Frequency Characteristics and Numerical Computation of Seismic Records Generated by a Giant Debris Flow in Zhouqu, Western China

Huang, Xinghui; Zhengyuan, Li; Fan, Jun; Yu, Dan; Xu, Qiang

doi:10.1007/s00024-019-02177-5

Cited by 9 publications

(4 citation statements)

References 26 publications

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“…The ZHQ seismic station is located some 170 m west of the outlet of the Sanyanyu gully, and its power system was destroyed by the Sanyanyu debris flow when its leading edge reached the vicinity of the seismic station. In the paper by Huang et al (2019), seismic signals recorded by the ZHQ station approximately 10 min before its termination were collected and analyzed to characterize the Sanyanyu debris flow, providing a good case of seismic recordings applied to the monitoring of other kinds of disasters.…”

Section: Other Regions and Other Phenomena Subject To Discussionmentioning

confidence: 99%

Continental Earthquakes: Physics, Simulation, and Data Science—Introduction

Zhang

Goebel

et al. 2019

Pure Appl. Geophys.

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During May 12-14, 2018, the International Conference for the Decade Memory of the Wenchuan Earthquake, in connection to the 4th International Conference on Continental Earthquakes (4th ICCE) and the 12th General Assembly of the Asian Seismological Commission (ASC), was held in Chengdu, China. There have been several outcomes of the Conference (for example, the book published jointly by Higher Education Press and Springer) as well as the present special issue. Among the 58 submissions, 34 have been accepted after peer review. Some of the papers came from the presentations during the Conference, but with additional submissions, the scope of this special issue is far beyond that of the proceedings of the meeting.

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Section: Other Regions and Other Phenomena Subject To Discussionmentioning

confidence: 99%

Continental Earthquakes: Physics, Simulation, and Data Science—Introduction

Zhang

Goebel

et al. 2019

Pure Appl. Geophys.

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“…Vibration sensors can also be used for testing and monitoring of vehicles with alternate fuels [19]. The main component of earthquake vibration or landslide vibration is a low-frequency component (2-20 Hz) [20,21]. In hilly terrain prone to landslides or earthquake-prone zones, various low-cost applications and inventions have developed using MEMS-based sensors such as MPU6050 for structural health monitoring [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Contact Type Vibration Measuring Sensors

Dhanda¹,

Pankaj²,

Dogra³

et al. 2022

Sound&Vibration

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With the Internet of Things (IoT) era dawning in, we are surrounded by a plethora of sensors. The present paper focuses on MEMS-based vibration measuring accelerometers, which are ubiquitously present in smartphones, tablets, smartwatches/bands, etc. These contact type vibration sensors have the unique advantage of being very small, low cost, low power, less weighing, and easily accommodatable in electronics. However, the accuracy of these sensors needs to be quantified with respect to more accurate sensors. With this objective, the paper presents a comparison of the relative sensitivity of a MEMS-based accelerometer (MPU 6050), a Geophone, and a sensor from Xiaomi Y2 smartphone with respect to a more standard Piezoelectric ICP based accelerometer, when all sensors are tested on a shaker table. Data are measured with harmonic excitation over a frequency range of 2-184 Hz. The relative sensitivity of MPU 6050 was 90% accurate in the frequency range 18-116 Hz for RMS measurements. Other sensors such as the one used in the Xiaomi Y2 smartphone and the Geophone were less accurate. The relative sensitivity measured in this work can be used to obtain sensitivity and hence more accurate data from these low-cost accelerometers.

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“…Andrade et al (2022) proposed a simple positive linear relationship between the peak amplitude of the seismic signal and the peak flow rate of the debris flow. Current research on seismic monitoring and debris flow early warning concentrates on event timing (Walter et al, 2017;Huang et al, 2020;Beason et al, 2021), location (Walter et al, 2017;Lai et al al., 2018), evolution of parameters such as velocity and flow (Arattano, 1999;Lai et al, 2018;Andrade et al 2022;Schimmel et al, 2022), and identification (Bessason et al, 2007;Schimmel and Hübl, 2016;Huang et al, 2020). To enable the widespread adoption of debris flow early warning systems using seismic monitoring, the approach needs to be standardized, quantified, and systematized (Bessason et al, 2007;Arattano et al, 2015;Allstadt et al, 2019).…”

mentioning

confidence: 99%

Real-time Monitoring and Analysis of Debris Flow Events: Insight from seismic signal features and dynamic flow characteristics

Yan,

Zeng,

Cui

et al. 2023

Preprint

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Abstract. Debris flows are among the most dangerous natural hazards worldwide because they start abruptly, move quickly, and transport large boulders, causing great loss of life and infrastructure. The most important approach to preventing and mitigating debris flows is through monitoring and early warning. In recent years, environmental seismology has emerged as a powerful method for monitoring debris flows because it allows non-contact observation over large areas and can provide extensive information on debris flow dynamics. However, further research is required on combining debris flow imagery with seismic signal analysis, incorporating information from post-disaster surveys, and the inversion of seismic signals into dynamic parameters of debris flows. Here, we aim to explore the basic parameters, development process, and magnitude of debris flows based on seismic signal analysis combined with other information recorded in real time during the formation and development of three debris flows in Wenchuan, China. The analysis involves three stages. First, we compensate for the energy loss of the seismic signal due to the absorption attenuation effect and restore the signal to an unchanged state as far as possible. Second, we identify the start and end time of the debris flow from the seismic signal, analyze the rainfall data to determine that the debris flow was triggered by the test rain, and determine that changes in the energy and frequency ranges of the seismic signal are highly consistent with the development of the debris flow. Third, a comprehensive analysis of debris flow images, the power spectral density (PSD) of the seismic signal, and forward modeling of the PSD of the seismic signal of the debris flow are used to reveal the relationship between the seismic signal and the development process of the debris flow and clarify the feasibility of debris flow analysis from the time-frequency characteristics of the seismic signal. Debris flow exhibits the characteristics of fast excitation and slow recession. Using the cross-correlation algorithm and verifying Manning's formula, a maximum velocity of 7.027 m/s was calculated for the second debris flow. A comparison of the frequency characteristics of the seismic signal allowed the relative magnitude of the three debris flows to be assessed. The study provides a theoretical basis and a case study exemplar for the reconstruction of the debris flow process and peak velocity estimation using debris flow seismology, offering a framework for upscaling debris flow monitoring networks and the determination of early warning thresholds.

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Frequency Characteristics and Numerical Computation of Seismic Records Generated by a Giant Debris Flow in Zhouqu, Western China

Cited by 9 publications

References 26 publications

Continental Earthquakes: Physics, Simulation, and Data Science—Introduction

Continental Earthquakes: Physics, Simulation, and Data Science—Introduction

Sensitivity Analysis of Contact Type Vibration Measuring Sensors

Real-time Monitoring and Analysis of Debris Flow Events: Insight from seismic signal features and dynamic flow characteristics

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