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A Leakage Current Forecast of the Polymeric Insulator Using ANFIS Method Based on LabView Pre-processed Thermal Image

Received: 28 October 2018     Accepted: 4 December 2018     Published: 4 January 2019
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Abstract

This paper reports estimates of leaky currents based on Thermal (Infrared) images of polymer insulators using LabVIEW as preliminary data from the ANFIS method for the purpose of condition-based non-contact monitoring. In this study, images of very high contaminated polymer insulators were taken using the FLIR-A600 thermal camera series. The laboratory pollution performance test is carried out in accordance with the standards of IEC 60507 with an 18 kV AC voltage. The pollution severity is indicated because the ESDD value is very high contaminated and the relative humidity conditions are maintained at the range of 85% RH to 95% RH and temperature at 28°C. Humidity and temperature are maintained through a mist-producing container that is connected to a controlled polymer isolator test container using an Arduino microcontroller with temperature and humidity sensors. LabVIEW is used to calculate the percentage of RGB color from a thermal image related to a certain measured leakage current. This RGB data is training data for ANFIS to predict leaky currents. The results show that this method is able to predict current leakage without spending time to reach RMSE 0.00008. By adding a calculation to determine the condition of the insulator in the category of Safe, Maintenance or Hazard so that the Field Technician can decide whether the insulator must be replaced or not. With a non-contact method that only through thermal analysis of polymer insulators can accelerate the process of checking the condition of the insulator.

Published in International Journal of Science, Technology and Society (Volume 6, Issue 6)
DOI 10.11648/j.ijsts.20180606.11
Page(s) 88-95
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Polymeric Insulator, Leakage Current, Partial Discharge, Infrared Images, Pollution

References
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Cite This Article
  • APA Style

    Darwison Darwison, Syukri Arief, Hairul Abral, Ariadi Hazmi, Novizon Novizon, et al. (2019). A Leakage Current Forecast of the Polymeric Insulator Using ANFIS Method Based on LabView Pre-processed Thermal Image. International Journal of Science, Technology and Society, 6(6), 88-95. https://doi.org/10.11648/j.ijsts.20180606.11

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    ACS Style

    Darwison Darwison; Syukri Arief; Hairul Abral; Ariadi Hazmi; Novizon Novizon, et al. A Leakage Current Forecast of the Polymeric Insulator Using ANFIS Method Based on LabView Pre-processed Thermal Image. Int. J. Sci. Technol. Soc. 2019, 6(6), 88-95. doi: 10.11648/j.ijsts.20180606.11

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    AMA Style

    Darwison Darwison, Syukri Arief, Hairul Abral, Ariadi Hazmi, Novizon Novizon, et al. A Leakage Current Forecast of the Polymeric Insulator Using ANFIS Method Based on LabView Pre-processed Thermal Image. Int J Sci Technol Soc. 2019;6(6):88-95. doi: 10.11648/j.ijsts.20180606.11

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  • @article{10.11648/j.ijsts.20180606.11,
      author = {Darwison Darwison and Syukri Arief and Hairul Abral and Ariadi Hazmi and Novizon Novizon and Aulia Aulia and Eka Putra Waldi},
      title = {A Leakage Current Forecast of the Polymeric Insulator Using ANFIS Method Based on LabView Pre-processed Thermal Image},
      journal = {International Journal of Science, Technology and Society},
      volume = {6},
      number = {6},
      pages = {88-95},
      doi = {10.11648/j.ijsts.20180606.11},
      url = {https://doi.org/10.11648/j.ijsts.20180606.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsts.20180606.11},
      abstract = {This paper reports estimates of leaky currents based on Thermal (Infrared) images of polymer insulators using LabVIEW as preliminary data from the ANFIS method for the purpose of condition-based non-contact monitoring. In this study, images of very high contaminated polymer insulators were taken using the FLIR-A600 thermal camera series. The laboratory pollution performance test is carried out in accordance with the standards of IEC 60507 with an 18 kV AC voltage. The pollution severity is indicated because the ESDD value is very high contaminated and the relative humidity conditions are maintained at the range of 85% RH to 95% RH and temperature at 28°C. Humidity and temperature are maintained through a mist-producing container that is connected to a controlled polymer isolator test container using an Arduino microcontroller with temperature and humidity sensors. LabVIEW is used to calculate the percentage of RGB color from a thermal image related to a certain measured leakage current. This RGB data is training data for ANFIS to predict leaky currents. The results show that this method is able to predict current leakage without spending time to reach RMSE 0.00008. By adding a calculation to determine the condition of the insulator in the category of Safe, Maintenance or Hazard so that the Field Technician can decide whether the insulator must be replaced or not. With a non-contact method that only through thermal analysis of polymer insulators can accelerate the process of checking the condition of the insulator.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - A Leakage Current Forecast of the Polymeric Insulator Using ANFIS Method Based on LabView Pre-processed Thermal Image
    AU  - Darwison Darwison
    AU  - Syukri Arief
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    T2  - International Journal of Science, Technology and Society
    JF  - International Journal of Science, Technology and Society
    JO  - International Journal of Science, Technology and Society
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    PB  - Science Publishing Group
    SN  - 2330-7420
    UR  - https://doi.org/10.11648/j.ijsts.20180606.11
    AB  - This paper reports estimates of leaky currents based on Thermal (Infrared) images of polymer insulators using LabVIEW as preliminary data from the ANFIS method for the purpose of condition-based non-contact monitoring. In this study, images of very high contaminated polymer insulators were taken using the FLIR-A600 thermal camera series. The laboratory pollution performance test is carried out in accordance with the standards of IEC 60507 with an 18 kV AC voltage. The pollution severity is indicated because the ESDD value is very high contaminated and the relative humidity conditions are maintained at the range of 85% RH to 95% RH and temperature at 28°C. Humidity and temperature are maintained through a mist-producing container that is connected to a controlled polymer isolator test container using an Arduino microcontroller with temperature and humidity sensors. LabVIEW is used to calculate the percentage of RGB color from a thermal image related to a certain measured leakage current. This RGB data is training data for ANFIS to predict leaky currents. The results show that this method is able to predict current leakage without spending time to reach RMSE 0.00008. By adding a calculation to determine the condition of the insulator in the category of Safe, Maintenance or Hazard so that the Field Technician can decide whether the insulator must be replaced or not. With a non-contact method that only through thermal analysis of polymer insulators can accelerate the process of checking the condition of the insulator.
    VL  - 6
    IS  - 6
    ER  - 

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Author Information
  • Department of Electrical Engineering, Universitas Andalas, Padang, Indonesia

  • Department of Chemistry, Universitas Andalas, Padang, Indonesia

  • Department of Mechanical Engineering, Universitas Andalas, Padang, Indonesia

  • Department of Electrical Engineering, Universitas Andalas, Padang, Indonesia

  • Department of Electrical Engineering, Universitas Andalas, Padang, Indonesia

  • Department of Electrical Engineering, Universitas Andalas, Padang, Indonesia

  • Department of Electrical Engineering, Universitas Andalas, Padang, Indonesia

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