To overcome this difficulty, this paper proposes a near-fault ground motion identification method based on ensemble empirical mode decomposition (EEMD). Compared with other near-fault identification methods, such as near-fault ground motion identification method based on empirical mode decomposition (EMD), this method can accurately obtain the low-frequency signal of ground motion, and then identify near-fault ground motion more accurately. To verify the quality of near-fault ground motions identified by near-fault ground motions based on EEMD, the fault distance, pulse period and acceleration response of near-fault ground motions are analyzed. It is found that the near-fault ground motions obtained by EEMD can effectively avoid the misidentification of near-fault ground motions, and the identified near-fault ground motions have stronger near-fault characteristics.
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This work is supported by the National Natural Science Foundation Key Project of China (No. 51178080) and Doctoral Research Initiation Fund of Shandong Technology and Business University (No. BS201931). The author would like to thank the Pacific Earthquake Engineering Research (PEER) Center for the earthquake data.
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Liu, Z., Li, X. & Zhang, Z. Quantitative Identification of Near-Fault Ground Motions Based on Ensemble Empirical Mode Decomposition. KSCE J Civ Eng 24, 922–930 (2020). https://doi.org/10.1007/s12205-020-1491-2
- Near-fault ground motion
- Quantitative identification
- Ensemble empirical mode decomposition
- Velocity pluses