PREPROCESSING OF HOPKINSON BAR EXPERIMENT DATA: FILTER ANALYSIS

Authors

  • Marcel Adorna Czech Technical University in Prague, Faculty of Transportation Sciences, Department of Mechanics and Materials, Konviktská 20, 120 00 Prague 1, Czech Republic
  • Jan Falta Czech Technical University in Prague, Faculty of Transportation Sciences, Department of Mechanics and Materials, Konviktská 20, 120 00 Prague 1, Czech Republic
  • Tomáš Fíla Czech Technical University in Prague, Faculty of Transportation Sciences, Department of Mechanics and Materials, Konviktská 20, 120 00 Prague 1, Czech Republic
  • Petr Zlámal Czech Technical University in Prague, Faculty of Transportation Sciences, Department of Mechanics and Materials, Konviktská 20, 120 00 Prague 1, Czech Republic

DOI:

https://doi.org/10.14311/APP.2018.18.0077

Keywords:

SHPB, filter analysis, strain-gage measurements, Chebyshev filter

Abstract

This work presents a data preprocessing procedure for signal acquired during high strain-rate loading using a custom Split Hopkinson Pressure Bar (SHPB). Before the evaluation of the experimental data, preprocessing of the measured signals including application of suitable digital or analog filter needs to be performed. Our department mainly focuses on measurements performed on advanced materials (e.g. materials with predefined structures or hybrid foams). For such measurements, it is essential to perform data preprocessing and apply suitable filter, to be able to appropriately determine deformation pulses on the measuring bars. This paper focuses foremost on spectral analysis of the measured signals, and design of optimal method of data filtering. Data from several different SHPB experiments were processed and results of different filtering methods are shown in this paper. Parameters of the best performing filter were optimized and shown to be universal for wide range of SHPB measurements.

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Published

2018-10-23

How to Cite

Adorna, M., Falta, J., Fíla, T., & Zlámal, P. (2018). PREPROCESSING OF HOPKINSON BAR EXPERIMENT DATA: FILTER ANALYSIS. Acta Polytechnica CTU Proceedings, 18, 77–81. https://doi.org/10.14311/APP.2018.18.0077