The 10th International Conference on Energy, Resources, Environment and Sustainable Development (ERESD 2024)

  In this study, we employed spark emission spectroscopy to develop a real-time analysis technique for detecting the concentration of metal components in coal dust. Quantitative measurements of Al, Si, Fe, Ca, and Ti elements in lignite, bituminous, and anthracite coals were conducted. Two experimental setups were designed, and data obtained from measurements were used for model calibration. The R² values of all calibration curves were approximately 0.90. Except for Si in lignite, the limit of detection (LOD) of other measured elements were within 0-40 ng. Comparative analysis with standard instruments revealed normalized root mean square error (NRMSE) concentrations of 9.1%, 9.8%, 10.7%, 24%, and 8.2% for various elements in lignite. This shows the effectiveness of spark emission spectroscopy in coal dust composition analysis, demonstrating high sensitivity and detection efficiency. Additionally, principal component analysis (PCA) was employed to identify coal sample categories, confirming the method's capability in distinguishing coal dust types.


 

Spark emission spectroscopy,Coal dust,Composition Measurement,PCA