Online Detection in the Separation Process of Tobacco Leaf Stems as Biomass Byproducts Based on Low Energy X-Ray Imaging

Zhu, Wenkui; Chen, Liangyuan; Wang, Bin; Zhaogai, Wang

doi:10.1007/s12649-017-9890-4

Cited by 6 publications

(5 citation statements)

References 17 publications

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Section: Calculation Methods Of Stem Mass From X-ray Imagementioning

confidence: 99%

“…Equation ( 4) can be simplified to the following Equation (5), in which σ, N, and A are assumed to be constant based on the assumption that the substances are consistent in the tobacco stems. [5] I I e Ba   0 where B = σ(Z,E)N/A is a constant; a = ρt is the area density of the medium. Equation ( 5) can be consequently transformed into: [6] Ba I I  ln 0 Notably, it can be easily found that the degree of X-ray attenuation is directly related to the area density of the tobacco stems according to Equation (6).…”

Section: Calculation Methods Of Stem Mass From X-ray Imagementioning

confidence: 99%

“…This method is well applicable to fully stripped stems with respect to accuracy. However, as to the leaves still containing stems, there could be similar suspension velocities to leaves, causing difficulty to remove the stems using the air classification method (5). The manual picking method is often used in tobacco primary processing to detect the content of stems with different morphologies, such as long stems (length > 20 mm) and thick stems (diameter > 2.38 mm) (4).…”

Section: Resumementioning

confidence: 99%

“…Thus, the stem content will be overestimated usually, based on the weight of the rejected stems. With low energy X-ray imaging, an identification method of stems from threshed tobacco leaves has been developed in our previous study (5). Compared to the visible light imaging, this method can precisely recognize the stems whether containing leaves or being wrapped by leaves.…”

Section: Resumementioning

confidence: 99%

“…In our previous work (5), the details of image preprocessing, segmentation, and stem identification have been given, as seen from step 1 to step 3 in Figure 4. The present work developed the quantitative algorith of stem mass further.…”

Section: Stem Recognition Algorithm From X-ray Imagementioning

confidence: 99%

See 4 more Smart Citations

Nondestructive Detection of Stem Content in Tobacco Strips Using X-Ray Imaging Analysis

Zhu

Liu

Zhang

et al. 2022

Contributions to Tobacco &Amp; Nicotine Research

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Summary For tobacco strips used in cigarette production, the stem content is an important quality index to assess the impurity level of the cut leaves. The presented work developed a nondestructive detection method of stems in cut leaf agricultural products by the low energy X-ray imaging. The algorithm of stem image processing and weight calculation principle was established, and then a machine vision system with X-ray imaging and image analysis was set up to verify the quantitative detection method. The results showed that the relative error of the detection method ranged from −3.64% to 2.76%. The determination of stems with a different morphology, such as the thick stem, were also realized based on the image analysis. The accuracy of determining thick stem and long stem was 94.67% and 99.33%, respectively. The developed method is superior to the current ISO detection method of tobacco stem in leaves under the same testing conditions in terms of accuracy and efficiency, which could be applied as an effective online detection method to monitor the quality of processed leaf for cigarette production.

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Section: Calculation Methods Of Stem Mass From X-ray Imagementioning

confidence: 99%