The paper presents the microscopic and mechanoacoustic study of degradation processes of the porcelain material C 130 type. This kind of material is used in the production of the most durable and reliable electrotechnical elements. Raw material composition of the studied porcelain was modified. This had an impact on the inner properties, cohesion and – in consequence – on operational properties of the material. Using mechanical-acoustic and microscopic methods of testing of small-size samples that were subjected to compression, it was possible to distinguish successive stages of degradation of the porcelain structure. These stages were generally typical of the porcelain materials. In the authors’ opinion, they are connected to the ageing process happening over many years of work under operating conditions. Optimization of composition and technological properties – important during technological processes – resulted in a slight decrease in inner cohesion of the porcelain. When compared to the reference material – typical domestic C 130 material, mechanical strength was somewhat lower. Carried out investigations proved that resistance of the investigated material to the ageing degradation process – during long term operation – also decreased. The improvement of technological parameters and the reduction in the number of defective elements occurred simultaneously with some decrease in the operational parameters of the material. To restore their initial high level, further work is needed to optimize the raw material composition of the porcelain.
In the article we described the evolution of optical technology from lens-type microscopes working in far-field to SNOM (Scanning Near-Field Optical Microscopy) constructions. We considered two systems elaborated in our laboratory, namely PSTM system (Photon Scanning Tunelling Microscope) and SNOM system. In both systems we obtained subwavelength resolution. Some details about optical point probe technology in both systems are given and experimental results presented.
In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones – the healthy blood cells (erythrocytes) and the pathologic ones (echinocytes). The separated blood cells are analysed in terms of their most important features by the eigenfaces method. The features are the basis for designing the neural network classifier, learned to distinguish between erythrocytes and echinocytes. As the result, the proposed system is able to analyse the smear blood images in a fully automatic way and to deliver information on the number and statistics of the red blood cells, both healthy and pathologic. The system was examined in two case studies, involving the canine and human blood, and then consulted with the experienced medicine specialists. The accuracy of classification of red blood cells into erythrocytes and echinocytes reaches 96%.
The objective of the investigation was to identify surface roughness after turning with wedges of coated sintered carbide. The investigation included predicting the average surface roughness in the dry machining of Duplex Stainless Steel (DSS) and the determination of load curves together with roughness profiles for various cutting conditions. The load curves and roughness profiles for various cutting wedges and variable cutting parameters were compared. It has been shown that dry cutting leads to a decrease in friction for lubricated surfaces, providing a small initial contact area where the surface is contacted. The study has been performed within a production facility during the production of electric motor parts and deep-well pumps.