In real fermentation processes, the sensor signal quality is often affected by various external factors - stirrer speed, reactor overpressure, volume changes, addition of antifoam agents, etc. Often, these external factors cause rapid changes or jumps in the sensor signal, which can significantly affect the accuracy of the measurements. In order to avoid this, it is recommended to use different filters of the sensor signal, which would reduce or even exclude the influence of the mentioned factors as much as possible.
In this regard, a new mathematical algorithm was developed, with the help of which it is possible to identify and minimize the rapid influence of external factors (change in the speed of the bioreactor mixer, adding an antifoam solution) on the environmental turbidity and dielectric permeability sensor signals. The mentioned method made it possible to reduce the influence of the mentioned sensor signal jumps on the accuracy of cell biomass measurements by 5- and 2-fold, respectively.
Overview of in-situ environmental turbidity and dielectric spectroscopy sensor signal filtering results:
More information - https://doi.org/10.3390/s21041268
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