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Research on CO_2 Detection System in Refrigerated Compartment of Agricultural Products Based on TDLAS Technology

机译：基于TDLAS技术的农产品冷藏隔室CO_2检测系统研究

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摘要

In the process of transporting refrigerated vehicle, the respiration of agricultural products after collection produces CO~(_2) and other gases, resulting in pollution, deterioration, and waste. This paper uses TDLAS technology to design the CO_2 detection system in refrigerated compartments, which is specially designed to deal with external disturbance factors such as detector noise, optical interference fringes and low temperature in refrigerated compartments. At last, it analyzes several CO_2 data preprocessing methods, for example, starting point alignment, bulky error rejecting, sampling point wavelength corresponding, multicycle average, smooth filtering and eigenvalue extraction. The experiment shows that the data preprocessing method of current tuning in this system can accurately detect CO_2 in refrigerated compartments. The total average relative concentration error is 1.2%, and the root mean square error is 0.07%, which provides a reliable technical support to food quality improve and refrigerated preservation of agricultural products.
机译：在输送式冷藏车的过程中，农产品的收集之后的呼吸产生CO〜（_2）和其它气体，造成污染，变质，和浪费。本文利用TDLAS技术来设计CO_2检测系统在冷藏室，其被特别设计来处理外部干扰因素，如检测器噪声，光学干涉条纹和在冷藏室低温。最后，分析了几个CO_2数据预处理的方法，例如，起点对准，笨重错误拒绝，采样点对应的波长，多周期平均，平滑滤波和特征值提取。实验表明，预处理当前调谐的方法在该系统中的数据能够准确地检测在CO_2冷藏隔室中。总的平均相对浓度误差为1.2％，和根均方误差为0.07％，这提供了对食品质量的可靠的技术支持和提高农产品的冷藏保存。

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