Evidence map›Paper›PMID 32947983›Full record

ArticleSensors (Basel, Switzerland)2020

Computer Vision Tool-Setting System of Numerical Control Machine Tool.

Bo Hou, Congpeng Zhang, Shoubo Yang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Bo HouKey laboratory of molecular imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.ORCID 0000-0002-3748-389X
Congpeng ZhangSchool of Mechanical and Materials Engineering, North China University of Technology, Beijing 100144, China.
Shoubo YangKey Laboratory of Precision Opt-mechatronics Technology, Ministry of Education, Beihang University, Beijing 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An automatic tool-setting and workpiece online detecting system was proposed to study the key technologies of next-generation intelligent vision computerized numerical control (CNC) machines. A computer vision automatic tool-setting system for a CNC machine was set up on the basis of the vision tool-setting principle. A rapid vision calibration method based on the position feedback from the CNC machine was proposed on the basis of the theory of traditional vision system calibration. The coordinate mapping relationship of the image and the CNC machine, the tool-setting mark point on the workpiece, and the tool tip were calibrated. The vision system performance testing and system calibration experiments were performed. Experimental results indicated that the time consumption was 128 ms in image processing. The precision of tool setting and measuring was less than 1 μm. The workpiece positioning and processing online detection function of the system can completely meet the requirements of visual CNC machine application, and the system has wide application prospects.

Indexed as

automatic tool-settingimage processingintelligent vision machine toolmachine visionvision measurement

Identifiers

PMID32947983
PMCPMC7571089

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.