Metrological traceability of a digital 3-axis MEMS accelerometers sensor network

Prato, Andrea; Mazzoleni, Fabrizio; D’Emilia, Giulio; Gaspari, Antonella; Natale, Emanuela; Schiavi, Alessandro

doi:10.1016/j.measurement.2021.109925

Cited by 22 publications

(16 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This aspect is crucial since this statistical methodology is in no way intended to replace the current rigorous metrological chain, nor to be used in applications that require measurements with high accuracy and low uncertainty. In fact, MEMS-based sensors are not intended as replacements for current traditional instrumentation but as complementary to them for the detection of physical phenomena, typically on a large scale through the use of extended sensor networks [22]. In practical applications, an extended sensor network, containing both statistically calibrated MEMS technology-based sensors and traditional higherquality measurement instruments in a few nodes, is certainly much safer and more trustworthy (and traceable) than any other network containing sensors of unknown or undefined sensitivity.…”

Section: Discussionmentioning

confidence: 99%

A Bayesian statistical method for large-scale MEMS-based sensors calibration: a case study on 100 digital accelerometers

Prato,

Pennecchi,

Genta

et al. 2023

Metrologia

Self Cite

View full text Add to dashboard Cite

Low-cost sensors and in particular Micro-Electro-Mechanical Systems (MEMS) devices are widely used in many applications, including consumer electronics, healthcare, automotive, and industrial automation. Their large-scale production (typically in the order of millions per week in a single factory) would require the calibration of a huge number of devices that would be costly and time-consuming. A solution can be found in the use of statistical methods in order to (at least partially) substitute for the typical calibration procedures. In this work, we propose a Bayesian method to statistically calibrate large batches of sensors using probabilistic models and prior knowledge. The method involves experimentally calibrating only a small sample of sensors, then infer the number of reliable sensors in the entire batch and assign an appropriate uncertainty to all the sensors. Therefore, it can be considered as a statistical calibration of the batch. The Bayesian nature of this approach allows reducing the number of experimental calibrations by incorporating the prior knowledge coming from the previous calibration of a “benchmark” batch, which is performed “once and for all” and is representative of the whole production process. The application and validation of the method are performed through the calibration of 100 digital MEMS accelerometers. Validation results showed an acceptable agreement between experimental-based bootstrap and theoretical values, with relative differences within ± 7 %.

show abstract

Section: Discussionmentioning

confidence: 99%

A Bayesian statistical method for large-scale MEMS-based sensors calibration: a case study on 100 digital accelerometers

Prato,

Pennecchi,

Genta

et al. 2023

Metrologia

Self Cite

View full text Add to dashboard Cite

show abstract

“…Several other NMIs are currently developing calibration systems with digital sensor interfaces [12,13]. Hence, a broader pilot study e.g.…”

Section: Discussionmentioning

confidence: 99%

Comparison in dynamic primary calibration of digital-output accelerometer between CEM and PTB

et al. 2022

View full text Add to dashboard Cite

In the framework of the EU-funded project \textit{Met4FoF} Metrology for the Factory of the future a method was developed to perform primary magnitude and phase calibration of accelerometers. The validation of the developed associated hard- and software, which is designed to complement conventional primary calibration systems, is demonstrated based on a comparison measurement between the project partners CEM and PTB. The results show that the statistical distribution of results is only a minor contribution to uncertainty. An evaluation of the comparison based on the conventional procedure and estabished CMCs proofes a good consistency between the two laboratories, although the utilized sensor was (only) industrial grade quality.

show abstract

“…This emerging need is addressed also to digital MEMS/NEMS accelerometers, although, at the present day, calibration of MEMS sensors with digital output is still a challenge in metrology of dynamic accelerations and vibrations. On the other hand, digital MEMS/NEMS accelerometers, as components of large sensor-networks, are nowadays widely used for monitoring and survey, in many applications, in which high precision is an essential requirement to supply high-quality data, within the due trustworthiness [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Metrological Characterization of Digital Mems Accelerometers in Dynamic Conditions: An Investigation of Linearity in Amplitude and Temperature Effects

Schiavi¹,

Prato²,

Mazzoleni³

et al. 2023

Proceedings of the 5th IMEKO TC22 Conference on Vibration Measurement

View full text Add to dashboard Cite

In several applications, such as industrial plants monitoring, or peculiar manufacturing process, the sensors are subjected to a wide range of acceleration amplitude levels or shocks, as well as thermal changes, that could affect the micro electromechanical inner parts, altering their performance and reliability. In this work, by applying a calibration procedure developed at INRIM, the main sensitivity of digital MEMS accelerometers is evaluated, as a function of amplitude, in the frequency domain. Moreover, a survey of temperature drift, from -20 °C up to 80 °C, is also performed, to characterize the suitability of digital MEMS accelerometers for actual applications.

show abstract

Metrological traceability of a digital 3-axis MEMS accelerometers sensor network

Cited by 22 publications

References 42 publications

A Bayesian statistical method for large-scale MEMS-based sensors calibration: a case study on 100 digital accelerometers

A Bayesian statistical method for large-scale MEMS-based sensors calibration: a case study on 100 digital accelerometers

Comparison in dynamic primary calibration of digital-output accelerometer between CEM and PTB

Metrological Characterization of Digital Mems Accelerometers in Dynamic Conditions: An Investigation of Linearity in Amplitude and Temperature Effects

Contact Info

Product

Resources

About