COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS USING GENETIC PROGRAMMING
Gas compressor diagnostics are vital in oil and gas industry because of the equipment criticalitywhich 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 re...
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2016
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oai:utpedia.utp.edu.my:214782024-07-25T00:26:58Z http://utpedia.utp.edu.my/id/eprint/21478/ COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS USING GENETIC PROGRAMMING SAFIYULLAH, FEROZKHAN TJ Mechanical engineering and machinery Gas compressor diagnostics are vital in oil and gas industry because of the equipment criticalitywhich 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 equipmentmanufacturer (OEM). Delayed decision on compressor maintenance intervention would cause prolonged downtime due to poorreadiness of spare parts and resources. The objective of this work is to develop a diagnosticmodel for gas compressor in oil and gas industry using the novel approach of genetic programming that can overcome the maintenance problems in relation to prediction of downtime. The maintenance activity of the gas compressor canbepredicted bycalculating the performance degradation. 2016-10 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/id/eprint/21478/1/2015-MECHANICAL-COMPUTATIONAL%20MODELING%20GAS%20COMPRESOR%20DIAGNOSTICS%20USING%20GENETIC%20PROGRAMMING-FEROZKHAN%20SAFIYULLAH.pdf SAFIYULLAH, FEROZKHAN (2016) COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS USING GENETIC PROGRAMMING. Masters thesis, Universiti Teknologi PETRONAS. |
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TJ Mechanical engineering and machinery SAFIYULLAH, FEROZKHAN COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS USING GENETIC PROGRAMMING |
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Gas compressor diagnostics are vital in oil and gas industry because of the equipment
criticalitywhich 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 equipmentmanufacturer
(OEM). Delayed decision on compressor maintenance intervention would cause
prolonged downtime due to poorreadiness of spare parts and resources. The objective
of this work is to develop a diagnosticmodel for gas compressor in oil and gas industry
using the novel approach of genetic programming that can overcome the maintenance
problems in relation to prediction of downtime. The maintenance activity of the gas
compressor canbepredicted bycalculating the performance degradation. |
format |
Thesis |
author |
SAFIYULLAH, FEROZKHAN |
author_facet |
SAFIYULLAH, FEROZKHAN |
author_sort |
SAFIYULLAH, FEROZKHAN |
title |
COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS
USING GENETIC PROGRAMMING |
title_short |
COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS
USING GENETIC PROGRAMMING |
title_full |
COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS
USING GENETIC PROGRAMMING |
title_fullStr |
COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS
USING GENETIC PROGRAMMING |
title_full_unstemmed |
COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS
USING GENETIC PROGRAMMING |
title_sort |
computational modeling of gas compressor diagnostics
using genetic programming |
publishDate |
2016 |
url |
http://utpedia.utp.edu.my/id/eprint/21478/1/2015-MECHANICAL-COMPUTATIONAL%20MODELING%20GAS%20COMPRESOR%20DIAGNOSTICS%20USING%20GENETIC%20PROGRAMMING-FEROZKHAN%20SAFIYULLAH.pdf http://utpedia.utp.edu.my/id/eprint/21478/ |
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