Signal processing for real-time identification of similar metals by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS) is regarded as a promising technique for realtime sorting of scrap metals due to its capability of fast multi-elemental and in-air analysis. This work reports a method for signal processing which ensures high accuracy and high speed during similar metal sorting by LIBS. Similar metals such as aluminum alloys or stainless steel are characterized by nearly the same constituent elements with slight variations in elemental concentration depending on metal type. In the proposed method, the original data matrix is substantially reduced for fast processing by selecting new input variables(spectral lines) using the information for the constituent elements of similar metals. Specifically, principal component analysis(PCA) of full-spectra LIBS data was performed and then, based on the loading plots, the input variables of greater significance were selected in the order of higher weights for each constituent element. The results for the classification test with aluminum alloy, copper alloy,stainless steel and cast steel showed that the classification accuracy of the proposed method was nearly the same as that of full-spectra PCA, but the computation time was reduced by a factor of 20 or more. The results demonstrated that incorporating the information for constituent elements can significantly accelerate classification speed without loss of accuracy.

Improvement in classification accuracy of stainless steel alloys by laser-induced breakdown spectroscopy based on elemental intensity ratio analysis

Laser-induced breakdown spectroscopy(LIBS) is a useful technique for accurate sorting of metal scrap by chemical composition analysis.In this work,a method for intensity-ratiobased LIBS classification of stainless steel applicable to highly fluctuating LIBS signal conditions is proposed.The spectral line pairs for intensity ratio calculation are selected according to elemental concentration and upper levels of emission lines.It is demonstrated that the classification accuracy can be significantly improved from that of full-spectra principal component analysis or intensity-based analysis.The proposed method is considered to be suited to an industrial scrap sorting system that requires minimal maintenance and low system price.

Three-dimensionalization via control of laser-structuring parameters for high energy and high power lithium-ion battery under various operating con ditions

Laser-structuring is an effective method to promote ion diffusion and improve the performance of lithium-ion battery(LIB)electrodes.In this work,the effects of laser structuring parameters(groove pitch and depth)on the fundamental characteristics of LIB electrode,such as interfacial area,internal resistances,material loss and electrochemical performance,are investigated,LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2) cathodes were structured by a femtosecond laser by varying groove depth and pitch,which resulted in a material loss of 5%-14%and an increase of 140%-260%in the in terfacial area between electrode surface and electrolyte.It is shown that the importance of groove depth and pitch on the electrochemical performance(specific capacity and areal discharge capacity)of laser-structured electrode varies with current rates.Groove pitch is more im porta nt at low current rate but groove depth is at high curre nt rate.From the mapping of lithium concentration within the electrodes of varying groove depth and pitch by laser-induced breakdown spectroscopy,it is verified that the groove functions as a diffusion path for lithium ions.The ionic,electronic,and charge transfer resistances measured with symmetric and half cells showed that these internal resistances are differently affected by laser structuring parameters and the changes in porosity,ionic diffusion and electronic pathways.It is demonstrated that the laser structuring parameters for maximum electrode performance and minimum capacity loss should be determined in consideration of the main operating conditions of LIBs.

Consistency of intensity ratio between spectral lines with similar self-absorption characteristics during ungated laser induced breakdown spectroscopy measurements

This work reports that the intensity ratio of spectral lines having similar self-absorption characteristics during laser induced breakdown spectroscopy(LIBS) analysis can become nearly constant over a wide range of irradiation conditions if the intensities are integrated over a sufficiently long time. It is shown that the plasma temperature and intensity ratio of these spectral lines have temporal similarity. The spectral lines with similar self-absorption properties may be selected to improve the accuracy and consistency of LIBS analysis results under an environment with fluctuating measurement conditions.

Weighted-averaging-based classification of laser-induced breakdown spectroscopy measurements using most informative spectral lines

In this study,efficient spectral line selection and wcightcd-avcraging-bascd processing schemes are proposed for the classification of laser-induced breakdown spectroscopy(UBS)measurements.For fast on-line classification,a set of representative spectral lines arc selected ami processed relying on the information metric,instead of the time consuming full spectrum based analysis.I he most informative spectral line sets arc investigated by the joint mutual information estimation(MIR)evaluated with the Gaussian kernel density,where dominant intensity peaks associated with the concentrated components arc not necessarily most valuable for classification.In order to further distinguish the characteristic patterns of die LIBS measured spectrum,two-dimensional spectral images are synthesized through column-wise concatenation of the peaks along with their neighbors.For fast classification while preserv ing die effect of distinctive peak patterns,column-wise Gaussian weighted averaging is applied to die synthesized images,yielding a favorable trade off between classification performance and computational complexity.To explore the applicability of the proposed schemes,two applications of alloy classification and skin cancer detection arc investigated with the multi-class and binary support vector machines classifiers,respectively.Ihc MIE measures associated with selected spectral lines in bodi applications show a strong correlation to the actual classification or detection accuracy,which enables to find out meaningful combinations of spectral lines.In addition,the peak patterns of the selected lines and their Gaussian weighted averaging with nciehbors of the selected peaks efficiently distineuish different classes of LIBS measured spectrum.

Way-out for laser-induced breakdown spectroscopy

Ever since its creation in 1963 [1], laser-induced breakdown spectroscopy(LIBS)has gained considerable attention due to its unique capability for real-time, in situ or online analysis [2, 3]. The future world is heading into the age of artificial intelligence(AI), and data would be the most valuable asset for human society [4].