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多准则优化方法在数字测量仪器校准过程中的应用。

Application of Multi-Criteria Optimization Methods in the Calibration Process of Digital Measuring Instruments.

机构信息

Faculty of Mechanical and Electrical Engineering Polish Naval Academy, Smidowicza 69, 81-127 Gdynia, Poland.

Faculty of Navigation and Naval Weapons Polish Naval Academy, Smidowicza 69, 81-127 Gdynia, Poland.

出版信息

Sensors (Basel). 2023 Mar 9;23(6):2984. doi: 10.3390/s23062984.

DOI:10.3390/s23062984
PMID:36991697
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10052159/
Abstract

The article describes the use of multi-criteria optimization methods during the calibration of digital multimeters. Currently, calibration is based on a single measurement of a specific value. The aim of this research was to confirm the possibility of using a series of measurements in order to reduce the measurement uncertainty without significantly extending the calibration time. The automatic measurement loading laboratory stand used during the conducted experiments was essential to obtain results that allowed confirming the thesis. This article presents the applied optimization methods and the results of the calibration of sample digital multimeters obtained thanks to them. As a result of the research, it was found that the use of a series of measurements increased the accuracy of the calibration, reduced the measurement uncertainty, and shortened the calibration time compared to traditional methods.

摘要

本文描述了在数字多用表校准过程中使用多准则优化方法。目前,校准是基于对特定值的单次测量。本研究的目的是确认使用一系列测量的可能性,以便在不显著延长校准时间的情况下降低测量不确定性。在进行实验过程中使用的自动测量加载实验室工作台对于获得允许确认论文的结果至关重要。本文介绍了所应用的优化方法以及通过这些方法获得的示例数字多用表的校准结果。研究结果表明,与传统方法相比,使用一系列测量可提高校准精度、降低测量不确定性并缩短校准时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/de25b36a6229/sensors-23-02984-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/80c393cdb943/sensors-23-02984-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/0608da26d087/sensors-23-02984-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/de25b36a6229/sensors-23-02984-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/661f1d1df212/sensors-23-02984-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/4bfa13019738/sensors-23-02984-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/667282a2e437/sensors-23-02984-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/2fda40daab53/sensors-23-02984-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/f09efb410739/sensors-23-02984-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/8e45ae373d0d/sensors-23-02984-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/80c393cdb943/sensors-23-02984-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/ddfe63e2c455/sensors-23-02984-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/b5de03c4893f/sensors-23-02984-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/0608da26d087/sensors-23-02984-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8f9/10052159/de25b36a6229/sensors-23-02984-g012.jpg

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