基于回归模型的数字双胞胎,用于工业动态交叉流过工艺
Matthias Heusel1, Gunnar Grim2, Joel Rauhut2
1Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.
Bioengineering (Basel, Switzerland)
|March 27, 2024
概括
为动态交叉流过 (DCF) 过程开发了一个数字双胞胎,实时优化设置点. 这种先进的技术在工业葡萄汁过中提高了15%的植物生产率.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 过程控制 过程控制
- 生物技术是生物技术.
背景情况:
- 动态交叉流过 (DCF) 对于食品和生物制药行业的固体液体分离至关重要.
- 目前的工业DCF工艺由于固定的操作配方,往往表现不佳.
- 不同的生物料材料特性需要适应性过程控制.
研究的目的:
- 为一个工业棕色领域的DCF工厂开发一个数字双胞胎.
- 为了提高流程效率,近乎实时优化设定点决策.
- 调整DCF操作以适应生物料流的动态特性.
主要方法:
- 一个结合过规律和专家知识的机械经验过程模型形成了数字双胞胎的核心.
- 基于模型的实验设计评估了参数对生产力的影响.
- 一个循环程序促进了双向通信,监控过程动态 (膜扭矩,跨膜压力) 和优化透流速设置点.
主要成果:
- 使用24个工业葡萄汁过批次 (2022-2023) 的数据训练了一种回归元模型.
- 数字双胞胎的实施导致2023年竞选活动平均生产率增加15%.
- 数字双胞胎框架通过基于混合模型的算法证明了对已建立的工业过程的有效控制.
结论:
- 开发的数字双胞胎框架成功优化了动态交叉流过过程.
- 接近实时的设置点优化显著提高了工业设备的生产率.
- 基于混合模型的方法可转移到其他生化和生物工艺应用中.
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