内蒙古地区强震动台站背景噪声与数据质量分析

Ambient noise and data quality analysis of strong motion stations in Inner Mongolia region

  • 摘要: 计算了内蒙古地区193个强震动台站2022年连续观测数据的加速度功率谱密度,通过绘制不同时空、不同加速度计、不同频段的功率谱密度和功率谱概率密度函数图及背景噪声速度均方根值分布图,评估了该区强震动台站的背景噪声变化特征,对出现的功率谱密度异常进行了具体分析,并针对强震动台站数据异常检测及处理提出了相应的建议。研究结果显示:不同加速度计、不同时空强震动台站的背景噪声功率谱密度昼夜差异主要体现在1 Hz以上频段,且不同区域的昼夜差异变化较大;QA-2g型、JS-A2型和TDA-33M型三种加速度计在2 s频点的背景噪声功率谱密度随区域和三分向变化较小;从强震动台站2 s频点背景噪声的监控能得到可靠的观测数据异常,数据异常主要由加速度计零点漂移大、加速度计故障、脉冲干扰、系统参数有误造成,建议优化站点观测环境,进一步规范仪器安装、调试及JOPENS系统的参数配置和审核。

     

    Abstract: Along with the construction of the project of National Earthquake Intensity Rapid Reporting and Early Warning, Inner Mongolia has established 193 strong motion stations and a data center. This paper calculated the acceleration power spectral density (PSD) of countinous waveform records of the 193 stations in 2022 by using the power spectral probability density function (PDF). By drawing the distribution maps of PSD, power spectral PDF and RMS value of ambient noise in different frequency bands in different time-space with different-type accelerometers, the variation characteristics of ambient noise at the strong motion stations in our studied region is evaluated, and then the PSD anomalies are analyzed. Accordingly, the constructive suggestions are put forward for the anomaly detection and strong ground motion data processing. The results show that the diurnal difference in PSD of ambient noise at different stations with different seismometers mainly appears in the frequency band above 1 Hz, and the diurnal PSD difference in different regions differs largely. The ambient noise values in the data recorded by seismometers QA-2g, JS-A2 and TDA-33M at frequency 2 s show little change with space and direction, so we can get reliable anomalies from the observation data by monitoring the ambient noise at frequency 2 s. The change of ambient noise with high frequency band at strong ground stations mainly comes from the change in environmental noise, but the influence of instrument self-noise cannot be completely ignored. Anomalous strong ground data is mainly resulted from large zero point shift of accelerometers, accelerometer failure, pulse interference and incorrect system parameters. Therefore it is recommended to optimize the observation environment of the stations, further standardize the instrument installation and debugging, and to configure and review the JOPENS system parameter.

     

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