Research progress of baseline correction for near-field strong motion accelerogram
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摘要: 强震动加速度记录特别是近场强震动记录中经常会出现基线偏移的现象，加速度记录中的微小基线偏移会导致积分获得速度和位移时程产生不合理的非物理特征. 本文详细地分析了低频误差和地面的倾斜或旋转对原始加速度记录积分获得的速度和位移时程的具体影响，讨论了近场强震动记录基线校正的准则. 针对低频误差引起的基线偏移，论述了应用最广泛的高通滤波方法的基本原理，讨论了滤波器的选择、非因果滤波的加零填充、余弦渐变平滑零填充部分和加速度记录的过渡带、非因果滤波截止频率的选取标准以及去除零填充后如何避免获得的速度、位移时程和加速度反应谱值不兼容的问题. 针对地面倾斜或旋转引起的基线偏移，论述了Iwan两段式基线校正方法的原理，以及基于Iwan方法开发和改进的基线校正方法的研究进展，并指出各种方法存在的问题. 说明了对于不同地震尺度的近场强震动记录基线校正方法的选择. 在没有可用的方法可以量化不同误差来源的贡献以及无法同时测量六个分量的强震动记录（三个平移分量和三个旋转分量）之前，利用大数据分析和机器学习等技术手段，基于Iwan方法原理，从海量的近场强震动记录中自动快速识别出稳定、可靠的强震段和结束段开始时间将是未来的发展方向.Abstract: The baseline drift is often found in strong motion accelerograms, especially in the near-field accelerogram. The small baseline drift in accelerogram will lead to linear drift in the velocity time history obtained through single integration and parabolic drift in the displacement time history obtained through double integration, which are unreasonable non-physical characteristics. Low frequency errors and tilting or rotation of the ground are the main factors causing baseline drift in strong motion accelerograms. This paper introduces the types of low frequency error and analyzes the effects of low frequency errors and ground tilt or rotation on the velocity and displacement time history obtained from the original accelerogram in detail. The principle of baseline correction for near-field strong motion accelerogram is discussed. Considering the baseline drift caused by the low frequency error, we discuss the basic principle of the most widely used high-pass filtering method, and how to select filters. Then we analyze adding zero pads before acausal filtering, cosine to smoothing the transition band of zero pads and accelerogram. The selection criteria of acausal cut-off frequency is investigated. Furthermore, we discuss how to avoid the incompatibility of velocity, displacement time histories, and acceleration response spectra after removing zero pads. Aiming at the baseline drift caused by ground tilt or rotation, the principle of the two-stage baseline correction method is illustrated by Iwan. The research progress and compute methods of the baseline correction methods developed and improved based on the principle of Iwan’s method are also discussed, and the problems of these methods are pointed out. We also illustrate the selection of baseline correction methods of near-field strong motion accelerogram for different magnitude scales. Because there is no available method that can quantify the contributions of different error sources and not available strong motion accelerogram of six components (three translational and three rotational components), most of the baseline correction methods still belong to the experience and the semi-empirical. There is no general baseline correction method applied to all near-field strong motion accelerograms of different earthquakes. With the accumulation of near-field strong motion accelerogram on a global scale, the maturity of extensive data analysis and machine learning, based on the principle of the Iwan method, automatically and quickly identified the reliable beginning times of the strong shaking phase and the post-seismic phase from the massive near-field strong motion accelerograms will be the future development direction.
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图 1 芦山MS7.0地震51YAM台站NS向原始加速度、速度和位移时程
Figure 1. Original acceleration, velocity and displacement time histories in the NS direction of 51YAM station from the Ms7.0 Lushan earthquake
图 2 Iwan等（1985）两段式校正方法原理图（修改自Wu and Wu, 2007）
Figure 2. Schematic diagram of Iwan et al. (1985) two-stage baseline correction method (modified from Wu and Wu, 2007)
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