Results 61 to 70 of about 257 (142)

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 on improved multivariable mode decomposition and optimized Extreme Learning Machine (ELM).
Qiuyang Lin, Congwei Wang, Luyi Zhang, Fengping Zhang, Zichi Zhao, Minyi Wei, Jiaqi Liu, Cheng Li   +7 more
openaire   +1 more source

Series-Core Fusion Based Multivariate Variational Mode Decomposition for Short-Term Wind Power Prediction Using Multiple Meteorological Data

Forecasting
Accurate wind power forecasting is critical for enhancing the operational efficiency and stability of electrical power grids. Conventional single-variable signal decomposition forecasting methods ignore the coupling relationship between wind power and ...
Wentian Lu, Zhenming Lu, Wenjie Liu, Yifeng Cao   +3 more
doaj   +1 more source

Identification method for miner fatigue levels based on coupling characteristics of electromyography signals

Meikuang Anquan
To accurately identify the muscle fatigue levels of miners engaged in long-term operations in coal mines, reduce human-factor risks, and precisely prevent safety accidents caused by miner fatigue, a muscle fatigue level recognition method for miners ...
Pengjia TU, Hongmei JIN, Qi WANG, Haoran WANG   +3 more
doaj   +1 more source

Enhancing Alzheimer’s detection from EEG using MVMD and feature optimization algorithm

Journal of King Saud University – Science
Alzheimer’s disease (AD) is a neurodegenerative disorder causing progressive cognitive decline, often associated with slower electroencephalogram activity (EEG) and reduced neural synchronization. Although EEG is important for diagnosing AD, distinguishing signals from individuals with mild cognitive impairment (MCI) or AD is challenging.
Ibrahim Al-Shourbaji, Abdalla Alameen
openaire   +1 more source

Time-Domain Electromagnetic Noise Suppression Using Multivariate Variational Mode Decomposition

Remote Sensing
Noise suppression is essential in time-domain electromagnetic (TDEM) data processing and interpretation. TDEM data are typically in broadband signal, which makes it difficult to separate the signal in the whole frequency band.
Kang Xing, Shiyan Li, Zhijie Qu, Xiaojuan Zhang   +3 more
doaj   +1 more source

Short-term forecasting of building heating load based on MVMD-SSA-LSTM

Clean Energy Science and Technology
A short-term heating load forecast for buildings is a critical step in the subsequent control of energy systems, directly impacting system energy consumption. However, given that heating load and its influencing factors constitute volatile time series data, noise interference within the data significantly limits prediction accuracy and stability.
Bo Zhou, Yueyi Zhang, Chaoyang Fei, Xiuming Li, Zhigang Xie, Daohe Li   +5 more
openaire   +1 more source

DYNAMIC UNBALANCE DETECTION OF CARDAN SHATF IN HIGH-SPEED TRAIN BASED ON MODIFIED VARIATIONAL MODE DECOMPOSITION

Jixie qiangdu, 2017
Aiming at the adverse influence of penalty parameter and mode number on the VMD（ variational mode decomposition）,a newly MVMD（ modification variational mode decomposition） was proposed through the information entropy difference.
HONG JianFeng, DING JianMing, LIN JianHui, ZHENG ShuBin   +3 more
doaj  

Research on Leak Location Method of Water Supply Pipeline Based on MVMD

Computer Modeling in Engineering & Sciences, 2023
Qiansheng Fang, Haojie Wang, Chenlei Xie, Jie Chen   +3 more
openaire   +1 more source

Data-driven multivariate time series prediction of in-vehicle equipment failure rates

Journal of Engineering and Applied Science
Effectively predicting the failure rate of train-controlled on-board equipment is of great significance for rationally allocating equipment spares, drawing up maintenance plans, and reducing the occurrence of failures.
Yongfei Guo, Yonggang Chen, Haiyong Wang, Yang Liu   +3 more
doaj   +1 more source

A Predictive Model for Voltage Transformer Ratio Error Considering Load Variations

World Electric Vehicle Journal
The accuracy of voltage transformer (VT) measurements is imperative for the security and reliability of power systems and the equitability of energy transactions.
Zhenhua Li, Jiuxi Cui, Paulo R. F. Rocha, Ahmed Abu-Siada, Hongbin Li, Li Qiu   +5 more
doaj   +1 more source