Power transformers have been described as an important equipment of electrical switchyard in which its failure results in long hours of outage. Some of the existing models for determining the Degree of Polymerization (DP) of power transformers were based on singular parameter which is not sufficient for the assessment of power transformers’ lifespan. This research paper therefore developed a hybridized model for determining the degree of polymerization of power transformers. The study employed the use 2-Furaldehyde (2FAL) content values of 0.5 ppm to 10ppm in determining the DP value and simulation was carried out using MATLAB. The result was compared with existing DP model for effectiveness of the Hybridized DP model. The developed model y...
O principal indicador utilizado para avaliar o estado da isolação sólida em equipamentos de potência...
Transformers are the most expensive and critical asset in any electrical power network. Their failur...
In this work, the application of a feed-forward artificial neural network (FFANN) in predicting the ...
Power transformers are important equipment of the electrical switchyard whose failure leads to long ...
The life expectancy of a transformer is largely depended on the service life of transformer polymer ...
The paper presents the results of research and analysis of literature data on the paper insulation's...
Transformers are generally considered to be the costliest assets in a power network. The lifetime of...
Effective lifetime and maintenance management of a transformer fleet requires precise monitoring of ...
For decades until now, manufacturers and end users alike have been absorbed by the challenge of exte...
At present several approaches are applied to evaluate and control the destruction level, the resourc...
The paper presents the results of a comparative study on accelerated aging of specially designed exp...
The oil-paper insulation in power transformers is subjected to various stresses due to environmental...
Kraft paper in combination with dielectric oil is the most common as insulation system used in power...
ABSTRACT: The analysis of the concentration of furanic compounds in oil has been accepted as one of ...
Oil-immersed transformers use paper and oil as insulation system which degrades slowly during the op...
O principal indicador utilizado para avaliar o estado da isolação sólida em equipamentos de potência...
Transformers are the most expensive and critical asset in any electrical power network. Their failur...
In this work, the application of a feed-forward artificial neural network (FFANN) in predicting the ...
Power transformers are important equipment of the electrical switchyard whose failure leads to long ...
The life expectancy of a transformer is largely depended on the service life of transformer polymer ...
The paper presents the results of research and analysis of literature data on the paper insulation's...
Transformers are generally considered to be the costliest assets in a power network. The lifetime of...
Effective lifetime and maintenance management of a transformer fleet requires precise monitoring of ...
For decades until now, manufacturers and end users alike have been absorbed by the challenge of exte...
At present several approaches are applied to evaluate and control the destruction level, the resourc...
The paper presents the results of a comparative study on accelerated aging of specially designed exp...
The oil-paper insulation in power transformers is subjected to various stresses due to environmental...
Kraft paper in combination with dielectric oil is the most common as insulation system used in power...
ABSTRACT: The analysis of the concentration of furanic compounds in oil has been accepted as one of ...
Oil-immersed transformers use paper and oil as insulation system which degrades slowly during the op...
O principal indicador utilizado para avaliar o estado da isolação sólida em equipamentos de potência...
Transformers are the most expensive and critical asset in any electrical power network. Their failur...
In this work, the application of a feed-forward artificial neural network (FFANN) in predicting the ...