| 面向小型化传感器的海水硝酸盐紫外检测波长优化与仿真研究 |
| Wavelength Optimization and Simulation for Miniaturized Ultraviolet Nitrate Sensors in Seawater |
| 投稿时间：2025-09-29 修订日期：2025-12-15 |
| DOI： |
| 中文关键词: 硝酸盐检测 紫外光谱 传感器小型化 有限波长 随机森林 低功耗 |
| 英文关键词:Nitrate Detection Ultraviolet Spectroscopy Sensor Miniaturization Limited Wavelengths Random Forest Low-Power Consumption |
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| 中文摘要: |
| 面向小型化、低功耗原位传感器的迫切需求,发展基于有限特征波长的检测方法是实现海水硝酸盐紫外光谱技术工程应用的关键。紫外光谱法虽具原位监测潜力,但传统宽谱扫描方案难以满足传感器小型化与低功耗要求,且其精度受海水复杂组分严重干扰。本研究旨在为解决这一核心问题提供方案。通过构建高保真仿真模型,我们精确模拟了硝酸盐紫外吸收、溴离子等干扰效应及仪器噪声。本研究的核心是提出一种“有限最优波长”检测策略,并利用随机森林算法进行波长智能筛选与非线性建模,以期用最少的硬件通道实现最优的检测性能。仿真结果表明,仅需三个优选波长(229、230、290 nm),所建模型即可达到决定系数(R2)0.965、残差相对误差约为2.87%的精度,显著优于传统方法。该策略极大降低了对光源与分光系统的要求,为开发基于特定紫外发光二极管的小型、低功耗传感器奠定了坚实基础。本研究为海水硝酸盐传感器的微型化与实用化提供了从理论模型、波长配置到智能算法的全链路设计依据。。 |
| 英文摘要: |
| Addressing the urgent need for miniaturized and low-power in-situ sensors, developing detection methods based on a limited set of characteristic wavelengths is key to the practical engineering application of ultraviolet (UV) spectroscopic technology for seawater nitrate detection. While UV spectroscopy holds potential for in-situ monitoring, traditional broad-spectrum scanning approaches are unsuitable for sensor miniaturization and power constraints, and their accuracy is severely compromised by complex seawater constituents. This study aims to provide a solution to this core challenge. A high-fidelity simulation model was constructed to accurately replicate nitrate UV absorption, interference effects (e.g., from bromide), and instrumental noise. The core of this research is to propose a "limited optimal wavelengths" detection strategy, employing the Random Forest algorithm for intelligent wavelength selection and non-linear modeling, with the goal of achieving optimal detection performance using the fewest hardware channels. Simulation results demonstrate that using only three selected wavelengths (229, 230, 290 nm), the established model achieves a coefficient of determination (R2) of 0.965 and a residual relative error of approximately 2.87%, significantly outperforming traditional methods. This strategy dramatically reduces the requirements for light sources and optical systems, laying a solid foundation for developing compact, low-power sensors based on specific UV light-emitting diodes (UV-LEDs). This research provides a comprehensive design rationale, encompassing theoretical models, wavelength configuration, and intelligent algorithms, for the miniaturization and practical application of seawater nitrate sensors. |
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