A system and method for monitoring debris flow based on seismic data

Abstract

The application discloses a kind of mud-rock flow monitoring system and method based on seismic data, system includes mud-rock flow monitoring service platform, data center, seismic monitor, mud-rock flow monitoring service platform provides seismic monitor state display for user, analysis and parameter inversion etc. Service of seismic signal;Data center is used to realize the transmission, storage, management and backup function of seismic monitoring data;Seismic monitor is used to collect the seismic motion signal generated in the process of mud-rock flow, and simultaneously provides 5G transmission network, and the seismic motion signal data is transmitted to data center.The application can realize remote contactless data acquisition of mud-rock flow, real-time monitoring and analysis of mud-rock flow occurrence position and time, solve the problem of difficult monitoring means, low information accuracy, complex operation of operating personnel and other problems.

Description

Technical Field

[0001] This invention belongs to the field of geological monitoring technology, specifically a debris flow monitoring system and method based on seismic data. Background Technology

[0002] Southwest my country is characterized by its vast and complex topography, featuring numerous high mountains and deep valleys with significant elevation differences. Located near the collision zone between the Indian and Eurasian plates, the region has experienced frequent earthquakes due to the development of folds and faults. Its subtropical monsoon climate, combined with abundant rainfall and heavy to torrential downpours, results in abundant precipitation. These factors combined make Southwest my country a high-risk area for large-scale landslides and debris flows. Large-scale landslides and debris flows are typically characterized by their large scale, high speed, and powerful impact. Once they occur, they not only cause immense damage to the natural ecosystem but also severely threaten densely populated areas along riverbanks and in low-lying valleys. In recent years, several large-scale landslide disasters in Southwest China have resulted in severe casualties and property damage.

[0003] In the early stages of debris flow disaster research, most studies employed field investigation methods, inferring the location of debris flow sources and the different stages of their movement based on on-site survey data. However, this method was wasteful of manpower, resources, and time, and had a limited scope of application. With technological advancements, new technologies and equipment have gained popularity among researchers, such as long-term monitoring sensors like mud level gauges, rain gauges, and piezometers, as well as drone aerial imagery to acquire three-dimensional data of debris flow areas and establish digital models. However, these methods have inherent limitations. The accuracy of data fusion from various sensors and evaluation systems such as early warning thresholds is relatively low. Drone aerial photography is only suitable for post-event analysis and cannot achieve real-time monitoring. Furthermore, these early warning methods struggle to perform dynamic analysis of debris flows, failing to accurately obtain physical parameters at each stage of debris flow occurrence, and lacking a comprehensive understanding of debris flows. Summary of the Invention

[0004] The purpose of this invention is to provide a debris flow monitoring system and method based on seismic data, aiming to solve the problems of difficult means of monitoring sudden debris flows, low information accuracy, and complicated operation for workers, and to realize remote, non-contact data acquisition of debris flows, as well as real-time monitoring and analysis of the location and time of debris flow occurrence.

[0005] The technical solution to achieve the purpose of this invention is as follows:

[0006] A debris flow monitoring method based on seismic data includes the following steps:

[0007] Step 1: Collect seismic motion data generated during the debris flow and perform noise reduction processing on the seismic data;

[0008] Step 2: Separate the main characteristic components of the seismic data to obtain effective ground motion signals generated by debris flows;

[0009] Step 3: Perform Fourier transform on the denoised seismic data to perform spectral analysis of the seismic data, and obtain the time information of debris flow occurrence and the power spectral density of ground motion signal.

[0010] Step 4: Establish the positional relationship between the earthquake monitoring instrument and the earthquake source, and obtain the location of the earthquake source;

[0011] Step 5: Establish the power spectral density function to calculate the power spectrum of the earthquake data and obtain the flow rate information of the debris flow.

[0012] A debris flow monitoring system based on seismic data includes:

[0013] Seismic monitoring instruments are used to collect seismic data generated during debris flows.

[0014] The data center is used to realize the data transmission, storage, management, and backup functions of the debris flow monitoring service platform;

[0015] The debris flow monitoring service platform is used to denoise seismic data, separate the main characteristic components of the seismic data, and obtain effective ground motion signals generated by debris flows; it performs Fourier transform on the denoised seismic data to achieve spectral analysis of the seismic data, obtain the time information of debris flow occurrence and the power spectral density of the ground motion signal; it establishes the positional relationship between the seismic monitoring instrument and the seismic source to obtain the location of the seismic source; and it uses the power spectral density function to calculate the power spectrum of the seismic data, providing users with status queries of the seismic monitoring instrument and seismic data, and displaying the location, time, and scale of debris flows.

[0016] The significant advantages of this invention compared to existing technologies are:

[0017] This invention integrates an earthquake monitoring instrument and 5G network equipment to achieve debris flow monitoring based on earthquake data, overcoming the shortcomings of traditional monitoring methods that are time-consuming, labor-intensive, and have low safety coefficients. Utilizing real-time transmitted earthquake data, timely monitoring can be provided in debris flow-prone areas, ensuring personnel safety. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of a debris flow monitoring system based on seismic data.

[0019] Figure 2 Diagram showing the components of a debris flow monitoring service platform.

[0020] Figure 3 This is a schematic diagram of an earthquake monitoring instrument.

[0021] Figure 4 This is a flowchart of the seismic data processing workflow. Detailed Implementation

[0022] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0023] This implementation case provides a debris flow monitoring method based on seismic data, including the following steps:

[0024] Step 1: Collect ground motion data generated during the debris flow using an earthquake monitoring instrument, and perform noise reduction processing on the earthquake data;

[0025] The original seismic data was denoised using a band-pass filter (BP filter). By identifying the frequency range of the effective signal, the amplitude of the signal within the seismic signal band was kept unchanged, while the amplitude outside the band was set to 0. Interference signals (other strong artificial or natural vibration signals) were eliminated, and seismic data related to debris flow disasters in a specific frequency band were obtained.

[0026] Step 2: Separate the main characteristic components of the seismic data to obtain effective ground motion signals generated by debris flows;

[0027] Empirical Mode Decomposition (EMD) is used to decompose the data into intrinsic mode functions (IMFs), thereby reducing noise in the ground motion data. Earthquake data generated by debris flow disasters are typical nonlinear stationary signals (significantly affected by noise) and are accompanied by other earthquake data of similar frequencies. EMD can effectively decompose the non-stationary and nonlinear signal into a set of orthogonal components, separating the principal eigencomponents from other residuals to obtain clear time-domain curves, thus achieving noise reduction of the original ground motion signal.

[0028] Step 3: Perform Fourier transform on the denoised seismic data to perform spectral analysis of the seismic data, and obtain the time information of debris flow occurrence and the power spectral density of ground motion signal.

[0029] Steps 2 and 3 yield effective seismic signals. The processed seismic signals are then analyzed using Fast Fourier Transform (FFT) and Short-Time Fourier Transform (STFT) to obtain information such as frequency variation over time, the occurrence time of each component, and the instantaneous frequency and amplitude at each moment. This allows for the analysis of the time of debris flow occurrence and the duration of different stages of the debris flow. Simultaneously, Fourier transform techniques are used to estimate the power spectral density, facilitating subsequent analysis of debris flow parameters using the power spectral density.

[0030] Step 4: Establish the positional relationship between the earthquake monitoring instrument and the earthquake source, and obtain the location of the earthquake source;

[0031] The coordinates of the earthquake monitoring instrument can be obtained precisely using methods such as BeiDou positioning, but the latitude and longitude of the earthquake source and the propagation speed of seismic waves are unknown. By acquiring the initial arrival data from different earthquake monitoring instruments and establishing three or more observation equations, the latitude and longitude of the earthquake source can be derived using least squares calculations. This can be achieved using built-in functions in MATLAB for nonlinear least squares calculations. The distance relationship between the earthquake monitoring instrument and the earthquake source can be expressed by the following formula:

[0032]

[0033] In the formula, x and y represent the latitude and longitude coordinates of the earthquake source, x i y i Let t represent the latitude and longitude coordinates of the i-th seismic monitoring instrument, respectively. i denoted by , v represents the time it takes for the seismic wave signal to travel from the source to the i-th seismic monitoring instrument, and v represents the velocity of the seismic S-wave.

[0034] By solving the above equations, the latitude and longitude of the earthquake source and the propagation velocity of the seismic waves can be obtained. After obtaining the latitude and longitude coordinates of the earthquake source, combined with the latitude and longitude of the seismic monitoring instruments, the distance of each seismic monitoring instrument from the earthquake source can be calculated, that is, the distance r0 between the seismic monitoring instrument and the debris flow source.

[0035] The time it takes for the seismic motion signal of a debris flow to reach seismographs at different distances will vary. Knowing the distance between two seismographs, the velocity of the debris flow can be estimated by the time difference between the arrival of the seismic signals between the two seismographs. This invention uses the time difference of the maximum amplitude to compare the values ​​of the two seismic motion signals. The average velocity u of the debris flow can be calculated by the following formula.

[0036]

[0037] In the formula, n represents the number of deployed seismic monitoring instruments, and Δs it represents the distance between the i-th seismic monitoring instrument and the (i-1)-th seismic monitoring instrument, which can be precisely determined in advance. i and t i+1 These represent the times when the seismic waves arrive at the i-th and i+1-th seismic monitoring instruments, respectively, from which the velocity of each section of the debris flow and the average velocity of the entire process can be calculated.

[0038] Step 5: Establish the power spectral density function to calculate the power spectrum of the seismic data and obtain information such as the flow rate of debris flows;

[0039] Establish the power spectral density function of debris flow, obtain the energy distribution of ground motion signal within a certain frequency range at various times, and understand the statistical characteristics of high, medium and low frequency components of ground motion signal during the debris flow process and the signal power distribution at different times.

[0040] The power spectral density function of debris flow is established as follows:

[0041]

[0042] In the formula, P is the power spectral density of the seismic signal at a specific frequency f, with units of (m / s). 2 / Hz, ξ is the seismic velocity parameter, V c Here, r0 is the Rayleigh wave phase velocity at 1 Hz, r0 is the distance between the seismic monitoring instrument and the debris flow source, Q is the Rayleigh wave quality factor, L and W are the length and width of the moving material, respectively, D is the diameter of the debris flow particles, and u is the average velocity of the debris flow. From the above formula, it can be seen that the amplitude of the P value largely depends on LWD. 3 u 3 The product of.

[0043] The value of P is related to the length and width of the specific debris flow segment, the diameter of the debris flow particles, and their velocity. The length and width of the debris flow basin, as determined by on-site surveys at debris flow disaster sites, can be known beforehand. Combined with the velocities of different debris flow segments, and based on the product relationship between P and L, W, and u, the diameter D of the debris flow particles can be calculated. From this, the particle sizes carried in different debris flow segments can be deduced, allowing for the analysis of the distribution of particulate matter carried at different stages of the debris flow.

[0044] Finally, by combining the length, width, and depth of the debris flow basin, and the debris flow velocity calculated according to formula (2), the flow rate of the debris flow can be calculated, as shown in formula (4).

[0045] Q = S × u = L × W × u (4)

[0046] In the formula, Q represents the flow rate of the debris flow, S represents the cross-sectional area of ​​the debris flow, L and W are the length and width of the debris flow, respectively, and u represents the average velocity of the debris flow.

[0047] The scale of a debris flow can be roughly assessed based on its flow rate, particle size and distribution at different stages.

[0048] This implementation case also provides a debris flow monitoring system based on seismic data, including a debris flow monitoring service platform, a data center, and seismic monitoring instruments, such as... Figure 1 As shown.

[0049] The debris flow monitoring service platform is used to provide users with status queries of earthquake monitoring instruments and earthquake data, as well as displays of the location, time, and scale of debris flows.

[0050] The data center is used to realize the data transmission, storage, management, and backup functions of the debris flow monitoring service platform;

[0051] The earthquake monitoring instrument is used to collect earthquake data generated during debris flow events, providing data support for the debris flow monitoring service platform. The earthquake monitoring instrument is a short-period high-frequency digital seismograph, with a built-in complete three-dimensional displacement transducer short-period seismometer. Its observation frequency band reaches 2 seconds to 50 Hz. It is compact, fully functional, and the entire system is lightweight.

[0052] The debris flow monitoring service platform includes an authentication management module, a secure communication module, an information management module, a data analysis module, an information query module, and an early warning release module, such as... Figure 2 As shown;

[0053] The authentication management module is used to perform secure authentication of users' identities and permissions when users log in to the debris flow monitoring service platform, and to control users' access and operation permissions.

[0054] The information management module is used to enable the debris flow monitoring service platform to comprehensively manage user information, permission information, earthquake data information, and disaster source location information, and to provide different operation permissions according to different user permissions;

[0055] The data analysis module allows users to perform comprehensive analysis of earthquake data. It mainly consists of signal preprocessing and parameter analysis. Signal preprocessing includes noise removal, mean removal, and trend removal to remove noise caused by other natural and human activities and obtain effective earthquake data. Parameter analysis includes time-frequency analysis and power spectral density analysis to determine the location and time of debris flow sources and analyze their scale. See steps 1-5 above for details, which will not be repeated here.

[0056] The information query module is used to enable the debris flow monitoring service platform to query user information, seismic monitoring instrument status information, debris flow location information, communication information, and early warning information.

[0057] The early warning release module is used to release disaster early warnings for specific debris flows, including the location and estimated scale of the debris flow.

[0058] The data center includes backup servers, storage devices, and network equipment. The backup servers store data generated during system operation, ensuring data security; the storage devices store user information, historical earthquake data, and previous early warning information; and the network equipment connects the system to the earthquake monitoring instruments.

[0059] The data center is used to transmit, store, manage, and back up data from the debris flow monitoring service platform. It mainly includes backup servers, storage devices, and network equipment. The storage devices are equipped with the corresponding database software.

[0060] Combination Figure 3 The earthquake monitoring instrument is a short-period high-frequency digital seismograph, with a built-in complete three-dimensional displacement transducer short-period seismometer. It has an observation frequency band from 2 seconds to 50 Hz, a compact structure, complete functions, and is lightweight. Its specific features are as follows:

[0061] (1) The structure is compact, the functions are complete, and the whole set of equipment is lightweight;

[0062] (2) The data collector has a built-in embedded Linux operating system, which has powerful data storage and management capabilities and data service capabilities. Through the LAN network interface, it supports multi-channel continuous real-time data stream transmission and remote FTP download of data files.

[0063] (3) Built-in 8G (expandable) large-capacity memory, which can store real-time acquired data for a long time.

[0064] Combination Figure 4 The earthquake monitoring instrument collects ground motion data generated during the debris flow; the earthquake monitoring instrument transmits the data to the data center; the data center forwards the data to the debris flow monitoring service platform; the debris flow monitoring service platform performs comprehensive analysis of the earthquake data; the debris flow monitoring service platform analyzes and obtains parameters such as the location, time, and scale of the debris flow.

Claims

1. A debris flow monitoring method based on seismic data, characterized in that, Includes the following steps: Step 1: Collect seismic motion data generated during the debris flow and perform noise reduction processing on the seismic data; Step 2: Separate the main characteristic components of the seismic data to obtain effective ground motion signals generated by debris flows; Step 3: Perform Fourier transform on the denoised seismic data to perform spectral analysis of the seismic data, and obtain the time information of debris flow occurrence and the power spectral density of ground motion signal. Step 4: Establish the positional relationship between the earthquake monitoring instrument and the earthquake source, and obtain the location of the earthquake source; Step 5: Establish the power spectral density function to calculate the power spectrum of the seismic data and obtain the flow rate information of the debris flow. The power spectral density function is: In the formula, It is a specific frequency of seismic signal The power spectral density, These are ground motion velocity parameters. It is the Rayleigh wave phase velocity at 1Hz. This represents the distance between the earthquake monitoring instrument and the debris flow source. It is the quality factor of Rayleigh ripple. and These are the length and width of the moving substance, respectively. The diameter of the debris flow particles. The average velocity of the debris flow is given.

2. The debris flow monitoring method based on seismic data according to claim 1, characterized in that, The location of the earthquake source can be obtained by establishing three or more observation equations and then using least squares to derive the latitude and longitude of the source; the distance between the seismic monitoring instrument and the source is expressed by the following formula: In the formula, Indicates the latitude and longitude coordinates of the earthquake source. They represent the first The latitude and longitude coordinates of each earthquake monitoring instrument. This indicates that the seismic wave signal travels from the source to the... The time of each earthquake monitoring instrument Indicates the velocity of the S-wave in an earthquake; By solving the above equations, the latitude and longitude of the earthquake source and the propagation speed of the seismic waves can be obtained. Combined with the latitude and longitude of the seismic monitoring instruments, the distance of each seismic monitoring instrument from the earthquake source can be obtained.

3. The debris flow monitoring method based on seismic data according to claim 1, characterized in that, Information on the scale of debris flows includes the flow rate and particle size. The particle diameter of debris flow is obtained through the debris flow power spectral density function; The formula for calculating the flow rate of debris flow is: In the formula, Represents the flow rate of debris flows. Represents the area of ​​the cross-section of the debris flow. and These are the length and width of the debris flow, respectively. This represents the average velocity of the debris flow.

4. The debris flow monitoring method based on seismic data according to claim 3, characterized in that, The formula for calculating the average velocity of debris flow is: In the formula, This represents the number of deployed earthquake monitoring instruments. Representing the The earthquake monitoring instrument and the first The distance between the earthquake monitoring instruments These represent the arrival times of the seismic waves. and the The time of each earthquake monitoring instrument.

5. A debris flow monitoring system based on seismic data, characterized in that, include: Seismic monitoring instruments are used to collect seismic data generated during debris flows. The data center is used to realize the data transmission, storage, management, and backup functions of the debris flow monitoring service platform; The debris flow monitoring service platform is used to denoise seismic data, separate the main characteristic components of the seismic data, and obtain effective ground motion signals generated by debris flows; it performs Fourier transform on the denoised seismic data to achieve spectral analysis of the seismic data, obtain the time information of debris flow occurrence and the power spectral density of the ground motion signal; it establishes the positional relationship between the seismic monitoring instrument and the seismic source to obtain the location of the seismic source; and it uses the power spectral density function to calculate the power spectrum of the seismic data, providing users with status queries of the seismic monitoring instrument and seismic data, and displaying the location, time, and scale of debris flows. The power spectral density function is: In the formula, It is a specific frequency of seismic signal The power spectral density, These are ground motion velocity parameters. It is the Rayleigh wave phase velocity at 1Hz. This represents the distance between the earthquake monitoring instrument and the debris flow source. It is the quality factor of Rayleigh ripple. and These are the length and width of the moving substance, respectively. The diameter of the debris flow particles. The average velocity of the debris flow is given.

6. The debris flow monitoring system based on seismic data according to claim 5, characterized in that, The debris flow monitoring service platform includes: The authentication management module is used to securely authenticate the user's identity and permissions when the user logs into the debris flow monitoring service platform, and to control the user's access and operation permissions. The information management module is used to enable the debris flow monitoring service platform to comprehensively manage user information, permission information, earthquake data information, and disaster source location information, and to provide different operation permissions according to different user permissions; The data analysis module is used to perform comprehensive analysis of earthquake data, obtain information on the time of debris flow occurrence and the power spectral density of ground motion signals, obtain the location of the epicenter, and obtain information on the flow rate of debris flow. The information query module is used to enable the debris flow monitoring service platform to query user information, seismic monitoring instrument status information, debris flow location information, communication information, and early warning information.

7. The debris flow monitoring system based on seismic data according to claim 6, characterized in that, The debris flow scale information includes the debris flow rate and particle size. The particle diameter of debris flow is obtained through the debris flow power spectral density function; The formula for calculating the flow rate of debris flow is: In the formula, Represents the flow rate of debris flows. Represents the area of ​​the cross-section of the debris flow. and These are the length and width of the debris flow, respectively. This represents the average velocity of the debris flow.

8. The debris flow monitoring system based on seismic data according to claim 7, characterized in that, The formula for calculating the average velocity of debris flow is: In the formula, This represents the number of deployed earthquake monitoring instruments. Representing the The earthquake monitoring instrument and the first The distance between the earthquake monitoring instruments These represent the arrival times of the seismic waves. and the The time of each earthquake monitoring instrument.

9. The debris flow monitoring system based on seismic data according to claim 5, characterized in that, The data center includes: Backup servers are used to store data generated during system operation and ensure data security. Storage devices are used to store user information, historical earthquake data, and previous early warning information; Networking equipment is used to connect the system and earthquake monitoring instruments.

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