Laser & Optoelectronics Progress, Volume. 62, Issue 3, 0330003(2025)

Determination of Aging State of Oil-Paper Insulation Raman Spectrum Based on Local Linear Embedding

Xingang Chen1,2、*, Wenxuan Zhang1, Yijie Fan1, Zhipeng Ma1, Zhixian Zhang1, Huimin Zeng1, Yi Ao1, and Bo Wang3
Author Affiliations
  • 1School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China
  • 2Chongqing Energy Internet Engineering Technology Research Center, Chongqing 400054, China
  • 3ABB Electrical Drives Co., Ltd., Beijing 100015, China
  • show less

    To solve the effect of redundant information caused by high-dimensional Raman-spectrum data on the rapid and accurate identification of the aging state of transformer oil-paper insulation, a Raman-spectrum feature-extraction method for oil-paper insulation based on local linear embedding is proposed. An accelerated thermal-aging experiment was performed to obtain 100 groups of oil-paper insulation samples at different aging stages. The samples were classified into 10 categories based on the polymerization degree of the insulation paper, and Raman spectroscopy was performed on the samples. The conventional principal component analysis (PCA) and locally linear embedding (LLE) feature-extraction methods were used to extract features from the Raman spectrum. Adaboost was introduced to build a discrimination model, and the aging status of the two feature-extraction results was discriminated. Next, the subsequent discrimination accuracy of the two feature-extraction methods was compared. The results show that the discrimination accuracies of the Raman-spectrum samples after feature extraction using LLE and PCA are 98.8% and 90.2%, respectively, which proves that LLE feature extraction offers a greater discrimination accuracy and facilitates subsequent discrimination. The identified spectral information reflects the data simplification and accurate discrimination of oil-paper insulation Raman-spectrum samples via LLE feature extraction combined with the Adaboost discrimination model, which has practical engineering significance for the aging discrimination of transformer oil-paper insulation.

    Keywords
    Tools

    Get Citation

    Copy Citation Text

    Xingang Chen, Wenxuan Zhang, Yijie Fan, Zhipeng Ma, Zhixian Zhang, Huimin Zeng, Yi Ao, Bo Wang. Determination of Aging State of Oil-Paper Insulation Raman Spectrum Based on Local Linear Embedding[J]. Laser & Optoelectronics Progress, 2025, 62(3): 0330003

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Spectroscopy

    Received: Apr. 22, 2024

    Accepted: Jun. 4, 2024

    Published Online: Feb. 20, 2025

    The Author Email:

    DOI:10.3788/LOP241131

    CSTR:32186.14.LOP241131

    Topics