Data Driven Modelling of Centrifugal Compressor Maps for Control and Optimization Applications

We apply Gaussian process regression to the problem of centrifugal compressor performance modelling using hyperparameter optimisation. We test the proposed approach for compressor pressure ratio and efficiency prediction using compressor maps from four different machines and compare the performance of Gaussian process regression with multivariate polynomial regression. Gaussian process regression is found to outperform multivariate polynomial regression for this task especially when a small number of training samples are available. The proposed approach can therefore be a suitable method for online adaptation of centrifugal compressor maps for control and optimisation applications when dealing with fouling and other sources of compressor performance degradation.