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使用数据同化改进低成本传感器的校准

Diego Alberto Aranda Britez¹, Alejandro Tapia Córdoba¹, Princy Johnson²

¹Department of Engineering, Universidad Loyola Andalucía, Avda. de las Universidades, s/n, Dos Hermanas, 41704 Seville, Spain.

Sensors (Basel, Switzerland)

|December 17, 2024

概括

在智能农业中,使用数据同化来校准低成本传感器,提高了准确的土壤湿度监测. 颗粒过器 (PF) 方法提高了84.8%的精度,超过了代组合光滑器 (IES).

科学领域:

农业工程农业工程
环境科学环境科学
数据科学数据科学数据科学

背景情况:

精确的土壤湿度监测对于智能农业至关重要,优化灌和作物产量.
低成本的电容式土壤湿度传感器提供了可负担性,但存在准确性问题,导致效率低下的做法.

研究的目的:

提出用于校准电容式土壤湿度传感器的数据同化方法.
为了提高用于精密农业应用的低成本土壤湿度传感器的准确性.

主要方法:

集成了Hydrus 1D模型与颗粒过器 (PF) 和Iterative Ensemble Smoother (IES) 进行传感器校准.
实施了物理约束,以确保更新的参数保持在可信范围之内.
使用滴灌农场的数据验证了该方法,将PF和IES与高精度参考传感器进行比较.

主要成果:

数据同化显著提高了传感器读取精度,使它们与参考测量和模型模拟保持一致.
颗粒过器 (PF) 方法的准确性比原始传感器读数提高了84.8%.
代组合光滑器 (IES) 方法提供了68%的精度改进,尽管其性能优于PF.

结论:

数据同化是准确农业大规模实施的一个强大而实用的方法.
在低成本的电容性土壤湿度传感器中,PF方法有效地减轻了观测噪声和传感器偏差.
这种校准技术提高了用水效率和作物产量潜力.

关键词:

校准校准的时间数据同化数据同化土壤湿度传感器的土壤湿度传感器

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