Assessment of the noise influence on power transformer failure characterization

• Grant number: 23/13076-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date until: December 01, 2023
• End date until: November 30, 2024
• Field of knowledge: Engineering - Electrical Engineering
• Principal Investigator: Bruno Albuquerque de Castro
• Grantee: Eduardo Oliveira Angerami de Castro
• Host Institution: Faculdade de Engenharia (FE). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil

Abstract

The diagnosis of partial and full discharges in power transformers is directly related to monitoring the integrity of the insulation system of this device. Therefore, discharge monitoring systems can avoid outages and improve maintenance management. One of the most promising methodologies for discharge diagnosing is the acoustic emission technique, in which piezoelectric transducers are coupled to the transformer wall, to sense the acoustic waves emitted by the discharges. Although effective, there are many scientific and technological challenges. For example, it is known that piezoelectric transducers are sensitive to low-frequency noises such as those generated by vibrations, as well as uniform white noise, commonly produced by ventilation systems, sunlight, etc. Therefore, in real applications, as opposed to controlled measurements, different types of noise can impair the conclusions about the transformers' operating conditions. Hence, the objective of this project is to investigate the influence of noise sources in the characterization of two types of failures in transformers: total discharges, which generally occur inside the transformer, when electrical arcs arise due to spots without insulation in its winding, and the partial discharges on the insulators, which are surface discharges caused by contamination of the surface by dust or any other material that is deposited there. Therefore, at the end of this study, it is expected to provide a more comprehensive overview of the influence of noise in the characterization of the mentioned faults and also to provide contributions to the advancement of diagnostic and monitoring techniques for transformers in environments where noise sources are present, as in measurements in power substations.