Time‐of‐flight prediction for fermentation process monitoring

Hoche, Sven; Hussein, Walid; Hussein, Mostafa; Becker, Thomas

doi:10.1002/elsc.201000177

Cited by 10 publications

(10 citation statements)

References 30 publications

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“…A MB2S transducer (General Electrics, 2 MHz centre frequency) and a rectangular excitation pulse of a half period duration were applied to generate the ultrasound signal. The time of flight (TOF) was analysed via cross‐correlation and root approximation as presented in (Hoche et al ., ). Relativising the covered distance, l to the passed time, TOF determines the speed of sound, USV:

USV = \frac{l}{TOF}

…”

Section: Materials Methods and Experimental Set‐upmentioning

confidence: 99%

Critical process parameter of alcoholic yeast fermentation: speed of sound and density in the temperature range 5–30 °C

Hoche

Hussein

Becker

2014

Int J of Food Sci Tech

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Summary To implement process analytical technology in beer manufacturing, a systematic study of the ternary system water–maltose–ethanol with respect to the critical process parameters, density, speed of sound and temperature was performed. The results are presented in the form of temperature and mass‐fraction‐dependent polynomial expressions. On average, a variation of 1% mass fraction maltose results in variations of 3.548 m s−1 ultrasound velocity and 0.0041 g cm−³ density, whereas in the case of ethanol, the variations are 8.060 m s−1 and −0.0018 g cm−3. Indeed, the relations are strictly nonlinear. Nevertheless, the determined data show the feasibility to predict online, concentrations of multicomponent mixtures of polar liquids by determining density and ultrasound velocity. With <0.1% error, the measured data show excellent agreement with reference data of binary mixtures as given in literature.

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USV = \frac{l}{TOF}

…”

Section: Materials Methods and Experimental Set‐upmentioning

confidence: 99%

Critical process parameter of alcoholic yeast fermentation: speed of sound and density in the temperature range 5–30 °C

Hoche

Hussein

Becker

2014

Int J of Food Sci Tech

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“…That might be the reason why most researchers oversample the data. In fact, mathematical approximation is a feasible solution to achieve higher accuracies with less time resolution (Hoche et al, 2011;Hoppe et al, 2001). Apart from that, when echo detection in pulse echo mode becomes problematic (e.g.…”

Section: Reference Analytics Validation and Uncertainty Considerationsmentioning

confidence: 99%

Ultrasound-based density determination via buffer rod techniques: a review

Hoche¹,

Hussein²,

Becker³

2013

J. Sens. Sens. Syst.

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Abstract. The review presents the fundamental ideas, assumptions and methods of non-invasive density measurements via ultrasound at solid-liquid interface. Since the first investigations in the 1970s there has been steady progress with regard to both the technological and methodical aspects. In particular, the technology in electronics has reached such a high level that industrial applications come within reach. In contrast, the accuracies have increased slowly from 1-2 % to 0.15 % for constant temperatures and to 0.4 % for dynamic temperature changes. The actual work reviews all methodical aspects, and highlights the lack of clarity in major parts of the measurement principle: simplifications in the physical basics, signal generation and signal processing. With respect to process application the accuracy of the temperature measurement and the presence of temperature gradients have been identified as a major source of uncertainty. In terms of analytics the main source of uncertainty is the reflection coefficient, and as a consequence of this, the amplitude accuracy in time or frequency domain.

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“…As the influences of sugar and ethanol on sound velocity are additive but nonlinear at different temperatures and concentrations of the solvents, the concentrations of ethanol and sugar could be determined by measuring the ultrasonic velocity at two different temperatures [13]. Furthermore the authors used ultrasonic velocity determination based on time of flight analysis in time domain for fermentation process control [14]. Since in bioprocesses, cells and nutrients are mixed together, this paper corroborates the dependence of ultrasonic attenuation and velocity on varying maltose and yeast concentrations in aqueous electrolyte suspensions.…”

Section: Introductionmentioning

confidence: 99%

Effects of yeast and maltose concentration on ultrasonic velocity and attenuation coefficient and its application for process monitoring

Geier

Heermann

Hussein

et al. 2014

Engineering in Life Sciences

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Monitoring substrate and cell concentration is important for controlling yeast propagation and fermentation processes. This usually requires two instruments, a density meter, and an optical turbidity meter. This paper presents a method for simultaneously determining yeast and maltose concentration with a single ultrasonic sensor. Ultrasonic velocity and attenuation were measured at varying maltose and yeast cell concentrations from 0 to 4 wt%. Ultrasonic velocity increased linearly with both yeast (R 2 = 0.999) and maltose concentration (R 2 = 0.996). In contrast, while attenuation coefficient depended linearly on yeast concentration (R 2 = 0.998), it did not significantly depend on maltose concentration (R 2 = 0.476). To draw conclusions about the main mechanisms of attenuation, the measured attenuation coefficients for yeast cells at 2 MHz were compared to predicted values. With a mean absolute percentage error of 0.25%, intrinsic absorption, thermal effects, and, to a lesser extent, viscous effects were identified as the main reason for damping. These results support the feasibility of combining ultrasonic velocity and attenuation measurements for estimating yeast cell and maltose concentration.

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Time‐of‐flight prediction for fermentation process monitoring

Cited by 10 publications

References 30 publications

Critical process parameter of alcoholic yeast fermentation: speed of sound and density in the temperature range 5–30 °C

Critical process parameter of alcoholic yeast fermentation: speed of sound and density in the temperature range 5–30 °C

Ultrasound-based density determination via buffer rod techniques: a review

Effects of yeast and maltose concentration on ultrasonic velocity and attenuation coefficient and its application for process monitoring

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