کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1239460 | 1495684 | 2016 | 11 صفحه PDF | دانلود رایگان |
Laser induced breakdown spectroscopy (LIBS) scanning measurements can generally be used to detect the presence of non-metallic inclusions in steel samples. However, the inexistence of appropriate standards to calibrate the LIBS instrument signal means that its application is limited to identifying simple diatomic inclusions and inclusions that are chemically fully distinct from one another. Oxide inclusions in steel products have varied and complex chemical content, with an approximate size of interest of 1 μm. Several oxide inclusions types have chemical elements in common, but it is the concentration of these elements that makes an inclusion type have little or, on the contrary, deleterious impact on the final steel product quality. During the LIBS measurement of such inclusions, the spectroscopic signal is influenced not only by the inclusions' chemical concentrations but also by their varying size and associated laser ablation matrix effects. To address the complexity of calibrating the LIBS instrument signal for identifying such inclusion species, a new approach was developed where a calibration dataset was created, combining the elemental concentrations of typical oxide inclusions with the associated LIBS signal, in order to define a multivariate discriminant function capable of identifying oxide inclusions from LIBS data obtained from the measurement of unknown samples.The new method was applied to a variety of steel product samples. Inclusions populations consisting of mixtures of several complex oxides, with overlapping chemical content and size ranging typically from 1 to 5 μm, were identified and correlated well with validation data. The ability to identify complex inclusion types from LIBS data could open the way to new applications as, for a given sample area, the LIBS measurement is performed in a fraction of the time required by scanning electron microscopy, which is the conventional technique used for inclusion characterisation in steel. Applications that would require speed for high throughput can benefit from this development where the LIBS measurement of inclusions can be used as a first stage rapid screening method for quality purposes. On the other hand, applications requiring inclusions data over large sample areas for investigation related to steel cleanness could also benefit from such development.
Journal: Spectrochimica Acta Part B: Atomic Spectroscopy - Volume 119, 1 May 2016, Pages 25–35