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Infrared and Laser Engineering, Volume. 50, Issue 9, 20200441(2021)

Quantitative analysis method of unburned carbon content of fly ash by laser-induced breakdown spectroscopy

Weizhe Ma1, Meirong Dong1,3,4, Yongru Huang1, Qi Tong1, Liping Wei1,2,3,4, and Jidong Lu1,3,4
Author Affiliations
  • 1School of Electric Power, South China University of Technology, Guangzhou 510640, China
  • 2Vkan Certification & Technology Co., Ltd., Guangzhou 510663, China
  • 3Guangdong Province Engineering Research Center of High Efficient and Low Pollution Energy Conversion, Guangzhou 510640, China
  • 4Guangdong Province Key Laboratory of Efficient and Clean Energy Utilization, Guangzhou 510640, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
    Equations (14)
    References (36)
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    Figures & Tables(10)
    Schematic diagram of LIBS system

    Fig. 1. Schematic diagram of LIBS system

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    LIBS spectrum of fly ash sample（#1）

    Fig. 2. LIBS spectrum of fly ash sample（#1）

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    Cross validation results of carbon content in fly ash based on MLR model 1 (a), 2 (b), 3 (c)

    Fig. 3. Cross validation results of carbon content in fly ash based on MLR model 1 (a), 2 (b), 3 (c)

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    Cross validation results of carbon content in fly ash based on PLSR model 1 (a), 2 (b), 3 (c)

    Fig. 4. Cross validation results of carbon content in fly ash based on PLSR model 1 (a), 2 (b), 3 (c)

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    Cross validation results of carbon content in fly ash based on ELM model 1 (a), 2 (b), 3 (c)

    Fig. 5. Cross validation results of carbon content in fly ash based on ELM model 1 (a), 2 (b), 3 (c)

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    Cross validation results of carbon content in fly ash based on SVR model 1 (a), 2 (b), 3 (c)

    Fig. 6. Cross validation results of carbon content in fly ash based on SVR model 1 (a), 2 (b), 3 (c)

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    • Table 1. Unburned carbon content of twenty fly ash samples

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      Table 1. Unburned carbon content of twenty fly ash samples

      Sample No. Carbon content (wt.%) Sample No. Carbon content(wt.%) Sample No. Carbon content (wt.%) Sample No. Carbon content (wt.%)
      #11.48#63.27#115.58#168.20
      #21.73#73.68#125.96#178.64
      #31.99#83.97#136.21#189.03
      #42.72#94.46#147.20#199.51
      #52.98#104.89#157.62#2010.43

    • Table 2. Characteristic spectral lines of fly ash samples

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      Table 2. Characteristic spectral lines of fly ash samples

      ElementCharacteristic spectral line/nm
      C193.66, 247.877
      N744.333, 746.932
      O777.21
      Si205.898, 221.167, 221.698, 251.669, 251.983, 252.423, 252.863, 288.165
      Fe248.827, 249.081, 371.952, 373.452, 373.702, 374.534, 374.949, 375.862
      Ca393.356, 396.808, 422.649, 442.577, 443.52, 445.472, 558.857, 610.351, 612.3, 616.278, 643.99, 646.305, 649.433
      Al236.787, 237.24, 257.551, 308.223, 309.311, 394.402, 396.167
      Mg277.976, 285.207, 516.709, 517.316, 519.392

    • Table 3. Prediction results of fly ash carbon content based on MLR and PLSR models

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      Table 3. Prediction results of fly ash carbon content based on MLR and PLSR models

      MLRPLSR
      Cross validation results1Sample No.Reference valueR2=0.96 R2=0.99
      Predicted valueRDRSDPredicted valueRDRSD
      63.27%3.15%3.57%18.93%2.49%23.79%7.66%
      125.96%5.74%3.66%15.15%5.90%0.93%27.61%
      189.03%9.01%0.16%9.10%7.72%14.46%1.28%
      Average value--2.46%14.39%-13.06%12.18%
      Cross validation Results2Sample No.Reference valueR2=0.96 R2=0.99
      Predicted valueRDRSDPredicted valueRDRSD
      52.98%3.32%11.46%6.62%2.72%8.67%46.92%
      115.58%6.02%7.74%33.39%6.39%14.42%25.78%
      178.64%8.97%7.26%15.77%9.05%4.70%11.20%
      Average value--8.97%18.59%-9.26%27.97%
      Cross validation results3Sample No.Reference valueR2=0.96 R2=0.99
      Predicted valueRDRSDPredicted valueRDRSD
      125.96%5.81%2.42%15.15%5.51%7.46%28.95%
      147.20%7.71%7.06%10.74%7.81%8.41%14.16%
      178.64%9.34%8.05%10.19%8.95%3.58%3.68%
      Average value--5.84%12.03%-6.48%15.60%

    • Table 4. Prediction results of carbon content in fly ash based on ELM and SVR models

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      Table 4. Prediction results of carbon content in fly ash based on ELM and SVR models

      ELMSVR
      Cross validation results 1Sample No.Reference valueR2=0.99 R2=0.99
      Predicted valueRDRSDPredicted valueRDRSD
      63.27%3.45%5.51%3.13%3.24%1.02%6.32%
      125.96%6.37%7.00%17.53%5.97%0.25%7.18%
      189.03%8.18%9.35%6.97%8.72%3.36%9.10%
      Average value--7.29%9.21%-1.54%7.53%
      Cross validation results 2Sample No.Reference valueR2=0.99 R2=0.99
      Predicted valueRDRSDPredicted valueRDRSD
      52.98%2.92%1.99%2.63%3.09%3.83%1.17%
      115.58%6.84%22.59%12.51%5.94%6.41%1.99%
      178.64%8.66%0.19%9.31%8.63%0.10%5.51%
      Average value--8.26%8.15%-3.45%2.89%
      Cross validation results 3Sample No.Reference valueR2=0.99 R2=0.99
      Predicted valueRDRSDPredicted valueRDRSD
      125.96%5.46%8.27%4.10%5.86%1.64%6.90%
      147.20%8.49%17.89%13.41%7.72%7.22%4.45%
      178.64%8.55%1.03%3.01%8.79%1.67%10.20%
      Average value--9.06%6.84%-3.51%7.18%
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    Weizhe Ma, Meirong Dong, Yongru Huang, Qi Tong, Liping Wei, Jidong Lu. Quantitative analysis method of unburned carbon content of fly ash by laser-induced breakdown spectroscopy[J]. Infrared and Laser Engineering, 2021, 50(9): 20200441

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    Paper Information

    Category: Lasers & Laser optics

    Received: Dec. 11, 2020

    Accepted: --

    Published Online: Oct. 28, 2021

    The Author Email:

    DOI:10.3788/IRLA20200441

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology