Fluorescence spectroscopy-based very sensitive detection technique for insulating oil conditions

Lu Mu; DaCheng Li; AnJing Wang; Jia Xie; Yue Zhao; XiaoBing Sun

doi:10.1117/12.2686928

6 August 2023 Fluorescence spectroscopy-based very sensitive detection technique for insulating oil conditions

Lu Mu, DaCheng Li, AnJing Wang, Jia Xie, Yue Zhao, XiaoBing Sun

Proceedings Volume 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023); 127811O (2023) https://doi.org/10.1117/12.2686928
Event: 2023 International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 2023, Guangzhou, JS, China

Abstract

This research proposes a highly sensitive transformer fault detection method based on fluorescence spectral analysis to solve the problems of DGA (Dissolved Gases Analysis) technology, which is widely used for insulating oil condition detection: (1) the detection cycle is long and cannot respond in time; (2) the detection sensitivity is insufficient and fails when the amount of dissolved gas is small or there is no dissolved gas under low-energy fault. Fluorescence spectroscopy-based rapid detection technique. To master the fluorescence spectrum features of insulating oil and its ideal acquisition settings, the fluorescence spectral characteristics of commercially available new oil and insulating oil from real functioning transformers were gathered and evaluated. Perform a thermal aging fault simulation test, collect fluorescence spectra from defective oil samples to determine the ideal excitation wavelength, and link the fluorescence bimodal characteristic ratio with the duration of the thermal aging fault. The comparison results show that the fluorescence spectroscopy analysis method can detect the fault on the 30th day of thermal aging, which is approximately ten days earlier than the DGA method, shows how the test can assist fluorescence analysis approaches in detecting failures at an earlier stage. Meanwhile, fluorescence spectroscopic detection and analysis are quick, allowing for online real-time defect monitoring. The approach has the benefits of being quick and sensitive and not requiring sample treatment, and it has a promising future in the field of transformer failure identification.

Citation Download Citation

Lu Mu, DaCheng Li, AnJing Wang, Jia Xie, Yue Zhao, and XiaoBing Sun "Fluorescence spectroscopy-based very sensitive detection technique for insulating oil conditions", Proc. SPIE 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 127811O (6 August 2023); https://doi.org/10.1117/12.2686928

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Fluorescence

Emission wavelengths

Fluorescence intensity

Transformers

Fluorescence spectroscopy

Statistical analysis

Spectroscopy

Keywords/Phrases

Search In:

Publication Years