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Advanced Methods in Rotating Machines

Author

Listed:
  • Xiaohua Song

    (School of Electronic Information Engineering, Xi’an Technological University, Xi’an 710021, China)

  • Jing Liu

    (Laboratory for Unmanned Underwater Vehicle, School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China)

  • Chaobo Chen

    (School of Electronic Information Engineering, Xi’an Technological University, Xi’an 710021, China)

  • Song Gao

    (School of Electronic Information Engineering, Xi’an Technological University, Xi’an 710021, China)

Abstract

The motions of power sources in industrial applications were always provided by electromechanical systems, which use around 70% of the gross energy consumption of industrialized economies [...]

Suggested Citation

  • Xiaohua Song & Jing Liu & Chaobo Chen & Song Gao, 2022. "Advanced Methods in Rotating Machines," Energies, MDPI, vol. 15(15), pages 1-3, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5414-:d:872670
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    References listed on IDEAS

    as
    1. Shu Han & Xiaoming Liu & Yan Yang & Hailin Cao & Yuanhong Zhong & Chuanlian Luo, 2021. "Intelligent Algorithm for Variable Scale Adaptive Feature Separation of Mechanical Composite Fault Signals," Energies, MDPI, vol. 14(22), pages 1-13, November.
    2. Ya Luo & Wenbing Tu & Chunyu Fan & Lu Zhang & Yudong Zhang & Wennian Yu, 2022. "A Study on the Modeling Method of Cage Slip and Its Effects on the Vibration Response of Rolling-Element Bearing," Energies, MDPI, vol. 15(7), pages 1-16, March.
    3. Lucia Frosini, 2020. "Novel Diagnostic Techniques for Rotating Electrical Machines—A Review," Energies, MDPI, vol. 13(19), pages 1-26, September.
    4. Jianguo Wang & Minmin Xu & Chao Zhang & Baoshan Huang & Fengshou Gu, 2020. "Online Bearing Clearance Monitoring Based on an Accurate Vibration Analysis," Energies, MDPI, vol. 13(2), pages 1-17, January.
    5. Bo Qin & Quanyi Luo & Zixian Li & Chongyuan Zhang & Huili Wang & Wenguang Liu, 2022. "Data Screening Based on Correlation Energy Fluctuation Coefficient and Deep Learning for Fault Diagnosis of Rolling Bearings," Energies, MDPI, vol. 15(7), pages 1-21, April.
    6. Akilu Yunusa-Kaltungo & Ruifeng Cao, 2020. "Towards Developing an Automated Faults Characterisation Framework for Rotating Machines. Part 1: Rotor-Related Faults," Energies, MDPI, vol. 13(6), pages 1-20, March.
    7. Bingbin Guo & Zhixiang Luo & Bo Zhang & Yuqing Liu & Zaigang Chen, 2021. "Dynamic Influence of Wheel Flat on Fatigue Life of the Traction Motor Bearing in Vibration Environment of a Locomotive," Energies, MDPI, vol. 14(18), pages 1-18, September.
    8. Sabin Sathyan & Ugur Aydin & Anouar Belahcen, 2020. "Acoustic Noise Computation of Electrical Motors Using the Boundary Element Method," Energies, MDPI, vol. 13(1), pages 1-13, January.
    9. Zia Ullah & Bilal Ahmad Lodhi & Jin Hur, 2020. "Detection and Identification of Demagnetization and Bearing Faults in PMSM Using Transfer Learning-Based VGG," Energies, MDPI, vol. 13(15), pages 1-17, July.
    10. Pawel Ewert & Teresa Orlowska-Kowalska & Kamila Jankowska, 2021. "Effectiveness Analysis of PMSM Motor Rolling Bearing Fault Detectors Based on Vibration Analysis and Shallow Neural Networks," Energies, MDPI, vol. 14(3), pages 1-24, January.
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