| Issue |
MATEC Web of Conferences
Volume 38, 2016
UTP-UMP Symposium on Energy Systems 2015 (SES 2015)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 6 | |
| Section | Thermal Engineering & Energy Conversion | |
| DOI | https://doi.org/10.1051/matecconf/20163801001 | |
| Published online | 11 January 2016 | |
Modeling the Isentropic Head Value of Centrifugal Gas Compressor using Genetic Programming
1 Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Tronoh, 31750, Malaysia
2 Department of Computer & Information Sciences, Universiti Teknologi PETRONAS, Tronoh, 31750, Malaysia
3 PETRONAS Carigali Sdn. Bhd., Kerteh, Terengganu, Malaysia
a Corresponding author: ferozkhan.safiyullah@nct.edu.om
Gas compressor performance is vital in oil and gas industry because of the equipment criticality which requires continuous operations. Plant operators often face difficulties in predicting appropriate time for maintenance and would usually rely on time based predictive maintenance intervals as recommended by original equipment manufacturer (OEM). The objective of this work is to develop the computational model to find the isentropic head value using genetic programming. The isentropic head value is calculated from the OEM performance chart. Inlet mass flow rate and speed of the compressor are taken as the input value. The obtained results from the GP computational models show good agreement with experimental and target data with the average prediction error of 1.318%. The genetic programming computational model will assist machinery engineers to quantify performance deterioration of gas compressor and the results from this study will be then utilized to estimate future maintenance requirements based on the historical data. In general, this genetic programming modelling provides a powerful solution for gas compressor operators to realize predictive maintenance approach in their operations.
Key words: Genetic programming / gas compressor / computational model / predictive maintenance
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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