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基于体素加权的无线电层析成像图像的稻米水分含量测定新方法。

A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images.

机构信息

Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia.

Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia.

出版信息

Sensors (Basel). 2021 May 26;21(11):3686. doi: 10.3390/s21113686.

DOI:10.3390/s21113686
PMID:34073162
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8197968/
Abstract

This manuscript presents a new method to monitor and localize the moisture distribution in a rice silo based on tomography images. Because the rice grain is naturally hygroscopic, the stored grains' quality depends on their level of moisture content. Higher moisture content leads to fibre degradation, making the grains too frail and possibly milled. If the moisture is too low, the grains become brittle and are susceptible to higher breakage. At present, the single-point measurement method is unreliable because the moisture build-up inside the silo might be distributed unevenly. In addition, this method mostly applies gravimetric analysis, which is destructive. Thus, we proposed a radio tomographic imaging (RTI) system to address these problems. Four simulated phantom profiles at different percentages of moisture content were reconstructed using Newton's One-Step Error Reconstruction and Tikhonov Regularization algorithms. This simulation study utilized the relationship between the maximum voxel weighting of the reconstructed RTI image and the percentage of moisture content. The outcomes demonstrated promising results, in which the weighting voxel linearly increased with the percentage of moisture content, with a correlation coefficient higher than 0.95 was obtained. Therefore, the results support the possibility of using the RTI approach for monitoring and localizing the moisture distribution inside the rice silo.

摘要

本手稿提出了一种基于断层图像监测和定位粮库中水分分布的新方法。由于稻谷具有天然吸湿性,储存稻谷的质量取决于其水分含量水平。较高的水分含量会导致纤维降解,使稻谷过于脆弱,可能无法碾磨。如果水分过低,稻谷会变得脆弱,更容易破碎。目前,单点测量方法不可靠,因为筒仓内的水分积聚可能分布不均匀。此外,这种方法主要应用重量分析,具有破坏性。因此,我们提出了一种放射性断层成像(RTI)系统来解决这些问题。使用牛顿一步误差重建和 Tikhonov 正则化算法对四个不同水分含量百分比的模拟体模轮廓进行了重建。这项模拟研究利用了重建的 RTI 图像中最大体素加权与水分含量百分比之间的关系。结果表明,加权体素与水分含量百分比呈线性增加,相关系数高于 0.95,这表明使用 RTI 方法监测和定位粮库内水分分布是可行的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/5b74d7bbcd1d/sensors-21-03686-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/bb92246dd294/sensors-21-03686-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/e9a435857d82/sensors-21-03686-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/d975466a288c/sensors-21-03686-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/b138ac7af69a/sensors-21-03686-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/f48847279c1f/sensors-21-03686-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/d584ce767b7e/sensors-21-03686-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/5b74d7bbcd1d/sensors-21-03686-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/bb92246dd294/sensors-21-03686-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/e9a435857d82/sensors-21-03686-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/d975466a288c/sensors-21-03686-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/b138ac7af69a/sensors-21-03686-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/f48847279c1f/sensors-21-03686-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/d584ce767b7e/sensors-21-03686-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ca2/8197968/5b74d7bbcd1d/sensors-21-03686-g007.jpg

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本文引用的文献

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A small and slim coaxial probe for single rice grain moisture sensing.一种用于单粒稻谷水分检测的小巧、纤细的同轴探头。
Sensors (Basel). 2013 Mar 14;13(3):3652-63. doi: 10.3390/s130303652.
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