Modification of Duval triangle for diagnostic transformer fault through a procedure of dissolved gases analysis

Desouky, S. S.; Kalas, Ahmed E.; El-Aal, R. A. Abd; Hassan, Abdel Moneim M.

doi:10.1109/eeeic.2016.7555796

Cited by 10 publications

(8 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When an incipient fault occurs in power transformer by either thermal or electrical stresses, the oil decomposes and generates a number of gases dissolve in the transformer oil. These dissolved gases mainly include hydrogen (H 2 ), methane (CH 4 ), ethane (C 2 H 6 ), ethylene (C 2 H 4 ), acetylene (C 2 H 2 ); in addition to that carbon monoxide (CO) and carbon dioxide (CO 2 ) will be present if cellulose degradation is involved [4–7]. These gases can be detected using dissolved gas analysis and then assess the condition of the transformer based on the various gases concentrations which provide good information about the fault type (thermal or electrical) [8].…”

Section: Introductionmentioning

confidence: 99%

Condition assessment of power transformers based on dissolved gas analysis

Gouda

El-Hoshy

E.L.-Tamaly

2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Condition assessment of power transformers based on dissolved gas analysis

Gouda

El-Hoshy

E.L.-Tamaly

2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…4. (25) The gases used in this method are CH 4 , C 2 H 4 , and C 2 H 2 . Before using Duval's triangle, it is important to determine whether it can be used.…”

Section: Duval's Trianglementioning

confidence: 99%

Automated Dissolved Gas Analysis Report Generator for Monitoring Condition of High-voltage Transformers

Chanchotisatien¹,

Phumpho²

2021

Sensors and Materials

View full text Add to dashboard Cite

Dissolved gas analysis (DGA) is a commonly used method that allows pending or occurring faults within transformers to be determined. DGA has been widely used for many years. There are various DGA techniques, including the evaluation of individual and total dissolved combustible gas (TDCG) concentrations, the Doernenburg method, the Rogers method, and Duval's triangle. To facilitate the process of monitoring the condition of transformers and reduce potential human error, we discuss how to create a user-friendly system to monitor and evaluate the condition of high-voltage transformers. The system receives key gas values, which are extracted from oil samples inside transformers obtained by gas chromatography (GC), and is capable of automatically generating downloadable reports of specified transformers and gives insight on any faults found. It also visualizes the changes in extracted key gas values of transformers over time. To develop this system, the front end of the application was made with HTML and CSS, and the back end was made with JavaScript with MySQL as a database combined with Microsoft SharePoint. The automatic downloadable report generator was made with Power Automate. This system assists the monitoring of transformer conditions.

show abstract

“…The original classification scheme for Duval's triangle proposed in [8] evaluates the relative amount of three gasses (C2H2, CH4, C2H4) and classifies them within the coordinates of a triangle. Fault regions within the triangle can be transformed into a numerical classification method as displayed in Table 9 [22]. Table 9.…”

Section: Appendixmentioning

confidence: 99%

“…Table 9. Duval's classification ratios [22]. The classification intervals in Table 9 can be discretized through the coding shown in Table 10.…”

Section: Appendixmentioning

confidence: 99%

Power transformer dissolved gas analysis through Bayesian networks and hypothesis testing

Aizpurua

Catterson

Stewart

et al. 2018

IEEE Trans. Dielect. Electr. Insul.

View full text Add to dashboard Cite

Accurate diagnosis of power transformers is critical for the reliable and cost-effective operation of the power grid. Presently there are a range of methods and analytical models for transformer fault diagnosis based on dissolved gas analysis. However, these methods give conflicting results and they are not able to generate uncertainty information associated with the diagnostics outcome. In this situation it is not always clear which model is the most accurate. This paper presents a novel multiclass probabilistic diagnosis framework for dissolved gas analysis based on Bayesian networks and hypothesis testing. Bayesian network models embed expert knowledge, learn patterns from data and infer the uncertainty associated with the diagnostics outcome, and hypothesis testing aids in the data selection process. The effectiveness of the proposed framework is validated using the IEC TC 10 dataset and is shown to have a maximum diagnosis accuracy of 88.9%.

show abstract

Modification of Duval triangle for diagnostic transformer fault through a procedure of dissolved gases analysis

Cited by 10 publications

References 5 publications

Condition assessment of power transformers based on dissolved gas analysis

Condition assessment of power transformers based on dissolved gas analysis

Automated Dissolved Gas Analysis Report Generator for Monitoring Condition of High-voltage Transformers

Power transformer dissolved gas analysis through Bayesian networks and hypothesis testing

Contact Info

Product

Resources

About