油纸绝缘老化拉曼光谱特征量提取及诊断方法

doi:10.19595/j.cnki.1000-6753.tces.162019

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (24352 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

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.

Key words： Raman spectroscopy oil-paper insulation features ageing diagnosis

Received: 27 December 2016 Published: 14 March 2018

PACS:

TM835

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Zou Jingxin
	ChenWeigen
	Wan Fu
	Fan Zhou

Cite this article:

Zou Jingxin,ChenWeigen,Wan Fu等. The Raman Spectral Feature Extraction and Diagnosis of Oil-Paper Insulation Ageing[J]. Transactions of China Electrotechnical Society, 2018, 33(5): 1133-1142.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.162019 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I5/1133

[1] Lundgaard L E, Allan D, Hohlein I, et al.Aging of cellulose in mineral-oil insulated transformers[J]. Electra, 2007: 50-59.
[2] Std I.IEEE guide for loading mineral-oil-immersed transformers[Z]. 2012:1-123 .
[3] Emsley A M.The kinetics and mechanisms of degradation of cellulosic insulation in power transformers[J]. Polymer Degradation and Stability, 1994, 44(3): 343-349.
[4] Emsley A M, Xiao X, Heywood R J, et al.Degradation of cellulosic insulation in power transformers. part 2: formation of furan products in insulating oil[J]. IEE Proceedings - Science, Measurement and Technology, 2000, 147(3):110-114.
[5] 王松林. 变压器绝缘老化诊断技术[J]. 电气技术, 2011,12(8): 82-85.
Wang Songlin.Transformer insulation aging diagnosis technology[J]. Electrical Engineering, 2011, 12(8): 82-85.
[6] 廖瑞金, 杨丽君, 郑含博, 等. 电力变压器油纸绝缘热老化研究综述[J]. 电工技术学报, 2012, 27(5): 1-12.
Liao Ruijin, Yang Lijun, Zheng Hanbo, et al.Reviews on oil-paper insulation thermal aging in power transformers[J]. Transactions of China Electrotechnical Society, 2012, 27(5): 1-12.
[7] 杨丽君, 廖瑞金, 孙会刚, 等. 变压器油纸绝缘热老化特性及特征量研究[J]. 电工技术学报, 2009, 24(8):27-33.
Yang Lijun, Liao Ruijin, Sun Huigang, et al.Investigation on properties and characteristics of oil-paper insulation in transformer during thermal degradation process[J]. Transactions of China Electrotechnical Society, 2009, 24(8): 27-33.
[8] 梁帅伟, 廖瑞金, 杨丽君, 等. 天然酯与矿物油纸绝缘的加速热老化特性研究[J]. 中国电机工程学报, 2008, 28(25): 20-24.
Liang Shuaiwei, Liao Ruijin, Yang Lijun, et al.Study on the accelerated thermal aging of nature ester-paper insulation and mineral oil-paper insulation[J]. Proceedings of the CSEE, 2008, 28(25): 20-24.
[9] Morais R M, Mannheimer W A, Carballeira M, et al.Furfural analysis for assessing degradation of thermally upgraded papers in transformer insulation[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 1999, 6(2):159-163.
[10] 杨丽君, 廖瑞金, 孙会刚, 等. 油纸绝缘热老化特性及生成物的对比分析[J]. 中国电机工程学报, 2008, 28(22): 53-58.
Yang Lijun, Liao Ruijin, Sun Huigang, et al.Contrasting analysis and investigation on properties and products of oil-paper during thermal aging process[J]. Proceedings of the CSEE, 2008, 28(22): 53-58.
[11] Okabe S, Ueta G, Tsuboi T.Investigation of aging degradation status of insulating elements in oil-immersed transformer and its diagnostic method based on field measurement data[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2013, 20(1): 346-355.
[12] 陈伟根, 万福, 顾朝亮, 等. 变压器油中溶解气体拉曼剖析及定量检测优化研究[J]. 电工技术学报, 2016, 31(2): 236-243.
Chen Weigen, Wan Fu, Gu Zhaoliang, et al.The research for raman analysis of dissolved gases in transformer oil and optimization of quantitative detection[J]. Transactions of China Electrotechnical Society, 2016, 31(2): 236-243.
[13] Arakelian V G.The long way to the automatic chromatographic analysis of gases dissolved in insulating oil[J]. IEEE Electrical Insulation Magazine, 2004, 20(6): 8-25.
[14] Terry S C, Jerman J H, Angell J B.A gas chromatograph air analyzer fabricated on a silicon wafer[J]. IEEE Transactions on Electron Devices, 1980, 26(12): 1880-1886.
[15] Taquet N, Pironon J, Donato P D, et al.Efficiency of combined FTIR and Raman spectrometry for online quantification of soil gases: application to the monitoring of carbon dioxide storage sites[J]. International Journal of Greenhouse Gas Control, 2013, 12(12): 359-371.
[16] 顾朝亮, 陈伟根, 邹经鑫, 等. 变压器油中溶解微量糠醛的激光拉曼光谱检测方法[J]. 电工技术学报, 2016, 31(20): 219-227.
Gu Zhaoliang, Chen Weigen, Zou Jingxin, et al.Detection of trace furfural dissolved in transformer oil using laser raman spectroscopy[J]. Transactions of China Electrotechnical Society, 2016, 31(20): 219-227.
[17] Somekawa T, Fujita M, Izawa Y, et al.Furfural analysis in transformer oils using laser raman spectroscopy[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2015, 22(1): 229-231.
[18] 陈伟根, 赵立志, 彭尚怡, 等. 激光拉曼光谱应用于变压器油中溶解气体分析[J]. 中国电机工程学报, 2014, 34(15): 2485-2492.
Chen Weigen, Zhao Lizhi, Peng Shangyi, et al.Analysis of dissolved gas in transformer oil based on laser raman spectroscopy[J]. Proceedings of the CSEE, 2014, 34(15): 2485-2492.
[19] And S C, Carroll D L.Synthesis and characterization of truncated triangular silver nanoplates[J]. Nano Letters, 2002, 2(9):1003-1007.
[20] 杨序纲. 拉曼光谱的分析与应用[M]. 北京: 国防工业出版社, 2008.
[21] Zhang Zhimin, Chen Shan, Liang Yize.Baseline correction using adaptive iteratively reweighted penalized least squares[J]. Analyst, 2010, 135(5): 1138-1146.
[22] Jiang Xingliang, Xia Yunfeng, Hu Jianlin, et al.An S-transform and support vector machine (SVM)-based online method for diagnosing broken strands in transmission lines[J]. Energies, 2011, 4(9): 1278-1300.
[23] 赵莹, 赵川, 叶华, 等. 应用主成分分析约简电压暂降扰动源识别特征的方法[J]. 电力系统保护与控制, 2015, 43(13): 105-110.
Zhao Ying, Zhao Chuan, Ye Hua, et al.Method to reduce identification feature of different voltage sag disturbance source based on principal component analysis[J]. Power System Protection and Control, 2015, 43(13):105-110.
[24] 律方成, 金虎, 王子建, 等. 基于主成分分析和多分类相关向量机的GIS局部放电模式识别[J]. 电工技术学报, 2015, 30(6): 225-231.
Lü Fangcheng, Jin Hu, Wang Zijian, et al.GIS partial discharge pattern recognition based on principal component analysis and milticlass relevance vector machine[J]. Transactions of China Electrotechnical Society, 2015, 30(6): 225-231.
[25] 薛浩然, 张珂珩, 李斌, 等. 基于布谷鸟算法和支持向量机的变压器故障诊断[J]. 电力系统保护与控制, 2015, 43(8): 8-13.
Xue Haoran, Zhang Keheng, Li Bin, et al.Fault diagnosis of transformer based on the cuckoo search and support vector machine[J]. Power System Protection and Control, 2015, 43(8): 8-13.
[26] DL/T984—2005. 油浸式变压器绝缘老化判断导则DL/T984—2005. 油浸式变压器绝缘老化判断导则[S].2005.
[27] 凡勇, 胡婷, 周竹君, 等. 植物绝缘油-纸板与矿物油-纸板的加速热老化寿命对比研究[J]. 绝缘材料, 2014(4): 105-109.
Fan Yong, Hu Ting, Zhou Zhujun, et al.Comparative study on accelerated thermal ageing of vegetable insulating oil-paperboard and mineral oil-paperboard[J]. Insulating Materials, 2014(4): 105-109.
[28] 贾嵘, 张云, 洪刚, 等. 基于改进PSO的LSSVM参数优化在变压器故障诊断中的应用[J]. 电力系统保护与控制, 2010, 38(17): 121-124.
Jia Rong, Zhang Yun, Hong Gang, et al.Parameter optimization of least squares support vector machine based on improved particle swarm optimization in fault diagnosis of transformer[J]. Power System Protection and Control, 2010, 38(17): 121-124.