CN115236741A - High-speed remote ice rock collapse disaster chain early warning method based on seismic oscillation signals - Google Patents
High-speed remote ice rock collapse disaster chain early warning method based on seismic oscillation signals Download PDFInfo
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Abstract
The invention discloses a high-speed remote ice rock collapse disaster chain early warning method based on seismic oscillation signals, which comprises the steps of collecting seismic signals generated in a mountain ice rock collapse stage; judging whether the type of the acquired seismic signal is a collapse signal or not; when the avalanche sliding signal is judged, processing the avalanche sliding signal by adopting a time domain analysis method based on a short-time ratio, a frequency spectrum analysis method based on empirical mode decomposition and an energy analysis method based on a time domain power spectral density function; interpreting the processing result of the collapse signal, identifying dynamic characteristic points, and judging the dynamic stage of the disaster body by combining a regional satellite map; and constructing an ice rock collapse disaster chain early warning grade division standard based on seismic signals, and early warning according to the dynamic stage of the disaster body and the divided early warning grade. The invention solves the key problems of high signal-to-noise ratio of seismic signals, lack of control standards for interpretation and early warning, difficulty in correspondence in time and space and the like for a long time, and effectively inhibits the influence of environmental noise on the definition of the signals.
Description
Technical Field
The invention relates to the technical field of landslide seismic signal processing, in particular to a high-speed remote ice rock collapse disaster chain early warning method based on seismic signals.
Background
In recent years, with global climate change becoming more severe, iceberg collapse disasters caused by melting of ice and snow frequently occur, and originally complex geological environments in himalaya alpine mountainous areas become more fragile. Disasters such as large landslides, avalanches and debris flows are often accompanied by huge destructive power, and serious threats are caused to the life and property safety of residents in villages and towns along the way. In addition, due to the extremely high concealment and difficult predictability of geological disasters, and the lack of large-scale monitoring equipment in most mountain areas, the formation of a high-speed and long-distance release disaster chain is difficult to be effectively warned. The small earthquake generated after the landslide body is contacted with the earth surface can be collected through the earthquake table network, the earthquake table network has the characteristics of wide monitoring range, high sensitivity, easy data acquisition and the like, at present, the application of earthquake signals to natural disaster interpretation and prediction is a large research hotspot abroad, but the problems of excessive environmental noise, lack of early warning standards and the like still advance in the field of interference resistance, if the related problems can be overcome, the earthquake signals can provide great contribution to the research in the directions of landslide motion process reconstruction, early warning, landslide earth parameter inversion and the like, and meanwhile, the digital sequence of the signals enables the signals to have a considerable application prospect in the large data fields of artificial intelligence and the like.
At present, many scholars try to apply a seismic source mechanical mechanism inversion method in seismology to the landslide earthquake field, and the method has the advantages that the accuracy is high, but a huge number of earthquake stations are needed; there is also debate on the conclusion that learners have worked on landslide parameter fitting, trying to back-calculate from the signals the kinetic parameters of sliding distance, height difference, volume, etc. of landslide, but again limited by the amount of data.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a high-speed remote icerock collapse disaster chain early warning method based on seismic signals, which utilizes time difference to realize high-speed remote icerock collapse disaster chain early warning.
In order to achieve the purpose of the invention, the invention adopts the technical scheme that:
a high-speed remote ice rock collapse disaster chain early warning method based on seismic signals comprises the following steps:
s1, collecting seismic signals generated in a mountain body ice rock collapse stage;
s2, judging whether the type of the acquired seismic signal is a collapse and slide signal; if yes, carrying out the next step; otherwise, returning to the step S1;
s3, processing the avalanche and slide signal by adopting a time domain analysis method based on a short-time ratio, a frequency spectrum analysis method based on empirical mode decomposition and an energy analysis method based on a time domain power spectral density function;
s4, interpreting the processing result of the collapse and slide signal, identifying dynamic characteristic points, and judging the dynamic stage of the disaster body by combining a regional satellite map;
and S5, constructing an icerock collapse disaster chain early warning grade division standard based on the seismic signals, and early warning according to the dynamic stage of the disaster body and the divided early warning grade.
Optionally, in step S2, it is determined whether the type of the acquired seismic signal is a avalanche slip signal according to the depth of the seismic source, the magnitude of the seismic source, and the ratio of the rise time to the fall time of the signal.
Optionally, in step S3, the avalanche and slide signal is processed by using a time domain analysis method based on a short-time ratio, specifically:
constructing a short-time ratio of the short-time energy to the short-time zero-crossing rate to characterize the variation intensity of the seismic signal, and analyzing the effective signal by setting the length of a short-time window, expressed as
Wherein the content of the first and second substances,
the short-time ratio of the short-time energy to the short-time zero-crossing rate;Nis the length of the short time window;x(m) Is an original signal; sgn is a sign function.
Optionally, in step S3, the frequency spectrum analysis method based on empirical mode decomposition is used to process the avalanche and slide signal, which specifically includes:
constructing a frequency spectrum of a short-time window superposition method calculation signal based on empirical mode decomposition, and expressing the frequency spectrum as
Wherein, the first and the second end of the pipe are connected with each other,
is the frequency spectrum of the signal;imf(τ) For each eigenmode function;r(τ) Is the EMD residual value;Nis the length of the short time window;fis the signal frequency.
Optionally, in step S3, the avalanche and slide signal is processed by using an energy analysis method based on a time domain power spectral density function, specifically:
constructing an improved time domain power spectral density function, representing the energy of each particle in the disaster body at each frequency in the frequency band range, and representing the energy
Wherein the content of the first and second substances,ξthe Rayleigh wave vertical attenuation coefficient is under a power function velocity model of the seismic signal;v c rayleigh phase velocity at 1 Hz;fis the signal frequency;r 0 the average distance of the seismic station from the event area;f p is the peak frequency;Qis a Rayleigh waveThe quality factor of (2);uaverage flow velocity for the disaster body;Dis the crumb particle diameter;LandWrespectively the length and the width of the disaster body;H(t, f) As a function of time for the frequency of the signal obtained by the Hilbert-Huang transform.
Optionally, step S4 specifically includes:
identifying each impact event in a time domain according to a short-time ratio of short-time energy to short-time zero-crossing rate and a time domain power spectral density result, and extracting each amplitude value as an impact point;
identifying a turning event in a frequency domain according to a signal frequency spectrum, and taking an energy change point of a frequency band as a turning point;
and acquiring a satellite image of an earthquake occurrence area, and judging the dynamic stage of the disaster body by combining the impact point and the turning point.
The invention has the following beneficial effects:
the invention adopts a time domain analysis method based on a short-time ratio, a frequency spectrum analysis method based on empirical mode decomposition and an energy analysis method based on a time domain power spectral density function to correspond time domain parameters, frequency spectrums and energy to a time sequence, solves the key problems that the signal-to-noise ratio of seismic signals is high for a long time, interpretation and early warning lack control standards, and the seismic signals are difficult to correspond in time and space, effectively inhibits the influence of environmental noise on the definition of the signals, and further provides a method for judging the stage of a disaster chain by identifying characteristic points and combining regional satellite images and early warning by using the time difference. The invention can greatly save cost because of no investment of additional equipment, can realize early warning and prediction of the high-speed remote collapse disaster chain by using the advantages of the earthquake platform net and adopting the existing conditions, and has great significance undoubtedly for the research of complex geological activities in alpine and high-altitude mountain areas.
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Fig. 1 is a schematic flow chart of a high-speed remote ice rock collapse disaster chain early warning method based on seismic signals in an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
As shown in fig. 1, an embodiment of the present invention provides a high-speed remote ice rock collapse disaster chain early warning method based on seismic signals, including the following steps S1 to S5:
s1, collecting seismic signals generated in a mountain body ice rock collapse stage;
in an optional embodiment of the invention, the invention monitors the region frequently suffering from the himalayan icy collapse disaster or the upstream of the key construction project through the earthquake table net, and collects the earthquake signals generated by the region in real time without difference through Short-Term Analysis/Long-Term Analysis (STA/LTA).
S2, judging whether the type of the acquired seismic signal is a collapse and slide signal; if yes, the next step is carried out; otherwise, returning to the step S1;
in an alternative embodiment of the invention, the invention requires that the seismic signals be distinguished after they are acquired.
Through the research on unconventional seismic events in recent years, it is found that there are several general laws in mountain landslide seismic signals (the landslide signal mentioned in the present invention refers to the seismic signal generated during the ice rock landslide stage of a mountain, not to the whole disaster chain): (1) the depth of the inversion seismic source is 0 or negative; (2) the earthquake magnitude is often less than 3 (except for part of ultra-large landslides, such as Yigong landslides in Tibet in 2000, the generated 4.2-level earthquake enables the global earthquake table network far in the United states to clearly receive related signals); (3) the avalanche signal has a significant rising timeT R And fall timeT D (while the disaster chain continues to evolve and generate subsequent signals), dammeier et al refer to it as a fusiform distribution, as occurs with conventional earthquakes, volcanic eruptions, and nuclear testsGeneral absence of signalT R OrT R Is extremely small. Through the three-point law and the combination of seismic source positioning, the type of the seismic signals can be preliminarily determined, and the probability grade determination standard of the avalanche and slip signals is shown in table 1.
TABLE 1 probability level determination criteria for avalanche signals
S3, processing the avalanche and slide signal by adopting a time domain analysis method based on a short-time ratio, a frequency spectrum analysis method based on empirical mode decomposition and an energy analysis method based on a time domain power spectral density function;
in an optional embodiment of the invention, the invention processes the avalanche slip signal from three aspects of time domain analysis, frequency domain analysis and energy analysis based on a time domain power spectral density function.
For time domain analysis, the invention provides a short-time ratio lambda S considering the change condition of signal time domain parameters based on short-time energy and short-time zero crossing rate analysis, and seismic signals are identified and extracted by setting the length of a window function.
In particular, the short-term energy and the short-term zero-crossing rate may reflect the time-domain energy of the seismic arrival signal (envelope curve andXarea of the shaftE A ) And number of zero crossingsn(the curve passes throughXNumber of axes) of the display. Construction of a short time ratio based on the twoλ S To characterize the varying strength of the signal and to analyze the effective signal by setting the length of a short time window, denoted as
Wherein, the first and the second end of the pipe are connected with each other,
the short-time ratio of the short-time energy to the short-time zero-crossing rate;Nis the length of the short time window;x(m) Is an original signal; sgn is a sign function whenx(n) When the value is not less than 0, sgnx(m)]=1, whenx(n)<When 0, sgn [, ]x(m)]=−1。
For frequency domain analysis, the invention decomposes the signal into a form composed of a plurality of Intrinsic Mode Functions (IMFs) (the specific number is determined according to the correlation coefficient) by an Empirical Mode Decomposition (EMD) method, and calculates the frequency spectrum of the signal by a short time window superposition (FA) method constructed by the invention
Specifically, the EMD decomposes the signal into a sum of several IMFs based on local features on the time scale of the signal, and the decomposed IMFs can effectively extract feature information of the original signal. In order to ensure that the original signal is not decomposed excessively, the correlation between the decomposed signal and the original signal should be considered, and the decomposition is terminated when the correlation approaches 0. Calculating the frequency spectrum of each IMF obtained by decomposition in a Hanning window, integrating the calculation results in all the windows to finally obtain the frequency spectrum of the whole signal, which is expressed as
Wherein, the first and the second end of the pipe are connected with each other,
is the frequency spectrum of the signal;imf(τ) For each eigenmode function;r(τ) Is the EMD residual value;Nis the length of the short time window;fis the signal frequency.
For energy analysis based on a Time domain Power spectral Density function, the method considers the Power Spectral Density (PSD) under various frequencies in a frequency band range on the basis of the currently established debris particle elastic vibration physical model, adopts Hilbert-Hunag transformation for further improvement, constructs a Time domain Power spectral Density (TPSD) function, and accurately analyzes the impact energy of a disaster body
Specifically, on the basis of the existing earthquake dynamic physical mechanical model of debris flow particle contact with the ground, the invention considers that a single signal is actually the result of the common combination of various frequencies in a frequency band range, calculates a signal frequency-time function through Hilbert-Huang transformation, and integrates the mechanical model along the function to obtain an improved time domain power spectral density function which represents the energy of each particle in a disaster body at each frequency in the frequency band range and is expressed as
Wherein, the first and the second end of the pipe are connected with each other,ξ≈0.25-0.5 is the Rayleigh wave vertical attenuation coefficient under the power function velocity model of the seismic signal;v c rayleigh phase velocity at 1 Hz;fis the signal frequency;r 0 the average distance of the seismic station from the event area;f p is the peak frequency;Qquality factors of Rayleigh waves;uaverage flow velocity of the disaster body;Dis the crumb particle diameter;LandWrespectively the length and the width of the disaster body;H(t, f) As a function of time for the frequency of the signal obtained by the Hilbert-Huang transform.
S4, interpreting the processing result of the collapse and slide signal, identifying dynamic characteristic points, and judging the dynamic stage of the disaster body by combining a regional satellite map;
in an optional embodiment of the present invention, step S4 specifically is:
identifying each impact event in a time domain according to a short-time ratio of short-time energy to a short-time zero-crossing rate and a time domain power spectral density result, and extracting each amplitude value as an impact point;
identifying a turning event in a frequency domain according to a signal frequency spectrum, and taking an energy change point of a frequency band as a turning point;
and acquiring a satellite image of an earthquake occurrence area, and judging the dynamic stage of the disaster body by combining the impact point and the turning point.
Specifically, the invention relates to an impact point in the evolution process of a disaster chainP I And turning pointP T Collectively called as feature points, in the process of identifying the dynamic feature points, firstly, according to the short-time ratio of short-time energy to short-time zero crossing rateλ S And time domain power spectral density (TPSD) results identifying individual crash events in the time domain, the crash effects causing signalsnReduceE A The temperature of the molten steel rises and rises,λ S will present an increasing trend, and the TPSD energy will also rise, so the amplitudes will be taken as the impact points; then, a turning event is identified in a frequency domain according to a signal frequency spectrum, because signal power generated in an ice rock caving stage is mainly distributed in three frequency bands (high-medium-low), two frequency band distributions (medium-low) exist in a debris flow stage, only one frequency band distribution (medium) exists in a flood stage, the energy change condition of the frequency bands usually indicates the change of the motion state of a disaster body, and the change is taken as a turning point; and finally, counting the processing result, further quickly positioning the incident area by means of a seismic source positioning system of the seismic platform net, acquiring the latest satellite image of the area, and judging the dynamic stage of the disaster body by combining the regional satellite image with the characteristic points. The criteria for determining the dynamic stage of the disaster body are shown in table 2.
TABLE 2 determination criteria for dynamic stages of a disaster body
And S5, constructing an icerock collapse disaster chain early warning grade division standard based on the seismic signals, and early warning according to the dynamic stage of the disaster body and the divided early warning grade.
In an optional embodiment of the invention, the formation of the disaster chain requires certain events, the ice rock collapse disaster chain in himalayas alpine region is generally composed of ice rock collapse-debris flow-damming dam-collapse flood, the damage path in the flood stage is the longest, the loss is usually the largest, but the damage path is in the last ring of the ice rock collapse chain disaster, and the damage path actually has enough time to carry out early warning, the invention utilizes the larger time difference to carry out warning on downstream villages and towns while judging the formation state of the disaster chain, and the early warning grades are divided into the following table 3.
TABLE 3 disaster chain early warning grading
In the following, the chain of iceberg collapse disasters that occurred in charoli areas, india, 2, 7/2021, will be exemplified. Since the disaster has occurred, only the feasibility of the invention is verified here.
The first step is to intercept seismic signal waveform data generated by ice rock collapse through the regional seismic table net. GHAN and BAYN stations of a seismic network in a Nepal country are selected, the GHAN and the BAYN stations are respectively 160 km and 171km away from a disaster site, the sampling rate of signals is 50Hz, and signals are extracted for 94s (the threshold value is 0.5) by adopting STA/LTA.
The second step is the possibility judgment of the avalanche signal. Since 0 < thereofS t < 1, seismic source depthH=0 (the partial table net returns the values above the negative number to 0), and the magnitude of 0 < (R) >MIf the probability is less than 3, judging the probability grade as I grade.
The third step is to get the slaveT S The starting waveform signal is input into a constructed signal processing system for analysis:
firstly, the short time ratio is adoptedλ S The signal is subjected to time domain analysis.
In the formula (I), the compound is shown in the specification,Nis the length of the short time window;x(m) Is an original signal; sgn is a sign function whenx(n) When the value is not less than 0, sgnx(m)]=1, whenx(n)<When 0, sgn [, ]x(m)]=−1。
The extracted signal was then subjected to EMD and the correlation coefficient abruptly dropped to 0.0001 when decomposed to the 5 th IMF. Therefore, 5 IMFs and 1 residual function obtained by decompositionr(x) Built-in spectral analysis modelThe calculation is performed in the model.
In the formula (I), the compound is shown in the specification,imf(τ) For each intrinsic mode function;r(τ) Is the EMD residual value;Nfor the length of the short time window function, here 512 data points are selected for the length;fis the signal frequency. The processing result shows that the avalanche and slide signal can generate at most three frequency band energy distributions, and when the motion state of the disaster body is changed (acceleration, deceleration or direction change), the distribution state can also generate abrupt change.
Finally, energy analysis based on a time domain power spectral density function is carried out, mainly for researching the change of the ground surface impact energy of the disaster body, and the mechanical model is as follows:
wherein the content of the first and second substances,ξ≈0.25-0.5 is the Rayleigh wave vertical attenuation coefficient under the power function velocity model of the seismic signal;v c is the Rayleigh phase velocity at 1 Hz;fis the frequency;r 0 is the average distance of the seismic station from the event zone;f p is the peak frequency, can be setdP/df=0 to solvef；QIs the quality factor of the Rayleigh wave;uis the average flow velocity of the disaster;Dis the crumb particle diameter;LandWrespectively the length and the length of the disaster body;H(t, f) Is a function of the frequency of the signal obtained by the Hilbert-Huang transform with respect to time.
The fourth step is to interpret the results obtained by the 3 methods in the third step to obtain 8P I 8, 8P H And 4 spectral distribution forms. And simultaneously, a satellite image of the area is called, the impact point of the ice rock collapse is defined through a positioning system of the seismic platform net, the downstream terrain condition is analyzed, and the disaster chain evolution stage is judged. By passingAnalyzing the disaster chain is divided into three movement stages: an ice rock collapse stage, a valley accelerated movement stage, a dam blocking stage caused by abrupt change of terrain, and a dam breaking and flooding stage.
The final processing results of this example show that the time from the initial ice rock collapse phase to the final flood collapse phase is as long as 15 minutes, while the entire flood phase appears to last 1 hour and 4 minutes on the seismic signal. The early warning grade is divided by considering the priority of the first grade, the probability of the collapse slip signal is I grade in the example, even if the dynamic stage is still in the initial collapse slip stage of the ice rock, the distance is calculatedS=The villages and towns of 8.5km still need to be subjected to primary early warning (and so on), and the actual results also show that facilities such as hydropower stations and the like in the villages and towns are seriously destroyed under the impact action of debris flow, so that huge loss and casualties are caused. Therefore, if the evolution stage of the disaster chain can be predicted, the downstream effective early warning can be completely realized by enough time difference.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.
Claims (6)
1. A high-speed remote ice rock collapse disaster chain early warning method based on seismic signals is characterized by comprising the following steps:
s1, collecting seismic signals generated in a mountain ice rock collapse stage;
s2, judging whether the type of the acquired seismic signal is a collapse and slide signal; if yes, carrying out the next step; otherwise, returning to the step S1;
s3, processing the avalanche and slide signal by adopting a time domain analysis method based on a short-time ratio, a frequency spectrum analysis method based on empirical mode decomposition and an energy analysis method based on a time domain power spectral density function;
s4, interpreting the processing result of the collapse and slide signal, identifying dynamic characteristic points, and judging the dynamic stage of a disaster body by combining a regional satellite map;
and S5, constructing an ice rock collapse disaster chain early warning grade division standard based on the seismic signals, and early warning according to the dynamic stage of the disaster body and the divided early warning grade.
2. The high-speed remote iceberg collapse disaster chain early warning method based on seismic signals according to claim 1, wherein in step S2, whether the type of the acquired seismic signals is a collapse signal or not is judged according to the seismic source depth and the seismic magnitude of the seismic signals and the ratio of the rise time to the fall time of the signals.
3. The high-speed remote ice rock collapse disaster chain early warning method based on the seismic signal according to claim 1, wherein the step S3 is to process the collapse signal by using a time domain analysis method based on a short time ratio, specifically:
constructing a short-time ratio of short-time energy to short-time zero crossing rate to characterize the variation intensity of the seismic signal, and analyzing the effective signal by setting the length of a short-time window, expressed as
Wherein the content of the first and second substances,
the short-time ratio of the short-time energy to the short-time zero-crossing rate;Nis the length of the short time window;x(m) Is an original signal; sgn is a sign function.
4. The seismic signal-based high-speed remote ice and rock collapse disaster chain early warning method according to claim 1, characterized in that in step S3, a frequency spectrum analysis method based on empirical mode decomposition is adopted to process collapse signals, specifically:
constructing a frequency spectrum of a short-time window superposition method calculation signal based on empirical mode decomposition, and expressing the frequency spectrum as
Wherein the content of the first and second substances,
is the frequency spectrum of the signal;imf(τ) For each intrinsic mode function;r(τ) Is the EMD residual value;Nis the length of the short time window;fis the signal frequency.
5. The seismic signal-based high-speed remote ice and rock collapse disaster chain early warning method according to claim 1, characterized in that in step S3, an energy analysis method based on a time domain power spectral density function is adopted to process collapse signals, specifically:
constructing an improved time domain power spectral density function, representing the energy of each particle in the disaster body at each frequency in the frequency band range, and representing the energy
Wherein, the first and the second end of the pipe are connected with each other,ξthe Rayleigh wave vertical attenuation coefficient is under a power function velocity model of the seismic signal;v c rayleigh phase velocity at 1 Hz;fis the signal frequency;r 0 the average distance of the seismic station from the event area;f p is the peak frequency;Qquality factors of Rayleigh waves;uaverage flow velocity of the disaster body;Dis the crumb particle diameter;LandWrespectively the length and the width of the disaster body;H(t, f) As a function of time for the frequency of the signal obtained by the Hilbert-Huang transform.
6. The seismic signal-based high-speed remote ice-rock collapse disaster chain early warning method according to claim 1, wherein the step S4 specifically comprises:
identifying each impact event in a time domain according to a short-time ratio of short-time energy to short-time zero-crossing rate and a time domain power spectral density result, and extracting each amplitude value as an impact point;
identifying a turning event in a frequency domain according to a signal frequency spectrum, and taking an energy change point of a frequency band as a turning point;
and acquiring a satellite image of the earthquake occurrence area, and judging the dynamic stage of the disaster body by combining the impact point and the turning point.
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