Dark spectrum fig 72a light spectrum fig 72b

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Dark spectrum – Fig. 7.2a; light spectrum – Fig. 7.2b. Measuring conditions: 40 kV, 150 µ A, 60 s, 50 µ m spot size origin can be seen from the spectra measured in the displayed spot of these images of the disk. The spectra are displayed in Fig. 7.3. In the first case (Fig. 7.2a, dark spectrum in Fig. 7.3) Si, S and Cl can be identified. These are elements that are characteristically found in the environment. Hence, it is necessary to improve the overall cleanliness or protection of the production environment. The other inclusion (Fig. 7.2b, light spectrum in Fig. 7.3) shows very clearly the elements Cr, Fe, and Ni with intensity ratios indicating stainless steel as the material of origin. This particle was an abrasion particle from the production equipment. In this case it had to be checked if the abrasion is too high in some places of the equipment or if it would be necessary to coat them with a hard material like TiN. Such measurements can be performed fast and without extensive sample preparation. The results provide information about the situation of a production line and identify the cause of manufacturing faults. With EPMA this kind of measurements would not have been possible in such an easy way, because the sample is not electrically conductive and the
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Methodological Developments and Applications 447 inclusions are within the plastic body. The sample would have to be polished or sectioned to bring the inclusion to the surface in order to be analysed and a conductive coating must be applied. Single Particle Analysis in Wear Debris The identification of single particles of different kinds in a set of particles is another example for particle analysis. This analytical task arises for wear debris. The identification of individual particles provides information about its particular source that can be helpful for specific maintenance require- ments of big engines from planes or ships. The result of small particle analy- sis may be influenced by their shape and size. As these geometric parame- ters can vary in a wide range, it is necessary to use special identification strategies. If the particle size is smaller than the depth from which the fluorescence radiation is also originating, the measured intensity depends both on concen- tration and on sample size (thickness). Then, the shape of the sample has to be taken into account, as well. In a first approximation the shape of the sam- ple can be derived from an optical image which demands an image processing stage in addition to the XRF analysis. Another alternative is the use of internal standards for the different sam- ples [21] or the use of chemometric methods for particle identification [22]. As an internal standard a main component of the sample may be used for normalisation. Assuming a fixed concentration of that main component for all samples, a normalisation procedure will reduce the influence of the sam- ple geometry. However, such an approach is valid only in cases for which the internal standard and the element of interest have similar matrix absorption parameters. This is applicable only in situations for which the atomic numbers
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  • Spring '14
  • MichaelDudley

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