High-speed railway earthquake early warning system simulation test and evaluation method and system

Abstract

The invention discloses a simulation test and evaluation method and system for a high-speed railway earthquake early warning system, and the method and system are corresponding schemes, in the scheme, simulation test data can be automatically and efficiently generated, the defects of single, discrete and static data in the prior art are overcome, and abundant and realistic input sources are provided for the test of a tested system; moreover, the sending time sequence of test data can be accurately controlled, the real time-space characteristics of seismic wave propagation can be simulated, high-concurrency data generation is supported, and the performance and stability of the system during processing real-time, concurrency and interlaced information are checked; in addition, simulation data and a test result of a tested object can be automatically collected, and automatic analysis and calculation can be completed. Basic function verification can be completed, and key performance indexes of the system can be quantitatively and objectively measured and evaluated.

Description

Technical Field

[0001] This invention relates to the field of system simulation testing and evaluation technology, and in particular to a simulation testing and evaluation method and system for a high-speed railway earthquake early warning system. Background Technology

[0002] High-speed railways operate at high speeds and with high frequency, thus placing significant pressure on earthquake prevention and disaster mitigation efforts. To prevent major earthquake damage to railways, since 2012, a high-speed railway earthquake safety research and development group led by the China Academy of Railway Sciences has been conducting research and development on high-speed railway earthquake early warning technology and line testing, resulting in the development of a high-speed railway earthquake early warning monitoring system. This system consists of a high-speed railway earthquake early warning monitoring system and onboard earthquake emergency response devices. The early warning monitoring system adopts a two-tier architecture, comprising a railway bureau central system and on-site monitoring equipment. The high-speed railway earthquake early warning monitoring system has begun to be promoted and applied throughout the railway network in recent years and has already been implemented on multiple high-speed railway lines.

[0003] The high-speed railway earthquake early warning and monitoring system aggregates information from the local line, adjacent lines, the local railway bureau, neighboring railway bureaus, and the seismic network. This information is complex and diverse, involving interfaces between lines, neighboring railway bureaus, railway networks, and the G-network. For these systems, a common approach is to manually send test data one by one, based on technical specifications and simulated interface communication protocols, to verify system functionality. However, this testing method can only verify the system's basic functions and cannot simulate the concurrent testing scenarios of multi-source information in real, complex environments. Furthermore, the testing process is cumbersome and inefficient. Existing methods cannot effectively test the concurrent processing capacity and timeliness of the high-speed railway earthquake early warning and monitoring system. This inefficient testing method makes it difficult to fully verify the system's reliability and robustness under real, extreme seismic events, severely limiting the system's testing capabilities and posing potential safety risks to its online operation.

[0004] Specifically, currently, the testing of high-speed railway earthquake early warning monitoring systems generally adopts a test scheme based on manual operation or database query. The core of this scheme lies in simulating the interface communication protocol, which mainly relies on the following two methods: (1) Manual script method: Testers pre-write or manually construct single test data according to the technical conditions document, and send the test data to the system under test manually and line by line through a custom script, and observe the system's response output to verify whether its basic functions are correct. (2) Database query method: Data of earthquake events that have occurred or manually constructed test cases are pre-entered into the database; during testing, data records are sent to the system under test sequentially and line by line through simple database queries and script reading. This method essentially replaces manual input with database reading, but the data processing method has not fundamentally changed.

[0005] The shortcomings of the above test scheme are: (1) It can only generate single, discrete, and static events, and cannot simulate complex earthquake scenarios such as multiple sources, multiple sources, and multiple stations; the data lacks necessary correlation, and data needs to be sent manually or by reading from the database, and can only generate single information. (2) It cannot accurately control the timestamps and delays between multiple data sources; it is difficult to guarantee that multiple types of information are sent simultaneously by manual sending or sequential reading from the database. (3) The generated test cases are limited and time-consuming to build, and heavily rely on the experience of testers and the historical data at hand. The test cases are affected by human habits, and it is impossible to exhaustively collect massive amounts of test data and conduct continuous testing. (4) It focuses on functional verification rather than performance and reliability evaluation; it can only verify the function of the system under test, and cannot evaluate the performance of the system under test. (5) It cannot automatically evaluate the generated test results.

[0006] Therefore, an automated simulation testing method is needed that can efficiently simulate complex earthquake scenarios and multi-source concurrent information, and comprehensively evaluate system performance, in order to solve the above-mentioned testing challenges and ensure the reliability and safety of the high-speed rail earthquake early warning system before it goes online.

[0007] In view of this, the present invention is hereby proposed. Summary of the Invention

[0008] The purpose of this invention is to provide a simulation test and evaluation method and system for a high-speed railway earthquake early warning system. This method can verify the correctness of the function of the tested system, more accurately quantify its performance and reliability, and provide crucial data support and decision-making basis for the effectiveness evaluation and optimization of the high-speed railway earthquake early warning system.

[0009] The objective of this invention is achieved through the following technical solution: A simulation testing and evaluation method for a high-speed railway earthquake early warning system includes: Configure earthquake simulation parameters; Earthquake event parameters are synthesized based on earthquake simulation parameters, and station simulation information, network simulation information and neighboring station simulation information are generated based on the earthquake event parameters. The occurrence time of each simulation information is calculated, and each simulation information is assigned a globally unique earthquake event ID, which is then sent to the earthquake early warning system of the high-speed railway under test. The system obtains the processing results and processing completion time of each simulation information from the tested high-speed railway earthquake early warning system. It matches the simulation information with the globally unique earthquake event ID of the simulation information, calculates the time delay information by combining the processing completion time and the occurrence time, and evaluates the tested high-speed railway earthquake early warning system based on the time delay information and processing results.

[0010] A simulation testing and evaluation system for a high-speed railway earthquake early warning system, used to implement the aforementioned method, includes: The simulation configuration module is used to configure earthquake simulation parameters; The simulation generation module is used to synthesize seismic event parameters based on seismic simulation parameters, and generate station simulation information, network simulation information and neighboring station simulation information based on the seismic event parameters. It calculates the occurrence time of each simulation information and assigns a globally unique seismic event ID to each simulation information before sending it to the high-speed railway earthquake early warning system under test. The evaluation module is used to obtain the processing results and processing completion time of each simulation information of the tested high-speed railway earthquake early warning system. It matches the simulation information with the globally unique earthquake event ID, calculates the time delay information by combining the processing completion time and the occurrence time, and evaluates the tested high-speed railway earthquake early warning system based on the time delay information and the processing results.

[0011] As can be seen from the technical solution provided by the present invention: (1) It can automatically and efficiently generate simulation test data, overcoming the defects of single, discrete, and static data in the prior art, and providing rich and realistic input sources for the test of the system under test; (2) It can accurately control the transmission sequence of test data, simulate the real spatiotemporal characteristics of seismic wave propagation, and support high-concurrency data generation, verifying the performance and stability of the system when processing real-time, concurrent, and interleaved information; (3) It can automatically collect simulation data and test results of the tested object, and can complete automatic analysis and calculation. It can complete basic function verification, and can also quantitatively and objectively measure and evaluate the key performance indicators of the system. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A flowchart of a simulation test and evaluation method for a high-speed railway earthquake early warning system provided in an embodiment of the present invention.

[0014] Figure 2 This is a schematic diagram of a simulation test and evaluation system for a high-speed railway earthquake early warning system provided in an embodiment of the present invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0016] First, the following explanations are provided for the terms that may be used in this article: The term "and / or" means that either or both can be achieved simultaneously. For example, X and / or Y means that it includes both "X" or "Y" as well as the three cases of "X and Y".

[0017] The terms "comprising," "including," "containing," "having," or other similar semantic descriptions should be interpreted as non-exclusive inclusion. For example, including a technical feature element (such as raw material, component, ingredient, carrier, dosage form, material, size, part, component, mechanism, device, step, process, method, reaction conditions, processing conditions, parameter, algorithm, signal, data, product or article of manufacture, etc.) should be interpreted as including not only the expressly listed technical feature element, but also other technical feature elements that are not expressly listed and are well-known in the art.

[0018] The following is a detailed description of a simulation testing and evaluation method and system for a high-speed railway earthquake early warning system provided by this invention. Contents not described in detail in the embodiments of this invention are prior art known to those skilled in the art. Where specific conditions are not specified in the embodiments of this invention, they shall be performed according to conventional conditions in the art or conditions recommended by the manufacturer. Instruments used in the embodiments of this invention, unless otherwise specified by the manufacturer, are all commercially available conventional products.

[0019] Example 1 This invention provides a simulation testing and evaluation method for a high-speed railway earthquake early warning system, such as... Figure 1 As shown, it mainly includes the following steps: Step 1: Configure earthquake simulation parameters.

[0020] In this embodiment of the invention, the earthquake simulation parameters mainly include: (1) basic attributes of earthquake events, including: automatic transmission interval time, used to control the transmission frequency of simulation information; parameter b in Gutenberg-Richter's law, which reflects the frequency magnitude distribution characteristics of earthquake activity; minimum magnitude; earthquake generation boundary; and depth parameter; (2) earthquake spatial distribution pattern: indicating whether to use the real earthquake distribution; (3) monitoring network, including: coordinates of each station.

[0021] Step 2: Generating simulated earthquake information.

[0022] In this embodiment of the invention, earthquake event parameters are synthesized based on earthquake simulation parameters, and station simulation information, network simulation information and neighboring station simulation information are generated based on the earthquake event parameters. The occurrence time of each simulation information is calculated, and each simulation information is assigned a globally unique earthquake event ID, which is then sent to the earthquake early warning system of the high-speed railway under test.

[0023] In this embodiment of the invention, the earthquake event parameters synthesized based on earthquake simulation parameters include: generating magnitude, focal location, and focal depth based on earthquake simulation parameters, calculating the time of occurrence, and determining the earthquake alarm level; wherein, based on the minimum magnitude configured in the earthquake simulation parameters and parameter b, which reflects the frequency magnitude distribution characteristics of earthquake activity in the Gutenberg-Richter law, the magnitude distribution probability density function is calculated, and a random magnitude is generated using an inverse transform sampling algorithm; based on the earthquake spatial distribution pattern and earthquake generation boundary in the earthquake simulation parameters, a focal location conforming to the laws of geological tectonic activity is generated; and based on the depth parameter in the earthquake simulation parameters, the focal depth is randomly generated according to a preset distribution model.

[0024] In this embodiment of the invention, the method for generating station simulation information is as follows: Based on the generated seismic event parameters and the station coordinate information in the seismic simulation parameters, the seismic wave propagation physical model is run to generate station simulation information, i.e., simulated station seismic information. The simulated station seismic information includes: P-wave and S-wave alarm information; the propagation path distance from the source to the i-th station is denoted as d_i. Based on the P-wave velocity parameter V_p and the S-wave velocity parameter V_s, alarm information for P-wave and S-wave is generated according to the arrival time of P-wave t_{p,i} = t_0 + (d_i / V_p) and the arrival time of S-wave t_{s,i} = t_0 + (d_i / V_s), respectively; where t_0 is the time of earthquake occurrence.

[0025] In this embodiment of the invention, the method for generating seismic network simulation information is as follows: seismic network early warning information is generated based on the earthquake event parameters and earthquake simulation parameters, wherein the earthquake simulation parameters involved here are mainly the earthquake generation boundary and the fault zone corresponding to the earthquake spatial distribution mode when it is in the enabled state; after the seismic network early warning information is generated, seismic network alarm information is generated according to the earthquake propagation law; after the seismic network early warning information and seismic network alarm information are generated, and are distinguished into automatic rapid reporting and manual confirmation; wherein the seismic network early warning information, seismic network alarm information and seismic network rapid reporting information are all seismic network simulation information; and each of the above three pieces of information corresponds to a different occurrence time and is assigned a different earthquake event ID.

[0026] In this embodiment of the invention, the method for generating neighboring railway simulation information is as follows: whether to generate neighboring railway simulation information is determined according to a preset parameter, which is a probability value. If the generation of neighboring railway simulation information is triggered, the occurrence time of the neighboring railway simulation information is randomly generated according to the preset parameter, and then the neighboring railway simulation information is generated according to the earthquake generation boundary in the earthquake simulation parameters and the obtained adjacent railway bureau codes.

[0027] In this embodiment of the invention, the generated simulation information also includes: false alarm simulation information; the false alarm scenarios and their cancellation mechanisms corresponding to the false alarm simulation information are as follows: Single station false alarm: If only one station generates P-wave alarm information and does not generate S-wave alarm information within a preset time, the corresponding station needs to automatically trigger a false alarm; Network false alarm: If a network alarm is triggered directly without a network warning, network false alarm information needs to be triggered, and no quick report information will be generated; Among them, P-wave alarm information and S-wave alarm information belong to station simulation information; network warning information, network alarm information, and network quick report information all belong to network simulation information; After the triggering conditions are met, the time is calculated based on the event ID when the simulation data is generated. For single station false alarm, the event ID when the simulation data is generated is the event ID corresponding to the P-wave warning, and for network false alarm, the event ID when the simulation data is generated is the event ID corresponding to the network alarm. After a preset delay Δt_cancel, the corresponding false alarm simulation information is confirmed to be generated, and the corresponding false alarm cancellation signal is sent to the high-speed railway earthquake early warning system under test.

[0028] Similarly, the probability of generating false alarm simulation information can be controlled by preset parameters. That is, after generating station P-wave alarm information, there is a probability that S-wave alarm information will not be generated. At this time, a false alarm (single station false alarm) will occur, or a network early warning or network alarm will be generated. It does not depend on the seismic event parameters, but is generated probabilistically based on the generated station P-wave or network early warning and alarm information.

[0029] Step 3: Dynamic evaluation of test results.

[0030] In this embodiment of the invention, the processing result and processing completion time of the high-speed railway earthquake early warning system under test for each simulation information are obtained. The simulation information is matched with the globally unique earthquake event ID of the simulation information. The time delay information is calculated by combining the processing completion time and the occurrence time. The high-speed railway earthquake early warning system under test is evaluated based on the time delay information and the processing result.

[0031] In this embodiment of the invention, the matching of simulation information with the globally unique earthquake event ID, and the calculation of delay information by combining the handling completion time and the occurrence time, include: for each simulation information, using the difference between the handling completion time and the occurrence time as the single data delay.

[0032] In this embodiment of the invention, the evaluation of the tested high-speed railway earthquake early warning system based on time delay information and processing results includes: (1) Statistical analysis: Based on time delay information, calculate the average time delay, maximum time delay, and minimum time delay, and statistically analyze the number and proportion of data entries whose time delay falls in different intervals to characterize the stability and consistency of system performance; (2) Reliability assessment, including: system survival rate and data integrity rate; wherein, the system survival rate is the ratio of the time during which the tested high-speed railway earthquake early warning system maintains a normal response without downtime or no response failure, wherein the state of maintaining a normal response without downtime or no response failure is determined based on whether the processing results of the corresponding simulation information are received; the data integrity rate is the proportion of the number of simulation information entries that successfully receive matching processing results to the total number of sent entries. Based on statistical analysis, output the corresponding time delay distribution map, and based on statistical analysis and reliability assessment, output the automated test report.

[0033] The above-mentioned solutions provided by the embodiments of the present invention mainly achieve the following beneficial effects: (1) It can automatically and efficiently generate simulation test data, support the simulation of complex earthquake scenarios with multiple sources, multiple seismic sources, multiple stations, and different fault zone conditions, overcome the defects of single, discrete, and static data in existing technologies, and provide rich and realistic input sources for system testing.

[0034] (2) It can precisely control the timestamps and delays between multiple data sources to simulate the real spatiotemporal characteristics of seismic wave propagation.

[0035] (3) It supports high-concurrency data generation, which can verify the performance and stability of the tested system when processing real-time, concurrent and interleaved information.

[0036] (4) Full-process automation, eliminating dependence on manual operation.

[0037] (5) It can quantitatively measure and evaluate the key performance indicators of the system.

[0038] To more clearly demonstrate the technical solution and its effects provided by the present invention, the method provided by the embodiments of the present invention will be described in detail below with reference to specific examples.

[0039] This invention provides a simulation testing and evaluation method for a high-speed railway earthquake early warning system, aiming to solve the following problems faced in the testing of high-speed railway earthquake early warning systems: (1) Insufficient complexity of test data: It can automatically and efficiently generate simulation test data, support the simulation of complex earthquake scenarios under conditions of multiple sources, multiple stations, and different fault zones, and overcome the problems of single, discrete, and static data in existing testing methods; (2) Timing control and concurrency issues in the testing process: It can accurately control the transmission timing of test data, simulate the real spatiotemporal characteristics of seismic wave propagation, and support high-concurrency data generation, verifying the system's performance and stability when processing real-time, concurrent, and interleaved information; (3) Automated evaluation of test results: It can automatically collect simulation data and test results of the tested object, and complete automatic analysis and calculation. It can complete basic function verification and also quantitatively and objectively measure and evaluate the key performance indicators of the system. See also Figure 1 The following is a detailed description of the three parts involved in this invention.

[0040] I. Configuration of simulated seismic parameters.

[0041] The core of this section lies in providing a complete human-computer interaction interface for comprehensively setting various parameters of the earthquake simulation, thereby driving the generation module to simulate and generate scientific and diverse test scenarios. The parameters involved and their functions are as follows: 1. Basic attributes of earthquake events.

[0042] (1) Automatic transmission interval. Controls the transmission frequency of simulation data packets (simulation information), in minutes, and is used to adjust the time interval between each transmission of simulation information by the simulation test system. This is set through the human-computer interaction interface and supports real-time adjustment.

[0043] (2) GR law b-value. Gutenberg-Richter earthquake statistical law: log 10 (N) = a - b * M, where parameter b is a parameter reflecting the frequency and magnitude distribution characteristics of seismic activity. The smaller the value of b, the higher the proportion of large-magnitude events, and vice versa. The magnitude of simulated seismic events can be generated according to the above law. Here, N is the number of events with magnitude ≥ M, which determines the frequency distribution characteristics of the simulated seismic event magnitude; M is the earthquake magnitude; and a is a parameter reflecting the overall level of seismic activity.

[0044] (3) Minimum magnitude: Filter out earthquake events below this value. This can be modified according to the testing requirements.

[0045] (4) Earthquake generation boundary: Used to limit the location of the hypocenter of simulated earthquake events to a specified geographical area (a specific region, province, or a combination of different regions and provinces). This function facilitates targeted testing by focusing on a specific area.

[0046] (5) Depth parameter: Set the source depth of the simulated earthquake (unit: kilometers). It can be set to a fixed value or a random range to simulate the effects of earthquakes at different depths.

[0047] 2. Configuration of earthquake spatial distribution pattern.

[0048] This mode indicates whether to use real earthquake distribution: when enabled, the epicenter location will be randomly selected from the coordinates of fault zones predefined based on authoritative data such as the "Map of Active Fault Distribution in China"; when disabled, coordinates will be randomly generated throughout the simulation scenario (e.g., within China) to adapt to different testing needs.

[0049] 3. Monitor network configuration.

[0050] Station information configuration: A pre-configured station information database, including station coordinates and other attributes. It can automatically filter and load stations within a defined geographical boundary, providing a foundation for generating station trigger information.

[0051] By flexibly combining and configuring the above parameters, users can control the statistical regularities, boundaries, and generation time of the simulation test, thereby simulating complex seismic event sequences with different source locations, magnitudes, and times of occurrence. Based on these basic events, multi-source information related to them can be generated and sent to the system under test, including simulated P-wave and S-wave information from different stations; simulated earthquake early warning, earthquake alarm, and earthquake rapid reporting information from the seismic network; simulated earthquake information from neighboring stations; and simulated false alarm information, thus constructing a simulation test environment for comprehensively testing the functions and performance of the high-speed railway earthquake early warning and monitoring system.

[0052] II. Generation of simulated earthquake information.

[0053] 1. Overall process and input.

[0054] The data input for this part comes from all the parameters configured in the previous part. The generation and output of simulated seismic information are controlled according to the input parameters. Each generated seismic information is assigned a seismic event ID that depends on the generation time. This information is used to ensure the uniqueness of the data and facilitate subsequent evaluation and calculation.

[0055] 2. Generation of core seismic event parameters.

[0056] (1) Magnitude generation: Strictly follow the Gutenberg-Richter earthquake statistical law, calculate the probability density function of the magnitude distribution based on the configured b value and minimum magnitude parameter, and use the inverse transformation sampling algorithm to generate random magnitudes to ensure that the statistical characteristics of more frequent small magnitude events can be accurately reproduced.

[0057] (2) Source location generation: Based on the preset spatial probability model of China earthquake fault zone (that is, the earthquake spatial distribution mode is enabled at this time), the source latitude and longitude coordinates that conform to the geological tectonic activity law are generated within the selected geographical boundary.

[0058] In this embodiment of the invention, a location generation model based on the spatial distribution of geological structures is used. Instead of generating coordinates randomly, it relies on authoritative seismic geological data to ensure that the generated seismic source locations are concentrated in geologically active areas, greatly improving the spatial realism of the simulation scene.

[0059] (3) Source depth generation: Within the set depth range, the source depth is randomly generated according to the preset distribution model.

[0060] Furthermore, based on the above parameters, the earthquake occurrence time t_0 is calculated, the earthquake warning level is determined, and the initialization of the core earthquake event is completed.

[0061] 3. Generation of station simulation information.

[0062] Based on the generated core seismic event parameters and preset station coordinate information, a seismic wave propagation physical model is run to generate simulated station seismic information, including P-waves and S-waves. Then, the propagation path distance d_i from the source (lat_s, lon_s) to the i-th station (lat_i, lon_i) is calculated. Based on the P-wave velocity parameter V_p and the S-wave velocity parameter V_s, alarm information for P-waves and S-waves is generated according to the arrival times t_{p,i} = t_0 + d_i / V_p and t_{s,i} = t_0 + d_i / V_s, respectively.

[0063] The simulated station P-wave and S-wave alarm information is encapsulated into information messages and sent to the system under test strictly according to the calculated timing sequence through the communication interface protocol: at time t = t_{p,i}, the P-wave information StationP_i of station i is sent; at t = t_{s,i}, its S-wave information StationS_i is sent.

[0064] 4. Generation of network simulation information.

[0065] Based on the generated core seismic event parameters, it is also possible to dynamically simulate seismic events in the seismic network: (1) The early warning information of the typhoon network is generated in the set fault zone and area.

[0066] (2) After the earthquake early warning information is generated, the earthquake alarm information t_ws is generated according to the earthquake propagation law.

[0067] (3) The rapid reporting information of the network is generated after the early warning and alarm information of the network, and is divided into automatic rapid reporting t_wx2 and manual confirmation t_wx3.

[0068] The information at each level strictly follows the preset triggering conditions, generation algorithm and timing rules, namely t_ws=t_wp+∆t, t_wx2=t_ws+∆t, t_wx3= t_wx2+∆t, and is sent to the system under test after being encapsulated by the protocol.

[0069] In addition, the generated earthquake event IDs for early warning, alarm, and rapid reporting information will be generated and transmitted concurrently, depending on the time of generation.

[0070] 5. Generation of neighboring office simulation information.

[0071] In this embodiment of the invention, neighboring seismic information is simulated and generated as a separate generation module, still following the set core seismic parameters. However, its occurrence time is not related to the above-mentioned network and station information. It is randomly generated according to preset parameters, and also obtains the codes of its neighboring railway bureaus according to the set boundaries, and then sends alarm information to the measured system. This information is encapsulated and sent through the communication interface.

[0072] In this embodiment of the invention, the neighboring station simulation information includes various types of simulation information (e.g., P-wave, S-wave, alarm, rapid report, false alarm, etc.), and the time difference and concurrency relationship between them are precisely controlled to simulate the data flow pressure of the real system.

[0073] 6. Simulate false alarm scenario generation.

[0074] In this embodiment of the invention, the following two typical false alarm scenarios and their resolution mechanisms are supported for simulation: (1) False alarm of a single station: If only one station generates a P-wave alarm message and does not generate an S-wave alarm message within a preset time, then this station needs to automatically trigger a false alarm.

[0075] (2) False alarm from the network: If a network alarm is triggered directly without a network warning, then a false alarm from the network needs to be triggered. And no further rapid alarm information will be generated.

[0076] Once the triggering conditions are met, the system calculates the time based on the event ID when generating the simulation data. After a preset delay Δt_cancel, it confirms the generation of false alarm information, and the generation module sends the corresponding false alarm cancellation signal to the system under test. After a false alarm event is triggered, the system will block the generation of subsequent quick alarm information from the same logical source to conform to the business logic.

[0077] The above-described solution provided in this invention, through scientific and rigorous parametric modeling and timing control mechanisms, can automatically simulate complex earthquake early warning events, including multi-source parameters, multi-station responses, multi-level early warnings, alarms, rapid reporting information, neighboring station interactions, and false alarm handling. It also controls the timing relationships and concurrency between various types of information, overcoming the fundamental shortcomings of existing manual / database methods in terms of complexity, automation level, and timing controllability. This provides strong test data support for comprehensively verifying the functionality and performance of the high-speed railway earthquake early warning system (especially its reliability under complex concurrency and extreme conditions).

[0078] III. Dynamic evaluation of test results.

[0079] This part mainly achieves automatic assessment of the processing delay and operational reliability of the system under test by collecting the response data of the system under test and the simulation information generated in the second part mentioned above.

[0080] 1. Data source: (1) Simulation information recording: Assign a globally unique seismic event ID to each piece of simulation data (including station P / S waves, network rapid reports, neighboring station information, false alarm commands, etc.) and record the precise occurrence time (T_send).

[0081] (2) System response record. Obtain the processing result message of the system under test for each simulation data and its processing completion timestamp (T_received).

[0082] (3) Data matching. Based on the earthquake event ID, the two types of data records sent and received are accurately matched to lay the foundation for subsequent analysis.

[0083] 2. Delay calculation.

[0084] (1) Calculation of single data delay: Based on the matching results of the query earthquake event ID, calculate the processing delay of each data: T_delay = T_received - T_send.

[0085] (2) Total event latency calculation: For a complete earthquake scenario, calculate the latency from the initial data to the final disposal instruction, and obtain the disposal data of the entire process. Evaluate the end-to-end performance by calculating the overall latency.

[0086] 3. Statistical analysis.

[0087] (1) Key indicator statistics: Based on the latency results of all data, calculate core statistics such as average latency, maximum latency, and minimum latency.

[0088] (2) Delay distribution statistics: Statistical analysis of the number and proportion of data items whose delay falls in different intervals to characterize the stability and consistency of system performance.

[0089] 4. Reliability assessment.

[0090] (1) System survival rate: The percentage of time during which the tested system continuously responds normally without downtime or unresponsive failure during the test period.

[0091] (2) Data integrity rate: The proportion of simulated data entries that successfully received matching and processing results out of the total number of sent data entries is used to identify problems such as data loss or unprocessed data.

[0092] The above two indicators can objectively measure the stability and reliability of the system during the testing process, eliminating the need for subjective judgment.

[0093] 5. Results presentation.

[0094] Delay distribution histogram: Generates an intuitive histogram with the horizontal axis representing the delay interval and the vertical axis representing the data frequency, clearly showing the central tendency and discrete distribution of the system processing time.

[0095] Automated test reports: Output structured reports that clearly list the actual test results of key performance indicators (average / maximum / minimum latency, data integrity rate, system survival rate).

[0096] The three parts provided in this embodiment of the invention together constitute a complete, closed-loop, and automated simulation testing and evaluation scheme. It not only verifies the correctness of the function of the tested system, but also accurately quantifies its performance and reliability, providing crucial data support and decision-making basis for the effectiveness evaluation and optimization of the high-speed railway earthquake early warning system.

[0097] Through the above description of the embodiments, those skilled in the art can clearly understand that the above embodiments can be implemented by software, or by using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of the above embodiments can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, mobile hard drive, etc.), including several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0098] Example 2 This invention also provides a simulation testing and evaluation system for a high-speed railway earthquake early warning system, which is mainly used to implement the methods provided in the aforementioned embodiments, such as... Figure 2 As shown, the system mainly includes: The simulation configuration module is used to configure earthquake simulation parameters; The simulation generation module is used to synthesize seismic event parameters based on seismic simulation parameters, and generate station simulation information, network simulation information and neighboring station simulation information based on the seismic event parameters. It calculates the occurrence time of each simulation information and assigns a globally unique seismic event ID to each simulation information before sending it to the high-speed railway earthquake early warning system under test. The evaluation module is used to obtain the processing results and processing completion time of each simulation information of the tested high-speed railway earthquake early warning system. It matches the simulation information with the globally unique earthquake event ID, calculates the time delay information by combining the processing completion time and the occurrence time, and evaluates the tested high-speed railway earthquake early warning system based on the time delay information and the processing results.

[0099] Since the main technical details of this system have been described in detail in previous embodiments, they will not be repeated here.

[0100] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above.

[0101] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A simulation testing and evaluation method for a high-speed railway earthquake early warning system, characterized in that, include: Configure earthquake simulation parameters; Earthquake event parameters are synthesized based on earthquake simulation parameters, and station simulation information, network simulation information and neighboring station simulation information are generated based on the earthquake event parameters. The occurrence time of each simulation information is calculated, and each simulation information is assigned a globally unique earthquake event ID, which is then sent to the earthquake early warning system of the high-speed railway under test. The system obtains the processing results and processing completion time of each simulation information from the tested high-speed railway earthquake early warning system. It matches the simulation information with the globally unique earthquake event ID of the simulation information, calculates the time delay information by combining the processing completion time and the occurrence time, and evaluates the tested high-speed railway earthquake early warning system based on the time delay information and processing results.

2. The simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 1, characterized in that, The earthquake simulation parameters include: The basic attributes of earthquake events include: automatic transmission interval, used to control the transmission frequency of simulation information; parameter b in Gutenberg-Richter's law, which reflects the frequency-magnitude distribution characteristics of earthquake activity; minimum magnitude; earthquake generation boundary; and depth parameter. Earthquake spatial distribution model: indicates whether the actual earthquake distribution is used; The monitoring network includes the coordinates of each station.

3. A simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 1 or 2, characterized in that, The earthquake event parameters synthesized from relevant parameters based on earthquake simulation include: The magnitude, focal location, and focal depth are generated based on earthquake simulation parameters, and the time of occurrence is calculated, as well as the earthquake alarm level is determined. Specifically, based on the minimum magnitude configured in the earthquake simulation parameters and the parameter b, which reflects the frequency magnitude distribution characteristics of earthquake activity in the Gutenberg-Richter law, the magnitude distribution probability density function is calculated, and a random magnitude is generated using an inverse transformation sampling algorithm; based on the earthquake spatial distribution pattern and earthquake generation boundary in the earthquake simulation parameters, the source location conforming to the geological tectonic activity law is generated; based on the depth parameter in the earthquake simulation parameters, the source depth is randomly generated according to the preset distribution model.

4. The simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 1, characterized in that, The method for generating station simulation information based on the earthquake event parameters is as follows: Based on the generated seismic event parameters and the station coordinate information in the seismic simulation parameters, the seismic wave propagation physical model is run to generate station simulation information, i.e., simulated station seismic information. The simulated station seismic information includes P-wave and S-wave alarm information. The propagation path distance from the source to the i-th station is denoted as d_i. Based on the P-wave velocity parameter V_p and the S-wave velocity parameter V_s, the P-wave arrival time t_{p,i} = t_0 + (d_i / V_p) and the S-wave arrival time t_{s,i} = t_0 + (d_i / V_s) are used to generate P-wave and S-wave alarm information, respectively, where t_0 is the time of earthquake occurrence.

5. The simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 1, characterized in that, The method for generating network simulation information is as follows: Based on the earthquake event parameters and earthquake simulation parameters, a seismic network early warning information is generated. After the earthquake network early warning information is generated, the earthquake network alarm information is generated according to the earthquake propagation law; After the typhoon warning information and typhoon alarm information are generated, the typhoon rapid report information is generated and distinguished into automatic rapid report and manual confirmation report; Among them, the earthquake network early warning information, earthquake network alarm information, and earthquake network rapid reporting information are all earthquake network simulation information; and each of the above three information corresponds to a different occurrence time and is assigned a different earthquake event ID.

6. The simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 1, characterized in that, The method for generating neighboring railway simulation information is as follows: whether to generate neighboring railway simulation information is determined based on preset parameters. These preset parameters are probability values. If the generation of neighboring railway simulation information is triggered, the occurrence time of the neighboring railway simulation information is randomly generated according to the preset parameters. Then, the neighboring railway simulation information is generated based on the earthquake generation boundary in the earthquake simulation parameters and the obtained codes of the adjacent railway bureaus.

7. The simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 1, characterized in that, The generated simulation information also includes: false alarm simulation information; The false alarm scenarios and their resolution mechanisms corresponding to the false alarm simulation information are as follows: Single-station false alarm: If only one station generates a P-wave alarm and no S-wave alarm is generated within a preset time, the corresponding station needs to automatically trigger a false alarm. Network false alarm: If a network alarm is triggered directly without a network warning, a network false alarm needs to be triggered, and no further rapid reporting information will be generated. P-wave and S-wave alarm information are station simulation information; network warning, network alarm, and network rapid reporting information are all network simulation information. The generation probability of false alarm simulation information is controlled by preset parameters. After the triggering conditions are met, the time is calculated based on the event ID when the simulation data is generated. For a single station false alarm, the event ID when the simulation data is generated is the event ID corresponding to the P-wave early warning. For a network false alarm, the event ID when the simulation data is generated is the event ID corresponding to the network alarm. After a preset delay Δt_cancel, the corresponding false alarm simulation information is confirmed to be generated, and the corresponding false alarm cancellation signal is sent to the high-speed railway earthquake early warning system under test.

8. The simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 1, characterized in that, The simulation information is matched using a globally unique earthquake event ID, and the delay information is calculated by combining the response completion time and the occurrence time. For each simulation data, the difference between the processing completion time and the occurrence time is used as the single data delay.

9. The simulation testing and evaluation method for a high-speed railway earthquake early warning system according to claim 8, characterized in that, The evaluation of the tested high-speed railway earthquake early warning system based on time delay information and processing results includes: Statistical analysis: Based on latency information, calculate the average latency, maximum latency, and minimum latency, and count the number and proportion of data entries whose latency falls within different intervals to characterize the stability and consistency of system performance; Reliability assessment includes: system survival rate and data integrity rate; where, system survival rate is: the ratio of time during which the tested high-speed railway earthquake early warning system maintains a continuous normal response without downtime or non-response failure, and the state of continuous normal response without downtime or non-response failure is determined based on whether the corresponding simulation information is received and the handling result is obtained; data integrity rate is: the ratio of the number of simulation information messages that successfully receive matching handling results to the total number of messages sent; Based on statistical analysis, the system outputs corresponding latency distribution maps, and based on statistical analysis and reliability assessment, it outputs automated test reports.

10. A simulation testing and evaluation system for a high-speed railway earthquake early warning system, characterized in that, To implement the method according to any one of claims 1 to 9, comprising: The simulation configuration module is used to configure earthquake simulation parameters; The simulation generation module is used to synthesize seismic event parameters based on seismic simulation parameters, and generate station simulation information, network simulation information and neighboring station simulation information based on the seismic event parameters. It calculates the occurrence time of each simulation information and assigns a globally unique seismic event ID to each simulation information before sending it to the high-speed railway earthquake early warning system under test. The evaluation module is used to obtain the processing results and processing completion time of each simulation information of the tested high-speed railway earthquake early warning system. It matches the simulation information with the globally unique earthquake event ID, calculates the time delay information by combining the processing completion time and the occurrence time, and evaluates the tested high-speed railway earthquake early warning system based on the time delay information and the processing results.

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