The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo Method

The analysis of rough surface morphology plays an important role in the functional characteristics of the contact surface of mechanical parts. Fractal geometry method is more accurate and sensitive than classical statistics model. For fractal representation of rough surface, it is necessary to deter...

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Main Authors: Shen Jingfang, Gong Yuqi, Meng Hang, Yang Jiajun
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:E3S Web of Conferences
Online Access:https://doi.org/10.1051/e3sconf/20183804013
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author Shen Jingfang
Gong Yuqi
Meng Hang
Yang Jiajun
author_facet Shen Jingfang
Gong Yuqi
Meng Hang
Yang Jiajun
author_sort Shen Jingfang
collection DOAJ
description The analysis of rough surface morphology plays an important role in the functional characteristics of the contact surface of mechanical parts. Fractal geometry method is more accurate and sensitive than classical statistics model. For fractal representation of rough surface, it is necessary to determine the proper fractal dimension calculation method. In this research, the effect of power spectral density method is studied based on Monte-Carlo method. The fractal dimensions are calculated, the theoretical and the calculated values are compared with paired samples. And the results are compared by non-parametric test. The result shows that power spectral density method has good characterization effect on fractal simulation contour curve. In addition, the precision of fractal dimension of power spectral density is related to fractal dimension of contour theory. The estimation methods of classical power spectral density have different application range.
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spelling doaj.art-884180f831b04f9fb11f807efbbdd9c42022-12-21T22:44:04ZengEDP SciencesE3S Web of Conferences2267-12422018-01-01380401310.1051/e3sconf/20183804013e3sconf_icemee2018_04013The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo MethodShen JingfangGong YuqiMeng HangYang JiajunThe analysis of rough surface morphology plays an important role in the functional characteristics of the contact surface of mechanical parts. Fractal geometry method is more accurate and sensitive than classical statistics model. For fractal representation of rough surface, it is necessary to determine the proper fractal dimension calculation method. In this research, the effect of power spectral density method is studied based on Monte-Carlo method. The fractal dimensions are calculated, the theoretical and the calculated values are compared with paired samples. And the results are compared by non-parametric test. The result shows that power spectral density method has good characterization effect on fractal simulation contour curve. In addition, the precision of fractal dimension of power spectral density is related to fractal dimension of contour theory. The estimation methods of classical power spectral density have different application range.https://doi.org/10.1051/e3sconf/20183804013
spellingShingle Shen Jingfang
Gong Yuqi
Meng Hang
Yang Jiajun
The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo Method
E3S Web of Conferences
title The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo Method
title_full The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo Method
title_fullStr The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo Method
title_full_unstemmed The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo Method
title_short The Fractal Characterization of Mechanical Surface Profile Based on Power Spectral Density and Monte-Carlo Method
title_sort fractal characterization of mechanical surface profile based on power spectral density and monte carlo method
url https://doi.org/10.1051/e3sconf/20183804013
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