小波分析在甘肃天水断层气氡数据分析中的应用

APPLICATION OF WAVELET ANALYSIS IN FAULT GAS RADON DATA ANALYSIS IN TIANSHUI,GANSU

利用db4小波变换分析原理,对甘肃天水毛集、马窑和原家庄3个测站2021—2022年的断层气氡观测数据进行分析,并将资料中低频和高频成分进行有效分离。结果表明:小波变换方法对不同频率的信息识别功能较强,能够更直观和显著地反映地震前兆异常现象。结合震例研究表明,小波分析是断层气氡观测资料消除噪声,识别地震中短期异常的一种有效方法。

Using the principle of db4 wavelet transform analysis,the fault gas radon observation data from Maoji,Mayao,and Yuanjiazhuang stations in Tianshui,Gansu from 2021 to 2022 were analyzed,and the low-frequency and high-frequency components in the data were effectively separated.The results show that the wavelet transform method has strong recognition function for information at different frequencies,and can reflect earthquake precursor anomalies intuitively and significantly.Combined with earthquake case studies,wavelet analysis is an effective method for eliminating noise in fault gas radon observation data and identifying short-term anomalies in earthquakes.