Evidence map›Paper›PMID 42451515›Full record

ArticleSensors (Basel, Switzerland)2026

High-Precision Rotation Axis Calibration of Line-Structured Light Measurement System Using a Stepped Cylinder.

Yuehua Li, Ziqi Jia, Haiyong Chang, Jingbo Zhou, Tiejun Li

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Yuehua LiSchool of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China.ORCID 0000-0003-1000-9247
Ziqi JiaSchool of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China.
Haiyong ChangSchool of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China.
Jingbo ZhouSchool of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China.ORCID 0000-0002-5093-6806
Tiejun LiSchool of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China.ORCID 0000-0003-1361-1014

Funding

Major Science and Technology Support Program of Hebei Province 252G1802DNatural Science Foundation of Hebei Province E2024208086Science and Technology Program of Shijiazhuang 2510801201A
6 · The paper itself

Abstract

Line-structured light sensors have the advantages of simple structure, low cost, and high precision. Integrating the sensor with a turntable is an important strategy to achieve complete results of complex surfaces. To enhance measurement accuracy, we proposed a rotation axis calibration method using a stepped cylinder. Coefficients of the laser plane are firstly optimized based on the principle of cross-ratio invariance to ensure the sensor's own accuracy. At each rotational angle, the laser plane intersects the cylinder, and corner points on the edges are extracted as feature points. Subsequently, an objective function is established by minimizing the average distance between rotated feature points and ideal circles and is solved using sequential quadratic programming method. After optimization, the average diameter error of the stepped cylinder is reduced by more than 90%. The relative errors of other typical features (ball diameter, cylinder diameter, groove depth) are all less than 0.15%. Measurement results of complex objects with different materials are also successfully obtained with their small features clearly observable.

Indexed as

line-structured light measurement systemrotation axis optimizationstepped cylindersystem calibration

Identifiers

PMID42451515
PMCPMC13363773

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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.