ABSTRACT
Selecting proper characteristic lines from enormous spectral intensities is crucially important to implement quantitative analysis of Laser-Induced Breakdown Spectroscopy using internal standard method. Manual selecting of characteristic lines by researchers is time consuming and energy consuming, which cannot guarantee the best result. An automatic method to select analytical and reference lines for internal standard method from the original spectra based on Genetic Algorithm was proposed in this paper. This method was utilized to select analytical and reference lines for internal standard methods from LIBS of Mn, Ni, Cr, Si and Fe of low alloy steels. The optimal characteristic lines optimized by this method were the analytical line 403.306 8 nm of Mn and the corresponding reference line 368.745 7 nm of Fe, the analytical line 288.157 7 nm of Si and the corresponding reference line 427.176 1 nm of Fe, the analytical line 286.510 0 nm of Cr and the corresponding reference line 272.753 9 nm of Fe and the analytical line 352.453 6 nm of Ni and the corresponding reference line 358.698 5 nm of Fe, respectively. Then these elements were quantified by the internal standard method using these selected lines. The results showed that this proposed method for selecting characteristic lines can automatically select the optimal analytical and reference lines and could guarantee the best quantitative result obtained by internal standard method.
ABSTRACT
In order to realize real-time, online monitoring of the component of steel and other metal smelting process, we designed a remote double-pulse laser-induced breakdown spectroscopy (LIBS) analysis system which can realize non-contact remote measurement and component analysis for long distance sample. The paper first tests the system on solid standard steel samples, which provides basis for online monitoring the component of molten steel. The experimental results showï¼laser focal spot is about 1mm in long distance; double-pulse ablation depth is deeper than single pulse's; the optimum delay of double-pulse is non-consistent in different distances; the enhancement effect of double- pulse in 3.1 m is better than that in 2.1 mï¼and the maximum enhancement is 5.19 of Ti(â ) 319.99 nm; the calibration curve of R2 is about 0.99, RSD being less than 5%, RMSE being less than 0.021%, LOD being less than 500 ppm for most elements in 2.1 m, which is better than that in 3.1 m.
ABSTRACT
In the present paper both the partial least squares (PLS) method and the calibration curve (CC) method are used to quantitatively analyze the laser induced breakdown spectroscopy data obtained from the standard alloy steel samples. Both the major and trace elements were quantitatively analyzed. By comparing the results of two different calibration methods some useful results were obtained: for major elements, the PLS method is better than the CC method in quantitative analysis; more importantly, for the trace elements, the CC method can not give the quantitative results due to the extremely weak characteristic spectral lines, but the PLS method still has a good ability of quantitative analysis. And the regression coefficient of PLS method is compared with the original spectral data with background interference to explain the advantage of the PLS method in the LIBS quantitative analysis. Results proved that the PLS method used in laser induced breakdown spectroscopy is suitable for quantitative analysis of trace elements such as C in the metallurgical industry.
ABSTRACT
To realize auto-selection of analytical lines for quantitative analysis of materials with laser-induced breakdown spectroscopy, two parameters, i. e. the relative detected-to-theory intensity ratio (RDTIR) and wavelength difference of detected and theory (WDDT) were defined. The spectral lines seriously disturbed by self-absorption and spectral interference were excluded automatically by setting reasonable thresholds of RDTIR and WDDT. By analyzing the experimental data of high-alloy steel (GBW01605), the analytical lines of iron (Fe), chromium (Cr), nickel (Ni), manganese (Mn) and copper (Cu) were selected, and the results were in line with the principle of lines selection.
ABSTRACT
The concentration of Mn and Si in different kinds of steels was determined by laser-induced breakdown spectroscopy (LIBS). The multivariate quadratic nonlinear function was adopted for calibration. Samples including common alloy steels, stainless steels and carbon tool steels were analyzed. The matrix effect was serious because of large difference in compositions of different kinds of steels and strong line overlaps in steel spectra. Therefore, the common calibration methods that only use one analytical line to calibrate the complex chemical compositions of alloy steels will lose much information. The multivariate calibration methods, however, can utilize more information of spectra, successfully reduce the matrix effect and improve the measurement repeatability and accuracy of LIBS. Compared with the common calibration method based on one analytical line, the relative standard deviation was reduced from above 20% to below 10%, and the accuracy was increased by more than 5 times for Mn and more than 6 times for Si.
ABSTRACT
The multielement components of some aluminium alloy samples were quantified by using laser-induced breakdown spectroscopy (LIBS). The Nd : YAG pulsed laser was used to produce plasma in ambient air. The spectral range of 200-980 nm was simultaneously obtained through a multichannel grating spectrometer and CCD detectors. The authors studied the influences of time delays, energy of the laser, and depth profile of elements in samples on spectral intensity, and optimized the experimental parameters based on the influence analysis. With the optimal experimental parameters, the authors made the calibration curves by four certified aluminum alloy samples for eight elements, Si, Fe, Cu, Mn, Mg, Zn, Sn, and Ni, and quantified the composition of an aluminum sample. The obtained maximum relative standard deviation (RSD) was 5.89%, and relative errors were--20.99%-15%. Experimental results show that LIBS is an effective technique for quantitative analysis of aluminum alloy samples, though the improved accuracy of the quantitative analysis is necessary.
