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Post-Processing of Raw Data Recorded Continuously Using a FORS-Fibre-Optic Rotational Seismograph.

Bartosz SakowiczMarek KamińskiMichał DudekAnna T KurzychLeszek R Jaroszewicz
Published in: Sensors (Basel, Switzerland) (2022)
Modern optoelectronic devices use the advantage of digital systems for data processing aimed at delivering reliable information. However, since commonly used DACs have limited accuracy, some artefacts can be observed in data streams, especially in systems designed for continuous, long-term process monitoring. In this paper, the authors' experience with data enhancement using a fibre-optic rotational seismograph (FORS) operating in a closed-loop mode is presented and discussed. Generally, two kinds of enhancement are described. The first one uses suitable filtering techniques adequate for FORS noise investigation, as well as a suitable data resampling method for transmitted data file size reduction. The second one relates to the artefacts observed during data recording in real time. The recording starting point is triggered when the detected signal exceeds a middle signal level and, therefore, the existence of artefacts generally disturbs the recording process. Although the artefacts are easily recognised by human eyes even at first sight, their automatic elimination is not so easy. In this paper, the authors propose a new concept of signal filtering to solve the above problem.
Keyphrases
  • electronic health record
  • big data
  • endothelial cells
  • healthcare
  • data analysis
  • air pollution
  • deep learning
  • optic nerve