一种基于SDDSI-SPA的稳定变量选择方法,用于在水pH监测中对Vis-NIR光谱的温度校准
Xiaojian Hu1, Lina Li1, Hanjun Su2
1College of Mechanical Engineering and Automation, Huaqiao University, Xiamen, 361021, China. lilina@hqu.edu.cn.
Analytical methods : advancing methods and applications
|June 27, 2025
概括
温度不稳定性会影响使用可见近红外 (Vis-NIR) 光谱的水质分析. 一种新的SDDSI-SPA方法通过选择稳定的光谱特征来提高pH预测的准确性,增强水监测温度校正.
科学领域:
- 环境科学 环境科学
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 温度波动对使用可见近红外 (Vis-NIR) 光谱测定水质有负面影响.
- 传统的光谱校正方法往往无法准确地解决温度诱导的光谱变化,从而降低了水pH值模型预测的准确性.
研究的目的:
- 提出和验证一种新的联合变量选择方法,SDDSI-SPA,用于可靠的温度独立的光谱特征提取.
- 提高在不同温度下监测水质的光谱校准算法的准确性和效率.
主要方法:
- 开发了SDDSI-SPA (初级和二级仪器之间的差异光谱标准偏差 - 连续投影算法) 方法用于联合变量选择.
- 应用了用于光谱校正的直接标准化 (DS) 和零碎直接标准化 (PDS) 算法.
- 通过使用20-60°C温度范围内收集的五个光谱数据集验证了该方法.
主要成果:
- 该SDDSI-SPA方法有效地提取了与pH相关的温度稳定,低对线性光谱特征.
- 与全波长和基于SDDSI的模型相比,SDDSI-SPA与PDS结合显示出优异的跨温度光谱校正.
- 对于30-60°C之间的光谱,实现了0.483的下根平均平方预测误差 (RMSEP).
结论:
- SDDSI-SPA方法提供了一种有效的解决方案,可以减少光谱数据的维度,并纠正温度引起的变化.
- 这种方法在复杂的温度条件下显著提高了Vis-NIR光谱中的水pH预测的准确性.
- 为在不同温度下运行的快速可靠的水质监测系统提供了宝贵的参考.
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