74 research outputs found
MEASUREMENT UNCERTAINTY: INTRODUCING NEW TRAINING MATERIAL AND A EUROPEAN TEACHERS’ COMMUNITY
Mixture distribution modelling of the sensitivities of a digital 3-axis MEMS accelerometers large batch
Huge quantities of low-cost analogue or digital MEMS sensors, in the order of millions per week, are produced by manufacturers. Their use is broad, from consumer electronic devices to Industry 4.0, Internet of Things and Smart Cities. In many cases, such sensors have to be calibrated by accredited laboratories to provide traceable measurements. However, at present, such a massive number of sensors cannot be calibrated and large-scale calibration systems and procedures are still missing. A first step to implementing these methods can be based on the distribution of the sensitivities of the large batches produced. Such distribution is also useful for sensor network end-users who need a single sensitivity, with the associated uncertainty, to be attributed to the whole network. Recently, a large batch of 100 digital 3-axis MEMS accelerometers was calibrated with a primary calibration system developed at INRiM and suitable for 3-axis accelerometers. Distributions of their sensitivities as a function of axis and frequency were analyzed and their non-normal behaviour was shown. However, in the preliminary phase of the study, the calibration uncertainties were not considered in these distributions. Therefore, in this paper, a mixture distribution modelling, based on Monte Carlo simulations and aimed at including the calibration uncertainties in the sensitivity distributions, is implemented and the resulting distributions are compared to the previous ones in histogram form. These distributions are also fitted with Johnson's unbounded and bimodal functions to get continuous distributions. This paper represents a further step towards the development of large-scale statistical calibration methods
Evaluating Measurement Uncertainty in Absolute Gravimetry: an Application of the Monte Carlo Method
Absolute gravity measurements are based on the reconstruction of the free-falling motion of a test body in vacuum. In this paper, two large disturbing effects are studied, namely, the non- gravitational accelerations originated by rotation and translation of the flying body. Their contribution to the uncertainty of the free-fall acceleration is evaluated using the method proposed in Supplement 1 to the GUM. The analysis is specifically applied to the IMGC-02 absolute gravimeter, but can be easily extended to other instruments
Stability study and uncertainty evaluation of CO2 certified reference materials for greenhouse gases monitoring
The continuous rising in the concentration of carbon dioxide (CO2) in the atmosphere is one of the main causes of
the increase in the greenhouse effect and global warming. To monitor the alarming scenario and to provide
Governments and decision makers with reliable emission data, gaseous certified reference materials (CRMs) at
atmospheric CO2 amount fraction are needed. This paper describes two independent metrological traceability
paths established at INRiM for the preparation of this kind of CRMs. The aim of this publication is to show a
method for evaluating the uncertainty associated with CRM stability and to demonstrate that there is no significant
trend in the results over time. Such CRMs are produced as an intermediate step towards the development
of novel generation CRMs certified also for the isotopic composition
Bayesian Machine Learning and variational inference for on-site sensor calibration in Smart Bay Santa Teresa seawater monitoring
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