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强震动记录的数据处理流程:去噪滤波

姚鑫鑫 任叶飞 岸田忠大 温瑞智 王宏伟 冀昆

姚鑫鑫, 任叶飞, 岸田忠大, 温瑞智, 王宏伟, 冀昆. 强震动记录的数据处理流程:去噪滤波[J]. 工程力学, 2022, 39(S): 320-329. doi: 10.6052/j.issn.1000-4750.2021.05.S058
引用本文: 姚鑫鑫, 任叶飞, 岸田忠大, 温瑞智, 王宏伟, 冀昆. 强震动记录的数据处理流程:去噪滤波[J]. 工程力学, 2022, 39(S): 320-329. doi: 10.6052/j.issn.1000-4750.2021.05.S058
YAO Xin-xin, REN Ye-fei, KISHIDA Tadahiro, WEN Rui-zhi, WANG Hong-wei, JI Kun. THE PROCEDURE OF FILTERING THE STRONG MOTION RECORD: DENOISING AND FILTERING[J]. Engineering Mechanics, 2022, 39(S): 320-329. doi: 10.6052/j.issn.1000-4750.2021.05.S058
Citation: YAO Xin-xin, REN Ye-fei, KISHIDA Tadahiro, WEN Rui-zhi, WANG Hong-wei, JI Kun. THE PROCEDURE OF FILTERING THE STRONG MOTION RECORD: DENOISING AND FILTERING[J]. Engineering Mechanics, 2022, 39(S): 320-329. doi: 10.6052/j.issn.1000-4750.2021.05.S058

强震动记录的数据处理流程:去噪滤波

doi: 10.6052/j.issn.1000-4750.2021.05.S058
基金项目: 国家重点研发计划项目(2019YFE0115700);黑龙江省自然科学基金优秀青年项目(YQ2019E036);国家自然科学基金项目(51878632,51808514);黑龙江省头雁行动计划项目
详细信息
    作者简介:

    姚鑫鑫(1994−),女,吉林人,博士生,主要从事强震动数据处理研究(E-mail: yaoxinxiniem@126.com)

    岸田忠大(1976−),男,日本人,教授,博士,主要从事工程地震相关研究(E-mail: tadahiro.kishida@ku.ac.ae)

    温瑞智(1968−),男,山东人,研究员,博士,博导,主要从事工程地震相关研究(E-mail: ruizhi@iem.ac.cn)

    王宏伟(1990−),男,山东人,副研究员,博士,主要从事地震动特征及预测相关研究(E-mail: whw1990413@163.com)

    冀 昆 (1990−),男,山西人,副研究员,博士,主要从事工程抗震地震动输入相关研究(E-mail: jikun@iem.ac.cn)

    通讯作者:

    任叶飞(1983−),男,江苏人,研究员,博士,主要从事工程地震相关研究(E-mail: renyefei@iem.net.cn)

  • 中图分类号: TU311.3

THE PROCEDURE OF FILTERING THE STRONG MOTION RECORD: DENOISING AND FILTERING

  • 摘要: 强震动记录一直以来被用于工程结构弹塑性时程分析的地震动输入,其由仪器观测获得,需在使用前进行必要的数据处理工作。中国台网目前已累积了大量强震动观测记录,但始终缺乏标准化的数据处理流程,给使用者造成了诸多不便,不能最大程度发挥其科学应用价值。该文针对我国观测数据现状,提出了一套完整的面向工程应用的强震动记录数据处理流程,给出了高通滤波截止频率的选取原则,包括:记录的傅里叶振幅谱低频段须符合w2震源模型、信噪比须大于3、确保与物理分辨率一致。研究了因果滤波与非因果滤波对记录时程的影响,结果表明:这两种滤波方式具有各自特性,因果滤波会引起记录相变、而非因果滤波则会引起信号前干扰震动;针对芦山地震数据集及2017年部分观测记录,研究了这两种滤波方式对伪加速度反应谱(PSA)的影响,结果表明因果滤波引起的相变会对有效周期范围内的PSA造成计算偏差,因此建议面向工程应用的强震动记录选用非因果滤波方式。此项工作有助于指导和规范强震动记录的合理使用。
  • 图  1  本文给出的强震动记录数据处理流程

    Figure  1.  A flow chart for data processing of strong motion record suggested by this study

    2  脉冲信号经因果和非因果滤波后振幅及相位对比结果

    2.  Comparisons of amplitude and phase of an impulse signal produced by causal and acausal filtering

    图  3  典型记录经因果和非因果滤波后加速度、速度和位移时程比较(右图为左图阴影区域的局部放大)

    Figure  3.  Comparisons of acceleration, velocity and displacement time-series of a typical record processing by causal and acausal filtering (right figure represents a local zoom-in picture)

    图  4  选取的数据集记录在因果和非因果滤波后加速度、速度和位移时程与原始时程的相关系数

    Figure  4.  Correlation coefficients of the original acceleration, velocity and displacement time-series in the dataset with those processing by causal and acausal filtering

    图  5  典型记录经因果和非因果滤波处理后位移时程比较以及识别的P波到时与S波到时比较

    Figure  5.  Comparison of displacement time-series and P-wave and S-wave onsets of a typical record processing by causal and acausal filtering

    图  6  典型有噪声窗的强震动记录fHP选取过程示意以及因果滤波后位移时程合理性评判

    Figure  6.  Illustration of the fHP selection for a typical record with noise window and the rationality judgement of displacement time-series after a causal filtering

    图  7  典型无噪声窗强震动记录fHP选取过程示意以及因果滤波后位移时程合理性判断

    Figure  7.  Illustration of the fHP selection for a typical record without noise window and the rationality judgement of displacement time-series after a causal filtering

    图  8  典型记录在因果滤波和非因果滤波前、后的拟加速度反应谱对比

    Figure  8.  Comparison of the pseudo spectral accelerations of a typical record before and after its causal and acausal filtering

    图  9  选取的数据集记录在因果和非因果滤波前后的PSA对数差

    Figure  9.  Differences of pseudo spectral accelerations on a logarithmic scale between original and causal and acausal filtered records in the dataset

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出版历程
  • 收稿日期:  2021-05-12
  • 修回日期:  2022-02-09
  • 网络出版日期:  2022-03-01
  • 刊出日期:  2022-06-06

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