偏移量(计算机科学)
残余物
基线(sea)
流离失所(心理学)
地震动
大地测量学
噪音(视频)
计算机科学
地质学
算法
地震学
人工智能
海洋学
图像(数学)
心理学
程序设计语言
心理治疗师
作者
Xiaoyu Chen,Dongsheng Wang
标识
DOI:10.1016/j.soildyn.2022.107162
摘要
A new automatic baseline correction method based on the Hilbert spectral analysis (HSA) is proposed to recover a relatively reasonable time history of baseline offset, permanent displacement, and stable peak ground motion displacement (PGD) from a raw near-fault ground motion record. This method can get rid of the selection of the start time of strong motion (corresponding to t1 in traditional methods) by an adaptive extraction procedure, then a stable PGD as well as an accurate permanent displacement can be obtained. For baseline offsets, there is no two-stage-segment assumption in this procedure, and the extracted time histories of these offsets include complex frequency changes, which is more consistent with the explanations of causes for baseline offsets. All causes of baseline offsets are treated as contaminants that exist in all frequency ranges in a record. Uncontaminated components can be extracted from the original record by the HSA, then information about strong motions can be retained as much as possible. The residual part is regarded as a heavily contaminated component of which the energy of the noise rivals that of the real ground motion. It is corrected based on only one time point. Finally, the corrected record is contributed by both of the uncontaminated and adjusted contaminated components. The HSA method, which depends on the energy distribution of original record in different frequency component, can obtain the baseline offset, PGD, and permanent displacement reasonably, stably, and automatically.
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