Transformer insulating oil characteristic changes observed using accelerated degradation in consideration of field transformer conditions

Kohtoh, M.; Ueta, Genyo; Okabe, Shigemitsu; Amimoto, T.

doi:10.1109/tdei.2010.5492254

Cited by 65 publications

(21 citation statements)

References 3 publications

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“…It shows that, during a dielectric breakdown measurement, the electrical field in the Voltesso medium around the center point is higher than the breakdown electrical field within the solid material [13]. This electrical field difference explains the inception of partial discharges when the applied voltage becomes high enough to cause breakdown in the surrounding medium.…”

Section: Modeling and Discussionmentioning

confidence: 96%

Influence of the surrounding medium on the dielectric strength measurement of LLDPE/clay nanocomposites

Daran-Daneau

David

Fréchette

et al. 2012

2012 IEEE International Symposium on Electrical Insulation

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This paper evaluates dielectric breakdown measurements according to the ASTM D149-09 standard for various specimen thicknesses and surrounding media. This study was performed on LLDPE/nanoclay with three different surrounding media. Pre-breakdown partial discharge activity was monitored and the electrical field in the breakdown area was computed by FEM modeling.It was observed that the variations of the dielectric breakdown values from the neat polymer to the nanostructured polymers strongly depends on the surrounding medium, a situation which could lead to non-valid conclusions if appropriate care is not taken to select the optimal experimental procedure. Also, the results underscore the influence of the pre-breakdown partial discharge gas generation on the electrical field distribution and the influence of the surrounding medium degradation.To conclude, the ASTM D149 Standard shows a lack of normalization in terms of the surrounding medium parameters and the sample thickness, even though a certain amount of normalization is needed in order to compare breakdown results from one experiment to the other and to improve the understanding of the solid dielectric breakdown phenomena.

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Section: Modeling and Discussionmentioning

confidence: 96%

Influence of the surrounding medium on the dielectric strength measurement of LLDPE/clay nanocomposites

Daran-Daneau

David

Fréchette

et al. 2012

2012 IEEE International Symposium on Electrical Insulation

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“…The normal operating temperature of transformer oil is 60 °C. Hence, one day of laboratory ageing (inside an oven) is equivalent to a year in the field [1]. Table 2 shows the description of the samples for different ageing times and metal substances.…”

Section: B Experimental Setup and Preparation Of Transformer Oil Samplementioning

confidence: 99%

Transformer Oil Ageing Detection using Mach–Zender Interferometry Configuration as a Sensor

2019

IJRTE

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Abstract: Paper In this paper, the fabrication and characterisation of an optical fibre sensor for transformer oil ageing detection are presented. Bare fibre is used in the Mach-Zender interferometry (MZI) configuration as a sensing arm. Hydrofluoric acid (30%) and a power meter are used in sensor fabrication. The MZI sensor is affected by the changes of the refractive index (RI) of the transformer oil. The sensor operates according to different output power levels at the receiving end of the optical sensor. Results agree with the AC breakdown voltage test and oil absorption spectrum test. This work contributes to the improvement of transformer oil monitoring systems by ensuring the availability of oil information and protecting such systems from damage.

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“…Their operating states are closely related to the safety and reliability of power grids [1][2][3][4]. With the development of ultrahigh voltage and extra-high voltage grids and increase in the short-circuit capacity of power systems, faults of the transformers can cause greater damage and have a large impact on power systems [5][6][7]. Thus, it is very important to effectively predict and diagnose the incipient faults of transformers as early as possible to avoid greater tragedy [8].…”

Section: Introductionmentioning

confidence: 99%

Application of a combined decision model based on optimal weights in incipient faults diagnosis for power transformer

Tingfang

Zhang

et al. 2016

IEEJ Transactions Elec Engng

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A new method for the diagnosis of incipient transformer faults based on a combined decision model using IEC 60599 three-ratio method, grey system theory (GS) algorithm, Dempster-Shafer evidence (DS) theory, and backpropagation (BP) neural network diagnosis method is proposed in this paper. The new method will eliminate the influence of any one individual diagnosis method due to insufficient information or diagnostic prejudices. In order to minimize the sum-of-squared errors of the proposed method, the optimal weights of every individual method which comprises the combined decision model are calculated based on their own diagnosis error ratios. Thus a combined decision model based on optimal weights (CDMOW) is formed. Then the optimal diagnosis result is obtained based on CDMOW. Results of diagnosis instances show that the use of CDMOW not only gives a much higher diagnostic accuracy rate but also more stability in fault diagnosis than any single method composing it.

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Transformer insulating oil characteristic changes observed using accelerated degradation in consideration of field transformer conditions

Cited by 65 publications

References 3 publications

Influence of the surrounding medium on the dielectric strength measurement of LLDPE/clay nanocomposites

Influence of the surrounding medium on the dielectric strength measurement of LLDPE/clay nanocomposites

Transformer Oil Ageing Detection using Mach–Zender Interferometry Configuration as a Sensor

Application of a combined decision model based on optimal weights in incipient faults diagnosis for power transformer

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