1. Ageing Status Identification of Oil-Paper Impregnated Insulation by NIRS Detection with Improved LDA Method
- Author
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Lincong Chen, Chen Xiaolin, Chuanfu Fu, Wenbo Zhang, Yuan Li, and Han Li
- Subjects
Identification (information) ,Ageing ,Computer science ,business.industry ,Electrical insulation paper ,Pattern recognition ,Statistical analysis ,Improved method ,Artificial intelligence ,Linear discriminant analysis ,business - Abstract
The ageing status of the oil-paper insulation is closely related to the operation of the transformers. Recently, near infrared spectroscopy (NIRS) is used to identify the ageing condition of oil-paper insulation for it is a more rapid and nondestructive detection than the traditional viscometry method. However, the identification accuracy of existing quantitative analysis method of NIRS are still insufficient. This paper proposed an improved Linear discriminant analysis (LDA) method to classify the spectra and to identify the ageing condition of the insulating paper. Based on DP measurement, the insulating paper specimens prepared in laboratory are divided into varying ageing groups. The principle of LDA method is introduced. The classic LDA method has been applied to identify the ageing status of specimens respectively from 4 ageing groups and 3 ageing groups. The results show that LDA has a better performance in classifying four groups than three groups. To achieve an accurate ageing condition identification with balanced accuracy of the model and enough categories of ageing status, the improved LDA method is proposed. The identification results show that the improved method has satisfactory performance and indicates great application potentials in the ageing assessment of the oil-paper impregnated insulation.
- Published
- 2021
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