Evidence map›Paper›PMID 38475243›Full record

ArticleSensors (Basel, Switzerland)2024

Temperature-Automated Calibration Methods for a Large-Area Blackbody Radiation Source.

Wenhang Yang, Chen Cao, Pujiang Huang, Jindong Bai, Bangjian Zhao, Shouzheng Zhu, Haijun Jin, Ke Jin, Xin He, Chunlai Li and 3 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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. Article
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.

Wenhang YangHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Chen CaoHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.ORCID 0000-0003-1579-3755
Pujiang HuangHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Jindong BaiHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Bangjian ZhaoHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Shouzheng ZhuHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Haijun JinHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Ke JinHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Xin HeHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Chunlai LiHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.ORCID 0000-0003-4364-6867
Jianyu WangHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.ORCID 0000-0001-6611-8528
Shijie LiuHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Hongxing QiHangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.

Funding

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences B025F40622004Zhejiang Provincial Department of Science and Technology 2023C03012
6 · The paper itself

Abstract

High-precision temperature control of large-area blackbodies has a pivotal role in temperature calibration and thermal imaging correction. Meanwhile, it is necessary to correct the temperature difference between the radiating (surface of use) and back surfaces (where the temperature sensor is installed) of the blackbody during the testing phase. Moreover, large-area blackbodies are usually composed of multiple temperature control channels, and manual correction in this scenario is error-prone and inefficient. At present, there is no method that can achieve temperature-automated calibration for a large-area blackbody radiation source. Therefore, this article is dedicated to achieving temperature-automated calibration for a large-area blackbody radiation source. First, utilizing two calibrated infrared thermometers, the optimal temperature measurement location was determined using a focusing algorithm. Then, a three-axis movement system was used to obtain the true temperature at the same measurement location on a large-area blackbody surface from different channels. This temperature was subtracted from the blackbody's back surface. The temperature difference was calculated employing a weighted algorithm to derive the parameters for calibration. Finally, regarding experimental verification, the consistency error of the temperature measurement point was reduced by 85.4%, the temperature uniformity of the surface source was improved by 40.4%, and the average temperature measurement deviation decreased by 43.8%. In addition, this system demonstrated the characteristics of strong environmental adaptability that was able to perform temperature calibration under the working conditions of a blackbody surface temperature from 100 K to 573 K, which decreased the calibration time by 9.82 times.

Indexed as

auto-calibrationinfrared thermometerlarge-area blackbody radiation source

Identifiers

PMID38475243
PMCPMC10934448

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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.