Geological disaster identification method based on seismic wave dynamics and kinematics characteristics

Abstract

The invention provides a geological disaster identification method based on seismic wave dynamics and kinematics characteristics, the geological disaster is mountain torrent or debris flow, and the method comprises the following steps: collecting seismic signals in a geological disaster potential risk area; the seismic signals are preprocessed; extracting early warning parameters from the pre-processed seismic signal, wherein the early warning parameters comprise a long and short time window energy ratio, a time-frequency spectrum parameter, a power spectrum density and a seismic signal duration; establishing an earthquake prediction model of the single-measuring-point geological disaster according to the extracted early warning parameters; fusing the earthquake prediction models of the geological disasters at multiple measuring points, and judging whether the earthquake signals are earthquake signals triggered by the geological disasters or not; and when it is judged that the seismic signal is triggered by the geological disaster flow, real-time early warning information issuing is carried out on the downstream risk area. The method can be applied to monitoring and early warning of geological disasters caused by artificial or natural activities such as mountain torrents, dam break, landslides, collapse and the like, and has wide engineering technology application and scientific research prospects.

Description

Technical Field

[0001] This invention relates to the field of geological disaster prediction, and more specifically, to a method for identifying geological disasters such as flash floods and debris flows based on seismic wave dynamics and kinematic characteristics. Background Technology

[0002] Intelligent identification and early warning of engineering risks of geological disasters in mountainous areas induced by earthquakes, landslides, and debris flows, and risk warning for areas prone to geological disasters such as mountainous areas, have important engineering and social significance. Summary of the Invention

[0003] The purpose of this invention is to address at least one of the aforementioned shortcomings of the existing technology. For example, one objective of this invention is to provide risk warnings for geological disasters such as flash floods and mudslides.

[0004] To achieve the above objectives, the present invention provides a method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics.

[0005] The method of one aspect includes the following steps: S10: acquiring seismic signals in potential risk areas of geological hazards; S20: preprocessing the acquired seismic signals; S30: extracting early warning parameters from the preprocessed seismic signals, including the long-short time window energy ratio, time-spectrum parameters, power spectral density, and seismic signal duration; S40: establishing a single-point geological hazard seismic prediction model based on the extracted early warning parameters; S50: using the single-point geological hazard seismic prediction model to determine whether the seismic signal is triggered by a geological hazard.

[0006] Optionally, step S10 includes: selecting the potential risk area; selecting a gully section in the potential risk area where a geological hazard has formed; deploying several real-time transmission three-component seismographs in the gully section and acquiring the seismic signals.

[0007] Alternatively, the preprocessing in step S20 may include: removing instrument response and bandpass filtering.

[0008] Alternatively, the energy ratio of the long and short time windows is determined according to the following equations (1)-(3):

[0009] H AB (t0)=H A (t0) / H B (t0) (1)

[0010]

[0011]

[0012] Among them, HAB (t0) represents the energy ratio before and after the time window, H A (t0) represents the average energy of the previous time window, H B (t0) represents the average energy of the subsequent time window; t0 is a certain moment, t2-t0 is the length of the preceding time window, and t0-t1 is the length of the subsequent time window; S n (t0) represents the seismic signal acquired by the nth seismograph at time t0.

[0013] Optionally, the step of obtaining the time-frequency parameters includes: performing time-frequency analysis on the seismic signal to obtain the time-frequency parameters.

[0014] Alternatively, the time-spectrum parameters can be determined according to equation (4):

[0015]

[0016] Where t is the earthquake recording time, f is the seismic wave frequency, and S STFT (t,f) is the expression for the time-frequency transformation of the seismic record s(τ), where τ is the time length for the time window w(τ) and s(t-τ), s(t-τ) is the seismic wave record with time t and time window length τ for the window function w(τ), and i is the imaginary part symbol.

[0017] Alternatively, the power spectral density can be determined according to equation (5):

[0018]

[0019] Among them, f max For the maximum frequency, f min For minimum frequency, PSD fmin～fmax f max -f min The power spectral density function, S STFT (t,f) represents the time-frequency spectrum parameters.

[0020] Alternatively, the earthquake prediction model for the single-point geological hazard is as follows:

[0021]

[0022] Among them, H AB (t0) represents the energy ratio of the long and short time windows, f0 represents the dominant frequency of the seismic wave, and PSD represents the voltage level. fmin～fmax Here, T represents the power spectral density and T represents the duration of the seismic signal.

[0023] Alternatively, if the following five conditions of the earthquake prediction model for geological hazards at a single measuring point are met, the seismic wave signal observed at measuring point n may be triggered by flash floods and debris flows:

[0024] (1)HAB (t0) exceeds the threshold value;

[0025] (2) The dominant frequency f0 of the seismic wave is within the dominant frequency region of seismic waves that may be excited by geological disaster flows;

[0026] (3) The maximum frequency f of the seismic wave max and minimum frequency f min The frequency is also within the frequency range of seismic waves triggered by geological disasters;

[0027] (4) PSD fmin～fmax (t) exceeds the possible threshold value before a geological disaster occurs;

[0028] (5) The duration T of the earthquake waveform exceeds the possible duration of the geological disaster.

[0029] In another aspect, the present invention provides a method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics.

[0030] The method includes: S10: collecting seismic signals in potential risk areas of geological disasters; S20: preprocessing the collected seismic signals; S30: extracting early warning parameters from the preprocessed seismic signals, including the long-short time window energy ratio, time-spectrum parameters, power spectral density, and seismic signal duration; S40: establishing an earthquake prediction model for geological disasters at a single measuring point based on the extracted early warning parameters.

[0031] S50: An earthquake prediction model that integrates geological hazards from multiple measurement points and is used to determine whether an earthquake signal is triggered by a geological hazard.

[0032] Optionally, step S10 may include: selecting a potential risk area; selecting a gully section in the potential risk area where a geological hazard has formed; deploying multiple real-time transmission three-component seismographs in the gully section and acquiring seismic signals.

[0033] Alternatively, steps S20 to S40 may be the same as S20 to S40 in the above aspect.

[0034] Optionally, step S50 includes: when any two measuring points meet the earthquake early warning model for a single-measuring-point geological disaster, calculating the time difference of arrival of seismic waves and the theoretically calculated time difference between any two measuring points; if the difference between the time difference of arrival of seismic waves and the theoretically calculated time difference is within a predetermined range, then determining that the seismic signal monitored by any two observation points is a possible seismic signal for a geological disaster; when the pairing number of any two measuring points meets a predetermined value, then determining that the seismic signal is a seismic signal triggered by flash floods or debris flows.

[0035] The earthquake prediction model for single-point geological hazards is as follows:

[0036]

[0037] H AB (t0) represents the energy ratio of the long and short time windows, f0 represents the dominant frequency of the seismic wave, and PSD represents the voltage level. fmin～fmax Where is the power spectral density, and T is the duration of the seismic signal;

[0038] The standard for achieving the earthquake early warning model for geological disasters at a single measuring point is to meet at least three of the following conditions:

[0039] (1)H AB (t0) exceeds the threshold value;

[0040] (2) The dominant frequency f0 of the seismic wave is within the dominant frequency region of seismic waves that may be excited by geological disaster flows;

[0041] (3) The maximum frequency f of the seismic wave max and minimum frequency f min The frequency is also within the frequency range of seismic waves triggered by geological disasters;

[0042] (4) PSD fmin～fmax (t) exceeds the possible threshold value before a geological disaster occurs;

[0043] (5) The duration T of the earthquake waveform exceeds the possible duration of the geological disaster.

[0044] Optionally, the method further includes step S60: when it is determined that the earthquake signal is triggered by a geological disaster flow, real-time early warning information on geological disasters is released to downstream risk areas through networks or other means.

[0045] Compared with the prior art, the beneficial effects of the present invention include: the method is based on seismic wave dynamics and kinematic parameters to carry out seismic monitoring and early warning of debris flow and flash flood. The results of this method can be applied to the monitoring and early warning of geological disasters caused by human or natural activities, such as flash floods, dam breaks, landslides, and collapses, and have broad engineering and scientific research prospects. Attached Figure Description

[0046] The above and other objects and / or features of the present invention will become clearer from the following description taken in conjunction with the accompanying drawings, in which:

[0047] Figure 1 A flowchart illustrating the geological hazard identification method of the present invention is shown. Detailed Implementation

[0048] The following will describe in detail the geological hazard identification method based on seismic wave dynamics and kinematic characteristics of the present invention with reference to exemplary embodiments.

[0049] This invention is based on deploying real-time transmission seismographs in high-risk areas prone to flash floods and debris flows. The seismographs receive seismic wave signals that may be triggered by flash floods and debris flows. By utilizing seismic wave dynamics and kinematic parameters such as amplitude, duration, frequency, and power spectrum, the invention can automatically identify seismic signals induced by geological disasters such as flash floods and debris flows, thereby determining the trajectory and scale of geological disasters and enabling risk warnings for such disasters.

[0050] Exemplary Example 1

[0051] This exemplary embodiment provides a method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics. This method can identify geological hazards using a single measuring point. The method includes:

[0052] S10: Conduct seismic signal acquisition in areas with potential geological hazards.

[0053] In this embodiment, step S10 may include: selecting a potential risk area; selecting a gully section in the potential risk area where geological hazards are formed; deploying several real-time transmission three-component seismographs in the gully section and collecting seismic signals.

[0054] S20: Preprocess the acquired seismic signals.

[0055] In this embodiment, preprocessing may include removing instrument response and bandpass filtering.

[0056] S30: Extract early warning parameters from the preprocessed seismic signal.

[0057] In this embodiment, the warning parameters may include the long-short window energy ratio H. AB (t0), time-frequency parameter S STFT (t,f), power spectral density PSD fmin～fmax (t) and the duration T of the seismic signal.

[0058] In this embodiment, H AB (t0) can be determined according to the following equations (1)-(3):

[0059] H AB (t0)=H A (t0) / H B (t0) (1)

[0060]

[0061] Among them, H AB (t0) represents the energy ratio before and after the time window, H A (t0) represents the average energy of the previous time window, HB (t0) represents the average energy of the subsequent time window; t0 is a certain moment, t2-t0 is the length of the preceding time window, and t0-t1 is the length of the subsequent time window; S n (t0) represents the seismic signal acquired by the nth seismograph at time t0.

[0062] In this embodiment, the time-spectrum parameter S can be determined according to equation (4). STFT (t,f):

[0063]

[0064] Where t is the earthquake recording time, f is the seismic wave frequency, and S STFT (t,f) represents the time-frequency transformation of the earthquake record s(τ), where τ is the time label for the time window w(t-τ), x(τ) is a segment of seismic wave record that coincides with a long time segment of the time window of w(t-τ), w(t-τ) is the t-τ spatiotemporal amplitude value of the window function waveform, and i is the imaginary part sign.

[0065] In this embodiment, the power spectral density can be determined according to equation (5):

[0066]

[0067] Among them, f max For the maximum frequency, f min For minimum frequency, PSD fmin～fmax f max -f min The power spectral density function, S STFT (t,f) represents the time-frequency spectrum parameters.

[0068] S40: Based on the extracted early warning parameters, establish an earthquake prediction model for geological hazards at a single measuring point, expressed as:

[0069]

[0070] T represents the duration of the seismic wave triggered by the debris flow.

[0071] S50: Use a single-point geological hazard earthquake prediction model to determine whether an earthquake signal is triggered by a geological hazard.

[0072] In this embodiment, step S50 includes: if a single measuring point satisfies the earthquake prediction model for geological disasters at a single measuring point, it can be preliminarily determined that the earthquake signal may be triggered by flash floods, debris flows, etc., that is, the earthquake wave signal observed at measuring point n is considered to be triggered by flash floods, debris flows, etc.

[0073] The criteria to be met are: H AB(t0) exceeds the threshold value; the dominant frequency f0 of the seismic wave is within the dominant frequency range of seismic waves that may be excited by geological disaster flows; the maximum frequency f of the seismic wave. max and minimum frequency f min The frequency is also within the frequency range of seismic waves triggered by geological disasters; PSD fmin～fmax (t) exceeds the possible threshold value before the geological disaster occurs; the duration T of the earthquake waveform exceeds the possible duration of the geological disaster.

[0074] Exemplary Example 2

[0075] This exemplary embodiment provides a method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics. This method can identify geological hazards through multiple measuring points. The method includes:

[0076] S10: Conduct seismic signal acquisition in areas with potential geological hazards.

[0077] In this embodiment, step S10 may include: selecting a potential risk area; selecting a gully section in the potential risk area where a geological disaster has occurred; deploying multiple real-time transmission three-component seismometers in the gully section and acquiring seismic signals.

[0078] S20: Preprocess the acquired seismic signals.

[0079] S30: Extract early warning parameters from the preprocessed seismic signal.

[0080] S40: Establish an earthquake prediction model for geological disasters at a single measuring point based on the extracted early warning parameters.

[0081] And S50: an earthquake prediction model that integrates geological hazards from multiple measurement points and determines whether the earthquake signal is a geological hazard-triggered earthquake signal.

[0082] In this embodiment, steps S20 to S40 can be the same as S20 to S40 in Exemplary Embodiment 1.

[0083] In this embodiment, step S50 may include: combining the time difference dt between the seismic waves triggered by the geological disaster arriving at any two observation points. (r,nm)The conditions are set to identify seismic signals of geological hazards. At any two observation points, the seismic early warning model for a single-point geological hazard is met. The arrival time difference of seismic waves and the theoretically calculated time difference between the two observation points are calculated. If the difference between the arrival time difference and the theoretically calculated time difference is within a predetermined range, the seismic signal monitored by any two observation points is determined to be a possible seismic signal of a geological hazard. When the number of pairs of any two observation points meets a predetermined value, the seismic signal is determined to be a flash flood or debris flow triggered by a geological disaster. The predetermined number can be greater than 2, for example, 3, 5, or 7, and this value may be modified due to geological environment and conditions.

[0084] The standard for meeting the earthquake early warning model for single-point geological disasters is to meet at least three of the following conditions. Of course, the more conditions met, the higher the reliability; the fewer conditions met, the lower the reliability. In this case, it is necessary to combine other observation points, i.e., the combination of multiple observation points is the focus of this exemplary embodiment.

[0085] (1)H AB (t0) exceeds the threshold value;

[0086] (2) The dominant frequency f0 of the seismic wave is within the dominant frequency region of seismic waves that may be excited by geological disaster flows;

[0087] (3) The maximum frequency f of the seismic wave max and minimum frequency f min The frequency is also within the frequency range of seismic waves triggered by geological disasters;

[0088] (4) PSD fmin～fmax (t) exceeds the possible threshold value before a geological disaster occurs;

[0089] (5) The duration T of the earthquake waveform exceeds the possible duration of the geological disaster.

[0090] In this embodiment, the method further includes step S60: when it is determined that the earthquake signal is triggered by a geological disaster flow, real-time early warning information on geological disasters is released to downstream risk areas through networks or other means.

[0091] Exemplary Example 3

[0092] This exemplary embodiment provides a method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics.

[0093] Figure 1 A flowchart illustrating the geological hazard identification method based on seismic wave dynamics and kinematic characteristics of the present invention is shown.

[0094] like Figure 1As shown, the overall process flow of this invention includes: identifying high-risk areas such as flash floods and debris flows using meteorological data, topographical features, remote sensing imagery, and other data; selecting high-risk valleys for flash floods and debris flows in high-risk watersheds and deploying an appropriate number of seismographs (such as 4G seismographs) along the valleys; collecting seismic signals in real time through a remote server, removing noise attenuation such as instrument response and bandpass filtering; extracting early warning parameters from continuously observed seismic signals: long-short time window energy ratio, time-spectrum parameters, power spectral density, and seismic signal duration; establishing a single-point debris flow earthquake early warning model for the nth observation point; establishing a multi-point integrated debris flow earthquake prediction model; and determining the occurrence of geological disasters and issuing early warnings.

[0095] Specifically, the method of identification may include the following:

[0096] (1) Design of earthquake observation in high-risk areas such as flash floods and debris flows.

[0097] Based on historical climate information, combined with local topography and InSar data, potential risk areas such as landslides, debris flows, and flash floods are selected. Within the risk watershed, gully sections formed by flash floods and debris flows are prioritized, and 1-5 real-time transmission three-component seismographs are deployed in these gully sections.

[0098] (2) Acquisition of earthquake signals of flash floods and debris flows, and real-time automated preprocessing of the data.

[0099] The seismic signals collected by the seismographs are transmitted to the terminal server through 4G / 5G or other networks. The seismic signal collected by the nth seismograph is Sn(t). The seismic signal Sn(t) is preprocessed, mainly including removing instrument response and bandpass filtering.

[0100] (3) Extract early warning parameters from the continuously observed seismic signal Sn(t).

[0101] 3.1 Energy ratio of long and short time windows

[0102] By selecting a rolling time window, i.e., at a certain time t0, its S n Time windows of certain lengths t2-t0 and t0-t1 are selected before and after (t0). The average energy within each time window is calculated, and the energy ratio is calculated using this average energy. The energy ratio H of the time window before and after time t0 is... AB (t0) is shown in the following formula:

[0103] H AB (t0)=H A (t0) / H B (t0) (1)

[0104] Its preceding time window average energy is defined as:

[0105]

[0106] The average energy after the time window is defined as:

[0107]

[0108] t0 is a certain time, t2-t0 is the length of the previous time window, and t0-t1 is the length of the next time window.

[0109] 3.2 Spectral parameters

[0110] For S n (t) Perform time-frequency analysis to obtain the seismic signal S n The time-frequency parameters of (t).

[0111]

[0112] Where t is the earthquake recording time, f is the seismic wave frequency, and S STFT (t,f) is the expression for time-frequency transformation of seismic record s(τ), where τ is the time length for time windows w(τ) and s(t-τ), s(t-τ) represents the seismic wave record with time t and time window length τ for window function w(τ), w(τ) is the spatiotemporal amplitude value of the time window function waveform, i is the imaginary part symbol, and fτi is the expression for the product of f, τ and i.

[0113] Where w(t) is a window function used to limit the time range, ω is the angular frequency, representing the frequency component of the signal, and ω=2πf.

[0114] By applying a sliding window function w(t) to the signal s(t), the STFT performs a local Fourier transform on the signal at each time point t, obtaining the amplitude and phase information of the frequency component f. The window function plays a crucial role in the STFT, primarily used to limit the time range of the Fourier transform and ensure the locality of the transform. Common window functions include rectangular windows, Hamming windows, Hanning windows, and Blackman windows, which extract the dominant frequency f0 and effective bandwidth f of the seismic wave within the time window. min ~f max .

[0115] 3.3 Power Spectral Density (PSD)

[0116] Power spectral density is a measure of the mean square value of a random variable. It defines how the power of a signal or time series is distributed with frequency. It can determine the signal power distribution at each moment and deduce the characteristics and origin of each signal component. Using S... STFT (t,f) spectrum, f min ~f maxThe power integral is the cumulative power, i.e., the representative power P(t) of the debris flow. Numerical integration is performed using the trapezoidal rule, and the calculation formula is as follows:

[0117]

[0118] Among them, f max For the maximum frequency, f min For minimum frequency, PSD fmin～fmax f max -f min The power spectral density function.

[0119] To detect debris flows, it is required The level increases by an order of magnitude in a short period of time. Mathematically, an order of magnitude increase should be M times, for example, so we use 5 and 10 simultaneously for testing. Detecting mudslides arriving... The added criterion is:

[0120]

[0121] This represents the power spectral density of the relevant background signal.

[0122] 3.4 Duration T of earthquake signal

[0123] Based on the arrival time t0 of the seismic waves, combined with Calculate the duration T of the debris flow seismic signal.

[0124] (4) Based on the characteristics of earthquake signal parameters such as debris flow and flash flood, establish a single-point earthquake early warning model for debris flow and flash flood.

[0125] According to parameter H AB (t0),f0,f min ~f max , T establishes a single-channel early warning model for debris flow, flash flood, and earthquake. The early warning model is as follows:

[0126]

[0127] It should be noted that the seismic signal data on which the model of this invention is based is a wide range of seismic data received by field seismographs. It may include signals such as debris flow and flash flood, or it may not. Therefore, it is necessary to determine the seismic signals such as flash flood and debris flow through multiple parameters in step (4).

[0128] (5) Integrating multi-point DebrisModel n Earthquake early warning models for mudslides, flash floods, etc.

[0129] 5.1 Combining the kinematic characteristics of seismic waves such as flash floods and debris flows, that is, combining the time difference dt of the debris flow-induced seismic waves arriving at any two observation points. r,nm The conditions are established to clarify whether the seismic signal is a debris flow, flash flood, or other type of earthquake. Specifically, the conditions are: if the propagation velocity of the seismic signal triggered by a flash flood or debris flow in the strata is V, and the distance between the two measuring points is ΔS, then dt r,nm <ΔS / V.

[0130] 5.2 Based on the established earthquake early warning models for debris flows, flash floods, etc., when multiple measuring points meet the requirements of the debris flow earthquake early warning model... n Calculate the time difference of arrival of seismic waves between any two measuring points and the theoretically calculated time difference. For example, the arrival time of the debris flow received by the nth upstream observation point is t. n,0 The arrival time of debris flow, flash flood, etc., received by the m-th downstream observation point is t. m,0 The theoretically calculated arrival time difference dt between upstream and downstream earthquake signals such as debris flows and flash floods is then calculated. c,nm =ΔS / V, where ΔS is the distance between the nth and mth observation points, and V is the seismic wave propagation velocity. Therefore, it can be determined whether the seismic signal was caused by a flash flood or debris flow based on multiple measurement points.

[0131] All the multiple measuring points meet the requirements of the Debris Model for earthquake early warning of debris flows. n This means that for each measuring point, for a single measuring point model, if at least three conditions are met, then the seismic wave signal observed at measuring point n may be triggered by a flash flood or debris flow: (1) H AB (t0) Exceeds the threshold value; (2) The dominant frequency f0 of the seismic wave is within the dominant frequency range of seismic waves that may be excited by geological disaster flows; (3) The maximum frequency f of the seismic wave max and minimum frequency f min The frequency is also within the frequency range of seismic waves triggered by geological disasters; (4) PSD fmin～fmax (t) exceeds the possible threshold value before the geological disaster occurs; (5) the duration of the earthquake waveform T exceeds the possible duration of the geological disaster.

[0132] For multiple measuring points, the time difference of arrival of seismic waves between any two measuring points and the theoretically calculated time difference |dt c,nm -dt r,nm | < ΔS / V is within the approximate range. Due to the influence of the actual geological environment, this value can often be taken as [0.5ΔS / V, 1.5ΔS / V], where V is the seismic wave propagation velocity in the area.

[0133] It should be noted that: If there is only one seismograph on site, the single-point measurement model can be used to determine whether it is triggered by mountain torrents and debris flows. If there are multiple seismographs in this area, more than two single-point measurement models can be used to determine the seismic signals of mountain torrents and debris flows. Of course, according to the actual geological conditions, even if there are multiple measurement points observing mountain torrents and debris flows, the single-point measurement model can also be used to determine whether the seismic signal is triggered by mountain torrents and debris flows. In this case, the single-point measurement model needs to meet five conditions to ensure reliability.

[0134] 5.3 The time difference dt of the seismic signals received by any nth and mth observation points excited by actual mountain torrents and debris flows r,nm = t n,0 - t m,0 , when the calculated time difference dt of any two measurement points n and m c,nm and the actual observed time difference dt r,nm The difference satisfies a certain error range, |dt c,nm - dt r,nm | < dt, dt is the error range set according to the region (i.e., "[0.5ΔS / V, 1.5ΔS / V]"), which indicates that the seismic signals monitored by the two measurement points n and m may be seismic signals of mountain torrents and debris flows. This point is used to determine whether it is a seismic signal of mountain torrents and debris flows based on the arrival time of the suspicious mountain torrent and debris flow seismic signals in the multi-point measurement model.

[0135] 5.4 When any two measurement points n and m both meet the conditions of 5.2 and 5.3, and the number of pairs of any measurement points that meet the conditions is k, when k meets a certain value, such as greater than 2 or other values, this value range may be changed due to geological environment and conditions, then it can be determined that the seismic signal is a seismic signal triggered by mountain torrents and debris flows. Among them, n is the number of the nth measurement point, and m is the number of the mth measurement point.

[0136] (6) Early warning of mountain torrent and debris flow earthquakes.

[0137] When it is determined that the seismic signal is triggered by mountain torrents and debris flows, real-time warning information such as debris flows is released to the downstream risk areas through networks and other means.

[0138] It should be noted that the present invention can be judged through a single measurement point or through multiple measurement points. It's just that the reliability of the multi-point measurement is higher.

[0139] Although the present invention has been described above in conjunction with exemplary embodiments and the accompanying drawings, those of ordinary skill in the art should understand that various modifications can be made to the above embodiments without departing from the spirit and scope of the claims.

Claims

1. A method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics, characterized in that, The method includes: S10: Conduct seismic signal acquisition in areas at potential risk of geological disasters; S20: Preprocess the acquired seismic signals; S30: Extract early warning parameters from the preprocessed seismic signal. The early warning parameters include the energy ratio of long and short time windows, time-spectrum parameters, power spectral density, and seismic signal duration. S40: Establish an earthquake prediction model for geological hazards at a single measuring point based on the extracted early warning parameters; S50: Use a single-point geological hazard earthquake prediction model to determine whether an earthquake signal is triggered by a geological hazard.

2. A method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics, characterized in that, The method includes: S10: Conduct seismic signal acquisition in areas at potential risk of geological disasters; S20: Preprocess the acquired seismic signals; S30: Extract early warning parameters from the preprocessed seismic signal. The early warning parameters include the energy ratio of long and short time windows, time-spectrum parameters, power spectral density, and seismic signal duration. S40: Establish an earthquake prediction model for geological hazards at a single measuring point based on the extracted early warning parameters; S50: An earthquake prediction model that integrates geological hazards from multiple measurement points and is used to determine whether an earthquake signal is triggered by a geological hazard.

3. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 1 or 2, characterized in that, S10 includes: Select the potential risk area; Select the valley sections where geological disasters may occur within the potential risk area; Several real-time transmission three-component seismographs were deployed in the valley section to collect the seismic signals.

4. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 1 or 2, characterized in that, The preprocessing in S20 includes: removing instrument response and bandpass filtering.

5. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 1 or 2, characterized in that, The energy ratio of the long and short time windows is determined according to the following formulas (1)-(3): H AB (t0)=H A (t0) / H B (t0) (1) Among them, H AB (t0) represents the energy ratio before and after the time window, H A (t0) represents the average energy of the previous time window, H B (t0) represents the average energy after the time window; t0 is a certain time, t2-t0 is the length of the previous time window, and t0-t1 is the length of the next time window; S n (t0) represents the seismic signal acquired by the nth seismograph at time t0.

6. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 1 or 2, characterized in that, The steps for obtaining the time-spectrum parameters include: Time-frequency analysis is performed on the seismic signal to obtain the time-spectrum parameters.

7. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 1 or 2, characterized in that, The time-frequency parameters are determined according to equation (4): Where t is the earthquake recording time, f is the seismic wave frequency, and S STFT (t,f) is the expression for the time-frequency transformation of the seismic record s(τ), where τ is the time length for the time window w(τ) and s(t-τ), s(t-τ) is the seismic wave record with time t and time window length τ for the window function w(τ), and i is the imaginary part symbol.

8. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 1 or 2, characterized in that, The power spectral density is determined according to equation (5): Among them, f max For the maximum frequency, f min For minimum frequency, PSD fmin～fmax f max -f min The power spectral density function, S STFT (t,f) represents the time-frequency spectrum parameters.

9. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 1, characterized in that, The earthquake prediction model for geological hazards at a single measurement point is as follows: Among them, H AB (t0) represents the energy ratio of the long and short time windows, f0 represents the dominant frequency of the seismic wave, and PSD represents the voltage level. fmin～fmax Where is the power spectral density, and T is the duration of the seismic signal; If the following five conditions of the earthquake prediction model for geological hazards at a single measuring point are met, then the seismic wave signal observed at measuring point n may be triggered by flash floods and debris flows: (1)H AB (t0) exceeds the threshold value; (2) The dominant frequency f0 of the seismic wave is within the dominant frequency region of seismic waves that may be excited by geological disaster flows; (3) The maximum frequency f of the seismic wave max and minimum frequency f min The frequency is also within the frequency range of seismic waves triggered by geological disasters; (4) PSD fmin～fmax (t) exceeds the possible threshold value before a geological disaster occurs; (5) The duration T of the earthquake waveform exceeds the possible duration of the geological disaster.

10. The method for identifying geological hazards based on seismic wave dynamics and kinematic characteristics according to claim 2, characterized in that, S50 includes: when any two measuring points meet the earthquake early warning model for a single-measuring-point geological disaster, calculating the time difference of arrival of seismic waves and the theoretically calculated time difference between any two measuring points; if the difference between the time difference of arrival of seismic waves and the theoretically calculated time difference is within a predetermined range, then determining that the seismic signal monitored by any two observation points is a possible seismic signal for a geological disaster; when the number of pairs of any two measuring points meets a predetermined value, then determining that the seismic signal is a seismic signal triggered by flash floods or debris flows. The earthquake prediction model for single-point geological hazards is as follows: H AB (t0) represents the energy ratio of the long and short time windows, f0 represents the dominant frequency of the seismic wave, and PSD represents the voltage level. fmin～fmax Where is the power spectral density, and T is the duration of the seismic signal; The standard for achieving the earthquake early warning model for geological disasters at a single measuring point is to meet at least three of the following conditions: (1)H AB (t0) exceeds the threshold value; (2) The dominant frequency f0 of the seismic wave is within the dominant frequency region of seismic waves that may be excited by geological disaster flows; (3) The maximum frequency f of the seismic wave max and minimum frequency f min The frequency is also within the frequency range of seismic waves triggered by geological disasters; (4) PSD fmin～fmax (t) exceeds the possible threshold value before a geological disaster occurs; (5) The duration T of the earthquake waveform exceeds the possible duration of the geological disaster.

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