LIF Technology and ELM Algorithm Power Transformer Fault Diagnosis Research

Peng-cheng YAN; Chao-yin ZHANG; Quan-sheng SUN; Song-hang SHANG; Ni-ni YIN; Xiao-fei ZHANG

doi:10.3964/j.issn.1000-0593(2022)05-1459-06

Journals >Spectroscopy and Spectral Analysis >Volume 42 >Issue 5 >Page 1459 > Article

Spectroscopy and Spectral Analysis
Vol. 42, Issue 5, 1459 (2022)

LIF Technology and ELM Algorithm Power Transformer Fault Diagnosis Research

Peng-cheng YAN^1、*, Chao-yin ZHANG^{2、2; *;}, Quan-sheng SUN^2、2;, Song-hang SHANG^2、2;, Ni-ni YIN^1、1;, and Xiao-fei ZHANG^2、2;

Author Affiliations

¹1. State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mine, Anhui University of Science and Technology, Huainan 232001, China

²2. College of Electrical and Information Engineering, Anhui University of Technology, Huainan 232001, China

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DOI: 10.3964/j.issn.1000-0593(2022)05-1459-06 Cite this Article

Peng-cheng YAN, Chao-yin ZHANG, Quan-sheng SUN, Song-hang SHANG, Ni-ni YIN, Xiao-fei ZHANG. LIF Technology and ELM Algorithm Power Transformer Fault Diagnosis Research[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1459 Copy Citation Text

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Fig. 1. Flow chart of oil sample spectrum collection

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Fig. 2. Two kinds of preprocessing and original image processing

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Fig. 3. Cumulative contribution rate of PCA

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Fig. 4. Cumulative contribution rate of KPCA

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Fig. 5. Comparison of prediction results of ELM test set output models

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Fig. 6. The relative error curve between predicted value and real value

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预处理	性能评价	KPCA-ELM	PCA-ELM
MSC	运行时间/s	0.5	3.296 9
	平均相对误差(MRE)	0.009 6	0.011 8
	均方误差(MSE)	0.000 7	0.001 1
	均方根误差(RMSE)	0.027 1	0.033 9
	拟合优度(R²)	0.999 41	0.999 19
SNV	运行时间/s	0.5175	3.343 8
	平均相对误差(MRE)	0.017 4	0.018 5
	均方误差(MSE)	0.001 3	0.001 5
	均方根误差(RMSE)	0.036 0	0.038 3
	拟合优度(R²)	0.999 08	0.998 83
Original	运行时间/s	0.578 1	3.484 4
	平均相对误差(MRE)	0.024 1	0.035 0
	均方误差(MSE)	0.004 0	0.005 3
	均方根误差(RMSE)	0.063 2	0.073 0
	拟合优度(R²)	0.996 95	0.996 02

Table 1. Performance comparison of ELM test set output models

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