Abstract：Accurate diagnosis of oil-paper insulation ageing stage serves as an important technology to prevent major accidents of oil-paper insulation equipment. The extraction of effective characteristics which reflect the insulation ageing proves to be the essential step. Raman spectroscopy has been demonstrated that it has great potential of mixture composition analysis and condition diagnosis. In this paper, the Raman spectral features of oil-paper insulation samples were researched and extracted based on the Raman spectroscopy platform. Firstly, the samples in different ageing stages were prepared by thermal accelerated ageing process. Then the principal component analysis method was employed to reduce dimensionality of the obtained Raman spectral data. Secondly, the spectral features strongly corresponding to the ageing of oil-paper insulation were extracted. Based on Raman spectral features, multi-classification support vector machine optimized by particle swarm algorithm was used to set up an oil-paper insulation ageing diagnosis model. Finally, the diagnostic capability and universality of the established algorithm were verified by the samples made in lab.
邹经鑫, 陈伟根, 万福, 范舟. 油纸绝缘老化拉曼光谱特征量提取及诊断方法[J]. 电工技术学报, 2018, 33(5): 1133-1142.
Zou Jingxin, ChenWeigen, Wan Fu, Fan Zhou. The Raman Spectral Feature Extraction and Diagnosis of Oil-Paper Insulation Ageing. Transactions of China Electrotechnical Society, 2018, 33(5): 1133-1142.
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2018, Vol. 33 
