Characterization of Geometric Surface Features Using Statistically Based Analytical Tools

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Azimi, F. (2019). Characterization of Geometric Surface Features Using Statistically Based Analytical Tools. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

The nature and quality of a surface’s topography can play an important role in a part’s performance and expected longevity. The complexity of a surface topography means that while commonly used ISO 25178-2 height based statistical metrics are capable of quantifying periodicity and directionality, they are unable to completely describe geometric isolated surface features, i.e. unwanted processing defects. The same standard does outline other metrics capable to describing geometric features, but these require more processing and user input. This dissertation presents a novel approach for quantifying both surface characteristics and features by calculating simple statistical height data metrics as a surface is rotated about its center and then graphing them in a polar plot format. Key polar plots metrics such as minimum and maximum radius, number of lobes and difference between their angular locations, etc. can be used to quantify surface isotropy, surface directionality, and surface periodicity. Uniquely, analysis of the polar plots can also provide estimates of the number and geometric sizes of isolated circular and linear geometric surface features. The capabilities and limitations of the approach are outlined, and discussed with respect to actual surfaces topographies. The simplicity, and potential speed of the method addresses the ever-present industrial need for fast, robust methods of surface characterization.

Details
Author

Azimi, Farzad

Title

Characterization of Geometric Surface Features Using Statistically Based Analytical Tools

Physical Description

1 online resource (255 pages) : PDF

Date

2019

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

The nature and quality of a surface’s topography can play an important role in a part’s performance and expected longevity. The complexity of a surface topography means that while commonly used ISO 25178-2 height based statistical metrics are capable of quantifying periodicity and directionality, they are unable to completely describe geometric isolated surface features, i.e. unwanted processing defects. The same standard does outline other metrics capable to describing geometric features, but these require more processing and user input. This dissertation presents a novel approach for quantifying both surface characteristics and features by calculating simple statistical height data metrics as a surface is rotated about its center and then graphing them in a polar plot format. Key polar plots metrics such as minimum and maximum radius, number of lobes and difference between their angular locations, etc. can be used to quantify surface isotropy, surface directionality, and surface periodicity. Uniquely, analysis of the polar plots can also provide estimates of the number and geometric sizes of isolated circular and linear geometric surface features. The capabilities and limitations of the approach are outlined, and discussed with respect to actual surfaces topographies. The simplicity, and potential speed of the method addresses the ever-present industrial need for fast, robust methods of surface characterization.

Genre

doctoral dissertations

Subjects--Topics

Mechanical engineering

Degree

Ph.D.

Keywords

Feature Characterization
Statistical Analysis
Surface Metrology

Subject Area

Mechanical Engineering

Advisor(s)

Mullany, Brigid

Committee Members

Suleski, Thomas
Davies, Matthew
Kazemi, Mohammad
Morse, Edward

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2019.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Azimi_uncc_0694D_12256

Permalink

http://hdl.handle.net/20.500.13093/etd:2221