一种用于酸溶液蒸发的新预测方法,整合了工艺知识和数据驱动的时空适应模型
Sen Xie1, Yuyang Hua2, Zhijiang Lou1
1Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen 518060, PR China.
ISA transactions
|January 6, 2024
概括
本研究引入了一种新的生产预测方法,将工艺知识和数据驱动模型整合起来. 新方法提高了工艺控制的准确性,并减少了能源消耗,以实现更绿色的制造.
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
- 材料科学 材料科学 材料科学
背景情况:
- 生产的蒸发过程对于资源回收和减少污染至关重要.
- 当前的离线质量评估导致不精确的过程控制和高能耗.
- 需要加强预测方法,以确保绿色和高效的生产.
研究的目的:
- 开发和验证生产的新型预测方法.
- 将流程知识与数据驱动的时空适应模型集成.
- 提高工艺控制精度,减少蒸发过程中的能源消耗.
主要方法:
- 数据协调技术用于预处理生产数据.
- 基于材料和热传递原理的机制建模.
- 使用双重局部加权内核PLS与时间差异和移动窗口模型的错误补偿.
- 集成数据驱动和基于过程知识的模型.
主要成果:
- 综合模型在工业酸溶液蒸发案例中证明了可行性.
- 在±2%的误差范围内实现了超过90%的预测准确性.
- 有效估计实际产品质量,提高预测可靠性.
结论:
- 开发的混合模型为生产中准确的质量预测提供了强大的解决方案.
- 这种方法有助于实现绿色和高效的制造实践.
- 该方法有效地解决了传统离线质量评估的局限性.
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