Projeto EfiCiência - PET Engenharia Elétrica da Udesc

EfiCiência is an extension project created, managed and executed by the PET Engenharia Elétrica group at the Santa Catarina State University, Joinville campus. The project works with the community and aims to transform its individuals through educational actions on the efficient and sustainable use of resources. This document brings the history of EfiCiência and illustrates its materials and methods. Some of the most relevant activities developed are also presented, where a great diversity of target audiences can be noted. The results demonstrate contribution of EfiCiência to the society and to the complete and citizen education of its members. This article is expected to assist other PET groups and independent extension programs.O EfiCiência é um projeto de extensão criado, administrado e executado pelo grupo PET Engenharia Elétrica da Universidade do Estado de Santa Catarina, campus Joinville. O projeto atua junto à comunidade e visa transformar seus indivíduos por meio de ações educacionais sobre o uso eficiente e sustentável de recursos. Este documento traz o histórico do EfiCiência e ilustra seus materiais e métodos. São apresentadas também algumas das mais relevantes atividades desenvolvidas, onde nota-se uma grande diversidade de públicos atingidos. Os resultados demonstram a contribuição do EfiCiência para a sociedade e para a formação cidadã e ampla dos integrantes. Espera-se com este artigo auxiliar a outros grupos PET e programas de extensão independentes

Wavelet group method of data handling for fault prediction in electrical power insulators

Electric power is increasingly being used in the globalized day-to-day and keeping the electric power system running is necessary. Insulators are important components of the electric power system. In case of failure in these components, there may be disconnections and, consequently, no electricity. Contaminated insulators can develop irreversible failures if they are not inspected. One equipment used for the inspection of the electric power system is the ultrasound, which generates an audible noise based on a time series that is used to identify possible failures. the time series forecast can be used for possible prediction of the development of failure. In this paper, a hybrid method that uses Wavelet Energy Coefficient (WEC) for feature extraction and Group Method of Data Handling (GMDH) for time series prediction is proposed, being defined as Wavelet GMDH. For comparison and validation of the proposed method, a benchmark is made with well-established algorithms such as Long Short-Term Memory (LSTM) and Adaptive Neuro-Fuzzy Inference System (ANFIS). For a fairer analysis, these algorithms are also evaluated based on the same data extraction with WEC. the proposed method proved to have good accuracy comparing with LSTM and ANFIS, and is much faster than the compared methods.Coordination for the Improvement of Higher Education Personnel (CAPES)National Council of Scientific and Technologic Development of Brazil -(CNPq) [307958/2019-1-PQ, 307966/2019-4-PQ, GS2404659/2016-0-Univ, GS2405101/2016-3-Univ]PRONEX 'Fundacao Araucaria'Fundacao Araucaria [042/2018]info:eu-repo/semantics/publishedVersio