Quantitative Analysis Of The Liquid Steel Components Based On LIBS

The level of industrialization is an important indicator to measure the degree of economic development. The total iron and steel has become an important index to measure a national industrialized level. Therefore, the requirements for the iron and steel quality are increasingly high. The composition of iron and steel is very complex. It’s smelting is conducted in the harsh environment, such as high temperature and so on. Therefore the real-time detection of steel components is very difficult. It is high time to develop a new technology to apply to the smelting industry so that we can conduct on-line detection of liquid steel components.Laser induced breakdown spectroscopy(LIBS) is a no-contact measurement without sample pretreatment. It can achieve the simultaneous measurement of multiple elements so that it has gradually introduced to the actual work of liquid steel composition. Every element has its unique feature spectral lines. Through spectral analysis to judge the type and content of elements.Through experiments can study on the mechanism of the formation of characteristic elements in the whole process of experiment and the analysis of spectral line effects of other factors. It has studied the influence of spectral lines intensity affected by temperature and concentration of plasma. LIBS is applied to the qualitative analysis on the study liquid steel. Based on the laser induced breakdown spectroscopy to measure the composition of molten steel. Detailed introduces is made to the method for analysis of LIBS steel liquid online quantitative liquid steel. The study showed that the internal standard method is applied to LIBS analysis, there is choosing a steel factory production of steel as the research object. The content of the Mn element is verified by the internal standard method, and using the method of spectral line selection to reduce the measurement error. The results show that quantitative analysis choose the correct analysis line, can make the calibration curve fitting is more than 90%, relative standard deviation less than 1% of the measurement result.