Results 111 to 120 of about 1,643,808 (218)

Remaining Useful Life (RUL) Prediction of Equipment in Production Lines Using Artificial Neural Networks. [PDF]

Sensors (Basel), 2021
Kang Z, Catal C, Tekinerdogan B.
europepmc   +1 more source

A Novel Remaining Useful Life Prediction Approach Combined eXtreme Gradient Boosting and Multi-Quantile Recurrent Neural Network

IEEE Access
Remaining useful life (RUL) prediction is a key technology to ensure the reliability and safety of high-end equipment. Deep learning is widely used for RUL prediction due to the excellent feature extraction ability and nonlinear fitting ability ...
Yantao Yin, Jianyin Zhao, Xiao Zhang, Ying Liu   +3 more
doaj   +1 more source

Remaining Useful Life Prediction of Rolling Bearings Based on Policy Gradient Informer Model

工程科学与技术
As a typical encoder–decoder, the transformer architecture has inherent limitations such as secondary time complexity, high memory usage, and a complex model structure; these issues can lead to lower prediction accuracy and decreased computational ...
Jiahao XIONG, Feng LI, Baoping TANG, Yongchao WANG, Ling LUO   +4 more
doaj  

Hybrid framework for Remaining Useful Life (RUL) prediction of rolling bearing faults

Remaining Useful Life (RUL) prediction is critical for preventing catastrophic failures in industrial systems, enabling efficient maintenance scheduling and resource optimization.
Arslan Shaukat, Ali Saeed, Salman Jan, Adeel M. Syed, M. Usman Akram, Muazzam A. Khan, Toqeer Ali Syed   +6 more
core   +1 more source

PEMFC RUL Prediction for Non-Stationary Time Series Based on Crossformer Model

Proton-Exchange Membrane Fuel Cells (PEMFCs), as efficient and environmentally friendly energy conversion devices, have wide application potential in areas such as transportation, mobile power, and distributed energy.
He Zeng, Ke Wang, Ning Zhou, Jianxin Zhou, Zefei Zheng   +4 more
core   +1 more source

A hybrid CNN-DNN model for battery remaining useful life RUL prediction. [PDF]

Sci Rep
Khoufi H, Bouazizi E, Khedr AE, Elshewey AM.   +3 more
europepmc   +1 more source

Fuzzy Particle Filtering Based Approach for Battery RUL Prediction With Uncertainty Reduction Strategies

This paper proposes a two-stage framework that combines uncertainty reduction and predictive modelling to enhance the accuracy of battery Remaining Useful Life (RUL) prediction.
Jung, Jason J.,, Kim, Dong Kyu,, Koo, Min,, Kim, Gwanpil,, Nalepa, Grzegorz,, Nowaczyk, Sławomir,, Jung, Jason J., Koo, Min, Nowaczyk, Slawomir, Nalepa, Grzegorz, Kim, Gwanpil, Kim, Dong Kyu   +11 more
core   +1 more source

Enabling generalizable RUL prediction for equipment: a dual-dimensional continual learning approach based on deep Gaussian process. [PDF]

Sci Rep
Xiuli L, Zifu C, Guoxin W, Shuo C.
europepmc   +1 more source

RUL Prediction Method for Lithium‐Ion Batteries Based on the SOA‐ELM Algorithm

With the rapid advancement of electrochemical energy storage power stations and electric vehicles, lithium‐ion batteries have gained widespread adoption due to their high specific energy and superior power performance.
Dong Yunchang, Zhang Jiajun, Meng Xiangdong, Li Dexin, Cao Xinyu, Zhang Haifeng, Li Gang   +6 more
core   +1 more source

RUL Prediction Based on xLSTM-Transformer Neural Network for Rolling Element Bearings Under Different Working Conditions. [PDF]

Sensors (Basel)
Jiang R, Li Z, Lu H, Mo W, Huang W, Xu M.   +5 more
europepmc   +1 more source