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Characteristics and interpretation of the seismic signal of a field-scale landslide dam failure experiment 被引量:5
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作者 YAN Yan CUI Peng +3 位作者 CHEN Su-chin CHEN Xiao-qing CHEN Hua-yong CHIEN Yi-liang 《Journal of Mountain Science》 SCIE CSCD 2017年第2期219-236,共18页
Outburst floods caused by breaches of landslide dams may cause serious damages and loss of lives in downstream areas; for this reason the study of the dynamic of the process is of particular interest for hazard and ri... Outburst floods caused by breaches of landslide dams may cause serious damages and loss of lives in downstream areas; for this reason the study of the dynamic of the process is of particular interest for hazard and risk assessment. In this paper we report a field-scale landslide dam failure experiment conducted in Nantou County, in the central of Taiwan.The seismic signal generated during the dam failure was monitored using a broadband seismometer and the signal was used to study the dam failure process.We used the short-time Fourier transform(STFT) to obtain the time–frequency characteristics of the signal and analyzed the correlation between the power spectrum density(PSD) of the signal and the water level. The results indicate that the seismic signal generated during the process consisted of three components: a low-frequency band(0–1.5 Hz), an intermediate-frequency band(1.5–10 Hz) and a highfrequency band(10–45 Hz). We obtained the characteristics of each frequency band and the variations of the signal in various stages of the landslide dam failure process. We determined the cause for the signal changes in each frequency band and its relationship with the dam failure process. The PSD sediment flux estimation model was used to interpret the causes of variations in the signal energy before the dam failure and the clockwise hysteresis during the failure. Our results show that the seismic signal reflects the physical characteristics of the landslide dam failure process. The method and equipment used in this study may be used to monitor landslide dams and providing early warnings for dam failures. 展开更多
关键词 Landslide dam Dam failure process Field-scale experiment Seismic signal
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Study on the Method of Short-Term Synthetic Earthquake Prediction in the North China Region
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作者 PingJianjun ZhangYongxian +4 位作者 ZhangQingrong LiuSuying ChenJianguo HuangWanfa MiXuemei 《Earthquake Research in China》 2004年第2期188-199,共12页
Based on the extraction and calculation of the short-term seismic precursory information magnitude from the 114 major precursory observations in the North China region, and together with consideration of factors such ... Based on the extraction and calculation of the short-term seismic precursory information magnitude from the 114 major precursory observations in the North China region, and together with consideration of factors such as geological structure, seismicity, crustal thickness, and in particular, the current geodynamics of the region, the authors studied the time-space evolution characteristics of the short-term earthquake precursory information magnitude and its relationship with earthquakes and proposed the index and method for the short-term synthetic prediction of earthquakes with M S≥5.0 in the North China region. The inspection through R-value shows that the method is effective to a certain extent for earthquake prediction. 展开更多
关键词 The North China region Precursory information magnitude of short-term earthquake anomaly Information field Evolution characteristics Methods of synthetic prediction
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The Application of Wavelet Transform in Analysis of Digital Precursory Observational Data
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作者 SongZhiping WuAnxu +5 位作者 WangWei GengJie SongXianyue NiYouzhong ZhuJiamiao KanDaoling 《Earthquake Research in China》 2004年第3期225-233,共9页
Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend... Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend anomalies and the short-term anomalies. This paper presents a method to separate the high frequency information from the low ones by using the wavelet transform to analyze the digital data of precursors, and illustrates with examples the train of thoughts of discriminating the short-term anomalies from trend anomalies by using the wavelet transform, thus provide a new effective approach for extracting the short-term and trend anomalies from the digital data of precursors. 展开更多
关键词 Wavelet transform Digital data of precursors High and low frequency variation information Trend anomaly and short-term anomaly
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