Two-step machine learning-assisted label-free surface-enhanced Raman spectroscopy for reliable prediction of dissolved furfural in transformer oil-Reference-Cited by-同舟云学术

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Two-step machine learning-assisted label-free surface-enhanced Raman spectroscopy for reliable prediction of dissolved furfural in transformer oil

Published:2024-11 Issue: Volume:321 Page:124571
ISSN:1386-1425
Container-title:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
language:en
Short-container-title:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Author:

Wan Fu^ORCID,Li Shufan,Lei Yu,Wang Mingliang,Liu Ruiqi,Hu Kaida,Xia Yaoyang,Chen Weigen

Funder

National Natural Science Foundation of China

Chongqing Natural Science Foundation

Publisher

Elsevier BV

Reference39 articles.

1. Feature selection and classification of transformer faults based on novel meta-heuristic algorithm;El-kenawy;Mathematics,2022

2. Aging assessment of oil-paper insulation based on visional recognition of the dimensional expanded Raman spectra;Song;IEEE Trans. Instrum. Meas.,2021

3. Power transformer insulation system: a review on the reactions, fault detection, shallenges and future prospects;Thiviyanathan;Alexandria Eng. J.,2022

4. State-of-art review on chemical indicators for monitoring the aging status of oil-immersed transformer paper insulation;Zhang;Energies,2023

5. Toward flexible surface-enhanced Raman scattering (SERS) sensors for point-of-care diagnostics;Xu;Adv. Sci.,2019

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