Power Transfomer Core Fault Diagnosis Using Frequency Response Analysis

Pleite, J.; González, Carlos Larrinaga; Vázquez, Juan Luís; Lázaro, A.

doi:10.1109/melcon.2006.1653298

Cited by 25 publications

(27 citation statements)

References 5 publications

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“…• The lateral phase length is higher than the central, what implies a higher reluctance as is explained in [13]. As a result, the associated lateral phases inductances are lower than the central.…”

Section: Magnetic Core Effect In the Fra Tracesmentioning

confidence: 94%

“…Thus only the series connected capacitances and fit the response. Taking the previous analysis into account, the response positive slope is fixed by the parameter corresponding to the and sum as expressed in (13). By the same way, the negative slope is fixed by , corresponding to the and series capacitance and given by (14).…”

Section: Magnetic Core Effect In the Fra Tracesmentioning

confidence: 99%

“…is the inductance due to the magnetic path core corresponding to the two unsymmetrical paths [13] and corresponds to the measured winding shunt capacitance plus the effect of shunt capacitances of the other phases due to the transformer core magnetic coupling.…”

Section: Magnetic Core Effect In the Fra Tracesmentioning

confidence: 99%

“…The results are given in Table I. The L m and C m values for the three phases (collected in Table II) can be obtained applying (13) and (14). The magnetizing inductance and shunt capacitances values of each phase are calculated using (26) and (28) and are shown in Table III Table III The values obtained and showed in Table III demonstrate the parameters capability to represent the transformer physical behavior:…”

Section: A Case 1: Power Transformer In Healthy Conditionmentioning

confidence: 99%

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Novel procedure for low frequency FRA traces interpretation

Herrera

Aponte

González-García

et al. 2012

2012 XXth International Conference on Electrical Machines

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This paper describes a new procedure to estimate separately the magnetization inductance Lm and winding shunt capacitance Cm for each power transformers phase, using and R-L-C electrical equivalent circuit developed to simulate the impedance measured in the Frequency Response Test. The Lm and Cm parameters can be used to analyze the traces obtained in the test. It is also shown experimental results that demonstrate the procedure ability to interpret the FRA traces providing an added value to the graphical comparison. This procedure has a direct application in the FRA based diagnosis because allows failure detection using reliable parameters when the magnetic field of the core is involved.

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Section: Magnetic Core Effect In the Fra Tracesmentioning

confidence: 94%

Section: Magnetic Core Effect In the Fra Tracesmentioning

confidence: 99%

Section: Magnetic Core Effect In the Fra Tracesmentioning

confidence: 99%

Section: A Case 1: Power Transformer In Healthy Conditionmentioning

confidence: 99%

See 2 more Smart Citations

Novel procedure for low frequency FRA traces interpretation

Herrera

Aponte

González-García

et al. 2012

2012 XXth International Conference on Electrical Machines

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“…Transformer is one of the most important equipment in power system [1], which is mainly used to transfer electrical energy between two or more circuits through electromagnetic induction. In the course of using this equipment, some factors such as electrical, thermal, and mechanical stresses may lead to irreversible damage to the insulating material [2].…”

Section: Introductionmentioning

confidence: 99%

Data‐Driven Fault Diagnosis Method for Power Transformers Using Modified Kriging Model

Ding

Liu

2017

Mathematical Problems in Engineering

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A data-driven fault diagnosis method that combines Kriging model and neural network is presented and is further used for power transformers based on analysis of dissolved gases in oil. In order to improve modeling accuracy of Kriging model, a modified model that replaces the global model of Kriging model with BP neural network is presented and is further extended using linearity weighted aggregation method. The presented method integrates characteristics of the global approximation of the neural network technology and the localized departure of the Kriging model, which improves modeling accuracy. Finally, the validity of this method is demonstrated by several numerical computations of transformer fault diagnosis problems.

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