论文信息 - Predicting concentrations of a mixture in bioreactor for on-line monitoring using Raman spectroscopy

Predicting concentrations of a mixture in bioreactor for on-line monitoring using Raman spectroscopy

Abstract On-line monitoring of biological processes is essential for maximizing productivity because reactions are very slow and much effort is required to analyze the composition of bio-product. The Raman spectroscopy is suitable for on-line monitoring of bioprocess with proper analysis algorithms. This work proposes a novel soft-sensor framework based on Raman spectra. It first removes the background effect and further reduces noise using the Rolling-Circle Filter (RCF) and Savitzky-Golay smoothing filter, respectively. Then Partial Least Square (PLS) is used to reduce the dimension of spectra and predict the concentrations based on latent variables. The prediction performance was improved by 30% by applying the proposed methods. The Raman spectrum can be used to analyze the concentrations by using the PLS.

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