBL] [Abstract][Full Text] [Related]
13. Method for remaining useful life prediction of rolling bearings based on deep reinforcement learning. Wang Y; Li Y; Lu H; Wang D Rev Sci Instrum; 2024 Sep; 95(9):. PubMed ID: 39283188 [TBL] [Abstract][Full Text] [Related]
14. A Cotraining-Based Semisupervised Approach for Remaining-Useful-Life Prediction of Bearings. Yan X; Xia X; Wang L; Zhang Z Sensors (Basel); 2022 Oct; 22(20):. PubMed ID: 36298116 [TBL] [Abstract][Full Text] [Related]
15. Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time-Frequency-Based Features and Deep Learning Models. Sayyad S; Kumar S; Bongale A; Kotecha K; Abraham A Sensors (Basel); 2023 Jun; 23(12):. PubMed ID: 37420825 [TBL] [Abstract][Full Text] [Related]
16. Remaining Useful Life Prediction of Rolling Bearings Based on Multi-Scale Attention Residual Network. Song L; Wu J; Wang L; Chen G; Shi Y; Liu Z Entropy (Basel); 2023 May; 25(5):. PubMed ID: 37238553 [TBL] [Abstract][Full Text] [Related]
17. Interactive Prognosis Framework Between Deep Learning and a Stochastic Process Model for Remaining Useful Life Prediction. Pei H; Si X; Li T; Zhang Z; Lei Y IEEE Trans Neural Netw Learn Syst; 2023 Sep; PP():. PubMed ID: 37725744 [TBL] [Abstract][Full Text] [Related]
18. A Lightweight Group Transformer-Based Time Series Reduction Network for Edge Intelligence and Its Application in Industrial RUL Prediction. Ren L; Wang H; Mo T; Yang LT IEEE Trans Neural Netw Learn Syst; 2024 Jan; PP():. PubMed ID: 38170656 [TBL] [Abstract][Full Text] [Related]
19. A novel gear RUL prediction method by diffusion model generation health index and attention guided multi-hierarchy LSTM. Chen X Sci Rep; 2024 Jan; 14(1):1795. PubMed ID: 38245612 [TBL] [Abstract][Full Text] [Related]
20. Degradation prediction model based on a neural network with dynamic windows. Zhang X; Xiao L; Kang J Sensors (Basel); 2015 Mar; 15(3):6996-7015. PubMed ID: 25806873 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]