Mingming Wei, Yan Qi, Xingwang Chen, Taocheng Zhou, Jie Miao
{"title":"Uncertainty evaluation for aneroid barometer measurement part II: \"Monte Carlo method\".","authors":"Mingming Wei, Yan Qi, Xingwang Chen, Taocheng Zhou, Jie Miao","doi":"10.1063/5.0233769","DOIUrl":null,"url":null,"abstract":"<p><p>To further improve the accuracy of the measurement uncertainty evaluation results of the aneroid barometer and verify the applicability of the GUM evaluation of the aneroid barometer, the Monte Carlo method (MCM) is proposed to evaluate the measurement uncertainty of the calibration results of the aneroid barometer. An improved calibration technique for the aneroid barometer was utilized in this process, yielding more precise calibration data through a meticulously designed experimental program. Subsequently, single-batch MCM and adaptive MCM (AMCM) were applied separately for evaluation, and their results were compared and analyzed against the GUM method to verify the applicability of each approach. In addition, to comprehensively assess the effectiveness of the new methods, this study also conducted control evaluations using traditional methods that did not account for the effects of the coefficient box and indicator box performance. The results show that MCM is superior to the GUM method in accuracy and reliability and is also more efficient in execution. In particular, the evaluation results of single-batch MCM and AMCM are in good agreement, but AMCM shows a superior performance with fewer simulations and more efficient execution. When evaluating the uncertainty of the temperature coefficient, introducing the new method has little effect on the evaluation results; however, when evaluating the uncertainty of the indication error, introducing a new method can significantly improve the accuracy of the evaluation results. This indicates that the new method has significant advantages in improving the accuracy of the evaluation results. In addition, the GUM method was validated by MCM, and the results showed that the GUM method is still suitable for the measurement uncertainty evaluation of the indication error of the aneroid barometer. Therefore, it is recommended that MCM, especially AMCM, which is more efficient in implementation, should be preferred in the field of measurement uncertainty evaluation of the aneroid barometer; meanwhile, the GUM method, as the basic assessment method in this field, should be retained and continue to play its role.</p>","PeriodicalId":21111,"journal":{"name":"Review of Scientific Instruments","volume":"96 3","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Scientific Instruments","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1063/5.0233769","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
引用次数: 0
Abstract
To further improve the accuracy of the measurement uncertainty evaluation results of the aneroid barometer and verify the applicability of the GUM evaluation of the aneroid barometer, the Monte Carlo method (MCM) is proposed to evaluate the measurement uncertainty of the calibration results of the aneroid barometer. An improved calibration technique for the aneroid barometer was utilized in this process, yielding more precise calibration data through a meticulously designed experimental program. Subsequently, single-batch MCM and adaptive MCM (AMCM) were applied separately for evaluation, and their results were compared and analyzed against the GUM method to verify the applicability of each approach. In addition, to comprehensively assess the effectiveness of the new methods, this study also conducted control evaluations using traditional methods that did not account for the effects of the coefficient box and indicator box performance. The results show that MCM is superior to the GUM method in accuracy and reliability and is also more efficient in execution. In particular, the evaluation results of single-batch MCM and AMCM are in good agreement, but AMCM shows a superior performance with fewer simulations and more efficient execution. When evaluating the uncertainty of the temperature coefficient, introducing the new method has little effect on the evaluation results; however, when evaluating the uncertainty of the indication error, introducing a new method can significantly improve the accuracy of the evaluation results. This indicates that the new method has significant advantages in improving the accuracy of the evaluation results. In addition, the GUM method was validated by MCM, and the results showed that the GUM method is still suitable for the measurement uncertainty evaluation of the indication error of the aneroid barometer. Therefore, it is recommended that MCM, especially AMCM, which is more efficient in implementation, should be preferred in the field of measurement uncertainty evaluation of the aneroid barometer; meanwhile, the GUM method, as the basic assessment method in this field, should be retained and continue to play its role.
期刊介绍:
Review of Scientific Instruments, is committed to the publication of advances in scientific instruments, apparatuses, and techniques. RSI seeks to meet the needs of engineers and scientists in physics, chemistry, and the life sciences.