Results 71 to 80 of about 1,643,808 (218)

A Real-Time Diagnostic System Using a Long Short-Term Memory Model with Signal Reshaping Technology for Ship Propellers

Sensors
This study develops a ship propeller diagnostic system to address the issue of insufficient ship maintenance capacity and enhance operational efficiency.
Sheng-Chih Shen, Chih-Chieh Chao, Hsin-Jung Huang, Yi-Ting Wang, Kun-Tse Hsieh   +4 more
doaj   +1 more source

Towards Reliable RUL Prediction

International Journal of Prognostics and Health Management
This study investigates feature selection techniques for predicting the Remaining Useful Life (RUL) of aircraft engines, addressing the persistent challenge of inaccurate predictions due to suboptimal feature selection. In this context, a robust methodology was developed to select optimal features for enhancing the model’s predictive power.
Gbore, Oluwasegun Oluwole, Shafiq, Mehak, Jain, Amit Kumar, McGlinchey, Don   +3 more
openaire   +2 more sources

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 Novel Hybrid Transformer for RUL Prediction in Predictive Maintenance for Smart Manufacturing [PDF]

EAI Endorsed Transactions on Industrial Networks and Intelligent Systems
Ensuring continuous operation and minimizing unexpected failures are critical priorities in industrial manufacturing. Due to this requirement, smart manufacturing has transformed maintenance strategies, moving from traditional scheduled approaches to predictive maintenance (PdM), which leverages actual machine health conditions.
Huu Du Nguyen, Xuan Hoang Nguyen, Bich Thuong Dao, Cong Ngon Do, Thu Huong Truong   +4 more
openaire   +1 more source

Clinical Prediction Models for Acute Kidney Injury in Neonatology—A Systematic Review and Modelling Analysis

Journal of Paediatrics and Child Health, EarlyView.
ABSTRACT Aims Acute kidney injury (AKI) affects up to one‐third of neonates admitted to neonatal intensive care units (NICUs). NICUs are highly data‐rich environments, offering opportunities to develop clinical prediction rules (CPRs) that use clinical and demographic data to estimate AKI risk.
Dermot Wildes, Lisa Corley, Deirdre O'Sullivan, David T. Selewski, Caoimhe Costigan, Atif Awan, Catherine Quinlan, Michael A. Boyle   +7 more
wiley   +1 more source

Rul prediction using moving trajectories between svm hyper planes

, 2013
A novel remaining useful life (RUL) prediction method inspired by support vector machines (SVM) classifiers is proposed. The historical instances of a system with life-time condition data are used to create a classification by SVM hyper planes.
Galar-Pascual, Diego, Tormos-Martínez, Bernardo, Huertas-Talón, José Luis, Berges-Muro, Luis, Lambán-Castillo, Ma Pilar   +4 more
core   +1 more source

Research on the Bearing Remaining Useful Life Prediction Method Based on Optimized BiLSTM

Sensors
The predictive performance of the remaining useful life (RUL) estimation model for bearings is of utmost importance, and the setting method of the bearing degradation threshold is crucial for detecting its early degradation point, as it significantly ...
Yi Zou, Wenlei Sun, Tiantian Xu, Bingkai Wang   +3 more
doaj   +1 more source

Bi‐Model Deep Learning Architectures: A Systematic Review of Fusion Strategies and Design Taxonomies

Concurrency and Computation: Practice and Experience, Volume 38, Issue 21, November 2026.
ABSTRACT Bi‐model deep learning, the coordinated use of two complementary models or modalities, has emerged as a powerful paradigm for improving predictive accuracy and robustness in complex real‐world applications. However, existing research remains scattered across domain‐specific studies, with no unified account of the architectural patterns, fusion
Jasmin Z. K. Chu, Joel C. M. Than, Colin C. L. Tan, Ngoc Dinh Tan   +3 more
wiley   +1 more source

Research progress on remaining useful life interval prediction of equipment based on deep learning

工程科学学报
Deep learning has been extensively employed for predicting the remaining useful life (RUL) of equipment owing to the powerful feature extraction ability of deep learning.
Chuang CHEN, Xianfeng LI, Jiantao SHI
doaj   +1 more source

Remaining Useful Life Prediction for Lithium-Ion Battery: A Deep Learning Approach

IEEE Access, 2018
Accurate prediction of remaining useful life (RUL) of lithium-ion battery plays an increasingly crucial role in the intelligent battery health management systems. The advances in deep learning introduce new data-driven approaches to this problem.
Lei Ren, Li Zhao, Sheng Hong, Shiqiang Zhao, Hao Wang, Lin Zhang   +5 more
doaj   +1 more source