Results 51 to 60 of about 226 (142)

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

Mine cable partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold [PDF]

The insulation state of the mine cable plays an important role in the stable operation of the mine power supply system. Partial discharge on-line monitoring is an important means of cable insulation state monitoring.
Jiyuan CAO, Le WANG, Peng CHEN, Weixiong ZHU, Xuan ZHOU, Yanwen WANG, Yihe ZHANG   +6 more
core   +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

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 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 robust multi-model framework for groundwater level prediction: The BFSA-MVMD-GRU-RVM model

Results in Engineering
Groundwater level prediction is critical for environmental protection and agricultural planning. Accurate predictions help manage risks associated with excessive groundwater extraction and land subsidence.
Akram Seifi, Sharareh Pourebrahim, Mohammad Ehteram, Hanieh Shabanian   +3 more
doaj   +1 more source

Enhancing machinery reliability in lunar bases: Optimized machine learning for bearing fault classification in DC power distribution networks [PDF]

In space missions and extraterrestrial habitats, ensuring the reliability of power systems is critical, particularly for DC distribution networks supporting lunar bases and space stations. These systems rely on rotating machinery such as motors and pumps,
Farooq, Umar, Guerrero, Josep M, Sadiq, Muhammad Tariq, Yousaf, Muhammad Zain   +3 more
core   +1 more source

Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis

, 2020
We propose a generic multivariate extension of detrended fluctuation analysis (DFA) that incorporates interchannel dependencies within input multichannel data to perform its long-range correlation analysis. We next demonstrate the utility of the proposed
Mukhtar, Sidra, Naveed, Khuram, Rehman, Naveed ur   +2 more
core  

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

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.
Ali, Mumtaz, Farooque, Aitazaz Ahsan, Jamei, Mehdi, Karbasi, Masoud, Xiang, Yong, Yaseen, Zaher Mundher, Zheng, Zihao   +6 more
core   +2 more sources