Earthquake intensity intelligent analysis system based on bidirectional dynamic visual identification

Abstract

The invention discloses an intelligent seismic intensity analysis system based on bidirectional dynamic visual identification, and relates to the field of intelligent seismic intensity analysis, and the system comprises an intelligent analysis center which is in communication connection with a data collection module, a data processing module, a data analysis module and a seismic intensity evaluation module. The method comprises the following steps: collecting video recording data of a building when an earthquake occurs, processing the collected video recording data of the building to obtain a building height change curve graph and a building height change broken line graph, and analyzing the obtained building height change curve graph and the building height change broken line graph to obtain a building height change curve graph and a building height change broken line graph; according to the method, the seismic intensity evaluation coefficient is obtained, and the seismic intensity is evaluated according to the obtained seismic intensity evaluation coefficient, so that the accuracy of seismic intensity evaluation is further improved, and the damage degree of the earthquake to the building is accurately explained.

Description

Technical Field

[0001] The invention relates to the field of intelligent analysis of earthquake intensity, and in particular to an intelligent analysis system of earthquake intensity based on bidirectional dynamic visual recognition. Background Art

[0002] With the frequent occurrence of earthquakes and the acceleration of urbanization around the world, earthquake disasters are posing an increasing threat to human society. Traditional earthquake intensity assessment methods often rely on on-site inspections and manual assessments by experts. Although this method is highly accurate, it has problems such as slow response, limited coverage, and the need for a large number of human resources. Especially after a large-scale earthquake, quickly and accurately assessing the intensity of the disaster area is crucial for rescue decision-making and resource allocation.

[0003] How to process and analyze the video recording data of the building to obtain the earthquake intensity assessment coefficient, evaluate the earthquake intensity according to the obtained earthquake intensity assessment coefficient, and further improve the accuracy of earthquake intensity assessment is a problem we need to solve. To this end, an earthquake intensity intelligent analysis system based on two-way dynamic visual recognition is provided. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide an intelligent analysis system of earthquake intensity based on bidirectional dynamic visual recognition.

[0005] The purpose of the present invention can be achieved by the following technical solutions: an intelligent analysis system for earthquake intensity based on two-way dynamic visual recognition, comprising an intelligent analysis center, wherein the intelligent analysis center is communicatively connected with a data acquisition module, a data processing module, a data analysis module, a data fusion and machine learning module, and an earthquake intensity assessment module;

[0006] The data acquisition module is used to collect video recording data of buildings when an earthquake occurs, and is connected to an earthquake monitoring network or related equipment to collect earthquake peak acceleration, earthquake peak velocity and earthquake effective duration data;

[0007] The data processing module is used to process the collected video recording data of the building to obtain a building height change curve graph and a building height change line graph;

[0008] The data analysis module is used to analyze the obtained building height change curve graph and building height change line graph to obtain a preliminary earthquake intensity assessment coefficient characteristic value;

[0009] The data fusion and machine learning module is used to receive the earthquake dynamic parameter (earthquake peak acceleration, earthquake peak velocity, earthquake effective duration) data from the data acquisition module and the preliminary earthquake intensity assessment coefficient characteristic value from the data analysis module, build a machine learning model (such as support vector machine, neural network, etc.) with a large amount of historical earthquake data as a training set, input the real-time collected data into the model for data fusion and training, and obtain the final earthquake intensity assessment coefficient;

[0010] The earthquake intensity assessment module is used to assess the earthquake intensity based on the earthquake intensity assessment coefficient obtained by the data fusion and machine learning module.

[0011] Furthermore, the process of the data acquisition module acquiring the video recording data of the building when the earthquake occurs includes:

[0012] The data acquisition module is composed of several data acquisition terminals;

[0013] The data acquisition terminal is configured to generate a corresponding configuration channel. The data acquisition terminal is connected to the city's server through the generated corresponding configuration channel. The data acquisition terminal obtains the video recording of the building when the earthquake occurs in the city's server through the corresponding configuration channel, and sends the obtained video recording of the building when the earthquake occurs to the data processing module. At the same time, the collected earthquake peak acceleration, earthquake peak velocity and earthquake effective duration data are transmitted to the data fusion and machine learning module.

[0014] Furthermore, the process of the data processing module processing the collected video recording data of the building includes:

[0015] Performing frame processing on the acquired video recording of the building to obtain a plurality of frames of video recording images of the building;

[0016] Perform bidirectional dynamic visual recognition on each frame of video recording to obtain the height of the building in each frame of video recording;

[0017] A building height variation curve graph and a building height variation line graph are obtained according to the height of the building in each frame of video recording image obtained.

[0018] Furthermore, the process of obtaining a building height change curve graph and a building height change line graph according to the height of the building in each frame of the video recording picture obtained includes:

[0019] Constructing a first two-dimensional rectangular coordinate system, wherein the abscissa of the first two-dimensional rectangular coordinate system is the number of the video recording picture, and the ordinate of the first two-dimensional rectangular coordinate system is the height of the building in the corresponding video recording picture;

[0020] Mapping the height of the building in each frame of the video recording image obtained into the constructed first two-dimensional rectangular coordinate system, generating corresponding first building height sample points, and connecting each first building height sample point in sequence through a curve in the order of the labels to obtain a building height change curve graph;

[0021] Constructing a third two-dimensional rectangular coordinate system, wherein the abscissa of the constructed third two-dimensional rectangular coordinate system is the number of the video recording picture, and the ordinate of the constructed third two-dimensional rectangular coordinate system is the height of the building in the corresponding video recording picture;

[0022] The height of the building in each frame of the video recording image is mapped to the constructed third two-dimensional rectangular coordinate system to generate corresponding second building height sample points, and each second building height sample point is connected in sequence by a straight line in the order of the labels to obtain a line graph of the building height changes.

[0023] Furthermore, the process of the data analysis module analyzing the obtained building height change curve graph and building height change line graph includes:

[0024] According to the obtained building height change line graph, a first earthquake intensity assessment coefficient characteristic value is obtained, and according to the obtained building height change curve graph, a second earthquake intensity assessment coefficient characteristic value is obtained;

[0025] According to the obtained first earthquake intensity assessment coefficient characteristic value and the second earthquake intensity assessment coefficient characteristic value, a preliminary earthquake intensity assessment coefficient characteristic value set is obtained and transmitted to the data fusion and machine learning module.

[0026] Furthermore, according to the obtained building height change line graph, the process of obtaining the characteristic value of the first earthquake intensity assessment coefficient includes:

[0027] Obtain the height of the building corresponding to the next second building height sample point of each second building height sample point. If the height of the building corresponding to the second building height sample point is the same as the height of the building corresponding to the next second building height sample point of the second building height sample point, record the second building height sample point as the ending second building height sample point, obtain the first ending second building height sample point, remove the second building height sample point and the ending second building height sample point behind the first ending second building height sample point, and obtain a standard building height change line graph;

[0028] Obtain the slope of the straight line between the second building height sample point and the next second building height sample point in the standard building height change line graph;

[0029] Draw a straight line parallel to the longitudinal axis through the second building height sample point, draw a straight line parallel to the horizontal axis through the next second building height sample point, obtain the intersection of the two straight lines, and obtain the area of ​​the right triangle formed by the second building height sample point, the next second building height sample point, and the intersection of the two straight lines;

[0030] Obtain the height of the building corresponding to the terminating second building height sample point in the standard building height change line graph, and obtain the first earthquake intensity assessment coefficient characteristic value according to the height of the building corresponding to the terminating second building height sample point, the slope of the straight line between the second building height sample point and the next second building height sample point, and the area of ​​the right triangle formed by the second building height sample point, the next second building height sample point, and the intersection of the two straight lines.

[0031] Furthermore, according to the obtained building height change curve diagram, the process of obtaining the characteristic value of the second earthquake intensity assessment coefficient includes:

[0032] Obtain a standard building height variation curve graph, draw a straight line through a first building height sample point parallel to the vertical axis, draw a straight line through a next first building height sample point parallel to the horizontal axis, obtain the intersection of the two straight lines, integrate the area of ​​a closed curve figure composed of the first building height sample point, the next first building height sample point, and the intersection of the two straight lines, and obtain an integral result;

[0033] The second earthquake intensity assessment coefficient characteristic value is obtained according to the height of the building corresponding to the acquired second building height termination sample point and the obtained integration result.

[0034] Furthermore, the process of the earthquake intensity assessment module assessing the earthquake intensity according to the obtained earthquake intensity assessment coefficient includes:

[0035] The earthquake intensity assessment coefficient threshold range is set according to the actual situation, and the earthquake intensity level is obtained according to the comparison result between the obtained earthquake intensity assessment coefficient and the set earthquake intensity assessment coefficient threshold range;

[0036] The earthquake intensity levels include level one earthquake intensity, level two earthquake intensity and level three earthquake intensity.

[0037] Compared with the prior art, the beneficial effects of the present invention are: collecting video recording data of buildings when an earthquake occurs, processing the collected video recording data of buildings, obtaining a building height change curve graph and a building height change line graph, analyzing the obtained building height change curve graph and building height change line graph, obtaining an earthquake intensity assessment coefficient, and assessing the earthquake intensity based on the obtained earthquake intensity assessment coefficient, thereby further improving the accuracy of the earthquake intensity assessment, thereby accurately illustrating the degree of damage to the building caused by the earthquake. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0039] like Figure 1 As shown, an intelligent analysis system for earthquake intensity based on bidirectional dynamic visual recognition includes an intelligent analysis center, wherein the intelligent analysis center is communicatively connected with a data acquisition module, a data processing module, a data analysis module and an earthquake intensity assessment module;

[0040] The data acquisition module is used to collect video recording data of buildings when an earthquake occurs;

[0041] It should be further explained that, in the specific implementation process, the process of the data acquisition module collecting the video recording data of the building when the earthquake occurs includes:

[0042] The data acquisition module is composed of a number of data acquisition terminals, and the data acquisition terminals are used to collect video recording data of buildings when an earthquake occurs;

[0043] The data acquisition terminal is configured to generate a corresponding configuration channel. The data acquisition terminal is connected to the city's server through the generated corresponding configuration channel. The data acquisition terminal obtains the video recording of the buildings when the earthquake occurs in the city's server through the corresponding configuration channel, and at the same time collects the earthquake peak acceleration, earthquake peak velocity and earthquake effective duration data from the earthquake monitoring equipment, and sends the obtained video recording of the buildings when the earthquake occurs to the data processing module, while the earthquake dynamics parameter data is transmitted to the data fusion and machine learning module, providing a comprehensive data basis for subsequent analysis and evaluation.

[0044] The data processing module is used to process the collected video recording data of the building to obtain a building height change curve graph and a building height change line graph;

[0045] It should be further explained that, in the specific implementation process, the data processing module processes the collected video recording data of the building to obtain the building height change curve graph and the building height change line graph, including:

[0046] The data processing module receives the video recording of the building when the earthquake occurs sent by the data acquisition module, performs frame processing on the received video recording of the building, obtains a plurality of frames of video recording images of the building, and labels the obtained plurality of frames of video recording images of the building, and marks them as i, i=1, 2, 3, ..., n, where n is a positive integer;

[0047] Perform bidirectional dynamic visual recognition on each frame of video recording to obtain the height of the building in each frame of video recording;

[0048] Constructing a first two-dimensional rectangular coordinate system, wherein the abscissa of the first two-dimensional rectangular coordinate system is the number of the video recording picture, and the ordinate of the first two-dimensional rectangular coordinate system is the height of the building in the corresponding video recording picture;

[0049] Mapping the height of the building in each frame of the video recording picture obtained to the constructed first two-dimensional rectangular coordinate system, generating corresponding first building height sample points, labeling the generated first building height sample points, denoted as i, the label of the first building height sample point is the same as the label of the video recording picture of the building, and connecting each first building height sample point in sequence through a curve in the order of the labels, to obtain a building height change curve graph;

[0050] Constructing a third two-dimensional rectangular coordinate system, wherein the abscissa of the constructed third two-dimensional rectangular coordinate system is the number of the video recording picture, and the ordinate of the constructed third two-dimensional rectangular coordinate system is the height of the building in the corresponding video recording picture;

[0051] The height of the building in each frame of the obtained video recording image is mapped to the constructed third two-dimensional rectangular coordinate system to generate corresponding second building height sample points, and the generated second building height sample points are labeled as i. The number of the second building height sample point is the same as the number of the video recording image of the building, and each second building height sample point is connected in sequence by a straight line in the order of the labels to obtain a line graph of building height changes.

[0052] The data analysis module is used to analyze the obtained building height change curve graph and building height change line graph to obtain the earthquake intensity assessment coefficient;

[0053] It should be further explained that, in the specific implementation process, the data analysis module analyzes the obtained building height change curve graph and building height change line graph to obtain the earthquake intensity assessment coefficient, and the process includes:

[0054] Analyze the line graph of building height changes to obtain the first earthquake intensity assessment coefficient;

[0055] It should be further explained that, in the specific implementation process, the process of analyzing the building height change line graph and obtaining the first earthquake intensity assessment coefficient includes:

[0056] Obtain the height of the building corresponding to the next second building height sample point of each second building height sample point. If the height of the building corresponding to the second building height sample point is the same as the height of the building corresponding to the next second building height sample point of the second building height sample point, record the second building height sample point as the ending second building height sample point, obtain the first ending second building height sample point, remove the second building height sample point and the ending second building height sample point behind the first ending second building height sample point, and obtain a standard building height change line graph;

[0057] The second building height sample point in the standard building height change line graph is labeled as j, j=1, 2, 3, ..., m, where m is a positive integer, and the slope of the straight line between the second building height sample point and the next second building height sample point in the standard building height change line graph is obtained. The slope of the straight line between the second building height sample point and the next second building height sample point in the obtained standard building height change line graph is recorded as K j ;

[0058] Draw a straight line parallel to the vertical axis through the second building height sample point, draw a straight line parallel to the horizontal axis through the next second building height sample point, obtain the intersection of the two straight lines, obtain the area of ​​the right triangle formed by the second building height sample point, the next second building height sample point and the intersection of the two straight lines, and record the area of ​​the right triangle formed by the obtained second building height sample point, the next second building height sample point and the intersection of the two straight lines as S j ;

[0059] Obtain the height of the building corresponding to the terminating second building height sample point in the standard building height change line graph, record the height of the building corresponding to the terminating second building height sample point as H, obtain the first earthquake intensity assessment coefficient according to the height of the building corresponding to the terminating second building height sample point, the slope of the straight line between the second building height sample point and the next second building height sample point, and the area of ​​the right triangle formed by the second building height sample point, the next second building height sample point and the intersection of the two straight lines, and record the obtained first earthquake intensity assessment coefficient as DY;

[0060] in, kp_1 is the adjustment coefficient of the slope of the straight line between the second building height sample point and the next second building height sample point in the standard building height change line graph, kp_2 is the adjustment coefficient of the area of ​​the right triangle formed by the second building height sample point, the next second building height sample point and the intersection of the two straight lines, and up_1 is the adjustment coefficient of the height of the building corresponding to the termination second building height sample point;

[0061] Analyze the building height change curve to obtain the second earthquake intensity assessment coefficient;

[0062] It should be further explained that, in the specific implementation process, the process of analyzing the building height change curve and obtaining the second earthquake intensity assessment coefficient includes:

[0063] Obtain the height of the building corresponding to the next first building height sample point of each first building height sample point. If the height of the building corresponding to the first building height sample point is the same as the height of the building corresponding to the next first building height sample point of the first building height sample point, record the first building height sample point as the ending first building height sample point, obtain the first ending first building height sample point, remove the first building height sample point and the ending first building height sample point behind the first ending first building height sample point, and obtain a standard building height change curve graph;

[0064] The first building height sample point in the standard building height change curve is labeled as j, a straight line parallel to the vertical axis is drawn through the first building height sample point, and a straight line parallel to the horizontal axis is drawn through the next first building height sample point, and the intersection of the two straight lines is obtained. The area of ​​the closed curve figure composed of the first building height sample point, the next first building height sample point and the intersection of the two straight lines is integrated to obtain the integral result, and the obtained integral result is recorded as T j ;

[0065] Obtaining a second earthquake intensity assessment coefficient according to the height of the building corresponding to the acquired second building height termination sample point and the obtained integration result, and recording the obtained second earthquake intensity assessment coefficient as DE;

[0066] in, kp_2 is the adjustment coefficient of the integral result, and up_2 is the adjustment coefficient of the building height corresponding to the termination second building height sample point;

[0067] Obtaining an earthquake intensity assessment coefficient according to the obtained first earthquake intensity assessment coefficient and the second earthquake intensity assessment coefficient, and recording the obtained earthquake intensity assessment coefficient as DZ;

[0068] Among them, DZ = kp_4×DY+kp_5×DE.

[0069] The earthquake intensity assessment module is used to assess the earthquake intensity according to the obtained earthquake intensity assessment coefficient;

[0070] It needs to be further explained that in the specific implementation process, the implementation process of the data fusion and machine learning module is:

[0071] The data fusion and machine learning module receives the earthquake peak acceleration, earthquake peak velocity, earthquake effective duration data from the data acquisition module and the preliminary earthquake intensity assessment coefficient characteristic value set from the data analysis module. Based on a large amount of historical earthquake data (these data cover the accurate correspondence between the above-mentioned data and the actual earthquake intensity), the module selects appropriate machine learning algorithms and neural network to build the model;

[0072] The real-time collected earthquake dynamic parameters and the preliminary earthquake intensity assessment coefficient characteristic values ​​are input into the trained model as input data. The model, based on its internal algorithm logic and the knowledge system obtained through training, deeply integrates and performs complex calculations on multi-source data, fully explores the inherent connections and laws between the data, and finally obtains an accurate earthquake intensity assessment coefficient.

[0073] It should be further explained that, in a specific implementation process, the process of the earthquake intensity assessment module assessing the earthquake intensity according to the obtained earthquake intensity assessment coefficient includes:

[0074] Receive the earthquake intensity assessment coefficient from the data fusion and machine learning module, set the earthquake intensity assessment coefficient threshold range according to the actual situation, and record the set earthquake intensity assessment coefficient threshold range as (DZ0, DZ1);

[0075] Obtaining the earthquake intensity level according to the comparison result between the obtained earthquake intensity assessment coefficient and the set earthquake intensity assessment coefficient threshold range;

[0076] The earthquake intensity levels include level one earthquake intensity, level two earthquake intensity and level three earthquake intensity;

[0077] It should be further explained that, in the specific implementation process, the damage or destruction of buildings caused by the third-level earthquake intensity is higher than that caused by the second-level earthquake intensity, which is higher than that caused by the first-level earthquake intensity;

[0078] When DZ≤DZ0, the earthquake intensity level is level one;

[0079] When DZ0<DZ<DZ1, the earthquake intensity level is level 2;

[0080] When DZ≥DZ1, the earthquake intensity level is level three.

[0081] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent analysis system for earthquake intensity based on bidirectional dynamic visual recognition, including an intelligent analysis center, characterized in that: The intelligent analysis center is communicatively connected with a data acquisition module, a data processing module, a data analysis module, a data fusion and machine learning module, and an earthquake intensity assessment module; The data acquisition module is used to collect video recording data of buildings when an earthquake occurs, and is connected to an earthquake monitoring network or related equipment to collect earthquake peak acceleration, earthquake peak velocity and earthquake effective duration data; The data processing module is used to process the collected video recording data of the building to obtain a building height change curve graph and a building height change line graph; The data analysis module is used to analyze the obtained building height change curve graph and building height change line graph to obtain a preliminary earthquake intensity assessment coefficient characteristic value; The data fusion and machine learning module is used to receive earthquake dynamic parameter data from the data acquisition module, the earthquake dynamic parameter data including earthquake peak acceleration, earthquake peak velocity and earthquake effective duration, and the characteristic value of the preliminary earthquake intensity assessment coefficient from the data analysis module, build a machine learning model with a large amount of historical earthquake data as a training set, input the real-time collected data into the model for data fusion and training, and obtain the final earthquake intensity assessment coefficient; The earthquake intensity assessment module is used to assess the earthquake intensity based on the earthquake intensity assessment coefficient obtained by the data fusion and machine learning module.

2. According to claim 1, the intelligent analysis system of earthquake intensity based on two-way dynamic visual recognition is characterized in that: The process of the data acquisition module acquiring video recording data of a building when an earthquake occurs includes: The data acquisition module is composed of several data acquisition terminals; The data acquisition terminal is configured to generate a corresponding configuration channel. The data acquisition terminal is connected to the city's server through the generated corresponding configuration channel. The data acquisition terminal obtains the video recording of the building when the earthquake occurs in the city's server through the corresponding configuration channel, and sends the obtained video recording of the building when the earthquake occurs to the data processing module. At the same time, the collected earthquake peak acceleration, earthquake peak velocity and earthquake effective duration data are transmitted to the data fusion and machine learning module.

3. The earthquake intensity intelligent analysis system based on bidirectional dynamic visual recognition according to claim 2 is characterized in that: The process of the data processing module processing the collected video data of the building includes: Performing frame processing on the acquired video recording of the building to obtain a plurality of frames of video recording images of the building; Perform bidirectional dynamic visual recognition on each frame of video recording to obtain the height of the building in each frame of video recording; A building height variation curve graph and a building height variation line graph are obtained according to the height of the building in each frame of video recording image obtained.

4. The intelligent analysis system for earthquake intensity based on bidirectional dynamic visual recognition according to claim 3 is characterized in that: The process of obtaining a building height change curve graph and a building height change line graph according to the height of the building in each frame of the video recording image obtained includes: Constructing a first two-dimensional rectangular coordinate system, wherein the abscissa of the first two-dimensional rectangular coordinate system is the number of the video recording picture, and the ordinate of the first two-dimensional rectangular coordinate system is the height of the building in the corresponding video recording picture; Mapping the height of the building in each frame of the video recording image obtained into the constructed first two-dimensional rectangular coordinate system, generating corresponding first building height sample points, and connecting each first building height sample point in sequence through a curve in the order of the labels to obtain a building height change curve graph; Constructing a third two-dimensional rectangular coordinate system, wherein the abscissa of the constructed third two-dimensional rectangular coordinate system is the number of the video recording picture, and the ordinate of the constructed third two-dimensional rectangular coordinate system is the height of the building in the corresponding video recording picture; The height of the building in each frame of the video recording image is mapped to the constructed third two-dimensional rectangular coordinate system to generate corresponding second building height sample points, and each second building height sample point is connected in sequence by a straight line in the order of the labels to obtain a line graph of the building height changes.

5. The intelligent analysis system for earthquake intensity based on bidirectional dynamic visual recognition according to claim 4 is characterized in that: The process of the data analysis module analyzing the obtained building height change curve graph and building height change line graph comprises: According to the obtained building height change line graph, a first earthquake intensity assessment coefficient characteristic value is obtained, and according to the obtained building height change curve graph, a second earthquake intensity assessment coefficient characteristic value is obtained; According to the obtained first earthquake intensity assessment coefficient characteristic value and the second earthquake intensity assessment coefficient characteristic value, a preliminary earthquake intensity assessment coefficient characteristic value set is obtained and transmitted to the data fusion and machine learning module.

6. The intelligent analysis system for earthquake intensity based on bidirectional dynamic visual recognition according to claim 5 is characterized in that: According to the obtained building height change line graph, the process of obtaining the characteristic value of the first earthquake intensity assessment coefficient includes: Obtain the height of the building corresponding to the next second building height sample point of each second building height sample point. If the height of the building corresponding to the second building height sample point is the same as the height of the building corresponding to the next second building height sample point of the second building height sample point, record the second building height sample point as the ending second building height sample point, obtain the first ending second building height sample point, remove the second building height sample point and the ending second building height sample point behind the first ending second building height sample point, and obtain a standard building height change line graph; Obtain the slope of the straight line between the second building height sample point and the next second building height sample point in the standard building height change line graph; Draw a straight line parallel to the longitudinal axis through the second building height sample point, draw a straight line parallel to the horizontal axis through the next second building height sample point, obtain the intersection of the two straight lines, and obtain the area of ​​the right triangle formed by the second building height sample point, the next second building height sample point, and the intersection of the two straight lines; Obtain the height of the building corresponding to the terminating second building height sample point in the standard building height change line graph, and obtain the first earthquake intensity assessment coefficient characteristic value according to the height of the building corresponding to the terminating second building height sample point, the slope of the straight line between the second building height sample point and the next second building height sample point, and the area of ​​the right triangle formed by the second building height sample point, the next second building height sample point, and the intersection of the two straight lines.

7. The intelligent analysis system for earthquake intensity based on bidirectional dynamic visual recognition according to claim 6 is characterized in that: According to the obtained building height change curve, the process of obtaining the characteristic value of the second earthquake intensity assessment coefficient includes: Obtain a standard building height variation curve graph, draw a straight line through a first building height sample point parallel to the vertical axis, draw a straight line through a next first building height sample point parallel to the horizontal axis, obtain the intersection of the two straight lines, integrate the area of ​​a closed curve figure composed of the first building height sample point, the next first building height sample point, and the intersection of the two straight lines, and obtain an integral result; The second earthquake intensity assessment coefficient characteristic value is obtained according to the height of the building corresponding to the acquired second building height termination sample point and the obtained integration result.

8. The intelligent analysis system for earthquake intensity based on bidirectional dynamic visual recognition according to claim 7 is characterized in that: The process of the seismic intensity assessment module assessing the seismic intensity according to the obtained seismic intensity assessment coefficient includes: The earthquake intensity assessment coefficient threshold range is set according to the actual situation, and the earthquake intensity level is obtained according to the comparison result between the obtained earthquake intensity assessment coefficient and the set earthquake intensity assessment coefficient threshold range; The earthquake intensity levels include level one earthquake intensity, level two earthquake intensity and level three earthquake intensity.

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