By the definition of the metal class
Keywords:
metal, entropy, information dimension, quality criteria, forecastAbstract
Formulation of the problem. The complexity and diversity of structural metal components is not always possible to make its functional description, strictly define the metric in the space of states. Problems are solved only with the help of irreducible algorithms, naturally are called numerical irreducible. The hypothesis of numerical irreducibility problem of identification of qualitative characteristics of metals (eg, steel) can be formulated as follows: resolution function domain which is the set of raster images of the metal thin sections, and the range of values - a set of vectors describing its quality, it can only be built by applying the exhaustive search algorithm. It is clear that, considering the technical and organizational difficulties along the way, at this stage of scientific and technological progress should be at least temporarily abandon attempts to solve this problem by using "pure" analytical apparatus. Purpose. To partially eliminate of the formal axiomatic incompleteness arised with describing of the metal structure by conventional methods, we propose a method based on the use of the multifractal formalism of estimation uncertainty (entropy) of the structure. Results and discussion. Currently used for the evaluation of quality indicators structure multifractal formalism can more accurately assess the specific structure of supplies to a particular class of metal. According to the theory of multifractals the spectrum statistical dimensions of the structure is calculated according to the classical formula Renyi. The data analysis shows that from the spectrum of the calculated statistical graphite dimension the best sensitivity to the cast iron hardness has an information dimension. Trends of the graphite informational dimension and an information indicator HX proposed by Shannon are acceptable match. They have a more accurate convergence, exeeding the visual rating in 0.89 / 0.22 = 4.05 times. Conclusions. Thus, the article shows one of the ways to determine the metal belonging to a particular class by its quality criteria prediction with a multifractal analysis and a structure information entropy applying.
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