Meteorological data processing method and device based on railway detection data platform

Abstract

The invention discloses a meteorological data processing method and device based on a railway detection data platform, which can be used in the technical field of railway engineering and safety, and the method comprises the steps: obtaining the meteorological data of a target railway region, and importing the meteorological data into a multi-layer data warehouse of the railway detection data platform for storage; determining latitude and longitude coordinates of each mileage point in the target railway area, and converting the latitude and longitude coordinates of each mileage point into plane Cartesian coordinates; determining latitude and longitude coordinates of each weather station, segmenting an area covered by each weather station to obtain a plurality of sub-areas, and converting the latitude and longitude coordinates of each sub-area into plane Cartesian coordinates; and calculating the Euclidean distance between each mileage point and each sub-region, determining a meteorological station corresponding to each mileage point, and determining accurate meteorological data of the target railway region according to the meteorological station corresponding to each mileage point and the meteorological data. According to the invention, the railway meteorological data processing capability can be improved, and timely and accurate meteorological service is provided for railway operation management.

Description

Technical Field

[0001] The present invention relates to the technical field of railway engineering and safety, and particularly to a method and device for processing meteorological data based on a railway detection data platform. Background Art

[0002] This section aims to provide background or context for the embodiments of the present invention. The description herein is not admitted to be prior art merely by virtue of being included in this section.

[0003] With the rapid expansion of the current high-speed railway network and the continuous increase in the operating mileage, railway infrastructure operation and maintenance are of great significance for ensuring railway operation safety, improving transportation efficiency, extending the service life of facilities, and enhancing service quality. Railway infrastructure is directly faced with the challenges and erosion of natural conditions for a long time, such as rainfall, snowfall, strong wind, high temperature, etc. These meteorological factors may cause problems such as damage and deformation of railway infrastructure, thus affecting the safe operation of trains. Real-time tracking and early warning of the potential impact of meteorological factors on railway infrastructure have become an essential and important link in ensuring the safe and stable operation of the railway system. This measure not only helps to timely discover potential safety hazards but also provides strong decision-making support for railway departments to ensure the safety and smoothness of railway transportation. Good infrastructure operation and maintenance are of great significance for improving railway transportation efficiency. If there are failures or problems with railway infrastructure, it will lead to train delays, cancellations, or reduced operating speeds, thus affecting the transportation capacity of the entire railway system. Summary of the Invention

[0004] Embodiments of the present invention provide a method for processing meteorological data based on a railway detection data platform to improve the processing ability of railway meteorological data and provide timely and accurate meteorological services for railway operation management. The method includes:

[0005] Obtain meteorological data of a target railway area, and import the meteorological data into a multi-layer data warehouse of the railway detection data platform for storage. The meteorological data includes a plurality of meteorological data periodically collected by each meteorological station set in the target railway area. The target railway area includes multiple railway lines, and each railway line is provided with multiple mileage points;

[0006] Obtain the longitude and latitude coordinates of the target railway area, determine the longitude and latitude coordinates of each mileage point according to the longitude and latitude coordinates of the target railway area, and convert the longitude and latitude coordinates of each mileage point into plane Cartesian coordinates;

[0007] Determine the longitude and latitude coordinates of each meteorological station according to the longitude and latitude coordinates of the target railway area, and divide the area covered by each meteorological station to obtain a plurality of sub-areas;

[0008] According to the longitude and latitude coordinates of each weather station, determine the longitude and latitude coordinates of each sub-region, and convert the longitude and latitude coordinates of each sub-region into plane Cartesian coordinates;

[0009] According to the plane Cartesian coordinates of each mileage point and the plane Cartesian coordinates of each sub-region, calculate the Euclidean distance between each mileage point and each sub-region, and respectively determine the sub-region with the smallest Euclidean distance from each mileage point;

[0010] According to the sub-region with the smallest Euclidean distance from each mileage point, determine the weather station corresponding to each mileage point. According to the weather station corresponding to each mileage point and the meteorological data, determine the accurate meteorological data of the target railway area, and analyze and process the accurate meteorological data of the target railway area through the railway detection data platform.

[0011] An embodiment of the present invention further provides a meteorological data processing device based on a railway detection data platform, which is used to improve the processing ability of railway meteorological data and provide timely and accurate meteorological services for railway operation management. The device includes:

[0012] A data acquisition module, which is used to acquire the meteorological data of the target railway area and import the meteorological data into the multi-layer data warehouse of the railway detection data platform for storage. The meteorological data includes a plurality of meteorological data periodically collected by each weather station set in the target railway area. The target railway area includes multiple railway lines, and each railway line is provided with multiple mileage points;

[0013] A mileage point conversion module, which is used to acquire the longitude and latitude coordinates of the target railway area, determine the longitude and latitude coordinates of each mileage point according to the longitude and latitude coordinates of the target railway area, and convert the longitude and latitude coordinates of each mileage point into plane Cartesian coordinates;

[0014] A segmentation module, which is used to determine the longitude and latitude coordinates of each weather station according to the longitude and latitude coordinates of the target railway area, segment the area covered by each weather station, and obtain a plurality of sub-regions;

[0015] A weather station conversion module, which is used to determine the longitude and latitude coordinates of each sub-region according to the longitude and latitude coordinates of each weather station, and convert the longitude and latitude coordinates of each sub-region into plane Cartesian coordinates;

[0016] A distance calculation module, which is used to calculate the Euclidean distance between each mileage point and each sub-region according to the plane Cartesian coordinates of each mileage point and the plane Cartesian coordinates of each sub-region, and respectively determine the sub-region with the smallest Euclidean distance from each mileage point;

[0017] An analysis and processing module is configured to determine the weather station corresponding to each mileage point according to the sub-region with the smallest Euclidean distance from each mileage point, determine the accurate weather data of the target railway area according to the weather stations corresponding to each mileage point and the weather data, and analyze and process the accurate weather data of the target railway area through the railway detection data platform.

[0018] An embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned weather data processing method based on the railway detection data platform is implemented.

[0019] An embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned weather data processing method based on the railway detection data platform is implemented.

[0020] An embodiment of the present invention further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned weather data processing method based on the railway detection data platform is implemented.

[0021] In an embodiment of the present invention, meteorological data of a target railway area is obtained and imported into a multi-layer data warehouse of a railway detection data platform for storage. The meteorological data includes a plurality of meteorological data periodically collected by each meteorological station set in the target railway area. The target railway area contains multiple railway lines, and each railway line is provided with multiple mileage points. The longitude and latitude coordinates of the target railway area are obtained, and according to the longitude and latitude coordinates of the target railway area, the longitude and latitude coordinates of each mileage point are determined, and the longitude and latitude coordinates of each mileage point are converted into plane Cartesian coordinates. According to the longitude and latitude coordinates of the target railway area, the longitude and latitude coordinates of each meteorological station are determined, the area covered by each meteorological station is segmented to obtain a plurality of sub-areas. According to the longitude and latitude coordinates of each meteorological station, the longitude and latitude coordinates of each sub-area are determined, and the longitude and latitude coordinates of each sub-area are converted into plane Cartesian coordinates. According to the plane Cartesian coordinates of each mileage point and the plane Cartesian coordinates of each sub-area, the Euclidean distance between each mileage point and each sub-area is calculated, and the sub-area with the smallest Euclidean distance from each mileage point is determined respectively. According to the sub-area with the smallest Euclidean distance from each mileage point, the meteorological station corresponding to each mileage point is determined, and according to the meteorological station corresponding to each mileage point and the meteorological data, the accurate meteorological data of the target railway area is determined, and the accurate meteorological data of the target railway area is analyzed and processed through the railway detection data platform. In this way, based on the railway monitoring data platform, meteorological data is stored, analyzed and processed. By performing coordinate transformation on the target railway area and meteorological stations, the meteorological data and railway area data are fused and analyzed, and the visualization display of meteorological data is realized, which is beneficial to improving the railway meteorological disaster prevention ability, improving the railway meteorological data processing ability, and providing timely and accurate meteorological services for railway operation management. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings:

[0023] Figure 1 is a flowchart of the meteorological data processing method based on the railway detection data platform provided in the embodiment of the present invention;

[0024] Figure 2 is a schematic diagram of storing meteorological data provided in the embodiment of the present invention;

[0025] Figure 3 is a schematic diagram of the weather change trend provided in the embodiment of the present invention;

[0026] Figure 4Schematic diagram of the meteorological data processing device based on the railway detection data platform provided in the embodiments of the present invention;

[0027] Figure 5 Block diagram of the structure of the electronic device provided in the embodiments of the present invention. Detailed implementation manners

[0028] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer and more understandable, the following further describes the embodiments of the present invention in detail with reference to the accompanying drawings. Herein, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but not to limit the present invention.

[0029] The term "and / or" in this article merely describes an association relationship, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" in this article means any one of a plurality or any combination of at least two of a plurality. For example, including at least one of A, B, and C can represent any one or more elements selected from the set composed of A, B, and C.

[0030] In the description of this specification, the terms "comprising", "including", "having", "containing", etc. are all open-ended terms, that is, they are intended to include but not limited to. The description with reference to terms such as "one embodiment", "one specific embodiment", "some embodiments", "for example", etc. means that the specific features, structures or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. The order of the steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of the steps is not limited and can be adjusted appropriately as needed.

[0031] With the rapid development of information technology, the application of emerging technologies such as big data, cloud computing, and the Internet of Things provides strong support for the acquisition, transmission, processing, and application of various data and information in the railway industry. By building a railway infrastructure detection and monitoring data platform, the correlation analysis, in-depth analysis, and intelligent analysis of detection and monitoring and operation and maintenance data are strengthened, the equipment status and evolution law are dynamically grasped, the safety risk warning ability is improved, scientific decision-making support for equipment maintenance and repair is provided, the maintenance and repair efficiency is improved, the maintenance and repair cost is reduced, and the continuous safe operation of high-speed railways is guaranteed. Based on the railway infrastructure detection and monitoring data platform, the real-time collection, transmission, processing, and analysis of meteorological information can be realized, providing timely and accurate meteorological services for railway operation management and data analysis personnel.

[0032] Based on the railway infrastructure detection and monitoring data platform, call the data service interface provided by the system of the meteorological center, and obtain the real-time, forecast, and early warning information data of the meteorology along the railway in real time according to the data change situation. The railway infrastructure detection and monitoring data platform needs to solve problems such as data exchange and processing, data storage and management, and data analysis and mining. Data storage and management requires establishing an efficient and stable database system to classify and store various meteorological data and manage them effectively. Use algorithms to associate meteorological data with railway line data, and data analysis and mining techniques to reveal the potential relationship between meteorological data and railway infrastructure failures, extract valuable information, and provide decision-making support for railway operation management departments.

[0033] Based on this, an embodiment of the present invention provides a method for processing meteorological data based on a railway detection data platform, as Figure 1 shown, including:

[0034] Step 101: Obtain the meteorological data of the target railway area, and import the meteorological data into the multi-layer data warehouse of the railway detection data platform for storage. The meteorological data includes a plurality of meteorological data periodically collected by each meteorological station set in the target railway area. The target railway area contains multiple railway lines, and each railway line is provided with multiple mileage points;

[0035] Step 102: Obtain the longitude and latitude coordinates of the target railway area, determine the longitude and latitude coordinates of each mileage point according to the longitude and latitude coordinates of the target railway area, and convert the longitude and latitude coordinates of each mileage point into plane Cartesian coordinates;

[0036] Step 103: Determine the longitude and latitude coordinates of each meteorological station according to the longitude and latitude coordinates of the target railway area, and divide the area covered by each meteorological station to obtain a plurality of sub-areas;

[0037] Step 104: Determine the longitude and latitude coordinates of each sub-area according to the longitude and latitude coordinates of each meteorological station, and convert the longitude and latitude coordinates of each sub-area into plane Cartesian coordinates;

[0038] Step 105: Calculate the Euclidean distance between each mileage point and each sub-area according to the plane Cartesian coordinates of each mileage point and the plane Cartesian coordinates of each sub-area, and respectively determine the sub-area with the smallest Euclidean distance from each mileage point;

[0039] Step 106: Determine the meteorological station corresponding to each mileage point according to the sub-area with the smallest Euclidean distance from each mileage point, determine the accurate meteorological data of the target railway area according to the meteorological station corresponding to each mileage point and the meteorological data, and analyze and process the accurate meteorological data of the target railway area through the railway detection data platform.

[0040] In specific implementation, the object of the present invention is to realize the key technologies and applications of meteorological information based on the railway infrastructure detection and monitoring data platform. The specific invention objects include:

[0041] (1) The overall technical solution and application of meteorological data in the railway infrastructure detection and monitoring data platform;

[0042] (2) The algorithm logic for associating meteorological data with railway lines.

[0043] The detection and monitoring system of high-speed railway infrastructure has been gradually improved, and the demand for more accurate, timely judgment and scientific evaluation of the service status of infrastructure has become more urgent. The operation safety and efficiency of railways are affected by weather conditions. Applying meteorological information to the detection and monitoring system of high-speed railway infrastructure provides favorable support for improving the integrated management, intelligent analysis and early warning capabilities of the operation status and performance laws of high-speed railways, and provides important references for the status analysis and evaluation, fault diagnosis and identification, and maintenance decision-making of railway infrastructure.

[0044] In view of the importance of meteorological information in the detection and monitoring system of high-speed railway infrastructure, the technical solution adopted by the present invention is to manage and algorithmically associate meteorological data based on the railway infrastructure detection and monitoring data platform, providing auxiliary support for the analysis and applications such as the temperature rise and upward arching of track slabs, the rainfall sensitivity of ballast bed detection data, the identification of subgrade frost heave, the operation status of track circuits, the minute changes in catenary geometric parameters, and the change in the detection effect of rail flaw detection, and fulfilling the requirements of the data platform for querying and visualizing meteorological data. A data warehouse design and an analysis library design are carried out on the meteorological historical data sources located in the database of the collection system in the railway infrastructure detection and monitoring data platform.

[0045] The beneficial effects of the present invention are:

[0046] (1) The meteorological information of the railway infrastructure detection and monitoring data platform can provide line weather information for the detection work of railway infrastructure detection personnel;

[0047] (2) Strengthen meteorological monitoring along the railway, establish a risk avoidance mechanism for railway meteorological disasters according to the actual situation of railway safety production, the characteristics and prevention priorities of meteorological disasters, and comprehensively improve the defense capabilities of the railway department against sudden meteorological disasters;

[0048] (3) Integrate and analyze the meteorological monitoring data along the railway, the monitoring information of meteorological stations along the railway by the meteorological department, and the railway infrastructure detection and monitoring data, and realize visual display, which is beneficial to improving the defense capabilities of railway meteorological disasters and providing relevant service guarantees for railway operation;

[0049] (4) Based on the railway infrastructure detection and monitoring data platform, deeply analyze the detection data of damage to railway facilities caused by severe weather conditions.

[0050] (5) The overall technical solution and application of meteorological data in the railway infrastructure detection and monitoring data platform can provide a reference for other data embedding platforms.

[0051] Figure 2 It is a schematic diagram of storing meteorological data provided in the embodiments of the present invention. As Figure 2 shown, in one embodiment, meteorological data of a target railway area is obtained, and the meteorological data is imported into a multi-layer data warehouse of the railway detection data platform for storage, including:

[0052] Step 201: Regularly obtain the meteorological data of the target railway area and store it in the source layer of the railway detection data platform. The railway detection data platform is used to store meteorological data through a multi-layer data warehouse;

[0053] Step 202: Generate a dimension layer data table for the current cycle, and read the CSV file of the meteorological data within the sub-cycle according to the preset sub-cycle;

[0054] Step 203: After parsing the CSV file, write it into a Hive table to form a source layer meteorological data table, and store the meteorological data through the source layer meteorological data table.

[0055] Specifically, when implementing, the line longitude and latitude table, meteorological station table, and wind force level table are set to be fully imported into the platform source layer at midnight every day, and the corresponding dimension layer data tables are generated. The hourly meteorological data new csv files in the shared disk are regularly read every hour, parsed and written into the Hive table to form a source layer meteorological data table. The line longitude and latitude table is read, and the meteorological data analysis algorithm is called to calculate the hourly meteorological data of each line respectively to obtain the meteorological data at the mileage point position of each line, and written into the detail layer. The hourly meteorological data in the detail layer is associated with the wind force level table to obtain the wind force level and wind force level name fields and written into the service layer hourly meteorological data wide table. Based on the hourly meteorological data wide table, the meteorological data of each line mileage point is statistically calculated by date and week respectively and written into the application layer. The application layer data is written into the Doris analysis library for application query.

[0056] In a specific embodiment, when querying the line meteorological data in the application layer, the following rules can be referred to: when the query time span is less than or equal to 2 months, query the line meteorological data table ADS_ZH_LINE_WEATHER_DI statistically by day; when the query time span is greater than 2 months, query the line meteorological data table ADS_ZH_LINE_WEATHER_WI statistically by week.

[0057] The meteorological historical data source comes from the collection system database, and the hourly meteorological information data comes from the meteorological center. The meteorological center regularly transmits files to the shared disk through the unified receiving system, and the meteorological format is shown in Table 1.

[0058] Table 1: Meteorological Format Description

[0059]

[0060] For the meteorological historical data sources in the collection system database and the hourly meteorological information data from the meteorological center, data warehouse design and analysis library design are carried out on the railway infrastructure detection and monitoring data platform. The data warehouse is designed as a source layer, a dimension layer, a detail layer, a service layer, and an application layer. The table designs of each layer are as follows.

[0061] Table 2: Source Layer - Line Mileage Coordinate Table

[0062] # Field Name Data Type Remarks 1 MILE Mileage double 2 MILE_CM Mileage (rounded to centimeters) double 3 POINTX Longitude double 4 POINTY Latitude double 5 LINECODE Line Code string 6 DIR_CD Line Type Code string

[0063] Table 3: Source Layer - Meteorological Station Table

[0064] # Field Name Data Type Remarks 1 STATION_NAME Meteorological Station Name string 2 PROVINCE Province string 3 CITY City string 4 STATION_ID_CD Meteorological Station Code 1 string 5 STATION_ID_D Meteorological Station Code 2 string 6 LAT Longitude double 7 LON Latitude double 8 STATION_LEVL Level string 9 CREATETIME Time string

[0065] Table 4: Source Layer - Wind Force Level Table

[0066] # Field Name Data Type Remarks 1 WIND_LEVEL Wind Level int 2 WIND_NAME Level Name string 3 NM_H Knots per Hour double 4 M_S Meters per Second double 5 KM_H Kilometers per Hour double

[0067] Table 5: Source Layer - Hourly Meteorological Information Table

[0068] # Field Name Data Type Remarks 1 STATION_NAME Meteorological Station Name string 2 STATION_ID_C Meteorological Station Code string 3 DATETIME Time string 4 TEM_1H Temperature in the Past 1 Hour / Air Temperature double 5 RHU_1H Humidity in the Past 1 Hour double 6 PRE_1H Precipitation in the Past 1 Hour double 7 WIN_D_AVG_2MI Average Wind Direction double 8 WIN_S_AVG_2MI Average Wind Speed double 9 FILE_NAME File Name string 10 DT Time string yyyyMMddHH 11 HOUR Hour int 12 IMPORT_AT Import Time string 13 DAY Date (Day) - Partition string

[0069] Table 6: Dimension Layer - Line Mileage Coordinate Table

[0070] # Field Name Data Type Remarks 1 MILE Mileage double 2 MILE_CM Mileage (rounded to centimeters) double 3 POINTX Longitude double 4 POINTY Latitude double 5 LINECODE Line Code string 6 DIR_CD Line Type Code string

[0071] Table 7: Dimension Layer - Meteorological Station Table

[0072]

[0073]

[0074] Table 8: Dimension Layer - Wind Force Level Table

[0075] # Field Name Data Type Remarks 1 WIND_LEVEL Wind Level int 2 WIND_NAME Level Name string 3 NM_H Knots per Hour double 4 M_S Meters per Second double 5 KM_H Kilometers per Hour double

[0076] Table 9: Detail Layer - Hourly Line Meteorological Data Table

[0077]

[0078] Table 10: Service Layer - Hourly Line Meteorological Data Table

[0079]

[0080] Table 11: Service Layer - Meteorological Early Warning Data Table

[0081]

[0082]

[0083] Table 12: Application Layer - Line Meteorological Data Sheet (Daily)

[0084]

[0085]

[0086] In one embodiment, converting the longitude and latitude coordinates of each mileage point into planar Cartesian coordinates includes:

[0087] Converting the longitude and latitude coordinates of each mileage point into radians respectively;

[0088] Using the Miller projection, converting the radians of each mileage point into actual distances to determine the planar Cartesian coordinates of each mileage point.

[0089] Before determining the longitude and latitude coordinates of each weather station according to the longitude and latitude coordinates of the target railway area, it further includes:

[0090] Preprocessing multiple meteorological data periodically collected by each weather station to remove problematic meteorological data.

[0091] Dividing the area covered by each weather station to obtain multiple sub - areas, including:

[0092] Evenly dividing the area covered by each weather station into a preset number of square areas, and determining the row and column positions of each square area;

[0093] According to the row and column positions of each square area, determining the longitude and latitude coordinates of each square area to obtain multiple sub - areas.

[0094] In specific implementation, first, the quality of meteorological data is managed. Meteorological data quality problems include issues such as invalid base stations, duplicate base stations, incomplete base station code tables, longitude and latitude matching, etc. Information of weather stations containing invalid data is excluded. Invalid data includes missing measurements and data that are not to be observed under certain conditions; when matching weather stations in the meteorological details table with the weather station code table, non - unique situations may occur, and the same weather station name may correspond to two different longitude and latitude information. Duplicate weather station information is screened, consulted with the meteorological center and deleted; some weather station names in the meteorological details table do not exist in the weather station code table. Retain the weather stations in the weather station code table in the meteorological details table and exclude the remaining weather stations.

[0095] In algorithm matching, the calculation logic of longitude and latitude is different from that of planar coordinates. The longitude and latitude coordinates are converted into a planar Cartesian coordinate system. The coordinate system conversion algorithm is as follows (the same applies to the conversion of line longitude and latitude).

[0096] First, convert the longitude and latitude into radians respectively:

[0097] x = lon × π / 180

[0098] y = lat × π / 180

[0099] Convert to the Miller projection:

[0100] y 1 = 1.25 × log(tan(0.25 × Π + 0.4 × y))

[0101] Convert the radians into the actual distance:

[0102] dikaerX = (W / 2) + (W / (2 * π)) * x

[0103] dikaerY = (H / 2) + (H / (2 * mill)) * y1

[0104] Where lon is the longitude, lat is the latitude, x is the radian of the longitude, y is the radian of the latitude, y1 is the Miller projection of the latitude, and DikaerY is the actual coordinate of the latitude.

[0105] In a specific embodiment, the area where the weather station is located in the planar coordinate system is divided into 10,000 uniform square areas, and each square area is marked with reference to the naming rules of the elements in the matrix. For example, the square area in the i-th row and j-th column is R ij . There is a set of longitude and latitude information every 100 meters on the line. According to the above calculation process, the line longitude and latitude are converted into a planar Cartesian coordinate system, and the square area where each set of Cartesian coordinates of the line is located and the information of the nearest weather station in the adjacent areas are found. For example, the area where a set of line longitude and latitude Cartesian coordinates is located is R 400 500 , and the adjacent areas are R 400 500 , R 399 499 , R 399 500 , R 399 501 , R 400 499 , R 400 501 , R 401 499 , R 401 500 , R401 501 Calculate the Euclidean distances between the longitude and latitude coordinates in this set of Cartesian coordinate systems and all meteorological stations in the adjacent areas. If there are two points A(X 1 , Y 1 ) and B(X 1 , Y 1 ), then the Euclidean distance between the two points Locate the meteorological station through the minimum Euclidean distance, and associate the located meteorological station with meteorological information such as temperature, precipitation, humidity, wind force, etc.

[0106] In one embodiment, analyze and process the meteorological data of the target railway area through the railway detection data platform, including:

[0107] Determine the trend of track geometry changes in the target railway area through the railway detection data platform, and conduct correlation analysis on the trend of track geometry changes in the target railway area and the accurate meteorological data;

[0108] Visually display the analysis results through the railway detection data platform.

[0109] Specifically, when implemented, the equipment status comprehensive map based on the railway infrastructure detection and monitoring data platform mainly displays ledger information, waveform information, key prompts, temperature, precipitation and other information corresponding to the mileage as Figure 3 shown. By conducting correlation analysis on the data of the track geometry change trend and weather conditions within a specific time period, the disease conditions of the track under different weather conditions can be predicted. For example, under continuous rainfall or high-temperature weather, the track may deform due to water penetration or thermal expansion and contraction. This prediction helps to take maintenance measures in advance to prevent the track geometry changes from affecting the safe operation of high-speed trains. According to the correlation data of weather conditions and track geometry change trends, a more accurate maintenance plan can be formulated. Before the arrival of bad weather, necessary inspections and repairs can be carried out on the track in advance to reduce track damage and train delays caused by weather factors.

[0110] Based on the GIS comprehensive display of the railway infrastructure detection and monitoring data platform, it mainly shows TQI, temperature, and precipitation information for railway bureaus and stations. Associating meteorological data with railway lines and rendering them through GIS maps can greatly enhance the intuitive perception and understanding of the weather conditions of running trains. The GIS map can display the weather conditions along the railway line in real time, including key information such as rainfall, wind speed, temperature, and humidity. In this way, both railway dispatchers and passengers can understand the current and future weather conditions at any time, and thus make corresponding decisions and adjustments. When encountering bad weather or sudden meteorological events, the GIS map can display warning information in real time, including warning levels, affected areas, and expected durations. In this way, the railway department can quickly take response measures, such as adjusting train operation plans, strengthening equipment inspection and maintenance, etc., to ensure the safe operation of trains.

[0111] In the embodiments of the present invention, a meteorological data processing device based on a railway detection data platform is also provided, as described in the following embodiments. Since the principle of this device for solving problems is similar to that of the meteorological data processing method based on a railway detection data platform, the implementation of this device can refer to the implementation of the meteorological data processing method based on a railway detection data platform, and the repeated parts will not be elaborated.

[0112] Figure 4 It is a schematic diagram of the meteorological data processing device based on a railway detection data platform provided in the embodiments of the present invention, as Figure 4 shown, the device includes:

[0113] A data acquisition module 401, configured to obtain meteorological data of a target railway area, import the meteorological data into a multi-layer data warehouse of the railway detection data platform for storage. The meteorological data includes a plurality of meteorological data periodically collected by each meteorological station set in the target railway area. The target railway area includes multiple railway lines, and each railway line is provided with multiple mileage points;

[0114] A mileage point conversion module 402, configured to obtain the longitude and latitude coordinates of the target railway area, determine the longitude and latitude coordinates of each mileage point according to the longitude and latitude coordinates of the target railway area, and convert the longitude and latitude coordinates of each mileage point into plane Cartesian coordinates;

[0115] A segmentation module 403, configured to determine the longitude and latitude coordinates of each meteorological station according to the longitude and latitude coordinates of the target railway area, segment the area covered by each meteorological station to obtain a plurality of sub-areas;

[0116] A meteorological station conversion module 404, configured to determine the longitude and latitude coordinates of each sub-area according to the longitude and latitude coordinates of each meteorological station, and convert the longitude and latitude coordinates of each sub-area into plane Cartesian coordinates;

[0117] A distance calculation module 405, configured to calculate the Euclidean distance between each mileage point and each sub-region according to the planar Cartesian coordinates of each mileage point and the planar Cartesian coordinates of each sub-region, and respectively determine the sub-region with the minimum Euclidean distance from each mileage point;

[0118] An analysis and processing module 406, configured to determine the weather station corresponding to each mileage point according to the sub-region with the minimum Euclidean distance from each mileage point, determine the accurate weather data of the target railway region according to the weather station corresponding to each mileage point and the weather data, and analyze and process the accurate weather data of the target railway region through the railway detection data platform.

[0119] In one embodiment, the data acquisition module 401 is specifically configured to:

[0120] Regularly acquire the weather data of the target railway region and store it in the source layer of the railway detection data platform, where the railway detection data platform is used to store the weather data through a multi-layer data warehouse;

[0121] Generate a dimension layer data table for the current period, and read the CSV file of the weather data within the sub-period according to a preset sub-period;

[0122] Parse the CSV file and write it into a Hive table to form a source layer weather data table, and store the weather data through the source layer weather data table.

[0123] In one embodiment, the mileage point conversion module 402 is specifically configured to:

[0124] Convert the longitude and latitude coordinates of each mileage point into radians respectively;

[0125] Adopt the Miller projection to convert the radians of each mileage point into the actual distance, and determine the planar Cartesian coordinates of each mileage point.

[0126] In one embodiment, the data acquisition module 401 is further configured to:

[0127] Preprocess multiple weather data periodically collected by each weather station to remove problematic weather data.

[0128] In one embodiment, the segmentation module 403 is specifically configured to:

[0129] Evenly divide the area covered by each weather station into a preset number of square areas, and determine the row and column positions of each square area;

[0130] According to the row and column positions of each square area, determine the longitude and latitude coordinates of each square area to obtain multiple sub-regions.

[0131] In one embodiment, the analysis and processing module 406 is specifically configured to:

[0132] Determine the track geometry change trend of the target railway area through the railway detection data platform, and conduct correlation analysis on the track geometry change trend of the target railway area and the accurate meteorological data;

[0133] Visualize the analysis results through the railway detection data platform.

[0134] Based on the foregoing inventive concept, as Figure 5 shown, the present invention also proposes a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored on the memory 510 and operable on the processor 520. When the processor 520 executes the computer program 530, the foregoing meteorological data processing method based on the railway detection data platform is implemented.

[0135] An embodiment of the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the foregoing meteorological data processing method based on the railway detection data platform is implemented.

[0136] An embodiment of the present invention also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the foregoing meteorological data processing method based on the railway detection data platform is implemented.

[0137] In summary, in the embodiments of the present invention, meteorological data of a target railway area is obtained and imported into a multi-layer data warehouse of a railway detection data platform for storage. The meteorological data includes a plurality of meteorological data periodically collected by each meteorological station arranged in the target railway area. The target railway area contains multiple railway lines, and each railway line is provided with multiple mileage points. The longitude and latitude coordinates of the target railway area are obtained, and according to the longitude and latitude coordinates of the target railway area, the longitude and latitude coordinates of each mileage point are determined, and the longitude and latitude coordinates of each mileage point are converted into plane Cartesian coordinates. According to the longitude and latitude coordinates of the target railway area, the longitude and latitude coordinates of each meteorological station are determined, the area covered by each meteorological station is segmented to obtain a plurality of sub-areas. According to the longitude and latitude coordinates of each meteorological station, the longitude and latitude coordinates of each sub-area are determined, and the longitude and latitude coordinates of each sub-area are converted into plane Cartesian coordinates. According to the plane Cartesian coordinates of each mileage point and the plane Cartesian coordinates of each sub-area, the Euclidean distance between each mileage point and each sub-area is calculated, and the sub-area with the minimum Euclidean distance from each mileage point is determined respectively. According to the sub-area with the minimum Euclidean distance from each mileage point, the meteorological station corresponding to each mileage point is determined, and according to the meteorological station corresponding to each mileage point and the meteorological data, the accurate meteorological data of the target railway area is determined, and the accurate meteorological data of the target railway area is analyzed and processed through the railway detection data platform. In this way, based on the railway monitoring data platform, meteorological data is stored, analyzed and processed. By performing coordinate transformation on the target railway area and meteorological stations, the meteorological data and railway area data are fused and analyzed to realize the visual display of meteorological data, which is beneficial to improving the railway meteorological disaster prevention ability, improving the railway meteorological data processing ability, and providing timely and accurate meteorological services for railway operation management.

[0138] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented 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.

[0139] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for realizing the process Figure 1One or more processes and / or boxes Figure 1 Apparatus for the functions specified in one or more boxes

[0140] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the processes Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes

[0141] These computer program instructions may also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 One or more processes and / or boxes Figure 1 One or more boxes

[0142] The specific embodiments described above further elaborate on the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A meteorological data processing method based on a railway detection data platform, characterized in that: include: Acquire meteorological data of a target railway area, and import the meteorological data into a multi-layer data warehouse of a railway detection data platform for storage, wherein the meteorological data includes a plurality of meteorological data periodically collected by meteorological stations arranged in the target railway area, wherein the target railway area includes a plurality of railway lines, and each railway line is provided with a plurality of mileage points; Obtain the longitude and latitude coordinates of the target railway area, determine the longitude and latitude coordinates of each mileage point according to the longitude and latitude coordinates of the target railway area, and convert the longitude and latitude coordinates of each mileage point into plane Cartesian coordinates; According to the longitude and latitude coordinates of the target railway area, the longitude and latitude coordinates of each meteorological station are determined, and the area covered by each meteorological station is divided to obtain multiple sub-areas; According to the longitude and latitude coordinates of each meteorological station, the longitude and latitude coordinates of each sub-area are determined, and the longitude and latitude coordinates of each sub-area are converted into plane Cartesian coordinates; According to the plane Cartesian coordinates of each mileage point and the plane Cartesian coordinates of each sub-area, the Euclidean distance between each mileage point and each sub-area is calculated, and the sub-area with the smallest Euclidean distance to each mileage point is determined respectively; According to the sub-area with the smallest Euclidean distance to each mileage point, the meteorological station corresponding to each mileage point is determined. According to the meteorological station and meteorological data corresponding to each mileage point, the precise meteorological data of the target railway area is determined, and the precise meteorological data of the target railway area is analyzed and processed through the railway detection data platform.

2. The method according to claim 1, characterized in that Obtain meteorological data for the target railway area and import the meteorological data into the multi-layer data warehouse of the railway inspection data platform for storage, including: Obtaining meteorological data of the target railway area at regular intervals and storing it in the source layer of the railway detection data platform, wherein the railway detection data platform is used to store meteorological data through a multi-layer data warehouse; Generate the dimension layer data table of the current period, and read the CSV file of meteorological data within the sub-period according to the preset sub-period; The CSV file is parsed and written into the Hive table to form a source layer meteorological data table, and the meteorological data is stored in the source layer meteorological data table.

3. The method according to claim 1, characterized in that Convert the latitude and longitude coordinates of each mileage point into plane Cartesian coordinates, including: Convert the latitude and longitude coordinates of each mileage point into radians; Miller projection is used to convert the arc of each mileage point into actual distance and determine the plane Cartesian coordinates of each mileage point.

4. The method according to claim 1, characterized in that According to the latitude and longitude coordinates of the target railway area, before determining the latitude and longitude coordinates of each meteorological station, it also includes: The multiple meteorological data collected periodically by each meteorological station are pre-processed to remove problematic meteorological data.

5. The method according to claim 1, characterized in that The area covered by each weather station is divided into multiple sub-areas, including: Evenly divide the area covered by each weather station into a preset number of square areas, and determine the row and column position of each square area; According to the row and column positions of each square area, the longitude and latitude coordinates of each square area are determined to obtain a plurality of sub-areas.

6. The method according to claim 1, characterized in that The railway inspection data platform is used to analyze and process the meteorological data of the target railway area, including: Determine the track geometry change trend of the target railway area through the railway inspection data platform, and conduct correlation analysis between the track geometry change trend of the target railway area and accurate meteorological data; The analysis results are visualized through the railway inspection data platform.

7. A meteorological data processing device based on a railway detection data platform, characterized in that: include: A data acquisition module is used to obtain meteorological data of a target railway area and import the meteorological data into a multi-layer data warehouse of a railway detection data platform for storage, wherein the meteorological data includes a plurality of meteorological data periodically collected by meteorological stations arranged in the target railway area, wherein the target railway area includes a plurality of railway lines, and each railway line is provided with a plurality of mileage points; The mileage point conversion module is used to obtain the longitude and latitude coordinates of the target railway area, determine the longitude and latitude coordinates of each mileage point according to the longitude and latitude coordinates of the target railway area, and convert the longitude and latitude coordinates of each mileage point into plane Cartesian coordinates; A segmentation module is used to determine the longitude and latitude coordinates of each meteorological station according to the longitude and latitude coordinates of the target railway area, and to segment the area covered by each meteorological station to obtain multiple sub-areas; A weather station conversion module is used to determine the longitude and latitude coordinates of each sub-area according to the longitude and latitude coordinates of each weather station, and convert the longitude and latitude coordinates of each sub-area into plane Cartesian coordinates; A distance calculation module is used to calculate the Euclidean distance between each mileage point and each sub-area according to the plane Cartesian coordinates of each mileage point and the plane Cartesian coordinates of each sub-area, and respectively determine the sub-area with the smallest Euclidean distance to each mileage point; The analysis and processing module is used to determine the meteorological station corresponding to each mileage point based on the sub-area with the smallest Euclidean distance from each mileage point, determine the precise meteorological data of the target railway area based on the meteorological station and meteorological data corresponding to each mileage point, and analyze and process the precise meteorological data of the target railway area through the railway detection data platform.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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