Electronic appendix to Automated Classification of Near-Fault Acceleration Pulses Using Wavelet Packet v2

This dataset supersedes the previous published version at doi: 10.5523/bris.1wc9d21lbd5fr2mvhng72zpyj3.

This study proposes a new algorithm for automatically classifying two types of velocity pulses that are produced either by a distinct acceleration pulse (acc-pulse) or a succession of high-frequency one-sided acceleration spikes (non-acc-pulse). For achieving this, wavelet packet transform is used to filter the high-frequency content and to extract the coherent velocity pulse. Then, the pulse period is unequivocally derived through the peak point method. Following the determination of the pulse-starting (ts) and pulse-ending (te) time instants in the velocity time-history, a local acceleration time-history truncated by ts and te is obtained. The maximum relative energy of the pulse between two adjacent zero crossings is then employed as indicator for distinguishing the two types of velocity pulses. The criteria for identifying acc-pulses and non-acc-pulses are calibrated using a training data set of manually classified ground motions from the Next Generation Attenuation West 2 project. Finally, significance of such a classification between velocity pulses of different characteristics is assessed through the comparison of elastic acceleration response spectra of the two categories of pulse-like records. Herein electronic appendix to the study including the algorithm output for the full database employed is proposed.

Creator(s) Flavia De Luca, Zhiwang Chang, Katsuichiro Goda
Publication date 12 Feb 2019
Language eng
Publisher University of Bristol
Licence Non-Commercial Government License for public sector information
DOI 10.5523/bris.3u7wmvffczr162ejyzn51zvy85
Complete download (zip) https://data.bris.ac.uk/datasets/3u7wmvffczr162ejyzn51zvy85/3u7wmvffczr162ejyzn51zvy85.zip
Citation Flavia De Luca, Zhiwang Chang, Katsuichiro Goda (2019): Electronic appendix to Automated Classification of Near-Fault Acceleration Pulses Using Wavelet Packet v2. https://doi.org/10.5523/bris.3u7wmvffczr162ejyzn51zvy85
Total size 6.6 MiB

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