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

Dataset

Description

** 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.
Date made available11 Feb 2019
PublisherUniversity of Bristol

Cite this

Luca, F. D. (Creator) (11 Feb 2019). Electronic appendix to Automated Classification of Near-Fault Acceleration Pulses Using Wavelet Packet v2. University of Bristol. 10.5523/bris.3u7wmvffczr162ejyzn51zvy85