Results 71 to 80 of about 10,541,846 (196)

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

A Review of Fault‐Tolerant Control Applications in Process Equipment: Boilers, Heat Exchangers, Pumps, Turbines, and Engines for Greater Reliability

Engineering Reports, Volume 8, Issue 9, September 2026.
The article explores ways such as ultrasonic guided wave testing, infrared thermography, acoustic emission, vibration analysis, and oil analysis to prevent faults from affecting the plant and help with fault isolation. It focuses on how FTC is combined with modern tools like Artificial Intelligence (AI), the Internet of Things (IoT), sliding mode ...
Arslan Ahmed Amin, Arslan Aslam, Ansa Mubarak, Saba Waseem, Umair Shahzad   +4 more
wiley   +1 more source

Fault Diagnosis and Prediction of Remaining Useful Life (RUL) of Rolling Element Bearing : A review state of art [PDF]

Fault diagnosis of rolling element bearings is a critical aspect of machine maintenance and reliability. Bearings are extensively used in various industrial applications, and their failure can lead to costly downtime and equipment damage.
R. V. Bhandare, V. M. Phalle, P. B. Kushare, Mogal, Shyam   +3 more
core   +1 more source

Artificial intelligence–driven decoupling structure–activity relationship for lithium‐ion batteries

InfoScience, Volume 3, Issue 3, September 2026.
Artificial intelligence can efferently accelerate the high‐throughput screening of battery materials, the analysis of multiphase mechanisms, and the precise prediction of capacity and cycle life. This review systematically summarizes the applications of machine learning (ML) in decoupling the complex structure‐activity relationships of lithium‐ion ...
Tao Wang, Yuhang Meng, Tianhao Chen, Xiangfen Jiang, Yoshio Bando, Jinjue Zeng, Xuebin Wang   +6 more
wiley   +1 more source

Remaining Useful Life Estimation of MoSi₂ Heating Element in a Pusher Kiln Process

Sensors
The critical challenge of estimating the Remaining Useful Life (RUL) of MoSi2 heating elements utilized in pusher kiln processes is to enhance operational efficiency and minimize downtime in industrial applications.
Hafiz M. Irfan, Po-Hsuan Liao, Muhammad Ikhsan Taipabu, Wei Wu   +3 more
doaj   +1 more source

Wind Turbine Blade Crack Detection and Assessment in Images Using Machine Learning

Wind Energy, Volume 29, Issue 9, September 2026.
ABSTRACT As the wind energy industry matures, inspection of wind turbine blades (WTBs) is shifting from a manual process involving rope access and grading of damage, towards unmanned aerial vehicle (UAV) photography and artificial intelligence‐aided processing of data.
Callum Rothon, Nina Dethlefs, Robert C. Houseago   +2 more
wiley   +1 more source

Stage-Based Remaining Useful Life Prediction for Bearings Using GNN and Correlation-Driven Feature Extraction

Machines
Bearings are critical components in mechanical systems, and their degradation process typically exhibits distinct stages, making stage-based remaining useful life (RUL) prediction highly valuable.
Guangzhong Huang, Wenping Lei, Xinmin Dong, Dongliang Zou, Shijin Chen, Xing Dong   +5 more
doaj   +1 more source

An Improved PF Remaining Useful Life Prediction Method Based on Quantum Genetics and LSTM

IEEE Access, 2019
Remaining useful life (RUL) is the premise and basis of the equipment health management plan. As accurate as possible life prediction is of great significance to reliability and economy of equipment maintenance.
Yang Ge, Lining Sun, Jiaxin Ma
doaj   +1 more source

Time Series Domain Adaptation: A Review

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
This survey provides a comprehensive and systematic review of TSDA methods from the perspectives of access‐privacy constraints, category‐space semantics, and source‐target topology, three orthogonal axes that unify existing approaches within a common taxonomy.
M. T. Furqon, Mahardhika Pratama, Wisnu Jatmiko   +2 more
wiley   +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