Results 71 to 80 of about 11,244 (210)

Online Bearing Remaining Useful Life Prediction Based on a Novel Degradation Indicator and Convolutional Neural Networks

, 2018
In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability
Cheng, Cheng, Ding, Han, Ma, Guijun, Sun, Mingyang, Teng, Fei, Yuan, Ye, Zhang, Yong   +6 more
core   +1 more source

Quantitative Dual‐Energy CT Perfusion Versus SPECT/CT V/Q Scintigraphy for Preoperative Lung Function Assessment: A Prospective Cohort Study

Journal of Medical Imaging and Radiation Oncology, EarlyView.
ABSTRACT Introduction Accurate preoperative physiological assessment is critical for high‐risk patients undergoing lung resection to predict postoperative lung function. This study compared quantitative dual‐energy CT (DECT) perfusion with SPECT/CT for lobar perfusion mapping in an at‐risk oncological cohort.
Jack Edward Liu, Kane Nicholls, Audree So, Siddharth M. Kulkarni, Anthony Tu Tran, Stephen A. Barnett, Amy Baker   +6 more
wiley   +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

Artificial Intelligence in the Food Industry: Transforming Safety, Efficiency, and Sustainability From Farm to Fork

eFood, Volume 7, Issue 3, June 2026.
This review synthesizes AI advancements in food systems, leveraging machine learning, computer vision, robotics, and IoT for 96%–100% accurate quality inspection, 30% reduced downtime, and enhanced traceability from farm to fork. It highlights transformative potential in sustainability and SDGs while addressing data, ethical, and scalability challenges
Muhammad Waqar, Mariyam Shahid, Manat Chaijan, Worawan Panpipat, Djilali Benabdelmoumene, Ahmed Mediani, Abdifetah Ibrahim Omar, Sabrin R. M. Ibrahim, Qudrat Ullah, Temesgen Anjulo Ageru   +9 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

Building a Digital Twin for Material Testing: Model Reduction and Data Assimilation

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT The rapid advancement of industrial technologies, data collection, and handling methods has paved the way for the widespread adoption of digital twins (DTs) in engineering, enabling seamless integration between physical systems and their virtual counterparts.
Rubén Aylwin, Nina Beranek, Gajendra Babu Budihala, Matthias Mettenleiter, Goksu Oruc, Karsten Urban   +5 more
wiley   +1 more source

Accelerated Aging System for Prognostics of Power Semiconductor Devices [PDF]

, 2010
Prognostics is an engineering discipline that focuses on estimation of the health state of a component and the prediction of its remaining useful life (RUL) before failure.
Celaya, Jose R., Saha, Sankalita, Vashchenko, Vladislav, Wysocki, Philip   +3 more
core   +1 more source

An Interpretable TCN– Transformer Framework for Lithium‐Ion Battery State of Health Estimation Using SHAP Analysis

Quality and Reliability Engineering International, Volume 42, Issue 4, Page 1426-1442, June 2026.
ABSTRACT Accurate state of health (SOH) estimation of Li‐ion batteries is essential for ensuring safety, reliability, and prolonging battery lifespan in energy storage systems and electric vehicles. This study proposes a hybrid temporal convolutional network (TCN)–transformer framework that effectively captures both short‐term temporal dynamics and ...
Fusen Guo, Zhibo Zhang, Xuzhe Ma, Lin Li, Hailing Zhou, Chaojie Li, Huadong Mo   +6 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