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Original scientific paper

https://doi.org/10.17559/TV-20200926113750

Applying Artificial Neural Network to Optimize the Performance of the Compressor Station: A Case Study

Ivan Đuračić* orcid id orcid.org/0000-0003-0819-2476 ; University of Slavonski Brod, Mechanical Engineering Faculty, Trg I. B. Mazuranic 2, 35000 SlavonskiBrod, Croatia
Marinko Stojkov ; University of Slavonski Brod, Mechanical Engineering Faculty, Trg I. B. Mazuranic 2, 35000 SlavonskiBrod, Croatia
Tomislav Šarić ; University of Slavonski Brod, Mechanical Engineering Faculty, Trg I. B. Mazuranic 2, 35000 SlavonskiBrod, Croatia
Tomislav Alinjak ; HEP-ODS d.o.o. Zagreb, Elektra Slavonski Brod, P. Krešimira IV 11, 35000 SlavonskiBrod, Croatia
Krešimir Crnogorac orcid id orcid.org/0000-0001-8882-0879 ; CONSTRUO-MAT d.o.o., Trg Ignjata Alojza Brlića 4, Slavonski Brod, Croatia


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Abstract

This paper presents the implementation of a reprogrammable PLC system as a monitoring control tool in the actual operating environment of a compressor station. A neural network is used to recognize the temperature pattern and to predict the temperature on the compressor station. A cooling system is installed for the optimization purpose of the observed system. The research was conducted in three stages in real working conditions within the production hall. The difference in temperatures with and without the added cooling system is shown. There are gaps in this research that represent opportunities for future development, therefore recommendations for further research are given.

Keywords

compressor; fan; IoT; neural network; optimization; preventive maintenance

Hrčak ID:

260792

URI

https://hrcak.srce.hr/260792

Publication date:

22.7.2021.

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