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Dataset of distribution transformers for predictive maintenance.
Bravo M, Diego-A; Alvarez Q, Laura-I; Lozano M, Carlos-A.
Afiliação
  • Bravo M DA; Universidad del Cauca, Calle 5 Nro. 4-70, Popayán 190001, Colombia.
  • Alvarez Q LI; Universidad del Valle, Calle 13 Nro. 100-00, Santiago de Cali 760001, Colombia.
  • Lozano M CA; Universidad del Valle, Calle 13 Nro. 100-00, Santiago de Cali 760001, Colombia.
Data Brief ; 38: 107454, 2021 Oct.
Article em En | MEDLINE | ID: mdl-34703850
In electricity sector is possible to collect large quantities of data that contain information on relevant processes and events that occur in a given period. It gives a knowledge of the different operation conditions of the electrical network and its components. Through the treatment and analysis of these data is possible to propose market, cost reduction, reduction of failures and repairs in machines and inventory decrease strategies. Grid operator can implement strategies to improve indicators of reliability and quality of service. From a maintenance point of view, the equipment operating time is a relevant aspect to identify and solve failures without service suspensions. This paper aims to show distribution transformers failures characteristics data using historical data collected by the grid operator (Compañia Energética de Occidente) at Cauca Department (Colombia), under the cooperation of the Universidad del Cauca and Universidad del Valle. The dataset could be helpful to researchers and data scientists who use machine learning to develop applications that help engineers in predictive maintenance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Data Brief Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Colômbia País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Data Brief Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Colômbia País de publicação: Holanda