Results 21 to 30 of about 106 (92)

Observability Analysis for Horizontal Axis Wind Turbines using Empirical Gramian Matrices

Journal of Physics: Conference Series, 2018
This contribution deals with the state observability and parameter identifiability analysis for nonlinear wind turbine control (WTC) systems based on empirical observability Gramian (EOG) matrices. The concepts of observability and Gramian matrices are introduced to investigate the inverse condition number (ICN) and the singular value decomposition ...
Bastian Ritter, Edwin Mora, Axel Schild
openaire   +1 more source

Advancing Diabetic Retinopathy Screening With DR‐NetFusion: A Hybrid Deep Learning Model for Enhanced Detection and Interpretability

Complexity, Volume 2026, Issue 1, 2026.
Diabetic retinopathy (DR) is one of the leading causes of preventable blindness worldwide, making timely and accurate detection crucial for effective management. This study introduces DR‐NetFusion, a novel hybrid deep learning framework designed to automate DR detection and classification.
Sunder R., V. Saravana Kumar, Kavitha M., S. Athinarayanan, Umesh Kumar Lilhore, Sarita Simaiya, Lidia Gosy Tekeste, Shimaa A. Hussien, Ehab Seif Ghith, Shonak Bansal   +9 more
wiley   +1 more source

emgr - Empirical Gramian Framework

, 2015
Empirical Gramian Framework Gramian-based model reduction is a well established method for linear state-space systems.Beyond linear systems, empirical gramians expand the scope of gramian-based methods to nonlinear systems. Furthermore, empirical gramians can also be used for parametric model order reduction, parameter identification and parameter ...
openaire   +1 more source

Attention‐Guided Coati‐Optimized GAF‐DenseNet169 for Fault Diagnosis in Electric Vehicle Drive Systems

International Journal of Energy Research, Volume 2026, Issue 1, 2026.
Reliable fault diagnosis of electric vehicle (EV) drive systems is essential for ensuring operational safety, predictive maintenance, and propulsion system reliability. Induction motors used in EV applications may be exposed to several electrical and loading abnormalities, including overload fault (OLF), overvoltage fault (OVF), undervoltage fault (UVF)
Emrah Aslan, Arnab Biswas
wiley   +1 more source

A Two‐Stage GAF‐CNN Anomaly Detection and Conditional Residual Transformer Data Imputation Method for Crack‐Width Monitoring Data

Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.
In structural health monitoring (SHM), crack‐width measurements are critical indicators of damage severity and serviceability in concrete structures. However, field data are frequently affected by sensor drift, environmental noise, and transmission errors, resulting in anomalous or missing segments that undermine safety assessments.
Congcong Fan, Youliang Ding, Kang Yang, Hoon Sohn   +3 more
wiley   +1 more source

A Comprehensive Review of Deep Transfer Learning for Intelligent Fault Diagnosis in Rotating Machines

Engineering Reports, Volume 7, Issue 11, November 2025.
This paper reviews recent advances in deep transfer learning for intelligent fault diagnosis of rotating machinery. The review categorizes existing methods into four key types, evaluates their strengths and weaknesses, and outlines current challenges and future directions to guide researchers and practitioners in selecting effective approaches for ...
Temesgen Tadesse Feisa, Hailu Shimels Gebremedhen, Fasikaw Kibrete, Dereje Engida Woldemichael, Solomon Dargie Ageze, Henok Dereje Nega   +5 more
wiley   +1 more source

A Critical Review of Pole Clustering Techniques: Common Pitfalls, Extension to MIMO and New Enhanced Variant of the Cuckoo Search Algorithm

Optimal Control Applications and Methods, Volume 46, Issue 6, Page 2501-2533, November/December 2025.
Enhanced Cuckoo Search for Model Order Reduction ABSTRACT This article presents a critical review of classical and modern pole clustering techniques for model order reduction in high‐order systems. It highlights key limitations and common pitfalls encountered in traditional approaches, especially when extended to Multi‐Input Multi‐Output (MIMO) systems.
Kamel Ben Slimane, Zied Tmar, Mongi Besbes   +2 more
wiley   +1 more source

Application of deep learning image recognition for lithium battery State of Health assessment

Energy Conversion and Economics, Volume 6, Issue 4, Page 246-255, August 2025.
Abstract Accurately estimating the State of Health (SOH) of lithium‐ion batteries is essential for ensuring their reliable operation. The constant‐current charging voltage curves of batteries at different aging levels show significant deviations.
Yanli Liu, Yu Su, Shaofan Zhang, Vladimir Terzija, Ze Cheng   +4 more
wiley   +1 more source

Damage detection for railway bridges using time‐frequency decomposition and conditional generative model

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 7, Page 959-977, 10 March 2025.
Abstract A novel damage detection model, which utilizes the spatiotemporal characteristics of the acceleration data, is proposed to assess the structural integrity of railway bridges. For this, the measured acceleration data are decomposed into several intrinsic mode functions (IMFs) using the sparse random mode decomposition model.
Jun S. Lee, Jeongjun Park, Hyun Min Kim, Robin Eunju Kim   +3 more
wiley   +1 more source

Physics‐Informed Estimation of Tidal and Subtidal Flow Fields From ADCP Repeat Transect Data

Water Resources Research, Volume 61, Issue 1, January 2025.
Abstract Acoustic Doppler current profilers (ADCPs) are a global standard in observing flow fields in rivers, estuaries and the coastal ocean. To date, it remains a labor intensive challenge to isolate mean flow fields governed by river discharge, tides and atmospheric forcing on the one hand, from small‐scale turbulence, positioning imprecision ...
H. Jongbloed, B. Vermeulen, A. J. F. Hoitink   +2 more
wiley   +1 more source