将可扩展的自适应混合建模框架更接近工业用途:在多个规模的真菌发酵上应用
Thomas Rydal1, Jesper Frandsen2, Gisela Nadal-Rey1
1Fermentation Pilot Plant, Novonesis A/S, Bagsværd, Denmark.
Biotechnology and bioengineering
|March 8, 2024
概括
这项研究开发了复杂的真菌发酵的数字影子,改善了实时监控和控制. 数字影子框架增强了流程优化和扩展,使数字双胞胎更接近工业用途.
科学领域:
- 生物技术和生物化学工程 生物技术和生物化学工程
- 工艺系统工程 工艺系统工程
- 工业微生物学 工业微生物学
背景情况:
- 数字化为发酵提供了先进的过程控制,但在复杂的工业应用中面临着挑战.
- 由于有限的测量和缺乏生物质数据,很难优化真菌发酵过程.
研究的目的:
- 开发和验证一个复杂的试点规模的真菌发酵过程的数字影子.
- 为应对实时监测,控制和优化工业发酵的挑战.
主要方法:
- 使用试点规模发酵数据开发数据驱动的软传感器,用于基质 (葡萄糖) 估计.
- 创建一个混合软传感器,将数据驱动和质量平衡模型结合起来,用于糖和生物质估计.
- 将机械模型与混合软传感器结合起来,建立一个数字影子建模框架.
主要成果:
- 一个数据驱动的软传感器在试点规模上实现了2%的N-RMSE用于血糖估计,在实验室规模上达到7.8%的N-RMSE.
- 混合软传感器估计糖醇和生物质分别为11%和21%的N-RMSE.
- 与单独的机械模型相比,数字影子框架显著提高了流程可预测性.
结论:
- 开发的数字影子框架增强了真菌发酵过程的理解和控制.
- 这种方法促进了数字影子的工业实施,以改善流程开发和扩展.
- 这项研究为工业生物技术中基于的先进工艺开发铺平了道路.
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