Short-Term Wind Power Prediction Based on MVMD-AVOA-CNN-LSTM-AM
International Transactions on Electrical Energy SystemsDue to the intermittent and fluctuating nature of wind power generation, it is difficult to achieve the desired prediction accuracy for wind power prediction.
Xiqing Zang +3 more
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A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy [PDF]
Shock and Vibration, 2020 Vibration signal, as an important means for diesel engine condition detection and fault diagnosis, has attracted attention for many years. In traditional vibration signal analysis, most processing methods are for single-channel data.
Cheng Gu +3 more
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A Novel EMG-Based Hand Gesture Recognition Framework Based on Multivariate Variational Mode Decomposition [PDF]
Sensors, 2021 Surface electromyography (sEMG) is a kind of biological signal that records muscle activity noninvasively, which is of great significance in advanced human-computer interaction, prosthetic control, clinical therapy, and biomechanics.
Kun Yang +4 more
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Smart Sensor-Based Monitoring Technology for Machinery Fault Detection [PDF]
SensorsRotary machines commonly use rolling element bearings to support rotation of the shafts. Most machine performance imperfections are related to bearing defects.
Ming Zhang, Xing Xing, Wilson Wang
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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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A High-Precision Short-Term Photovoltaic Power Forecasting Model Based on Multivariate Variational Mode Decomposition and Gated Recurrent Unit-Attention with Crested Porcupine Optimizer-Enhanced Vector Weighted Average Algorithm [PDF]
SensorsThe increasing reliance on renewable energy sources, such as photovoltaic (PV) systems, is pivotal for achieving sustainable development and addressing global energy challenges. However, short-term power forecasting for distributed PV systems often faces
Jinxiang Pian, Xianliang Chen
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A Field Verification Denoising Method for Partial Discharge Ultrasonic Sensors Based on IPSO-Optimated Multivariate Variational Mode Decomposition Combined with Improved Wavelet Transforms [PDF]
SensorsField verification of contact-type ultrasonic sensors enables rapid evaluation of their sensitivity performance, thereby ensuring the accuracy of partial discharge (PD) ultrasonic monitoring results.
Tienan Cao +8 more
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Fault Diagnosis of Wind Turbine Gearbox Based on Improved Multivariate Variational Mode Decomposition and Ensemble Refined Composite Multivariate Multiscale Dispersion Entropy [PDF]
EntropyWind turbine planetary gearboxes have complex structures and operating environments, which makes it difficult to extract fault features effectively. In addition, it is difficult to achieve efficient fault diagnosis.
Xin Xia, Xiaolu Wang, Weilin Chen
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Three-point bending damage detection of GFRP composites doped with graphene oxide by acoustic emission technology [PDF]
iScience, 2023 Summary: The incorporation of graphene oxide (GO) into composite materials can modulate their overall performance. To enhance the performance of acoustic emission (AE) signals, 3% GO was incorporated into glass fiber-reinforced polymer (GFRP) composites,
Wangyong Shu +4 more
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Fault feature extraction method for rolling bearing based on MVMD and complex Fourier transform [PDF]
Journal of Vibroengineering, 2022 The vibration signals caused by rolling bearing defects in different directions may be different, and the fault diagnosis based on single channel vibration signals may be made incorrectly, and the observation results may be understood wrong. To avoid it, a new rolling bearing fault feature extraction method based on multivariate variational mode ...
Chuanjin Huang, Haijun Song
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