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Previous issue date: 2014-06-27 / The industries are getting more and more rigorous, when security is in question, no
matter is to avoid financial damages due to accidents and low productivity, or when it s
related to the environment protection. It was thinking about great world accidents around
the world involving aircrafts and industrial process (nuclear, petrochemical and so on)
that we decided to invest in systems that could detect fault and diagnosis (FDD) them.
The FDD systems can avoid eventual fault helping man on the maintenance and exchange
of defective equipments. Nowadays, the issues that involve detection, isolation, diagnose
and the controlling of tolerance fault are gathering strength in the academic and industrial
environment. It is based on this fact, in this work, we discuss the importance of techniques
that can assist in the development of systems for Fault Detection and Diagnosis (FDD)
and propose a hybrid method for FDD in dynamic systems. We present a brief history
to contextualize the techniques used in working environments. The detection of fault
in the proposed system is based on state observers in conjunction with other statistical
techniques. The principal idea is to use the observer himself, in addition to serving as an
analytical redundancy, in allowing the creation of a residue. This residue is used in FDD.
A signature database assists in the identification of system faults, which based on the
signatures derived from trend analysis of the residue signal and its difference, performs
the classification of the faults based purely on a decision tree. This FDD system is tested
and validated in two plants: a simulated plant with coupled tanks and didactic plant with
industrial instrumentation. All collected results of those tests will be discussed / As ind?strias est?o cada vez mais rigorosas quando o assunto ? seguran?a, tanto para
evitar preju?zos financeiros com acidentes e baixa produtividade, quanto para preservar
o meio ambiente. Diante dos grandes acidentes em todo o mundo envolvendo aeronaves
e processos industriais (nucleares, petroqu?micos etc) procurou-se investir em sistemas
que pudessem detectar e diagnosticar falhas (FDD-Fault Detection and Diagnosis). Os
sistemas FDD podem evitar eventuais falhas auxiliando o homem na manuten??o e troca
de equipamentos defeituosos. Nos dias de hoje os assuntos que envolvem detec??o, isolamento,
identifica??o e diagn?stico de falhas est?o ganhando for?a no meio acad?mico e
industrial. Diante deste impulso, neste trabalho ser? discutido a import?ncia do estudo de
t?cnicas que possam auxiliar o desenvolvimento de sistemas de detec??o e diagn?stico de
falhas e proposto um m?todo h?brido para a detec??o e diagn?stico de falhas em sistemas
din?micos. Um breve hist?rico ? apresentado de forma a contextualizar as t?cnicas utilizadas
no trabalho. A detec??o de falhas pelo sistema proposto ? baseada em observadores
de estado juntamente com outras t?cnicas estat?sticas. A ideia principal ? utilizar o pr?prio
observador, para al?m de servir como redund?ncia anal?tica, permitir a cria??o de um
res?duo que ser? utilizado na detec??o da falha e tamb?m no seu diagn?stico. Um banco
de assinaturas auxiliar? o sistema de identifica??o de falhas, que, baseado nas assinaturas
oriundas das an?lises de tend?ncia do sinal do res?duo e sua derivada, ir? realizar a classifica??o
das falhas baseada em uma ?rvore de decis?o. Este sistema FDD ser? submetido
a alguns testes e valida??es em duas plantas: uma planta simulada de tanques acoplados
e em uma planta did?tica com instrumenta??o industrial. Os resultados colhidos desses
ensaios se mostraram satisfat?rios para um grupo de falhas testadas e ser?o discutidos no
decorrer do trabalho
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/15255 |
| Date | 27 June 2014 |
| Creators | Vale, Marcelo Roberto Bastos Guerra |
| Contributors | CPF:42046637100, http://lattes.cnpq.br/0477027244297797, Martins, Allan de Medeiros, CPF:01979076448, http://lattes.cnpq.br/4402694969508077, Casillo, Danielle Simone da Silva, CPF:02796900452, http://lattes.cnpq.br/2111858571672626, Gabriel Filho, Oscar, CPF:11376040697, http://lattes.cnpq.br/4171033998524192, Moreira, Vicente Delgado, CPF:02118457448, http://lattes.cnpq.br/4549279470957332, Maitelli, Andr? Laurindo |
| Publisher | Universidade Federal do Rio Grande do Norte, Programa de P?s-Gradua??o em Engenharia El?trica, UFRN, BR, Automa??o e Sistemas; Engenharia de Computa??o; Telecomunica??es |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/doctoralThesis |
| Format | application/pdf |
| Source | reponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN |
| Rights | info:eu-repo/semantics/openAccess |
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