Int. J. Metrol. Qual. Eng.
Volume 12, 2021
|Number of page(s)||9|
|Published online||14 June 2021|
Use of MEMS sensors for condition monitoring of devices: discussion about the accuracy of features for diagnosis
Department of Industrial and Information Engineering and Economics, University of L'Aquila,
* Corresponding author: email@example.com
Accepted: 16 May 2021
This paper analyses the effect of the variability of metrological characteristics of a set of low-cost Micro Electro-Mechanical Systems (MEMS) for the acceleration measurement, on the calculation of typical features used for condition monitoring (CM) of automatic production lines. The knowledge of the contribution of the variability of metrological characteristics to the final accuracy of features is an aspect of interest when networks of low-cost sensors are used, in particular in case the variability of their characteristics is high. In fact, due to a mass production, the calibration is not carried out sensor by sensor, but the characteristics are determined on a sample basis and assigned to the entire batch. Neglecting the variability between sensors can lead to effects on the results of data analysis, which are not easily predictable. In this paper, the real variability of the sensor's characteristics, experimentally evaluated through the calibration of a set of 25 low-cost MEMS accelerometers, has been taken into account. Digital sensitivity, signal-to-noise ratio and data rate variability of each device have been considered for the analysis. The analysis has been carried out with reference to two different test cases of industrial interest, by modifying the real outputs of high performance piezoelectric accelerometers used for CM, in order to simulate the effect of the metrological characteristics of MEMS sensors. The results show which features, among those typically used for CM, are more affected and which characteristics of MEMS are more influencing the features themselves, with reference to the specific considered applications.
Key words: Condition monitoring / accuracy / sensor networks / MEMS accelerometers
© G. D'Emilia and E. Natale, Published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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