在蒸发过程中母液度的软感应建模,基于简化的强大的最小平方支向量机器
Xiaoshan Qian1, Lisha Xu2, Xinmei Yuan1
1College of Physical Science and Engineering Technology, Yichun University, Yichun 336000, China.
Mathematical biosciences and engineering : MBE
|December 5, 2023
概括
本研究引入了一种新的软测量策略,用于在线检测生产中的母液度. 先进的模型提高了关键过程控制的准确性和跟踪能力.
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
- 数据科学数据科学数据科学
背景情况:
- 蒸发过程在生产中至关重要.
- 母液度是一个关键的控制参数,需要准确的在线监测.
- 现有的在线检测方法由于过程复杂性和数据可变性而面临挑战.
研究的目的:
- 开发一种高效准确的软测量策略,用于在线检测母液度.
- 为了应对过程变量波动和变量间合所带来的挑战.
- 提高软传感模型在工业应用中的性能.
主要方法:
- 使用灰色相关性分析和内核主要组件分析来进行数据维度缩小和特征提取.
- 采用了简化的强大的最小平方支向量机 (LSSVM) 来进行主要组件建模和预测.
- 实现了一个改进的模式搜索-微分演化 (PS-DE) 算法用于LSSVM参数优化.
主要成果:
- 成功降低了流程数据的输入维度和计算复杂性.
- 开发了一个LSSVM模型,对主要组件进行了增强的预测性能.
- 使用拟议的PS-DE算法优化了LSSVM参数,从而实现了卓越的模型准确性.
- 工业数据验证显示出出色的跟踪能力和更高的准确性.
结论:
- 拟议的软测量策略,集成先进的数据分析和机器学习技术,对于在线母液度检测非常有效.
- 该方法为生产中的实时过程监控提供了强大的解决方案.
- 增强型号的精度和跟踪性能使其适用于关键的工业控制应用.
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