201919th International Congress of Metrology
|Number of page(s)||7|
|Section||IOT and Calibration Challenges / IOT : défis pour l’étalonnage|
|Published online||23 September 2019|
Methods for dynamic calibration and augmentation of digital acceleration MEMS sensors.
Physikalisch-Technische Bundesanstalt, Bundesallee 100, 38116 Braunschweig
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We present a method for data acquisition and calibration of digital accelerometers which is being developed within the EMPIR Met4FoF project based on STM32 microcontrollers. Unlike analog sensors, some MEMS sensors with digital interface generate the sample clock themselves. For a dynamic calibration the exact knowledge of the sample times is essential. Therefore, an interrupt controlled data acquisition based on hardware timers with absolute time stamping was implemented. These routines are generic and can be used both for sensors that perform the measurements automatically, or for sensors whose data acquisition is requested by a hardware or software interrupt. The synchronization of the hardware timer with the absolute time is done via GNS time services or another PPS time source. The data is transferred from the microcontroller via ethernet to a host PC, which is to provide an OPC-UA interface and thus enables simple integration of the sensor system into larger measuring systems, like existing calibration setups. In addition to the acquisition of raw data for sensor calibrations, the system consisting of microcontroller and driver on the host system is also intended to provide dynamic measurement uncertainties. In addition, information about the calibration and the status of the sensor should be available on the system. The calibration data should be stored inform of a signed xml file on the microcontroller. In addition to this static information, the system should also record dynamic information about the status of the sensor, such as operating time, exceeding of measuring ranges, min and max temperature during operation.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.