Effect of DC Voltage Ramp Rate on Breakdown in Ferrofluid Based on Transformer Oil

Bartko, Pavol; Rajňák, Michal; Cimbala, Roman; Kolcunová, Iraida; Paulovičová, K.; Τimko, M.; Kopčanský, P.; Kurimský, Juraj

doi:10.12693/aphyspola.137.970

Cited by 3 publications

(1 citation statement)

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“…Ramp speed: if the risk of breakdown is represented as a differential breakdown rate per unit time, then different ramp speeds might result in different maximum breakdown voltages. This has been observed in borosilicate glass and alumina [21], as well as ferrofluid [22], and oilimpregnated pressboard [23]. However, note that in thin film polymers an opposite dependence was observed [24] (i.e.…”

mentioning

confidence: 71%

Study of dielectric breakdown in liquid xenon with the XeBrA experiment

Watson¹,

Olcina²,

Soria³

et al. 2022

Preprint

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Maintaining the electric fields necessary for the current generation of noble liquid time projection chambers (TPCs), with drift lengths exceeding one meter, requires a large negative voltage applied to their cathodes. Delivering such high voltage is associated with an elevated risk of electrostatic discharge and electroluminescence, which would be detrimental to the performance of the TPC. The Xenon Breakdown Apparatus (XeBrA) is a five-liter high-voltage test chamber built to investigate the factors contributing to high voltage breakdown in noble liquids. In this work, we present data collected during 2020-21 and compare them to previous data gathered in 2018. Area scaling and surface finish were observed to be the dominant factors affecting breakdown. Based on these results, we recommend that the next generation of TPCs should not withstand fields larger than 20 kV/cm on the electrode surfaces. In addition, small electrical activity was frequently observed during high voltage ramps prior to electrostatic discharge. Furthermore, the position of breakdowns was reconstructed with a system of high-speed cameras and good agreement with electric field simulations was found.

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mentioning

confidence: 71%

Study of dielectric breakdown in liquid xenon with the XeBrA experiment

Watson¹,

Olcina²,

Soria³

et al. 2022

Preprint

View full text Add to dashboard Cite

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Study of dielectric breakdown in liquid xenon with XeBrA: The xenon breakdown apparatus

Watson

Olcina

Soria

et al. 2023

Review of Scientific Instruments

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Maintaining the electric fields necessary for the current generation of noble liquid time projection chambers (TPCs), with drift lengths exceeding 1 m, requires a large negative voltage applied to their cathode. Delivering such high voltage is associated with an elevated risk of electrostatic discharge and electroluminescence, which would be detrimental to the performance of the experiment. The Xenon Breakdown Apparatus (XeBrA) is a 5-l, high voltage test chamber built to investigate the contributing factors to electrical breakdown in noble liquids. In this work, we present the main findings after conducting scans over stressed electrode areas, surface finish, pressure, and high voltage ramp speed in the medium of liquid xenon. Area scaling and surface finish were observed to be the dominant factors affecting breakdown, whereas no significant changes were observed with varying pressure or ramp speed. A general rise in both the anode current and photon rate was observed in the last 30 s, leading up to a breakdown, with a marked increase in the last couple of seconds. In addition, the position of breakdowns was reconstructed with a system of high-speed cameras and a moderate correlation with the Fowler–Nordheim field emission model was found. Tentative evidence for bubble nucleation being the originating mechanism of breakdown in the liquid was also observed. We deem the results presented in this work to be of particular interest for the design of future, large TPCs, and practical recommendations are provided.

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Temperature and Fault Prediction of Transformer in Distribution Station Based on Digital Twin Model

Zhang,

Li,

Chen

et al. 2024

Applied Mathematics and Nonlinear Sciences

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This article presents an innovative method for predicting transformer temperature and faults in distribution substations using a digital twin model combined with deep learning techniques. By constructing a digital model of the transformer, real-time monitoring and precise simulation of its operating status are achieved. In the prediction process, convolutional neural networks (CNN) and long short-term memory networks (LSTM) are fused to mine data features deeply and predict the future state of the transformer. The results show that this method demonstrates significant advantages in transformer temperature and fault prediction, with an accuracy rate as high as 96.55%. Moreover, the error rate of this method has been significantly reduced through comparative experimental verification. In addition to ensuring high accuracy, this method achieves a false alarm rate of less than 0.12% and an average detection time of only 1.35 seconds, further highlighting its effectiveness in practical applications. Therefore, the transformer temperature and fault prediction system developed in this article for distribution substations can effectively improve the stability and safety of the electrical power system (EPS) and provide new and powerful support for the intelligent management and maintenance of transformers.

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Effect of DC Voltage Ramp Rate on Breakdown in Ferrofluid Based on Transformer Oil

Cited by 3 publications

References 0 publications

Study of dielectric breakdown in liquid xenon with the XeBrA experiment

Study of dielectric breakdown in liquid xenon with the XeBrA experiment

Study of dielectric breakdown in liquid xenon with XeBrA: The xenon breakdown apparatus

Temperature and Fault Prediction of Transformer in Distribution Station Based on Digital Twin Model

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