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Anti-corrosion wood automatic sorting robot system based on near-infrared imaging technology

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Abstract

To implement the discovery of discarded anti-corrosion wood, an automatic sorting robot system was built. Three kinds of commonly used wood were selected as the research object, which uses hyperspectral imaging technology to achieve the identification. In the range of 900–1700 nm (230 bands), the infrared spectra of three kinds of anti-corrosion wood were collected, and then the characteristic information was obtained through the analysis of MATLAB to distinguish them. Among them, three kinds of preservative woods are Scots pine (add CCA treatment), Pseudotsuga menziesii (high-temperature carbonization treatment) and Incense Cedar (pressurized treatment). After the pretreatment by the Savitzky-Golay method, spectral data were conducted by principal component analysis (PCA), and the contribution rate of the first three principal components reached 99.902 %. Besides, through the loading coefficients of the first three principal components that were plotted on the wavelength, we obtained five characteristic wavelengths and corresponding reflectance information, simultaneously; this set up a typical discriminant analysis model. Then, the model was validated by the validation set, and the accuracy rate of the prediction set was 98.89 %. This method can effectively identify and classify three kinds of anti-corrosion wood, which can provide a scientific method and basis for a solid waste sorting system.

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Abbreviations

R :

Calibrated hyperspectral image

W :

White calibration i mage

B :

Black calibration i mage

R o :

Original i mage

W 0 :

Weight vector or coefficient vector

W n+1 :

Constant

W = (w1,w2,…,Wn+1):

Augmented weight vector

X′ = (X1,X2,…,Xn,1)T :

Augmented feature vector

r1, r2, r3 :

The identification radius

d1,d2,d3 :

The distance

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Acknowledgments

This research is supported by the “Quanzhou science and technology project” (project No. 2018Z001), Fujian Provincial Natural Science Foundation-funded projects (No. 2017J01086 and No. 2016J01236), and National Natural Science Foundation of China (No. 51505161 and No. 61603144).

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Authors and Affiliations

  1. Key Laboratory of Process Monitoring and System Optimization for Mechanical and Electrical Equipment, Huaqiao University, Fujian Province, China

    Huaxue Jin, Wei Fan, Hua Chen & Yin Wang

Authors
  1. Huaxue Jin
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  2. Wei Fan
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  3. Hua Chen
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  4. Yin Wang
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Corresponding author

Correspondence to Wei Fan.

Additional information

Recommended by Editor Ja Choon Koo

Huaxue Jin is studying for the M.S. at Huaqiao University Xiamen City, Fujian Province, China. Her main research direction is micro/nano drive.

Wei Fan began teaching at Huaqiao University-Xiamen after obtaining his doctorate from Hefei University of Technology. And he has obtained the title of Associate Professor in same university. His main research direction is micro/nano drive.

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Jin, H., Fan, W., Chen, H. et al. Anti-corrosion wood automatic sorting robot system based on near-infrared imaging technology. J Mech Sci Technol 34, 3049–3055 (2020). https://doi.org/10.1007/s12206-020-0636-z

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  • DOI: https://doi.org/10.1007/s12206-020-0636-z

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