Gearbox Fault Diagnosis Based on ICEEMDAN-MPE-AWT and SE-ResNeXt50 Transfer Learning Model

Article Properties
  • Language
    English
  • DOI (url)
    10.3390/app14062565
  • Publication Date
    2024/03/19
  • Journal
    Applied Sciences
  • Indian UGC (journal)
  • Refrences
    30
  • Hongfeng Gao Handan Branch of Hebei Special Equipment Supervision and Inspection Institute, Handan 056000, China
  • Tiexin Xu School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China
  • Renlong Li School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China
  • Chaozhi Cai School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China ORCID (unauthenticated)
Abstract
Cite
Gao, Hongfeng, et al. “Gearbox Fault Diagnosis Based on ICEEMDAN-MPE-AWT and SE-ResNeXt50 Transfer Learning Model”. Applied Sciences, vol. 14, no. 6, 2024, p. 2565, https://doi.org/10.3390/app14062565.
Gao, H., Xu, T., Li, R., & Cai, C. (2024). Gearbox Fault Diagnosis Based on ICEEMDAN-MPE-AWT and SE-ResNeXt50 Transfer Learning Model. Applied Sciences, 14(6), 2565. https://doi.org/10.3390/app14062565
Gao, Hongfeng, Tiexin Xu, Renlong Li, and Chaozhi Cai. “Gearbox Fault Diagnosis Based on ICEEMDAN-MPE-AWT and SE-ResNeXt50 Transfer Learning Model”. Applied Sciences 14, no. 6 (2024): 2565. https://doi.org/10.3390/app14062565.
1.
Gao H, Xu T, Li R, Cai C. Gearbox Fault Diagnosis Based on ICEEMDAN-MPE-AWT and SE-ResNeXt50 Transfer Learning Model. Applied Sciences. 2024;14(6):2565.
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Refrences
Title Journal Journal Categories Citations Publication Date
Gear and bearing fault classification under different load and speed by using Poincaré plot features and SVM Journal of Intelligent Manufacturing
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Manufactures
  • Technology: Technology (General): Industrial engineering. Management engineering
  • Technology: Engineering (General). Civil engineering (General)
 21 2022
GASF–MSNN: A New Fault Diagnosis Model for Spatiotemporal Information Extraction Industrial & Engineering Chemistry Research
  • Technology: Chemical technology: Chemical engineering
  • Technology: Chemical technology: Chemical engineering
  • Science: Chemistry
 11 2021
A novel feature extraction method for bearing fault classification with one dimensional ternary patterns ISA Transactions
  • Technology: Mechanical engineering and machinery
  • Technology: Engineering (General). Civil engineering (General)
  • Science: Mathematics: Instruments and machines
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
 56 2020
A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load Mechanical Systems and Signal Processing
  • Technology: Mechanical engineering and machinery
  • Technology: Mechanical engineering and machinery
  • Technology: Engineering (General). Civil engineering (General)
 779 2018
Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning 2018