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.     

Hydrogen-enhanced cracking of 2205 duplex stainless steel

Tensile and fatigue crack growth tests of 2205 duplex stainless steel (DSS) were performed in laboratory air, gaseous hydrogen at 0.2 MPa and saturated H₂S solution. The longitudinal specimen showed a lesser degradation of tensile properties than the transverse ones in saturated H₂S solution. The orientation of specimens with respect to rolling direction had little influence on the fatigue crack growth rate (FCGR) of the alloy in air. Furthermore, 2205 duplex stainless steel was susceptible to hydrogen‐enhanced fatigue crack growth. Transmission electron micrographs, in addition to X‐ray diffraction, revealed that the strain‐induced austenite to martensite transformation occurred near the crack surface within a rather narrow depth. Fatigue fractography of the specimens tested in air showed mainly transgranular fatigue fracture with a small amount of flat facet fracture. Furthermore, extensive quasi‐cleavage fracture of 2205 duplex stainless steel was associated with the hydrogen‐enhanced crack growth.     

Effect of Addition of Chloride Salts on Rancidity of Ground Pork Inoculated with a Moraxella or a Lactobacillus Species

Two experiments were conducted to determine rancidity development in raw-refrigerated ground pork treated with different types and levels of chloride salts. In the first experiment, raw ground pork was inoculated with either a Moraxella or a Lactobacillus species. In the second experiment, samples were not inoculated. In both experiments, samples were treated with either NaCl, KCl, or MgCl₂ at ionic strength of either 0.73 or 0.37 and stored at 5°C. Regardless of inoculation, in both experiments addition of any chloride salt increased (P < 0.05) TBA values over those values for controls (no added salt). Addition of NaCl resulted in the highest (P < 0.05) TBA values among inoculated samples, but these differences were not apparent for noninoculated samples.     

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

In this study, efficient spectral line selection and weighted-averaging-based processing schemes are proposed for the classification of laser-induced breakdown spectroscopy(LIBS) measurements. For fast on-line classification, a set of representative spectral lines are selected and processed relying on the information metric, instead of the time consuming full spectrum based analysis. The most informative spectral line sets are investigated by the joint mutual information estimation(MIE)evaluated with the Gaussian kernel density, where dominant intensity peaks associated with the concentrated components are not necessarily most valuable for classification. In order to further distinguish the characteristic patterns of the LIBS measured spectrum, two-dimensional spectral images are synthesized through column-wise concatenation of the peaks along with their neighbors.For fast classification while preserving the effect of distinctive peak patterns, column-wise Gaussian weighted averaging is applied to the 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 are investigated with the multi-class and binary support vector machines classifiers, respectively. The MIE measures associated with selected spectral lines in both 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 neighbors of the selected peaks efficiently distinguish different classes of LIBS measured spectrum.