基于时间序列分析法的地震智能预警系统  

An Earthquake Intelligent Early Warning System Based on Time Series Analysis Method

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作  者:张令 马梦丹 ZHANG Ling;MA Mengdan(Puyang Earthquake Station,Puyang 457000,China)

机构地区:[1]濮阳市地震台,河南濮阳457000

出  处:《微型电脑应用》2025年第2期206-209,共4页Microcomputer Applications

摘  要:为了提升地震感知能力及等级判断准确性,提出基于时间序列分析法的地震智能预警系统。在系统硬件部分利用GNSS接收机实现卫星电文信号的接收及解码,配置加速度传感器测量地震波的加速度,结合串口通信与多个无线收发设备,满足系统内信号稳定无冲突传输需求。软件部分引入EEMD算法,提取GNSS接收机解码数据的时间序列的多尺度IMF分量,结合Hilbert变换得到描述地震信号内时间分布特征的Hilbert谱,以优化地震感知能力。将Hilbert谱转化为三元组形式后,输入Triplet-CNN网络,通过反复训练,使Triplet-CNN网络具备地震等级判断能力,并通过声光警报程序及液晶显示程序对地震等级判断结果实施预警输出。实验表明,所提系统对地震的感知能力较强,地震等级判断精准。To improve the ability of earthquake perception and the accuracy of level judgment,an earthquake intelligent early warning system based on time series analysis method is proposed.In the hardware part of the system,GNSS receivers are used to receive and decode satellite message signals,and acceleration sensors are configured to measure the acceleration of earthquake waves.Combined with serial communication and multiple wireless transceiver devices,stable and conflict-free signal transmission requirements are satisfied within the system.The software part introduces the EEMD algorithm to extract the multi-scale IMF components of the time series of the data decoded by the GNSS receiver,and combines the Hilbert transform to obtain the Hilbert spectrum that describes the temporal distribution characteristics of earthquake signals to optimize earthquake perception ability.After converting the Hilbert spectrum into triplet form,it is input into the Triplet-CNN network.Through repeated training,the Triplet-CNN network is equipped with earthquake level judgment ability,and the earthquake level judgment results are warned and output through sound and light alarm programs and liquid crystal display programs.The experiment shows that the proposed system has stronger perception ability for earthquakes and accurate judgment of earthquake level.

关 键 词:地震 智能预警系统 GNSS接收机 EEMD算法 Triplet-CNN网络 

分 类 号:TP315[自动化与计算机技术—计算机软件与理论]

 

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