Analysis of measurement uncertainty of a surface acoustic wave micro-pressure sensor

Huang, Jian; Li, Yuanyuan; Jiang, Bei; Cao, Le

doi:10.1177/0020294018819554

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…And a considerable amount of papers has been published on uncertainty evaluation for multi-output nonlinear measurement models in many fields (Dadamos et al, 2019; Kowaluk et al, 2018; Tomczyk, 2019; Wang et al, 2018). Some analysts (Moona et al, 2018) have attempted to draw subtle distinctions between MCM and GUM (Huang et al, 2019; Ramebäck and Lindgren, 2018; Witkovský et al, 2017). The uncertainty of non-uniform residual stresses was evaluated in MCM (Peral et al, 2017), and the most critical parameters of the model were determined by comparing the influence of the input probability density on the uncertainty.…”

Section: Related Workmentioning

confidence: 99%

Adaptive quasi-Monte Carlo method for uncertainty evaluation in centroid measurement of planetary rovers

Qiang

Tao

et al. 2020

Transactions of the Institute of Measurement and Control

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The measurement of the centroid is of great significance to improve the control performance and reduce the energy consumption of the planetary rover (PR). The uncertainty is an essential indicator of the reliability of centroid measurement results. The purpose of the current study is to evaluate the uncertainty of centroid measurement in the multi-configuration rover. For the measurement of the centroid, the model with 37 parameters of two measurements as the input and the centroid coordinates as the output is derived. Further, the mechanical and electrical integrated system is developed, which can measure the centroid of PRs in different configurations and sizes. Moreover, to overcome the shortcomings of the Monte Carlo method (MCM) in uncertainty evaluation, an adaptive algorithm that automatically determines the number of input sequences is proposed. On this basis, an adaptive quasi-Monte Carlo method (AQMCM) is presented in order to accelerate the uncertainty evaluation, which is characterized by the randomized Sobol sequence. Besides, experiments are performed to compare the uncertainty evaluation process and results of the AQMCM and the adaptive Monte Carlo method (AMCM) in multiple configurations. The result shows that the standard uncertainty of the AQMCM is almost the same as that of the AMCM, but the sequence size of AQMCM is evidently smaller than that of AMCM. Taken together, we identify that the AQMCM evaluates the uncertainty of CM for the multi-configuration rover in an efficient and fast way. Furthermore, the AQMCM provides a new method for uncertainty evaluation, particularly for nonlinear models in different states.

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Section: Related Workmentioning

confidence: 99%

Adaptive quasi-Monte Carlo method for uncertainty evaluation in centroid measurement of planetary rovers

Qiang

Tao

et al. 2020

Transactions of the Institute of Measurement and Control

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“…In order to align with internationalization, China released the JJF1059.1-1999" Evaluation and Representation of Measurement Uncertainty" in 1999. At present, research on the evaluation of measurement uncertainty of air pressure sensors has been carried out successively, such as Huang J et al [9], Theodoro F R F et al [10], DellEra G et al [11], using the GUM method to evaluate the measurement uncertainty of surface acoustic wave micro-pressure sensor, pressure sensor submitted to a step input, and unsteady pressure single sensor probe, and achieving good research results. However, there are currently no relevant reports on research on aneroid barometer.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Evaluation of Measurement Uncertainty of Aneroid Barometer Based on GUM Method

Li,

Zhou

et al. 2024

Advances in Transdisciplinary Engineering

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In response to the current lack of research on the evaluation of measurement uncertainty for aneroid barometer, this study used the GUM method to evaluate the measurement uncertainty of their calibration results. The study first analyzed the evaluation process and steps of the GUM method. Then, according to the requirements of JJG 272-2007 “Aneroid barometer and Aneroid Barograph”, calibration experiments were conducted on the DYM3 type aneroid barometer. Finally, the measurement uncertainty of the calibration results was evaluated using the GUM method, and the expanded uncertainty U95 = 0.8hPa and U = 0.8hPa were obtained. This study provides a reference route and scheme for the evaluation of measurement uncertainty of aneroid barometer. This provides technical support for effectively improving the accuracy of air pressure measurement of aneroid barometer.

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“…On the other hand, Type-B uncertainty incorporates the effects of factors such as the measurement process itself or the measurement equipment, methods or environment, which usually cannot be directly calculated through the use of statistical methods. Instead, estimations based on information such as expert opinions, past experience, manufacturers' statements, literature data or calibration reports can be used [4].…”

Section: Introduction (Helvetica 10p Bold)mentioning

confidence: 99%

Measurement Resolution in Uncertainty Calculation with the GUM Method Approach: A LabVIEW Application

Çıtak

Bicakcı

2023

EJT

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GUM (Guide to the Expression of Uncertainty in Measurement) is a method used for calculating uncertainty in measurements. The method involves an uncertainty calculation approach which also constitutes a reference for the international ISO/IEC 17025 standard. In the GUM method, all uncertainties are expressed as standard uncertainty. An uncertainty may incorporate various components where impacts from multiple sources are taken into consideration. Resolution errors resulting from the sensitivity of the measurement equipment has a significant impact in the calculation of uncertainty. Sensitivity of an analog measurement device such as a multimeter depends on the resolution of the ADC it contains. Multimeters with 8-bit resolution ADCs are often used as measurement devices for sensor voltage values to be read once or several times. Factors such as high measurement resolution and reading errors by operators lead to an increase in uncertainty. Multiple data from a sensor or many sensors cause a significant increase in uncertainty, which results in a serious loss of time and labor. In order to mitigate said two factors which increase uncertainty in such cases, analog data needs to be converted to digital data at high resolution and transferred into computer medium. In this study, an D7714 analog/digital converter IC with 24-bit resolution has been used to transfer digital data into computer medium via myRIO 1950. A LabVIEW-based software has been developed to perform register settings for the AD7714 IC and to retrieve data at 24-bit resolution.

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Analysis of measurement uncertainty of a surface acoustic wave micro-pressure sensor

Cited by 3 publications

References 11 publications

Adaptive quasi-Monte Carlo method for uncertainty evaluation in centroid measurement of planetary rovers

Adaptive quasi-Monte Carlo method for uncertainty evaluation in centroid measurement of planetary rovers

Analysis and Evaluation of Measurement Uncertainty of Aneroid Barometer Based on GUM Method

Measurement Resolution in Uncertainty Calculation with the GUM Method Approach: A LabVIEW Application

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