ICA algorithm based on recursively updating of feature space and application to fermentation process monitoring
Updating the monitoring model timely to address the time-variant characteristics has vital significance in detecting abnormalities of chemical process and equipment breakdown exactly.The conventional ICA-based methods used to update the model have a high computational load and low efficiency.RUFS-ICA algorithm was proposed to model and monitor a fed-batch penicillin fermentation process on line.Compared with conventional ICA methods,the proposed method reduced the false alarm rate to 1.67% and basically overcame alarm failures.Compared with other methods,the algorithm could greatly decrease the computation time by about 54.1%,and saved the memory.