86 results about "Earthquake hazard" patented technology

The invention discloses an earthquake disaster loss dynamic assessment method and system based on multi-source disaster situation data, and relates to the technical field of earthquake disaster loss assessment, and the method comprises the following steps: S1, obtaining the multi-source original data of an earthquake disaster, and carrying out the preprocessing, the multi-source original data comprises seismic oscillation parameter data and multi-source disaster data; and S2, based on the preprocessed multi-source data, constructing a coupling driving model of the earthquake influence field and the multi-source disaster situation data, and generating a regional disaster damage thermodynamic map. According to the earthquake disaster loss dynamic evaluation method and system based on the multi-source disaster situation data, the earthquake multi-source disaster situation data is acquired, the coupling driving model of the earthquake influence field and the multi-source disaster situation data is constructed, and the influence of various factors on the earthquake disaster loss is comprehensively considered, so that the limitation that a traditional method depends on a single data source is overcome; the real situation of earthquake disaster loss can be reflected more comprehensively and accurately, and a more reliable basis is provided for rescue decision making.

The invention provides a structure vulnerability analysis method and system based on earthquake magnitude, distance and site conditions, a storage medium and a computer program product. The method comprises the following steps: adopting a preset sampling algorithm to obtain preset earthquake magnitude, distance and site conditions, and acceleration time history samples corresponding to the preset earthquake magnitude, distance and site conditions; based on the acceleration time-history sample, performing nonlinear dynamic time-history analysis on a to-be-evaluated structure by using a finite element analysis method to obtain nonlinear structure seismic response corresponding to the to-be-evaluated structure and the acceleration time-history sample; establishing a change relationship between the statistical parameters of the seismic response of the nonlinear structure and the preset magnitude, distance and site conditions by using a regression fitting method; and constructing a vulnerability curved surface of a to-be-evaluated structure based on the preset earthquake magnitude, distance and site conditions based on the statistical parameters of the seismic response of the nonlinear structure and the change relationship between the preset earthquake magnitude, distance and site conditions. According to the embodiment of the invention, the four elements of a seismic source, a propagation path, a site and a structure can be completely coupled, and the method can be suitable for earthquake disaster risk analysis and rapid evaluation of post-earthquake disasters under various medium-short period structure systems.

The invention discloses a post-disaster recovery large-scale city power grid toughness evaluation method, device and medium, and the method comprises the steps: constructing a large-scale city power grid fault scene and a power transmission line time-varying fault probability model under an earthquake disaster, generating an earthquake-fault combined scene based on Monte Carlo simulation, and selecting k high-risk typical scenes, and then, by taking the maximum weighted load recovery total amount in the system full recovery period as a core optimization target, constructing a power grid post-disaster collaborative recovery model, constructing a multi-dimensional dynamic toughness index system based on the grid robustness, the system self-healing capability and the post-disaster first-aid repair capability, and evaluating the large-scale urban power grid toughness level of power grid post-disaster collaborative recovery. And outputting a good and bad sequence of the optimization strategy. By evaluating the toughness level of the large-scale urban power grid subjected to post-disaster collaborative recovery of the power grid, the performance of the whole recovery process can be comprehensively quantified, the advantages and disadvantages of strategies can be effectively distinguished, and the recovery speed and the recovery degree can be accurately quantified, so that an effective recovery strategy cannot be adopted, and a reliable basis is provided for disaster prevention and emergency of the power grid.

The invention discloses an equipment attitude automatic correction method and device and an optical terminal intensity instrument, the equipment attitude automatic correction method is applied to a preset monitoring terminal comprising a triaxial MEMS accelerometer and a magnetometer, and the method comprises the following steps: collecting acceleration and magnetometer data; calculating acceleration stable three-axis offset; calculating roll and pitch angles and determining a horizontal plane; positioning magnetic north and calculating a magnetic north azimuth angle; calculating a magnetic declination angle and a yaw angle by combining longitude and latitude; generating a rotation matrix and converting a coordinate system; judging angle change and updating the matrix; and completing calibration and attitude stabilization. According to the technical scheme provided by the invention, the monitoring terminal equipment can be ensured to automatically and accurately adjust and stably maintain the attitude after being installed, so that the effective operation of the earthquake monitoring and early warning system is ensured, and the earthquake disaster prevention and flooding earthquake (vibration) monitoring performance is improved.

The invention relates to the technical field of large language models, in particular to a large language model anti-seismic report examination method and device based on domain knowledge enhancement, and provides a large language model anti-seismic report examination method based on domain knowledge enhancement. The method comprises the steps that firstly, a building earthquake-proof professional field large language model is trained, then data preprocessing is conducted on an earthquake-proof examination report, and finally examination is conducted on the basis of the trained building earthquake-proof professional field large language model, so that accumulated earthquake-proof special examination experience and the large language model are fused, and a professional LLM of the vertical field is built; strict examination can be carried out according to standards and files, interference of human errors and subjective factors is effectively avoided, accuracy and reliability of examination results are improved, examination efficiency is improved, a more scientific and accurate basis is provided for expert examination and internal pre-examination, the earthquake resistance and disaster prevention capacity of a construction project is further improved, and the earthquake disaster risk is reduced.

The application discloses a correction method and device of a seismic disaster personnel casualty assessment model and a storage medium, and relates to the technical field of disaster emergency management. By constructing an emergency preparedness index and an emergency response index as a nonlinear attenuation correction factor, the traditional assessment model's defects of relying on expert experience for manual correction and lacking in automation and intelligence are overcome. The coupling correction formula takes the nonlinear attenuation correction factor as the core, and through the multiplication coupling of independent double indexes, the synergistic attenuation effect of emergency preparedness and emergency response is accurately reflected. Through a closed-loop optimization mechanism, highly reliable data support is provided for emergency command. The correction process not only outputs personnel casualty prediction values, but also quantitatively diagnoses regional resilience by generating an emergency preparedness index and an emergency response index, so that emergency plans can be optimized, rescue force deployment can be adjusted or popular science drills can be strengthened, thereby directly serving the active prevention and control and rapid recovery goals of a resilient city.

The invention discloses an earthquake numerical value prediction method based on kernel density and machine learning, and belongs to the technical field of earthquake prediction. The method comprises the steps of performing magnitude standardization and energy association processing on original seismic directory data to form standard seismic directory data, performing completeness processing on the standard seismic directory data to determine a minimum complete magnitude, and performing screening to obtain a complete seismic directory; determining a first bandwidth and a second bandwidth for the complete seismic directory through a nuclear density bandwidth sensitivity test, calculating seismic frequency and energy nuclear density distribution of the target area in combination with a time and magnitude sliding window, and obtaining nuclear density anomaly distribution data by making a difference between the seismic frequency and energy nuclear density distribution and long-term average nuclear density distribution; and inputting the kernel density abnormal distribution data of the target magnitude range under multiple time scales into a pre-trained random forest model, and outputting an occurrence prediction result of a target magnitude earthquake in the target region. According to the method, the spatial accuracy and timeliness of earthquake prediction are improved, and technical support is provided for earthquake disaster risk prevention and control.

This invention discloses an automatic attitude correction method, device, and optical terminal intensity meter for equipment. The automatic attitude correction method is applied to a pre-set monitoring terminal including a triaxial MEMS accelerometer and a magnetometer, and includes the following steps: acquiring acceleration and magnetometer data; calculating acceleration-stabilized triaxial offset; calculating roll and pitch angles and determining the horizontal plane; locating magnetic north and calculating the magnetic north azimuth; calculating magnetic declination and yaw angle using latitude and longitude; generating a rotation matrix and performing coordinate system transformation; judging angle changes and updating the matrix; and completing calibration and attitude stabilization. The technical solution provided by this invention ensures that the monitoring terminal equipment can automatically and accurately adjust and maintain its attitude after installation, thereby guaranteeing the effective operation of the earthquake monitoring and early warning system and improving earthquake disaster prevention and seismic monitoring capabilities.

The invention provides an engineering machinery man-machine cooperative scheduling system and method applied to an earthquake disaster site, and relates to the technical field of man-machine cooperative scheduling, and the system comprises a site environment information obtaining module which is used for obtaining the site environment information of the earthquake disaster site; the rasterization processing module is used for performing area rasterization processing to generate a disaster area grid map; the task execution list generation module is used for performing task allocation evaluation, generating a rescue task execution list and extracting a primary task and a secondary task; the path planning module is used for performing path planning and generating a first rescue path and a second rescue path; and the collaborative rescue scheduling module is used for carrying out collaborative rescue scheduling on earthquake disasters. The technical problems that in the prior art, due to the fact that an effective man-machine cooperative scheduling mechanism is lacked, the collaboration between rescue workers and engineering machinery is poor, rescue resources are wasted, and the rescue efficiency is low are solved.

The utility model discloses an operating table for simulating earthquake disasters, which comprises an earthquake simulation vibration table, a house model is arranged at the top of the earthquake simulation vibration table, a support column is fixedly mounted at the bottom of the earthquake simulation vibration table, the bottom of the support column is connected with a bottom support plate, the house model is composed of a plurality of floors, and the floors are connected with the house model. A bridging plate is fixedly mounted at the bottom of the floor, and the earthquake disaster simulation device relates to the technical field of earthquake disaster simulation, a house model is arranged on an earthquake simulation vibration table, and earthquake waves are simulated and emitted through a simulation earthquake signal generator in the earthquake simulation vibration table, so that the disaster condition of the house model under an earthquake can be simulated; a plurality of dampers are jointly hinged between the floors, so that the different floors have corresponding swing amplitudes and directions during earthquake simulation, and the disaster conditions of the floors with different heights can be simulated.

This invention relates to the field of earthquake disaster emergency monitoring technology, specifically to an intelligent system and method for identifying earthquake surface rupture zones. The system includes modules for heterogeneous data registration, feature extraction and fusion, rupture zone segmentation, active learning, and morphological optimization. It achieves accurate processing of remote sensing data and intelligent identification of rupture zones. The system employs multi-scale feature point matching and adaptive weight registration, improving data registration accuracy by over 30% and overcoming the reliance on human experience in traditional methods. Through multi-modal feature decoupling and attention-guided feature fusion, combined with multi-scale spatial pyramid pooling and deformation-sensitive segmentation, the system effectively identifies rupture zones and assesses prediction uncertainty. The active learning module optimizes training data through Bayesian estimation and a hybrid sampling strategy, while the morphological optimization module utilizes geological constraints and fault topology inference to ultimately output accurate rupture zone distribution and attribute information, improving the intelligence level and efficiency of earthquake disaster emergency monitoring.

The application belongs to the technical field of earthquake disaster scenario construction, and discloses a method for constructing an earthquake disaster scenario based on big data, and the specific steps are as follows: step one: multi-source heterogeneous data acquisition and preprocessing ground structure data acquisition: the spatial distribution characteristics of urban building groups are obtained by using multi-platform remote sensing technology. By integrating multi-source data, a three-dimensional coupling model of underground pipe network and ground building is constructed, the defects of isolated analysis of ground and underground systems in traditional methods are solved, the synchronous simulation of the dynamic correlation process of pipe network rupture and building damage is realized, the additional influence of pipe network failure on building foundation stability and the chain effect of soil erosion caused by leakage fluid are accurately analyzed, and the space-time correlation rules of pipe network rupture events, building fire, fire fighting failure and other types of secondary disasters are established, the building group function paralysis risk and disaster diffusion range under different damage degrees are dynamically predicted, and the disaster evolution path is displayed in real time through a visual platform.

The invention specifically discloses an optimal selection method for a seismic oscillation intensity index of an underground diaphragm wall-subway station system, and relates to the technical field of underground structure anti-seismic performance evaluation. The method comprises the following steps: constructing a diaphragm wall-subway station two-dimensional nonlinear finite element model; obtaining an engineering demand parameter EDP through nonlinear time-history analysis, calculating a candidate seismic oscillation intensity index set IMs, forming an original database of IMs and EDP, and dividing a training set and a test set; generating an optimal candidate IM combination on the training set by using a filtering method, an embedding method and a wrapping method; building a multi-model verification platform, and evaluating the generalization performance of each combination based on a model-independent evaluation standard; comprehensively analyzing and determining the combination of the optimal scalar IM and the optimal vector IM; and verifying the whole optimization method through vulnerability analysis. According to the method, the limitation of a traditional method is broken through, the accuracy of earthquake resistance evaluation is improved, the adaptability of the method is defined, and reliable technical support is provided for earthquake disaster prediction and vulnerability analysis.

The application discloses a kind of multi-scale seismic geology disaster assessment method considering deformation field and ground motion characteristics, comprising the following steps: based on deformation field and seismic ground motion parameter, the risk assessment of regional scale is carried out;With the background of the risk assessment result of regional scale, the dynamic risk score of corridor scale is carried out;Based on the dynamic risk score of corridor scale, the disaster process simulation is carried out, the disaster prediction of site scale is carried out, and the final seismic disaster visualization map and report are generated.The application is coupled with multi-scale dynamic coupling and multi-physical field simulation, combines deformation field, seismic ground motion parameter and numerical simulation technology, through the hierarchical evaluation method of different scales (region, corridor, site), can more comprehensively identify geological disaster risk under the action of earthquake, and adapt to different application scenarios, improve the accuracy and engineering applicability of evaluation.

The invention discloses an earthquake sand liquefaction deformation prediction method based on machine learning, and relates to the technical field of earthquake engineering and machine learning. Missing value processing, abnormal value detection, feature selection and standardization processing are carried out on the multi-source coupling seismic data set to obtain a seismic sand liquefaction deformation data set, a seismic sand liquefaction deformation prediction model is constructed according to the seismic sand liquefaction deformation data set, the root-mean-square error, the mean absolute error and the decision coefficient of the model are calculated, and the seismic sand liquefaction deformation prediction result is obtained. And according to corresponding threshold judgment, carrying out hyper-parameter adjustment on the model through Bayesian optimization or carrying out model packaging through Flask, processing the obtained new seismic sand liquefaction characteristic data, and inputting the processed data into the packaged model to obtain a seismic sand liquefaction deformation prediction result. The method can effectively predict earthquake sand liquefaction deformation, and provides support for earthquake disaster prevention and engineering design.

The invention provides a millimeter wave linear array three-dimensional imaging radar system. The millimeter wave linear array three-dimensional imaging radar system comprises a W-frequency-band transceiving antenna array, a W-frequency-band transceiving channel, a radar signal processor and a clock / local oscillation frequency source, the W-band transmit-receive antenna array is arranged by using an MIMO architecture and is connected to one side, facing a target, of the aerial carrier platform. According to the method, an MIMO architecture is adopted for arraying, and special processing such as period extraction is carried out on a sparse arraying method for the W frequency band. In addition, under the condition of the same number of antenna units in sparse array arrangement, the array size is increased, the system resolution is improved, and meanwhile the cost of a radar system is reduced; a system combining a downward-looking linear array technology and a downward-looking synthetic aperture radar technology is adopted, the resolution in the elevation direction is greatly improved, reliability is enhanced, long-distance, large-range and efficient continuous operation can be achieved, and an effective means is provided for mountain deformation and landslide monitoring, earthquake disaster damage evaluation, agriculture and forestry pest and disease monitoring and the like under atrocious weather conditions.

The application discloses a method and a program product for automatically generating a three-dimensional geological finite element model, which determines a horizontal reference surface based on the maximum height difference of the ground surface, determines a first grid size and a second grid size based on a shear wave velocity, and then comprehensively determines the number of ground surface part grids and divides hexahedral units; according to the first grid size, equally divides a base part into horizontal slices with the same height, and determines the grid size of the horizontal slices in combination with a corrected minimum shear wave velocity; according to the grid size and thickness requirement, combines adjacent horizontal slices to obtain a final rock layer division scheme, and then comprehensively determines the number of rock layer grids and divides the rock layer into hexahedral units; and according to the three-dimensional center coordinates of each hexahedral unit, compares the three-dimensional center coordinates with an original geological model, and sets the stratum category of the hexahedral unit. The application greatly reduces the modeling time and cost of a three-dimensional non-uniform field finite element model of a complex terrain, has high grid quality, and is beneficial to the application of the three-dimensional geological model in the simulation and analysis of earthquake disasters.

The invention provides an earthquake scene simulation system and method and computer equipment, and relates to the technical field of earthquake emergency. The system comprises a natural language interaction layer, a central scheduling module, a multi-source data fusion layer, a professional calculation layer and a visualization and decision support layer. The earthquake scene simulation system receives a natural language instruction based on a natural language interaction layer under the condition of earthquake scene simulation; the central scheduling module is used for sequentially sending trigger instructions to other levels of the system based on the structured instruction; the multi-source data fusion layer is used for querying seismic data and obtaining a unified seismic feature data set based on association integration of a knowledge graph; the professional calculation layer is used for generating a structured decision scheme and determining seismic intensity and seismic loss evaluation results; and the visualization and decision support layer is used for constructing a city-level three-dimensional scene and generating multi-class earthquake thematic maps. The system can improve scientificity and timeliness of earthquake disaster response decisions.

The present application belongs to the field of urban power system operation and maintenance technology, and discloses a city power system earthquake disaster resilience determination method and system based on multi-dimensional data analysis. The present application obtains the earthquake parameters, power facility information, geographic data and social economic data of each county in the city, and constructs a multi-source heterogeneous evaluation database. Based on the seismic motion parameters and the power facility vulnerability function, the damage probability and the expected loss rate of the function of different voltage level substations and transmission lines are calculated, and the residual function matrix of regional power supply is generated. Combined with the real-time power demand model and the power supply capacity recovery curve, the post-earthquake power supply gap rate is calculated, and the influence of the terrain characteristics on the transmission line repair cost is evaluated to quantify the influence of the earthquake on the economic loss, the affected population and the social stability. The present application can effectively improve the resilience and risk management capability of the power system in the earthquake disaster, and provide technical support for the post-earthquake power rapid recovery and resource optimization allocation.

This invention discloses a machine learning-based method for predicting earthquake-induced sand liquefaction deformation, relating to the fields of earthquake engineering and machine learning. The method constructs a multi-source coupled earthquake dataset using engineering survey reports and monitoring data from historical earthquake cases. This dataset undergoes missing value processing, outlier detection, feature selection, and standardization to obtain an earthquake-induced sand liquefaction deformation dataset. Based on this dataset, a prediction model is constructed. The root mean square error, mean absolute error, and coefficient of determination of the model are calculated. Based on corresponding thresholds, the model is adjusted for hyperparameters using Bayesian optimization or encapsulated using Flask. New earthquake-induced sand liquefaction feature data is then processed and input into the encapsulated model to obtain the predicted earthquake-induced sand liquefaction deformation results. This method can effectively predict earthquake-induced sand liquefaction deformation, providing support for earthquake disaster prevention and engineering design.

The invention discloses an electricity-hydrogen coupling system anti-seismic reliability evaluation method and system, and the method comprises the steps: quantifying the fault probability of a power transmission line under a given magnitude and an epicenter position based on an elliptical attenuation model, and constructing a power transmission line fault probability model under an earthquake disaster; in the electricity-hydrogen coupling system, according to the electricity-hydrogen coupling characteristics, an optimal load loss model is established, and the load loss in any given fault state is obtained based on the fault probability model; establishing an uncertainty scene processing model according to the optimal loss load model, generating a related scene, performing scene reduction, and extracting a typical source-load scene set; taking the lost load as a reliability evaluation index, and establishing an anti-seismic reliability evaluation model considering a high-order fault mode; and for scenes in the typical source-load scene set, solving the anti-seismic reliability evaluation model, and calculating a reliability index in a given fault state. According to the method, the calculation efficiency of reliability evaluation of the electricity-hydrogen coupling system under the earthquake disaster can be remarkably improved.

A nuclear power plant post-earthquake long-term safety management method belongs to the nuclear power field. The method comprises the following steps: establishing an earthquake response action matrix, wherein elements in the matrix comprise two dimensions of an actually measured damage level and an actually measured level relative to a design level; based on earthquake PSA analysis, performing earthquake response action grade assignment on each element, and providing a corresponding long-term response measure list; after an earthquake occurs, the earthquake consequences are matched with elements in the earthquake response action matrix, and corresponding response measures are executed. The method can effectively improve the response efficiency of the nuclear power plant to the earthquake disaster, optimizes the decision reasonability, and improves the safety and economy of the nuclear power plant to the earthquake disaster.

The invention discloses a multi-disaster-oriented environment coupling type power grid vulnerability assessment method and system, and relates to the technical field of fault assessment. Firstly, a power transmission line is decomposed into an electric tower node and a virtual node, so that the linear damage calculation complexity is reduced, power grid second-level time sequence simulation is supported, and the power grid vulnerability assessment efficiency is improved; secondly, by constructing a multi-disaster unified coupling mechanism: constructing a geographic matrix, an environment matrix and a meteorological matrix, driving a plurality of disaster damage models, and realizing joint quantification of a disaster chain physical process; and finally, by taking the topology power supply availability rate and the cascade failure fault condition as damage measurement indexes, power grid vulnerability evaluation is performed in an earthquake disaster scene and a storm disaster scene, and the problem of fault underestimation caused by neglecting power redistribution in a traditional model is solved.

The invention relates to the field of emergency management and material allocation, and discloses a post-earthquake emergency material demand prediction method based on CBR algorithm feature weight allocation, and the method comprises the following steps: collecting earthquake disaster data, extracting key feature attributes, and constructing a case library; feature weights in the case library are optimized by adopting a game theory-SAGA-AHP algorithm, and subjective weights and objective weights are integrated to improve the scientificity of weight distribution; utilizing the optimized case-based reasoning model to predict the number of affected population after the earthquake; in combination with a safety inventory theory, establishing a classification demand model of diet, medical and cold-resistant materials, and dynamically calculating the demand quantity of different materials; and outputting a prediction result in a visual form or a visual form, and supporting dynamic updating. The method has the advantages of high prediction precision, high dynamic adaptability and wide application range.

The invention relates to a refined earthquake buried population estimation method and a medium, and relates to the technical field of population data calculation. Firstly, function types of buildings in a target area are identified based on remote sensing data, so that population weights of the buildings of all the function types are obtained, and after an earthquake disaster occurs, rescue force can be accurately positioned to each high-risk building instead of a fuzzy area. Secondly, for each building, based on the function type, the building area and the population weight of the building, the building scale population number is calculated, and the collapse rate and the person in-room rate when an earthquake occurs are obtained, so that the estimated number of buried people can be dynamically obtained; therefore, more refined buried population spatial distribution can be obtained by integrating various complex nonlinear potential influence factor relationships, and a more scientific and effective decision basis is provided for earthquake emergency response.

The application relates to a high-speed rail earthquake emergency disposal equipment linkage control method, device, equipment and medium. The method comprises the following steps: firstly, collecting multi-source vibration and geological displacement information of key nodes along the line, removing interference noise through a filtering algorithm, and generating a purified earthquake precursor signal data set. Then, a feature vector is extracted from the data set, the preliminary intensity is quantitatively calculated, and after the threshold value, a warning signal containing a time stamp, a warning level and the like is generated through multi-dimensional verification. Then, based on the warning signal feature parameters and the geological data, the earthquake wave propagation mode is analyzed by using deep learning, the track displacement and crack detection results are integrated, and a section damage level sequence sorted by mileage is generated. Finally, a priority list is constructed according to the sequence, train shutdown scheduling and rescue resource allocation are guided, and an optimized emergency disposal scheme is obtained. The method realizes efficient response of the whole chain from earthquake precursor monitoring to emergency disposal, and improves the safety guarantee capability and emergency disposal efficiency of high-speed rail in response to earthquake disasters.

The invention relates to the technical field of earthquake disaster assessment, and particularly discloses a multi-precision earthquake disaster rapid assessment method, which comprises the following steps: step 1, processing building basic data, and dividing the precision of the collected building data from high to low; step 2, calculating and generating seismic intensity distribution through a seismic intensity attenuation formula on the basis of three-element information of seismic time, magnitude and epicenter position of the earthquake; 3, selecting an evaluation precision strategy, wherein the evaluation precision strategy comprises an optimal precision strategy and a manual specified precision strategy; and step 4, based on the processed building basic data, calculating the obtained seismic intensity distribution and the screened building data participating in the calculation. According to the method, the building basic data is graded according to the precision, the optimal precision strategy and the manual specified precision strategy are supported, the method can adapt to the basic data precision of different areas, the maximum benefit of the data precision is fully played, and the problem that the evaluation precision of an existing method is single is solved.

The application discloses a kind of based on spatial data mining and geological constraint seismic activity fault model construction method, system, equipment and medium.The method is first arranged and analyzed to seismic data, extracts minimum complete subdirectory;Using improved mean shift algorithm for spatial clustering, identify each active fault corresponding small earthquake cluster;Subsequently, each fault cluster is three-dimensional slice, and least square method fitting is generated fault interpretation line;With interpretation line as foundation, initial seismic activity fault three-dimensional model is constructed, and is optimized by multi-source geological constraint, and active fault three-dimensional fine model is obtained;Finally, the model is integrated with digital earth spatial registration.This application can realize the whole process automation and quantization from seismic data analysis to active fault three-dimensional fine model construction and application, improve the objectivity, efficiency, precision and reliability of model construction, provide important technical support for seismic disaster risk assessment, active fault detection.

The application discloses a bridge rescue training facility and method, and belongs to the technical field of bridge rescue training facilities.The bridge rescue training facility has a bridge area and an under-bridge area, and a plurality of engineering elevators and a plurality of staircases are arranged on the sides of the bridge area, the engineering elevators are used for assisting in carrying instruments to the bridge surface, the bridge rescue training facility is provided with structural stress monitoring sensors at structural stress points, the structural stress monitoring sensors are used for monitoring the structural stability in real time, and an automatic alarm is given when a structural member is damaged or reaches a maximum set stress value; the bridge area is provided with a bridge intact section, a bridge damaged section and a traffic accident occurrence section; the under-bridge area is provided with a dangerous chemical tank vehicle accident occurrence section; the bridge damaged section is provided with bridge damage points and a bridge fracture zone; the bridge damaged section simulates the bridge superstructure damage, the bridge substructure damage, the foundation damage and the bridge fracture scene after an earthquake disaster, and the bridge damaged section is used for carrying out the training of rapidly rescuing and repairing a damaged bridge; and the bridge damage points are located at the bridge surface plate, the beam plate, the anti-falling baffle, the support seat, the pier column and the foundation part.

This invention provides a method and system for collaborative scheduling of unmanned vehicles and drones on earthquake-damaged roads, belonging to the field of earthquake disaster relief scheduling technology. It includes constructing an unmanned vehicle road network and a drone flight path network; acquiring road condition changes, demand data, and vehicle status based on the unmanned vehicle road network and drone flight path network; constructing a comprehensive objective function with the goals of minimizing total rescue time, ensuring fair allocation of relief supplies, and maximizing the efficiency of casualty transfer; solving the comprehensive objective function based on road condition changes, demand data, and vehicle status to obtain a post-earthquake relief supply transportation and casualty transfer scheme under unmanned vehicle-drone collaboration. This shortens the rescue and road clearing time, enables multi-objective collaborative operation of unmanned vehicles and drones, and improves the efficiency of material delivery during the golden rescue period.