Evidence map›Paper›PMID 36079450›Full record

ArticleMaterials (Basel, Switzerland)2022

A Measurement Solution of Face Gears with 3D Optical Scanning.

Xinxin Lu, Xing Zhao, Bo Hu, Yuansheng Zhou, Zhezhen Cao, Jinyuan Tang

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xinxin LuState Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China.ORCID 0000-0002-1107-7359
Xing ZhaoState Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China.
Bo HuState Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China.ORCID 0000-0002-4345-610X
Yuansheng ZhouState Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China.ORCID 0000-0002-4738-289X
Zhezhen CaoState Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China.
Jinyuan TangState Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China.

Funding

National Natural Science Foundation of China 51705541National Science and Technology Major Project of China 2019-VII-0017-0158
6 · The paper itself

Abstract

Gears are usually measured by the contact metrology method in gear measuring centers or coordinate measuring machines. Recently, three-dimensional (3D) optical scanning, a non-contact metrology method, has been applied in the industry as an advanced measurement technology mainly due to its high efficiency. However, its applications to gears with complicated geometry, such as face gears, are still limited due to its relatively low accuracy and the void of related measurement solutions. In this work, an accurate measurement solution with 3D optical scanning is proposed for the tooth surface deviations of orthogonal face gears. First, point cloud collection is carried out by the 3D scanner. Furthermore, the measurement solution is implemented with a three-stage algorithm by aligning point clouds with the design model. Subsequently, 3D modeling is studied by numbering the points and reconstructing the real tooth surfaces. An example with a measurement experiment and loaded tooth contact analysis is given to show the validity of the proposed method.

Indexed as

3D optical scanningface gearsloaded tooth contact analysispoint cloudstooth surface deviations

Identifiers

PMID36079450
PMCPMC9457429

What OpenQuestion holds

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Registered trials

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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.