Partial Discharge Fault Diagnosis in Power Transformers Based on SGMD Approximate Entropy and Optimized BILSTM [PDF]
EntropyPartial discharge (PD) fault diagnosis is of great importance for ensuring the safe and stable operation of power transformers. To address the issues of low accuracy in traditional PD fault diagnostic methods, this paper proposes a novel method for the ...
Haikun Shang, Jiawen Li
exaly +7 more sources
A Systematic Framework for Optimizing a Sweeping Gas Membrane Distillation (SGMD) [PDF]
Membranes, 2020 The present work has undertaken a meticulous glance on optimizing the performance of an SGMD configuration utilized a porous poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-co-HFP) membrane.
Salah S Ibrahim +2 more
exaly +9 more sources
A Novel Joint Denoising Method for Hydrophone Signal Based on Improved SGMD and WT [PDF]
SensorsUnderwater acoustic technology as an important means of exploring the oceans is receiving more attention. Denoising for underwater acoustic information in complex marine environments has become a hot research topic.
Xiaohao Wang, Kai Ni, Qⅰan Zhou
exaly +7 more sources
A Fault Diagnosis Approach for Rolling Bearing Integrated SGMD, IMSDE and Multiclass Relevance Vector Machine [PDF]
Sensors, 2020 The vibration signal induced by bearing local fault has strong nonstationary and nonlinear property, which indicates that the conventional methods are difficult to recognize bearing fault patterns effectively.
Xiaoan Yan, Minping Jia, Yan Xiaoan
exaly +8 more sources
Train Axlebox Bearing Fault Diagnosis Based on MSC–SGMD [PDF]
Sensors, 2023 Train axlebox bearings are subject to harsh service conditions, and the difficulty of diagnosing compound faults has brought greater challenges to the maintenance of high–quality train performance.
Yongliang Bai, Hai Xue, Jiangtao Chen
doaj +5 more sources
Research on the Fault Feature Extraction of Rolling Bearings Based on SGMD-CS and the AdaBoost Framework [PDF]
Energies, 2021 Symplectic geometric mode decomposition (SGMD) is a newly proposed signal processing method. Because of its superiority, it has gained more and more attention in the field of fault diagnosis. However, the similar component reorganization problem involved
Fan Li, Rong Jia, Xingqi Luo
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Gear fault diagnosis based on SGMD noise reduction and CNN
Journal of Advanced Mechanical Design, Systems and Manufacturing, 2022 Gear vibration fault signals are non-stationary and nonlinear, so it is very difficult to accurately extract the fault characteristics for diagnosis. As symplectic geometry mode decomposition (SGMD) has shown excellent decomposition performance and noise
Wei CHEN +3 more
exaly +4 more sources
Comprehensive Separation Algorithm for Single-Channel Signals Based on Symplectic Geometry Mode Decomposition [PDF]
SensorsThis paper aims to explore the difficulty of obtaining source signals from complex mixed signals and the issue that the FastICA algorithm cannot directly decompose the received single-channel mixed signals and distort the signal separation in low signal ...
Xinyu Wang, Jin Zhao, Xianliang Wu
doaj +3 more sources
The Partial Reconstruction Symplectic Geometry Mode Decomposition and Its Application in Rolling Bearing Fault Diagnosis [PDF]
Sensors, 2023 Extracting the fault characteristic information of rolling bearings from intense noise disturbance has been a heated research issue. Symplectic geometry mode decomposition (SGMD) has already been adopted for bearing fault diagnosis due to its advantages ...
Yanfei Liu +5 more
doaj +3 more sources
Comparative Energetics of Various Membrane Distillation Configurations and Guidelines for Design and Operation [PDF]
Membranes, 2023 This paper presents a comparative performance study of single-stage desalination processes with major configurations of membrane distillation (MD) modules.
Md Rashedul Islam +4 more
doaj +3 more sources