Research on Electric Breakdown Fault Diagnosis Model of Transformer Insulated Oil Based on Fluorescent Double-Color Ratio

doi:10.3964/j.issn.1000-0593(2022)04-1134-05

	Research on Electric Breakdown Fault Diagnosis Model of Transformer Insulated Oil Based on Fluorescent Double-Color Ratio
	Zhao Yue 1; Ma Feng-xiang 1; Wang An-jing 2; Li Da-cheng 2; Song Yu-mei 1; Wu Jun 2; Cui Fang-xiao 2; Li Yang-yu 2; Cao Zhi-cheng 2
刊名	SPECTROSCOPY AND SPECTRAL ANALYSIS
	2022-04-01
卷号	42
关键词	Transformer insulated oil Fluorescence spectra Double-color ratio detection Fault diagnosis model
ISSN号	1000-0593
DOI	10.3964/j.issn.1000-0593(2022)04-1134-05
通讯作者	Wang An-jing(ajwang@aiofm.ac.cn)
英文摘要	Traditional fluorescence analysis and detection methods of transformer insulated oil quality, which use fluorescence spectrophotometer to collect the full bands' fluorescence spectrum of the oil sample and establish the diagnostic model of transformer operation states using the full bands' fluorescence characteristics of insulating oil with a different aging degree, have the problems of large volume and the high price of photometer and the inability to realize real-time monitoring due to a long time of spectrum acquisition, a new method to detect the quality of transformer insulating oil based on the fluorescent double-color ratio to extract fluorescence characteristic dual band information and establish fault diagnosis model of transformer operation was raised to solve it. Thus, the traditional fluorescence spectrophotometer can be replaced by custom filters and visible photodetectors to realize the rapid acquisition and processing of double-color fluorescence information, which can meet the on-line monitoring and reduce the hardware cost. The aging of transformer insulating oil caused by discharge breakdown fault was analyzed by fluorescence analysis. Different discharge breakdown conditions were simulated. NYNAS oil samples with different discharge breakdown times (10, 30, 50, 70, 90 and 120 min) were prepared as fluorescence detection targets. Fluorescence emission spectra at different excitation wavelengths were collected by fluorescence spectrophotometer, and the optimal fixed excitation wavelength was found to be 280 nm. The 3-point moving mean smoothing method was used to smooth the fluorescence spectrum of the samples and by analyzing the variation of the fluorescence characteristic peak of the oil sample under different discharge breakdown times, bands of 380 similar to 388 and 399 similar to 407 nm were selected as the double-color information extraction band. The fault diagnosis model of transformer insulated oil discharge based on fluorescent double-color ratio was established by least-square curve fitting. The study results demonstrate the effectiveness of the fluorescent double-color method on the fault diagnosis of transformer insulated electric oil breakdown, which provides a theoretical and practical basis for establishing a small, low-cost, fast and effective online monitoring system.
WOS研究方向	Spectroscopy
语种	英语
出版者	OFFICE SPECTROSCOPY & SPECTRAL ANALYSIS
WOS记录号	WOS:000791027500021
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/130851]
专题	中国科学院合肥物质科学研究院
通讯作者	Wang An-jing
作者单位	1.State Grid Anhui Elect Power Res Inst, Hefei 230000, Peoples R China 2.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Key Lab Gen Opt Calibrat & Characterizat Technol, Hefei 230031, Peoples R China
推荐引用方式 GB/T 7714	Zhao Yue,Ma Feng-xiang,Wang An-jing,et al. Research on Electric Breakdown Fault Diagnosis Model of Transformer Insulated Oil Based on Fluorescent Double-Color Ratio[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2022,42.
APA	Zhao Yue.,Ma Feng-xiang.,Wang An-jing.,Li Da-cheng.,Song Yu-mei.,...&Cao Zhi-cheng.(2022).Research on Electric Breakdown Fault Diagnosis Model of Transformer Insulated Oil Based on Fluorescent Double-Color Ratio.SPECTROSCOPY AND SPECTRAL ANALYSIS,42.
MLA	Zhao Yue,et al."Research on Electric Breakdown Fault Diagnosis Model of Transformer Insulated Oil Based on Fluorescent Double-Color Ratio".SPECTROSCOPY AND SPECTRAL ANALYSIS 42(2022).