Partial discharges: keys for condition monitoring and diagnosis of power transformers

2018 ◽  
pp. 39-85 ◽  
Author(s):  
Ricardo Albarracin ◽  
Guillermo Robles ◽  
Jorge Alfredo Ardila-Rey ◽  
Andrea Cavallini ◽  
Renzo Passaglia
Keyword(s):  
Condition Monitoring ◽  
Partial Discharges ◽  
Power Transformers ◽  
Monitoring And Diagnosis

scholarly journals Review of Fiber Optic Diagnostic Techniques for Power Transformers

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1789 ◽  
Author(s):  
Janvier Sylvestre N’cho ◽  
Issouf Fofana
Keyword(s):  
Condition Monitoring ◽  
Fiber Optic ◽  
Diagnostic Techniques ◽  
Test Methods ◽  
Partial Discharges ◽  
Power Transformers ◽  
Economic Losses ◽  
Safe Operation ◽  
Service Interruptions ◽  
Conventional Test

Diagnostic and condition monitoring of power transformers are key actions to guarantee their safe operation. The subsequent benefits include reduced service interruptions and economic losses associated with their unavailability. Conventional test methods developed for the condition assessment of power transformers have certain limitations. To overcome such problems, fiber optic-based sensors for monitoring the condition of transformers have been developed. Flawlessly built-up fiber optic-based sensors provide online and offline assessment of various parameters like temperature, moisture, partial discharges, gas analyses, vibration, winding deformation, and oil levels, which are based on different sensing principles. In this paper a variety and assessment of different fiber optic-based diagnostic techniques for monitoring power transformers are discussed. It includes significant tutorial elements as well as some analyses.

A strategy to locate partial discharges in power transformers using acoustic emission

2007 ◽  
Vol 1 (05) ◽  
pp. 596-600 ◽  
Author(s):  
Giscard Franceire Cintra Veloso ◽  
◽  
Luiz Eduardo Borges da Silva ◽  
Germano Lambert-Torres
Keyword(s):  
Acoustic Emission ◽  
Partial Discharges ◽  
Power Transformers

Research on transformer vibration monitoring and diagnosis based on Internet of things

2021 ◽  
Vol 30 (1) ◽  
pp. 677-688
Author(s):  
Zhenzhuo Wang ◽  
Amit Sharma
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Power Transformers ◽  
Normal Operation ◽  
Analysis Method ◽  
Power Distribution Network ◽  
Monitoring And Diagnosis ◽  
Distribution Transformers

Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

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