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

被引：2

作者：

Duracic, Ivan ^{[1
]}

Stojkov, Marinko ^{[1
]}

Saric, Tomislav ^{[1
]}

Alinjak, Tomislav ^{[2
]}

Crnogorac, Kresimir ^{[3
]}

机构：

[1] Univ Slavonski Brod, Mech Engn Fac, Trg IB Mazuranic 2, Slavonskibrod 35000, Croatia

[2] HEP ODS doo Zagreb, Elektra Slavonski Brod, P Kresimira IV 11, Slavonskibrod 35000, Croatia

[3] CONSTRUO MAT doo, Trg Ignjata Alojza Brlica 4, Slavonski Brod, Croatia

来源：

TEHNICKI VJESNIK-TECHNICAL GAZETTE | 2021年 / 28卷 / 04期

关键词：

compressor; fan; IoT; neural network; optimization; preventive maintenance; PREDICTION; LOGIC; SYSTEM;

D O I：

10.17559/TV-20200926113750

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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.

引用

页码：1197 / 1202

页数：6

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