Study On Gas Raman Spectroscopy For On-line Detection Of Coal-to-gas System

Coal-to-gas technology has become an essential part of clean energy development in China,with the advantages of its cleanness,efficiency,and environment-friendly.The online detection of Coal-to-gas ensures efficient production.The traditional online-detection system combines a variety of detection technologies,resulting in a long detection cycle and a vast of restrictions.Therefore,it is difficult to meet the rapid development requirements of coal-to-gas technology.The development of a novel and efficient online detection system for coal-to-gas has become a hot issue in the field of clean energy intelligent manufacturing.In this thesis,an on-line detection strategy of pressurized catalytic coal-to-gas based on gas Raman spectroscopy was proposed for the six essential gases in production control according to the gasification characteristics.According to the design points of the coal-to-gas on-line detection,a gas Raman online detection device was established based on previous research.A Raman spectral analysis method was further proposed based on the characteristics of gas Raman spectra.Thus,a Gas Raman Spectroscopy for On-line Detection of Coal-to-gas System(GRS-ODCS)is formed combined with the device and the analysis method.On this basis,GRS-ODCS was innovatively applied to the actual production of coal-to-gas,and has carried out experiments for three months in Yinchuan,Xinzhou,Ordos and other coal to gas bases.Two functional modules of abnormal state warning and decision guidance of coal-to-gas production are expanded based on the accurate on-line detection of the coal-to-gas process and the analysis of the pressurized catalysis technology.The thesis explored and summarizes five key factors that affect the production of coal-to-gas and established the corresponding relationship between state information and decision guidance.Thus,the primary transformation of the gas Raman coal gasification on-line detection system from a pure data collector to a data analyst was completed.The thesis evaluated and tested the system to validate the effectiveness of GRS-ODCS.The model test result illustrated the six key components has an excellent linear correlation due to the relative error that does not exceed 2.0%,and the average value of R~2 is 0.994.The result of the comparison test with the conventional coal-to-gas online detection system showed the excellent abnormal state warning and decision-guidance capabilities of GRS-ODCS.These satisfactory results show that the GRS-ODCS has good accuracy and reliability of the analysis,providing accurate information support for coal gas and coal gas intelligent manufacturing.