Results 111 to 120 of about 211 (127)

Acoustic blade damage diagnosis based on improved symplectic geometry mode decomposition

Measurement Science and Technology
Abstract Wind turbine blades are vulnerable to damage due to coupled operational loads. Acoustic detection demonstrates strong potential for blade monitoring, but its performance is often hindered by complex noise and imbalanced monitoring samples.
Siyu Zhang, Yuchen Song, Bin Chen, Yisha Shi   +3 more
openaire   +1 more source

A bearing fault diagnosis method with improved symplectic geometry mode decomposition and feature selection

Measurement Science and Technology
Abstract A rolling bearing fault diagnosis method based on improved symplectic geometry mode decomposition (SGMD) and feature selection was proposed to solve the problem of low fault identification due to the influence of noise on early bearing fault features.
Shengfan Chen, Xiaoxia Zheng
openaire   +1 more source

An adaptive threshold-selected symplectic geometry mode decomposition for application to multi-modulation complex fault signals

Measurement Science and Technology
Abstract The signals obtained from complex mechanical systems are characterized by multilevel modulation and strong noise, which can lead to difficulties in fault feature extraction. Symplectic geometry mode decomposition (SGMD) proves to be a valid approach for decomposing signals.
Zhe Lv, Congming Li, Xiaoyan Xiong, Xiangrong Wang, Wei Song, Bing Wu   +5 more
openaire   +1 more source

Residential load forecasting based on symplectic geometry mode decomposition and GRU neural network with attention mechanism

Applied Stochastic Models in Business and Industry
AbstractShort‐term residential load forecasting plays an increasingly important role in modern smart grids, with its main challenge being the high volatility and uncertainty of load curves. This article proposes a hybrid Symplectic Geometry Mode Decomposition‐Gated Recurrent Unit with Attention Mechanism (SGMD‐GRUAM) model for hourly residential load ...
Yuting Lu, Gaocai Wang, Xianfei Huang, Man Wu   +3 more
openaire   +1 more source

Energy bubble entropy guided symplectic geometry mode decomposition for rotating machinery incipient fault feature extraction

Measurement Science and Technology
Abstract Extracting incipient fault features is a critical aspect of monitoring the rotating machinery operation condition. However, existing methods based on symplectic geometry mode decomposition (SGMD) suffer from limited parameter adaptability and noise robustness. Therefore, this paper proposes an energy bubble entropy (EbEn) guided
Wenxin Jiang, Hongkai Jiang, Renhe Yao, Mingzhe Mu, Yutong Dong   +4 more
openaire   +1 more source

A Fault Diagnosis Method Based on Optimized SVDD And Multi-Symplectic Geometry Mode Decomposition for Rolling Bearings

2023 23rd International Conference on Control, Automation and Systems (ICCAS), 2023
Jianqun Zhang, Qing Zhang, Wenzong Feng, Yuantao Sun   +3 more
openaire   +1 more source

A Novel Hybrid Residential Load Forecasting Model Using Symplectic Geometry Mode Decomposition and Gru Neural Network

SSRN Electronic Journal, 2022
Yuting Lu, Gaocai Wang, Xianfei Huang, Man Wu   +3 more
openaire   +1 more source

An Improved Symplectic Geometry Mode Decomposition Method for Rolling Bearing Fault Diagnosis under Variable Speed Conditions

2021 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), 2021
Guangyao Zhang, Yi Wang, Yi Qin, Baoping Tang   +3 more
openaire   +1 more source

Symplectic Geometry Mode Decomposition-Based NMR Data Noise Attenuation

IEEE Transactions on Geoscience and Remote Sensing
Jinning Zhou, Qiaosheng Wan, Ranhong Xie, Yongjie Zhao, Lizhi Xiao, Jiangfeng Guo   +5 more
openaire   +1 more source

Symplectic geometry packet decomposition and its applications to gear fault diagnosis

Mechanical Systems and Signal Processing, 2022
Jian Cheng, Junsheng Cheng
exaly