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Symmetrical Loss of Excitation Fault Diagnosis in an Asynchronized High-Voltage Generator

Author

Listed:
  • Yanling Lv

    (School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China)

  • Yuting Gao

    (School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China)

  • Jian Zhang

    (State Grid Heilongjiang Electric Power Company Limited Electric Power Research Institute, Harbin 150030, China)

  • Chenmin Deng

    (School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China)

  • Shiqiang Hou

    (School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China)

Abstract

As a new type of generator, an asynchronized high-voltage generator has the characteristics of an asynchronous generator and high voltage generator. The effect of the loss of an excitation fault for an asynchronized high-voltage generator and its fault diagnosis technique are still in the research stage. Firstly, a finite element model of the asynchronized high-voltage generator considering the field-circuit-movement coupling is established. Secondly, the three phase short-circuit loss of excitation fault, three phase open-circuit loss of excitation fault, and three phase short-circuit fault on the stator side are analyzed by the simulation method that is applied abroad at present. The fault phenomenon under the stator three phase short-circuit fault is similar to that under the three phase short-circuit loss of excitation. Then, a symmetrical loss of the excitation fault diagnosis system based on wavelet packet analysis and the Back Propagation neural network (BP neural network) is established. At last, we confirm that this system can eliminate the interference of the stator three phase short-circuit fault, accurately diagnose the symmetrical loss of the excitation fault, and judge the type of symmetrical loss of the excitation fault. It saves time to find the fault cause and improves the stability of system operation.

Suggested Citation

  • Yanling Lv & Yuting Gao & Jian Zhang & Chenmin Deng & Shiqiang Hou, 2018. "Symmetrical Loss of Excitation Fault Diagnosis in an Asynchronized High-Voltage Generator," Energies, MDPI, vol. 11(11), pages 1-18, November.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3054-:d:181038
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    References listed on IDEAS

    as
    1. Sen-lin Cheng & Qiang Wei & Zhao-hong Ye, 2012. "Fault diagnosis system based on fuzzy-inference," Fuzzy Information and Engineering, Springer, vol. 4(1), pages 51-61, March.
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    Cited by:

    1. Nasha Wei & James Xi Gu & Fengshou Gu & Zhi Chen & Guoxing Li & Tie Wang & Andrew D. Ball, 2019. "An Investigation into the Acoustic Emissions of Internal Combustion Engines with Modelling and Wavelet Package Analysis for Monitoring Lubrication Conditions," Energies, MDPI, vol. 12(4), pages 1-19, February.

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