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Degradation detection of submersible electric pumps: application of Artificial Intelligence techniques combined with reliability techniques

Grant number: 25/08216-0
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date: July 01, 2025
End date: June 30, 2026
Field of knowledge:Engineering - Mechanical Engineering - Mechanical Engineering Design
Principal Investigator:Gilberto Francisco Martha de Souza
Grantee:Danilo Giangiardi Pereira da Silva
Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Company:Universidade de São Paulo (USP). Escola Politécnica (EP)
Associated research grant:22/03698-8 - OTIC Offshore Technology Innovation Centre, AP.PCPE

Abstract

The requirement for efficiency in the maintenance of engineering systems aimed at maximizing their operational availability can be achieved by employing intelligent systems for detecting abnormalities that use data from the monitoring system of these physical assets to assess the occurrence of degradation processes in their operational condition. Such systems are based on the use of Artificial Intelligence techniques and aim to provide support for planning the maintenance of engineering systems. However, the development of these detection systems for more complex engineering systems, such as submerged systems used in oil and natural gas exploration, still requires further studies, considering the diversity of failure modes and operational conditions that these systems may present. This research project aims to develop an intelligent system for detecting abnormalities in submerged electric pumps, which are used in the process of extracting oil from oil wells in an offshore environment, which should be based on artificial intelligence techniques associated with reliability techniques, aiming to obtain greater assertiveness in the process. The system developed in the research will be applied in the analysis of electric pump operation data presented in a public data repository. (AU)

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