Spectral monitoring at SwissFEL using a high-resolution on-line hard X-ray single-shot spectrometer

The performance and parameters of the online photon single-shot spectrometer (PSSS) at the Aramis beamline of the SwissFEL free-electron laser are presented. The device operates between the photon energies 4 and 13 keV and uses diamond transmission gratings and bent Si crystals for spectral measurements on the first diffraction order of the beam. The device has an energy window of 0.7% of the median photon energy of the free-electron laser pulses and a spectral resolution (full width at half-maximum) ΔE/E on the order of 10−5. The device was characterized by comparing its performance with reference data from synchrotron sources, and a parametric study investigated other effects that could affect the reliability of the spectral information.

Methodical approaches to plant identification in high-resolution images in multispectral monitoring using UAVS

Crop management used in these technologies is one of the main trends in the modernization of agricultural technologies. To implement crop management, growers need accessible and effective information about the state of crops. The aim of the work is to develop a method of plant identification on multispectral images of high resolution for crops of continuous sowing on the example of winter wheat. The research was conducted on 03/17/2019 on winter wheat crops in the tillering vegetation phase, Mukan variety in production fields near the village of Horodyshche, Kyiv region. Aerial monitoring from a height of 100 meters was carried out using a spectral complex Slantrange 3p, mounted on a UAV UAV DJI Matrice 600. To extract the reference graphics data from Slantview made a copy of the screen in full screen mode of the image window. Statistical processing of graphical data of spectral monitoring results was performed in MathCad. It was found that the reliable establishment of the spectral portrait of the soil for its pixel-by-pixel filtering from multispectral images is a difficult task because its color significantly depends on the state of moisture, which may differ in open and shaded by plants. A more promising way to eliminate random inclusions is to use a spectral portrait of plants based on the intensity ratios of its spectral components. A promising parameter for assessing the condition of crops is to assess their area of heir horizontal surface, which can be determined by pixel analysis of the image. A filtering option is proposed, which, as in the solutions implemented in Slantview software, needs to be debugged. In further researches it is expedient to consider questions of methodical maintenance of an estimation of quality of a filtration of data of spectral monitoring of vegetation.

Application of Experiment Planning Methods in Researching of Reinforced Concrete Constructions Corrosion Process

The article discusses statistical methods of experiment planning for determining the significance of influencing factors on the course of the corrosion process. The application of the proposed method in conjunction with spectral monitoring methods is shown. Mathematical models are presented that allow to investigate the corrosion process with various combinations of influencing factors. The response surface of the dependent variable on the most significant factors is constructed. The conclusion is made that spectral methods can be used to determine the corrosion state of reinforced concrete structures.