Evidence map›Paper›PMID 39459124›Full record

ArticleMicromachines2024

Image-Based Auto-Focus Microscope System with Visual Servo Control for Micro-Stereolithography.

Yijie Liu, Xuexuan Li, Pengfei Jiang, Ziyue Wang, Jichang Guo, Chao Luo, Yaozhong Wei, Zhiliang Chen, Chang Liu, Wang Ren and 3 more

Abstract read
In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

13 authors.

Yijie LiuCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.ORCID 0000-0003-4853-8515
Xuexuan LiState Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
Pengfei JiangCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Ziyue WangCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Jichang GuoCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Chao LuoCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Yaozhong WeiCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Zhiliang ChenCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Chang LiuCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Wang RenCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Wei ZhangCoal Mining Research Institute, China Coal Technology and Engineering Group Co., Ltd., Beijing 100013, China.
Juntian QuShenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.ORCID 0000-0002-1799-5847
Zhen ZhangState Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.ORCID 0000-0002-2122-7963

Funding

National Natural Science Foundation of China 52104091National Natural Science Foundation of China 52104162National Natural Science Foundation of China 52275564National Natural Science Foundation of China 52304140National Natural Science Foundation of China 52304172National Natural Science Foundation of China 52374125State Key Laboratory of Tribology in Advanced Equipment SKLT2024Z13
6 · The paper itself

Abstract

Micro-stereolithography (μSL) is an advanced additive manufacturing technique that enables the fabrication of highly precise microstructures with fine feature resolution. One of the primary challenges in μSL is achieving and maintaining precise focus throughout the fabrication process. For the successful application of μSL, it is essential to maintain the sample surface within a focal depth of several microns. Despite the growing interest in auto-focus devices, limited attention has been directed towards auto-focus systems in image-based auto-focus microscope systems for precision μSL. To address this challenge, we propose an image-based auto-focus microscope system incorporating visual servo control. In the optical design, a transflective beam splitter is employed, allowing the laser beam to pass through for fabrication while reflecting the focused beam on the sample surface to the microscope and camera. Utilizing captured spot images and the Foucault knife-edge test, a deep learning-based laser spot image processing algorithm is developed to determine the focus position based on spot size and the number of spot pixels on both sides. Experimental results demonstrate that the proposed auto-focus system effectively determines the relative position of the focal point using the laser spot image and achieves auto-focusing through visual servo control.

Indexed as

auto-focusdeep learninglasermachine visionmicro-stereolithographyvisual servo control

Identifiers

PMID39459124
PMCPMC11509336

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.