Fractal geometry for industrial data evaluation

In the present work surface roughness of copper samples after mechanical surface preparation processes (polishing, grinding, sand-blasting) and after exposure in non-oxidizing (high purity argon) and oxidizing (air) conditions at 700 and 750°C have been evaluated by contact profilometer and by fractal analysis. Quantitative description of surfaces that are hidden from the sight of conventional methods is possible by fractal analysis, e.g. in the present work, the roughness of Cu 2 O/Cu boundary has been evaluated under oxide layer. It has been pointed out, that in both oxidizing and non-oxidizing conditions initial surface roughness of copper is affected by annealing at high temperature: at 700°C surface roughness of polished and ground samples increased but at 750°C decreased in comparison to surface roughness prior to heat treatment. For sand-blasted samples in both oxidizing and non-oxidizing conditions the lowest values of surface roughness parameters were obtained at 750°C. It is then concluded that two phenomena are responsible for such effect: chemical reaction between copper and oxygen and surface diffusion of copper due to high temperature of annealing.

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“…All of them base on digital image analysis. It ensures that no deep valley on convoluted surface will be left "blind" during analysis [29].…”

Section: Surface Roughness Evaluationmentioning

confidence: 99%

“Mechanically prepared copper surface in oxidizing and non-oxidizing conditions”

Serafin

Nowak

Wierzba

2019

Applied Surface Science

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“…In Chemistry, it has been applied to modify natural starch as a bio-polymeric product [35]. Fractal Geometry can be a useful and powerful tool for an explicit, objective and automatic description of data of the production process in Industrial Engineering, where complex and irregular structures are described [45]. It has also been used in the optical evaluation of vibratory systems [46] and for the texture analysis of colors [47], as well as in several different situations within the field of architecture [48].…”

Section: Introductionmentioning

confidence: 99%

Thermal Storage Systems Assessment for Energy Sustainability in Housing Units

et al. 2016

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Abstract:In order to achieve greater enhancements in energy sustainability for housing, the function and efficiency of two different passive cooling systems were studied: encapsulated water in recycled bottles of Polyethylene terephthalate (PET) and polystyrene plates, in comparison with standard concrete slab systems, which are customarily used in housing. Experiments were placed over a tile surface, in which temperature changes were monitored for a period of 20 days from 08:00 to 20:00. The efficiency of passive thermal storage systems was endorsed through statistical analysis using the "SPSS" software. This resulted in a 17% energy saving, thus promoting energy sustainability in housing units, which reduces the use of electrical appliances required to stabilize conditions to achieve optimum thermal comfort for the human body inside a house, therefore, reducing electrical power consumption, CO 2 emissions to the atmosphere and generating savings. Due to the complexity of a system with temperature changes, a fractal analysis was performed for each experimental system, using the "Benoit" software (V.1.3 with self-compatible tools of rescaled range (R/S) and a wavelets method), showing that the thermal fluctuations on the tiles with the thermal storage system adapt to the rescaled range analysis and the regular tiles adapt to the wavelets method.

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“…Final results of over a thousand measurements from a real production process show a very good potential for the on-line application [3,4,8,20]. The on-line corrugation test was implemented and showed good stability of the evaluation methodology.…”

Section: Example: Corrugation Testmentioning

confidence: 99%

“…To analyse one-dimensional signals, we use statistical methods, power spectral analysis, and an estimate of the FD [3,4]. The estimation of the FD is calculated using the rescaled range method [5] and the box counting method from an "iso-set" [6], also compass counting and EEE method can be used.…”

Section: Description Of One-dimensional Signalsmentioning

confidence: 99%

Application of Fractal Dimension in Industry Practice

Hotař¹

2017

Fractal Analysis - Applications in Physics, Engineering and Technology

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Today, industrial production lines commonly use off-line and automatic on-line quality monitoring and control. Monitoring and control units analyse data from a production process, and analysis should be able to obtain reliable information that correspond with the character of the data obtained. The character of the data set obtained from production processes or from products can be highly structured in all industrial areas. Structured surface, complex time series (topologically one dimensional signals), difficulty to describe dividing curves are much more common than it can be expected. For this kind of data set, a powerful tool for analysis of complexity -fractal geometry (especially a fractal dimension) should be used. The fractal dimension with a combination of statistical tools is an interesting and powerful tool for complex data quantification, for tracing the source of poor quality, production optimization and investigating the source of instability of production process subsystems in industrial applications. The methodology for evaluation of complex and irregular data was developed and applied in industrial practice. This methodology searches appropriated parameters for a complex evaluation of data. Only the chosen parameters are used for a complete analysis of the data in order to reduce processing time.

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Fractal geometry for industrial data evaluation

Cited by 19 publications

References 1 publication

“Mechanically prepared copper surface in oxidizing and non-oxidizing conditions”

“Mechanically prepared copper surface in oxidizing and non-oxidizing conditions”

Thermal Storage Systems Assessment for Energy Sustainability in Housing Units

Application of Fractal Dimension in Industry Practice

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