Electric power facility earthquake disaster risk assessment method and system based on earthquake deformation field

Abstract

The invention provides an electric power facility earthquake disaster risk assessment method and system based on an earthquake deformation field, and the method comprises the steps: carrying out the complementation of seismic source fault geometric parameters through seismic parameter data obtained based on an internal and external network one-way data isolation transmission mechanism, and importing an elastic dislocation model for forward modeling calculation; obtaining three-dimensional earth surface deformation parameters of the seismic region; on the basis of the obtained digital elevation model data, fault node data and the three-dimensional earth surface deformation parameters, terrain gradient parameters, fault distance parameters and deformation gradient characteristic quantities are obtained through calculation, and the deformation gradient characteristic quantities, the terrain gradient parameters and the fault distance parameters are mapped to a pre-constructed three-dimensional evaluation matrix; the technical problems that a traditional earthquake emergency tool is insufficient in data timeliness, ground surface deformation simulation is missing, the electric power facility earthquake disaster risk quantitative evaluation capability is weak, and internal and external network safety isolation transmission of a power grid is achieved are solved.

Description

Technical Field

[0001] This invention relates to the field of computers, and specifically to a method and system for assessing the seismic disaster risk of power facilities based on seismic deformation fields. Background Technology

[0002] As a country prone to earthquakes, China frequently experiences significant casualties and economic losses due to strong earthquakes. However, in the initial post-earthquake period, insufficient data coverage hinders timely and effective information support for rescue decisions. Current geodesy, through millimeter-precision continuous observations (GNSS) and large-scale surface monitoring (InSAR), provides crucial support for research on earthquake deformation mechanisms. Although the method of inverting coseismic deformation using combined ascending and descending orbit InSAR data has been shown to have good agreement with the displacement field of the Okada model, the limitation of satellite revisit cycles makes it difficult to quickly obtain comprehensive spatial observation data covering the disaster area in the initial post-earthquake period, thus restricting the timeliness of emergency rescue.

[0003] Earthquakes have multi-dimensional impacts on power infrastructure. Direct equipment damage primarily manifests as the collapse of transmission line towers (e.g., the Wenchuan earthquake caused the collapse of more than 20 110kV line towers), the displacement of substation equipment (e.g., the Niigata earthquake in Japan caused a transformer fire at a nuclear power plant), and the widespread destruction of power poles in the distribution network (e.g., 540 poles were damaged in the 2011 Tohoku earthquake in Japan). Secondary disasters such as landslides and mudslides caused by earthquakes also threaten transmission facilities, disrupt power security in affected areas, and hinder post-disaster reconstruction and rapid response. For example, the 2013 Lushan earthquake caused the entire power grid in Lushan, Tianquan, and Baoxing counties to collapse, resulting in the shutdown of 34 35kV and above substations, 265 10kV and above transmission and distribution lines, and damage to a total of 626 pieces of equipment, causing a cumulative economic loss of over 700 million yuan.

[0004] To collect earthquake information in real time, various fully automated online earthquake emergency response tools based on earthquake data have been developed. These include the USGS earthquake information release website developed by the U.S. Geological Survey, ShapeMap developed by Wald et al. and ShakeAlert improved by Kohler et al., the China Earthquake Networks Center built by the China Earthquake Administration, and the Guangdong Provincial Earthquake Rapid Reporting System developed by the Guangdong Earthquake Administration. However, these websites only provide earthquake information and cannot simulate earthquake-induced deformation or assess the risk of post-earthquake surface deformation to power facilities.

[0005] Current online earthquake emergency response tools cannot meet the security and concealment requirements of power facilities. Power facilities (such as substations, transmission networks, and dispatch centers) are typically part of critical national infrastructure, and their geographical location, network architecture, and operational data are highly sensitive to security threats. Concealment refers not only to the confidentiality of physical location but also to the prevention of leakage of information such as network topology, communication protocols, and control commands, in order to prevent potential attackers from obtaining critical intelligence.

[0006] To eliminate the above risks, a common approach is to isolate internal and external networks to block attack paths. The external network is used for office network and internet access operations, while the internal network directly controls power equipment. Layered protection is implemented at the data and protocol levels, reducing risks by isolating data flows and using different protocols. Furthermore, to meet the security regulations for power monitoring systems, it is explicitly required that a one-way isolation device (such as a network gateway) be deployed between the production control area (internal network) and the management information area (external network) to prohibit direct communication.

[0007] Based on the above issues, it is of great significance to address the technical problems of traditional earthquake emergency tools, such as insufficient data timeliness, lack of surface deformation simulation, weak ability to quantitatively assess earthquake disaster risks of power facilities, and secure isolation and transmission between the power grid and its internal and external networks. Summary of the Invention

[0008] To address the shortcomings of existing earthquake emergency response tools, such as insufficient data timeliness, lack of surface deformation simulation, weak ability to quantitatively assess earthquake disaster risks of power facilities, and inadequate secure isolation transmission between the power grid and its internal and external networks, this invention proposes a method and system for assessing earthquake disaster risks of power facilities based on earthquake deformation fields.

[0009] Firstly, a method for assessing the seismic disaster risk of power facilities based on seismic deformation fields is provided, including: The geometric parameters of the seismic source fault were completed using seismic parameter data obtained through a one-way data isolation transmission mechanism between internal and external networks, and then imported into an elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone. Based on the acquired digital elevation model data, fault node data, and the three-dimensional surface deformation parameters, the terrain slope parameters, fault distance parameters, and deformation gradient characteristic quantities are calculated respectively. The deformation gradient features, terrain slope parameters, and fault distance parameters are mapped to a pre-constructed three-dimensional evaluation matrix to determine the seismic risk level of the location of the power facilities.

[0010] Secondly, a seismic disaster risk assessment system for power facilities based on seismic deformation fields is provided, including: The completion module is used to complete the geometric parameters of the seismic source fault using seismic parameter data obtained based on the one-way data isolation transmission mechanism between internal and external networks, and import it into the elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone. The calculation module is used to calculate the terrain slope parameter, fault distance parameter and deformation gradient characteristic quantity based on the acquired digital elevation model data, fault node data and the three-dimensional surface deformation parameters, respectively. The assessment module is used to map the deformation gradient features, terrain slope parameters, and fault distance parameters to a pre-constructed three-dimensional assessment matrix to determine the seismic risk level of the location of the power facilities.

[0011] In another aspect, the present invention also provides an electronic device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a method for assessing the seismic disaster risk of power facilities based on seismic deformation fields, as described above, is implemented.

[0012] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the above-described method for assessing the seismic disaster risk of power facilities based on seismic deformation fields.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a method and system for assessing the seismic risk of power facilities based on seismic deformation fields. The method utilizes seismic parameter data obtained through a one-way data isolation transmission mechanism between internal and external power grids to complete the geometric parameters of the source fault. This data is then imported into an elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone. Based on the acquired digital elevation model data, fault node data, and the three-dimensional surface deformation parameters, terrain slope parameters, fault distance parameters, and deformation gradient characteristics are calculated. These parameters are then mapped to a pre-constructed three-dimensional assessment matrix to determine the seismic risk level of the power facility's location. This method addresses the technical problems of traditional earthquake emergency tools, such as insufficient data timeliness, lack of surface deformation simulation, weak quantitative assessment capabilities for seismic risk of power facilities, and the need for secure isolation transmission between the power grid and internal / external networks.

[0014] Specifically, this invention implements a one-way channel conditional internal and external network data transmission and isolation method for seismic risk assessment of power facilities. Under the premise of ensuring the security and controllability of power facility data, it achieves efficient transmission of seismic data and hourly response to post-earthquake risk assessment of high-risk earthquakes. This invention also implements a method for assessing the risk of power facilities based on an elastic dislocation model. By constructing a three-dimensional assessment matrix through parameters such as deformation gradient, terrain slope, and fault distance, it achieves efficient and quantitative assessment of the seismic risk of power facilities. Attached Figure Description

[0015] Figure 1 This is a flowchart of the seismic disaster risk assessment method for power facilities based on seismic deformation field according to the present invention; Figure 2This is a schematic diagram of the earthquake monitoring, early warning, and risk assessment platform for the power facility earthquake disaster risk assessment method based on seismic deformation field of the present invention; Figure 3 This is a schematic diagram of landslide risk assessment using the seismic disaster risk assessment method for power facilities based on seismic deformation field according to the present invention; Figure 4 This is a schematic diagram illustrating the comprehensive risk and tower risk assessment of the power facility seismic disaster risk assessment method based on seismic deformation field according to the present invention; Figure 5 This is a schematic diagram of the seismic disaster risk assessment system for power facilities based on seismic deformation field according to the present invention; Figure 6 This is a schematic diagram of an electronic device structure according to the present invention. Detailed Implementation

[0016] The purpose of this invention is to provide a platform capable of supporting the search for seismic data, simulation of surface deformation, and assessment of deformation risks in areas where power facilities are located. This platform takes into account the information security requirements during unidirectional transmission between the internal and external networks of the power grid system, and solves the problem that traditional seismic information platforms lack the ability to simulate surface deformation and assess risks, thus possessing high scientific significance and practical value. Its main technical means include: (1) proposing a method for data transmission and isolation between internal and external networks under unidirectional channels; and (2) proposing a method for assessing different surface deformation risks based on an elastic dislocation model.

[0017] To better understand the present invention, the following description, in conjunction with the accompanying drawings and embodiments, will further illustrate the content of the present invention.

[0018] Example 1: A method for seismic disaster risk assessment of power facilities based on seismic deformation fields, such as... Figure 1 As shown, it includes: Step 1: Use the seismic parameter data obtained based on the one-way data isolation transmission mechanism between internal and external networks to complete the geometric parameters of the source fault, and import it into the elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone; Step 2: Based on the acquired digital elevation model data, fault node data, and the three-dimensional surface deformation parameters, the terrain slope parameters, fault distance parameters, and deformation gradient characteristic quantities are calculated respectively. Step 3: Map the deformation gradient features, terrain slope parameters, and fault distance parameters to a pre-constructed three-dimensional evaluation matrix to determine the seismic risk level of the location of the power facilities.

[0019] In this embodiment, before completing the geometric parameters of the seismic fault based on seismic parameter data in step 1, a data query request needs to be initiated to the external network through a one-way data isolation transmission mechanism between the internal and external networks, and the seismic parameter data needs to be obtained by reading the data through the internal network. This satisfies the requirements of the concealment and security of power grid equipment and effectively protects the security of information related to power facilities. Specifically, this includes: In response to a data query request initiated by an intranet user or system to an external web crawling system through a pre-defined interface, the external web crawling system parses the data query request and sends it to the core crawler module. The core crawler module performs cyclic detection on the external network target data source corresponding to the data query request, captures earthquake parameter data that meets the preset conditions, and writes the earthquake parameter data into an isolated database after performing data cleaning operations. The intranet system monitors and reads earthquake parameter data from the isolated database, and returns the data to the intranet user or system.

[0020] In a specific embodiment, the implementation process of internal and external network data crawling technology can be divided into three main stages: internal network request processing, external network data crawling, and data storage and return. The overall process is as follows: Figure 2 As shown.

[0021] During the intranet request processing phase, intranet users or systems initiate data requests to the crawling system via an interface, specifying the target data or query conditions to be obtained. Upon receiving the request, the crawling system parses it and sends the task to the core crawler module. This phase is primarily implemented through the intranet API service (based on Flask), while ensuring the legitimacy and completeness of the request.

[0022] During the external network data crawling phase, the system iteratively checks the target data source on the external network to determine if there is any updated data or new content that meets the criteria. This process is implemented through a scheduled task, sending HTTP requests to the target data source and retrieving the response content. During this process, it is necessary to address potential anti-crawling mechanisms of the external network data source, which can be solved by using a proxy IP pool or a headless browser to simulate user behavior. The core crawler module is responsible for extracting the required data from the target data source on the external network and parsing it into structured data. The crawled data may be in HTML, JSON, or XML format, and useful information needs to be extracted using parsing tools (such as BeautifulSoup, lxml). For dynamic content, browser simulation technology is also required for crawling. After processing, the crawled data is cleaned, deduplicated, formatted, and written to the database for subsequent use. The chosen database is a relational database (MySQL).

[0023] During data storage and return, after data is stored in the MySQL database, the intranet system continuously monitors the data in the database to determine if there is any new data that meets the criteria and needs to be returned to the user or system. Through triggers or scheduled tasks, the system can promptly detect data changes and send notifications to intranet users. Finally, the intranet system calls the core code to further process the data (such as analysis, aggregation, or transformation) and returns the final results to the intranet user or system in the form of an API or file.

[0024] This internal and external network data crawling technology achieves a complete closed loop from internal network requests to external network data acquisition, storage, and return, ensuring the efficiency and reliability of data crawling. Key technologies include the implementation of the external network crawler, countermeasures against anti-crawling mechanisms, data storage and monitoring, and efficient processing of internal network requests.

[0025] In this embodiment, after obtaining seismic parameter data through a one-way data isolation transmission mechanism between internal and external networks based on the aforementioned content, the geometric parameters of the seismic source fault can be completed based on this seismic parameter data, and then imported into an elastic dislocation model for calculation, providing a foundation for the subsequent establishment of multivariate evaluation indicators. Specifically, this includes: Based on the moment magnitude in the seismic parameter data obtained by the one-way data isolation transmission mechanism between internal and external networks, the fault rupture length and fault rupture width are calculated using the relationship between the moment magnitude and the fault length and width. Based on the seismic moment in the seismic parameter data, the fault slip value is calculated using the relationship between the seismic moment and the moment magnitude. The earthquake parameter data, the fault rupture length, the fault rupture width, and the fault slip value are used as input parameters and substituted into the elastic uniform half-space matrix dislocation model to perform three-dimensional surface deformation simulation, thereby obtaining the three-dimensional surface deformation parameters of the seismic zone. The earthquake parameter data includes one or more of the following: moment magnitude, focal center coordinates, focal depth, strike angle, dip angle, and slip angle.

[0026] In one specific embodiment, earthquake occurrence is based on the elastic rebound theory. Steketee first established a link between seismic activity and coseismic displacement deformation in 1958. Okada, in 1985, summarized previous research and further refined the elastic dislocation theory, deriving the elastic homogeneous half-space matrix dislocation model. This is achieved through fault plane length... , width of the cross-section ,depth and tilt angle Fault vector ( , , Parameters such as ) can accurately represent surface deformation.

[0027] Earthquake parameters obtainable from the USGS website via data crawling include latitude and longitude, moment magnitude, focal depth, strike angle, dip angle, and slip angle, but fault length and width parameters are missing. Therefore, empirical formulas for faults are used to calculate fault length and width. The relationship between magnitude and fault length and width is as follows: (1) in, Represents the fracture length. Represents the fracture width. It represents the magnitude of the moment magnitude.

[0028] The earthquake moment is estimated using the moment magnitude obtained from the USGS, and the magnitude of the fault slip value is further estimated using the following formula: (2) in, The estimated fault slip value, Moment magnitude, This is the seismic moment.

[0029] Therefore, the above formula can be combined with the moment magnitude. Fault length Fault width The slip value on the fault is calculated, and the latitude and longitude of the earthquake source center, depth, fault length, fault width and slip value are input into the OKADA model to simulate three-dimensional surface deformation.

[0030] In this embodiment, after obtaining the three-dimensional surface deformation parameters of the seismic zone based on the aforementioned step 1, the key elements can be calculated based on the three-dimensional surface deformation parameters, the acquired digital elevation model data, and the fault node data to establish a multi-source three-dimensional risk assessment system.

[0031] In one specific embodiment, assessing the risk of power equipment using a three-dimensional surface deformation model obtained through simulation calculation of an elastic dislocation requires establishing multi-dimensional evaluation indicators. Generally, greater surface deformation increases the likelihood of continuous surface disasters, steeper terrain slopes increase the risk of landslides, and closer proximity to faults where earthquakes occur increases the likelihood of large-scale surface deformation. Therefore, a multi-dimensional three-dimensional risk assessment system is established by comprehensively considering three key elements: deformation parameters, terrain features, and tectonic environment. The four-directional deformation gradient field at discrete points in space is calculated based on the difference algorithm: (3) in, This represents the three-dimensional surface deformation parameters at adjacent points. , Spacing in a rectangular coordinate system. , The spacing is a 45° oblique coordinate system. This represents the characteristic quantity of deformation gradient. The gradient value reflects the degree of spatial variation in surface deformation.

[0032] Surface slope B is calculated using digital elevation model (DEM) data: (4) in and These represent the elevation change rates in the x and y directions, respectively, while the slope parameter characterizes the stability of the original landform.

[0033] The Euclidean distance from each point to the nearest active fault was calculated using spatial analysis algorithms: (5) In the formula ( , () represents the coordinates of the point to be evaluated. , ) represents the set of fault line node coordinates, reflecting the attenuation characteristics of tectonic activity, and C is the fault distance parameter.

[0034] In this embodiment, after calculating the terrain slope parameters, fault distance parameters, and deformation gradient characteristics through step 2, a three-dimensional assessment matrix can be constructed based on these parameters. The seismic risk level of the power facility's location is then determined based on this constructed three-dimensional assessment matrix, enabling a multi-dimensional and comprehensive assessment of the seismic risk of power facilities after an earthquake. Specifically, this includes: The deformation gradient feature, terrain slope parameter, and fault distance parameter are discretized and standardized into multiple risk levels, and the standardized parameters are substituted into a pre-constructed three-dimensional evaluation matrix for spatial mapping to obtain normalized risk values. Based on the normalized risk value, the earthquake risk level of the location of the power facility is determined using a preset risk assessment threshold.

[0035] In one specific embodiment, a multi-factor coupled evaluation system is established by combining the above parameters. First, all parameters are standardized; second, a three-dimensional evaluation matrix is ​​constructed; and finally, the specific risk level of the power facility is determined. The collaborative evaluation of multiple parameters is achieved through spatial mapping of the three-dimensional matrix, and the specific steps are as follows: (1) Parameter standardization Each parameter is discretized into a 5-level risk level: Deformation gradient feature A: A1 (low) ~ A5 (high) Terrain slope parameter B: B1 (gentle) ~ B5 (steep) Fault distance parameter C: C1 (near) ~ C5 (far), classified according to the radius of influence of the fault zone. (2) Construction of three-dimensional evaluation matrix The calculation is performed by combining the deformation risk map, landslide risk map, and distance-from-epicenter risk map. The calculation logic is as follows:

[0036] (After normalization, the risk level ranges from [0,100]). Among them, low risk (0-20); relatively low risk (20-40); medium risk (40-60); relatively high risk (60-80); and high risk (80-100).

[0037] (3) Risk level classification The output values ​​are divided into 5 risk levels: 01 Low risk: Q≤Q1 02 Lower risk: Q1 < Q ≤ Q2 03 Medium risk: Q2 < Q ≤ Q3 04 Higher risk: Q3 < Q ≤ Q4 05 High Risk: Q≥Q4 This invention innovatively couples the spatial gradient field, topographic slope field, and tectonic stress field in three dimensions, and constructs an scalable matrix evaluation system through parameter discretization, providing a quantitative analysis tool for post-earthquake risk early warning of power infrastructure.

[0038] The present invention has the following beneficial effects: (1) Considering the security requirements of power grid equipment network systems, this invention proposes a method for data transmission and isolation between internal and external networks under a one-way channel. By using JDBC to isolate the internal and external network databases, a one-way application channel for external data is realized based on the internal network control page. External network data is crawled through the external webpage, effectively avoiding the risk of information leakage. This method can meet the concealment and security requirements of power grid equipment and effectively protect the security of information related to power facilities.

[0039] (2) To address the potential risks to power facilities caused by post-earthquake surface deformation, this invention employs a deformation gradient characteristic method that considers deformation parameters to process deformation simulation data. The deformation parameters are generated from the focal mechanism solution and the rectangular dislocation model, and are used to assess the intensity of spatial changes in surface deformation. This assessment index can effectively evaluate the deformation risk in areas of severe deformation, such as fault contact surfaces.

[0040] (3) To assess the potential risks of post-earthquake landslides to power facilities, this invention uses a terrain slope parameter that considers topographic features to process the digital elevation model. The terrain slope parameter is generated from DEM data and is used to assess the degree of spatial variation in surface topography. This assessment index can effectively evaluate coseismic landslides caused by high terrain slopes.

[0041] (4) To assess the impact of earthquake-originating faults on power facilities, this invention uses fault distance parameters from the tectonic environment for evaluation. The fault is generated from the focal mechanism solution and empirical parameters, while the fault distance parameter is generated from the Euclidean distance to the fault, used to assess the degree of damage caused by the fault to the entire area. This assessment index can detect the secondary disaster risk to power facilities affected by faults.

[0042] (5) This invention proposes a risk assessment index based on DEM and earthquake-simulated deformation field, and applies it to the assessment of power facilities. This method innovatively incorporates spatial gradient field, topographic slope field and tectonic stress field into the risk assessment system, and conducts a multi-dimensional and comprehensive assessment of the earthquake disaster risk of power facilities after an earthquake through the above three risk indicators.

[0043] Example 2: The following example, the earthquake in December 2023, illustrates the seismic risk assessment of power facilities according to this invention: 2.1 Earthquake Catalog Search By entering the time range, earthquake magnitude, earthquake depth, and the latitude and longitude range of the search area in the earthquake catalog function page of the disaster monitoring and early warning interface, an earthquake event catalog search was performed. Within the range of 60°E to 150°E and 0°N to 60°N, earthquakes of magnitude 3 to 8 with depths of 0 to 20 km were searched from December 1st to December 31st, 2023. A total of 161 earthquakes were found. Clicking on the earthquake information allows viewing the focal depth and latitude and longitude information of the Gansu Jishishan earthquake that occurred at 23:59:30 on December 18th, 2023.

[0044] 2.2 Landslide Risk Assessment Map Taking the Jishishan earthquake in Gansu as an example, it illustrates a risk diagram considering the topographic slope parameter B, which takes into account terrain features. For example... Figure 3 As can be easily seen, the slope on the southwest side of Jishi Mountain is steeper, posing a greater risk of landslides.

[0045] 2.3 Comprehensive Risk and Tower Risk Assessment Diagram Taking the Jishishan earthquake in Gansu Province as an example, we present a comprehensive risk assessment map obtained based on a risk assessment method using DEM and earthquake-simulated deformation fields. For example... Figure 4 As shown, the risk assessment indicators above indicate that there is a high risk of damage to power facilities within a relatively short distance of the Jishishan epicenter. Reports from the disaster relief site of the Jishishan earthquake revealed that multiple power facilities within a 100-kilometer radius of the epicenter were damaged and experienced power outages. Therefore, our risk assessment method is highly consistent with the actual situation.

[0046] Example 3: Based on the same inventive concept, this invention also provides a power facility seismic disaster risk assessment system based on seismic deformation fields, such as... Figure 5 As shown, it includes: The completion module is used to complete the geometric parameters of the seismic source fault using seismic parameter data obtained based on the one-way data isolation transmission mechanism between internal and external networks, and import it into the elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone. The calculation module is used to calculate the terrain slope parameter, fault distance parameter and deformation gradient characteristic quantity based on the acquired digital elevation model data, fault node data and the three-dimensional surface deformation parameters, respectively. The assessment module is used to map the deformation gradient features, terrain slope parameters, and fault distance parameters to a pre-constructed three-dimensional assessment matrix to determine the seismic risk level of the location of the power facilities.

[0047] Preferably, in the completion module, the acquisition of seismic parameter data includes: In response to a data query request initiated by an intranet user or system to an external web crawling system through a pre-defined interface, the external web crawling system parses the data query request and sends it to the core crawler module. The core crawler module performs cyclic detection on the external network target data source corresponding to the data query request, captures earthquake parameter data that meets the preset conditions, and writes the earthquake parameter data into an isolated database after performing data cleaning operations. The intranet system monitors and reads earthquake parameter data from the isolated database, and returns the data to the intranet user or system.

[0048] Preferably, the completion module is further used for: Based on the moment magnitude in the seismic parameter data obtained by the one-way data isolation transmission mechanism between internal and external networks, the fault rupture length and fault rupture width are calculated using the relationship between the moment magnitude and the fault length and width. Based on the seismic moment in the seismic parameter data, the fault slip value is calculated using the relationship between the seismic moment and the moment magnitude. The earthquake parameter data, the fault rupture length, the fault rupture width, and the fault slip value are used as input parameters and substituted into the elastic uniform half-space matrix dislocation model to perform three-dimensional surface deformation simulation, thereby obtaining the three-dimensional surface deformation parameters of the seismic zone. The earthquake parameter data includes one or more of the following: moment magnitude, focal center coordinates, focal depth, strike angle, dip angle, and slip angle.

[0049] Preferably, the relationship between the moment magnitude and the fault length and width in the completion module is as follows:

[0050] in, Indicates the fracture length. Indicates the fracture width. Indicates the magnitude of the moment magnitude The relationship between the seismic moment and the moment magnitude is shown below:

[0051] in, This represents the fault slip value. This is the seismic moment.

[0052] Preferably, the deformation gradient feature quantity in the calculation module is obtained by the following formula:

[0053] in, This represents the three-dimensional surface deformation parameters at adjacent points. , Spacing in a rectangular coordinate system. , The spacing is a 45° oblique coordinate system. This represents the deformation gradient characteristic quantity.

[0054] Preferably, the terrain slope parameter is calculated based on the digital elevation model data obtained from the digital elevation model using the following formula:

[0055] in, This represents the rate of change of elevation in the x-direction. This represents the rate of change of elevation in the y-direction. This represents the terrain slope parameter.

[0056] Preferably, the Euclidean distance from each point to the nearest active fault is calculated using the set of fault line node coordinates obtained from the fault node data and the following spatial analysis algorithm as the fault distance parameter:

[0057] in, , The coordinates of the point to be evaluated are: , Let C be the set of fault line node coordinates, and let C be the fault distance parameter.

[0058] Preferably, the evaluation module is further configured to: The deformation gradient feature, terrain slope parameter, and fault distance parameter are discretized and standardized into multiple risk levels, and the standardized parameters are substituted into a pre-constructed three-dimensional evaluation matrix for spatial mapping to obtain normalized risk values. Based on the normalized risk value, the earthquake risk level of the location of the power facility is determined using a preset risk assessment threshold.

[0059] Example 4 like Figure 6 As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0060] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to realize the corresponding method flow or corresponding function, so as to realize the steps of the power facility seismic disaster risk assessment method based on seismic deformation field in the above embodiments.

[0061] Example 5 Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the power facility seismic disaster risk assessment method based on seismic deformation fields in the above embodiments.

[0062] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0063] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0064] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0065] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0066] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for assessing the seismic disaster risk of power facilities based on seismic deformation fields, characterized in that, include: The geometric parameters of the seismic source fault were completed using seismic parameter data obtained through a one-way data isolation transmission mechanism between internal and external networks, and then imported into an elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone. Based on the acquired digital elevation model data, fault node data, and the three-dimensional surface deformation parameters, the terrain slope parameters, fault distance parameters, and deformation gradient characteristic quantities are calculated respectively. The deformation gradient features, terrain slope parameters, and fault distance parameters are mapped to a pre-constructed three-dimensional evaluation matrix to determine the seismic risk level of the location of the power facilities.

2. The method according to claim 1, characterized in that, The acquisition of the seismic parameter data includes: In response to a data query request initiated by an intranet user or system to an external web crawling system through a pre-defined interface, the external web crawling system parses the data query request and sends it to the core crawler module. The core crawler module performs cyclic detection on the external network target data source corresponding to the data query request, captures earthquake parameter data that meets the preset conditions, and writes the earthquake parameter data into an isolated database after performing data cleaning operations. The intranet system monitors and reads earthquake parameter data from the isolated database, and returns the data to the intranet user or system.

3. The method according to claim 1, characterized in that, The seismic parameter data obtained using a one-way data isolation transmission mechanism between internal and external networks is used to complete the geometric parameters of the seismic source fault, and then imported into an elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone, including: Based on the moment magnitude in the seismic parameter data obtained by the one-way data isolation transmission mechanism between internal and external networks, the fault rupture length and fault rupture width are calculated using the relationship between the moment magnitude and the fault length and width. Based on the seismic moment in the seismic parameter data, the fault slip value is calculated using the relationship between the seismic moment and the moment magnitude. The earthquake parameter data, the fault rupture length, the fault rupture width, and the fault slip value are used as input parameters and substituted into the elastic uniform half-space matrix dislocation model to perform three-dimensional surface deformation simulation, thereby obtaining the three-dimensional surface deformation parameters of the seismic zone. The earthquake parameter data includes one or more of the following: moment magnitude, focal center coordinates, focal depth, strike angle, dip angle, and slip angle.

4. The method according to claim 3, characterized in that, The relationship between the moment magnitude and the fault length and width is shown in the following formula: in, Indicates the fracture length. Indicates the fracture width. Indicates the magnitude of the moment magnitude The relationship between the seismic moment and the moment magnitude is shown below: in, This represents the fault slip value. This is the seismic moment.

5. The method according to claim 1, characterized in that, The deformation gradient feature is obtained by the following formula: in, This represents the three-dimensional surface deformation parameters at adjacent points. , Spacing in a rectangular coordinate system. , The spacing is a 45° oblique coordinate system. This represents the deformation gradient characteristic quantity.

6. The method according to claim 1, characterized in that, The terrain slope parameter is calculated based on the digital elevation model data obtained from the digital elevation model using the following formula: in, This represents the rate of change of elevation in the x-direction. This represents the rate of change of elevation in the y-direction. This represents the terrain slope parameter.

7. The method according to claim 1, characterized in that, The Euclidean distance from each point to the nearest active fault is calculated using the set of fault line node coordinates obtained from the fault node data and the following spatial analysis algorithm: in, , The coordinates of the point to be evaluated are: , Let C be the set of fault line node coordinates, and let C be the fault distance parameter.

8. The method according to claim 1, characterized in that, The process of mapping the deformation gradient features, terrain slope parameters, and fault distance parameters to a pre-constructed three-dimensional evaluation matrix to determine the seismic risk level of the power facility's location includes: The deformation gradient feature, terrain slope parameter, and fault distance parameter are discretized and standardized into multiple risk levels, and the standardized parameters are substituted into a pre-constructed three-dimensional evaluation matrix for spatial mapping to obtain normalized risk values. Based on the normalized risk value, the earthquake risk level of the location of the power facility is determined using a preset risk assessment threshold.

9. A seismic disaster risk assessment system for power facilities based on seismic deformation fields, characterized in that, include: The completion module is used to complete the geometric parameters of the seismic source fault using seismic parameter data obtained based on the one-way data isolation transmission mechanism between internal and external networks, and import it into the elastic dislocation model for forward modeling to obtain the three-dimensional surface deformation parameters of the seismic zone. The calculation module is used to calculate the terrain slope parameter, fault distance parameter and deformation gradient characteristic quantity based on the acquired digital elevation model data, fault node data and the three-dimensional surface deformation parameters, respectively. The assessment module is used to map the deformation gradient features, terrain slope parameters, and fault distance parameters to a pre-constructed three-dimensional assessment matrix to determine the seismic risk level of the location of the power facilities.

10. An electronic device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the method for assessing the seismic disaster risk of power facilities based on seismic deformation fields as described in any one of claims 1 to 8 is implemented.

11. A readable storage medium, characterized in that, It contains an execution program, which, when executed, implements the method for assessing the seismic disaster risk of power facilities based on seismic deformation fields as described in any one of claims 1 to 8.

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