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A Non-Destructive Optical Method for the DP Measurement of Paper Insulation Based on the Free Fibers in Transformer Oil

Author

Listed:
  • Lei Peng

    (Electric science and research institute of Guangdong Power Grid Co. Ltd., Guangzhou 510080, China)

  • Qiang Fu

    (Electric science and research institute of Guangdong Power Grid Co. Ltd., Guangzhou 510080, China)

  • Yaohong Zhao

    (Electric science and research institute of Guangdong Power Grid Co. Ltd., Guangzhou 510080, China)

  • Yihua Qian

    (Electric science and research institute of Guangdong Power Grid Co. Ltd., Guangzhou 510080, China)

  • Tiansheng Chen

    (Electric science and research institute of Guangdong Power Grid Co. Ltd., Guangzhou 510080, China)

  • Shengping Fan

    (Electric science and research institute of Guangdong Power Grid Co. Ltd., Guangzhou 510080, China)

Abstract

In order to explore a non-destructive method for measuring the polymerization degree (DP) of paper insulation in transformer, a new method that based on the optical properties of free fiber particles in transformer oil was studied. The chromatic dispersion images of fibers with different aging degree were obtained by polarizing microscope, and the eigenvalues ( r , b , and Mahalanobis distance) of the images were extracted by the RGB (red, blue, and green) tricolor analysis method. Then, the correlation between the three eigenvalues and DP of paper insulation were simulated respectively. The results showed that the color of images changed from blue-purple to orange-yellow gradually with the increase of aging degree. For the three eigenvalues, the relationship between Mahalanobis distance and DP had the best goodness of fit (R 2 = 0.98), higher than that of r (0.94) and b (0.94). The mean square error of the relationship between Mahalanobis distance and DP (52.17) was also significantly lower than that of r and b (97.58, 98.05). Therefore, the DP of unknown paper insulation could be calculated by the simulated relationship of Mahalanobis distance and DP.

Suggested Citation

  • Lei Peng & Qiang Fu & Yaohong Zhao & Yihua Qian & Tiansheng Chen & Shengping Fan, 2018. "A Non-Destructive Optical Method for the DP Measurement of Paper Insulation Based on the Free Fibers in Transformer Oil," Energies, MDPI, vol. 11(4), pages 1-9, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:716-:d:137480
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    References listed on IDEAS

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    1. Stefan Tenbohlen & Sebastian Coenen & Mohammad Djamali & Andreas Müller & Mohammad Hamed Samimi & Martin Siegel, 2016. "Diagnostic Measurements for Power Transformers," Energies, MDPI, vol. 9(5), pages 1-25, May.
    2. Janvier Sylvestre N’cho & Issouf Fofana & Yazid Hadjadj & Abderrahmane Beroual, 2016. "Review of Physicochemical-Based Diagnostic Techniques for Assessing Insulation Condition in Aged Transformers," Energies, MDPI, vol. 9(5), pages 1-29, May.
    3. Jingxin Zou & Weigen Chen & Fu Wan & Zhou Fan & Lingling Du, 2016. "Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers," Energies, MDPI, vol. 9(11), pages 1-14, November.
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    Cited by:

    1. Fabio Henrique Pereira & Francisco Elânio Bezerra & Shigueru Junior & Josemir Santos & Ivan Chabu & Gilberto Francisco Martha de Souza & Fábio Micerino & Silvio Ikuyo Nabeta, 2018. "Nonlinear Autoregressive Neural Network Models for Prediction of Transformer Oil-Dissolved Gas Concentrations," Energies, MDPI, vol. 11(7), pages 1-12, June.
    2. Xiaowen Wu & Ling Li & Nianguang Zhou & Ling Lu & Sheng Hu & Hao Cao & Zhiqiang He, 2018. "Diagnosis of DC Bias in Power Transformers Using Vibration Feature Extraction and a Pattern Recognition Method," Energies, MDPI, vol. 11(7), pages 1-20, July.
    3. Hao Pan & Liang Xue & Chuankai Yang & Fenghong Chu & Youhua Jiang & Hongmei Zhu & Yue Li & Lei Xin, 2022. "Detection of Cellulose Particles in Transformer Oil Based on Transport of Intensity Equation," Energies, MDPI, vol. 15(16), pages 1-11, August.
    4. Piotr Przybylek & Hubert Moranda & Hanna Moscicka-Grzesiak & Dominika Szczesniak, 2019. "Application of Synthetic Ester for Drying Distribution Transformer Insulation—The Influence of Cellulose Thickness on Drying Efficiency," Energies, MDPI, vol. 12(20), pages 1-16, October.
    5. Kakou D. Kouassi & Issouf Fofana & Ladji Cissé & Yazid Hadjadj & Kouba M. Lucia Yapi & K. Ambroise Diby, 2018. "Impact of Low Molecular Weight Acids on Oil Impregnated Paper Insulation Degradation," Energies, MDPI, vol. 11(6), pages 1-13, June.
    6. Piotr Przybylek, 2018. "A New Concept of Applying Methanol to Dry Cellulose Insulation at the Stage of Manufacturing a Transformer," Energies, MDPI, vol. 11(7), pages 1-13, June.

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