Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers
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 (CL...
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| Format: | Article |
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MDPI AG
2016-11-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/9/11/946 |
| _version_ | 1798043463944503296 |
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| author | Jingxin Zou Weigen Chen Fu Wan Zhou Fan Lingling Du |
| author_facet | Jingxin Zou Weigen Chen Fu Wan Zhou Fan Lingling Du |
| author_sort | Jingxin Zou |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T22:49:26Z |
| format | Article |
| id | doaj.art-f23179d563214f6e8807a3dbad9a6f9e |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T22:49:26Z |
| publishDate | 2016-11-01 |
| publisher | MDPI AG |
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| series | Energies |
| spelling | doaj.art-f23179d563214f6e8807a3dbad9a6f9e2022-12-22T03:58:37ZengMDPI AGEnergies1996-10732016-11-0191194610.3390/en9110946en9110946Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed TransformersJingxin Zou0Weigen Chen1Fu Wan2Zhou Fan3Lingling Du4State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, ChinaState Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, ChinaState Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, ChinaState Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, ChinaState Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, ChinaThe 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.http://www.mdpi.com/1996-1073/9/11/946Raman spectroscopypower transformersaging stageprincipal component analysisclustering analysisdegree of polymerizationsupport vector machine |
| spellingShingle | Jingxin Zou Weigen Chen Fu Wan Zhou Fan Lingling Du Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers Energies Raman spectroscopy power transformers aging stage principal component analysis clustering analysis degree of polymerization support vector machine |
| title | Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers |
| title_full | Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers |
| title_fullStr | Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers |
| title_full_unstemmed | Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers |
| title_short | Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers |
| title_sort | raman spectral characteristics of oil paper insulation and its application to ageing stage assessment of oil immersed transformers |
| topic | Raman spectroscopy power transformers aging stage principal component analysis clustering analysis degree of polymerization support vector machine |
| url | http://www.mdpi.com/1996-1073/9/11/946 |
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