Results 41 to 50 of about 1,643,808 (218)

A Novel Combination Neural Network Based on ConvLSTM-Transformer for Bearing Remaining Useful Life Prediction

Machines, 2022
A sensible maintenance strategy must take into account the remaining usable life (RUL) estimation to maximize equipment utilization and avoid costly unexpected breakdowns.
Feiyue Deng, Zhe Chen, Yongqiang Liu, Shaopu Yang, Rujiang Hao, Litong Lyu   +5 more
doaj   +1 more source

Prediction sketch of the RUL of batteries.

, 2016
Prediction sketch of the RUL of batteries.
Kuei-Hsiang Chao (3121788), Lingling Li (427154), Yang Xie (46489), Pengchong Wang (3121785), Yatong Zhou (3121791)   +4 more
core   +1 more source

Rolling Bearing Health Indicator Extraction and RUL Prediction Based on Multi-Scale Convolutional Autoencoder

, 2022
Rolling bearings are some of the most crucial components in rotating machinery systems. Rolling bearing failure may cause substantial economic losses and even endanger operator lives.
Qiang Zhang, Zijian Ye, Yuwei Zhao, Tianlin Niu, Siyu Shao   +4 more
core   +1 more source

Three-stage feature selection approach for deep learning-based RUL prediction methods [PDF]

, 2023
The remaining useful life (RUL) prediction plays an increasingly important role in predictive maintenance. With the development of big data and the Internet-of-Things (IoT), deep learning (DL) techniques have been widely adopted for RUL prediction ...
Wang, Youdao, Zhao, Yifan, Youdao Wang, Yifan Zhao   +3 more
core   +1 more source

A Lithium-Ion Battery Capacity and RUL Prediction Fusion Method Based on Decomposition Strategy and GRU

, 2023
To safeguard the security and dependability of battery management systems (BMS), it is essential to provide reliable forecasts of battery capacity and remaining useful life (RUL).
Chaolong Zhang, Huihan Liu, Laijin Luo, Yanmei Li   +3 more
core   +1 more source

A Two-Stage Transfer Regression Convolutional Neural Network for Bearing Remaining Useful Life Prediction

Machines, 2022
Recently, deep learning techniques have been successfully used for bearing remaining useful life (RUL) prediction. However, the degradation pattern of bearings can be much different from each other, which leads to the trained model usually not being able
Xianling Li, Kai Zhang, Weijun Li, Yi Feng, Ruonan Liu   +4 more
doaj   +1 more source

Rethinking RUL Prediction

Annual Conference of the PHM Society
Prognostics and Health Management (PHM) plays a key role in predicting the Remaining Useful Life (RUL) of systems, which is essential for enabling decision-making for Predictive Maintenance (PdM) and operations. While most research has traditionally focused on improving the accuracy of RUL predictions, this paper argues that four essential ...
Salinas-Camus, Mariana, Goebel, Kai, Eleftheroglou, Nick   +2 more
openaire   +2 more sources

Remaining Useful Lifetime (RUL): Probabilistic Predictive Model

International Journal of Prognostics and Health Management, 2021
Reliability evaluations and assurances cannot be delayed until the device (system) is fabricated and put into  operation. Reliability of an electronic product should be  conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications), by  electrical, optical ...
openaire   +3 more sources

Intrapatient tumour heterogeneity and clonal evolution in an autopsy study of metastatic salivary gland cancer

Molecular Oncology, EarlyView.
Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche, Niels J. van Ruitenbeek, Charlotte Adang, Luke O'Gorman, Pui Yuen Lee, Willemijn M. Klein, Adriana C. H. van Engen‐van Grunsven, Jack A. Schalken, Sander Bervoets, Gerald W. Verhaegh, Carla M. L. van Herpen   +10 more
wiley   +1 more source

Remaining Useful Life Prediction for Rolling Bearings Based on TCN–Transformer Networks Using Vibration Signals

Sensors
Remaining useful life (RUL) prediction plays a core role in industrial prognostics and health management (PHM), requiring data-driven models with higher predictive capability for accurate long time series prediction.
Xiaochao Jin, Yaping Ji, Shiteng Li, Kailang Lv, Jianzheng Xu, Haonan Jiang, Shengnan Fu   +6 more
doaj   +1 more source