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Time-of-flight prediction for fermentation process monitoring

机译:发酵过程监控的飞行时间预测

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This work presents an ultrasound-based inline sensor system, which is used to monitor the alcoholic yeast fermentation. The pulse-echo method is used to determine ultrasound velocity (USV) of the sample medium. The major aim of the paper is to highlight the importance of an accurate time-of-flight (TOF) estimation for accurate concentration determination and to present method immanent strategies to fulfill the requirements. An algorithm aiming at a stable and highly accurate TOF estimation in time domain was developed. The basic methods of the algorithm are a frame-wise signal analysis based on the sensor dimensions, cross-correlation to find complementary impulses and root estimation via polynomial fit to calculate the TOF in time domain. The analysis results of laboratory-scale validation trials (demineralized, vented water) and of real process data (yeast propagation) are presented. In spite of the stable algorithm performance in the lab scale, the algorithm fails in a few cases of real processsignals. The relevant signals and corresponding causes for failure were analyzed and future strategies for algorithm enhancement are discussed. Reviewing the results, the aimed USV accuracy of 0.075 m/s can be achieved. The maximum USV error of the usedprinciples and applied methods in the investigated temperature range is ±0.02%.
机译:这项工作提出了一种基于超声波的在线传感器系统,该系统用于监视酒精酵母发酵。脉冲回波法用于确定样品介质的超声速度(USV)。本文的主要目的是强调准确飞行时间(TOF)估计对于准确浓度确定的重要性,并提出满足要求的方法内在策略。提出了一种针对时域稳定,高精度的TOF估计的算法。该算法的基本方法是基于传感器尺寸的逐帧信号分析,互相关以找到互补脉冲,以及通过多项式拟合求根以在时域中计算TOF。给出了实验室规模的验证试验(去离子水,排放水)和实际过程数据(酵母菌繁殖)的分析结果。尽管在实验室规模上算法性能稳定,但在实际过程信号的少数情况下,算法仍会失败。分析了相关的信号和相应的失败原因,并讨论了算法增强的未来策略。回顾结果,可以实现0.075 m / s的目标USV精度。在研究的温度范围内,所用原理和应用方法的最大USV误差为±0.02%。

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