1. Characterization of corrosion processes by current noise waveletbased fractaland correlation analysisPeter Planinšič, Aljana Petek, 2008, izvirni znanstveni članek Opis: Electrochemical noise data in the presence of pitting, general corrosion and passivity were analyzed using the discrete wavelet transform. The registered current noise was decomposed into a set of bandlimited details, which contain information about corrosion events occurring at a determined timescale. It has been observed that the signal variance and variances of details depend on the intensity of processes. Distribution of the signal energy among different details was characteristic for the particular type of corrosion. The characterization of corrosion processes on the basis of in the wavelet domain calculated Hurst parameter H and fractal dimension, D, of electrochemical noise signals has been established. It is concluded that general corrosion is a stationary random process with a weak persistence and D= 2.14, whereas pitting corrosion is a nonstationary process with a long memory effect and D = 1.07. Passivity is a nonstationary process near to the Brownian motion with D = 1.56. The persistence features of electrochemical noise signals were explained also by correlation coefficients calculated between signals obtained by discrete wavelet multiresolution decomposition. Ključne besede: elektrokemijski šum, valčki, Hurstov parameter, fraktalna dimenzija, korelacijski koeficient, korozija, electrochemical noise, wavelets, Hurst parameter, fractal dimension, correlation coefficients, corrosion Objavljeno: 31.05.2012; Ogledov: 1386; Prenosov: 70 Povezava na celotno besedilo 
2. A new method for estimating the Hurst exponent H for 3D objectsMatej Babič, Peter Kokol, Nikola Guid, Peter Panjan, 2014, izvirni znanstveni članek Opis: Mathematics and computer science are very useful in many other sciences. We use a mathematical method, fractal geometry, in engineering, specifically in laser techniques. Characterization of the surface and the interfacial morphology of robotlaserhardened material is crucial to understand its properties. The surface microstructure of robotlaserhardened material is rough. We aimed to estimate its surface roughness using the Hurst parameter H, which is directly related to the fractal dimension. We researched how the parameters of the robotlaser cell impact on the surface roughness of the hardened specimen. The Hurst exponent is understood as the correlation between the random steps X1 and X2, which are followed by time for the time difference t. In our research we understood the Hurst exponent H to be the correlation between the random steps X1 and X2, which are followed by the space for the space difference d. We also have a space component. We made test patterns of a standard label on the point robotlaserhardened materials of DIN standard GGG 60, GGG 60 L, GGG 70, GGG 70 L and 1.7225. We wanted to know how the temperature of point robotlaser hardening impacts on the surface roughness. We developed a new method to estimate the Hurst exponent H of a 3Dobject. This method we use to calculate the fractal dimension of a 3Dobject with the equation D = 3  H. Ključne besede: fractal structure, Hurst exponent, robot, hardening, laser Objavljeno: 14.03.2017; Ogledov: 661; Prenosov: 79 Celotno besedilo (468,97 KB) Gradivo ima več datotek! Več...

3. Prediction of the hardness of hardened specimens with a neural networkMatej Babič, Peter Kokol, Igor Belič, Peter Panjan, Miha Kovačič, Jože Balič, Timotej Verbovšek, 2014, izvirni znanstveni članek Opis: In this article we describe the methods of intelligent systems to predict the hardness of hardened specimens. We use the mathematical method of fractal geometry in laser techniques. To optimize the structure and properties of tool steel, it is necessary to take into account the effect of the selforganization of a dissipative structure with fractal properties at a load. Fractal material science researches the relation between the parameters of fractal structures and the dissipative properties of tool steel. This paper describes an application of the fractal dimension in the robot laser hardening of specimens. By using fractal dimensions, the changes in the structure can be determined because the fractal dimension is an indicator of the complexity of the sample forms. The tool steel was hardened with different speeds and at different temperatures. The effect of the parameters of robot cells on the material was better understood by researching the fractal dimensions of the microstructures of hardened specimens. With an intelligent system the productivity of the process of laser hardening was increased because the time of the process was decreased and the topographical property of the material was increased. Ključne besede: fractal dimension, fractal geometry, neural network, prediction, hardness, steel, tool steel, laser Objavljeno: 17.03.2017; Ogledov: 711; Prenosov: 70 Celotno besedilo (632,41 KB) Gradivo ima več datotek! Več...
