Evidence map›Paper›PMID 33668404›Full record

ArticleMicromachines2021

Characterization of Machined Surface Topography Based on the Normal Declination Angle of Microfacets.

Wei-Chao Shi, Jian-Ming Zheng, Qi-Long Wang, Li-Jie Wang, Qi Li

Abstract read
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Wei-Chao ShiSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.
Jian-Ming ZhengSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.
Qi-Long WangSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.
Li-Jie WangSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.
Qi LiSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is important to characterize surface topography in order to study machined surface characteristics. Due to the features of periodicity and randomness of machined surface topography, the existing topographical parameters may not describe its features accurately. A novel characterization method called the normal declination angle of microfacet-based surface topography is thus proposed for this task. The topography of machined surfaces is measured and the data on the normal declination angle are obtained. Then, surface topography is analyzed via the distribution of the normal declination angle. The lognormal distribution characterization model of machined surface topography is established, and the accuracy of the model is verified by error analysis. The results show that the calculated results of the present characterization model are generally consistent with the distribution of the normal declination angle, where the maximal root mean square errors (RMSE) is 4.5%. Therefore, this study may serve as an effective and novel way to describe the characteristics of the machined surface topography.

Indexed as

characterization methodlognormal distributionmachined surface topographymicrofacet theorynormal declination angle

Identifiers

PMID33668404
PMCPMC7996345

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.