Optics and Precision Engineering, Volume. 32, Issue 10, 1470(2024)

Study on LIBS system for high-precision coal components rapid and quantitative analysis

Shulin LIU1... Meng WANG1, An LI2, Ying ZHANG2, Xiaodong LIU2 and Ruibin LIU2,* |Show fewer author(s)
Author Affiliations
  • 1School of Mechanical Engineering, Xi’an University of Science and Technology, Xian70054, China
  • 2School of Physics, Beijing Institute of Technology, Beijing100081, China
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    Figures & Tables(15)
    Laser induced breakdown technology coal quality rapid analyzer
    Influence of selecting the number of principal components npc in the process of establishing a coal parameter prediction model based on PCA on the prediction score of the test set. (Left) Determination coefficient R2 (Right) Root mean square error RMSE of prediction results
    Using LIBS industrial on-site equipment to collect coal spectral data and establish a quantitative analysis model
    Validation results of the coal quality rapid quantitative analysis equipment model
    System stability test, the baseline of the bar graph is the true value of the corresponding sample, and the black dashed line in the subgraph identifies the position of ± 1 wt.%
    System stability test, the baseline of the bar graph is the true value of the corresponding sample
    • Table 1. Evaluation results of the effectiveness of prediction models for various parameters of coal quality

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      Table 1. Evaluation results of the effectiveness of prediction models for various parameters of coal quality

      0固定碳灰分挥发分热值
      测试集R20.960 00.989 20.929 20.987 60.933 3
      RMSE1.326 90.971 21.036 80.024 60.674 0
    • Table 2. Statistics of stability test results

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      Table 2. Statistics of stability test results

      参数W1W2W3W4W5
      固定碳/%真值52.5560.2255.9957.0356.88
      平均值51.7460.3955.7956.8957.25
      s0.720.660.600.640.62
      灰分/%真值19.7111.0211.718.778.53
      平均值19.4011.4611.648.798.74
      s0.190.820.130.290.70
      硫/%真值0.330.910.420.960.80
      平均值0.340.920.390.960.78
      s0.040.030.050.080.03

      热值

      (MJ·kg-1

      真值26.4729.6528.3631.3529.43
      平均值26.4431.6728.3731.3129.48
      s0.150.120.090.090.13
    • Table 3. Comparison of dynamic precision experimental records-ash gradient Ⅰ

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      Table 3. Comparison of dynamic precision experimental records-ash gradient Ⅰ

      序号分析仪示值 Ai参比值Ri分析仪示值与参比值之差di
      合计51.2452.161.12
      16.396.520.13
      26.406.520.12
      36.446.520.08
      46.546.520.02
      56.476.520.05
      66.606.520.08
      76.126.520.40
      86.286.520.24
    • Table 4. Comparison of dynamic precision experimental records-ash gradient Ⅱ

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      Table 4. Comparison of dynamic precision experimental records-ash gradient Ⅱ

      序号分析仪示值 Ai参比值Ri分析仪示值与参比值之差di
      合计198.78199.682.36
      124.7624.960.20
      224.8124.960.15
      324.6324.960.33
      424.3624.960.60
      525.1024.960.14
      625.5224.960.56
      724.6124.960.35
      825.0024.960.04
    • Table 5. Comparison of dynamic precision experimental records-ash gradient Ⅲ

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      Table 5. Comparison of dynamic precision experimental records-ash gradient Ⅲ

      序号分析仪示值 Ai参比值Ri分析仪示值与参比值之差di
      合计354.85359.044.65
      144.4544.880.43
      244.8744.880.01
      344.8744.880.01
      443.7944.881.09
      544.2444.880.64
      644.1744.880.71
      743.3544.881.53
      845.1144.880.23
    • Table 6. Record of dynamic precision experiment-gradient total sulfur Ⅰ

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      Table 6. Record of dynamic precision experiment-gradient total sulfur Ⅰ

      序号分析仪示值 Ai参比值Ri分析仪示值与参比值之差di
      合计4.1325.201.07
      10.6150.650.03
      20.5890.650.06
      30.5000.650.15
      40.5090.650.14
      50.4480.650.20
      60.5480.650.10
      70.4930.650.16
      80.4310.650.22
    • Table 7. Record of dynamic precision experiment-gradient total sulfur Ⅱ

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      Table 7. Record of dynamic precision experiment-gradient total sulfur Ⅱ

      序号分析仪示值 Ai参比值Ri分析仪示值与参比值之差di
      合计10.44410.720.52
      11.3011.340.04
      21.3651.340.03
      31.2851.340.05
      41.3311.340.01
      51.2931.340.05
      61.2671.340.07
      71.1651.340.18
      81.4381.340.10
    • Table 8. Prediction error evaluations of various major industrial parameters under different content ranges

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      Table 8. Prediction error evaluations of various major industrial parameters under different content ranges

      不同

      浓度的

      样本

      灰分

      梯度Ⅰ

      梯度

      灰分Ⅱ

      梯度

      灰分Ⅲ

      梯度

      全硫Ⅰ

      梯度

      全硫Ⅱ

      方差0.015 60.041 20.280 40.004 10.002 7
      标准差0.124 70.202 90.529 50.064 30.052 2
      精密度0.320 60.521 41.360 80.165 30.134 2
      准确度0.139 50.295 30.581 70.133 50.065 3
    • Table 9. Summary of Dynamic Precision Comparison Data

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      Table 9. Summary of Dynamic Precision Comparison Data

      项目LIBS人工中子
      重复性再现性重复性再现性重复性再现性
      灰分/%≤150.320.140.20.311.2
      15~300.520.290.30.51.21.6
      ≥301.360.580.50.721.5
      挥发分/%-0.550.31----
      全硫/%-0.150.150.10.20.30.3
      热值/(MJ·kg-1-0.40.450.450.6
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    Shulin LIU, Meng WANG, An LI, Ying ZHANG, Xiaodong LIU, Ruibin LIU. Study on LIBS system for high-precision coal components rapid and quantitative analysis[J]. Optics and Precision Engineering, 2024, 32(10): 1470

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    Paper Information

    Category:

    Received: Nov. 8, 2023

    Accepted: --

    Published Online: Jul. 8, 2024

    The Author Email: LIU Ruibin (liusir@bit.edu.cn)

    DOI:10.37188/OPE.20243210.1470

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