Results 61 to 70 of about 10,183 (167)

A Novel Method of Pure Output Modal Identification Based on Multivariate Variational Mode Decomposition

Structural Control and Health Monitoring
This paper proposes a novel parameterized frequency‐domain modal parameter identification method, called direct modal variational mode decomposition (DMVMD), based on the multivariate variational mode decomposition (MVMD) framework and the principle of modal superposition. Under the constraint of normalized mode shapes, this paper theoretically derives
Tao Li, Rui Hou, Kangkang Zheng, Lingfeng Li, Bo Liu   +4 more
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Fault-Line Selection Method in Active Distribution Networks Based on Improved Multivariate Variational Mode Decomposition and Lightweight YOLOv10 Network

Energies
In active distribution networks (ADNs), the extensive deployment of distributed generations (DGs) heightens system nonlinearity and non-stationarity, which can weaken fault characteristics and reduce fault detection accuracy.
Sizu Hou, Wenyao Wang
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Blind Parameter Identification of MAR Model and Mutation Hybrid GWO-SCA Optimized SVM for Fault Diagnosis of Rotating Machinery

Complexity, 2019
As a crucial and widely used component in industrial fields with great complexity, the health condition of rotating machinery is directly related to production efficiency and safety. Consequently, recognizing and diagnosing rotating machine faults remain
Wenlong Fu, Jiawen Tan, Xiaoyuan Zhang, Tie Chen, Kai Wang   +4 more
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A Noise Reduction Algorithm for White Noise and Periodic Narrowband Interference Noise in Partial Discharge Signals

Applied Sciences
Partial discharge (PD) detection plays an important role in online condition monitoring of electrical equipment and power cables. However, the noise of PD measurement will significantly reduce the performance of the detection algorithm. In this paper, we
Jiyuan Cao, Yanwen Wang, Weixiong Zhu, Yihe Zhang   +3 more
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Early fault diagnosis of transformer windings based on the improved MVMD-ELM

Frontiers in Energy Research
Aiming at the problems of weak early fault characteristics of transformer windings, large noise interference and insufficient accuracy of traditional diagnostic methods, this paper proposes an early fault diagnosis method for transformer windings based ...
Qiuyang Lin, Congwei Wang, Luyi Zhang, Fengping Zhang, Zichi Zhao, Minyi Wei, Jiaqi Liu, Cheng Li   +7 more
doaj   +1 more source

Denoising of CT and MRI Images Using Decomposition-Based Curvelet Thresholding and Classical Filtering Techniques

Applied Sciences
Medical image denoising is crucial for enhancing the diagnostic accuracy of CT and MRI images. This paper presents a modular hybrid framework that combines multiscale decomposition techniques (Empirical Mode Decomposition, Variational Mode Decomposition,
Mahmoud Nasr, Krzysztof Brzostowski, Rafał Obuchowicz, Adam Piórkowski   +3 more
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Prediction of Sea Level Using Double Data Decomposition and Hybrid Deep Learning Model for Northern Territory, Australia

Mathematics
Sea level rise (SLR) attributed to the melting of ice caps and thermal expansion of seawater is of great global significance to vast populations of people residing along the world’s coastlines.
Nawin Raj, Jaishukh Murali, Lila Singh-Peterson, Nathan Downs   +3 more
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Multiscale Functional Connectivity analysis of episodic memory reconstruction

Frontiers in Cognition
Our ability to share memories constitutes a social foundation of our world. When exposed to another person's memory, individuals can mentally reconstruct the events described, even if they were not present during the related events.
Manuel Morante, Kristian Frølich, Muhammad Shahzaib, Sadia Shakil, Naveed ur Rehman   +4 more
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Innovative daily runoff prediction model integrating black-winged kite algorithm and Mamba2–Transformer architecture

Ecological Informatics
The accurate prediction of daily runoff is crucial for effective water resource management, flood prevention, and disaster mitigation. However, current runoff prediction models face dual challenges in extracting discriminative features from random and ...
Dong-mei Xu, Xiao-xue Hu, Wen-chuan Wang, Jun Wang, Can-can Shi, Hong-fei Zang   +5 more
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Fault diagnosis method using MVMD signal reconstruction and MMDE-GNDO feature extraction and MPA-SVM

Frontiers in Physics
To achieve a comprehensive and accurate diagnosis of faults in rolling bearings, a method for diagnosing rolling bearing faults has been proposed.
Min Mao, Chengjiang Zhou, Bingwei Xu, Dongjin Liao, Jingzong Yang, Shuangyao Liu, Yiqing Li, Tong Tang   +7 more
doaj   +1 more source