Levente Solecki
57204589095
Publications - 7
Macrogeometric Measurement of Camshafts of Internal Combustion Engines
Publication Name: Strojnicky Casopis
Publication Date: 2024-11-01
Volume: 74
Issue: 2
Page Range: 71-82
Description:
In this work, cam profiles of a camshaft are measured by a roundness measurement machine. First, the measured cam profiles are transformed into their actual sizes, based on the measurement of the bearing locations. The 8 cams of the camshaft are of two types. From the 4-4 cam profiles of each type an approximate profile is created by fitting them to one another using their base circles as reference, and calculating the center of gravity of the cumulative points of these fitted profiles corresponding to an arc segment.
Open Access: Yes
The effect of background and outlier subtraction on the structural entropy of two-dimensional measured data
Publication Name: International Journal of Reasoning Based Intelligent Systems
Publication Date: 2020-01-01
Volume: 12
Issue: 3
Page Range: 200-209
Description:
For colonoscopy images the main information is in the fine structure of the surface of the bowel or colorectal polyps, similarly to the case of combustion engine cylinder surface scans, where the grooving and wear can be detected from the fine pattern superposed to a cylinder curvature. In both cases appear outliers, colonoscopy images have many reflections, whereas the roughness scanners detect small dust particles as well as the micron scale vibrations from the environment. The method presented in this paper takes care of both the problems using histogram stretching together with a special type of filtering. Also, masks are introduced in order to control the effect of the operators. The effects of the processing steps on the structural entropy of the image is also studied, as structural entropies are used in characterisation of the images. By removing the background makes the structural entropies much smaller, and by suppressing the outliers the structural entropies increase.
Open Access: Yes
DOI: DOI not available
On wavelet based enhancing possibilities of fuzzy classification methods
Publication Name: Journal of Automation Mobile Robotics and Intelligent Systems
Publication Date: 2020-01-01
Volume: 14
Issue: 2
Page Range: 32-41
Description:
If the antecedents of a fuzzy classification method are derived from pictures or measured data, it might have too many dimensions to handle. A classification scheme based on such data has to apply a careful selection or processing of the measured results: either a sampling, re-sampling is necessary. or the usage of functions, transfor-mations that reduce the long, high dimensional observed data vector or matrix into a single point or to a low number of points. Wavelet analysis can be useful in such cases in two ways. As the number of resulting points of the wavelet analysis is approximately half at each filters, a consecutive application of wavelet transform can compress the me-asurement data, thus reducing the dimensionality of the signal, i.e., the antecedent. An SHDSL telecommunication line evaluation is used to demonstrate this type of appli-cability, wavelets help in this case to overcome the pro-blem of a one dimensional signal sampling. In the case of using statistical functions, like mean, variance, gradient, edge density, Shannon or Rényi entropies for the extraction of the information from a picture or a measured data set, and they don not produce enough information for performing the classification well enough, one or two consecutive steps of wavelet analysis and applying the same functions for the thus resulting data can extend the number of antecedents, and can dis-till such parameters that were invisible for these functions in the original data set. We give two examples, two fuzzy classification schemes to show the improvement caused by wavelet analysis: a measured surface of a combustion engine cylinder and a colonoscopy picture. In the case of the first example the wear degree is to be deter-mine, in the case of the second one, the roundish polyp content of the picture. In the first case the applied statistical functions are Rényi entropy differences, the structural entropies, in the second case mean, standard deviation, Canny filtered edge density, gradients and the entropies. In all the examples stabilized KH rule interpolation was used to treat sparse rulebases.
Open Access: Yes
Applying fuzzy hough transform for identifying honed microgeometrical surfaces
Publication Name: Studies in Computational Intelligence
Publication Date: 2020-01-01
Volume: 819
Issue: Unknown
Page Range: 35-42
Description:
In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent measurements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface processing method resulting in pattern consisting of straight valleys crossing at various angles. Honing pattern is of great help to find a special location. The main goal of this article is to find a method that is able to give some characteristic points that can be used for fitting two measured surfaces together. Hough transform is used in finding straight lines in an image or map, thus it could be used for determining crossing points of the honed surface. However, classical Hough transform either finds way too many disturbing lines in the case of a typical honed surface or almost none, depending on the parameter selection. To solve this rapid changing in the number of the resulting lines, we introduced fuzzy Hough transform. If a fuzzified version of the weights of the individual points in the Hough transform is used, the inverse of the transform becomes clearer, resulting in a pattern more suitable for finding the same location on two measured versions of a surface.
Open Access: Yes
On wavelet based enhancing possibilities of fuzzy classification methods
Publication Name: Advances in Intelligent Systems and Computing
Publication Date: 2020-01-01
Volume: 945
Issue: Unknown
Page Range: 56-73
Description:
If the antecedents of a fuzzy classification method are derived from pictures or measured data, it might have too many dimensions to handle. A classification scheme based on such data has to apply a careful selection or processing of the measured results: either a sampling, re-sampling is necessary or the usage of functions, transformations that reduce the long, high dimensional observed data vector or matrix into a single point or to a low number of points. Wavelet analysis can be useful in such cases in two ways. As the number of resulting points of the wavelet analysis is approximately half at each filters, a consecutive application of wavelet transform can compress the measurement data, thus reducing the dimensionality of the signal, i.e., the antecedent. An SHDSL telecommunication line evaluation is used to demonstrate this type of applicability, wavelets help in this case to overcome the problem of a one dimensional signal sampling. In the case of using statistical functions, like mean, variance, gradient, edge density, Shannon or Rényi entropies for the extraction of the information from a picture or a measured data set, and they don not produce enough information for performing the classification well enough, one or two consecutive steps of wavelet analysis and applying the same functions for the thus resulting data can extend the number of antecedents, and can distill such parameters that were invisible for these functions in the original data set. We give two examples, two fuzzy classification schemes to show the improvement caused by wavelet analysis: a measured surface of a combustion engine cylinder and a colonoscopy picture. In the case of the first example the wear degree is to be determine, in the case of the second one, the roundish polyp content of the picture. In the first case the applied statistical functions are Rényi entropy differences, the structural entropies, in the second case mean, standard deviation, Canny filtered edge density, gradients and the entropies. In all the examples stabilized KH rule interpolation was used to treat sparse rulebases. The preliminary version of this paper was presented at the 3rd Conference on Information Technology, Systems Research and Computational Physics, 2–5 July 2018, Cracow, Poland [1].
Open Access: Yes
Wavelet analysis and structural entropy based intelligent classification method for combustion engine cylinder surfaces
Publication Name: Studies in Computational Intelligence
Publication Date: 2019-01-01
Volume: 794
Issue: Unknown
Page Range: 127-138
Description:
Structural entropy is a good candidate for characterizing roughness of surfaces as it is sensitive not only to the general shape of the surface, but also to the rate of the high and low surface points. Wavelet analysis of the surface can separate the larger-scale behavior from the fine details, and together with the structural entropy it can define a behavior profile for the surface which is typically slightly different for new and for worn tribological surfaces. Also it is important to know whether the method of the surface scan has influence on the structural entropy’s wavelet analysis profile, as the lower cost images based on silicone replica and optical scanner have less sensitivity than the higher cost contact scan of the prepared real surface parts. An intelligent fuzzy classification scheme is introduced to characterize surfaces according to both their degree of wear and method of the surface measurement. The basis of the classification is the structural entropies of the original and the first wavelet transform of the height scan of the new and worn surfaces.
Open Access: Yes
Some remarks on comparing microgeometrical profiles and the application of replicas in microgeometrical measurements
Publication Name: Surface Topography Metrology and Properties
Publication Date: 2018-09-25
Volume: 6
Issue: 4
Page Range: Unknown
Description:
First a method for comparing profiles given in the following considerations. The profile comparisons have to be carried out in such position, that their average distance should be the smallest possible. Helmert transform is used for fitting measured points sets to one another in geodesy so that the least square distance of the measured points would be the smallest. However, for Helmert transform corresponding point pairs are to be found, i.e. for each point of one of the profiles has to be found a nearest one on the other profile. Multiple approaches are studied for finding corresponding point to a measured point in a point set. The effectiveness of the Helmert transform and the results of profile comparison are given for profiles of rounded triangle wave shaped regular roughness standards in the most used mechanical roughness range taken by contact stylus and confocal white light optical scanner. As an application, a method for qualifying replica materials is also presented. Our method uses roughness standards of at least three different roughnesses and takes replicas of them. The inverted scanned profiles of the replicas are compared with the scanned profiles of the original surfaces. The comparison uses Helmert transform to fit the two corresponding profiles. The average distance of one of the profile point sets from the other one is calculated by determining the distance of all the points in one profile from the circles given by their three nearest measured points in the other profile. The method is also used for comparing the less noisy stylus scans and the more sensitive optical scans of the original surface in order to determine, whether the noise in the replica scans are due to the replica taking process or to the scanning.
Open Access: Yes
