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Classification study of composite insulator chemical formulations based on laser-induced breakdown spectroscopy

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Abstract

High-temperature vulcanized silicone rubber insulators are widely used in high-voltage transmission lines and substation equipment because of their excellent fouling resistance. The aging of silicone rubber occurs due to environmental factors as its operating life advances and is closely related to its production formulation. Establishing a classification method for insulator chemical formulations is beneficial regarding operational performance and proposing a more reasonable operating scheme for composite insulators. However, the silicone rubber production formulations of various manufacturers are usually confidential, and there is no technology that can quickly identify insulator chemical formulations. In this study, a rapid classification method for composite insulator chemical formulations was investigated based on laser-induced breakdown spectroscopy (LIBS). Returned insulators from seven different manufacturers are considered as the research object. Spectral data were collected separately, and the insulators were initially classified using the characteristic spectral lines of the elements corresponding to different fillers doped in silicone rubber. The spectral data were characterized using a recursive feature elimination algorithm for feature selection and a linear discriminant algorithm for data dimensionality reduction in the characteristic spectral data. Accordingly, the insulators were classified using a backpropagation neural network algorithm, achieving the best experimental results with an accuracy of about 95%. Thus, LIBS technology can achieve rapid classification of insulator chemical formulations, which can provide a basis for formulation correlation for the operation and maintenance of composite insulators, as well as guarantee the safety of transmission lines.

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References

  1. Yu Z, Guangya W, Rui Z (2006) Operating characteristics and analysis of high temperature vulcanized silicone rubber. Electr Porcelain Electr Porcelain Arrester 03:18–22

    Google Scholar 

  2. Liu Y, Wang Q, Lv F, Liang Y (2010) Effect of ultraviolet radiation on properties of high temperature vulcanized silicone rubber. High Volt Technol 36(11):2634–2638

    Google Scholar 

  3. Meng X, Mei H, Zhu B, Yin F, Wang L (2022) Influence of pollution on surface streamer discharge. Electr Power Syst Res 212:108638. https://doi.org/10.1016/j.epsr.2022.108638

    Article  Google Scholar 

  4. Wei S, Wenwei S, Guoli W, Yulu W, Guanjun Z (2013) Effect of corona discharge aging on trap characteristics of high temperature vulcanized silicone rubber. High Volt Technol 39(04):979–986

    Google Scholar 

  5. Nianping Y, Ziyi F, Hua W, Zheng C, Zhidong J (2017) Aging status and characterization technology of high temperature vulcanized silicone rubber. Insulation 50(12):1–9

    Google Scholar 

  6. Wang L, Zhou K, Zhao C et al (2012) Experimental verification of evaluation system for external insulation condition of saturated damp insulators. High Volt Technol 38(8):7

    Google Scholar 

  7. Zhu Hu, Weiguo Li, Ye L (2006) Status and development of insulator detection methods. Porcelain Light Arrester 06:13–17

    Google Scholar 

  8. Cheng L, Liu Y, Chen R et al (2022) Method for predicting the water absorption of external insulating silicone rubber. IEEE Trans Dielectr Electr Insul. https://doi.org/10.1109/TDEI.2022.3183653

    Article  Google Scholar 

  9. Zhang S, Cheng L, Liao R et al (2022) Process improvement to restrain emergency heating defect of composite insulator. IEEE Trans Dielectr Electr Insul 29(2):446–453. https://doi.org/10.1109/TDEI.2022.3157929

    Article  Google Scholar 

  10. Yang R, Zhou X, Luo C et al (1991) Modern instrumental analysis of polymers. Tsinghua University Press, Beijing

    Google Scholar 

  11. Pablo A, Foster A (2020) Guide to laser-induced breakdown spectroscopy. Nova Science Publishers, Inc., New York

    Google Scholar 

  12. Liu F, Wang W, Shen T et al (2019) Rapid Identification of kudzu powder of different origins using laser-induced breakdown spectroscopy. Sensors 19(6):1453–1463

    Article  Google Scholar 

  13. Zhu Y, Yang P, Yang X, Li J, Hao Z, Li Q, Guo L, Li X, Zeng X, Lu Y (2017) Identification of fresh meat varieties by Support vector machine combined with principal component analysis and Laser-induced breakdown spectroscopy. Anal Chem 45(03):336–341

    Google Scholar 

  14. Yu X, Peng J, Liu F, He Y (2017) Laser-induced breakdown spectroscopy technology for rapid identification of matcha and green tea powder. Spectrosc Spectr Anal 37(06):1908–1911

    Google Scholar 

  15. Li W, Chen G, Zeng Q, Yuan M, He W, Jiang Z, Liu Y, Nie C, Yu H, Guo L (2021) Fiber optic laser- induced breakdown spectroscopy for rapid detection and classification of iron and steel. Spectrosc Spect Anal 41(08):2638–2643

    Google Scholar 

  16. Sungho S, Youngmin M, Jaepil LEE et al (2020) Improvement in classification accuracy of stainless steel alloys by laser-induced breakdown spectroscopy based on elemental intensity ratio analysis. Plasma Sci Technol 22(7):074011

    Article  Google Scholar 

  17. Yu Q, Ma X, Wang R, Zhao H (2014) Research on rapid classification method based on LIBS and principal component analysis. Spectrosc Spect Anal 34(11):3095–3099

    Google Scholar 

  18. Meng D, Zhao N, Ma M, Gu Y, Yu Y, Fang L, Wang Y, Jia Y, Liu W, Liu J (2017) Study on rapid soil classification based on Laser-induced breakdown spectroscopy technique. Spectrosc Spect Anal 37(01):241–246

    Google Scholar 

  19. Lanza NL, Wiens RC, Clegg SM et al (2010) Calibrating the ChemCam laser-induced breakdown spectroscopy instrument for carbonate minerals on Mars. Appl Opt 49(13):211–217

    Article  Google Scholar 

  20. Park J, Kumar S, Han SH et al (2021) Combination of diffuse optical reflectance spectroscopy and laser-induced breakdown spectroscopy for accurate classification of edible salts. Spectrochim Acta Part B 179:106088

    Article  Google Scholar 

  21. Wang X, Wang H, Chen C et al (2016) Ablation properties and elemental analysis of silicone rubber using laser-induced breakdown spectroscopy[J]. IEEE Trans Plasma Sci 44(11):2766–2771

    Article  Google Scholar 

  22. Wang X, Liu X, Lu S, Qin X, Wang X, Jia Z (2022) Insulator glucose Laser-induced breakdown spectroscopy detection. High Volt Technol 48(03):876–882

    Google Scholar 

  23. Martin W, Wiese W, Musgrove A et al (2005) NIST atomic spectra database. Memorie Della Societa Astronomica Italiana Supplementi 8(1):96

    Google Scholar 

  24. Ji C, Guan Y, Zhang X, Li X, Wang X, Sun D (2015) Research progress of RTV silicone rubber anti-pollution flashover coatings. Coat Ind 45(11):81–87

    Google Scholar 

  25. Niu W, Zhang X, Qiao J, Yang H, Hou K (2020) Optimum design of silicone rubber filler for thermal insulation. New Chem Mater 48(01):115–119

    Google Scholar 

  26. Gao W, Wang Q, Yang S, Deng X, Xie Z (2000) Reinforcement effect of calcium carbonate and silicon carbide on RTV silicone rubber. J Polym Sci 2000(01):1–4

    Google Scholar 

  27. Xue Y, Li X, Zhang D et al (2018) Comparison of ATH and SiO2 fillers filled silicone rubber composites for HTV insulators. Compos Sci Technol 155:137–143

    Article  Google Scholar 

  28. Lin Y, Wang L, Yin F et al (2019) Comparison of four commonly used high temperature vulcanized silicone rubber formulas for outdoor insulator and their regional adaptability. J Appl Polym Sci 136(19):47477

    Article  Google Scholar 

  29. Rubber basics[M]. iSmithers Rapra Publishing, 2002

  30. Wang JC, Pan XC, Xue Y et al (2012) Studies on the application properties of calcium sulfate whisker in silicone rubber composites[J]. J Elastomers Plast 44(1):55–66

    Article  Google Scholar 

  31. Zhang J (2014) Research on classification feature selection algorithms for high dimensional small sample data [D]; Hefei University of Technology

  32. Qin S, Li M, Dai Y, Gao X, Song C, Lin J (2022) Spatial binding Support vector machine improves the accuracy of Fe analysis in Laser-induced breakdown spectroscopy aluminum alloys [J]. Spectrosc Spect Anal 42(02):582–586

    Google Scholar 

  33. Liu X, Zhang D, Feng Z, Ding J, Yang R, Sun S, Wang K, Zhu J, Wei Z (2021) Aircraft alloy identification based on remote Laser-induced breakdown spectroscopy technology. J Photonics 50(10):173–180

    Google Scholar 

  34. Zhao W, Min H, Liu S, An Y, Yu J (2021) Application progress of artificial neural network in Laser-induced breakdown spectroscopy data analysis. Spectrosc Spect Anal 41(07):1998–2004

    Google Scholar 

Download references

Funding

This work was supported by the National Natural Science Foundation of China (51677101), and Shenzhen fundamental research and discipline layout project (No. JCYJ20180508152044145).

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Authors and Affiliations

  1. China Southern Power Grid Shenzhen Power Supply Bureau Limited Company, Shenzhen, 518055, Guangdong, China

    Jinyang Song & Qishen Lyu

  2. Institute of Electric Power Research, Guangxi Power Grid Company Ltd., Nanning, 530023, Guangxi, China

    Xinran Qin

  3. China Southern Power Grid Guangzhou Power Supply Bureau of Guangdong Power Grid, Guangzhou, 510000, Guangdong, China

    Weinan Fan

  4. Engineering Laboratory of Power Equipment Reliability in Complicated Coastal Environments, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, Guangdong, China

    Qi Wang, Xilin Wang & Zhidong Jia

Authors
  1. Jinyang Song
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  2. Xinran Qin
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  3. Qishen Lyu
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  4. Weinan Fan
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  5. Qi Wang
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  6. Xilin Wang
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  7. Zhidong Jia
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Contributions

JS contributed to data curation and investigation; XQ contributed to investigation and methodology; QL contributed to data curation, investigation and methodology; WF contributed to methodology and formal analysis; QW contributed to methodology and writing; XW contributed to project administration and investigation; ZJ contributed to funding acquisition.

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Correspondence to Xilin Wang.

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Song, J., Qin, X., Lyu, Q. et al. Classification study of composite insulator chemical formulations based on laser-induced breakdown spectroscopy. Electr Eng 105, 1775–1782 (2023). https://doi.org/10.1007/s00202-023-01771-0

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  • DOI: https://doi.org/10.1007/s00202-023-01771-0

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