Railway track information extraction method and system, electronic equipment and storage medium

Abstract

The invention discloses a railway track information extraction method and system, electronic equipment and a storage medium, and the system comprises a satellite monitoring unit, a meteorological monitoring unit, a central processing unit, an information extraction unit, an information calling unit and a display management unit. Therefore, the railway track information corresponding to the rail section which is highly influenced by the environmental factor risk is extracted in a targeted manner, the efficiency of extracting the railway track information is improved, and the data processing amount is reduced; after information extraction, integrated parallel processing and deep analysis of feature information are carried out by constructing a risk influence function of dynamic change of environmental factors on a rail structure under a specific geographical condition, so that the data measurement time is shortened, the data processing efficiency is improved, and the reliability of the system is improved. And in combination with real-time meteorological monitoring, pertinence and timeliness of rail risk management and maintenance are ensured, so that safety and stability of rail operation are ensured.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a railway track information extraction method, system, electronic equipment and storage medium. Background Art

[0002] Railway tracks, as an integral engineering structure, are laid on the roadbed and play a guiding role in train operation. Railway tracks in specific geographical areas are greatly affected by the environment and climate. For example, the looser the geological state in cold climate areas, the more likely it is that groundwater will freeze and swell, resulting in unstable foundations and the appearance of "floating tracks". In hot climate areas, loose geology will make the rails easy to deform, and when the high-temperature area suddenly cools down, the rails will become brittle. When the geology in a geographical area is loose and the terrain slope is high, when the rainfall in the climate suddenly increases, it may cause risks such as soil loss and mudslides, as well as the sinking or tilting of the railway track roadbed.

[0003] However, it is difficult to extract the geographical areas and corresponding railway sections that are most affected by environmental factors during the extraction process of existing railway track information. Since the environmental climate will have different impacts on railway tracks in different geographical areas, the meteorological monitoring of railway tracks can only conduct an overall analysis of the environmental climate, lacking the correlation between environmental climate factors and regional geographical conditions, and lacking targeted risk assessment of railway sections in geographical areas. Among them, the low efficiency of information extraction will lead to data processing overload and delayed emergency response, which will lead to untimely railway operation scheduling and management, affecting people's railway travel;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to solve the technical defects of the existing railway track information extraction, the lack of correlation between environmental climate factors and regional geographical conditions, the targeted risk assessment of the railway track sections in the geographical area, and the resulting data processing overload, emergency response delay, and untimely railway track operation scheduling management. The present invention establishes a correlation factor between regional geography and environmental climate, thereby targetedly extracting the railway track information corresponding to the railway track sections with a high degree of risk influence of environmental factors, thereby improving the efficiency of railway track information extraction and reducing the data processing volume; after the information is extracted, the risk impact function of the dynamic change of environmental factors on the railway track structure under specific geographical conditions is constructed, and the integrated parallel processing and in-depth analysis of the feature information are performed, thereby reducing the data calculation time, improving the data processing efficiency, and combining with real-time meteorological monitoring to ensure the targeted and timely maintenance of railway risk management, thereby ensuring the safety and stability of railway operation.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for extracting railway track information comprises the following steps:

[0008] Step 1: Conduct satellite remote sensing monitoring of the railway track: The satellite monitoring unit obtains a global satellite image of the railway track through satellite remote sensing technology, and constructs an image processing model to process the global satellite image of the railway track, thereby obtaining railway track information, wherein the railway track information includes regional geographical parameters and railway track geographical parameters;

[0009] Step 2: Meteorological monitoring of the area where the railway track is located: the meteorological monitoring unit monitors the regional environmental climate state of the railway track, thereby obtaining environmental climate data;

[0010] Step 3: Preliminary analysis of railway track information and environmental climate data: Preliminary analysis of regional geographical parameters and environmental climate data is performed to obtain the correlation factors between the environmental climate factors of the area where the railway track is located and the regional geographical structure, and a threshold of the correlation factor is set, so as to extract the railway track information of some geographical areas where the correlation factor exceeds the threshold, mark it as railway track feature information, and then establish an information extraction database and store the railway track feature information in the information extraction database;

[0011] Step 4: In-depth analysis of the extracted rail feature information and its environmental climate data: by combining the rail geographic parameters of the extracted rail feature information with the environmental climate data corresponding to the geographical area, a risk impact function of the dynamic change of environmental climate on the rail section under specific geographical conditions is constructed, so as to evaluate the real-time risk situation of each rail section in the extracted geographical area, generate a risk warning signal of a corresponding level, set a threshold for the risk warning signal level, and when the level of the risk warning signal exceeds the threshold, set an identifier for the rail section and store it in the information extraction database;

[0012] Step 5, calling the rail section identifier and its corresponding railway track information: calling the railway track information of the rail section with the identifier by receiving the risk warning signal, then performing the management design of the railway track, and generating the corresponding early warning management signal.

[0013] Furthermore, the specific process of building the image processing model is as follows:

[0014] Regional geographical parameters include the geological looseness and terrain slope of the area where the railway track is located; rail geographical parameters include rail transverse slope and rail longitudinal slope;

[0015] Sa1, input global satellite images of railway tracks into the image processing model;

[0016] The global satellite image of the railway track is divided into N1 characteristic areas, and the global satellite image of the railway track includes image data corresponding to the N1 characteristic areas; wherein the image data includes band reflection brightness values ​​and spectral reflection curves;

[0017] The spectral reflectance curve is a curve in which the ratio of reflected luminous flux to incident luminous flux varies with wavelength, that is, the horizontal axis is wavelength and the vertical axis is reflectivity;

[0018] Through satellite remote sensing technology, light of n0 characteristic bands is emitted to any characteristic area J, and then the reflected light is received to construct a spectral reflectance curve, and the spectral reflectance curve of the characteristic area J is marked as GPj;

[0019] Set characteristic spectral curves corresponding to n1 geological types and integrate them into a geological spectral library, mark the characteristic spectral curve corresponding to geological type e as GPe, and mark the geological looseness of geological type e as ηe;

[0020] Sa2, by comparing the spectral reflectance curve GPj of the characteristic area J with the characteristic spectral curve in the geological spectrum library, the geological type of the characteristic area J is determined, thereby obtaining the geological looseness η1 of the characteristic area J; and then combining the band reflectance brightness value of the characteristic area J to obtain the terrain slope η2 of the characteristic area J;

[0021] Sa3, any feature area J includes N2 rail sections, any rail section is marked as i, and the rail transverse slope δ1 of the rail section i is obtained by performing brightness comparison on the areas on both sides of the rail section i; the rail longitudinal slope δ2 of the rail section i is obtained by performing brightness comparison on the areas on both ends of the rail section i;

[0022] Sa4, the image processing model outputs the regional geographic parameters of the N1 feature areas and the rail geographic parameters of the N2 rail sections of the feature areas, and integrates them into railway track information.

[0023] Furthermore, the specific process of preliminarily analyzing the railway track information and environmental climate data and extracting the railway track characteristic information is as follows:

[0024] Environmental climate parameters include temperature, humidity and rainfall. The temperature, humidity and rainfall of feature area J are marked as WDj, SDj and LYj respectively;

[0025] Through the regional geographic parameters of characteristic area J and the environmental climate parameters of characteristic area J, an association matching degree analysis is established to obtain the correlation factor between environmental climate and regional geography. The specific process is as follows:

[0026] Regional geographic parameters include geological looseness η1 and terrain slope η2 of characteristic area J;

[0027] The first correlation factor ψ1 is obtained through the temperature WDj of the characteristic area J and the regional geographical parameters, and the second correlation factor ψ2 is obtained through the humidity SDj and the rainfall LYj of the characteristic area J and the regional geographical parameters;

[0028] The thresholds of the first correlation factor ψ1 and the second correlation factor ψ2 are set to h1 and h2 respectively, and the first correlation factor ψ1>h1 of the feature region J is marked as the first condition, and the second correlation factor ψ2>h2 of the feature region J is marked as the second condition; when the feature region J satisfies any one of the first condition and the second condition, the railway track information corresponding to the feature region J is extracted; otherwise, it is not extracted;

[0029] The number of the feature regions to be extracted is marked as M1, and the railway track information of the M1 feature regions of the railway track global satellite image is extracted and marked as railway track feature information.

[0030] Furthermore, the rail feature information extracted by in-depth analysis and the specific process are as follows:

[0031] Any extracted characteristic region is marked as Jt, the region Jt whose characteristic environmental climate data includes N2 rail sections, and any rail section of the characteristic region Jt is marked as Qi;

[0032] Through the regional geographic parameters and environmental climate data of the characteristic area Jt, the correlation factor of the characteristic area Jt is obtained to evaluate the risk impact of the environmental climate on the regional geography, and then the rail geographical parameters of each rail section of the characteristic area Jt are combined to obtain the rail influence coefficient of each rail section;

[0033] The first and second correlation factors of the feature area Jt are marked as ψt1 and ψt2 respectively, and the rail transverse slope and rail longitudinal slope of the rail section Qi are marked as δ1 Qi , δ2 Qi , thereby obtaining the risk impact function F0 of the feature area Jt;

[0034] Then, the rail geographical parameters of the rail section Qi are substituted into the risk influence function F0 to obtain the rail influence coefficient Xqi of the rail section Qi;

[0035] Set the evaluation interval of the rail influence coefficient Xqi, evaluate the real-time risk situation of the rail section Qi in the characteristic area Jt through interval comparison, and generate a risk warning signal of the corresponding level.

[0036] A railway track information extraction system comprises a satellite monitoring unit, a meteorological monitoring unit, a central processing unit, an information extraction unit, an information calling unit and a display management unit, wherein the satellite monitoring unit, the meteorological monitoring unit, the central processing unit, the information extraction unit, the information calling unit and the display management unit are communicatively connected, and the system applies a railway track information extraction method as described above;

[0037] The satellite monitoring unit is used to conduct satellite remote sensing monitoring of railway tracks, construct a global satellite map of railway tracks, and obtain regional geographic parameters and railway track geographic parameters through image analysis;

[0038] The meteorological monitoring unit is used to monitor the meteorological conditions in the area where the railway tracks are located and obtain environmental climate data;

[0039] The central processor is used to preliminarily analyze the railway track information and environmental climate data to obtain the correlation and matching degree between the environmental climate and regional geography of the evaluated geographical area; then conduct in-depth analysis of the feedback rail feature information to evaluate the real-time risk situation of each rail section in the extracted geographical area, thereby generating a risk warning signal; then set identifiers for the rail sections and conduct management design, thereby generating an early warning management signal;

[0040] The information extraction unit is used to extract the railway track information of some geographical areas where the correlation matching degree exceeds the threshold, mark it as railway track feature information, and then store the railway track feature information and the railway track section with the identifier set in the information extraction database;

[0041] The information calling unit is used to call the rail feature information, the rail section identifier and the corresponding railway track information, and feed the rail feature information back to the central processor for in-depth analysis, and feed the railway track information with the identifier back to the central processor for management design;

[0042] The display management unit is used to receive risk warning signals and early warning management signals, and perform corresponding display and management operations.

[0043] An electronic device includes a memory, a display, a central processing unit, and a computer program stored in the memory and executable on the processor, wherein the central processing unit implements the above-mentioned railway track information extraction method when executing the program.

[0044] A computer-readable storage medium stores a computer program, which, when executed by a central processing unit, implements a railway track information extraction method as described above.

[0045] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0046] The present invention analyzes the geographical environment of the area where the rails are located through satellite remote sensing images, establishes the correlation factor between the regional geography and the environmental climate, and thus specifically extracts the railway track information corresponding to the rail sections that are highly affected by the risk of environmental factors, thereby improving the efficiency of railway track information extraction and reducing the amount of data processing; after the information is extracted, the risk impact function of the dynamic change of environmental factors on the rail structure under specific geographical conditions is constructed, and the integrated parallel processing and in-depth analysis of the characteristic information are performed, thereby reducing the data calculation time and improving the data processing efficiency, and combining with real-time meteorological monitoring to ensure the pertinence and timeliness of rail risk management and maintenance, thereby ensuring the safety and stability of rail operation;

[0047] Among them, the present invention realizes automatic real-time monitoring of the risk of dynamic environmental changes affecting the rails by performing regional targeted extraction and analysis of rail track information and risk positioning, thereby extracting rail track information of high-risk rail sections in a targeted manner, facilitating efficient emergency response and auxiliary scheduling decisions, and ensuring the safety of rail operation; then, by setting identifiers for rail sections and performing long-term risk prediction on rail sections with identifiers and their rail track information, corresponding track maintenance plan management is provided to ensure the continuous stability of rail operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram showing the module connection of the system of the present invention is shown;

[0049] Figure 2 A schematic diagram of the process steps of the method of the present invention is shown. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] Embodiment 1:

[0052] like Figure 1-Figure 2 As shown, a railway track information extraction method comprises the following steps:

[0053] S1, satellite remote sensing monitoring of railway tracks: the satellite monitoring unit obtains a global satellite image of the railway track through satellite remote sensing technology, and constructs an image processing model to process the global satellite image of the railway track, thereby obtaining railway track information, wherein the railway track information includes regional geographical parameters and railway track geographical parameters;

[0054] Regional geographical parameters include the geological looseness and terrain slope of the area where the railway track is located;

[0055] The rail geographical parameters include rail transverse slope and rail longitudinal slope;

[0056] The specific process of building an image processing model is as follows:

[0057] Sa1, input global satellite images of railway tracks into the image processing model;

[0058] The global satellite image of the railway track is divided into N1 characteristic areas, and the global satellite image of the railway track includes image data corresponding to the N1 characteristic areas; wherein the image data includes band reflection brightness values ​​and spectral reflection curves;

[0059] The spectral reflectance curve is a curve in which the ratio of reflected luminous flux to incident luminous flux varies with wavelength, that is, the horizontal axis is wavelength and the vertical axis is reflectivity;

[0060] Through satellite remote sensing technology, light of n0 characteristic bands is emitted to any characteristic area J, and then the reflected light is received to construct a spectral reflectance curve, and the spectral reflectance curve of the characteristic area J is marked as GPj;

[0061] Set characteristic spectral curves corresponding to n1 geological types and integrate them into a geological spectral library. Mark the characteristic spectral curve corresponding to geological type e as GPe, and mark the geological looseness of geological type e as ηe; (the geological looseness of the geological type is determined by testing the soil looseness of the corresponding geology after field soil sampling, and then using it as the geological looseness to preset different geological types according to experience)

[0062] For example, in the 350-600nm band, the soil spectral reflectance curve has a monotonically increasing trend with the increase of wavelength, especially near the 560nm band, where there are absorption peaks of varying strengths, which helps to identify different components and states in the soil, thereby determining different geological types;

[0063] Sa2, by comparing the spectral reflectance curve GPj of the characteristic area J with the characteristic spectral curve in the geological spectrum library, the geological type of the characteristic area J is determined, thereby obtaining the geological looseness η1 of the characteristic area J; and then combining the band reflectance brightness value of the characteristic area J to obtain the terrain slope η2 of the characteristic area J;

[0064] Among them, if the geological type of the characteristic area J is determined to be e, the geological looseness of the characteristic area J is η1 = ηe;

[0065] The calculation formula of the preset terrain slope η2 is:

[0066] Among them, g refers to the light label of any characteristic band, LD g max refers to the maximum value of the reflected light brightness of the characteristic band g in the characteristic area J, LD g min refers to the minimum value of the brightness of the reflected light of the characteristic band g in the characteristic area J, and ΔDSg refers to the maximum value of the brightness of the reflected light of the characteristic band g in the characteristic area J. g The coordinate point of max and the minimum value LD g The distance difference between the coordinate points where min is located can be calculated by locating the pixels through the global satellite image of the railway track; ωg refers to the weight coefficient of the characteristic band g, which is preset according to experience after being verified by a large amount of experimental data, and ωg is greater than 0;

[0067] The geological looseness η1 and terrain slope η2 of the characteristic area J are integrated into the regional geographic parameters of the characteristic area J;

[0068] Sa3, any feature area J includes N2 rail sections, any rail section is marked as i, and the rail transverse slope δ1 of the rail section i is obtained by performing brightness comparison on the areas on both sides of the rail section i; the rail longitudinal slope δ2 of the rail section i is obtained by performing brightness comparison on the areas on both ends of the rail section i;

[0069] The calculation formula for the preset rail cross slope δ1 is: The number of brightness value coordinate points extracted from the two sides of the preset rail section i is m0, LD p1 Indicates the reflection brightness value of a specific band at any point in the area on one side of the track section i, LD p2 It represents the reflection brightness value of a specific band at any point in the area on the other side of the railway section i. The specific band is preset and selected according to the geological type of the characteristic area J and in combination with a large amount of data sampling experience. The band light with finer image brightness data after band reflection is preferred. For example, the 600-1000nm band is selected. The curve of this band is gentle, almost straight, and has no obvious absorption, which is suitable for observing the overall reflection characteristics of the soil; ωp is the first correction coefficient and the value range is ωp∈(0,1). The first correction coefficient is preset in combination with the width of the railway track. When the width of the railway track is larger, the preset value of ωp is closer to 0; when the difference in the overall brightness of the areas on both sides of the railway section i is higher, the cross slope δ1 of the railway track is higher;

[0070] The calculation formula for the preset rail longitudinal slope δ2 is: The number of brightness value coordinate points extracted from the two end areas of the preset rail section i is m1, LD q1 It represents the reflection brightness value of a specific band at any point in the area at one end of the track section i, LD q2Indicates the reflection brightness value of a specific band at any point in the other end area of ​​the rail section i. The specific band is consistent with the specific band of the rail transverse slope δ1. Similarly, it is selected according to the geological type of the characteristic area J, and the band light with finer image brightness data after band reflection is preferred; ωq is the second correction coefficient and the value range is ωq∈(0,1). The second correction coefficient is preset in combination with the length of the rail. When the length of the rail is longer, the preset value of ωq is closer to 0; when the difference in the overall brightness of the two end areas of the rail section i is higher, the rail longitudinal slope δ2 is higher;

[0071] Integrate the track longitudinal slope δ1 and the track longitudinal slope δ2 of the track section i into the track geographical parameters of the track section i;

[0072] Sa4, the image processing model outputs the regional geographic parameters of N1 feature areas and the rail geographic parameters of N2 rail sections of the feature areas, and integrates them into railway track information;

[0073] S2, meteorological monitoring of the area where the railway track is located: the meteorological monitoring unit monitors the regional environmental climate state of the railway track, thereby obtaining environmental climate data;

[0074] Environmental climate parameters include temperature, humidity and rainfall. The temperature, humidity and rainfall of feature area J are marked as WDj, SDj and LYj respectively;

[0075] S3, preliminary analysis of railway track information and environmental climate data: preliminary analysis of regional geographical parameters and environmental climate data, analysis to obtain the correlation factor between the dynamic changes of regional environmental climate and the railway track in the current geographical area, and set the threshold of the correlation factor, so as to extract the railway track information of some geographical areas where the correlation factor exceeds the threshold, mark it as railway track feature information, and store the railway track feature information in the information extraction database. The specific process is as follows:

[0076] Set the correlation matching degree between the environmental climate parameters of the characteristic area J and the regional geographical parameters, and evaluate the degree to which the railway track of the characteristic area J is affected by environmental factors by analyzing the dynamic changes of the environmental climate parameters of the characteristic area J;

[0077] Through the regional geographic parameters of characteristic area J and the environmental climate parameters of characteristic area J, the correlation matching degree analysis is established to obtain the correlation factor between environmental climate and regional geography. The specific process is as follows:

[0078] Environmental climate parameters: temperature WDj, humidity SDj and rainfall LYj of characteristic area J;

[0079] Regional geographical parameters: geological looseness η1 and terrain slope η2 of characteristic area J;

[0080] Obtain the No. 1 correlation factor through the temperature WDj of the characteristic area J and the regional geographical parameters;

[0081] Correlation factor ψ1: Among them, α1 and α2 are the weight coefficients of geological looseness η1 and terrain slope η, respectively, and α1 and α2 are both greater than 0; ΔWD refers to the temperature change value of the characteristic area J, and the temperature change measurement cycle is set to regularly measure the difference between the temperatures WDj of two adjacent cycles; WDmin and WDmax are the low temperature threshold and high temperature threshold of the temperature WDj, respectively. When the temperature WDj of the characteristic area J is lower than or equal to the low temperature threshold WDmin, or higher than or equal to the high temperature threshold WDmax, the No. 1 correlation factor is calculated in combination with the geographical conditions of the characteristic area. The specific process is as follows:

[0082] sa01, when the temperature WDj of the characteristic area J is lower than or equal to the low temperature threshold WDmin, the difference between the temperature WDj and the low temperature threshold WDmin is used. The higher the difference, the higher the low temperature risk. The first correlation judgment is made in combination with the geographical conditions of the characteristic area. When the temperature WDj is too low and the geology is loose and the terrain slope is high, it means that the cold area may produce groundwater freezing and frost heaving effect, which will lead to unstable foundation and "floating rail" phenomenon. When the temperature change value ΔWD is higher, it means that the temperature in the high temperature area may drop suddenly, which will make the rail brittle. The looser the geology, the easier it is for the rail to be damaged.

[0083] sa02, when the temperature WDj of the characteristic area J is higher than or equal to the high temperature threshold WDmax, the difference between the temperature WDj and the high temperature threshold WDmax is used. The higher the difference, the higher the high temperature risk. The first correlation judgment is made in combination with the geographical conditions of the characteristic area. When the temperature WDj is too high and the geology is loose and the terrain slope is high, it means that the rail is easy to deform. And when the temperature change value ΔWD is higher, the risk of rail deformation will be higher.

[0084] The second correlation factor is obtained through the humidity SDj and rainfall LYj of the characteristic area J and the regional geographical parameters;

[0085] sb01, the second correlation factor ψ2:

[0086] ψ2=(SDj-SDmax) β1 *(LYj-LYmax) β2 *(η1α 1 +η2α 2 );

[0087] Among them, SDmax and LYmax are the risk thresholds of humidity SDj and rainfall LYj respectively. The humidity risk difference is obtained by measuring the difference between the current humidity SDj and the humidity risk threshold SDmax; the rainfall risk difference is obtained by measuring the difference between the current rainfall LYj and the rainfall risk threshold LYmax; β1 and β2 are the weight coefficients of the humidity risk difference and the rainfall risk difference respectively, and both β1 and β2 are greater than 0;

[0088] sb02, when the humidity SDj and rainfall LYj of the characteristic area exceed the corresponding risk thresholds, the second correlation factor is calculated in combination with the geographical conditions of the characteristic area. When the humidity risk difference and the rainfall risk difference are higher, and the local geology is looser and the terrain slope is higher, it means that the rainfall is heavy and the foundation is flooded, which may cause the track to sink or tilt, and soil loss to produce mudslides or erosion;

[0089] sc01, set the thresholds of the first correlation factor ψ1 and the second correlation factor ψ2 to h1 and h2 respectively, mark the first correlation factor ψ1 of the feature area J>h1 as the first condition, and mark the second correlation factor ψ2 of the feature area J>h2 as the second condition; when the feature area J satisfies any one of the first and second conditions, the railway track information corresponding to the feature area J is extracted; otherwise, it is not extracted;

[0090] sc02, extract the railway track information of part of the geographical area of ​​the global satellite image of the railway track, and mark it as railway track feature information, mark the number of extracted feature areas as M1, and the part of the geographical area is the M1 extracted feature areas;

[0091] S4, in-depth analysis of the extracted rail feature information and its environmental climate data: by combining the rail geographic parameters of the extracted rail feature information with the environmental climate data corresponding to the geographical area, a risk impact function of the dynamic change of environmental climate on the rail section under specific geographical conditions is constructed, thereby evaluating the real-time risk situation of each rail section in the extracted geographical area and generating risk warning signals of corresponding levels. The specific process is as follows:

[0092] Mark any extracted feature area as Jt, the feature area Jt includes N2 rail sections, and mark any rail section of the feature area Jt as Qi;

[0093] Through in-depth analysis of rail feature information, a functional relationship between the impact of environmental climate dynamic changes on the risk of rail sections under specific geographical conditions is established;

[0094] Among them, the correlation factor of the characteristic area Jt is obtained through the regional geographical parameters and environmental climate data of the characteristic area Jt, and the risk impact of the environmental climate on the regional geography is evaluated. Then, the rail geographical parameters of each rail section of the characteristic area Jt are combined to obtain the rail influence coefficient of each rail section;

[0095] The first and second correlation factors of the characteristic region Jt are marked as ψt1 and ψt2 respectively; the rail transverse slope and rail longitudinal slope of the rail section Qi are marked as δ1 Qi , δ2 Qi ; Thus, the risk impact function F0 of the characteristic area Jt is obtained;

[0096] Then substitute the rail geographical parameters of the rail section Qi into the risk impact function F0 to obtain the rail impact coefficient Xqi of the rail section Qi:

[0097] Xqi=F0(δ1 Qi , δ2 Qi )=(λ1*δ1 Qi +λ2*δ2 Qi ) σ1*ψt1+σ2*ψt2 ;

[0098] Among them, λ1 and λ2 are the rail cross slope δ1 Qi and track slope δ2 Qi The weight coefficients are λ1 and λ2, and both are greater than 0; σ1 and σ2 are the weight coefficients of the first correlation factor ψt1 and the second correlation factor ψt2, respectively, and both are greater than 0; the weight coefficients are obtained by preset experience after a large amount of experimental data measurement, and λ1+λ2=1, σ1+σ2=1; when the rail cross slope δ1 Qi and track slope δ2 Qi The higher it is, the more susceptible the current railway track is to the regional geographical environment and climate. When the No. 1 correlation factor ψt1 and the No. 2 correlation factor ψt2 are, the higher the risk of environmental climate affecting the regional geographical feature area Jt is. The higher the rail influence coefficient Xqi is, the more susceptible the rail section Qi is to environmental factors.

[0099] The rail influence coefficients of the N2 rail sections of the characteristic area Jt are processed in an integrated and parallel manner, and are calculated synchronously according to the risk influence function F0. The evaluation interval of the rail influence coefficient Xqi is set, and the real-time risk situation of the rail section Qi of the characteristic area Jt is evaluated through interval comparison, and a risk warning signal of the corresponding level is generated;

[0100] There are n2 evaluation intervals for the preset rail influence coefficient Xqi, and any of the evaluation intervals is marked as Qr, where r is the serial number of the evaluation interval and r is in the interval [1, n2]. When the rail influence coefficient Xqi is in the evaluation interval Qr, an R-level risk warning signal is generated, and the level of the real-time risk degree of the rail section Qi of the characteristic area Jt is evaluated as R-level. Thus, the real-time risk situation of each rail section of the extracted geographical area, i.e., the characteristic area Jt, is globally evaluated. The higher the rail influence coefficient Xqi is, the higher the degree of influence of the rail section by the regional geographical conditions and environmental climate factors is.

[0101] The level of the risk warning signal is marked as R, and a threshold Rx of the risk warning signal level is set. When the level R of the risk warning signal exceeds the threshold Rx, an identifier is set for the rail section and stored in the information extraction database. Setting the identifier indicates that the rail section has a high risk.

[0102] S5, calling the rail section identifier and its corresponding railway track information: calling the railway track information of the rail section with the identifier by receiving the risk warning signal, then performing management design of the railway track, and generating a corresponding early warning management signal;

[0103] Railway track management and design includes track route planning and design and long-term track maintenance and management;

[0104] Among them, the rail route planning and design is to have professional technicians mark the entry and exit points and intersections of the rails for emergency dispatch. Under the premise of ensuring that the route entrances, exits and stops remain unchanged, the rail sections in risk areas are avoided according to the actual situation, and high-risk rail sections are promptly sealed and repaired;

[0105] Long-term rail maintenance management is to make long-term risk predictions for the environmental climate of the rail sections with identifiers and the geographical areas where they are located. Environmental climate predictions are made through the meteorological monitoring platform to obtain the predicted values ​​of environmental climate data. Then, the data is substituted into the risk impact function in the same way as above, and the rail impact coefficient of the rail section is analyzed and obtained, and marked as the rail impact prediction value.

[0106] By making long-term risk predictions for the railway sections with identifiers and the environmental climate of the geographical areas where they are located, the risk prediction level of a specific geographical area is evaluated as a whole, and early warning management signals of corresponding levels are generated. The process of generating risk warning signals is similar to that of generating risk warning signals, so it will not be elaborated on here.

[0107] The level of the early warning management signal is marked as U, and a threshold Ux of the early warning management signal level is set. When the level U of the early warning management signal exceeds the threshold Ux, it is determined that the predicted risk level displayed by the early warning management signal is high; otherwise, it is determined that the predicted risk level displayed by the early warning management signal is low;

[0108] When the predicted risk level shown by the early warning management signal is high, a rail risk management plan will be generated in advance according to the early warning management signal level, so as to carry out corresponding rail maintenance management; when the predicted risk level shown by the early warning management signal is low, no action will be taken, indicating that the regional stability is good, the environmental climate is stable, and the impact on the rails is not significant, and only regular monitoring is required.

[0109] A railway track information extraction system comprises a satellite monitoring unit, a meteorological monitoring unit, a central processing unit, an information extraction unit, an information calling unit and a display management unit, wherein the satellite monitoring unit, the meteorological monitoring unit, the central processing unit, the information extraction unit, the information calling unit and the display management unit are communicatively connected, and the system applies a railway track information extraction method as described above;

[0110] The satellite monitoring unit is used to conduct satellite remote sensing monitoring of railway tracks, construct a global satellite map of railway tracks, and obtain regional geographic parameters and railway track geographic parameters through image analysis;

[0111] The meteorological monitoring unit is used to monitor the meteorological conditions in the area where the railway tracks are located and obtain environmental climate data;

[0112] The central processor is used to preliminarily analyze the railway track information and environmental climate data to obtain the correlation and matching degree between the environmental climate and regional geography of the evaluated geographical area; then conduct in-depth analysis of the feedback rail feature information to evaluate the real-time risk situation of each rail section in the extracted geographical area, thereby generating a risk warning signal; then set identifiers for the rail sections and conduct management design, thereby generating an early warning management signal;

[0113] The information extraction unit is used to extract the railway track information of some geographical areas where the correlation matching degree exceeds the threshold, mark it as railway track feature information, and then store the railway track feature information and the railway track section with the identifier set in the information extraction database;

[0114] The information calling unit is used to call the rail feature information, the rail section identifier and the corresponding railway track information, and feed the rail feature information back to the central processor for in-depth analysis, and feed the railway track information with the identifier back to the central processor for management design;

[0115] The display management unit is used to receive risk warning signals and early warning management signals, and perform corresponding display and management operations.

[0116] An electronic device includes a memory, a display, a central processing unit, and a computer program stored in the memory and executable on the processor, wherein the central processing unit implements a railway track information extraction method as described above when executing the program; wherein the display is used to display corresponding signals of risk warning signals and early warning management signals, and to visualize data information in a called information extraction database; and the memory is used to store the computer program and the information extraction database.

[0117] A computer-readable storage medium stores a computer program, which, when executed by a central processing unit, implements a railway track information extraction method as described above.

[0118] In summary, the present invention analyzes the geographical environment of the area where the rails are located through satellite remote sensing images, establishes the correlation factor between the regional geography and the environmental climate, and thus specifically extracts the railway track information corresponding to the rail sections that are highly affected by the risk of environmental factors, thereby improving the efficiency of railway track information extraction and reducing the amount of data processing; after the information is extracted, the risk impact function of the dynamic change of environmental factors on the rail structure under specific geographical conditions is reconstructed, and the integrated parallel processing and in-depth analysis of the characteristic information are performed, which reduces the data calculation time and improves the data processing efficiency, and combines with real-time meteorological monitoring to ensure the pertinence and timeliness of rail risk management and maintenance, thereby ensuring the safety and stability of rail operation;

[0119] Among them, the present invention realizes automatic real-time monitoring of the risk of dynamic environmental changes affecting the rails by performing regional targeted extraction and analysis of rail track information and risk positioning, thereby extracting rail track information of high-risk rail sections in a targeted manner, facilitating efficient emergency response and auxiliary scheduling decisions, and ensuring the safety of rail operation; then, by setting identifiers for rail sections and performing long-term risk prediction on rail sections with identifiers and their rail track information, corresponding track maintenance plan management is provided to ensure the continuous stability of rail operation.

[0120] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0121] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0122] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for extracting railway track information, characterized in that: The following steps are involved: Step 1: Conduct satellite remote sensing monitoring of the railway track: The satellite monitoring unit obtains a global satellite image of the railway track through satellite remote sensing technology, and constructs an image processing model to process the global satellite image of the railway track, thereby obtaining railway track information, wherein the railway track information includes regional geographical parameters and railway track geographical parameters; Step 2: Meteorological monitoring of the area where the railway track is located: the meteorological monitoring unit monitors the regional environmental climate state of the railway track, thereby obtaining environmental climate data; Step 3: Preliminary analysis of railway track information and environmental climate data: Preliminary analysis of regional geographical parameters and environmental climate data is performed to obtain the correlation factors between the environmental climate factors of the area where the railway track is located and the regional geographical structure, and a threshold of the correlation factor is set, so as to extract the railway track information of some geographical areas where the correlation factor exceeds the threshold, mark it as railway track feature information, and then establish an information extraction database and store the railway track feature information in the information extraction database; Step 4: In-depth analysis of the extracted rail feature information and its environmental climate data: by combining the rail geographic parameters of the extracted rail feature information with the environmental climate data corresponding to the geographical area, a risk impact function of the dynamic change of environmental climate on the rail section under specific geographical conditions is constructed, so as to evaluate the real-time risk situation of each rail section in the extracted geographical area, generate a risk warning signal of a corresponding level, set a threshold for the risk warning signal level, and when the level of the risk warning signal exceeds the threshold, set an identifier for the rail section and store it in the information extraction database; Step 5, calling the rail section identifier and its corresponding railway track information: calling the railway track information of the rail section with the identifier by receiving the risk warning signal, then performing the management design of the railway track, and generating the corresponding early warning management signal.

2. A railway track information extraction method according to claim 1, characterized in that: The specific process of building an image processing model is as follows: Regional geographical parameters include the geological looseness and terrain slope of the area where the railway track is located; rail geographical parameters include rail transverse slope and rail longitudinal slope; Sa1, input global satellite images of railway tracks into the image processing model; The global satellite image of the railway track is divided into N1 characteristic areas, and the global satellite image of the railway track includes image data corresponding to the N1 characteristic areas; wherein the image data includes band reflection brightness values ​​and spectral reflection curves; The spectral reflectance curve is a curve in which the ratio of reflected luminous flux to incident luminous flux varies with wavelength, that is, the horizontal axis is wavelength and the vertical axis is reflectivity; Through satellite remote sensing technology, light of n0 characteristic bands is emitted to any characteristic area J, and then the reflected light is received to construct a spectral reflectance curve, and the spectral reflectance curve of the characteristic area J is marked as GPj; Set characteristic spectral curves corresponding to n1 geological types and integrate them into a geological spectral library, mark the characteristic spectral curve corresponding to geological type e as GPe, and mark the geological looseness of geological type e as ηe; Sa2, by comparing the spectral reflectance curve GPj of the characteristic area J with the characteristic spectral curve in the geological spectrum library, the geological type of the characteristic area J is determined, thereby obtaining the geological looseness η1 of the characteristic area J; and then combining the band reflectance brightness value of the characteristic area J to obtain the terrain slope η2 of the characteristic area J; Sa3, any feature area J includes N2 rail sections, any rail section is marked as i, and the rail transverse slope δ1 of the rail section i is obtained by performing brightness comparison on the areas on both sides of the rail section i; the rail longitudinal slope δ2 of the rail section i is obtained by performing brightness comparison on the areas on both ends of the rail section i; Sa4, the image processing model outputs the regional geographic parameters of the N1 feature areas and the track geographic parameters of the N2 track sections of the feature areas, and integrates them into railway track information.

3. A railway track information extraction method according to claim 2, characterized in that: The specific process of preliminarily analyzing the railway track information and environmental climate data and extracting the railway track characteristic information is as follows: Environmental climate parameters include temperature, humidity and rainfall. The temperature, humidity and rainfall of feature area J are marked as WDj, SDj and LYj respectively; Through the regional geographic parameters of characteristic area J and the environmental climate parameters of characteristic area J, the correlation matching degree analysis is established to obtain the correlation factor between environmental climate and regional geography. The specific process is as follows: Regional geographic parameters include geological looseness η1 and terrain slope η2 of characteristic area J; The first correlation factor ψ1 is obtained through the temperature WDj of the characteristic area J and the regional geographical parameters, and the second correlation factor ψ2 is obtained through the humidity SDj and the rainfall LYj of the characteristic area J and the regional geographical parameters; The thresholds of the first correlation factor ψ1 and the second correlation factor ψ2 are set to h1 and h2 respectively, and the first correlation factor ψ1>h1 of the feature region J is marked as the first condition, and the second correlation factor ψ2>h2 of the feature region J is marked as the second condition; when the feature region J satisfies any one of the first condition and the second condition, the railway track information corresponding to the feature region J is extracted; otherwise, it is not extracted; The number of the feature regions to be extracted is marked as M1, and the railway track information of the M1 feature regions of the railway track global satellite image is extracted and marked as railway track feature information.

4. A railway track information extraction method according to claim 3, characterized in that: The rail feature information extracted by in-depth analysis and the specific process are as follows: Any extracted characteristic region is marked as Jt, the region Jt whose characteristic environmental climate data includes N2 rail sections, and any rail section of the characteristic region Jt is marked as Qi; Through the regional geographic parameters and environmental climate data of the characteristic area Jt, the correlation factor of the characteristic area Jt is obtained to evaluate the risk impact of the environmental climate on the regional geography, and then the rail geographical parameters of each rail section of the characteristic area Jt are combined to obtain the rail influence coefficient of each rail section; The first and second correlation factors of the characteristic region Jt are marked as ψt1 and ψt2 respectively, and the rail transverse slope and rail longitudinal slope of the rail section Qi are marked as , , thereby obtaining the risk impact function F0 of the feature area Jt; Then, the rail geographical parameters of the rail section Qi are substituted into the risk influence function F0 to obtain the rail influence coefficient Xqi of the rail section Qi; Set the evaluation interval of the rail influence coefficient Xqi, evaluate the real-time risk situation of the rail section Qi in the characteristic area Jt through interval comparison, and generate a risk warning signal of the corresponding level.

5. A railway track information extraction system, characterized in that: The system comprises a satellite monitoring unit, a meteorological monitoring unit, a central processing unit, an information extraction unit, an information calling unit and a display management unit, wherein the satellite monitoring unit, the meteorological monitoring unit, the central processing unit, the information extraction unit, the information calling unit and the display management unit are communicatively connected with each other, and the system applies a railway track information extraction method as described in any one of claims 1 to 4 above; The satellite monitoring unit is used to conduct satellite remote sensing monitoring of railway tracks, construct a global satellite map of railway tracks, and obtain regional geographic parameters and railway track geographic parameters through image analysis; The meteorological monitoring unit is used to monitor the meteorological conditions in the area where the railway tracks are located and obtain environmental climate data; The central processor is used to preliminarily analyze the railway track information and environmental climate data to obtain the correlation and matching degree between the environmental climate and regional geography of the evaluated geographical area; then conduct in-depth analysis of the feedback rail feature information to evaluate the real-time risk situation of each rail section in the extracted geographical area, thereby generating a risk warning signal; then set identifiers for the rail sections and conduct management design, thereby generating an early warning management signal; The information extraction unit is used to extract the railway track information of some geographical areas where the correlation matching degree exceeds the threshold, mark it as railway track feature information, and then store the railway track feature information and the railway track section with the identifier set in the information extraction database; The information calling unit is used to call the rail feature information, the rail section identifier and the corresponding railway track information, and feed the rail feature information back to the central processor for in-depth analysis, and feed the railway track information with the identifier back to the central processor for management design; The display management unit is used to receive risk warning signals and early warning management signals, and perform corresponding display and management operations.

6. An electronic device comprising a memory, a display, a central processing unit, and a computer program stored in the memory and executable on the processor, characterized in that: When the central processing unit executes the program, a railway track information extraction method as described in any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a central processing unit, a railway track information extraction method as described in any one of claims 1 to 4 is implemented.

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