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Universidade Federal do Rio de Janeiro

Análise modal operacional de uma bomba centrífuga submersa utilizando a decomposição melhorada no domínio da frequência

Abstract

dc:description.abstract

The identification of modal parameters of electrical submersible pumps (ESP) is part of the process of increasing the reliability of this equipment, which is installed in places that are inaccessible, from a maintenance point of view, for oil exploitation, such as offshore oil wells and seabed, so that any type of intervention is very costly, in addition to production loss. This work aims to identify the modal parameters, that is, the natural frequencies, damping rates and vibration modes of an ESP installed in a mock well through operational and impact tests. The operational modal analysis method employed was the Enhanced Frequency Domain Decomposition (EFDD). The same method was used to identify the modal parameters through impact tests. An EFDD algorithm was developed and tested using theoretical signals and impact test performed on a metal bar. In the case study, using an ESP, the identified modal parameters were compared with those obtained using commercial software and a time domain modal identification algorithm known as Eigen Realization Algorithm (ERA).

Degree

thesis:*
Grantor dc:publisher
Universidade Federal do Rio de Janeiro
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Huamani, Jairo Alvaro Cotaquispe
Advisor dc:contributor.advisor
  • Silva Neto, Severino Fonseca da

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • Acesso Aberto
Language dc:language
por

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11422/7409
OAI identifier oai:identifier
oai:pantheon.ufrj.br:11422/7409

Chain of custody

source
Harvested from
Brazil UERJ
Base URL
pantheon.ufrj.br/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Huamani, Jairo Alvaro Cotaquispe. Análise modal operacional de uma bomba centrífuga submersa utilizando a decomposição melhorada no domínio da frequência. Universidade Federal do Rio de Janeiro, 2017. http://hdl.handle.net/11422/7409