A method and device for evaluating dynamic quality of urban rail transit vibration-damping ballast bed based on displacement data

Abstract

The present invention discloses a method and device for evaluating the dynamic quality of a vibration-damping track bed of urban rail transit based on displacement data, the method comprising: acquiring real-time displacement monitoring data in each monitoring section; preprocessing the acquired real-time displacement monitoring data in each monitoring section; calculating the preprocessed displacement monitoring data to determine track dynamic quality correlation parameters, and using the obtained correlation parameters to evaluate the dynamic quality of the track bed. The method and device for evaluating the dynamic quality of a vibration-damping track bed of urban rail transit based on displacement data of the present invention calculates the preprocessed displacement monitoring data to determine track dynamic quality correlation parameters, and uses the obtained correlation parameters to evaluate the dynamic quality of the track bed, which can predict the health status of the vibration-damping track, realize intelligent early warning of the vibration-damping track status, and help evaluate the health status of the vibration-damping track bed, which is of great significance to improving the performance retention capability of the vibration-damping track.

Description

Technical Field

[0001] The present invention belongs to the technical field of rail transit, and in particular relates to a method and device for evaluating the dynamic quality of a vibration-damping roadbed of an urban rail transit based on displacement data. Background Art

[0002] With the rapid development of urban rail transit and the improvement of people's requirements for living and riding environment, the vibration and noise impacts caused by urban rail transit operations have increasingly attracted the attention of residents and passengers along the line. In order to reduce the environmental vibration and noise problems induced by urban rail transit, corresponding rail vibration reduction measures were taken according to the requirements of the environmental impact assessment report during the subway construction phase. However, as the operation time increases, some sections will have problems such as excessive ground vibration or secondary structure noise and excessive noise inside the car, which will affect the quality of life of residents along the line and the riding experience of passengers, and cause related complaints.

[0003] The vibration and noise status of urban rail transit is mainly related to the dynamic quality of the track and the dynamic quality of the ballast. At present, the dynamic quality of the track is mainly analyzed and evaluated by track inspection vehicles and other equipment. The evaluation index is mainly the track quality index TQI (track quality index) that reflects the smoothness of the line section. However, there are no clear evaluation indicators and evaluation methods for the dynamic quality of the ballast in the industry. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes a dynamic quality assessment method and device for urban rail transit vibration-damping track based on displacement data based on dynamic displacement data obtained by real-time monitoring. This method helps to evaluate the health status of the vibration-damping track and is of great significance to improving the performance retention capability of the vibration-damping track.

[0005] The first aspect of the present invention provides a method for evaluating the dynamic quality of an urban rail transit vibration-damping ballast based on displacement data, comprising:

[0006] Obtain real-time displacement monitoring data in each monitoring section;

[0007] Preprocessing the real-time displacement monitoring data acquired in each monitoring section;

[0008] The preprocessed displacement monitoring data are calculated to determine the track dynamic quality correlation parameters, and the obtained correlation parameters are used to evaluate the dynamic quality of the track bed.

[0009] According to an embodiment of the present invention, the displacement monitoring data includes: data of at least five vertical displacement measurement points and data of at least two lateral displacement measurement points;

[0010] Acquiring real-time displacement monitoring data in each monitoring section includes: placing at least one front-end displacement sensing device at specific positions on both sides of the vibration-damping track bed plate to obtain real-time track bed displacement signals.

[0011] The preprocessing of the acquired real-time displacement monitoring data in each monitoring section includes:

[0012] Determine each displacement waveform according to the acquired real-time ballast bed displacement signal;

[0013] A specific time period when a train passes through is captured from the collected real-time displacement monitoring data as data for subsequent calculation of the roadbed quality index; the specific time period when the train passes through includes the minimum data capture start time and the maximum data capture end time of all displacement measuring points as the displacement data waveform capture time range in each monitoring section.

[0014] According to an embodiment of the present invention, calculating the preprocessed displacement monitoring data to determine the track dynamic quality associated parameters includes:

[0015] According to the time range of displacement data waveform interception in each monitoring section, the mean value of the intercepted data time history curve is determined;

[0016] According to the mean value of the intercepted data time history curve, the track dynamic quality correlation parameters corresponding to the vertical displacement or lateral displacement of the track bed in each monitoring section are determined.

[0017] According to an implementation scheme of the present invention, the track dynamic quality associated parameters include at least one of the maximum standard deviation of the vertical displacement of the track bed, the maximum standard deviation of the lateral displacement of the track bed, the standard deviation of the dynamic superelevation of the track bed, the standard deviation of the vertical displacement between track beds, the standard deviation of the vertical torsion of the track bed, and the standard deviation of the horizontal torsion of the track bed.

[0018] According to an embodiment of the present invention, the track dynamic quality correlation parameter is the track bed quality index TSI, TSI = σ V +σ H +σ sh +σ bt +σ vtw +σ htw

[0019] Among them, σ v is the maximum standard deviation of the vertical displacement of the ballast bed, σ H is the maximum standard deviation of the lateral displacement of the track bed, σ sh is the standard deviation of the dynamic superelevation of the track bed, σ bt is the standard deviation of vertical displacement between ballasts, σ vtw is the standard deviation of the vertical torsion of the ballast bed, σ htw is the standard deviation of the horizontal torsion of the ballast bed.

[0020] A second aspect of the present invention provides a device for evaluating the dynamic quality of an urban rail transit vibration-damping ballast bed based on displacement data, comprising:

[0021] An acquisition module, used to acquire real-time displacement monitoring data in each monitoring section;

[0022] A preprocessing module, used for preprocessing the acquired real-time displacement monitoring data in each monitoring section;

[0023] The determination module is used to calculate the pre-processed displacement monitoring data to determine the track dynamic quality correlation parameters, and use the obtained correlation parameters to evaluate the dynamic quality of the track bed.

[0024] A third aspect of the present invention provides an electronic device, comprising: a memory and one or more processors;

[0025] The memory is used to store one or more programs;

[0026] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for dynamic quality assessment of urban rail transit vibration-damping track bed based on displacement data as provided in any embodiment.

[0027] A fourth aspect of the present invention provides a storage medium containing computer executable instructions, which are used by a computer processor to implement a method for evaluating the dynamic quality of an urban rail transit vibration-damping track bed based on displacement data as provided in any embodiment.

[0028] Compared with the prior art, the present invention has the following advantages:

[0029] The method and device for evaluating the dynamic quality of the vibration-damping track bed of urban rail transit based on displacement data of the present invention can calculate the preprocessed displacement monitoring data to determine the track dynamic quality correlation parameters, and use the obtained correlation parameters to evaluate the dynamic quality of the track bed, which can predict the health status of the vibration-damping track, realize intelligent early warning of the vibration-damping track status, and help evaluate the health status of the vibration-damping track bed, which is of great significance to improving the performance retention capability of the vibration-damping track. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Flow chart of a method for evaluating dynamic quality of urban rail transit vibration-damping ballast based on displacement data according to an embodiment of the present invention;

[0031] Figure 2 for Figure 1 Cross-sectional diagram of displacement measuring points in ;

[0032] Figure 3 for Figure 1 Plane diagram of displacement measuring points in ;

[0033] Figure 4 is another flow chart of a method for evaluating dynamic quality of an urban rail transit vibration-damping ballast based on displacement data according to an embodiment of the present invention;

[0034] Figure 5 for Figure 4 Schematic diagram of displacement signal preprocessing in ;

[0035] Figure 6 is another flow chart of a method for evaluating dynamic quality of an urban rail transit vibration-damping ballast based on displacement data according to an embodiment of the present invention;

[0036] Figure 7 is a schematic diagram of a dynamic quality assessment device for an urban rail transit vibration-damping ballast based on displacement data according to an embodiment of the present invention; and

[0037] Figure 8 The figure is a schematic diagram of the arrangement of measurement points for the ballast bed acceleration, rail acceleration and tunnel wall acceleration according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The present invention is further described in detail below through specific embodiments in conjunction with the accompanying drawings. The shown contents are used to fully illustrate the contents of the present invention, but are not used to limit the present invention.

[0039] like Figure 1 As shown, the present invention provides a method for evaluating the dynamic quality of an urban rail transit vibration-damping ballast bed based on displacement data, comprising:

[0040] S101, obtaining real-time displacement monitoring data in each monitoring section;

[0041] The displacement monitoring data includes: data from at least five vertical displacement measurement points and data from at least two lateral displacement measurement points; obtaining real-time displacement monitoring data in each monitoring section includes: arranging at least one front-end displacement sensing device at specific positions on both sides of the vibration-damping track bed plate to obtain real-time track bed displacement signals.

[0042] The real-time acquisition of displacement monitoring data is mainly divided into five steps: front-end sensing equipment deployment, data collection, data analysis, real-time data upload, and data storage. Based on the above steps, the roadbed displacement signal of each train passing through a designated section of urban rail transit can be obtained.

[0043] like Figure 2 and Figure 3As shown in the figure, the front-end displacement sensing equipment needs to be arranged on both sides of the vibration-damping track bed, which is mainly divided into 7 vertical displacement measuring points and lateral displacement measuring points. There are 5 vertical displacement measuring points: 1 at each of the 4 corners of the vibration-damping track bed 1 (measuring points 1 to 4), and 1 at the end of the vibration-damping track bed 2 that is closer to the vibration-damping track bed 1 (measuring point 5); 2 lateral displacement measuring points: 1 at each of the 2 corners of the 1st side of the vibration-damping track bed 1 (measuring points 6 and 7).

[0044] S102, preprocessing the acquired real-time displacement monitoring data in each monitoring section;

[0045] like Figure 4 and 5 As shown, the preprocessing of the acquired real-time displacement monitoring data in each monitoring section includes:

[0046] The time history diagram of the vertical displacement monitoring data collected according to the above steps is as follows: Figure 5 As shown, since the speeds of each subway vehicle passing through the monitoring section are different, in order to ensure that the entire process of the subway vehicle passing through the monitoring section can be collected, the present invention uniformly adopts a sampling time of 60 seconds. Before calculating the roadbed quality index, it is first necessary to intercept the time period when the train passes from the collected displacement data as the subsequent roadbed quality index calculation data.

[0047] S101-1. Determine each displacement waveform according to the acquired real-time ballast bed displacement signal;

[0048] Assuming that the sampling frequency of displacement monitoring data is f, the number of sampling points nfft obtained by collecting data for each subway train is

[0049] nfft=60×f

[0050] Assuming that the vertical displacement response time history is y, first find the absolute maximum value S of the displacement response time history:

[0051] S = max(abs(y(1:1:nfft)))

[0052] Then, the vertical displacement limit is selected as α times the absolute maximum displacement value. The value of α can be selected according to actual conditions. In the embodiment of the present invention, α=0.2.

[0053] S101-2, extracting a specific time period when a train passes through from the collected real-time displacement monitoring data as data for subsequent calculation of the roadbed quality index;

[0054] Finally, based on the displacement limit, the data of the train passing period is intercepted, and the interception principle is as follows:

[0055] for i=1:1:nfft if(y(t i)>αS)T start =t i

[0056] for j=nff:1:1 if(y(t j )>αS)T end =t j

[0057] Among them, T start is the start time of data capture, T end The data capture end time.

[0058] Since each monitoring section has multiple vertical displacement measurement points, in order to ensure the integrity of each vertical displacement waveform;

[0059] The specific time period during the passage includes the minimum value of the data capture start time and the maximum value of the data capture end time of all displacement measuring points as the displacement data waveform capture time range in each monitoring section.

[0060] S103, calculating the preprocessed displacement monitoring data to determine track dynamic quality correlation parameters, and using the obtained correlation parameters to evaluate the dynamic quality of the track bed.

[0061] The dynamic quality evaluation index of the subway vibration-damping track bed is the track bed quality index TSI (Track Status Index). The track bed quality index TSI is mainly composed of 6 sub-indicators: the maximum standard deviation of the track bed vertical displacement, the maximum standard deviation of the track bed lateral displacement, the standard deviation of the track bed dynamic superelevation, the standard deviation of the vertical displacement between track beds, the standard deviation of the track bed vertical torsion, and the standard deviation of the track bed horizontal torsion. The calculation methods of each sub-indicator are as follows:

[0062] 1. Maximum standard deviation of vertical displacement of track bed

[0063] Each monitoring section has 5 track bed vertical displacement measurement points ( Figure 4 ), the standard deviation of the jth vertical displacement measurement point is calculated as

[0064]

[0065] Wherein, μ is the mean value of the data time course curve after data interception.

[0066] The maximum standard deviation of the vertical displacement of the ballast bed is the maximum standard deviation of the five ballast bed vertical displacement measurement points.

[0067]

[0068] 2. Maximum standard deviation of lateral displacement of track bed

[0069] Each monitoring section has 2 lateral displacement measurement points of the track bed ( Figure 4), the standard deviation of the jth lateral displacement measurement point is calculated as

[0070]

[0071] Wherein, μ is the mean value of the data time course curve after data interception.

[0072] The maximum standard deviation of the lateral displacement of the track bed is the maximum standard deviation of the two lateral displacement measurement points of the track bed.

[0073]

[0074] 3. Standard deviation of dynamic superelevation of track bed

[0075] The standard deviation of dynamic superelevation of the track bed refers to the time-history standard deviation obtained by subtracting the vertical displacement waveforms of measuring points 1 and 2 (after data interception). The specific calculation formula is as follows

[0076]

[0077]

[0078] 4. Standard deviation of vertical displacement between ballasts

[0079] The standard deviation of vertical displacement between track beds refers to the time-course standard deviation obtained by subtracting the vertical displacement waveforms of measuring points 4 and 5 (after data interception). The specific calculation formula is as follows:

[0080]

[0081]

[0082] 5. Standard deviation of vertical torsion of ballast bed

[0083] The standard deviation of the vertical torsion of the track bed refers to (subtraction of the vertical displacement waveforms of measuring points 1 and 2) - (subtraction of the vertical displacement waveforms of measuring points 3 and 4) (after data truncation). The specific calculation formula for calculating the time history standard deviation is as follows:

[0084]

[0085]

[0086] 6. Standard deviation of horizontal torsion of track bed

[0087] The standard deviation of vertical torsion of the track bed refers to the time-history standard deviation obtained by subtracting the vertical displacement waveforms of the 4th and 5th measuring points (after data interception). The specific calculation formula is as follows:

[0088]

[0089]

[0090] Based on the above components, the calculation method of the track bed quality index TSI is as follows:

[0091] TSI=σ V +σ H +σ sh +σ bt +σ vtw +σ htw

[0092] Among them, σ v is the maximum standard deviation of the vertical displacement of the ballast bed, σ H is the maximum standard deviation of the lateral displacement of the track bed, σ sh is the standard deviation of the dynamic superelevation of the track bed, σ bt is the standard deviation of vertical displacement between ballasts, σ vtw is the standard deviation of the vertical torsion of the ballast bed, σ htw is the standard deviation of the horizontal torsion of the ballast bed.

[0093] According to the implementation scheme of the present invention, the vibration-damping track bed of urban rail transit can adopt, for example, a steel spring floating plate track bed or a high-grade vibration-damping track bed. According to the dynamic quality assessment method of the urban rail transit vibration-damping track bed based on displacement data of the present invention, the track dynamic quality association parameter can adopt the above-mentioned TSI, and the dynamic quality of the subway vibration-damping track bed can be divided into Grade I, Grade II, and Grade III. More specifically, for the steel spring floating plate track bed, 0<TSI≤2.6 is excellent, 2.6<TSI≤3.0 is good, and TSI>3.0 is poor; for the high-grade vibration-damping track bed such as the trapezoidal sleeper, 0<TSI≤1.6 is excellent, 1.6<TSI≤2.0 is good, and TSI>2.0 is poor.

[0094] Figure 7 A schematic diagram of a dynamic quality assessment device for urban rail transit vibration-damping ballast bed based on displacement data is provided for an embodiment of the present invention. Figure 7 As shown, including:

[0095] An acquisition module 710 is used to acquire real-time displacement monitoring data in each monitoring section;

[0096] A preprocessing module 720 is used to preprocess the acquired real-time displacement monitoring data in each monitoring section;

[0097] The determination module 730 is used to calculate the pre-processed displacement monitoring data to determine the track dynamic quality correlation parameters, and use the obtained correlation parameters to evaluate the dynamic quality of the track bed.

[0098] Optionally, the displacement monitoring data includes: data of at least five vertical displacement measurement points and data of at least two lateral displacement measurement points;

[0099] The pre-processing module 720 is used to arrange at least one front-end displacement sensing device at specific positions on both sides of the vibration-damping roadbed plate to obtain a real-time roadbed displacement signal;

[0100] Determine each displacement waveform according to the acquired real-time ballast bed displacement signal;

[0101] A specific time period when a train passes through is captured from the collected real-time displacement monitoring data as data for subsequent calculation of the roadbed quality index; the specific time period when the train passes through includes the minimum data capture start time and the maximum data capture end time of all displacement measuring points as the displacement data waveform capture time range in each monitoring section.

[0102] Optionally, the determination module 730 is used to determine the mean value of the intercepted data time course curve according to the interception time range of the displacement data waveform in each monitoring section;

[0103] According to the mean value of the intercepted data time history curve, the track dynamic quality correlation parameters corresponding to the vertical displacement or lateral displacement of the track bed in each monitoring section are determined.

[0104] Optionally, the track dynamic quality associated parameters include at least one of the maximum standard deviation of the track bed vertical displacement, the maximum standard deviation of the track bed lateral displacement, the standard deviation of the track bed dynamic superelevation, the standard deviation of the track bed vertical displacement between track beds, the standard deviation of the track bed vertical torsion, and the standard deviation of the track bed horizontal torsion.

[0105] Optionally, the track dynamic quality associated parameter is the track bed quality index TSI,

[0106] TSI=σ V +σ H +σ sh +σ bt +σ vtw +σ htw

[0107] Among them, σ v is the maximum standard deviation of the vertical displacement of the ballast bed, σ H is the maximum standard deviation of the lateral displacement of the track bed, σ sh is the standard deviation of the dynamic superelevation of the track bed, σ bt is the standard deviation of vertical displacement between ballasts, σ vtw is the standard deviation of the vertical torsion of the ballast bed, σ htw is the standard deviation of the horizontal torsion of the ballast bed.

[0108] The urban rail transit vibration-damping track bed dynamic quality assessment device based on displacement data provided in an embodiment of the present invention can execute the urban rail transit vibration-damping track bed dynamic quality assessment method based on displacement data provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0109] Figure 8 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 8 As shown, the electronic device includes a processor 810, a memory 820, an input device 830 and an output device 840; the number of the processor 810 in the electronic device can be one or more. Figure 8 A processor 810 is taken as an example; the processor 810, the memory 820, the input device 830 and the output device 840 in the electronic device can be connected via a bus or other means. Figure 8 The example of connecting through bus is taken in the following.

[0110] The memory 820, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the method for dynamic quality assessment of urban rail transit vibration-damping roadbed based on displacement data in the embodiment of the present invention (for example, the real-time displacement monitoring data representation acquisition module 710, the pre-processed real-time displacement monitoring data representation preprocessing module 720, and the track dynamic quality associated parameter representation determination module 730 in the device for dynamic quality assessment of urban rail transit vibration-damping roadbed based on displacement data). The processor 810 executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 820, that is, realizes the above-mentioned method for dynamic quality assessment of urban rail transit vibration-damping roadbed based on displacement data.

[0111] The memory 820 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 820 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 820 may further include a memory remotely arranged relative to the processor 810, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0112] The input device 830 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the electronic device. The output device 840 may include a display device such as a display screen.

[0113] The embodiment of the present invention further provides a storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute a method for evaluating the dynamic quality of a vibration-damping roadbed of urban rail transit based on displacement data when executed by a computer processor, including:

[0114] Obtain real-time displacement monitoring data in each monitoring section;

[0115] Preprocessing the real-time displacement monitoring data acquired in each monitoring section;

[0116] The preprocessed displacement monitoring data are calculated to determine the track dynamic quality correlation parameters, and the obtained correlation parameters are used to evaluate the dynamic quality of the track bed.

[0117] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present invention is not limited to the method operations described above, and can also execute related operations in the method for dynamic quality assessment of urban rail transit vibration-damping trackbed based on displacement data provided in any embodiment of the present invention.

[0118] The above description of the embodiments is to facilitate the understanding and application of the present invention by those skilled in the art. It is obvious that those skilled in the art can easily make various modifications to these embodiments and apply the general principles described herein to other embodiments without creative work. Therefore, the present invention is not limited to the embodiments herein, and improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the present invention should be within the scope of protection of the present invention.

Claims

1. A method for evaluating the dynamic quality of urban rail transit vibration-damping ballast based on displacement data, characterized in that: Including: S101. Obtain the real-time displacement monitoring data in each monitoring section; S102. Preprocess the real-time displacement monitoring data obtained in each monitoring section; And S103. Calculate the preprocessed displacement monitoring data to determine the track dynamic quality correlation parameters, and use the obtained correlation parameters to evaluate the dynamic quality of the roadbed; Among them, step S103 includes: Determine the time range according to the displacement data waveform in each monitoring section, and determine the mean value of the time history curve of the data after interception; and According to the mean value of the time history curve of the data after interception, determine the track dynamic quality correlation parameters corresponding to the vertical displacement or lateral displacement of the roadbed in each monitoring section; Among them, the track dynamic quality correlation parameter is the roadbed quality index TSI, TSI=σ V +s H +s sh +s bt +s vtw +s htw Among them, σ v is the maximum standard deviation of the vertical displacement of the ballast bed, σ H is the maximum standard deviation of the lateral displacement of the track bed, σ sh is the standard deviation of dynamic superelevation of the track bed, σ bt is the standard deviation of vertical displacement between ballasts, σ vtw is the standard deviation of the vertical torsion of the ballast bed, σ htw is the standard deviation of the horizontal torsion of the ballast bed.

2. The method for evaluating the dynamic quality of urban rail transit vibration-damping ballast bed based on displacement data according to claim 1, characterized in that: In S101, the displacement monitoring data includes: data of at least five vertical displacement measurement points and data of at least two lateral displacement measurement points.

3. The method for evaluating the dynamic quality of urban rail transit vibration-damping ballast bed based on displacement data according to claim 1, characterized in that: Step S102 includes: Determine each displacement waveform according to the obtained real-time roadbed displacement signal; and Intercept a specific time period when the train passes from the collected real-time displacement monitoring data as the subsequent roadbed quality index calculation data; the specific time period when the train passes includes the minimum data interception start time and the maximum data interception end time of all displacement measurement points as the time range for intercepting the displacement data waveform in each monitoring section.

4. The method for evaluating the dynamic quality of urban rail transit vibration-damping ballast bed based on displacement data according to claim 1, characterized in that: The vibration damping roadbed is a steel spring floating slab roadbed. When 0 < TSI ≤ 7, the quality of the vibration damping roadbed is judged as excellent; when 7 < TSI ≤ 10, it is judged as good, and when TSI > 10, it is judged as poor.

5. The method for evaluating the dynamic quality of urban rail transit vibration-damping ballast bed based on displacement data according to claim 1, characterized in that: The vibration damping roadbed is a high-level vibration damping roadbed. When 0 < TSI ≤ 1.6, the quality of the vibration damping roadbed is judged as excellent; when 1.6 < TSI ≤ 2.2, it is judged as good, and when TSI > 2.2, it is judged as poor.

6. A dynamic quality assessment device for urban rail transit vibration-damping ballast bed based on displacement data, characterized in that: Including: An acquisition module for acquiring the real-time displacement monitoring data in each monitoring section; A preprocessing module for preprocessing the real-time displacement monitoring data obtained in each monitoring section; A determination module for calculating the preprocessed displacement monitoring data to determine the track dynamic quality correlation parameters, and using the obtained correlation parameters to evaluate the dynamic quality of the roadbed; Among them, the track dynamic quality correlation parameter is the roadbed quality index TSI, TSI=σ V +s H +s sh +s bt +s vtw +s htw Among them, σ v is the maximum standard deviation of the vertical displacement of the ballast bed, σ H is the maximum standard deviation of the lateral displacement of the track bed, σ sh is the standard deviation of dynamic superelevation of the track bed, σ bt is the standard deviation of vertical displacement between ballasts, σ vtw is the standard deviation of the vertical torsion of the ballast bed, σ htw is the standard deviation of the horizontal torsion of the ballast bed.

7. An electronic device, characterized in that: Including: A memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1-5.

8. A storage medium containing computer executable instructions, characterized in that: The computer-executable instructions implement the method according to any one of claims 1-5 by a computer processor.

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