Method, system, device and medium for generating vertical tamping scheme of railway track

Abstract

The present application relates to the technical field of rail measurement data processing, specifically to a method, system, device and medium for generating a tamping scheme for a railway track in the vertical direction; the present application firstly performs quadratic interpolation processing on a measured deviation curve based on preset head and tail constraint points to obtain an initial target curve; then, performs equidistant sampling processing on the initial target curve to obtain a first constraint point set, and performs deviation value correction processing on corresponding key points based on the change of the initial target deviation value within a neighborhood range to obtain a second constraint point set; subsequently, an optimized target curve is obtained based on the second constraint point set and the first constraint point set; then, high and low values ​​and undulation values ​​are obtained, and a target loss function is constructed; finally, based on the target loss function, a least squares method is performed on the optimized target curve to obtain an optimal target curve with good quality, and then a vertical track start curve with a suitable track start amount is obtained, thereby improving and reducing the quality of tamping of the rail in the vertical direction.

Description

Technical Field

[0001] The invention relates to the technical field of rail measurement data processing, and in particular to a method, system, device and medium for generating a tamping plan for a railway track in a vertical direction. Background Art

[0002] Track precision measurement and tamping refers to measuring the track based on the control network and precision measurement technology, and using the measurement results to guide large-scale track maintenance machinery to implement digital precision tamping operations. Existing technologies often measure the state parameters of the track in the vertical direction to obtain measured data, and then make a difference between the design data and the measured data to obtain the actual deviation of the line, and then use the actual deviation as the track start amount to perform vertical tamping on the track.

[0003] However, when there is a large gap between the measured data and the design data, the deviation value will be high and the amount of track lifting will be too large. At this time, not only more complex or more frequent tamping work is required to gradually adjust the track, thereby increasing the track tamping cost and affecting the track tamping, but also excessive track lifting can easily damage the structural stability of the rail and reduce the vertical tamping quality of the rail. Summary of the invention

[0004] The purpose of the present invention is to provide a method, system, device and medium for generating a vertical tamping plan for a railway track.

[0005] The technical solution of the present invention is as follows:

[0006] A method for generating a vertical tamping plan for a railway track comprises the following operations:

[0007] S1. Convert all mileage values ​​and corresponding elevation values ​​of the measured railway track into a measured elevation curve with the mileage value as the abscissa and the elevation value as the ordinate; use the difference curve between the designed elevation curve and the measured elevation curve as a measured deviation curve with the mileage value as the abscissa and the deviation value as the ordinate; perform quadratic interpolation on the measured deviation curve based on the preset head and tail constraint points to obtain an initial target curve with the initial target mileage value as the abscissa and the initial target deviation value as the ordinate;

[0008] S2. Perform equidistant sampling processing on the initial target curve to obtain a number of first constraint points, forming a first constraint point set; based on the change of the initial target deviation value in the neighborhood of each initial target mileage value in the initial target curve, select a number of initial target mileage values ​​from all the initial target mileage values ​​as second mileage values; perform forward correction processing on the initial target deviation value corresponding to the second mileage value to obtain a correction deviation value; each second mileage value and the corresponding correction deviation value respectively form a number of second constraint points; all the second constraint points form a second constraint point set; the second constraint point set and the first constraint point set are arranged in order from small to large according to the corresponding mileage values, and then curve fitting processing is performed to obtain an optimized target curve;

[0009] S3. Based on the preset upper and lower limits of the track start amount, the difference curve between the initial target curve and the measured deviation curve is adjusted to obtain a limited track start amount curve with the horizontal axis as the limited mileage value and the vertical axis as the limited deviation value; based on the sum value curve of the limited track start amount curve and the measured deviation curve, the high and low values ​​are obtained; the initial target curve is traversed with a fixed step length, and the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step length is obtained to obtain the absolute value of the target deviation of each step length; the absolute values ​​of the target deviations of all step lengths are summed to obtain the undulation value; based on the undulation value and the high and low values, the target loss function is obtained;

[0010] S4. Based on the target loss function, the optimized target curve is processed by the least square method to obtain the optimal target curve; the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track rise curve of the railway track; according to the vertical track rise curve, the railway track is tamped in the vertical direction.

[0011] The method for obtaining the second mileage value in S2 is specifically as follows: traverse each initial target mileage value in the initial target curve, and take the initial target mileage value whose continuous rising value or continuous falling value in the neighborhood reaches the rising threshold or the falling threshold respectively as the second mileage value.

[0012] The correction deviation value in S2 is the sum of the initial target deviation value and the forward deviation.

[0013] Before the least squares processing operation in S4, it also includes: splicing each constraint mileage value and the corresponding constraint deviation value in the optimization target curve to obtain each constraint point data; all constraint point data are arranged in order from small to large according to the constraint mileage value, and then spliced ​​to obtain a constraint point sequence; the constraint point sequence, sequence constraint rules and target loss function are used as inputs for the least squares processing to obtain the optimal target curve.

[0014] The sequence constraint rules include: the horizontal coordinate limit condition of the constraint point i in the constraint point sequence: x(i) < x(i + 1), where x(i) is the horizontal coordinate of the constraint point i, x(i + 1) is the horizontal coordinate of the constraint point i + 1, and the horizontal coordinate positions of the first constraint point and the last constraint point remain unchanged; the vertical coordinate limit condition of the constraint point i in the constraint point sequence: y(i) > c(i) + Δ, where y(i) is the vertical coordinate of the constraint point i, c(i) is the constraint deviation value of the constraint point i, and Δ is an adjustable positive number.

[0015] The operation of obtaining the high and low values in S3 is specifically as follows: perform the summation processing of the corresponding deviation values of the mileage values on the restricted track lifting amount curve and the measured deviation curve to obtain a summation value curve; obtain the standard deviation and the average value of all the summation values in the summation value curve, and use the ratio of the standard deviation to the average value as the high and low values.

[0016] The target loss function in S2 is obtained based on the weighted summation function of the undulation degree value and the high and low values.

[0017] A system for implementing a method for generating a tamping scheme in the vertical direction of a railway track, comprising:

[0018] An initial target curve generation module, configured to convert all the mileage values and the corresponding elevation values of the measured railway track into a measured elevation curve with the mileage value as the abscissa and the elevation value as the ordinate; use the difference curve between the designed elevation curve and the measured elevation curve as a measured deviation curve with the mileage value as the abscissa and the deviation value as the ordinate; perform quadratic interpolation processing on the measured deviation curve based on the preset start and end constraint points to obtain an initial target curve with the initial target mileage value as the abscissa and the initial target deviation value as the ordinate;

[0019] An optimized target curve generation module, configured to perform equidistant sampling processing on the initial target curve to obtain a number of first constraint points, forming a first constraint point set; based on the change of the initial target deviation value within the neighborhood range of each initial target mileage value in the initial target curve, select a number of initial target mileage values from all the initial target mileage values as the second mileage values; perform forward correction processing on the initial target deviation values corresponding to the second mileage values to obtain corrected deviation values; each second mileage value and the corresponding corrected deviation value respectively form a number of second constraint points; all the second constraint points form a second constraint point set; after the second constraint point set and the first constraint point set are arranged in ascending order according to the corresponding mileage values, perform curve fitting processing to obtain an optimized target curve;

[0020] The target loss function generation module is used to adjust the difference curve between the initial target curve and the measured deviation curve based on the preset upper and lower limits of the track start amount, so as to obtain a limited track start amount curve with the horizontal axis as the limited mileage value and the vertical axis as the limited deviation value; obtain the high and low values ​​based on the sum value curve of the limited track start amount curve and the measured deviation curve; traverse the initial target curve with a fixed step length, obtain the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step length, and obtain the absolute value of the target deviation of each step length; the absolute values ​​of the target deviations of all steps are summed to obtain the undulation value; and obtain the target loss function based on the undulation value and the high and low values;

[0021] The vertical track rise curve generation and vertical tamping module is used to perform least squares processing on the optimized target curve based on the target loss function to obtain the optimal target curve; the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track rise curve of the railway track; and the railway track is vertically tamped according to the vertical track rise curve.

[0022] A device for generating a vertical tamping scheme for a railway track comprises a processor and a memory, wherein the processor implements the above-mentioned method for generating a vertical tamping scheme for a railway track when executing a computer program stored in the memory.

[0023] A computer-readable storage medium is used to store a computer program, wherein the computer program, when executed by a processor, implements the above-mentioned method for generating a vertical tamping plan for a railway track.

[0024] The beneficial effects of the present invention are:

[0025] The method for generating a tamping scheme for a railway track in the vertical direction provided by the present invention firstly uses the difference curve between the designed elevation curve and the measured elevation curve as the measured deviation curve, and based on preset head and tail constraint points, performs quadratic interpolation processing on the measured deviation curve to obtain a relatively smooth initial target curve; then, performs equidistant sampling processing on the initial target curve to obtain a first constraint point set evenly distributed on the initial target curve, and based on the change of the initial target deviation value within the neighborhood range, selects key points related to the key area of ​​tamping in the vertical direction of the track from the initial target curve and performs deviation value correction processing to obtain a second constraint point set; then, based on the second approximate The bundle point set and the first constraint point set are subjected to curve fitting processing to obtain an optimized target curve which is smoother than the initial target curve and can better avoid excessive track lifting amount; then, based on the initial target curve, the upper and lower limits of track lifting amount and the measured deviation curve, the high and low values ​​used to reflect the quality and stability of the track, as well as the fluctuation value used to reflect the degree of deformation of the rail are obtained, and the target loss function is constructed based on the high and low values ​​and the fluctuation value; finally, based on the target loss function, the optimized target curve is processed by the least squares method to obtain the optimal target curve with good quality, and then the vertical track lifting amount curve with appropriate track lifting amount is obtained, thereby improving and reducing the tamping quality of the rail in the vertical direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] By reading the detailed description of the preferred embodiment below, the scheme and advantages of the present application will become clear to those skilled in the art. The accompanying drawings are only for the purpose of illustrating the preferred embodiment and are not to be considered as limiting the present invention.

[0027] In the attached picture:

[0028] Figure 1 It is a combined diagram of the optimal target curve and the measured deviation curve in the embodiment;

[0029] Figure 2 2 is a vertical track quantity curve diagram in an embodiment. DETAILED DESCRIPTION

[0030] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings.

[0031] This embodiment provides a method for generating a vertical tamping plan for a railway track, including the following operations:

[0032] S1. Convert all mileage values ​​and corresponding elevation values ​​of the measured railway track into a measured elevation curve with the mileage value as the abscissa and the elevation value as the ordinate; use the difference curve between the designed elevation curve and the measured elevation curve as a measured deviation curve with the mileage value as the abscissa and the deviation value as the ordinate; perform quadratic interpolation on the measured deviation curve based on the preset head and tail constraint points to obtain an initial target curve with the initial target mileage value as the abscissa and the initial target deviation value as the ordinate;

[0033] S2. Perform equidistant sampling processing on the initial target curve to obtain a number of first constraint points, forming a first constraint point set; based on the change of the initial target deviation value in the neighborhood of each initial target mileage value in the initial target curve, select a number of initial target mileage values ​​from all the initial target mileage values ​​as second mileage values; perform forward correction processing on the initial target deviation value corresponding to the second mileage value to obtain a correction deviation value; each second mileage value and the corresponding correction deviation value respectively form a number of second constraint points; all the second constraint points form a second constraint point set; the second constraint point set and the first constraint point set are arranged in order from small to large according to the corresponding mileage values, and then curve fitting processing is performed to obtain an optimized target curve;

[0034] S3. Based on the preset upper and lower limits of the track start amount, the difference curve between the initial target curve and the measured deviation curve is adjusted to obtain a limited track start amount curve with the horizontal axis as the limited mileage value and the vertical axis as the limited deviation value; based on the sum value curve of the limited track start amount curve and the measured deviation curve, the high and low values ​​are obtained; the initial target curve is traversed with a fixed step length, and the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step length is obtained to obtain the absolute value of the target deviation of each step length; the absolute values ​​of the target deviations of all step lengths are summed to obtain the undulation value; based on the undulation value and the high and low values, the target loss function is obtained;

[0035] S4. Based on the target loss function, the optimized target curve is processed by the least square method to obtain the optimal target curve; the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track rise curve of the railway track; according to the vertical track rise curve, the railway track is tamped in the vertical direction.

[0036] S1. Convert all mileage values ​​and corresponding elevation values ​​of the measured railway track into a measured elevation curve with the mileage value as the horizontal coordinate and the elevation value as the vertical coordinate; use the difference curve between the designed elevation curve and the measured elevation curve as the measured deviation curve with the mileage value as the horizontal coordinate and the deviation value as the vertical coordinate; based on the preset first and last constraint points, perform quadratic interpolation on the measured deviation curve to obtain an initial target curve with the initial target mileage value as the horizontal coordinate and the initial target deviation value as the vertical coordinate.

[0037] Since the deviation value obtained by directly subtracting the design data from the measured data is often much larger than the upper limit of the allowable adjustment, directly using the deviation value as the vertical track start amount may destroy the structural stability of the rail. Therefore, it is necessary to design a smooth target curve as the actual target for tamping, and subtract the target curve from the measured deviation curve to obtain the appropriate tamping amount, which can be used as the basis for the operation of the tamping machine, thereby improving the quality of tamping in the vertical direction of the railway track.

[0038] In order to solve the above problems, this embodiment uses the difference curve between the designed elevation curve and the measured elevation curve as the measured deviation curve, and based on the preset first and last constraint points, performs quadratic interpolation on the measured deviation curve to obtain a smoother initial target curve for subsequent formation of a high-quality vertical track start curve.

[0039] Firstly, all the mileage values ​​and corresponding elevation values ​​of the measured railway tracks are converted into measured elevation curves with the horizontal axis being the mileage value and the vertical axis being the elevation value, which are used to show the changing trend of the measured elevation of the tracks.

[0040] Then, the difference curve between the designed elevation curve and the measured elevation curve is used as the measured deviation curve with the horizontal axis as the mileage value and the vertical axis as the deviation value to show the deviation between the measured elevation data and the designed elevation data.

[0041] Finally, based on the preset first and last constraint points, the measured deviation curve is processed by quadratic interpolation to obtain the initial target curve with the initial target mileage value as the abscissa and the initial target deviation value as the ordinate. The first and last constraint points are the first and last data points of the measured deviation curve.

[0042] S2. Perform equidistant sampling processing on the initial target curve to obtain a number of first constraint points, forming a first constraint point set; based on the change of the initial target deviation value in the neighborhood of each initial target mileage value in the initial target curve, select a number of initial target mileage values ​​from all the initial target mileage values ​​as second mileage values; perform forward correction processing on the initial target deviation value corresponding to the second mileage value to obtain a correction deviation value; each second mileage value and the corresponding correction deviation value respectively form a number of second constraint points; all the second constraint points form a second constraint point set; the second constraint point set and the first constraint point set are arranged in order from small to large according to the corresponding mileage values, and then curve fitting processing is performed to obtain an optimized target curve.

[0043] In order to achieve smooth processing of the initial target curve and avoid the problem of uneven deformation of the track structure caused by excessive track start-up amount obtained later, the initial target curve is firstly subjected to equidistant sampling processing to obtain the first constraint point set evenly distributed on the initial target curve; and based on the change of the initial target deviation value within the neighborhood range, the key points related to the key area of ​​tamping in the vertical direction of the track are selected from the initial target curve and the deviation value correction processing is performed to obtain the second constraint point set; then, based on the second constraint point set and the first constraint point set, curve fitting processing is performed to obtain an optimized target curve that is smoother than the initial target curve and can better avoid excessive track start-up amount.

[0044] First, the initial target curve is processed by equidistant sampling to obtain a number of first constraint points, forming a first constraint point set, which is used for subsequent smoothing of the initial target curve to obtain a reasonable optimized target curve. The first constraint points are evenly distributed on the initial target curve.

[0045] Then, since the peaks and troughs in the initial target curve actually correspond to the key areas of vertical tamping of the track (areas with large tamping volume), in order to avoid deformation of the rails caused by excessive single track lifting in the key areas, it is necessary to select some appropriate key points at the peaks and troughs in the initial target curve to correct the deviation values, so as to obtain a smooth curve later.

[0046] In order to solve this technical problem, this embodiment selects several initial target mileage values ​​from all the initial target mileage values ​​as second mileage values ​​based on the change of the initial target deviation value in the neighborhood of each initial target mileage value in the initial target curve; and performs forward correction processing on the initial target deviation value corresponding to the second mileage value to obtain a corrected deviation value.

[0047] The method for obtaining the second mileage value is specifically as follows: traverse each initial target mileage value in the initial target curve, and take the initial target mileage value that reaches the rising threshold or the falling threshold in the neighborhood range with continuous rising values ​​or continuous falling values, respectively, as the second mileage value at the key point at the peak or trough.

[0048] The correction deviation value is the sum of the initial target deviation value and the forward deviation, that is, the forward correction process is achieved by adding the initial target deviation value to the forward deviation.

[0049] Therefore, each second mileage value and the corresponding correction deviation value form a number of second constraint points respectively; all the second constraint points form a second constraint point set representing key points at the peaks or troughs for smoothing the initial target curve.

[0050] Finally, the second constraint point set and the first constraint point set are arranged in order from small to large according to the corresponding mileage values, and then curve fitting is performed to obtain the optimized target curve.

[0051] S3. Based on the preset upper and lower limits of the track start amount, the difference curve between the initial target curve and the measured deviation curve is adjusted to obtain a restricted track start amount curve with the horizontal axis as the restricted mileage value and the vertical axis as the restricted deviation value; based on the sum value curve of the restricted track start amount curve and the measured deviation curve, the high and low values ​​are obtained; the initial target curve is traversed with a fixed step size to obtain the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step size to obtain the absolute value of the target deviation for each step size; the absolute values ​​of the target deviations of all steps are summed to obtain the undulation value; based on the undulation value and the high and low values, the target loss function is obtained.

[0052] Based on the initial target curve, the upper and lower limits of the track start amount and the measured deviation curve, the high and low values ​​used to reflect the quality and stability of the track, as well as the undulation value used to reflect the degree of deformation of the rail are obtained; and based on the high and low values ​​and the undulation value, a target loss function is constructed for further smoothing and optimizing the target curve in the future, so as to obtain an optimal target curve with good quality, and then obtain a vertical track start amount curve with good quality.

[0053] Since the purpose of tamping is to reduce the TQI (Track Quality Index) of the line and improve the smoothness of the track, when obtaining the final target curve, this embodiment uses TQI as an optimization target of the target curve to further smooth and optimize the target curve, so that the final optimal target curve has less fluctuations and is as flat as possible, and avoids the problem of uneven deformation of the track structure caused by excessive track start-up in the subsequent step as much as possible, thereby improving the tamping quality of the rails.

[0054] Therefore, this embodiment first adjusts the difference curve between the initial target curve and the measured deviation curve based on the preset upper and lower limits of the track start amount, and obtains a limited track start amount curve with the horizontal coordinate being the limited mileage value and the vertical coordinate being the limited deviation value. When the difference in the difference curve between the initial target curve and the measured deviation curve exceeds the deviation value corresponding to the upper limit of the track start amount, the difference is adjusted to the deviation value corresponding to the upper limit of the track start amount; when the difference in the difference curve between the initial target curve and the measured deviation curve is less than the deviation value corresponding to the lower limit of the track start amount, the difference is adjusted to the deviation value corresponding to the lower limit of the track start amount. In this way, the subsequent optimal target curve can be as high as possible above the actual deviation curve, and the part of the optimal target curve that is lower than the actual deviation curve directly takes the minimum track start amount to prevent excessive track start amount. Among them, the limited mileage value corresponds one-to-one to the initial target mileage value.

[0055] Then, based on the summation curve of the limit track start curve and the measured deviation curve, the high and low values ​​reflecting the quality and stability of the track are obtained.

[0056] The operations for obtaining high and low values ​​may specifically be: summing the corresponding deviation values ​​of the mileage values ​​of the restricted start-up amount curve and the measured deviation curve to obtain a summed value curve; obtaining the standard deviation (used to measure the dispersion of the deviation values) and the average value (used to measure the overall trend of the deviation values) of all summed values ​​in the summed value curve, and taking the ratio of the standard deviation to the average value as the high and low values.

[0057] The operation of obtaining the high and low values ​​may specifically be: summing the corresponding deviation values ​​of the mileage values ​​of the restricted start-up amount curve and the measured deviation curve to obtain a summation value curve; obtaining the average value of all summation values ​​in the summation value curve as the high and low values.

[0058] At the same time, the initial target curve is traversed with a fixed step size, and the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step size is obtained to obtain the absolute value of the target deviation for each step size. The absolute values ​​of the target deviations of all steps are summed to obtain the undulation value used to reflect the undulation degree and deformation degree of the rail.

[0059] Finally, based on the undulation value and the height value, the target loss function for further smoothing and optimizing the target curve is obtained. The target loss function is obtained based on the weighted sum function of the undulation value and the height value. S4. Based on the target loss function, the optimized target curve is processed by the least square method to obtain the optimal target curve; the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track start curve of the railway track; according to the vertical track start curve, the railway track is vertically tamped.

[0060] Based on the target loss function, the target curve is further smoothed and optimized to obtain the optimal target curve with good quality, and then the vertical track lifting amount curve with appropriate track lifting amount is obtained, thereby improving the vertical tamping quality of the rail.

[0061] First, in order to further optimize the optimization target curve, the optimization target curve is processed by the least square method based on the target loss function to obtain the optimal target curve. Figure 1 .

[0062] In this process, an accurate optimal target curve can be obtained quickly. Before the least squares processing operation, it also includes: splicing each constraint mileage value and the corresponding constraint deviation value in the optimization target curve to obtain each constraint point data; all constraint point data are arranged in order from small to large according to the constraint mileage value, and then spliced ​​to obtain a constraint point sequence in the form of x1, y1, x2, y2,…, xn, yn; the constraint point sequence, sequence constraint rules and target loss function are used as inputs for the least squares processing to obtain the optimal target curve.

[0063] The sequence constraint rules include: the horizontal coordinate limit condition of the constraint point i in the constraint point sequence: x(i) < x(i + 1), where x(i) is the horizontal coordinate of the constraint point i, x(i + 1) is the horizontal coordinate of the constraint point i + 1, and the horizontal coordinate positions of the first and the last constraint points remain unchanged; the vertical coordinate limit condition of the constraint point i in the constraint point sequence: y(i) > c(i) + Δ, where y(i) is the vertical coordinate of the constraint point i, c(i) is the constraint deviation value of the constraint point i, and Δ is an adjustable positive number.

[0064] Then, the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track lifting amount curve of the railway track. See Figure 2 .

[0065] Finally, the railway track is tamped in the vertical direction according to the vertical track lifting amount curve.

[0066] This embodiment also provides a system for implementing the method for generating the tamping scheme in the vertical direction of the railway track, including:

[0067] An initial target curve generation module, which is used to convert all mileage values and corresponding elevation values of the measured railway track into a measured elevation curve with the mileage value as the abscissa and the elevation value as the ordinate; the difference curve between the designed elevation curve and the measured elevation curve is used as the measured deviation curve with the mileage value as the abscissa and the deviation value as the ordinate; based on the preset start and end constraint points, the measured deviation curve is processed by the quadratic interpolation method to obtain an initial target curve with the initial target mileage value as the abscissa and the initial target deviation value as the ordinate;

[0068] An optimized target curve generation module, which is used to perform equidistant sampling on the initial target curve to obtain a number of first constraint points, forming a first constraint point set; based on the change of the initial target deviation value within the neighborhood range of each initial target mileage value in the initial target curve, a number of initial target mileage values are selected from all the initial target mileage values as the second mileage values; the positive correction process is performed on the initial target deviation values corresponding to the second mileage values to obtain the corrected deviation values; each second mileage value and the corresponding corrected deviation value respectively form a number of second constraint points; all the second constraint points form a second constraint point set; after the second constraint point set and the first constraint point set are arranged in ascending order according to the corresponding mileage values, the curve fitting process is performed to obtain the optimized target curve;

[0069] The target loss function generation module is used to adjust the difference curve between the initial target curve and the measured deviation curve based on the preset upper and lower limits of the track start amount, so as to obtain a limited track start amount curve with the horizontal axis as the limited mileage value and the vertical axis as the limited deviation value; obtain the high and low values ​​based on the sum value curve of the limited track start amount curve and the measured deviation curve; traverse the initial target curve with a fixed step length, obtain the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step length, and obtain the absolute value of the target deviation of each step length; the absolute values ​​of the target deviations of all steps are summed to obtain the undulation value; and obtain the target loss function based on the undulation value and the high and low values;

[0070] The vertical track rise curve generation and vertical tamping module is used to perform least squares processing on the optimized target curve based on the target loss function to obtain the optimal target curve; the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track rise curve of the railway track; and the railway track is vertically tamped according to the vertical track rise curve.

[0071] This embodiment also provides a device for generating a vertical tamping plan for a railway track, comprising a processor and a memory, wherein the processor implements the above-mentioned method for generating a vertical tamping plan for a railway track when executing a computer program stored in the memory.

[0072] This embodiment also provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the above-mentioned method for generating a vertical tamping plan for a railway track.

[0073] The method for generating a tamping plan for a railway track in the vertical direction provided in the present embodiment firstly uses the difference curve between the designed elevation curve and the measured elevation curve as the measured deviation curve, and based on the preset first and last constraint points, performs quadratic interpolation processing on the measured deviation curve to obtain a relatively smooth initial target curve; then, performs equidistant sampling processing on the initial target curve to obtain a first constraint point set evenly distributed on the initial target curve, and based on the change of the initial target deviation value within the neighborhood range, selects key points related to the key area of ​​vertical tamping of the track from the initial target curve and performs deviation correction processing to obtain a second constraint point set; then, based on the second constraint point set, and the first constraint point set, and curve fitting processing is performed to obtain an optimized target curve that is smoother than the initial target curve and can better avoid excessive track lifting; then, based on the initial target curve, the upper and lower limits of track lifting and the measured deviation curve, high and low values ​​used to reflect the quality and stability of the track, as well as the fluctuation value used to reflect the wear and deformation degree of the rail surface are obtained, and based on the high and low values ​​and the fluctuation value, a target loss function is constructed; finally, based on the target loss function, the optimized target curve is processed by least squares method to obtain an optimal target curve with good quality, and then a vertical track lifting curve with appropriate track lifting is obtained, thereby improving and reducing the tamping quality of the rail in the vertical direction.

Claims

1. A method for generating a vertical tamping plan for a railway track, characterized in that: The following operations are included: S1. Convert all the mileage values ​​and corresponding elevation values ​​of the measured railway track into a measured elevation curve with the abscissa being the mileage value and the ordinate being the elevation value; The difference curve between the designed elevation curve and the measured elevation curve is used as the measured deviation curve with the horizontal axis being the mileage value and the vertical axis being the deviation value; Based on the preset first and last constraint points, the measured deviation curve is processed by quadratic interpolation to obtain an initial target curve whose abscissa is the initial target mileage value and whose ordinate is the initial target deviation value; S2, performing equidistant sampling processing on the initial target curve to obtain a plurality of first constraint points, thereby forming a first constraint point set; Based on the change of the initial target deviation value in the neighborhood of each initial target mileage value in the initial target curve, a number of initial target mileage values ​​are selected from all the initial target mileage values ​​as the second mileage value; the method for obtaining the second mileage value is specifically as follows: traverse each initial target mileage value in the initial target curve, and take the initial target mileage value with a continuous rising value or a continuous falling value in the neighborhood that reaches the rising threshold or the falling threshold, respectively, as the second mileage value; Performing a positive correction process on the initial target deviation value corresponding to the second mileage value to obtain a correction deviation value; each second mileage value and the corresponding correction deviation value respectively form a plurality of second constraint points; all the second constraint points form a second constraint point set; The second constraint point set and the first constraint point set are arranged in order from small to large according to the corresponding mileage values, and then curve fitting is performed to obtain an optimized target curve; S3. Based on the preset upper and lower limits of the track start amount, the difference curve between the initial target curve and the measured deviation curve is adjusted to obtain a restricted track start amount curve whose abscissa is the restricted mileage value and whose ordinate is the restricted deviation value; Based on the summation curve of the restricted track start amount curve and the measured deviation curve, high and low values ​​are obtained; the operation of obtaining the high and low values ​​is specifically as follows: summing the deviation values ​​corresponding to the mileage values ​​of the restricted track start amount curve and the measured deviation curve to obtain the summation curve; obtaining the standard deviation and average value of all summation values ​​in the summation curve, and taking the ratio of the standard deviation to the average value as the high and low values; The initial target curve is traversed with a fixed step length, and the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step length is obtained to obtain the absolute value of the target deviation of each step length; the absolute values ​​of the target deviations of all steps are summed to obtain the fluctuation degree value; Based on the fluctuation degree value and the high and low values, a target loss function is obtained; S4. Based on the target loss function, the optimized target curve is processed by least square method to obtain the optimal target curve; the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track rise curve of the railway track; and the railway track is vertically tamped according to the vertical track rise curve.

2. The method for generating a vertical tamping plan for a railway track according to claim 1, characterized in that: The correction deviation value in S2 is the sum of the initial target deviation value and the forward deviation.

3. The method for generating a vertical tamping plan for a railway track according to claim 1, characterized in that: Before the least squares processing operation in S4, the following steps are further included: Each constraint mileage value and the corresponding constraint deviation value in the optimization target curve are spliced ​​to obtain each constraint point data; all constraint point data are arranged in order from small to large according to the constraint mileage value, and then spliced ​​to obtain a constraint point sequence; The constraint point sequence, sequence constraint rules and target loss function are used as inputs of the least squares method to obtain the optimal target curve.

4. The method for generating a vertical tamping plan for a railway track according to claim 3, characterized in that: The sequence constraint rules include: Constraint points in the constraint point sequence i The horizontal axis constraints are: x(i) <x(i+1) , x(i) Constraint point i The horizontal axis of x (i+1) Constraint point i+1 The horizontal coordinates of the first and last constraint points remain unchanged; Constraint points in the constraint point sequence i The vertical axis constraints are: y(i)>c(i)+Δ , y(i) Constraint point i The vertical coordinate of c (i) Constraint point i The constraint deviation value, Δ An adjustable positive number.

5. The method for generating a vertical tamping plan for a railway track according to claim 1, characterized in that: The target loss function in S2 is obtained based on a weighted sum function of the fluctuation degree value and the high and low values.

6. A system for implementing the method for generating a vertical tamping plan for a railway track according to claim 1, characterized in that: include: The initial target curve generation module is used to convert all the mileage values ​​and corresponding elevation values ​​of the measured railway track into a measured elevation curve with the mileage value as the horizontal coordinate and the elevation value as the vertical coordinate; use the difference curve between the designed elevation curve and the measured elevation curve as the measured deviation curve with the mileage value as the horizontal coordinate and the deviation value as the vertical coordinate; based on the preset head and tail constraint points, the measured deviation curve is processed by quadratic interpolation to obtain the initial target curve with the initial target mileage value as the horizontal coordinate and the initial target deviation value as the vertical coordinate; The optimized target curve generation module is used to perform equidistant sampling processing on the initial target curve to obtain a plurality of first constraint points, forming a first constraint point set; based on the change of the initial target deviation value in the neighborhood of each initial target mileage value in the initial target curve, select a plurality of initial target mileage values ​​from all the initial target mileage values ​​as second mileage values; perform forward correction processing on the initial target deviation value corresponding to the second mileage value to obtain a correction deviation value; each second mileage value and the corresponding correction deviation value respectively form a plurality of second constraint points; all the second constraint points form a second constraint point set; the second constraint point set and the first constraint point set are arranged in order from small to large according to the corresponding mileage values, and then curve fitting processing is performed to obtain the optimized target curve; The target loss function generation module is used to adjust the difference curve between the initial target curve and the measured deviation curve based on the preset upper and lower limits of the track start amount, so as to obtain a limit track start amount curve whose abscissa is the limit mileage value and whose ordinate is the limit deviation value; obtain the high and low values ​​based on the sum value curve of the limit track start amount curve and the measured deviation curve; traverse the initial target curve with a fixed step length, obtain the absolute value of the difference between the initial target deviation values ​​between adjacent points in each step length, and obtain the absolute value of the target deviation of each step length; the absolute values ​​of the target deviations of all the step lengths are summed to obtain the undulation value; and obtain the target loss function based on the undulation value and the high and low values; The vertical track rise curve generation and vertical tamping module is used to perform least squares processing on the optimized target curve based on the target loss function to obtain the optimal target curve; the difference curve between the optimal target curve and the measured deviation curve is used as the vertical track rise curve of the railway track; and the railway track is vertically tamped according to the vertical track rise curve.

7. A device for generating a vertical tamping plan for a railway track, characterized in that: It comprises a processor and a memory, wherein when the processor executes the computer program stored in the memory, it implements the method for generating a vertical tamping plan for a railway track as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: Used to store a computer program, wherein when the computer program is executed by a processor, the method for generating a vertical tamping plan for a railway track according to any one of claims 1 to 5 is implemented.

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