Professor Mateus Giesbrecht (Unicamp) presented advances in his wind energy projects at the 50th edition of IECON (the annual international conference of the IEEE Industrial Electronics Society). The event was held from November 3 to 6 last year in Chicago (USA) and one of its focuses was the development of diagnostic methods for electrical machines used in the energy transition.

Through four posters, Giesbrecht, who coordinates the CINE Energy Generation program, presented methods that can allow early detection of faults in wind turbines, more specifically, in the bearings (parts that support the rotating shaft of the turbines and that, when they fail, can cause major damage to the machine).

“The subject of the works was to study how to detect faults in bearings simply by measuring their vibration or the electrical current in the electrical generator that is part of the rotating machine”, says the researcher. The studies used computational techniques, including machine learning, to extract information that indicates the existence of failures. “If the techniques are implemented in commercial turbines, there will be the possibility of early detection of failures, enabling a maintenance plan to be implemented,” he says.

According to Giesbrecht, IECON 2024 had a major impact on the international academic community in the field of industrial electronics, in addition to contributing to the creation of new partnerships between research institutions and companies in the sector.