Railway track precision tamping plan generation method, system, device, and medium

Abstract

The present application relates to the technical field of rail measurement data processing and specifically to a method, system, device and medium for generating a precise tamping scheme for a railway track. Firstly, a superelevation curve is generated according to superelevation values ​​corresponding to all mileage values ​​of the actually measured railway track, and the superelevation curve is subjected to low-pass filtering and peak filtering to obtain a precise filtered superelevation curve; then, a curve corresponding to a key wave crest area in the precise filtered superelevation curve is used as a curve to be processed, and straight-slow points, slow-straight points, slow-round points and round-slow points are obtained to form flat curve design data; finally, based on the flat curve design data, an accurate track design curve is designed; and based on the track design curve and the actually measured data, a flat curve actually measured deviation curve and a flat curve target curve are designed, and a difference curve between the flat curve target curve and the flat curve actually measured deviation curve is used as a flat curve starting amount curve of the railway track to perform precise tamping on the railway track.

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 railway track precision tamping plan. Background Art

[0002] Track precision measurement and tamping refers to the measurement of superelevation and elevation of tracks based on control networks and precision measurement technology, and the use of measurement results to guide large-scale track maintenance machinery to implement digital precision tamping operations of rails. GNSS (Global Navigation Satellite System) and inertial navigation track inspection instruments are often used in track precision measurement and tamping. The track inspection instrument has the ability to measure high-precision trajectories within a short distance with high-precision inertial navigation, but because the inertial navigation error will accumulate over time, the GNSS positioning information will be combined with the positioning information of the GNSS to correct the trajectory coordinates during track precision measurement and tamping, and finally obtain high-precision position coordinate information of the track line. Then, by comparing the measured position coordinates with the design coordinates, the track start amount (track adjustment amount) is obtained to guide the operation of the tamping machine and achieve track precision measurement and tamping tasks.

[0003] However, some rail lines lack line design data for various reasons, or the design data is inaccurate due to lack of maintenance, making it difficult to generate a suitable track precision tamping plan and to achieve accurate track precision measurement and tamping. Summary of the invention

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

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

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

[0007] S1. Convert all the measured mileage values ​​corresponding to the superelevation values ​​of the railway track into a superelevation curve with the mileage value as the abscissa and the superelevation value as the ordinate; the superelevation curve is processed by low-pass filtering to obtain a primary filter superelevation curve; the primary filter superelevation curve is processed by peak filtering to obtain a fine filter superelevation curve;

[0008] S2. The corresponding curve of the key peak area in the fine filtration superelevation curve is used as the curve to be processed; all the curves to be processed form a set of curves to be processed; in the corresponding curve of the key peak area, the average value of the fine filtration superelevation value is greater than the superelevation average value threshold; based on the difference of the fine filtration superelevation value corresponding to the previous and next fine filtration mileage values, each curve to be processed in the set of curves to be processed is traversed to obtain the straight-slow point and slow-straight point of each curve to be processed; based on the variance value of the fine filtration superelevation value, the part of the curves to be processed corresponding to the straight-slow point to the slow-straight point of each curve to be processed is traversed to obtain the slow-round point and round-slow point of each curve to be processed; based on the slow-round point and round-slow point of each curve to be processed, the center of the circle and the radius of the circular curve of each curve to be processed are obtained; after all the curves to be processed in the set of curves to be processed are traversed, all the straight-slow points, slow-straight points, slow-round points, round-slow points and circular curve radius are obtained to form the flat curve design data;

[0009] S3. Based on the flat curve design data, as well as the measured track centerline coordinates and corresponding elevation values ​​of the railway track, the track design curve is obtained; the difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates and corresponding elevation values ​​of the railway track is obtained as the measured deviation curve of the flat curve; based on the measured deviation curve of the flat curve, the flat curve target curve is obtained; the difference curve between the flat curve target curve and the measured deviation curve of the flat curve is used as the flat curve starting quantity curve of the railway track; and the railway track is finely rammed according to the flat curve starting quantity curve.

[0010] The specific operation of the peak filtering processing in S1 is as follows: traverse each primary filter mileage value in the primary filter super-high curve. If the primary filter super-high value corresponding to the current primary filter mileage value is the maximum value within the current primary filter mileage value ± the first distance range, retain the current primary filter mileage value as the first fine filter mileage value; take the primary filter mileage value corresponding to the primary filter super-high value greater than the primary filter super-high value threshold within the current primary filter peak mileage ± the second distance range as the second fine filter mileage value; after all the primary filter mileage values ​​in the primary filter super-high curve are traversed, all the first fine filter mileage values ​​and all the second fine filter mileage values ​​are obtained to form a fine filter mileage data set; connect the fine filter mileage data set corresponding to the primary filter super-high value into a line to obtain a fine filter super-high curve with the horizontal axis being the fine filter mileage value and the vertical axis being the fine filter super-high value.

[0011] The method for obtaining the straight-slow point and the slow-straight point in S2 is specifically as follows: in the process of traversing from the starting point position of the current curve to be processed to the end point position, if the difference between the fine filtering super-high value corresponding to the current fine filtering mileage value and the next fine filtering mileage value is greater than the fine filtering super-high value difference threshold of the forward traversal, then the point of the current fine filtering mileage value on the current curve to be processed is used as the straight-slow point of the current curve to be processed; in the process of traversing from the end point position of the current curve to be processed to the starting point position, if the difference between the fine filtering super-high value corresponding to the current fine filtering mileage value and the next fine filtering mileage value is greater than the fine filtering super-high value difference threshold of the reverse traversal, then the point of the current fine filtering mileage value on the current curve to be processed is used as the slow-straight point of the current curve to be processed.

[0012] The specific method for obtaining the slow round point and the round-slow point in S2 is: take the part of the curve to be processed corresponding to the straight-slow point to the slow-straight point of the current curve to be processed as the peak curve; traverse the peak curve from both ends of the peak curve at the same time, and in the traversal process, take the first and last two fine filtering mileage values ​​in the part of the peak curve corresponding to the minimum value of the fine filtering ultra-high value variance value as the corresponding points on the current curve to be processed as the slow round point and the round-slow point of the current curve to be processed.

[0013] The method for obtaining the center of the circle and the radius of the circular curve in S2 is specifically as follows: based on the slow circle point and the slow circle point of the current curve to be processed, a center loss function is constructed; the center loss function is processed by the least squares method to obtain the center of the current curve to be processed; the average distance between the center of the circle and the slow circle point and the slow circle point corresponding to all points on the circular curve is used as the circular curve radius of the current curve to be processed.

[0014] The specific operation of the low-pass filtering process in S1 is as follows: use a sliding window of a fixed size to traverse each mileage value in the superelevation curve; during the traversal process, use the average value of the superelevation value in the sliding window at the current mileage value position as the initial filter superelevation value at the current mileage value position; after all mileage values ​​are traversed by the sliding window, all mileage values ​​are used as initial filter mileage values ​​to obtain a primary filter superelevation curve with the initial filter mileage value as the horizontal axis and the initial filter superelevation value as the vertical axis.

[0015] A system for realizing a method for generating a railway track precision tamping plan, comprising:

[0016] The fine filter superelevation curve generation module is used to convert the superelevation values ​​corresponding to all the measured mileage values ​​of the railway track into superelevation curves with the horizontal coordinate being the mileage value and the vertical coordinate being the superelevation value; the superelevation curve is processed by low-pass filtering to obtain the primary filter superelevation curve; the primary filter superelevation curve is processed by peak filtering to obtain the fine filter superelevation curve;

[0017] The flat curve design data generation module is used to take the curve corresponding to the key peak area in the fine filtering superelevation curve as the curve to be processed; all the curves to be processed form a set of curves to be processed; in the curve corresponding to the key peak area, the average value of the fine filtering superelevation value is greater than the superelevation average value threshold; based on the fine filtering superelevation value difference corresponding to the previous and next fine filtering mileage values, each curve to be processed in the set of curves to be processed is traversed to obtain the straight-slow point and slow-straight point of each curve to be processed; based on the variance value of the fine filtering superelevation value, the part of the curves to be processed corresponding to the straight-slow point to the slow-straight point of each curve to be processed is traversed to obtain the slow-round point and round-slow point of each curve to be processed; based on the slow-round point and round-slow point of each curve to be processed, the center of the circle and the radius of the circular curve of each curve to be processed are obtained; after all the curves to be processed in the set of curves to be processed are traversed, all the straight-slow points, slow-straight points, slow-round points, round-slow points and circular curve radius are obtained to form the flat curve design data;

[0018] The module for generating and fine-ramming processing the horizontal curve starting quantity curve is used to obtain the track design curve based on the horizontal curve design data, the measured track centerline coordinates and the corresponding elevation values ​​of the railway track; obtain the difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates and the corresponding elevation values ​​of the railway track as the horizontal curve measured deviation curve; obtain the horizontal curve target curve based on the horizontal curve measured deviation curve; use the difference curve between the horizontal curve target curve and the horizontal curve measured deviation curve as the horizontal curve starting quantity curve of the railway track; and perform fine-ramming processing on the railway track according to the horizontal curve starting quantity curve.

[0019] A railway track precision tamping scheme generating device comprises a processor and a memory, wherein the processor implements the above-mentioned railway track precision tamping scheme generating method when executing a computer program stored in the memory.

[0020] A computer-readable storage medium is used to store a computer program, wherein when the computer program is executed by a processor, the above-mentioned method for generating a railway track precision tamping plan is implemented.

[0021] The beneficial effects of the present invention are:

[0022] The invention provides a method for generating a railway track fine tamping scheme. First, a superelevation curve is generated according to superelevation values ​​corresponding to all mileage values ​​of the actually measured railway track. The superelevation curve is subjected to low-pass filtering and peak filtering to obtain a fine-filtered superelevation curve that retains superelevation information at the wave crest and can show the superelevation value change trend at the wave crest. Then, a curve corresponding to a key wave crest area in the fine-filtered superelevation curve that can indirectly reflect stress concentration and track wear during train operation is used as a curve to be processed. The straight-slow point, slow-straight point, slow-round point and the smooth-smooth point are obtained based on the difference of the fine-filtered superelevation values ​​corresponding to the previous and next fine-filtered mileage values ​​and the variance value of the fine-filtered superelevation values. rounding points to form flat curve design data; finally, based on the flat curve design data, an accurate track design curve is designed to make up for the technical deficiency of generating a suitable track precision tamping scheme due to the lack of design data; and based on the track design curve and the measured data, a flat curve measured deviation curve and a flat curve target curve are designed, and the difference curve between the flat curve target curve and the flat curve measured deviation curve is used as the flat curve starting curve of the railway track, and the railway track is precision tamped to achieve accurate track precision measurement and precision tamping, which can not only enhance the safety of the track, but also avoid the shaking and discomfort caused by abrupt track changes during the actual operation of the train. DETAILED DESCRIPTION

[0023] A method for generating a railway track precision tamping plan includes the following operations:

[0024] S1. Convert all the measured mileage values ​​corresponding to the superelevation values ​​of the railway track into a superelevation curve with the mileage value as the abscissa and the superelevation value as the ordinate; the superelevation curve is processed by low-pass filtering to obtain a primary filter superelevation curve; the primary filter superelevation curve is processed by peak filtering to obtain a fine filter superelevation curve;

[0025] S2. The corresponding curve of the key peak area in the fine filtration superelevation curve is used as the curve to be processed; all the curves to be processed form a set of curves to be processed; in the corresponding curve of the key peak area, the average value of the fine filtration superelevation value is greater than the superelevation average value threshold; based on the difference of the fine filtration superelevation value corresponding to the previous and next fine filtration mileage values, each curve to be processed in the set of curves to be processed is traversed to obtain the straight-slow point and slow-straight point of each curve to be processed; based on the variance value of the fine filtration superelevation value, the part of the curves to be processed corresponding to the straight-slow point to the slow-straight point of each curve to be processed is traversed to obtain the slow-round point and round-slow point of each curve to be processed; based on the slow-round point and round-slow point of each curve to be processed, the center of the circle and the radius of the circular curve of each curve to be processed are obtained; after all the curves to be processed in the set of curves to be processed are traversed, all the straight-slow points, slow-straight points, slow-round points, round-slow points and circular curve radius are obtained to form the flat curve design data;

[0026] S3. Based on the flat curve design data, as well as the measured track centerline coordinates and corresponding elevation values ​​of the railway track, the track design curve is obtained; the difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates and corresponding elevation values ​​of the railway track is obtained as the measured deviation curve of the flat curve; based on the measured deviation curve of the flat curve, the flat curve target curve is obtained; the difference curve between the flat curve target curve and the measured deviation curve of the flat curve is used as the flat curve starting quantity curve of the railway track; and the railway track is finely rammed according to the flat curve starting quantity curve.

[0027] S1. Convert the superelevation values ​​corresponding to all the measured mileage values ​​of the railway track into superelevation curves with the horizontal axis being the mileage value and the vertical axis being the superelevation value; the superelevation curves are processed by low-pass filtering to obtain a primary filter superelevation curve; the primary filter superelevation curves are processed by peak filtering to obtain a fine filter superelevation curve.

[0028] According to the superelevation values ​​corresponding to all the measured mileage values ​​of the railway track, a superelevation curve is generated, and the superelevation curve is low-pass filtered to eliminate the high-frequency change data in the superelevation curve, so as to show the superelevation value change trend and obtain a preliminary filtered superelevation curve; the preliminary filtered superelevation curve is peak filtered to obtain a fine filtered superelevation curve that retains the superelevation information at the peak and shows the superelevation value change trend at the peak, so as to analyze the change of track superelevation value and generate accurate design data later, thereby generating accurate track start amount.

[0029] First, all the mileage values ​​of the measured railway tracks correspond to superelevation values, and all the mileage values ​​of the measured railway tracks correspond to superelevation values, and are converted into superelevation curves with mileage values ​​as the horizontal axis and superelevation values ​​as the vertical axis. Superelevation value, also known as track inclination or superelevation, refers to the height of the outer rail relative to the inner rail on the curve section of the railway track. It is designed to offset the centrifugal force generated when the train passes through the curve at high speed, thereby improving the stability and comfort of the train operation. The superelevation value can be obtained based on the elevation values ​​corresponding to the mileage values ​​of the outer rail and the mileage values ​​of the inner rail.

[0030] Then, considering that the design superelevation value of the rail has a low frequency of change, in order to eliminate the high-frequency change data in the superelevation curve, the superelevation curve is low-pass filtered to obtain the primary filtered superelevation curve.

[0031] The operation of low-pass filtering processing can be as follows: use a sliding window of a fixed size to traverse each mileage value in the superelevation curve; during the traversal process, use the average value of the superelevation value in the sliding window at the current mileage value position as the initial filtration superelevation value at the current mileage value position; after all mileage values ​​are traversed by the sliding window, use all mileage values ​​as initial filtration mileage values ​​to obtain an initial filtration superelevation curve with the initial filtration mileage value as the horizontal axis and the initial filtration superelevation value as the vertical axis.

[0032] The low-pass filter processing operation can also be: use a sliding window of fixed size to traverse each mileage value in the superelevation curve; during the traversal process, take the weighted average of the superelevation values ​​in the sliding window at the current mileage value position as the initial filter superelevation value at the current mileage value position; after all mileage values ​​are traversed by the sliding window, all mileage values ​​are taken as the initial filter mileage values, and the initial filter superelevation curve is obtained with the horizontal axis as the initial filter mileage value and the vertical axis as the initial filter superelevation value. The weight corresponding to each mileage value decreases according to the Gaussian distribution, which is conducive to balancing the relationship between superelevation value smoothing and superelevation value retention, making the superelevation value change trend more obvious.

[0033] Finally, in order to enhance the changing trend of the peak area in the initial filter superelevation curve on the basis of reducing the amount of data, facilitate the analysis of the change of track superelevation value, and facilitate the subsequent generation of accurate design data, thereby generating accurate track start-up amount, the initial filter superelevation curve is subjected to peak filtering to obtain the fine filter superelevation curve.

[0034] The specific operation of the peak filtering process is as follows: traverse each primary filter mileage value in the primary filter super-high curve. If the primary filter super-high value corresponding to the current primary filter mileage value is the maximum value within the current primary filter mileage value ± the first distance range, retain the current primary filter mileage value as the first fine filter mileage value at the peak; at the same time, in order to retain the super-high value with a larger value near the peak and improve the accuracy of subsequent analysis, the primary filter mileage value corresponding to the primary filter super-high value greater than the primary filter super-high value threshold within the current primary filter peak mileage ± the second distance range is used as the second fine filter mileage value; after all the primary filter mileage values ​​in the primary filter super-high curve are traversed, all the first fine filter mileage values ​​and all the second fine filter mileage values ​​are obtained to form a fine filter mileage data set; the fine filter mileage data set corresponding to the primary filter super-high value is connected into a line to form a fine filter super-high curve with the horizontal axis being the fine filter mileage value and the vertical axis being the fine filter super-high value. S2. Take the curve corresponding to the key peak area in the fine filtration superelevation curve as the curve to be processed; all the curves to be processed form a set of curves to be processed; based on the difference of the fine filtration superelevation values ​​corresponding to the previous and next fine filtration mileage values, traverse each curve to be processed in the set of curves to be processed to obtain the straight-slow point and slow-straight point of each curve to be processed; based on the variance value of the fine filtration superelevation value, traverse the part of the curves to be processed corresponding to the straight-slow point to the slow-straight point of each curve to be processed to obtain the slow-round point and round-slow point of each curve to be processed; based on the slow-round point and round-slow point of each curve to be processed, obtain the center of the circle and the radius of the circular curve of each curve to be processed; all the straight-slow points, slow-straight points, slow-round points, round-slow points and circular curve radius form the design data of the flat curve.

[0035] The corresponding curve of the key peak area in the fine filtering superelevation curve, which can indirectly reflect the stress concentration and large track wear during train operation, is used as the curve to be processed, and based on the difference of the fine filtering superelevation values ​​corresponding to the previous and next fine filtering mileage values, and the variance value of the fine filtering superelevation values, the straight-slow point, slow-straight point, slow-circular point and circular-slow point as the key points in the curve to be processed are obtained, so as to facilitate the subsequent acquisition of accurate design data, generate accurate track design curves, and generate accurate track start amounts.

[0036] First, the corresponding curves of the key peak areas in the fine-filter superelevation curves are taken as the curves to be processed; all the curves to be processed form a set of curves to be processed; in the corresponding curves of the key peak areas, the average value of the fine-filter superelevation value is greater than the superelevation average value threshold. These key peak areas corresponding to the set of curves to be processed are often places where stress concentration and track wear are greater during train operation. Focusing on these areas helps to quickly obtain accurate design data, thereby obtaining accurate track start-up volume, which is beneficial to subsequent track safety and stable train operation.

[0037] Then, in order to obtain the starting position where the superelevation value in the key peak area of ​​the curve to be processed occurs suddenly, so as to facilitate the subsequent acquisition of accurate design data, based on the difference of the fine filtration superelevation values ​​corresponding to the previous and next fine filtration mileage values, each curve to be processed in the set of curves to be processed is traversed to obtain the straight-slow point and slow-straight point of each curve to be processed.

[0038] The specific method for obtaining the straight-slow point and the slow-straight point is as follows: in the process of traversing from the starting point position of the current curve to be processed to the end point position, if the difference between the fine filtering super-high value corresponding to the current fine filtering mileage value and the next fine filtering mileage value is greater than the fine filtering super-high value difference threshold of the forward traversal, then the point of the current fine filtering mileage value on the current curve to be processed is used as the straight-slow point of the current curve to be processed; in the process of traversing from the end point position of the current curve to be processed to the starting point position, if the difference between the fine filtering super-high value corresponding to the current fine filtering mileage value and the next fine filtering mileage value is greater than the fine filtering super-high value difference threshold of the reverse traversal, then the point of the current fine filtering mileage value on the current curve to be processed is used as the slow-straight point of the current curve to be processed.

[0039] Next, in order to obtain the starting position of the super-high value at the peak of the key peak area in the curve to be processed when it oscillates, the key transition points in the design data are obtained, and based on the variance value of the fine-filtered super-high value, the part of the curve to be processed corresponding to the straight-slow point to the slow-straight point of each curve to be processed is traversed to obtain the slow-round point and round-slow point of each curve to be processed.

[0040] The specific method for obtaining the slow round point and the round slow point is as follows: the part of the to-be-processed curve corresponding to the straight slow point to the slow straight point of the current to-be-processed curve is used as the peak curve; the peak curve is traversed from both ends of the peak curve at the same time, and during the traversal process, the first and last fine filter mileage values ​​of the part of the peak curve corresponding to the minimum value of the fine filter super high value variance value are respectively used as the slow round point and the round slow point of the current to-be-processed curve at the corresponding points on the current to-be-processed curve. In the above traversal process, the fine filter super high value variance value is the fine filter super high value variance value of all points between the two traversal points before and after (including the two traversal points) on the peak curve at the current moment.

[0041] Subsequently, based on the slow-down point and slow-down point of each curve to be processed, the center point and radius of each curve to be processed are obtained, so as to facilitate the generation of design data for generating accurate track design curves.

[0042] The method for obtaining the center of the circle and the radius of the circular curve is as follows: based on the slow circle point and the slow circle point of the current curve to be processed, a center loss function is constructed; the center loss function is processed by the least squares method to obtain the center of the current curve to be processed; the average distance between the center of the circle and the slow circle point and the slow circle point corresponding to all points on the circular curve is used as the circular curve radius of the current curve to be processed.

[0043] Specifically, according to the positions of the slow circle points and the slow circle points, the position coordinates of all circular curves are intercepted, and the center position of the circle is used as the solution target. The average value of the distance between the center of the circle and all circular curve points is the radius of the circular curve. The square of the difference between the distance between all points on the circular curve and the center position and the radius of the circular curve is used as the loss function. The least squares method is used to solve and get the center position of the circle.

[0044] Finally, after traversing all the curves to be processed in the curve set to be processed, all straight-slow points, slow-straight points, slow-circular points, circular-slow points and circular curve radius are obtained, forming the flat curve design data, which is used to adjust the measured railway track data to form track design data, thereby facilitating the subsequent generation of a suitable track precision tamping plan.

[0045] S3. Based on the flat curve design data, as well as the measured track centerline coordinates and corresponding elevation values ​​of the railway track, the track design curve is obtained; the difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates and corresponding elevation values ​​of the railway track is obtained as the measured deviation curve of the flat curve; based on the measured deviation curve of the flat curve, the flat curve target curve is obtained; the difference curve between the flat curve target curve and the measured deviation curve of the flat curve is used as the flat curve starting quantity curve of the railway track; and the railway track is finely rammed according to the flat curve starting quantity curve.

[0046] Based on the flat curve design data, an accurate track design curve is designed to make up for the current technical deficiency of generating a suitable track precision tamping plan due to the lack of design data; and based on the track design curve and the measured data, a flat curve measured deviation curve and a flat curve target curve are designed, and the difference curve between the flat curve target curve and the flat curve measured deviation curve is used as the flat curve starting curve of the railway track, and the railway track is precision tamped to achieve accurate track precision measurement and precision tamping, which can not only enhance the safety of the track, but also avoid shaking and discomfort caused by abrupt track changes during actual train operation.

[0047] First, based on the horizontal curve design data, the measured track centerline coordinates and corresponding elevation values ​​of the railway track, the track design curve is obtained. The measured track centerline coordinates and corresponding elevation values ​​can be calculated based on the measured east coordinates and north coordinates of the outer track, the measured east coordinates and north coordinates of the inner track, and the corresponding elevation values.

[0048] Specifically, based on the measured track centerline coordinates and corresponding elevation values ​​of the railway track, a measured elevation curve is generated with the horizontal coordinate being the measured track centerline east coordinate and the vertical coordinate being the elevation value; curve fitting is performed on the corresponding points of the straight-slow point and the slow-round point in the measured elevation curve in the flat curve design data, and circular curve fitting is performed on the corresponding points of the slow-round point and the round-slow point in the measured elevation curve based on the corresponding circular curve radius; curve fitting is performed on the corresponding points of the round-slow point and the slow-straight point in the measured elevation curve to obtain a track design curve with good continuity and smooth transition and the ability to avoid sudden changes. The curve is used for track start calculation, which can not only enhance the safety of the track, but also avoid shaking and discomfort caused by abrupt track changes during actual train operation.

[0049] Then, the difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates of the railway track and the corresponding elevation value is obtained as the measured deviation curve of the horizontal curve.

[0050] Next, based on the measured deviation curve of the flat curve, the target curve of the flat curve is obtained. Specifically, based on the measured deviation curve of the flat curve, the constraint points and the threshold of the track start amount are set, and the measured deviation curve of the flat curve is subjected to secondary interpolation processing to obtain the target curve of the flat curve.

[0051] Then, the difference curve between the flat curve target curve and the flat curve measured deviation curve is used as the flat curve starting quantity curve of the railway track;

[0052] Finally, according to the horizontal curve starting curve, the outer and inner rails of the railway track are finely rammed to achieve accurate track precision measurement and ramming.

[0053] This embodiment also provides a system for realizing a method for generating a railway track precision tamping plan, comprising:

[0054] The fine filter superelevation curve generation module is used to convert the superelevation values ​​corresponding to all the measured mileage values ​​of the railway track into superelevation curves with the horizontal coordinate being the mileage value and the vertical coordinate being the superelevation value; the superelevation curve is processed by low-pass filtering to obtain the primary filter superelevation curve; the primary filter superelevation curve is processed by peak filtering to obtain the fine filter superelevation curve;

[0055] The flat curve design data generation module is used to take the curve corresponding to the key peak area in the fine filtering superelevation curve as the curve to be processed; all the curves to be processed form a set of curves to be processed; in the curve corresponding to the key peak area, the average value of the fine filtering superelevation value is greater than the superelevation average value threshold; based on the fine filtering superelevation value difference corresponding to the previous and next fine filtering mileage values, each curve to be processed in the set of curves to be processed is traversed to obtain the straight-slow point and slow-straight point of each curve to be processed; based on the variance value of the fine filtering superelevation value, the part of the curves to be processed corresponding to the straight-slow point to the slow-straight point of each curve to be processed is traversed to obtain the slow-round point and round-slow point of each curve to be processed; based on the slow-round point and round-slow point of each curve to be processed, the center of the circle and the radius of the circular curve of each curve to be processed are obtained; after all the curves to be processed in the set of curves to be processed are traversed, all the straight-slow points, slow-straight points, slow-round points, round-slow points and circular curve radius are obtained to form the flat curve design data;

[0056] The module for generating and fine-ramming processing the horizontal curve starting quantity curve is used to obtain the track design curve based on the horizontal curve design data, the measured track centerline coordinates and the corresponding elevation values ​​of the railway track; obtain the difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates and the corresponding elevation values ​​of the railway track as the horizontal curve measured deviation curve; obtain the horizontal curve target curve based on the horizontal curve measured deviation curve; use the difference curve between the horizontal curve target curve and the horizontal curve measured deviation curve as the horizontal curve starting quantity curve of the railway track; and perform fine-ramming processing on the railway track according to the horizontal curve starting quantity curve.

[0057] This embodiment also provides a railway track precision tamping plan generation device, including a processor and a memory, wherein the processor implements the above-mentioned railway track precision tamping plan generation method when executing a computer program stored in the memory.

[0058] 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 railway track precision tamping plan.

[0059] The present embodiment provides a method for generating a railway track fine tamping plan. First, a superelevation curve is generated according to the superelevation values ​​corresponding to all mileage values ​​of the actually measured railway track. The superelevation curve is subjected to low-pass filtering and peak filtering to obtain a fine-filtered superelevation curve that retains the superelevation information at the peak and can show the superelevation value change trend at the peak. Then, the corresponding curve of the key peak area in the fine-filtered superelevation curve that can indirectly reflect the stress concentration and track wear during the operation of the train is used as the curve to be processed, and the straight-slow point, slow-straight point, and slow-round point are obtained based on the difference of the fine-filtered superelevation values ​​corresponding to the previous and next fine-filtered mileage values ​​and the variance value of the fine-filtered superelevation values. and round slow points to form flat curve design data; finally, based on the flat curve design data, an accurate track design curve is designed to make up for the current technical deficiency of generating a suitable track precision tamping plan due to the lack of design data; and based on the track design curve and the measured data, a flat curve measured deviation curve and a flat curve target curve are designed, and the difference curve between the flat curve target curve and the flat curve measured deviation curve is used as the flat curve starting curve of the railway track, and the railway track is precision tamped to achieve accurate track precision measurement and precision tamping, which can not only enhance the safety of the track, but also avoid shaking and discomfort caused by abrupt track changes during actual train operation.

Claims

1. A method for generating a railway track precision tamping plan, characterized in that: The following operations are included: S1. Convert the superelevation values ​​corresponding to all the measured mileage values ​​of the railway track into a superelevation curve with the mileage value as the abscissa and the superelevation value as the ordinate; the superelevation curve is processed by low-pass filtering to obtain a primary filter superelevation curve; the primary filter superelevation curve is processed by peak filtering to obtain a fine filter superelevation curve; The operation of the low-pass filtering process is specifically as follows: using a sliding window of a fixed size to traverse each mileage value in the superelevation curve; during the traversal process, taking the average value of the superelevation value in the sliding window at the current mileage value position as the initial filtered superelevation value at the current mileage value position; After all mileage values ​​are traversed by the sliding window, all mileage values ​​are used as the primary filtration mileage values ​​to obtain the primary filtration super-high curve whose abscissa is the primary filtration mileage value and whose ordinate is the primary filtration super-high value; The peak filtering process is specifically performed as follows: traverse each primary filter mileage value in the primary filter super-high curve, if the primary filter super-high value corresponding to the current primary filter mileage value is the maximum value within the current primary filter mileage value ± the first distance range, retain the current primary filter mileage value as the first fine filter mileage value; take the primary filter mileage value corresponding to the primary filter super-high value greater than the primary filter super-high value threshold within the current primary filter peak mileage ± the second distance range as the second fine filter mileage value; after all primary filter mileage values ​​in the primary filter super-high curve are traversed, all first fine filter mileage values ​​and all second fine filter mileage values ​​are obtained to form a fine filter mileage data set; connect the primary filter mileage data set corresponding to the primary filter super-high value into a line to obtain the fine filter super-high curve with the horizontal axis being the fine filter mileage value and the vertical axis being the fine filter super-high value; S2, taking the curve corresponding to the key peak area in the fine filtration ultra-high curve as the curve to be processed; all the curves to be processed form a set of curves to be processed; in the curve corresponding to the key peak area, the average value of the fine filtration ultra-high value is greater than the ultra-high average value threshold; Based on the difference of the fine filtration super-high values ​​corresponding to the previous and next fine filtration mileage values, traverse each of the to-be-processed curves in the to-be-processed curve set to obtain the straight-slow point and the slow-straight point of each of the to-be-processed curves; Based on the ultra-high variance value of the fine filtering, the part of the to-be-processed curve corresponding to the straight-slow point to the slow-straight point of each to-be-processed curve is traversed to obtain the slow-round point and the round-slow point of each to-be-processed curve; Based on the slow-down point and slow-down point of each curve to be processed, the center point and the radius of the circular curve of each curve to be processed are obtained; After all the to-be-processed curves in the to-be-processed curve set are traversed, all straight-slow points, slow-straight points, slow-circular points, circular-slow points and circular curve radius are obtained, forming flat curve design data; S3, based on the horizontal curve design data, and the measured track centerline coordinates and corresponding elevation values ​​of the railway track, obtaining a track design curve; Obtaining a difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates and corresponding elevation values ​​of the railway track as a measured deviation curve of the horizontal curve; Based on the measured deviation curve of the flat curve, a target flat curve is obtained; and a difference curve between the target flat curve and the measured deviation curve of the flat curve is used as a flat curve starting amount curve of the railway track; The railway track is finely rammed according to the horizontal curve starting amount curve.

2. The method for generating a railway track precision tamping plan according to claim 1, characterized in that: In S2, the method for obtaining the straight-slow point and the slow-straight point is specifically as follows: In the process of traversing from the starting point of the current curve to be processed to the end point, if the difference between the fine filtering super-high value corresponding to the current fine filtering mileage value and the next fine filtering mileage value is greater than the positive traversal fine filtering super-high value difference threshold, the point of the current fine filtering mileage value on the current curve to be processed is used as the straightening point of the current curve to be processed; During the traversal from the end point of the current curve to be processed to the starting point, if the difference between the fine filtering super-high value corresponding to the current fine filtering mileage value and the next fine filtering mileage value is greater than the reverse traversal fine filtering super-high value difference threshold, the point of the current fine filtering mileage value on the current curve to be processed is used as the straightening point of the current curve to be processed.

3. The method for generating a railway track precision tamping plan according to claim 1, characterized in that: In S2, the method for obtaining the slow round point and the slow round point is specifically as follows: The part of the curve to be processed corresponding to the straight-slow point to the slow-straight point of the current curve to be processed is taken as the peak curve; the peak curve is traversed simultaneously from both ends of the peak curve. During the traversal process, the first and last two fine filtering mileage values ​​in the part of the peak curve corresponding to the minimum value of the fine filtering ultra-high value variance value are respectively used as the slow round point and round-slow point of the current curve to be processed at the corresponding points on the current curve to be processed.

4. The method for generating a railway track precision tamping plan according to claim 1, characterized in that: In S2, the method for obtaining the center of the circle and the radius of the circular curve is specifically as follows: Based on the slow circle point and slow circle point of the current curve to be processed, a center loss function is constructed; the center loss function is processed by the least squares method to obtain the center of the current curve to be processed; the average value of the distance between the center of the circle and the slow circle point and the slow circle point and all points on the circular curve corresponding to the slow circle point is used as the circular curve radius of the current curve to be processed.

5. A system for implementing the method for generating a railway track precision tamping plan according to claim 1, characterized in that: include: A fine filtering superelevation curve generation module is used to convert the superelevation values ​​corresponding to all the mileage values ​​of the measured railway tracks into a superelevation curve with the mileage value as the horizontal coordinate and the superelevation value as the vertical coordinate; the superelevation curve is processed by low-pass filtering to obtain a preliminary filtering superelevation curve; the preliminary filtering superelevation curve is processed by peak filtering to obtain a fine filtering superelevation curve; The flat curve design data generation module is used to take the corresponding curve of the key peak area in the fine filtration superelevation curve as the curve to be processed; all the curves to be processed form a set of curves to be processed; in the curve corresponding to the key peak area, the average value of the fine filtration superelevation value is greater than the superelevation average value threshold; Based on the difference of the fine filtering super-high values ​​corresponding to the front and rear fine filtering mileage values, each of the to-be-processed curves in the to-be-processed curve set is traversed to obtain the straight-slow point and the slow-straight point of each to-be-processed curve; based on the variance value of the fine filtering super-high value, the part of the to-be-processed curves corresponding to the straight-slow point to the slow-straight point of each to-be-processed curve is traversed to obtain the slow-round point and the round-slow point of each to-be-processed curve; based on the slow-round point and the round-slow point of each to-be-processed curve, the center of the circle and the radius of the circular curve of each to-be-processed curve are obtained; after all the to-be-processed curves in the to-be-processed curve set are traversed, all the straight-slow points, slow-straight points, slow-round points, round-slow points and the radius of the circular curve are obtained, forming the flat curve design data; The module for generating and fine-ramming processing the horizontal curve start-of-track quantity curve is used to obtain the track design curve based on the horizontal curve design data, the measured track centerline coordinates of the railway track and the corresponding elevation values; obtain the difference curve between the track design curve and the corresponding measured elevation curve of the measured track centerline coordinates of the railway track and the corresponding elevation values ​​as the horizontal curve measured deviation curve; obtain the horizontal curve target curve based on the horizontal curve measured deviation curve; use the difference curve between the horizontal curve target curve and the horizontal curve measured deviation curve as the horizontal curve start-of-track quantity curve of the railway track; and perform fine-ramming processing on the railway track according to the horizontal curve start-of-track quantity curve.

6. A railway track precision tamping plan generation device, characterized in that: The method comprises a processor and a memory, wherein the processor implements the method for generating a railway track precision ramming plan as described in any one of claims 1 to 4 when executing a computer program stored in the memory.

7. 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 railway track fine tamping plan according to any one of claims 1 to 4 is implemented.