Results 31 to 40 of about 7,212 (303)
IEEE Access, 2020 The deep belief network is widely used in fault diagnosis and health management of rotating machinery. However, on the one hand, deep belief networks only tend to focus on the global information of bearing vibration, ignoring local information.
Chao Zhang +5 more
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ROTOR FAULT FEATURE EXTRACTION METHOD USING MVMD AND IEDPE (MT)
Jixie qiangdu, 2023 To accurately characterize the different operating states of the rotor system, a modified variational mode decomposition（MVMD） combined with instantaneous energy distribution permutation entropy（IEDPE） is proposed to quantify and extract rotor fault ...
WU YaoChun +6 more
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IEEE Access, 2020 This paper describes a novel multichannel signal denoising approach based on multivariate variational mode decomposition (MVMD). MVMD is the extended version of the variational mode decomposition (VMD) algorithm for multichannel data sets.
Peipei Cao, Huali Wang, Kaijie Zhou
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Zhejiang dianli, 2022 In view of the difficulty in signal identification in vibration acoustic detection of post porcelain insulators， A BP （backpropagation） neural network identification method based on variational mode decomposition （VMD） is proposed to identify the damage ...
LUO Hongjian +3 more
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Heart Rate Estimation Considering Reconstructed Signal Features Based on Variational Mode Decomposition via Multiple-Input Multiple-Output Frequency Modulated Continuous Wave Radar. [PDF]
Sensors (Basel)Nakatani S, Bouazizi M, Ohtsuki T.
europepmc +3 more sources
Short-term traffic flow prediction: An ensemble machine learning approach
Alexandria Engineering Journal, 2023 The inconvenience of travel, air pollution and consequent economic losses caused by traffic congestion have seriously restricted the healthy and sustainable development of cities in China.
Guowen Dai, Jinjun Tang, Wang Luo
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Frontiers in Energy Research, 2023 With the emergence of various new power systems, accurate wind power prediction plays a critical role in their safety and stability. However, due to the historical wind power data with few samples, it is difficult to ensure the accuracy of power system ...
Hang He, Hang He, Manman Yuan
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Radar fingerprint extraction via variational mode decomposition [PDF]
2017 25th Signal Processing and Communications Applications Conference (SIU), 2017 In iMs paper, a novel method for extracting radar fingerprint using the unintentional modulation on radar signals is proposed. Proposed technique decomposes the unintentional modulations into its components using Variational Mode Decomposition (VMD) technique. Then, features that characterize each component are calculated.
Gök, Gökhan +2 more
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Harmonic Detection for Power Grids Using Adaptive Variational Mode Decomposition
Energies, 2019 The harmonic pollution problem in power grids has become increasingly prominent with the large-scale application of power electronic equipment, nonlinear loads, and renewable energy.
Guowei Cai +4 more
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Variational Mode Decomposition Features for Heartbeat Classification
Computing in Cardiology Conference (CinC), 2018 In software applications to analyse Heart Rate Variability (HRV) or to detect heart rhythm disorders, automatic heartbeat classification is a first step to expose abnormalities in the electrical activity of the heart. We propose a new morphological description of heartbeats based on Variational Mode Decomposition (VMD) to classify them as normal ...
Villa Gómez, A. +4 more
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