RESUMO
Friction stir welding (FSW) is an environmentally friendly, solid-state welding technique. In this research work, we analyze the microstructure of a new type of FSW weld applying a two- stage framework based on image processing algorithms containing a segmentation step and microstructure analysis of objects occurring in different layers. A dual-speed tool as used to prepare the tested weld. In this paper, we present the segmentation method for recognizing areas containing particles forming bands in the microstructure of a dissimilar weld of aluminum alloys made by FSW technology. A digital analysis was performed on the images obtained using an Olympus GX51 light microscope. The image analysis process consisted of basic segmentation methods in conjunction with domain knowledge and object detection located in different layers of a weld using morphological operations and point transformations. These methods proved to be effective in the analysis of the microstructure images corrupted by noise. The segmentation parts as well as single objects were separated enough to analyze the distribution on different layers of the specimen and the variability of shape and size of the underlying microstructures, which was not possible without computer vision support.
RESUMO
In the paper the positivity problem of the model of an one dimensional heat transfer process is addressed. Such a problem has not been considered yet. The considered thermal process is described by the fractional order state equation, derived from parabolic heat equation with homogenous Neumann boundary conditions and distributed control and observation. The internal and external positivity of the model depend on heater and sensor location as well as the size of the model. It is proved that the external positivity of the considered system can be achieved without internal positivity. Conditions of the internal and external positivity are proposed and proved. Theoretical considerations are supported by experiments. Experiments were done using the real system containing typical industrial components. The proposed results can be applied in real temperature measurements, for example in thermal cameras.