Pre-earthquake reinforcement and post-earthquake damaged area determination method and device for fabricated building

Abstract

The application discloses a method and device for pre-earthquake reinforcement and post-earthquake damaged area determination of fabricated buildings. The method comprises the following steps: decomposing a plurality of natural earthquake wave vibration curves of main earthquakes and aftershocks into a plurality of types of sub-vibration curves; obtaining a probability density function of each characteristic parameter of the sub-vibration curves; expanding the number of each type of sub-vibration curve to form artificial earthquake wave vibration curves of the main earthquakes and the aftershocks; inputting the earthquake wave vibration curves into a structure dynamic analysis model to calculate a structure damage index; establishing a mapping function relationship between the structure damage index and characteristic parameters of the earthquake wave vibration curves; and based on a generation probability value of the earthquake wave vibration curves and the mapping function relationship, forming a probability density function of the structure damage index. The damage probability of the structure damage index is used to identify a vulnerable area and reinforce the vulnerable area before an earthquake. Through the mapping function relationship, a building layer-by-layer damage state is output in real time after an earthquake, so that a damaged area can be quickly determined. The application can realize closed-loop management and control of precise pre-earthquake defense and post-earthquake rapid evaluation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of seismic performance evaluation of building structures, and in particular to a method and device for pre-earthquake reinforcement and post-earthquake damaged area determination of fabricated buildings. BACKGROUND

[0002] Fabricated high-rise buildings are widely used in the global construction field due to their industrialized construction advantages, but the structural ductility is insufficient due to the prefabricated node construction characteristics, and the risk of damage concentration under seismic action is significantly increased. The current seismic performance evaluation technology has certain problems, that is, in the pre-earthquake defense stage, the quantitative mapping mechanism of the probability distribution of ground motion parameters and structural damage response is not established, so it is impossible to identify high-risk areas, resulting in a lack of targeted protective measures. At the same time, in the post-earthquake emergency stage, due to the lack of rapid analysis capability of the overall damage of the structure, the artificial experience investigation mode is relied on, and it is difficult to locate the damage within the golden disposal period, which seriously restricts the development of the seismic reliability of fabricated buildings. Therefore, it is urgent to establish a method for pre-earthquake reinforcement and post-earthquake damaged area determination of fabricated buildings to solve the above problems in the prior art. SUMMARY

[0003] The purpose of the present application is to overcome the above-mentioned defects and problems in the prior art, and to provide a method and device for pre-earthquake reinforcement and post-earthquake damaged area determination of fabricated buildings. Based on the damage probability of the structural damage index before the earthquake, the vulnerable areas with damage probability exceeding the threshold value are identified and directional reinforcement is carried out; after the earthquake, the mapping function relationship between the structural damage index and the characteristic parameters of the seismic wave vibration curve of the main shock and aftershocks is used to output the layer-by-layer damage state of the fabricated building in real time, so as to quickly determine the damaged area, thereby realizing the closed-loop control of pre-earthquake accurate defense and post-earthquake rapid evaluation.

[0004] To achieve the above purpose, the technical solution of the present application is as follows:

[0005] In a first aspect, the present application provides a method for pre-earthquake reinforcement and post-earthquake damaged area determination of fabricated buildings, comprising:

[0006] Selecting a plurality of natural seismic wave vibration curves of main shocks and aftershocks matched with the seismic risk of the region where the fabricated building is located;

[0007] The natural seismic wave vibration curves of the main shock and the aftershock are respectively decomposed into a plurality of types of sub-vibration curves by using the variational mode decomposition method; sub-vibration curves of the same type are combined to form a characteristic parameter matrix of the sub-vibration curve, and the probability density function of each characteristic parameter in the characteristic parameter matrix is obtained by using the kernel density estimation method;

[0008] The number of each type of sub-vibration curve is amplified by Monte Carlo simulation, a large number of main shock and aftershock artificial earthquake wave vibration curves are formed by random sampling, and the probability density functions of the characteristic parameters of the artificial earthquake wave vibration curves are calculated;

[0009] A database of main shock and aftershock earthquake wave vibration curves including natural earthquake waves and artificial earthquake waves is established, and the generation probability values of the earthquake wave vibration curves are calculated;

[0010] The main shock and aftershock earthquake wave vibration curves are input into the structural dynamic analysis model of the prefabricated building to obtain the structural response results, the ratio of the inter-story drift angle value of each floor structure to the specification limit value is extracted as the structural damage index, and the damage and destruction degree interval is determined;

[0011] A mapping function relationship between the structural damage index and the characteristic parameters of the main shock and aftershock earthquake wave vibration curves is established using a back propagation neural network model, and based on the generation probability values of the earthquake wave vibration curves and the mapping function relationship, a probability density function of the structural damage index is formed;

[0012] The damage probability of the structural damage index in each damage and destruction degree interval is determined through the probability density function of the structural damage index, and compared with the severe damage probability threshold, so as to determine whether the prefabricated building needs to be reinforced;

[0013] According to the characteristic parameters of the main shock and aftershock earthquake wave vibration curves collected on site, the mapping function relationship between the structural damage index and the characteristic parameters of the main shock and aftershock earthquake wave vibration curves is established, the structural damage index value of the prefabricated building after the earthquake is predicted, and the damage area of the prefabricated building is determined.

[0014] Preferably, the probability density function of each characteristic parameter in the characteristic parameter matrix includes:

[0015] The probability density function of each characteristic parameter in the characteristic parameter matrix of the sub-vibration curve of the natural earthquake wave of the main shock is:

[0016] ;

[0017] ;

[0018] ;

[0019] In the formula, is the probability density function of the center frequency of the type sub-vibration curve; is the number of natural earthquake wave vibration curves of the main shock; is the bandwidth; is ​the center frequency of the type sub-vibration curve; the natural seismic wave vibration curve of the main shock of the first the center frequency of the type sub-vibration curve corresponding to the center frequency of the type sub-vibration curve; the center frequency of the type sub-vibration curve; the probability density function of the instantaneous amplitude of the type sub-vibration curve; the dimension corresponding to the instantaneous amplitude and the instantaneous phase shift of the sub-vibration curve of the natural seismic wave of the main shock; the bandwidth matrix; the center frequency of the type sub-vibration curve; the instantaneous amplitude of the type sub-vibration curve; the natural seismic wave vibration curve of the main shock of the first the instantaneous amplitude of the type sub-vibration curve corresponding to the instantaneous amplitude of the type sub-vibration curve; the vector transpose; the instantaneous amplitude of the type sub-vibration curve; the probability density function of the instantaneous phase shift of the type sub-vibration curve; the instantaneous phase shift of the type sub-vibration curve; the instantaneous phase shift of the type sub-vibration curve; the natural seismic wave vibration curve of the main shock of the first the instantaneous phase shift of the type sub-vibration curve corresponding to the instantaneous phase shift of the type sub-vibration curve;

[0020] the probability density function of each characteristic parameter in the characteristic parameter matrix of the sub-vibration curve of the natural seismic wave of the aftershock is:

[0021] ;

[0022] ;

[0023] ;

[0024] wherein, the center frequency of the type sub-vibration curve; the center frequency of the type sub-vibration curve; the number of natural seismic wave vibration curves of the aftershock; the center frequency of the type sub-vibration curve; the center frequency of the type sub-vibration curve; the natural seismic wave vibration curve of the main shock of the first the center frequency of the type sub-vibration curve corresponding to the center frequency of the type sub-vibration curve; the center frequency of the type sub-vibration curve; the probability density function of the instantaneous amplitude of the type sub-vibration curve; the dimension corresponding to the instantaneous amplitude and the instantaneous phase shift of the sub-vibration curve of the natural seismic wave of the main shock; the bandwidth matrix; instantaneous amplitude of the type of sub-vibration curve; instantaneous amplitude of the type of sub-vibration curve corresponding to the natural seismic wave vibration curve of the aftershock;

[0025] Preferably, the generated probability value of the seismic wave vibration curve is:

[0026]

[0027]

[0028]

[0029]

[0030] wherein, are the number of each type of sub-vibration curve of the main shock and the aftershock respectively after Monte Carlo simulation amplification; ​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​a probability density value of the instantaneous amplitude of the i-th vibration curve; is a probability density value of the instantaneous amplitude of the i-th vibration curve in the type sub-vibration curve; a probability density value of the instantaneous amplitude of the i-th vibration curve; is a probability density value of the instantaneous amplitude of the i-th vibration curve in the type sub-vibration curve; a probability density value of the instantaneous phase shift of the i-th vibration curve; is a probability density value of the instantaneous phase shift of the i-th vibration curve in the type sub-vibration curve; a probability density value of the instantaneous amplitude of the i-th vibration curve; is a probability density value of the instantaneous amplitude of the i-th vibration curve in the type sub-vibration curve; a probability density value of the instantaneous amplitude of the i-th vibration curve; is a probability density value of the instantaneous amplitude of the i-th vibration curve in the type sub-vibration curve; a probability density value of the instantaneous phase shift of the i-th vibration curve.

[0031] Preferably, the structural damage indicator is:

[0032] ;

[0033] wherein, is a structural damage indicator; is an inter-story drift angle value; is an inter-story drift angle limit value of an elastic deformation interval;

[0034] The damage and destruction interval is:

[0035] ;

[0036] wherein, is an inter-story drift angle limit value of an elastic deformation interval.

[0037] Preferably, the mapping function relationship between the structural damage indicator and the characteristic parameters of the seismic wave vibration curves of the main shock and the aftershock is:

[0038] ;

[0039] ;

[0040] wherein, is a mapping function of a back propagation neural network model; is a characteristic parameter matrix corresponding to the seismic wave vibration curve extracted from the main shock seismic wave vibration curve database; is a characteristic parameter matrix corresponding to the seismic wave vibration curve extracted from the aftershock seismic wave vibration curve database; A vector formed by the structural damage indices of each floor of a prefabricated building; The total number of floors in the prefabricated building; For the first Layer and first Structural damage index corresponding to the inter-layer displacement angle.

[0041] Preferably, the probability density function of the structural damage index is:

[0042] ;

[0043] In the formula, For the first Layer and first The probability density function of structural damage index corresponding to the inter-story drift angle between layers; and These are the first in the seismic wave vibration curve database. The mainshock wave vibration curve and the first The probability value of generating the vibration curve of an aftershock seismic wave; For the first Layer and first The vector formed by the structural damage index corresponding to the inter-layer displacement angle between layers; For the first Layer and first Predicted values ​​of structural damage indices corresponding to inter-story drift angles. The first in the mainshock wave database The characteristic parameter matrix corresponding to each vibration curve. The first in the aftershock seismic wave database The characteristic parameter matrix corresponding to each vibration curve; and The number of seismic wave vibration curves in the database of seismic wave vibration curves for the mainshock and aftershock, respectively; For bandwidth.

[0044] Preferably, the probability of the structural damage index falling within each damage severity range is:

[0045] ;

[0046] In the formula, For the first Layer and first The structural damage index corresponding to the inter-layer displacement angle is the probability of damage falling within each damage severity range.

[0047] Secondly, the present invention provides a device for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings, the device being applied to the above-described method, the device comprising:

[0048] The seismic wave database establishment module is used for selecting a plurality of main shock and aftershock natural seismic wave vibration curves matched with the seismic risk of the region where the fabricated building is located; the natural seismic wave vibration curves of the main shock and aftershock are respectively decomposed into a plurality of types of sub-vibration curves by using a variational mode decomposition method; the sub-vibration curves of the same type are combined to form a characteristic parameter matrix of the sub-vibration curves, and a kernel density estimation method is used to obtain the probability density function of each characteristic parameter in the characteristic parameter matrix; the number of each type of sub-vibration curve is amplified by Monte Carlo simulation, a large number of artificial seismic wave vibration curves of the main shock and aftershock are formed by random sampling, and the probability density function of each characteristic parameter of the artificial seismic wave vibration curve is calculated; a seismic wave vibration curve database of the main shock and aftershock containing the natural seismic wave and the artificial seismic wave is established, and the generation probability value of the seismic wave vibration curve is calculated;

[0049] The structural damage index acquisition module is used for inputting the seismic wave vibration curves of the main shock and aftershock into the structural dynamic analysis model of the fabricated building to obtain the structural response results, extracting the ratio of the inter-story drift angle value of each floor structure to the specification limit value as the structural damage index, and determining the damage and destruction degree interval;

[0050] The probability density function acquisition module is used for establishing the mapping function relationship between the structural damage index and the characteristic parameters of the seismic wave vibration curves of the main shock and aftershock by using a back propagation neural network model, and forming the probability density function of the structural damage index based on the generation probability value of the seismic wave vibration curve and the mapping function relationship;

[0051] The pre-earthquake structural reinforcement processing module is used for determining the damage probability of the structural damage index in each damage and destruction degree interval by the probability density function of the structural damage index, and comparing with the severe damage probability threshold, so as to determine whether to reinforce the fabricated building;

[0052] The post-earthquake damaged area determination module is used for predicting the structural damage index value of the fabricated building after the earthquake according to the characteristic parameters of the seismic wave vibration curves of the main shock and aftershock collected on site, by the established mapping function relationship between the structural damage index and the characteristic parameters of the seismic wave vibration curves of the main shock and aftershock, and determining the damaged area of the fabricated building.

[0053] In a third aspect, the present application provides a pre-earthquake reinforcement and post-earthquake damaged area determination device for a fabricated building, comprising a memory and a processor;

[0054] The memory is used for storing computer program codes and transmitting the computer program codes to the processor;

[0055] The processor is used for executing the method as described above according to the instructions in the computer program codes.

[0056] In a fourth aspect, the present application provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to implement the method described above.

[0057] Compared with the prior art, the present application has the following beneficial effects:

[0058] 1、The method in the prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method and device fuses variational mode decomposition and Monte Carlo simulation method, decomposes the collected natural main shock and aftershock seismic wave vibration curve into a plurality of sub-vibration curves with physical significance, and forms a plurality of artificial seismic waves through random sampling on the basis. The artificial seismic wave constructed on the one hand is derived from the natural seismic wave record, retains the real physical properties such as frequency distribution, non-stationarity, non-linear structure and statistical characteristics of the natural seismic wave; on the other hand, the uncertainty characteristics of the natural seismic wave are fully considered on the basis of conforming to the probability distribution of each sub-vibration curve, and the problems such as single wave and incomplete spectrum coverage caused by the traditional artificial amplitude modulation method are avoided. The seismic wave sample generated by the method is more comprehensive, diverse and physically credible, and can accurately reflect the vibration behavior and failure mechanism of the structure under complex seismic action, thereby providing more stable, scientific data support for structural seismic performance evaluation, design optimization and safety decision.

[0059] 2、The prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method and device, the main shock and aftershock seismic wave database established not only contains the vibration curve of natural and artificial seismic waves, but also gives each seismic wave vibration curve corresponding generation probability, thereby forming a seismic wave vibration curve set with physical rationality and statistical significance, providing standardized data support for machine learning model training, seismic wave physical model testing and other research, and significantly improving the robustness of seismic design and the scientificity of seismic risk assessment. At the same time, the database also has a real-time updating mechanism, can integrate the newly occurring natural seismic wave into the existing database system, so that the database still maintains the ability to describe the multi-scale characteristics and probability characteristics of the seismic wave during the updating process, and provides dynamic updated data support for seismic engineering research and application.

[0060] 3、The application is a prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method and device, which establishes a mapping function relationship between seismic wave characteristic parameters and structural damage indicators through a machine learning model, generates a damage indicator probability distribution by combining probability analysis, realizes double engineering application: pre-earthquake based on structural damage indicator probability value, identifies vulnerable areas with damage probability exceeding the threshold value, and performs directional reinforcement; After the earthquake, the mapping function relationship is used to output the building layer-by-layer damage state in real time, so as to quickly locate the damaged area. The application changes the seismic decision from experience judgment to probability quantization, directly supports multi-level probabilistic seismic design specifications, realizes pre-earthquake accurate defense and post-earthquake rapid evaluation closed-loop control. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 is a flowchart of a prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method of the application.

[0062] Figure 2 is a structural diagram of the BP neural network model provided by the embodiment of the application.

[0063] Figure 3 is a model diagram of a certain prefabricated building structure in a finite element software provided by the embodiment of the application.

[0064] Figure 4 is a structural block diagram of a prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination device of the application.

[0065] Figure 5 is a structural block diagram of a prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination device of the application. DETAILED DESCRIPTION

[0066] The application will be further described in detail in combination with the description of the drawings and specific embodiments.

[0067] Referring to Figure 1 , the application provides a prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method, comprising:

[0068] S1, selecting a plurality of main shock and aftershock natural seismic wave vibration curves matched with the seismic risk of the region where the prefabricated building is located;

[0069] S2, using a variational mode decomposition method to decompose the natural seismic wave vibration curves of the main shock and aftershock into a plurality of types of sub-vibration curves; merging the sub-vibration curves of the same type to form a characteristic parameter matrix of the sub-vibration curves, and using a kernel density estimation method to obtain the probability density function of each characteristic parameter in the characteristic parameter matrix;

[0070] S3, the number of each type of sub-vibration curve is amplified by Monte Carlo simulation, a large number of main shock and aftershock artificial earthquake wave vibration curves are formed by random sampling, and the probability density function of each characteristic parameter of the artificial earthquake wave vibration curve is calculated;

[0071] S4, a database of main shock and aftershock earthquake wave vibration curves containing natural earthquake waves and artificial earthquake waves is established, and the generation probability value of the earthquake wave vibration curve is calculated;

[0072] S5, input the main shock and aftershock earthquake wave vibration curve into the structural dynamic analysis model of the fabricated building to obtain the structural response result, extract the ratio of the inter-story drift angle value of each floor structure to the specification limit as the structural damage index, and determine the damage and damage degree interval;

[0073] S6, a mapping function relationship between the structural damage index and the characteristic parameters of the main shock and aftershock earthquake wave vibration curve is established by using the back propagation neural network model, and based on the generation probability value of the earthquake wave vibration curve and the mapping function relationship, the probability density function of the structural damage index is formed;

[0074] S7, the damage probability of the structural damage index in each damage and damage degree interval is determined through the probability density function of the structural damage index, and compared with the severe damage probability threshold, so as to judge whether the fabricated building needs to be reinforced;

[0075] S8, according to the characteristic parameters of the main shock and aftershock earthquake wave vibration curve collected on site, the mapping function relationship between the structural damage index and the characteristic parameters of the main shock and aftershock earthquake wave vibration curve is established, the structural damage index value of the fabricated building after the earthquake is predicted, and the area of the fabricated building where damage occurs is determined.

[0076] The present application is used to solve the problems of existing fabricated building structure damage evaluation lag under the action of earthquake response and insufficient modeling of ground motion uncertainty, etc. The key damage indicators of the fabricated building structure after the action of earthquake are used as the core basis for the evaluation of the structural stability. First, a plurality of natural earthquake wave vibration curves are selected, including main shock vibration curves and aftershock vibration curves, which match the seismic risk of the region where the fabricated building is located. Then, the selected earthquake wave vibration curves are decomposed by using the variational mode decomposition (VMD) method to obtain a plurality of typical modal components, and the key characteristic parameters of each modal component are extracted, including instantaneous amplitude, main frequency characteristics and phase information, etc. Then, the probability density function of each modal parameter is constructed by using the kernel density estimation method, and the modal characteristics are reconstructed and amplified by combining the Monte Carlo simulation. A plurality of artificial earthquake wave vibration curves with statistical representativeness are generated by randomly extracting and combining different types of sub-vibration curves, and a main shock earthquake wave curve database and an aftershock earthquake wave curve database are established. Then, the generated artificial main shock and aftershock earthquake waves are input into the structural dynamic analysis model of the fabricated building to obtain the structural response results, and the ratio of the inter-story drift angle of each floor structure to the specification limit value is extracted as the structural damage indicator. According to the relevant specifications, the threshold value of the structural damage indicator is set to determine the damage and destruction degree interval. Then, based on a large amount of sample data, the mapping function relationship between the seismic wave characteristic parameters and the structural damage indicators is established by using the back propagation neural network model (BP), and the probability density function of the structural damage indicator is further formed. Finally, according to the formed probability density function of the structural damage indicator, the fabricated building is evaluated to determine the damage probability of the structural damage indicator in each damage and destruction degree interval, and compared with the severe damage probability threshold to determine the vulnerable damage area of the fabricated building and perform reinforcement treatment. When the actual earthquake comes, the damage situation of the fabricated building after the earthquake is quickly evaluated according to the mapping function relationship between the structural damage indicator and the seismic wave characteristic parameters, so as to quickly and point-to-point investigate the structural damage area. The above method can efficiently evaluate the damage risk of the structure on the basis of fully considering the uncertainty of ground motion, and provide scientific and reliable technical support for targeted reinforcement of vulnerable areas before the earthquake and quick and point-to-point investigation of structural damage areas after the earthquake.

[0077] Further, taking a certain fabricated high-rise building structure as an example, the building adopts a fabricated shear wall-frame structure, the total number of floors is 30, the total height of the building is about 90 meters, the fabrication rate is more than 60%, and the seismic fortification intensity of the region where the building is located is 8 degrees, and the site type is type II.

[0078] According to the site conditions, structural dynamic response characteristics, site type and relevant provisions in the standard "Building Seismic Design Standard" (GB 50011-2010) of a certain fabricated high-rise building, 20 natural main shock earthquake wave vibration curves and 10 natural aftershock earthquake wave vibration curves are selected which match the seismic risk of the region where the building is located.

[0079] The selected natural seismic wave vibration curves of multiple mainshocks and aftershocks possess different peak ground acceleration and spectral characteristics, covering various scenarios from common to rare earthquakes in the region. Furthermore, by eliminating the random bias of individual seismic waves, the reliability requirements of time history analysis are met according to regulations. Based on the selected 20 natural mainshock seismic wave vibration curves, the duration of energy within the 5% to 95% range of each mainshock seismic wave vibration curve was statistically analyzed. Zero-padding was then used to process the mainshock seismic wave vibration curves, ensuring that the duration of all vibration curves was consistent, and that the energy percentage of each vibration curve reached 90% within this time period. Based on the selected 10 natural aftershock seismic wave vibration curves and the processing method used for the mainshock seismic wave vibration curves, the 10 natural aftershock seismic wave vibration curves were processed to ensure consistent duration and that the energy percentage within this time period reached 90%.

[0080] Furthermore, based on the processed seismic wave vibration curves of the mainshock and aftershocks, the variational mode decomposition method was used to decompose the seismic wave vibration curves of the mainshock and aftershocks into 8 and 6 types of sub-vibration curves, respectively. The functional expressions for each sub-vibration curve and the seismic wave vibration curve were established using the following formula.

[0081] ;

[0082] ;

[0083] In the formula, For the first The vibration curve of the natural mainshock seismic wave in Vibration value at time; For the first The vibration curve of the natural mainshock seismic wave Type sub-vibration curves in Instantaneous amplitude at a given moment; for The center frequency of the sub-vibration curve; for Type sub-vibration curves in Instantaneous phase shift at a given moment; For a given moment in the vibration curve of the natural mainshock seismic wave, its value range is... , This refers to the effective duration corresponding to the duration of the vibration curve of the natural mainshock seismic wave. The value is 30s; The range of values ​​is ; For the first The vibration curve of the natural aftershock seismic wave in Vibration value at time; For the first Vibration curves of natural aftershock seismic waves Type sub-vibration curves in Instantaneous amplitude at a given moment; for The center frequency of the sub-vibration curve; for Type sub-vibration curves in Instantaneous phase shift at a given moment; The range of values ​​is , This represents the total time points corresponding to the duration of the vibration curve of natural aftershock seismic waves. The value is 20s; The range of values ​​is .

[0084] The Variational Mode Decomposition (VMD) method is an adaptive signal processing algorithm that decomposes complex signals into multiple modal components with finite bandwidth by constructing a variational model. Since seismic wave vibration curves are non-stationary signals composed of superimposed different types of seismic waves, such as P-waves and S-waves, the frequency and amplitude of each wave dynamically change over time. Therefore, the VMD method is used to decompose them into modal components with different characteristics, i.e., different types of sub-vibration curves, in order to accurately extract the spectral characteristics and other parameters of each sub-vibration curve.

[0085] Furthermore, based on the sub-vibration curves decomposed from the natural mainshock seismic wave vibration curve and their characteristic parameters, sub-vibration curves of the same type are merged into a group to form a group reflecting all... The characteristic parameter matrix of the sub-vibration curve is shown in the following equation:

[0086] ;

[0087] In the formula, For all The characteristic parameter matrix of the sub-vibration curves is obtained by dividing the 20 natural mainshock seismic wave vibration curves into 8 types of sub-vibration curves and extracting all... The characteristic parameters of the type vibration curve are combined.

[0088] Based on the sub-vibration curves decomposed from the vibration curves of natural aftershocks and their characteristic parameters, sub-vibration curves of the same type are merged into a group to form a reflection of... The matrix of all characteristic parameters of the sub-vibration curve is shown in the following equation:

[0089] ;

[0090] In the formula, For all The characteristic parameter matrix of the type sub-vibration curve is composed of the characteristic parameters of all the 10 natural main shock seismic wave vibration curves divided into 6 types of sub-vibration curves. The characteristic parameter matrix of the type sub-vibration curve is composed of the characteristic parameters of all the 10 natural main shock seismic wave vibration curves divided into 6 types of sub-vibration curves.

[0091] Further, the probability density function of each characteristic parameter in the characteristic parameter matrix includes:

[0092] The formula of the kernel density estimation method is as follows:

[0093] ;

[0094] ;

[0095] In the formula, is the parameter to be estimated and is in scalar form; is the sample number; is the sample number; is the bandwidth; is the exponential function with the natural constant as the base; is the probability density function of the parameter to be estimated; is the parameter to be estimated and is in vector form; is the dimension value of the parameter ; is the bandwidth matrix; is the vector transpose symbol; is the probability density function of the vector .

[0096] The center frequency in the characteristic parameter matrix is in scalar form, and the instantaneous amplitude and instantaneous phase offset are in vector form.

[0097] According to the obtained characteristic parameter matrix of the natural seismic wave vibration curve of the main shock after decomposition , the kernel density estimation method is used to form the probability density function of each characteristic parameter in the characteristic parameter matrix , as shown in the following formula:

[0098] ;

[0099] ;

[0100] ;

[0101] In the formula, is the probability density function of the center frequency of the type sub-vibration curve; is the bandwidth; is the probability density function of the center frequency of the type sub-vibration curve; is the bandwidth; The center frequency of the subtype vibration curve; For the first The natural seismic wave vibration curve corresponding to the mainshock The center frequency of the subtype vibration curve; for The probability density function of the instantaneous amplitude of the sub-vibration curve; The dimensions corresponding to the instantaneous amplitude and instantaneous phase shift of the sub-vibration curves of the natural seismic wave of the mainshock; This is the bandwidth matrix; for The instantaneous amplitude of the sub-vibration curve; For the first The natural seismic wave vibration curve corresponding to the mainshock The instantaneous amplitude of the sub-vibration curve; Transpose of a vector; for The probability density function of the instantaneous phase shift of the sub-vibration curve; for Instantaneous phase shift of the sub-vibration curve; For the first The natural seismic wave vibration curve corresponding to the mainshock Instantaneous phase shift of the sub-vibration curve.

[0102] Based on the obtained matrix The probability density functions of each characteristic parameter in the model are independent of each other. This is achieved by calculating the probability density function of the mainshock wave. Joint probability density function of sub-vibration curves .

[0103] .

[0104] Based on the characteristic parameter matrix obtained from the decomposition of the natural seismic wave vibration curves of the aftershocks The kernel density estimation method is used to form the feature parameter matrix. The probability density functions of each feature parameter are shown in the following equation:

[0105] ;

[0106] ;

[0107] ;

[0108] In the formula, for The probability density function of the center frequency of the sub-vibration curve; for a center frequency of the type sub-vibration curve; the natural earthquake wave vibration curve of the aftershock corresponding to the a center frequency of the type sub-vibration curve; the natural earthquake wave vibration curve of the aftershock corresponding to the a center frequency of the type sub-vibration curve; a probability density function of the instantaneous amplitude of the type sub-vibration curve; a dimension corresponding to the instantaneous amplitude and the instantaneous phase offset of the sub-vibration curve of the natural earthquake wave of the aftershock; a center frequency of the type sub-vibration curve; an instantaneous amplitude of the type sub-vibration curve; the natural earthquake wave vibration curve of the aftershock corresponding to the an instantaneous amplitude of the type sub-vibration curve; the natural earthquake wave vibration curve of the aftershock corresponding to the a probability density function of the instantaneous phase offset of the type sub-vibration curve; an instantaneous phase offset of the type sub-vibration curve; an instantaneous phase offset of the type sub-vibration curve; an instantaneous phase offset of the type sub-vibration curve; the natural earthquake wave vibration curve of the aftershock corresponding to the an instantaneous phase offset of the type sub-vibration curve. According to the probability density functions of the characteristic parameters in the obtained matrix

[0109] the joint probability density functions of the type sub-vibration curves in the aftershock earthquake wave are formed.

[0110] .

[0111] The kernel density estimation method is a non-parametric probability density estimation technique, which estimates the probability density function of data by placing a kernel function on each data point and summing it up with weighting, so as to intuitively reflect the distribution form of data without assuming the distribution of data in advance. Therefore, the parameter characteristic distribution of each type of sub-vibration curve is calculated by the kernel density estimation method, and the corresponding probability density function is formed, thereby establishing a probability analysis basis for the probability function of the artificial earthquake wave to be obtained subsequently.

[0112] Further, according to the joint probability density functions of all types of sub-vibration curves in the main shock and the aftershock earthquake wave, sampling is performed by a Monte Carlo simulation method, the number of all types of main shock and aftershock sub-vibration curves is respectively expanded to 100 and 50, and the sub-vibration curves decomposed from the original natural earthquake wave are contained, and the extraction process conforms to the joint probability density function distribution of each type of sub-vibration curve.

[0113] ​​The Monte Carlo simulation method described above generates a large set of virtual samples that conform to the distribution of the original data through random sampling. These virtual samples possess statistical characteristics similar to the original data, thus effectively expanding the sample coverage of the original data. Therefore, compared to the limited number of original sub-vibration curve samples, the Monte Carlo sampling method, by expanding the number of sample curves according to the probability density function corresponding to each type of sub-vibration curve, can both maintain the statistical characteristics of various sub-vibration curves and enhance the representativeness and comprehensiveness of seismic motion simulation. This provides more sufficient data support for subsequently establishing the mapping function relationship between structural damage indicators and seismic wave characteristic parameters.

[0114] Based on the obtained sub-vibration curves, the vibration curves of artificial mainshock and aftershock seismic waves are formed by random sampling. The occurrence probability values ​​corresponding to the vibration curves of artificial mainshock and aftershock seismic waves are calculated by the following formula, and then a database containing seismic wave vibration characteristic parameters and their occurrence probabilities is built.

[0115] The aforementioned mainshock and aftershock seismic wave vibration curve database is established by randomly combining various types of sub-vibration curves to generate artificial seismic waves that conform to the statistical characteristics of real ground motion, thereby creating a database containing the characteristic parameters of artificial seismic waves and their generation probabilities.

[0116] The probability of generating a seismic wave vibration curve is:

[0117] ;

[0118] ;

[0119] ;

[0120] ;

[0121] In the formula, The generation probability value of the seismic wave vibration curve of the mainshock; for The first type of vibration curve The joint probability density value of the vibration curves; for The first type of vibration curve The joint probability density value of the vibration curves; This represents the probability value for generating the seismic wave vibration curve of an aftershock. for The first type of vibration curve The joint probability density value of the vibration curves; for The first type of vibration curve The joint probability density value of the vibration curves; For the probability density value of the instantaneous amplitude of the first vibration curve in the type sub-vibration curve; For the probability density value of the instantaneous amplitude of the first vibration curve in the type sub-vibration curve; For the probability density value of the instantaneous phase offset of the first vibration curve in the type sub-vibration curve; For the probability density value of the instantaneous amplitude of the first vibration curve in the type sub-vibration curve; For the probability density value of the instantaneous amplitude of the first vibration curve in the type sub-vibration curve; For the probability density value of the instantaneous phase offset of the first vibration curve in the type sub-vibration curve.

[0122] Further, according to the structure form of the fabricated high-rise building and the specification requirements of the "Building Seismic Design Standard" (GB 50011-2010), the elastic deformation interval limit value of the inter-story drift angle of the structure under the action of the earthquake is selected (1 / 550) and the elastic-plastic deformation interval limit value (1 / 100), and a structure damage index and a damage and destruction degree interval are established.

[0123] The structure damage index is:

[0124] ;

[0125] In the formula, is the structure damage index; is the inter-story drift angle value; is the inter-story drift angle limit value of the elastic-plastic deformation interval;

[0126] The damage and destruction degree interval is:

[0127] .

[0128] The structure damage index is according to the specification requirements of the "Building Seismic Design Standard" (GB 50011-2010), the structure type of the fabricated high-rise building, the specification limit value of the inter-story drift angle of the structure under the action of the earthquake in the elastic deformation interval and the elastic-plastic deformation interval, and the ratio is formed, forming the damage and destruction degree interval, i.e. the slight damage area, the moderate damage area and the severe damage area.

[0129] Further, according to the structural form of the fabricated high-rise building, a model is established in the finite element software, as shown in the figure. Figure 3 Subsequently, 3000 groups of vibration curves are randomly selected from the established main shock and aftershock seismic wave database, each group containing 1 main shock seismic wave vibration curve and 1 aftershock seismic wave vibration curve, and input into the finite element software in sequence, to simulate the vibration response of the fabricated building structure under the action of earthquakes, and then collect the inter-story drift angle data of each layer of the building, and form the structural damage index vector of each layer, as shown in the following formula:

[0130] .

[0131] The dynamic analysis model is a numerical model of the fabricated high-rise building structure constructed based on the finite element software, and the connection nodes are finely modeled and parameterized, which can more accurately simulate the dynamic response characteristics of the building under the action of seismic waves, so as to determine the inter-story drift angle of each layer.

[0132] According to the selected main shock seismic wave and aftershock seismic wave vibration curve and the determined structural damage index vector, a BP neural network model is established, as shown in the figure. Figure 2 In order to eliminate the influence of the dimension of the characteristic parameters of the seismic wave vibration, the characteristic parameters are normalized according to the following formula, so that the data value is located in the interval.

[0133] ;

[0134] In the formula, x is the normalized data value; x0 is the original data value; xmin is the minimum value in the original data; and xmax is the maximum value in the original data.

[0135] According to the obtained data, the number of input layer neurons of the determined BP neural network model is 42, and the number of output layer neurons is 29, and the number of hidden layer neurons is 15 according to the following formula.

[0136] ;

[0137] In the formula, the parameter n is an integer between 1 and 15.

[0138] ​​​​​​​​​​According to the determined normalized data and the number of neurons in each layer of the BP neural network, the instantaneous amplitude, the center frequency and the instantaneous phase offset parameters corresponding to each sub-vibration curve of the main shock and the aftershock seismic wave and the damage index of each layer of the structure are brought into the BP neural network model, and a mapping function relationship reflecting the damage index of the structure and the characteristic parameters of the vibration curve of the main shock and the aftershock is formed through training, as shown in the following formula:

[0139] ;

[0140] In the formula, is a mapping function of the back propagation neural network model; is a characteristic parameter matrix corresponding to the extracted seismic wave vibration curve from the main shock seismic wave vibration curve database; is a characteristic parameter matrix corresponding to the extracted seismic wave vibration curve from the main shock seismic wave vibration curve database; is a vector formed by the structural damage index of each layer of the assembled building.

[0141] The back propagation neural network model can learn and utilize a large amount of data between independent variables and dependent variables, and form a mapping function relationship without revealing the function equation corresponding to the mapping relationship in advance. Since the generated artificial seismic wave contains multiple characteristic parameters in the form of scalar and vector, and has a complex high-dimensional nonlinear relationship with the inter-story drift angle of the structure. Therefore, the BP neural network model can deeply learn the complex relationship between the two and form a mapping function relationship between the two. At the same time, by using the established BP neural network model, the characteristic parameters of the vibration curve of the remaining combination of the main shock and the aftershock in the seismic wave database are input to obtain the structural damage index of each layer of the structure, which can not only reduce the calculation time cost of the finite element model, but also provide a large amount of data support for subsequent construction of the probability density function of the structural damage index.

[0142] Further, according to the generated probability function of the vibration curve of the main shock seismic wave and the aftershock seismic wave, and the established mapping function relationship, the probability density function of the structural damage index is established by the kernel density estimation formula, as shown in the following formula:

[0143] ;

[0144] In the formula, is the probability density function of the structural damage index corresponding to the inter-story drift angle between the first layer and the second layer; is the probability density function of the structural damage index corresponding to the inter-story drift angle between the first layer and the second layer; and are the first main shock seismic wave vibration curve and the second main shock seismic wave vibration curve in the seismic wave vibration curve database, respectively; and ​The generating probability value of the aftershock seismic wave vibration curve; The structure damage index corresponding to the interlayer displacement angle between the first layer and the second layer; The predicted value of the structure damage index corresponding to the interlayer displacement angle between the first layer and the second layer, the predicted value including the finite element simulation data included in the BP neural network model training stage and the direct prediction result data not obtained through finite element simulation calculation, The characteristic parameter matrix corresponding to the first vibration curve in the main shock seismic wave database, The characteristic parameter matrix corresponding to the first vibration curve in the aftershock seismic wave database; The bandwidth.

[0145] The probability density function of the structure damage index is obtained by collecting the structure damage index values of the dynamic model of the structure under the action of the seismic wave, using the Dirac function to establish the probability density function of the structure damage index values including the BP model mapping function and the generating probability function of the seismic wave, using the kernel density estimation method to smooth the discrete probability points, and then converting the discrete model into a continuous probability density function, so as to intuitively present the complete probability distribution form of the structure damage index, and provide more rigorous technical support for seismic risk assessment, pre-earthquake vulnerability area reinforcement, post-earthquake rapid assessment of building damage and fixed-point inspection of damaged areas.

[0146] Further, the damage probability of the structure damage index in each damage and destruction degree interval is:

[0147] ;

[0148] In the formula, The damage probability of the structure damage index in each damage and destruction degree interval between the first layer and the second layer.

[0149] Further, according to the expert scoring method and the requirements of the relevant specifications, the severe damage probability threshold is determined to be 3%. By comparing the severe damage probability values of each layer of the structure with the threshold, when the severe damage probability value of a layer is greater than 3%, the layer needs to be reinforced to reduce the structural damage caused by the earthquake.

[0150] Further, according to the field collected main shock and aftershock seismic wave vibration curves, the main shock and aftershock seismic wave vibration curves are decomposed into corresponding type sub-vibration curves, and the characteristic parameters of each type of sub-vibration curve are extracted, the mapping function relationship between the structure damage index and the characteristic parameters of the main shock and aftershock seismic wave vibration curves is established, the structure damage index values of each layer of the prefabricated building after the earthquake are predicted, and the damaged area of the prefabricated building is determined.

[0151] Referring to Figure 4 The application further provides a prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination device, which is applied to the prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method, and comprises:

[0152] The earthquake wave database establishment module is used for selecting a plurality of main shock and aftershock natural seismic wave vibration curves matched with the seismic risk of the region where the prefabricated building is located, decomposing the main shock and aftershock natural seismic wave vibration curves into a plurality of types of sub-vibration curves by using a variational mode decomposition method, combining the sub-vibration curves of the same type to form a characteristic parameter matrix of the sub-vibration curves, obtaining the probability density functions of the characteristic parameters in the characteristic parameter matrix by using a kernel density estimation method, amplifying the number of each type of sub-vibration curve by Monte Carlo simulation, randomly sampling to form a large number of artificial main shock and aftershock seismic wave vibration curves, calculating the probability density functions of the characteristic parameters of the artificial seismic wave vibration curves, establishing a main shock and aftershock seismic wave vibration curve database containing natural seismic waves and artificial seismic waves, and calculating the generation probability values of the seismic wave vibration curves.

[0153] The structure damage index acquisition module is used for inputting the main shock and aftershock seismic wave vibration curves into the structure dynamic analysis model of the prefabricated building to obtain the structure response results, extracting the ratio of the inter-story drift angle value of each floor structure to the specification limit value as the structure damage index, and determining the damage and destruction degree interval.

[0154] The probability density function acquisition module is used for establishing the mapping function relationship between the structure damage index and the characteristic parameters of the main shock and aftershock seismic wave vibration curves by using a back propagation neural network model, and forming the probability density function of the structure damage index based on the generation probability values of the seismic wave vibration curves and the mapping function relationship.

[0155] The pre-earthquake structure reinforcement processing module is used for determining the damage probability of the structure damage index in each damage and destruction degree interval by using the probability density function of the structure damage index, and comparing the damage probability with a severe damage probability threshold value, so as to determine whether to reinforce the prefabricated building.

[0156] The post-earthquake damaged area determination module is used for predicting the structural damage index value of the prefabricated building after the earthquake according to the characteristic parameters of the earthquake wave vibration curve of the main shock and aftershocks, and determining the damaged area of the prefabricated building.

[0157] Referring to Figure 5 The application further provides a prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination device.

[0158] The memory is used for storing computer program codes and transmitting the computer program codes to the processor.

[0159] The processor is used for executing the prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method according to the instructions in the computer program codes.

[0160] The application further provides a computer readable storage medium, which stores computer programs, and the computer programs are executed by the processor to realize the prefabricated building pre-earthquake reinforcement and post-earthquake damaged area determination method.

[0161] Generally, the computer instructions used to realize the method of the application can be carried by any combination of one or more computer readable storage media. The non-transitory computer readable storage medium can include any computer readable medium except the signal itself in the process of transmission.

[0162] The computer readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples (non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EKROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component.

[0163] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages, particularly Python language and platform frameworks based on TensorFlow, PyTorch, etc. suitable for neural network computing. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0164] The above device and non-transitory computer readable storage medium can refer to the specific description of the pre-earthquake reinforcement and post-earthquake damaged area determination method of the prefabricated building and the beneficial effects, which will not be repeated here.

[0165] Although the embodiments of the present application have been shown and described above, it should be understood by those skilled in the art that the above embodiments are exemplary and cannot be interpreted as a limitation of the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A method for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings, characterized in that, include: Select vibration curves of natural seismic waves from multiple mainshocks and aftershocks that match the seismic hazard of the area where the prefabricated building is located; The variational mode decomposition method is used to decompose the natural seismic wave vibration curves of the mainshock and aftershock into several types of sub-vibration curves respectively; the sub-vibration curves of the same type are merged to form the characteristic parameter matrix of the sub-vibration curve, and the kernel density estimation method is used to obtain the probability density function of each characteristic parameter in the characteristic parameter matrix; The number of sub-vibration curves of various types was increased by Monte Carlo simulation, and a large number of artificial seismic wave vibration curves of mainshock and aftershock were generated by random sampling. The probability density function of each characteristic parameter of the artificial seismic wave vibration curve was calculated. Establish a database of seismic wave vibration curves containing the mainshock and aftershocks of natural and artificial seismic waves, and calculate the generation probability values ​​of the seismic wave vibration curves. The seismic wave vibration curves of the main shock and aftershocks are input into the structural dynamic analysis model of the prefabricated building to obtain the structural response results. The ratio of the inter-story drift angle value of each floor structure to its code limit is extracted as a structural damage index, and the range of damage degree is determined. A backpropagation neural network model was used to establish a mapping function relationship between structural damage indicators and characteristic parameters of seismic wave vibration curves of the main shock and aftershocks. Based on the generation probability value of the seismic wave vibration curves and the mapping function relationship, a probability density function of structural damage indicators was formed. The probability density function of the structural damage index is used to determine the damage probability of the structural damage index in each damage level range, and then compared with the severe damage probability threshold to determine whether the prefabricated building needs to be reinforced. Based on the characteristic parameters of the seismic wave vibration curves of the mainshock and aftershocks collected on-site, the structural damage index value of prefabricated buildings after the earthquake is predicted by establishing a mapping function relationship between the structural damage index and the characteristic parameters of the seismic wave vibration curves of the mainshock and aftershocks, and the areas of damage to the prefabricated buildings are determined.

2. The method for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings according to claim 1, characterized in that, The probability density function of each feature parameter in the feature parameter matrix includes: The probability density function of each characteristic parameter in the characteristic parameter matrix of the sub-vibration curve of the mainshock's natural seismic wave is: ； ； ； In the formula, for The probability density function of the center frequency of the sub-vibration curve; The number of natural seismic wave vibration curves for the mainshock; For bandwidth; for The center frequency of the subtype vibration curve; For the first The natural seismic wave vibration curve corresponding to the mainshock The center frequency of the subtype vibration curve; for The probability density function of the instantaneous amplitude of the sub-vibration curve; The dimensions corresponding to the instantaneous amplitude and instantaneous phase shift of the sub-vibration curves of the natural seismic wave of the mainshock; This is the bandwidth matrix; for The instantaneous amplitude of the sub-vibration curve; For the first The natural seismic wave vibration curve corresponding to the mainshock The instantaneous amplitude of the sub-vibration curve; Transpose of a vector; for The probability density function of the instantaneous phase shift of the sub-vibration curve; for Instantaneous phase shift of the sub-vibration curve; For the first The natural seismic wave vibration curve corresponding to the mainshock Instantaneous phase shift of the sub-vibration curve; The probability density function of each characteristic parameter in the characteristic parameter matrix of the sub-vibration curve of the natural seismic wave of the aftershock is: ； ； ； In the formula, for The probability density function of the center frequency of the sub-vibration curve; The number of natural seismic wave vibration curves for aftershocks; for The center frequency of the subtype vibration curve; For the first The natural seismic wave vibration curve corresponding to the aftershock The center frequency of the subtype vibration curve; for The probability density function of the instantaneous amplitude of the sub-vibration curve; The dimension corresponding to the instantaneous amplitude and instantaneous phase shift of the sub-vibration curve of the natural seismic wave of the aftershock; for The instantaneous amplitude of the sub-vibration curve; For the first The natural seismic wave vibration curve corresponding to the aftershock The instantaneous amplitude of the sub-vibration curve; for The probability density function of the instantaneous phase shift of the sub-vibration curve; for Instantaneous phase shift of the sub-vibration curve; For the first The natural seismic wave vibration curve corresponding to the aftershock Instantaneous phase shift of the sub-vibration curve.

3. The method for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings according to claim 2, characterized in that, The generation probability value of the seismic wave vibration curve is: ； ； ； ； In the formula, The generation probability value of the seismic wave vibration curve of the mainshock; for The first type of vibration curve The joint probability density value of the vibration curves; for The first type of vibration curve The joint probability density value of the vibration curves; The total number of types of sub-vibration curves decomposed from the seismic wave vibration curve of the mainshock; This represents the probability value for generating the seismic wave vibration curve of an aftershock. for The first type of vibration curve The joint probability density value of the vibration curves; for The first type of vibration curve The joint probability density value of the vibration curves; The total number of types of sub-vibration curves that can be decomposed from the seismic wave vibration curves of aftershocks; and These represent the number of sub-vibration curves of the seismic waves of the mainshock and aftershock after Monte Carlo simulation amplification; for The first type of vibration curve The probability density value of the center frequency of the vibration curve; for The first type of vibration curve The probability density value of the instantaneous amplitude of the vibration curve; for The first type of vibration curve The probability density value of the instantaneous phase shift of the vibration curve; for The first type of vibration curve The probability density value of the center frequency of the vibration curve; for The first type of vibration curve The probability density value of the instantaneous amplitude of the vibration curve; for The first type of vibration curve The probability density value of the instantaneous phase shift of the vibration curve.

4. The method for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings according to claim 1, characterized in that, The structural damage index is: ； In the formula, As an indicator of structural damage; This represents the inter-story drift angle value. This is the limit value for the interlayer displacement angle within the elastic-plastic deformation range; The range of damage severity is as follows: ； In the formula, This represents the inter-layer displacement angle limit within the elastic deformation range.

5. The method for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings according to claim 4, characterized in that, The mapping function relationship between the structural damage index and the characteristic parameters of the seismic wave vibration curves of the mainshock and aftershocks is as follows: ； ； In the formula, For the mapping function of the backpropagation neural network model; This is the characteristic parameter matrix corresponding to the seismic wave vibration curves extracted from the seismic wave vibration curve database of the mainshock; This is the characteristic parameter matrix corresponding to the seismic wave vibration curves extracted from the seismic wave vibration curve database of aftershocks. A vector formed by the structural damage indices of each floor of a prefabricated building; The total number of floors in the prefabricated building; For the first Layer and first Structural damage index corresponding to the inter-layer displacement angle.

6. The method for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings according to claim 5, characterized in that, The probability density function of the structural damage index is: ； In the formula, For the first Layer and first The probability density function of structural damage index corresponding to the inter-story drift angle between layers; and These are the first in the seismic wave vibration curve database. The mainshock wave vibration curve and the first The probability value of generating the vibration curve of an aftershock seismic wave; For the first Layer and first The vector formed by the structural damage index corresponding to the inter-layer displacement angle between layers; For the first Layer and first Predicted values ​​of structural damage indices corresponding to inter-story drift angles. The first in the mainshock wave database The characteristic parameter matrix corresponding to each vibration curve. The first in the aftershock seismic wave database The characteristic parameter matrix corresponding to each vibration curve; and The number of seismic wave vibration curves in the database of seismic wave vibration curves for the mainshock and aftershock, respectively; For bandwidth.

7. The method for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings according to claim 6, characterized in that, The probability of the structural damage index falling within each damage severity range is: ； In the formula, For the first Layer and first The structural damage index corresponding to the inter-layer displacement angle is the probability of damage falling within each damage severity range.

8. A device for pre-earthquake reinforcement and post-earthquake damage area determination in prefabricated buildings, characterized in that, The apparatus is used in the method according to any one of claims 1-7, the apparatus comprising: The seismic wave database establishment module is used to select multiple natural seismic wave vibration curves of mainshocks and aftershocks that match the seismic hazard of the area where the prefabricated building is located. The variational mode decomposition method is used to decompose the natural seismic wave vibration curves of mainshocks and aftershocks into several types of sub-vibration curves. Sub-vibration curves of the same type are merged to form a characteristic parameter matrix of the sub-vibration curves. The kernel density estimation method is used to obtain the probability density function of each characteristic parameter in the characteristic parameter matrix. The number of sub-vibration curves of each type is increased through Monte Carlo simulation, and a large number of artificial seismic wave vibration curves of mainshocks and aftershocks are formed by random sampling. The probability density function of each characteristic parameter of the artificial seismic wave vibration curves is calculated. A seismic wave vibration curve database containing both natural and artificial seismic waves of mainshocks and aftershocks is established, and the generation probability value of the seismic wave vibration curves is calculated. The structural damage index acquisition module is used to input the seismic wave vibration curves of the main shock and aftershocks into the structural dynamic analysis model of the prefabricated building to obtain the structural response results, extract the ratio of the inter-story drift angle value of each floor structure to its code limit as the structural damage index, and determine the range of damage degree. The probability density function acquisition module is used to establish a mapping function relationship between structural damage indicators and the characteristic parameters of seismic wave vibration curves of the main shock and aftershocks using a backpropagation neural network model, and to form the probability density function of structural damage indicators based on the generation probability value of seismic wave vibration curves and the mapping function relationship. The pre-earthquake structural reinforcement module is used to determine the probability of structural damage indicators falling within each damage severity range by using the probability density function of structural damage indicators, and compare it with the severe damage probability threshold to determine whether to reinforce the prefabricated building. The post-earthquake damage area determination module is used to predict the structural damage index value of prefabricated buildings after an earthquake and to determine the areas where prefabricated buildings are damaged, based on the characteristic parameters of the seismic wave vibration curves of the main shock and aftershocks collected on site and through the established mapping function relationship between the structural damage index and the characteristic parameters of the seismic wave vibration curves of the main shock and aftershocks.

9. A device for pre-earthquake reinforcement and post-earthquake damage area determination of prefabricated buildings, characterized in that, Including memory and processor; The memory is used to store computer program code and to transmit the computer program code to the processor; The processor is configured to execute the method as described in any one of claims 1 to 7 according to instructions in the computer program code.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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