Stable functioning of the technical objects is estimated using methods of the statistical process control. However this approach does not always provide the timely detection
of violations. It is suggested using machine learning methods for the binary classification of object states (stable or unstable). A program has been developed for calculation in the Matlab environment which allows for analysis of impact of the learning method, classification quality criteria, method of validation set as well as methods of selection of significant indicators on the object’s stable functioning forecast precision. Stable operation of the water treatment management system, stable vibration of the hydraulic unit, machining operation process are taken as examples.
The method of identification of objects on images of the microstructure of cast iron with spherical graphite of the correct shape with uniform distribution is presented. Morphological analysis techniques were used to identify shrinkage pores and graphite inclusions in microstructure images. Geometric features of the shape of graphite inclusions were used as methods for identifying graphite, in particular, particle size analysis, which is widely used to identify various objects in computer microscopy. The computer analysis of the image was performed with the program ImageJ. To determine the pores against the background of graphite inclusions, two characteristics were used - the shape and size of the objects themselves. The pores, presented on the image, differ from graphite inclusions by a complex, fractal border and comparatively large areas. For the visualization of the research results, the combination of the graphite part with the calculation and analytical part was used. Such presentation of the results is the most significant and allows to perform the most correct evaluation of the graphitized cast iron microstructure in accordance with GOST 3443-87.
The basics of metallography and modern systems used to study and analyse the structures of materials are presented. Special attention is paid to the methods of quantitative microscopy. The review of modern computer programs for analysis of image microstructures obtained from digital microscopes is given. The fundamentals of fractal analysis as a highly effective tool for calculating numerical values of parameters of geometrically complex objects are described. The analysis of the graphitized cast iron structure is provided as an example; the application of the fractal analysis method for determining such characteristics of the graphite phase as the shape of graphite inclusions and their distribution in the amount of the alloy is demonstrated. In the course of the research, different classes of cast iron have been studied. To determine the shape of graphite inclusions it was suggested to use fractal dimension. The nonuniformity of the distribution was estimated by such function as lacunarity. The separate stages of determining these characteristics with a specialized FracLac plugin within the ImageJ program are presented. The results obtained have shown high adequacy. In spite of positive assessments, there are shortcomings revealed in the course of the research on the application of fractal analysis methods for identifying geometrically complex dimensional and topological parameters of the graphite phase in cast iron. The ways to further improve these methods in order to solve a wide range of problems in metallography of alloys are suggested.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.