Tip Discharge Evolution Characteristics and Mechanism Analysis via Optical–Electrical Sensors in Oil-Immersed Transformers

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Authors: Zehao Chen, Yong Qian, Gehao Sheng, Fenghua. Wang, Bing Xue, Chunhui Zhang, Chengxiang Liu
Cited by: 1
References: 20

Abstract

Tip discharge in oil-immersed transformers poses a significant threat to insulation integrity. Conventional detection methods, such as gas and electrical analysis, are limited by slow response times or susceptibility to interference. Additionally, the lack of systematic comparisons between aged and fresh oil using multi-modal signal correlations hinders the development of accurate diagnostic strategies. To address this, a multi-modal sensing platform employing optical, UHF, and HFCT sensors, complemented by visual observation, was developed to investigate the evolution characteristics and mechanisms of tip discharge and to compare the detection effectiveness of these methods. Experimental results reveal that aged oil undergoes a novel four-stage evolution, where discharge signals first rise to a local peak, then experience suppression, followed by a dramatic surge, and finally decline slightly before breakdown. This process is governed by an "Impurity-Assisted Cumulative Breakdown Mechanism," driven by impurity bridge growth and space charge effects, with signal transitions from 'decoupling' to synchronization. The optical sensor demonstrated superior sensitivity in early discharge stages compared to electrical methods. In contrast, fresh oil exhibited a "High-Field-Driven Stochastic Breakdown Mechanism," with isolated pulses from micro-bubble discharges maintaining a metastable state until a critical threshold triggers instantaneous failure. This study enhances the understanding of how oil condition alters discharge mechanisms and underscores the value of multi-modal sensing for insulation condition assessment.

Fields of Study & Subjects

Power Transformer Diagnostics and Insulation High voltage insulation and dielectric phenomena Magneto-Optical Properties and Applications

Publication details

Journal / source
Sensors
Publisher
MDPI AG
Volume
26
Issue
1
Pages
331–331
Publication date
4 January 2026
Language
EN