One of the branches of sustainable agriculture is the precision farming which assumes an individual approach to each plant. The main problem encountered by the precision agriculture is to quickly acquire and analyze good quality data assessing the condition of the crop. One of the fastest growing monitoring techniques is the analysis of images obtained from cameras placed on UAV. The studies used the chaos tools to determine Hurst exponent values received from images collected during UAV flights over the fields. The obtained results of image analysis indicated the presence of a strong dependency between the Hurst exponent values and state of crops. Images showed crops which are in good standing have been seen as strong organize objects represented by the mean Hurst exponent values from 0.8 to 0.87. Crops in which occurred the destruction of plants on the collected images were estimated by the Hurst exponent between 0.41 and 0.49 values, which indicates the presence of the characteristics of chaotic changes in the distribution of color attributes.
The article compares the results of experimental and modelling research of switched reluctance motor at two different operational states: one proper and one with mechanical fault, i.e., with dynamic eccentricity of the rotor. The experiments were carried out on a test bench and then the results were compared with mathematical modelling of quasi-static and dynamic analysis of 2D geometry model. Finally, it was examined how the operation with dynamic eccentricity fault of the motor affected its main physical parameter—the phase current. The analysis was presented in the frequency domain using the Fast Fourier Transform (FFT); however, individual current waveforms in the time domain are also shown for comparison. Applying results of the research could increase reliability of the maintenance of SRM and enhance its application in vehicles for special purposes as well as its military and industrial applications.
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