Research progress and application of online coal quality and coal quantity analyses
The coal industry urgently needs real-time access to comprehensive information on coal quality and quantity for its digital trans-formation.Based on analyzing the industrial application requirements for comprehensive analysis of coal quality and quantity,this paper focuses on the technical principles,research status,and industrial application of spectroscopic techniques represented by laser-induced breakdown spectroscopy(LIBS)and multispectral fusion with other spectroscopic techniques.It also discusses the artificial intelligence-based coal quality and quantity detection methods represented by image analysis.Then,based on the industrial application scenarios of dif-ferent technologies,we need to analyze the technical limitations of real-time coal quality and quantity online detection technology in indus-trial applications.These limitations include detection accuracy issue based on technical principles,equipment stability issue caused by complex environmental factors,algorithm analysis issue based on large-scale data processing,technical applicability,and flexibility issue in the entire coal industry chain,respectively.Finally,four development suggestions for future comprehensive analysis and online detec-tion technology of coal quality and quantity were proposed,they are research on coal quality online detection technology considering geo-logical conditions,research on industrial-scale multispectral fusion technology,research on comprehensive analysis of coal quality and quantity using spectroscopy and image analysis techniques and in-depth research on the application of intelligent technologies in real-time coal quality and quantity detection,respectively.Coal quality online detection is a complex field that involves multiple disciplines and spe-cialized knowledge.It relies on interdisciplinary scientific and technological fields such as coal petrography,spectroscopy,instrument en-gineering,data processing,pattern recognition,artificial intelligence,and machine learning.Establishing industrial application scenario-coal quality and coal quantity parameters-actual application guidance databases is an important direction for achieving intelligent coal quality and coal quantity online detection and obtaining comprehensive coal quality and coal quantity information.
万方数据
维普
