Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers

Jingxin Zou, Weigen Chen, Fu Wan, Zhou Fan and Lingling Du
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Jingxin Zou: State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China
Weigen Chen: State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China
Fu Wan: State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China
Zhou Fan: State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China
Lingling Du: State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China

Energies, 2016, vol. 9, issue 11, 1-14

Abstract: The aging of oil-paper insulation in power transformers may cause serious power failures. Thus, effective monitoring of the condition of the transformer insulation is the key to prevent major accidents. The purpose of this study was to explore the feasibility of confocal laser Raman spectroscopy (CLRS) for assessing the aging condition of oil-paper insulation. Oil-paper insulation samples were subjected to thermal accelerated ageing at 120 °C for up to 160 days according to the procedure described in the IEEE Guide. Meanwhile, the dimension of the Raman spectrum of the insulation oil was reduced by principal component analysis (PCA). The 160 oil-paper insulation samples were divided into five aging stages as training samples by clustering analysis and with the use of the degree of polymerization of the insulating papers. In addition, the features of the Raman spectrum were used as the inputs of a multi-classification support vector machine. Finally, 105 oil-paper insulation testing samples aged at a temperature of 130 °C were used to further test the diagnostic capability and universality of the established algorithm. Results demonstrated that CLRS in conjunction with the PCA-SVM technique provides a new way for aging stage assessment of oil-paper insulation equipment in the field.

Keywords: Raman spectroscopy; power transformers; aging stage; principal component analysis; clustering analysis; degree of polymerization; support vector machine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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