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Task-specific uncertainty of areal surface texture measurement using structured illumination microscopy

Surface quality plays a vital role in controlling the function performance of the workpiece. With the development of the measuring technique, areal surface measurement has been widely applied in the industry. However, estimating the uncertainty of areal surface measurement is still a challenge. Except for the metrological characteristics of the measurement system, measurement conditions should be considered for uncertainty evaluation.
The dissertation investigates the influence of measurement settings on surface measurement. A silver-plated surface, three different rough grinding surfaces, and three different rough cylindrical grinding surfaces were measured using structured illumination microscopy. The measurements were at the different objective lenses, vertical scanning interval, exposure time, and sample tilt. The results show that the measurement settings influence the non-measured points, measurement noise, and areal surface texture parameters. Therefore, according to the investigation, the sample tilt and exposure time should also be included in the uncertainty budget.
An approach was proposed to investigate the influence of non-measured points on the areal surface texture parameters. The relation between the non-measured points ratio and measurement settings was investigated, and how the areal surface texture parameters changed due to the non-measured points was studied. Moreover, an approach based on the metrological characteristic method was proposed to estimate the uncertainty due to the measurement noise. This method can be extended to the uncertainty evaluation due to other metrological characteristics. Additionally, an approach based on the Monte Carlo Method was proposed to estimate the measurement uncertainty due to different influences. This approach was verified as feasible in the practical measurement.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:85621
Date31 May 2023
CreatorsLi, Zhen
ContributorsGröger, Sophie, Seewig, Jörg, Technische Universität Chemnitz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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