129 results about "Ground motion" patented technology

The invention discloses a transmission tower vulnerability analysis method and system based on seismic simulation, and belongs to the technical field of electric power facility disaster prevention, and the method comprises the steps: correcting bedrock seismic oscillation parameters based on equivalent shear wave velocity, and generating a high-precision earth surface PGA distribution diagram; automatically positioning a key node layer through eigenvalue decomposition, reducing the order of the three-dimensional model of the power transmission tower into a two-dimensional series multi-degree-of-freedom model, and outputting a layer mass vector, a condensation stiffness matrix and rod piece bending stiffness; performing time-history analysis by using the corrected PGA-driven reduced-order model to generate an earthquake damage probability; the multi-source remote sensing data and the PGA are fused, the landslide space probability is output through a deep learning model, and the impact strength and the landslide kinetic energy are calculated to judge the landslide damage probability; and based on the dual-threshold condition triggering probability union set, calculating a comprehensive damage probability, and generating a three-dimensional vulnerable curved surface. According to the method, the problems of high missing report rate and low calculation efficiency of single disaster assessment are solved, and minute-level accurate early warning of the composite disaster risk of the power transmission tower is realized.

The invention discloses a seismic oscillation generation method based on a DFEM model, and the method comprises the steps: obtaining multi-source data in a target simulation region, and obtaining fusion stratum wave velocity structure data; determining the minimum grid size of the DFEM model according to the fused stratum wave velocity structure data and a preset simulation frequency upper limit, and dividing grids and determining nodes according to the minimum grid size; constructing a seismic propagation related physical constraint set; the physical constraint is embedded into a primary training process of a DFEM model, a Green function of a fracture surface sub-source in a target simulation area is obtained, convolution operation is carried out on the Green function, expanded seismic oscillation samples under different scenes are generated, and the expanded seismic oscillation samples and full-physical simulation seismic oscillation samples form a data set; performing secondary training on the DFEM model based on the data set to obtain a seismic motion prediction model; and generating diversified vibration samples based on the seismic motion prediction model. The problems that traditional pure physical simulation seismic oscillation simulation is high in cost, long in time and the like are solved.

The invention relates to the technical field of seismic data analysis, in particular to a seismic station ground motion noise quantification method and related equipment based on a GPU (Graphics Processing Unit), and the method comprises the steps: firstly obtaining waveform record data of a target seismic station in a set time period; performing sliding window segmentation processing on the waveform recording data in parallel by utilizing a GPU (Graphics Processing Unit) to obtain a plurality of waveform recording sub-segments; preprocessing the data of the plurality of waveform recording sub-segments in parallel through a GPU (Graphics Processing Unit); finally, the power spectrum density of the ground motion noise in the preprocessed sub-segments is calculated in parallel through the GPU; and carrying out parallel statistics on a power spectrum density probability density function result based on the power spectrum density by utilizing a GPU (Graphics Processing Unit) to complete the quantitative calculation of the earth motion noise. According to the method, the data processing efficiency is improved based on the parallel computing capability of the GPU, hardware computing resources are fully called, and the earthquake noise quantification of the seismic station record can be efficiently realized. The whole method is based on a CUDA programming model and a C language, cross-platform transplantation is easy, and the large-scale seismic network monitoring capability can be effectively improved.

The invention belongs to the technical field of underground engineering and computer-aided engineering analysis, and particularly relates to an anti-seismic safety collaborative analysis method for multi-modal data of proximity tunnel engineering. By integrating engineering geology, structural design, construction monitoring and multi-level seismic oscillation data, a three-dimensional numerical model fusing geology and structural information is constructed. Firstly, refined simulation of the whole construction process and the operation static load is carried out, and a reference mechanical state is obtained; carrying out multi-task condition earthquake dynamic time history analysis on the basis, dynamically capturing dynamic response of surrounding rock and a structure, carrying out collaborative interpretation on static and dynamic analysis results, emphatically analyzing spatio-temporal evolution and connectivity risks of a tunnel anchor and an adjacent highway tunnel surrounding rock plastic zone, and extracting a plurality of quantitative collaborative indexes; and an interactive analysis report integrating a three-dimensional visual scene, a multi-dimensional comparison chart and a rule base-based safety interpretation conclusion is automatically generated, and systematic decision support is provided for seismic design, construction control and safety evaluation of proximity projects.

The invention discloses an intelligent anti-seismic structure optimization design method and system for a high-rise building, and relates to the technical field of anti-seismic design of the high-rise building. A working condition database considering multidirectional seismic oscillation and soil-structure interaction is established in combination with seismic oscillation time history and site investigation parameters; constructing a structure model on the BIM platform, and importing frequency characteristics and load to generate a preliminary design; an inter-story displacement angle, a story acceleration, a plastic rotation angle and an energy dissipation ratio index are set in the model, an anti-seismic performance comprehensive function is constructed, constraints are set according to a standard limit value, the structure model is converted into an optimizable problem, and optimal design is achieved by iteratively calling a working condition database and automatically correcting key component parameters and damping arrangement. According to the method disclosed by the invention, the structural optimization design of the high-rise building under the multidirectional earthquake action is realized by establishing an earthquake working condition database and parameterizing structural modeling and performance function constraint.

The invention provides a physical information long-short-term memory network site seismic response prediction method based on kinematics derivative constraint and data folding. The method comprises the following steps: collecting and preprocessing bedrock and ground surface seismic oscillation data; displacement, speed and acceleration supervision labels are constructed through surface acceleration integration; constructing a long-short-term memory network containing a data folding and unfolding module; physical constraint loss is constructed by utilizing kinematics derivative relations between displacement and speed and between speed and acceleration, and a network is trained by combining an adaptive weight strategy; and outputting earth surface displacement, speed and acceleration time history by adopting the trained network. According to the method, under the condition that constitutive parameters of a soil layer are not explicitly given, physical consistency constraint can be applied to the field seismic response prediction process, the long-time program train training burden is reduced through sequence folding processing, and the method is suitable for field seismic response prediction.

The invention discloses a method for generating a post-earthquake seismic oscillation parameter field in a peripheral area of a railway by considering a topographic site, which can consider the influence of topographic features on seismic oscillation, improve the estimation precision of the post-earthquake seismic oscillation parameter field and provide technical support for post-earthquake inspection and driving order recovery. Meanwhile, railway workers can carry out targeted field inspection according to the mileage range, the inspection range is reduced, the emergency disposal time is shortened, the road network post-earthquake emergency disposal capacity is improved, the post-earthquake loss is reduced, and the railway transportation safety is guaranteed; moreover, the calculation work can be completed before the earthquake occurs, the calculation amount is relatively small after the earthquake occurs, and the actual demand of quick response after the earthquake of the railway can be met; besides, earthquake rapid report and station observation data from an earthquake station network center are comprehensively applied, information of a railway self-built station is fused, information utilization is comprehensive, and meanwhile, earthquake oscillation around the railway is better reflected.

The invention discloses a physical simulation method and device for seismic response certainty of an urban underground rail transit network, and the method comprises the steps: constructing a mixed seismic source model based on the active fault parameters and kinematic parameters of a target region, the seismic source model integrates a low-wavenumber deterministic slip component and a high-wavenumber random slip component on a fault fracture surface to generate a broadband seismic wave field source reflecting the physical process of a seismic source; the constructed seismic source model is used as input, a regional crustal velocity structure model is combined, propagation of seismic waves in a layered geological medium is simulated through a frequency-wavenumber domain method, and a seismic oscillation space-time field is obtained through calculation; and establishing a finite element model of the urban underground rail transit network, applying the seismic oscillation time-space field as non-consistent seismic oscillation input to the finite element model, and solving through dynamic time-history analysis to obtain the dynamic response of the whole underground rail transit network in the earthquake process. According to the invention, a complete physical chain from seismic source fracture to structural response can be reproduced.

A method for seismic fragility analysis of a shield tunnel considering surface surcharge effects includes the steps of: determining mechanical property parameters of tunnel materials and physical-mechanical parameters of soil layers; investigating case studies of surface surcharge to define surface surcharge scenarios; selecting seismic waves and performing one-dimensional equivalent linear site response analysis on soil conditions; establishing a dynamic finite element numerical model of a soil-tunnel system considering surface surcharge; defining ground motion intensity measures (IM), tunnel damage measures (DM), and damage states (DS); and establishing probabilistic seismic demand models for the tunnel under various surface surcharge effects. Based on key parameters, seismic fragility curves for tunnel structures under surface surcharge effects are established. Through a nonlinear incremental dynamic analysis method, this method establishes the finite element numerical model of the soil-tunnel system, allowing for quantitative assessment of tunnel seismic fragility and seismic performance under various surface surcharge effects.

The invention discloses a multi-source wave velocity structure fusion method, which comprises the following steps: acquiring original data sources including a large-range wave velocity structure data set covering the range of an engineering structure, an earth surface geological lithology distribution diagram and engineering site drilling exploration information; for the earth surface geological lithology distribution map, classifying rocks through image recognition, and setting a wave velocity based on rock categories; for the remaining original data sources, outliers are removed through data cleaning and standardization processing so as to determine corresponding wave velocities; according to the wave velocity determined based on engineering site drilling exploration information, a transition area is additionally arranged around a drilling point to convert the one-dimensional wave velocity into the three-dimensional wave velocity; performing data enhancement on the three-dimensional wave velocity corresponding to each original data source through an interpolation method; and carrying out weight fusion on various wave velocities after data enhancement to obtain a fused wave velocity structure. According to the method, the modeling precision and efficiency of the wave velocity structure are improved, so that the wave velocity structure can be matched with broadband seismic oscillation numerical simulation of the required calculation frequency.

The utility model discloses an electrostatic induction pendulum for earthquake monitoring and early warning based on electrostatic induction. The device comprises a pendulum and an electrostatic induction sensor, and tiny potential changes can be detected in the swinging process. As a core component, the electrostatic induction sensor consists of the following key parts: a weight module, a connecting layer I, an electrode layer, a connecting layer II and an electrostatic interaction layer. Wherein the weight module provides necessary mass so as to ensure the dynamic characteristics of the pendulum; the first connecting layer is used for fixing the connection between the weight module and the electrode layer; the electrode layer is responsible for detecting electrostatic induction signals generated by pendulum motion and converting the signals into measurable potential change; the second connecting layer is used for fixing the electrode layer and the electrostatic interaction layer; the material of the electrostatic interaction layer carries charges, and the electrostatic induction signal of the electrode layer is enhanced in the earthquake monitoring and early warning process. Through the design, the device can realize high-sensitivity monitoring of earthquake precursor, and can capture fine ground movement caused by earthquake waves. In combination with a data acquisition system and a machine learning algorithm, the device can analyze the signals in real time and automatically send early warning information to related departments and individuals when an abnormal vibration mode is detected, so that precious time is won for taking preventive measures.

The application discloses a main aftershock induced slope slip prediction method based on multi-parameter regression, aims to utilize a large amount of ground motion data and a Newmark rigid block method to construct an explicit expression for predicting permanent slip displacement of a slope under the action of a main aftershock from peak ground acceleration, peak velocity and slope yield acceleration. The method comprises the following steps: step 1, selecting ground motion data from a ground motion database NGA-West2 and calculating each ground motion parameter and the slope slip displacement under different slope yield accelerations; step 2, identifying optimal ground motion parameters according to effectiveness criteria and applicability criteria; step 3, obtaining a plurality of prediction models through optimal parameters and a multi-parameter nonlinear regression analysis method and then testing the prediction performance to determine a final slip prediction model; and step 4, predicting the permanent slip displacement of the slope under a given seismic scenario and slope condition. Based on the method, the application develops and discloses a main aftershock induced slope slip prediction model with good accuracy, universality and practicability, and has certain guiding significance for slope stability evaluation and seismic design under the action of a main aftershock.

The present application relates to a kind of assembled frame structure earthquake response prediction algorithm based on LSTM algorithm, by establishing full-scale structure model and using ABAQUS to carry out nonlinear time-history analysis, obtain ground motion and inter-story displacement response data, construct structure earthquake response database.Based on the numerical simulation result, establish deep learning architecture, by the sensitivity study of window length, hidden layer and training sample size, use R and RMSE such as index to evaluate model performance, and select the model with minimum validation loss as the final prediction model.In the prediction phase, input any ground motion record can quickly generate complete inter-story displacement time-history through recursive slicing and step-by-step updating mechanism, so as to realize the efficient estimation of aluminum alloy foam concrete structure earthquake response.The present application can replace the high-cost iterative calculation of traditional finite element analysis, and provide fast and reliable decision support for regional seismic risk assessment, structure safety determination and aluminum alloy foam concrete structure seismic design.

The application provides a visual device for simulating rainfall scouring of a slope under earthquake conditions, comprising: a vibration table for providing a vibration signal to simulate ground motion characteristics under earthquake action; an adjusting mechanism placed on the vibration table for providing different slope angles; a model box placed on the adjusting mechanism, the model box comprising an open-top box body with transparent side walls, which carries a slope model; a rainfall simulation assembly arranged at the open end of the top of the model box for simulating a natural rainfall environment; and a data acquisition and processing unit for collecting real-time change information inside and outside the slope model during the experiment, and analyzing response rules and instability evolution processes of the slope model under rainfall and / or earthquake action according to the collected data. The device has high structural integration, perfect functions, is suitable for slope response simulation under the coupling action of earthquake and rainfall, and has good visual effect and application promotion value.

The application relates to the technical field of earthquake prediction, and particularly provides a lightweight on-site ground motion parameter prediction model construction method and an earthquake early warning system. The lightweight on-site ground motion parameter prediction model construction method comprises the following steps: training an initial prediction model according to acceleration waveform data when a P wave of an earthquake arrives, to obtain a pre-training prediction model; taking the pre-training prediction model as a teacher model, and transferring the knowledge of the teacher model to a student model through distillation; and constructing a lightweight on-site ground motion parameter prediction model based on the student model. The method can reduce the complexity and calculation amount of the student model by transferring the knowledge in the pre-training prediction model to the student model through distillation; and the lightweight on-site ground motion parameter prediction model can be constructed based on the student model, so that the demand of the model for hardware resources can be reduced while the on-site ground motion parameter prediction efficiency is ensured, and the deployable scene of the model is expanded.

The invention discloses a method and system for calculating a seismic oscillation amplification coefficient of a river valley field under SV wave incidence, and belongs to the technical field of rock-soil seismic engineering, and the method comprises the steps: building a model; analyzing an infinitesimal body; establishing a free field; establishing a scattering field; substituting boundary conditions; solving a matrix equation; and calculating an amplification coefficient. According to the method, a wave field caused by an irregular terrain of the earth surface is constructed by an interval decomposition strategy taking a terrain cuspidal point as a demarcation point, a method for calculating the seismic oscillation amplification coefficient of the river valley field under SV wave incidence is provided, and the influence of factors such as river valley geometric parameters, material parameters, the frequency and incident angle of incident waves and the like on the river valley seismic oscillation amplification coefficient is revealed; a theoretical basis is provided for aseismic design of major projects of river valleys; the calculation method is a semi-analytical method, reveals the physical nature of irregular terrains on seismic wave propagation and scattering, improves the calculation precision and efficiency, and can be used as a reference for verification of a numerical method.

The invention provides a landslide dynamic response judgment method and device based on a centrifugal machine vibration table and a medium, and the method comprises the steps: obtaining the landslide position and other information of a target landslide, building a profile generalization physical model of the target landslide in combination with a preset similarity ratio, setting at least two groups of measurement points with different coordinates in the profile generalization physical model, and determining the landslide dynamic response of the target landslide; and measuring point acceleration sensors in one-to-one correspondence with the measuring points are arranged. According to historical earthquake acceleration time history information, a physical model is generalized by using a vibration section of a centrifuge vibration table, and measurement point model domain acceleration response data is acquired through a measurement point acceleration sensor. And preprocessing the measurement point model domain acceleration response data according to a preset similarity ratio to obtain measurement point prototype domain acceleration response data, and extracting target seismic oscillation characteristic parameters from the measurement point prototype domain acceleration response data. The landslide dynamic response discrimination method based on the centrifuge vibration table provided by the invention can improve the accuracy of quantitatively discriminating the landslide dynamic response.

This invention relates to the field of numerical simulation and computational technology for seismic wave propagation, and discloses a method and apparatus for generating seismic ground motions based on target spectra and Green's functions. It aims to address the difficulty in achieving a balance between physical consistency, computational efficiency, and spectral compatibility in existing methods. The scheme mainly includes: preprocessing environmental noise records and extracting empirical Green's functions through unsupervised clustering; constructing a spatially continuous propagation tensor by performing depth correction and gradient interpolation based on surface wave eigenfunctions; discretizing the kinematically finite fault model into sub-source units and generating long-period seismic ground motions including path effects using propagation tensor convolution; optimizing source parameters through Bayesian inversion using the GMPE target spectrum as a constraint; and finally generating high-frequency components and fusing them with the long-period waveform to obtain a broadband seismic ground motion time history. This invention achieves a unification of physical propagation mechanisms and statistical spectral constraints, significantly improving computational efficiency while ensuring spectral compatibility, and is particularly suitable for basin areas.

The invention discloses a rigid-body-like medical equipment earthquake vulnerability evaluation method considering multi-motion-state coupling, and aims to solve the problem that the earthquake vulnerability of wheeled medical equipment under the influence of factors such as strong shock, rolling, sliding-swinging coupling and non-uniform friction is difficult to accurately evaluate only depending on classic rigid body sliding or overturning criteria. Medical equipment is regarded as a rigid body, the motion state of the rigid body at each moment in the earthquake process is determined according to geometric parameters and supporting information of the rigid body, the gravitational acceleration and the earthquake oscillation time history, and the motion states comprise fixed foot support sliding, trundle rolling, swinging and sliding-swinging coupling. The maximum translation displacement and the maximum rotation angle of the rigid body are obtained based on the motion state, the damage state of the rigid body is judged according to the maximum translation displacement and the maximum rotation angle, nonlinear incremental dynamic analysis is conducted on the rigid body, an earthquake vulnerability function is obtained, the larger the median value of the earthquake vulnerability function is, the lower the earthquake vulnerability of the rigid body is, and otherwise, the higher the earthquake vulnerability of the rigid body is. The invention belongs to the field of shock resistance of medical instruments.

The invention discloses a bridge seismic response prediction method based on Bayesian optimization and an SCINet-Attention-LSTM hybrid network, and relates to the field of civil engineering, and the method comprises the steps: inputting seismic oscillation data into a trained SCINet-Attention-LSTM hybrid prediction model, and obtaining a seismic response prediction result of a target bridge structure; an SCINet feature extraction module in the hybrid prediction model is used for performing feature extraction on input data through an iterative down-sampling-convolution-interaction mechanism, and outputting a feature vector sequence containing original seismic oscillation sequence time sequence information; the Attention module is used for performing dot product or weighting processing on the feature vector sequence; and the LSTM module is used for carrying out time sequence modeling on the feature vector sequence processed by the Attention module and outputting an earthquake response prediction result of the target bridge structure.

The invention discloses a rapid evaluation method for traffic safety of a railway bridge after an earthquake based on a genetic algorithm. The method comprises the following steps: creating a track-bridge nonlinear finite element model; simulating high-frequency acceleration seismic oscillation, simulating low-frequency velocity pulses, converting high-frequency acceleration into high-frequency velocity, and performing superposition of high-frequency and low-frequency components to generate a seismic oscillation sample; performing bridge response calculation on the track-bridge nonlinear finite element models under different earthquake magnitudes, and extracting post-earthquake track residual deformation; taking post-earthquake track residual deformation as compensation of an initial irregularity spectrum, and adding the initial irregularity spectrum into a trigonometric series superposition method to obtain a post-earthquake track irregularity spectrum; calculating to obtain a post-earthquake driving condition, and storing the earthquake magnitude and the corresponding driving state; and building a post-earthquake traffic safety rapid evaluation platform based on a genetic algorithm, and evaluating whether the railway bridge can safely run after the earthquake. The technical effect of the invention is that technical support is provided for rapidly evaluating the traffic safety of the railway bridge after the earthquake and stopping inspection.

The invention belongs to the technical field of seismic oscillation, and particularly relates to a local terrain seismic oscillation simulation method considering site soil parameter randomness. The method comprises the following steps: S1, based on a random field theory and site soil exploration data, obtaining site soil parameters with soil layer variability; s2, based on the random field soil parameters, solving local terrain seismic oscillation by using an IBEM to obtain seismic response data of a single sample; s3, establishing a CNN model for solving a local terrain earthquake response; random field soil parameters are set as CNN input parameters, an earth surface point acceleration peak value of each group of independent samples is solved by using an IBEM, the earth surface point acceleration peak value is set as CNN output parameters, a data set is constructed based on the input parameters and the output parameters of each independent sample, and model training is carried out; and S4, based on the trained CNN model, obtaining local terrain ground motion considering site soil parameter randomness by using MCS. The method provided by the invention has good accuracy and applicability.

The application discloses a kind of intelligent control excavator laser radar identification device, belong to excavator laser radar technical field, this intelligent control excavator laser radar identification device, including control excavator ground movement's walking component, walking component is equipped with mechanical arm, mechanical arm is rotatably installed with excavator, walking component is installed with the driver's cabin of human control mechanical movement, the top surface of driver's cabin is fixed with support frame, two groups of hollow tubes are vertically fixed on support frame, telescopic connection is equipped with lifting rod in hollow tube, the top of lifting rod is rotatably connected with steering seat, the upper surface of steering seat is fixed with disc base, disc base is fixed with the laser radar detection device for providing environmental data for intelligent control, and laser radar detection device upper end surface is rotatably provided with camera for further sensing, monitoring surrounding environment;The laser radar identification device can adjust the detection and identification height and angle in real time, avoid detection and identification blind area, improve the precision of excavator intelligent control.

The invention relates to the technical field of rail bridge engineering, in particular to a high-speed railway bridge seismic actuation irregularity detection method, medium and equipment, and the method comprises the steps: obtaining seismic oscillation parameters of a to-be-detected object; and inputting the seismic oscillation parameters of the to-be-measured object into the seismic actuation irregularity prediction model, and outputting the seismic actuation irregularity to obtain the seismic-induced orbit movement irregularity of the to-be-measured object. The shock actuation irregularity of the high-speed railway bridge can be obtained in a short time without relying on a large number of experiments; the seismic-induced orbit dynamic irregularity under the corresponding pulse seismic oscillation can be obtained only by obtaining the seismic oscillation parameters, the basic natural vibration frequency ratio and dynamic irregularity mapping function and the seismic-induced dynamic irregularity amplitude function under the pulse seismic oscillation, so that a large amount of finite element calculation time is saved; and the method has important reference value for damage detection of a track-bridge system and guidance of post-earthquake driving.

The application provides a time-varying coherence estimation method of ground motion based on Bayesian collaborative optimization. The method constructs double target constraints covering physical consistency and spectrum graph distinguishability through generalized S transform and time-frequency bidirectional exponential smoothing method, cooperatively determines the optimal combination of generalized S transform kernel parameters and exponential smoothing operator by using a Bayesian optimization algorithm, and outputs an optimal parameter set and a corresponding time-varying coherence spectrum graph. Therefore, more real data reflecting the spatial variation characteristics of ground motion can be obtained, and the design requirements under the limit adverse state can be met.

This invention relates to a seismic performance optimization and evaluation system for long-span bridges based on digital twins, belonging to the fields of computer science and bridge engineering. The optimization and evaluation system includes a data acquisition and preprocessing module, a model update module, and a performance evaluation and optimization module. The optimization and evaluation method includes identifying the structural modes and frequencies to obtain the bridge's mode shapes and natural frequencies, and establishing a digital twin model of the target bridge. Based on a multi-objective optimization design function, supercomputing-driven optimization of vibration reduction device parameters is performed, outputting the optimal parameter combination to control the bridge's graded response under earthquakes. The artificial wave generated based on the bridge's design response spectrum can fully consider the dynamic characteristics of long-span cable-stayed bridges and the seismic motion characteristics of the design site. Simultaneously, the seismic optimization design process only involves the time history analysis of a single ground motion, significantly reducing the computational load of the optimization design and better considering the comprehensive influence of various nonlinear factors on the bridge's seismic response, thus significantly simplifying the complexity of seismic optimization for long-span bridges.

The invention relates to the technical field of seismic engineering and artificial intelligence, in particular to a seismic oscillation selection method and system based on spectral feature extraction and clustering, and discloses a seismic oscillation record selection method based on principal component analysis dimensionality reduction and K-means clustering. The method comprises the following steps: firstly, acquiring candidate records from a database according to set seismic parameters of a site, and performing pulse and non-pulse label division; amplitude modulation and normalization preprocessing are carried out on the response spectrum data, and a high-dimensional acceleration response spectrum is compressed into low-dimensional potential features through PCA dimension reduction; and finally, on the basis of a dimension reduction result, performing grouping by applying a K-means clustering method, and performing record selection and response spectrum comparison. The system comprises a record reading and processing module, a feature extraction module, a feature clustering module, a verification module and an output module, velocity pulse and non-pulse classification is carried out before an alternative record data set is constructed, and a near fault velocity pulse effect is considered at the beginning of record selection.

The embodiment of the invention discloses a non-stationary seismic oscillation generation method and device, electronic equipment and a storage medium, and relates to the technical field of seismic engineering, and the method comprises the steps: 1, generating a seed seismic oscillation time history based on a power spectrum model; 2, performing wavelet packet decomposition on the seed seismic oscillation time history to obtain a group of sub-signal components in a time-frequency domain, and identifying a strong seismic time period; 3, constructing a time-varying function, and correcting sub-signal components in a strong earthquake time period; 4, reconstructing and generating an intermediate seismic oscillation time history according to the adjusted sub-signal components, and judging whether the intermediate seismic oscillation time history meets a preset precision requirement or not; if not, taking the intermediate seismic oscillation time history as a new seed seismic oscillation time history, and repeating the steps until a preset precision requirement is met; through time domain localization correction, the contradiction between response spectrum matching and intensity non-stationary maintenance is solved, seismic oscillation which accords with a target response spectrum and has real non-stationary characteristics is generated, and the reliability of anti-seismic analysis is improved.

The invention discloses a near-fault multi-point multi-dimensional fully non-stationary seismic oscillation dimension reduction simulation method and system, and belongs to the technical field of seismic engineering and disaster prevention and reduction. The method provided by the invention comprises the following steps: firstly, screening near-fault strong earthquake records containing horizontal and vertical velocity pulses, fitting the extracted pulses by using a Gabor wavelet model, identifying low-frequency key parameters and establishing probability distribution; a high-frequency component is simulated by a 1D-nV non-stationary random vector process, and dimensionality reduction is carried out in combination with a random orthogonal function; and generating a representative point set through number theory point selection and equal probability inverse transformation, substituting the representative point set into the model to generate high and low frequency speed time histories, and superposing the high and low frequency speed time histories to obtain a seismic oscillation sample with complete probability information. The system comprises a data screening module, a parameter identification module and the like. According to the method, samples meeting the precision are generated by using extremely few random variables, the simulation efficiency is improved, and the method can be combined with the probability density evolution theory for engineering structure dynamic response and anti-seismic reliability analysis.

The application discloses a kind of hierarchical yielding damper vibration reduction structure design methods based on multistage shock absorption target, including in finite element software, establishing uncontrolled vibration reduction structure model, and carrying out time history analysis, obtains the maximum inter-story drift angle and maximum floor acceleration of original structure;Determine the setting position of damper and structure optimization expectation, wherein, damper uses single yield point metal damper;The preset parameter of optimization algorithm is set, including population size N and maximum iteration number T max ;Small earthquake, medium earthquake, large earthquake and super large earthquake are independently used in optimization algorithm respectively under four load conditions The parameter of damper is optimized and calculated;Obtain the optimal parameters of damper under each working condition;Construct the skeleton curve of four-order hierarchical yielding damper;Construct the hysteretic model of hierarchical yielding damper, and bring the hysteretic model into the nonlinear time history analysis of vibration reduction structure.The application solves the problem that traditional damper is difficult to adapt to multi-level, especially super large seismic ground motion demand.