Articles | Volume 7, issue 1
https://doi.org/10.5194/jsss-7-245-2018
https://doi.org/10.5194/jsss-7-245-2018
Regular research article
 | 
06 Apr 2018
Regular research article |  | 06 Apr 2018

Calibration of tri-axial MEMS accelerometers in the low-frequency range – Part 1: comparison among methods

Giulio D'Emilia, Antonella Gaspari, Fabrizio Mazzoleni, Emanuela Natale, and Alessandro Schiavi

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Cited articles

Batista, P., Silvestre, C., Oliveira, P., and Cardeira, B.: Accelerometer calibration and dynamic bias and gravity estimation: Analysis, design, and experimental evaluation, IEEE T. Control Syst. Technol., 19, 1128–1137, https://doi.org/10.1109/TCST.2010.2076321, 2011. 
Borgia, E.: The Internet of Things vision: Key features, applications and open issues, Comput. Commun., 54, 1–31, https://doi.org/10.1016/j.comcom.2014.09.008, 2014. 
Chen, D. and Han, J.: Application of wavelet neural network in signal processing of MEMS accelerometers, Microsyst. Technol., 17, 1–5, https://doi.org/10.1007/s00542-010-1169-7, 2011. 
Czech, K. R. and Gosk, W.: Measurement of surface vibration accelerations propagated in the environment, Proc. Eng., 189, 45–50, https://doi.org/10.1016/j.proeng.2017.05.008, 2017. 
D'Emilia, G., Gaspari, A., and Natale, E.: Dynamic calibration uncertainty of three-axis low frequency accelerometers, Acta IMEKO, 4, 75–81, https://doi.org/10.21014/acta_imeko.v4i4.239, 2015. 
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Short summary
Low-frequency vibration measurements are of great interest in many fields like energy production, structural health monitoring (SHM) of buildings, geotechnical applications, human vibration and bio-dynamics, mainly because of the increasing development of MEMS embedded in mobile devices and in applications in the field of the Internet of Things (IoT). We investigated the effectiveness and efficaciousness of some available calibration techniques to promote their aware, widespread, use.