Analysis on Baseline Correction Method of Strong Motion Accelerogram Recorded on Near-fault Site by the Shaking Table Test
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摘要: 为了获取近场永久位移，通常采用基线校正方法，对近场加速度记录进行基线校正并积分得到永久位移值，但这一结果主观性较强，其可靠性也往往缺乏验证。为了解决这一问题，本文提出了一种能产生包含永久位移振动过程的振动台实验方案，采用振动台加滑动机构的方法，模拟记录到永久位移台站测点的真实振动情况；在实验中分别采用加速度计、摄影测量方法分别直接得到加速度和位移时程，对加速度时程进行基线校正并积分得到位移时程，将其与直接获得的位移时程进行对比，以验证采用基线校正方法的有效性。实验结果表明，在实验室条件下采用现有的基线校正方法校正后，通过积分能得到可以接受的位移时程。Abstract: For determining the near-fault site permanent displacement in some specialized methods, near-fault accelerogram was corrected with baseline, and integrated into the displacement time history. The above result is often of uncertain and even not easy to be validated because of using the subjective parameters in process. To solve this problem, we proposed a shaking table test scheme to simulate the shake process including the permanent displacement. In the test, a system comprising the shaking table and the specialized sliding mechanism were used to model the actual shake situation on the site recorded the permanent displacement. The accelerogram was recorded by the accelerometer on the sliding mechanism, and the actual displacement time history was achieved on close-range photogrammetry. The displacement integrated by the accelerogram corrected the baseline was compared with the actual displacement to prove the reliability of the correction method. Our results show that the accelerogram could be integrated to the reliable displacement time history under the laboratory condition, after the baseline corrected with the specialized method.
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图 1 基于机器视觉的动态位移测量方法工作流程
Figure 1. Work flow of dynamic displacement measurement based on computer vision
图 2 标识点识别算法及优化算法实现效果图
Figure 2. Identification results of mark identification and color extraction algorithm
图 4 摄像帧率为25帧/s时的实验数据处理结果及局部放大比较
Figure 4. Dynamic displacement measurement results from 25 frames/s format video
图 5 摄像帧率为50帧/s时的实验数据处理结果及局部放大比较
Figure 5. Dynamic displacement measurement results from 50 frames/s format video
图 8 振动台峰值加速度200cm/s2、永久位移40cm工况位移时程获取和基线校正结果
Figure 8. Baseline corrected dynamic displacement history from accelerogram integration and displacement history by the proposed method in the work
图 9 积分校正位移时程和本文方法直接测得位移时程对比
Figure 9. Baseline corrected dynamic displacement history from accelerogram integration and displacement history by the proposed method in the study
表 1 不同测量方法得到动态位移峰值
Table 1. Dynamic displacement peak values measured from different methods
摄像帧率/帧·s－1 验证试验次数序号 拉线位移计测量值/mm 基于机器视觉测量方法的测量值/mm 白底方案 黑底方案 1 10.038 9.681（－3.56%） 9.687（－3.50%） 25 2 10.458 10.137（－3.07%） 10.169（－2.76%） 3 5.917 5.755（－2.74%） 5.721（－3.31%） 4 4.911 4.818（－1.89%） 4.804（－2.18%） 1 5.836 5.805（－0.53%） 5.770（－1.13%） 50 2 8.438 8.490（0.62%） 8.290（－1.75%） 3 10.775 10.608（－1.55%） 10.426（－3.24%） 4 10.368 10.201（－1.61%） 9.974（－3.80%） 
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表 2 永久位移15cm和40cm积分位移时程和视频处理位移时程尾值
Table 2. Permanent displacement from the baseline corrected accelerogram integration and proposed measurement method in the study
不同方法得到的永久位移值
/mm100cm/s2 200cm/s2 500cm/s2 永久位移
15cm永久位移
40cm永久位移
15cm永久位移
40cm永久位移
15cm永久位移
40cm积分得到位移 136.5 428.2 136.2 423.5 140.2 390.1 本文方法直接测量 152.3 443.0 130.1 417.6 159.8 367.4 相对误差/% 10.37 3.34 4.47 1.39 12.26 5.82
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