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Previous issue date: 2017-07-03 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / Alarmes industriais tem natureza inerentemente ass?ncrona e s?o fundamentais para a
manuten??o da seguran?a operacional e sa?de de processos industriais complexos. Entretanto,
sistemas de alarmes industriais mal configurados tendem a gerar quantidades
excessivas de alarmes, o que os tornam ineficientes. Dentre os poss?veis agentes degradantes
de um sistema de alarmes, est?o os alarmes causais. Situa??es de alarmes causais
ocorrem quando a ativa??o de um determinado alarme implica na ativa??o de um ou mais
alarmes decorrentes, gerando informa??o redundante no sistema de alarmes. Diante da relev?ncia
do problema, nesta disserta??o s?o analisados os desempenhos de duas t?cnicas
para determina??o de alarmes causais: correla??o cruzada e teste de causalidade de Granger.
Como dados de alarmes industriais s?o essencialmente de natureza discreta, antes de
se aplicar ambas as t?cnicas, houve a necessidade de se realizar um pr?-processamento
sobre os dados de alarmes, atrav?s de uma t?cnica de suaviza??o de sinais. Para obten??o
dos resultados, foram utilizados dados de alarmes provenientes de cen?rios de simula??o
de gera??o de alarmes e do Benchmark Tennessee Eastman Process. Os resultados obtidos
indicam que, em aspectos gerais, o teste de causalidade de Granger obteve maior
efici?ncia que a correla??o cruzada na tarefa de indica??o de rela??es causais em alarmes
industriais. Tamb?m foram realizados estudos comparativos da aplica??o do teste de
causalidade de Granger sobre vari?veis de processo e alarmes no Benchmark Tennessee
Eastman Process, indicando suas caracter?sticas. / Industrial alarms are inherently asynchronous in nature and are critical to maintaining
the operational safety and health of complex industrial processes. However, poorly configured
industrial alarm systems tend to generate excessive amounts of alarms, making
them inefficient. Among the possible degrading agents of an alarm system are the causal
alarms. Causal alarm situations occur when the activation of a given alarm implies the
activation of one or more of the resulting alarms, generating redundant information in the
alarm system. Given the relevance of the problem, this dissertation analyzes the performance
of two techniques for determining causal alarms: Cross-correlation and Granger
causality test. The industrial alarm data is essentially of a discrete nature, before performing
both techniques, there was a need to perform a preprocessing on the alarm data,
through the signal smoothing technique. To obtain the results, we used alarm data from
the alarm generation simulation scenarios and the Tennessee Eastman Process Benchmark.
Therefore, the results indicate that, in general aspects, the Granger causality test
performed a greater efficiency than the cross-correlation in the task of indicating causal
relations between industrial alarms. We also performed comparative studies of the application
of the Granger causality test on process variables and alarms in the Tennessee
Eastman Process Benchmark, indicating their characteristics.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/24011 |
| Date | 03 July 2017 |
| Creators | Miranda, Tiago Fernandes de |
| Contributors | 21929564287, Silva, Ivanovitch Medeiros Dantas da, 04665499462, Munaro, Celso Jos?, 43102158072, Oliveira, Luiz Affonso Henderson Guedes de |
| Publisher | PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA EL?TRICA E DE COMPUTA??O, UFRN, Brasil |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| 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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