Analysis on Behaviour of Wavelet Coefficient during Fault Occurrence in Transformer

Sreewirote, Bancha; Ngaopitakkul, Atthapol

doi:10.1088/1755-1315/127/1/012008

Cited by 1 publication

(1 citation statement)

References 5 publications

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“…On the basis of constructing the above insulation fault information acquisition model of power transformer, the high resolution spectrum feature extraction and fault on-line monitoring system of power transformer insulation fault are carried out [ 11 ]. In this paper, an on-line monitoring method of power transformer insulation fault based on Bayesian network is proposed, and the power transformer insulation fault feature detection is carried out by using Bayesian network feature decomposition model.…”

Section: On-line Monitoring Of Insulation Fault Of Power Transformermentioning

confidence: 99%

On-line Monitoring Method of Power Transformer Insulation Fault Based on Bayesian Network

Chen

Tan²,

Liu³

2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Power transformer insulation fault location is the key to improve the stability of power transformer. A Bayesian network based on power transformer insulation fault on-line monitoring method is proposed. The Bayesian network characteristic decomposition model is used to detect the insulation fault of power transformer, the high-resolution spectrum characteristic quantity of insulation fault of power transformer is extracted, the load balance analysis is carried out according to the output voltage and load difference of power transformer, the Bayesian network detection model of insulation fault of power transformer is constructed. Combined with PCI integrated information processor and relay transmission node network topology model, the on-line monitoring system design of power transformer insulation failure is realized. The simulation results show that the fault location of power transformer insulation is accurate and the visual resolution of fault is strong.

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Section: On-line Monitoring Of Insulation Fault Of Power Transformermentioning

confidence: 99%

On-line Monitoring Method of Power Transformer Insulation Fault Based on Bayesian Network

Chen

Tan²,

Liu³

2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

View full text Add to dashboard Cite

show abstract

Analysis on Behaviour of Wavelet Coefficient during Fault Occurrence in Transformer

Cited by 1 publication

References 5 publications

On-line Monitoring Method of Power Transformer Insulation Fault Based on Bayesian Network

On-line Monitoring Method of Power Transformer Insulation Fault Based on Bayesian Network

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