Resumen

RODRIGUEZ RAMOS, Adrián  y  LLANES SANTIAGO, Orestes. Monitoring system based on deep learning in industrial systems. EAC [online]. 2023, vol.44, n.1, pp. 47-57.  Epub 06-Dic-2023. ISSN 1815-5928.

The Industry 4.0 paradigm aims to obtain high levels of productivity and efficiency, more competitive final products, and compliance with demanding regulations related to industrial safety and cyber-security. To achieve these goals, industrial systems must be equipped with condition monitoring systems for the early detection and localization of faults and cyber-attacks. This paper proposes a robust condition-monitoring strategy through the use of Deep Learning algorithms. The proposed scheme was validated using a Tennessee Eastman (TE) process with excellent results. The proposed strategy was compared with other condition monitoring schemes. The higher performance obtained by the proposed scheme indicates its feasibility.

Palabras clave : Industry 4.0; Cybersecurity; Fault diagnosis; Deep learning; monitoring system.

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