masterThesis
Análise de desempenho de técnicas de indicação de causalidade aplicadas a alarmes industriais
Fecha
2017-07-03Registro en:
MIRANDA, Tiago Fernandes de. Análise de desempenho de técnicas de indicação de causalidade aplicadas a alarmes industriais. 2017. 86f. Dissertação (Mestrado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2017.
Autor
Miranda, Tiago Fernandes de
Resumen
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.