Results 61 to 70 of about 3,491,274 (129)

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

Structural Control and Health Monitoring, Volume 2024, Issue 1, 2024.
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, Chia-Ming Chang   +5 more
wiley   +1 more source

A customised 1D-CNN for recognition of freezing of gait in Parkinson’s disease using multivariate decomposition techniques

Open Computer Science
The freezing of gait (FoG) presents a sudden challenge in sustaining movement which becomes a common gait issue in people with later stages of Parkinson’s disease (PD). FoG often results in falls that reduces the individual’s impact on life.
Rajendran Nancy, Selvaraj Thomas G., Pennagaram Krushnakumar Kalkeseetharaman, Ashwala Ravi T., Muthu Sinnasamy Pandian Subathra   +4 more
doaj   +1 more source

A Multisource Uncertainty Fusion Reliability Evaluation Method for the Control Rod Drive Mechanism of Nuclear Power Plants

International Journal of Energy Research, Volume 2024, Issue 1, 2024.
The reliability of a pressurized water reactor power plant’s control rod drive mechanism (CRDM) is affected by many factors, such as operation states, unit performance, and dynamic environments. Multiple sources of uncertainties, including random, interval, and fuzzy, exist when analyzing the reliability of CRDMs.
Zhihu Gao, Bo Sun, Zeyu Wu, Yang Xi, Qiang Feng, Zili Wang, Yeli Zhou, Junlin Pan, Jiankun Xu, Chaofan Sun   +9 more
wiley   +1 more source

Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis [PDF]

, 2023
We propose a novel multivariate signal denoising method that performs long-range correlation analysis of multiple modes in input data by considering inherent inter-channel dependencies of the data.
Mukhtar, Sidra, Rehman, Naveed ur, Naveed, Khuram   +2 more
core   +1 more source

Bearing Fault Prediction Based on Mixed Domain Features and GWO‐SVM

Journal of Electrical and Computer Engineering, Volume 2024, Issue 1, 2024.
The rotating machinery is composed of rolling bearing connection, so the fault identification of rolling bearing is a very critical task. We propose a bearing fault identification algorithm based on grey wolf optimizer (GWO) to address the common problems of high signal noise, inability of a single indicator to accurately reflect the true state of ...
Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao, Antonio J. Marques Cardoso   +7 more
wiley   +1 more source

A Single-End Location Method for Small Current Grounding System Based on the Minimum Comprehensive Entropy Kurtosis Ratio and Morphological Gradient

Applied Sciences
Fault location technology is crucial for enhancing the efficiency of fault maintenance and ensuring the safety of the power supply in small current grounding systems.
Jiyuan Cao, Yanwen Wang, Lingjie Wu, Yongmei Zhao, Le Wang   +4 more
doaj   +1 more source

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

Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach

, 2023
Reference evapotranspiration can cause huge discrepancies in soil moisture and runoff which is responsible for uncertainties in drought warning systems.
Mehdi Jamei, Masoud Karbasi, Yong Xiang, Zheng, Zihao, Karbasi, Masoud, Zihao Zheng, Zaher Mundher Yaseen, Yaseen, Zaher Mundher, Ali, Mumtaz, Mumtaz Ali, Jamei, Mehdi, Xiang, Yong, Aitazaz Ahsan Farooque, Farooque, Aitazaz Ahsan   +13 more
core   +1 more source

Short-Term Photovoltaic Power Generation Based on MVMD Feature Extraction and Informer Model

Applied Sciences
Photovoltaic (PV) power fluctuates with weather changes, and traditional forecasting methods typically decompose the power itself to study its characteristics, ignoring the impact of multidimensional weather conditions on the power decomposition ...
Ruilin Xu, Jianyong Zheng, Fei Mei, Xie Yang, Yue Wu, Heng Zhang   +5 more
doaj   +1 more source

Probabilistic forecasting of multivariate loads based on MVMD and dynamic hybrid graph attention network

Zhejiang dianli
Accurate load forecasting is essential for ensuring the economic and reliable operation of integrated energy systems （IESs）. However， the nonstationarity， dynamically time-varying coupling， and high stochasticity of multivariate loads pose significant ...
MAO Junchen, JI Liang, LI Shengwen, CHANG Xiao, LI Botong, LI Zhenkun   +5 more
doaj   +1 more source