COMPUTATIONAL MODELING OF GAS COMPRESSOR DIAGNOSTICS USING GENETIC PROGRAMMING

• Main Author: SAFIYULLAH, FEROZKHAN
• Format: Thesis
• Language: English
• Published: 2016
• Subjects: TJ Mechanical engineering and machinery
• Online Access: 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/

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.