| Summary: | The use and application of compressors cannot be overemphasized in the aeronautical and oil & gas industries. Yet research works in sufficient depth has not been conducted previously to analyze their actual behaviour under degraded or even new conditions in operation.
For the purpose of degradation modeling and simulation, a compressor model was set up using thermodynamic equations and affinity laws representing the characteristics of a clean compressor. HYSYS was used for degradation modeling analysis by implanting known linear and nonlinear degradation trends for an operating point and taking the compressor measurement changes. It was then assumed the degradation levels are unknown and these were established by applying the compressor health indices to the new compressor map. A diagnostic method for compressors was developed where the prediction in degradation levels were compared for diagnostic purposes.
By applying a unique “successive iteration method” to a real gas site compressor data at various speeds, a compressor performance adaptation technique has been developed in this thesis which maps out the actual performance of the compressor shows the errors in performance prediction has been reduced from 5-15% to a minimum. This performance adaptation method allows the compressor performance map to be adapted against field data of a compressor for a range of speeds. All data were corrected to a common datum and GPA Indices were utilised for the evaluation of confidence in the established method.
By observing the centrifugal compressor performance data from 2006 to 2010, the actual compressor degradation was quantified and modeled by trending techniques for diagnostic and prognostic purposes so that the operator can plan ahead for maintenance by knowing an estimate for the actual health of the compressor at any time.
The major conclusions are that the performance adaptation developed for the site compressor and the diagnostic technique by data trending has been successful. And estimation of degradation in health indicators (throughput, pressure ratio and efficiency drops) by scaling the measurable parameters is a useful tool for diagnostic purposes.
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