Results 101 to 110 of about 26,721 (240)

Anomaly-informed remaining useful life estimation (AIRULE) of bearing machinery using deep learning framework

MethodsX
A rolling bearing is a crucial element within rotating machinery, and its smooth operation profoundly influences the overall well-being of the equipment.
Pooja Kamat, Satish Kumar, Shruti Patil, Ketan Kotecha   +3 more
doaj   +1 more source

A New Strategy: Remaining Useful Life Prediction of Wind Power Bearings Based on Deep Learning under Data Missing Conditions

Mathematics
With its formidable nonlinear mapping capabilities, deep learning has been widely applied in bearing remaining useful life (RUL) prediction. Given that equipment in actual work is subject to numerous disturbances, the collected data tends to exhibit ...
Xuejun Li, Xu Lei, Lingli Jiang, Tongguang Yang, Zhenyu Ge   +4 more
doaj   +1 more source

A Fault-Signal-Based Generalizing Remaining Useful Life Prognostics Method for Wheel Hub Bearings

Applied Sciences, 2019
The goal of this work is to improve the generalization of remaining useful life (RUL) prognostics for wheel hub bearings. The traditional life prognostics methods assume that the data used in RUL prognostics is composed of one specific fatigue damage ...
Shixi Tang, Jinan Gu, Keming Tang, Rong Zou, Xiaohong Sun, Saad Uddin   +5 more
doaj   +1 more source

A noval RUL prediction method for rolling bearing: TcLstmNet-CBAM

Scientific Reports
Rolling bearings are pivotal components within rotating mechanical systems, and accurately predicting their remaining service life holds significant practical importance.
Qiang Liu, Zhengwei Dai, Hongxi Lai, Minghao Chen, Huiyuan Huang, Jiahui Fu, Mingxin Hou, Xiaoming Xu, Guangbin Wang, Jin Yan   +9 more
doaj   +1 more source

Remaining Useful Life Prediction Method for Electric Submersible Pump System Based on DA-RNN

Shiyou jixie
Electric submersible pump （ESP） is the main artificial lift equipment in offshore oilfields. Its operation and maintenance costs are extremely high. Once it gets out of order， it will cause losses to oilfield operations.
Yu Jifei, Ji Yuchen, Lu Xin, Sui Xianfu, Peng Jianlin, Han Guoqing, Yang Yang   +6 more
doaj   +1 more source

RUL-QMoE: Multiple Non-crossing Quantile Mixture-of-Experts for Probabilistic Remaining Useful Life Predictions of Varying Battery Materials [PDF]

Association for Artificial Intelligence 2026, Ninad Dixit, Sel Ly, Hung Nguyen, Rufan Yang   +4 more
  +6 more sources

Principle of Duality on Prognostics [PDF]

, 2014
The accurate estimation of the remaining useful life (RUL) of various components and devices used in complex systems, e.g., airplanes remain to be addressed by scientists and engineers. Currently, there area wide range of innovative proposals put forward
Alghassi, A., Alghassi, A., Amir, M., Amir, M., Kapetanios, E., Kapetanios, E., Motlagh, A.M.S., Motlagh, A.M.S., Perinpanayagam, S., Perinpanayagam, S., Samie, M., Samie, M.   +11 more
core   +2 more sources

An Improved Method for Predicting the Remaining Useful Life Using a Spatial–Temporal Feature Extraction Network With Attention Mechanism

IEEE Access
The prediction of the remaining useful life (RUL) of mechanical equipment is of vital importance to its operation and maintenance. Deep learning methods can effectively extract degradation information closely related to equipment RUL from extensive ...
Xiaojia Yan, Weige Liang, Shiyan Sun
doaj   +1 more source

Data-driven prognostic method based on Bayesian approaches for direct remaining useful life prediction.

, 2014
International audienceReliability of prognostics and health management systems (PHM) relies upon accurate understanding of critical components' degradation process to predict the remaining useful life (RUL).
Medjaher, Kamal, Mosallam, Ahmed, Zerhouni, Noureddine   +2 more
core   +3 more sources

Assessment of overall remaining useful life of lubricants by integrating oil quality and performance

Heliyon
Effective lubricant health monitoring programs are essential for extending the lifespan of both the lubricant and machinery. An accurate and reliable remaining useful life (RUL) prediction is necessary for maintenance decision support. The degradation of
Wasan Chokelarb, Pongsert Sriprom, Lasuardi Permana, Pornsawan Assawasaengrat   +3 more
doaj   +1 more source