Study On The Key Problems Of Analyzing Trace Composition Of Alloy Based On DP-LIBS

Laser Induced Breakdown Spectroscopy(LIBS)is widely used in the field of metallurgical analysis because of its features such as no pretreatment of samples,rapid analysis of multiple elements at the same time,and remote real-time online detection.In this paper,the double-pulse laser induced breakdown spectroscopy(DP-LIBS)was used to detect the trace elements in the alloy steel,and some key issues in the detection process,such as the outside atmosphere,the acquisition delay of the spectrometer,the energy ratio and inter-pulse delay time of the two-pulse,and the influence of sample temperature were studied.At the same time,this article also studied how to improve the stability and accuracy of the trace elements in the alloy steel by DP-LIBS analysis.For the application of DP-LIBS in the detection of alloy steels,this article will elaborate on the following organizational structure:First of all,we mainly introduce the research purpose and significance of this article and the development status of LIBS.Secondly,the experimental equipment and LIBS quantitative analysis method used in this paper are introduced.The design experiment was then started with a focus on the detection of carbon in solid-state alloy steels.The effects of ambient gas atmosphere,spectrometer acquisition delay times,energy ratios and inter-pulse delay time of the two-pulse on the measurement results were studied.We focus on combining plasma image and carbon element spectral information to discuss the dual-pulse ablation mechanism with different pulse interval times.Based on the above key issues,the experimental conditions were optimized.The internal standard method and absolute strength method were used to quantitatively analyze the carbon element in alloy steel,and the results of single pulse and double pulse analysis were compared.The final analysis results show that the internal standard method can effectively overcome the influence of experimental conditions fluctuations and improve the accuracy of quantitative analysis of carbon in alloy steel samples.The appropriate pulse interval can effectively improve the spectral characteristics and detection sensitivity of collinear DP-LIBS so that the calibration model has better linear correlation.Next,we mainly use collinear DP-LIBS to carry out experiments on the detection of carbon,chromium,manganese and silicon elements in alloy steel.Unlike previous studies,this study focused on the influence of sample temperature changes on the plasma spectrum.First of all,it is found that the spectral intensity exhibits a nonlinear increasing trend with increasing sample temperature through experiments.Secondly,the plasma temperature of solid alloy steel and liquid alloy steel was calculated by using the Boltzmann plane method,and the reason why the spectral intensity was enhanced was discussed.Finally,in order to overcome the influence of the sample temperature,a neural network with nonlinear fitting ability was introduced for quantitative analysis and compared with the analysis result of the internal standard method.The research results show that compared with the internal standard method,the neural network analysis results are better in terms of stability and accuracy.The thesis document ends with a general conclusion and outlooks.