Method for estimating ballast lateral resistance based on roughness of pillow bottom

Abstract

The application discloses a method for estimating track bed lateral resistance based on sleeper bottom roughness, which comprises the following steps: determining a sleeper bottom roughness index, establishing a plurality of sleeper models under different index values; obtaining a reference standard of lateral resistance based on sleeper and track bed models under different index values; defining sleepers on a to-be-tested track bed as to-be-tested sleepers, collecting sleeper bottom roughness of the to-be-tested sleepers; counting the proportion of the sleeper bottom roughness of the to-be-tested sleepers under the different index values; and calculating the lateral resistance of the to-be-tested track bed based on the proportion of the sleeper bottom roughness of the to-be-tested sleepers under the different index values and the reference standard of the lateral resistance. The application provides a method for estimating track bed lateral resistance based on sleeper bottom roughness, so as to solve the problem of low efficiency and serious dependence on railway field environment in the prior art when testing track bed lateral resistance, and achieve the purpose of efficiently and accurately estimating track bed lateral resistance.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of rail transit, in particular to a method for estimating ballast bed lateral resistance based on sleeper bottom roughness. BACKGROUND

[0002] Sleeper is a basic component in railway track structure for supporting steel rails and maintaining their position. The roughness of the contact surface between the sleeper bottom and the ballast bed has a significant impact on the friction between the sleeper and the ballast bed; a higher roughness of the sleeper bottom can provide greater friction, thereby increasing the adhesion of the sleeper and the ballast bed, which helps to prevent the displacement of the sleeper when the train passes; at the same time, a higher roughness of the sleeper bottom can increase the friction with the ballast bed, thereby increasing the lateral resistance and enhancing the anti-displacement ability of the track.

[0003] Therefore, in the design and maintenance of railway tracks, the roughness of the sleeper bottom and the lateral resistance of the ballast bed need to be considered comprehensively to ensure the reliability and safety of the track system. For example, in high-speed railways or heavy-load railways, due to the high speed of train operation or large axle load, the requirement for track stability is higher, so a rougher sleeper bottom design is adopted.

[0004] In the prior art, the test of the lateral resistance of the ballast bed needs to be completed by actually pushing the sleeper to move on the ballast bed, which is low in efficiency and heavily dependent on the railway site environment; and this traditional manual contact test method is prone to test errors and difficult to ensure accuracy. Therefore, it is necessary to develop a more efficient method for estimating the lateral resistance of the ballast bed. SUMMARY

[0005] The present application provides a method for estimating the lateral resistance of the ballast bed based on the roughness of the sleeper bottom, to solve the problem of low efficiency and heavy dependence on the railway site environment in testing the lateral resistance of the ballast bed in the prior art, and to achieve the purpose of efficiently and accurately estimating the lateral resistance of the ballast bed.

[0006] The present application is implemented by the following technical solutions:

[0007] A method for estimating the lateral resistance of the ballast bed based on the roughness of the sleeper bottom, comprising:

[0008] determining the roughness index of the sleeper bottom, and establishing a plurality of sleeper models under different index values;

[0009] based on the sleeper and ballast bed models under different index values, obtaining a reference standard for lateral resistance;

[0010] defining the sleeper on the ballast bed to be tested as a sleeper to be tested, and collecting the roughness index of the sleeper bottom of the sleeper to be tested;

[0011] statistically analyzing the proportion of the roughness index of the sleeper bottom of the sleeper to be tested under the different index values;

[0012] Based on the proportion of the sleeper bottom roughness index of the to-be-tested sleeper at different index values, and the reference standard of the lateral resistance, the lateral resistance of the to-be-tested track bed is calculated.

[0013] In view of the low efficiency and dependence on railway site environment in the prior art for testing the lateral resistance of the track bed, the present application provides a method for estimating the lateral resistance of the track bed based on sleeper bottom roughness. The method first determines an index representing the sleeper bottom roughness, which is defined as a sleeper bottom roughness index. Then, a plurality of models of the sleeper bottom roughness index at different values are established. Then, based on the plurality of models, a reference standard of the lateral resistance of the sleeper is obtained, which is used to represent the relationship between the lateral resistance and the sleeper bottom roughness index. Then, the sleeper bottom roughness index of the to-be-tested sleeper is collected, and the proportion of the sleeper bottom roughness index of the to-be-tested sleeper at different index values is counted. Finally, the counted proportion is combined with the reference standard of the lateral resistance of the sleeper, and the lateral resistance of the to-be-tested track bed is calculated.

[0014] It can be seen that the present application completely abandons the manual contact test method for the lateral resistance of the track bed in the prior art, and does not need to actually push the sleeper to move and does not depend on the railway site environment. At the same time, the present application overcomes the defect that the traditional test method is prone to test errors caused by manual operation errors, significantly improves the efficiency of obtaining the lateral resistance of the track bed, and is more conducive to ensuring the accuracy of the obtained lateral resistance of the track bed.

[0015] The sleeper bottom roughness index in the present application can be any index that can represent the roughness of the sleeper bottom surface that can be thought of by those skilled in the art, such as sleeper bottom roughness amplitude and / or sleeper bottom roughness wavelength. Preferably, both the sleeper bottom roughness amplitude and the sleeper bottom roughness wavelength are used as the sleeper bottom roughness index, which can improve the accuracy of the present application.

[0016] Further, the sleeper model at different index values is: the sleeper bottom roughness amplitude is taken as a plurality of different values in the range of 5-10 mm, the sleeper bottom roughness wavelength is taken as a plurality of different values in the range of 5-10 mm, different sleeper bottom roughness amplitudes and sleeper bottom roughness wavelengths are arranged and combined, and a plurality of sleeper models are obtained. The amplitude range of 5-10 mm can completely meet the simulation needs of the sleeper filled with coarse aggregate at present, thereby avoiding wasting computing power and time; the wavelength range of 5-10 mm is the same.

[0017] For example, A different sleeper bottom roughness amplitudes and B different sleeper bottom roughness wavelengths are arranged and combined to obtain AxB schemes, and a sleeper model is established for each scheme.

[0018] Further, the method for obtaining the reference standard of the lateral resistance comprises:

[0019] The sleeper model under different index values is simulated respectively to obtain the lateral resistance borne by the sleeper under different index values;

[0020] An interpolation operation is performed based on the lateral resistance borne by the sleeper under different index values to obtain a lateral resistance judgment curve group;

[0021] The lateral resistance judgment curve group is taken as a reference standard of the lateral resistance.

[0022] The scheme obtains the lateral resistance borne by the sleeper when the sleeper bottom roughness index is in different index values through simulation means, and performs an interpolation operation based on the obtained point values to obtain the required lateral resistance judgment curve. The interpolation operation can be implemented by using an existing mature interpolation algorithm, which is not limited here.

[0023] Further, the method for collecting the sleeper bottom roughness index of the sleeper to be tested comprises:

[0024] The sleeper bottom surface of the sleeper to be tested is scanned to obtain scanning data;

[0025] The sleeper bottom roughness index is extracted from the scanning data.

[0026] The scheme obtains the scanning data of the sleeper bottom surface through a non-contact scanning mode, and extracts the required sleeper bottom roughness index therefrom. The scanning mode can be any scanning mode that can be implemented by a person skilled in the art, such as laser, point cloud, infrared, ultrasonic wave, etc.

[0027] Further, the scanning data is obtained by a non-contact scanning process through a laser displacement sensor or a distance measuring sensor. The non-contact scanning process can avoid direct contact between the related test equipment and the sleeper bottom surface, and significantly reduces the risk of damage to the sleeper.

[0028] Further, the method for counting the proportion of the sleeper bottom roughness index of the sleeper to be tested under different index values comprises:

[0029] A sleeper bottom roughness index curve is drawn based on the extracted sleeper bottom roughness index;

[0030] The sleeper bottom roughness index curve is divided into a plurality of half-period intervals based on modal decomposition, and the starting point and the ending point of each half-period interval are identified;

[0031] The peak value of each half-period interval is detected to determine the wavelength of each half-period interval, and the maximum value and the minimum value in each half-period interval;

[0032] Each half-period interval is fitted based on the starting point, the ending point, the wavelength, the maximum value and the minimum value of each half-period interval to obtain a fitting function of each half-period interval;

[0033] Based on the fitting function of all half-cycle intervals, the amplitude of the pillow bottom roughness is statistically analyzed to obtain a dataset of amplitude and wavelength;

[0034] The proportion of different combinations of amplitude and wavelength of pillow bottom roughness in the data set for calculating amplitude and wavelength.

[0035] This scheme clearly defines the statistical methods for the proportion of different index values. First, after extracting the values ​​of the pillow bottom roughness index from the scanning data, the pillow bottom roughness index curve can be directly plotted. Then, the pillow bottom roughness index curve is divided into several half-cycle intervals using modal decomposition technology. After determining the start and end points of each half-cycle interval, the wavelength and extreme values ​​of each half-cycle interval can be determined, and then each half-cycle interval is fitted. Each half-cycle interval can obtain a fitting function. By combining the fitting functions of all half-cycle intervals, the fitting function corresponding to the entire pillow bottom roughness index curve can be obtained. Each half-cycle interval corresponds to a point value of pillow bottom roughness amplitude and a point value of pillow bottom roughness wavelength. By combining the point values ​​of pillow bottom roughness amplitude and pillow bottom roughness wavelength in all half-cycles, the amplitude and wavelength data set corresponding to the pillow bottom roughness index curve can be obtained. Based on this data set, the proportion of different combinations of amplitude and wavelength can be directly calculated.

[0036] Furthermore, the lateral resistance of the track bed under test is calculated using the following formula:

[0037] f=∑ω i ·f i ;

[0038] In the formula: f is the lateral resistance of the track bed to be measured; ω i f represents the percentage of the surface roughness index of the sleeper bottom under the i-th index value; i In the reference standard for lateral resistance, the lateral resistance value corresponding to the i-th index value.

[0039] It is understood that i = 1, 2, ..., N, where N is the total number of different index values ​​for the pillow bottom roughness index. Those skilled in the art should understand that each "index value" corresponds to a value for the pillow bottom roughness amplitude and a value for the pillow bottom roughness wavelength.

[0040] Furthermore, it also includes calculating the pillow bottom roughness index using the following method:

[0041] Calculate the surface roughness corresponding to each pillow bottom roughness index curve;

[0042] Based on the surface roughness corresponding to all the sleeper bottom roughness index curves, the sleeper bottom roughness index of the sleeper under test is calculated.

[0043] In existing technologies, the testing of lateral resistance of the track bed and the testing of sleeper bottom roughness are two completely independent sets of tests. If data on both lateral resistance and sleeper bottom roughness are required, two different tests must be performed on the sleepers, which is cumbersome and inefficient. However, with this solution, the sleeper bottom roughness can be obtained simultaneously during the estimation of lateral resistance of the track bed, significantly reducing the number of testing steps and improving testing efficiency.

[0044] Specifically, after drawing the pillow bottom roughness index curve through the aforementioned steps, this solution directly calculates the surface roughness corresponding to the curve and converts the surface roughness into the pillow bottom roughness index.

[0045] Since this application does not limit the specific number of scan data points for the pillow bottom surface, the scan data can be one, two, or more sets. Therefore, the pillow bottom roughness index curves can also be one, two, or more. When there is more than one pillow bottom roughness index curve, the surface roughness corresponding to each pillow bottom roughness index curve can be calculated separately, and then the overall pillow bottom roughness index of the sleeper under test can be obtained through statistical methods.

[0046] Furthermore, the formula for calculating the surface roughness corresponding to each pillow bottom roughness index curve is as follows:

[0047]

[0048] In the formula: q represents the q-th pillow bottom roughness index curve; R q Let A represent the surface roughness corresponding to the qth pillow bottom roughness index curve; m represents the mth half-cycle interval; n1 is the total number of half-cycle intervals in the qth pillow bottom roughness index curve; A m λ represents the roughness amplitude of the pillow bottom corresponding to the m-th half-cycle interval; m This represents the wavelength corresponding to the m-th half-cycle interval;

[0049] The formula for calculating the roughness index of the sleeper bottom is as follows:

[0050]

[0051] In the formula: R avg ω represents the surface roughness index of the sleeper bottom; i is the percentage of the bottom roughness of the sleeper under test at the i-th index value; n2 is the total number of bottom roughness index curves.

[0052] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0053] 1. The method for estimating the lateral resistance of a track bed based on the roughness of a sleeper bottom, which discards the manual contact type test mode for the lateral resistance of a track bed in the prior art, does not need to actually push the sleeper to move, does not depend on the railway site environment, overcomes the defect that the test error is large due to the manual operation error in the traditional test mode, significantly improves the efficiency of obtaining the lateral resistance of a track bed, and is more conducive to ensuring the accuracy of the obtained lateral resistance of a track bed.

[0054] 2. The method for estimating the lateral resistance of a track bed based on the roughness of a sleeper bottom, which obtains the scanning data of the sleeper bottom surface through a non-contact scanning mode, and extracts the required roughness index of the sleeper bottom, so that the direct contact between the related test equipment and the sleeper bottom surface is avoided, and the damage risk of the sleeper in the test process is reduced.

[0055] 3. The method for estimating the lateral resistance of a track bed based on the roughness of a sleeper bottom, which can simultaneously complete the acquisition of the roughness of the sleeper bottom in the process of estimating the lateral resistance of a track bed, significantly reduces the test steps, and improves the test efficiency. DETAILED DESCRIPTION

[0056] The accompanying drawings, which are included to provide a further understanding of the embodiments of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:

[0057] Figure 1 is a flowchart of the specific embodiment of the application;

[0058] Figure 2 is a schematic diagram of a sleeper model in the specific embodiment of the application;

[0059] Figure 3 is a schematic diagram of a discrete element model in the specific embodiment of the application;

[0060] Figure 4 is a partial schematic diagram of a lateral resistance determination curve in the specific embodiment of the application.

[0061] Figure 5 is a schematic diagram of a sleeper bottom roughness index curve in the specific embodiment of the application;

[0062] Figure 6 is a structural schematic diagram of a scanning device in the specific embodiment of the application;

[0063] Figure 7 is a top view of the scanning device in the specific embodiment of the application;

[0064] Figure 8 is a sectional view of the scanning device in the specific embodiment of the application.

[0065] Markings in the drawings and corresponding names of parts: Markings in the drawings and corresponding names of parts:

[0066] 1-Bracket, 2-Sliding frame, 3-Scanning equipment, 4-Displacement monitoring equipment, 5-Optical axis, 6-Sliding bearing, 7-Pull rope, 8-Sleeper. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments and accompanying drawings. The illustrative embodiments and descriptions of this invention are for explaining the invention only and are not intended to limit the invention. In the description of this application, it should be understood that terms such as "front," "rear," "left," "right," "upper," "lower," "vertical," "horizontal," "high," "low," "inner," and "outer," indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the scope of protection of this application.

[0068] Example 1:

[0069] like Figure 1 The method for estimating the lateral resistance of the track bed based on the roughness of the sleeper bottom, as shown, includes the following steps:

[0070] Step 1: Determine the roughness index of the sleeper bottom and establish several sleeper models under different index values.

[0071] Step 2: Based on the sleeper and track bed models under different index values, obtain the reference standard for lateral resistance; specifically including:

[0072] S201. Simulate the sleeper model under different index values ​​to obtain the lateral resistance of the sleeper under different index values.

[0073] S202. Based on the lateral resistance of the sleepers under different index values, interpolation calculations are performed to obtain a set of lateral resistance determination curves.

[0074] S203. The set of lateral resistance determination curves shall be used as the reference standard for lateral resistance.

[0075] Step 3: Define the sleepers on the track bed to be tested as sleepers to be tested, and collect the surface roughness index of the sleeper bottom; specifically including:

[0076] S301. Scan the bottom surface of the sleeper to be tested to obtain scan data; the scan data is obtained using a laser displacement sensor or a distance sensor through a non-contact scanning process.

[0077] S302. Extract the pillow bottom roughness index from the scan data.

[0078] Step 4, statistics of the proportion of the sleeper bottom roughness index of the to-be-tested sleeper at different index values; specifically comprising:

[0079] S401, based on the extracted sleeper bottom roughness index, a sleeper bottom roughness index curve is drawn;

[0080] S402, based on modal decomposition, the sleeper bottom roughness index curve is divided into several half-period intervals, and the starting point and the ending point of each half-period interval are identified;

[0081] S403, peak detection is performed on each half-period interval, and the wavelength of each half-period interval, as well as the maximum value and the minimum value in each half-period interval are determined;

[0082] S404, based on the starting point, the ending point, the wavelength, the maximum value and the minimum value of each half-period interval, each half-period interval is fitted to obtain a fitting function of each half-period interval;

[0083] S405, based on the fitting functions of all half-period intervals, the sleeper bottom roughness amplitude is calculated, and a dataset of amplitude and wavelength is obtained;

[0084] S406, in the dataset of amplitude and wavelength, the proportion corresponding to different combinations of sleeper bottom roughness amplitude and sleeper bottom roughness wavelength is calculated.

[0085] Step 5, based on the proportion of the sleeper bottom roughness of the to-be-tested sleeper at different index values, and the reference standard of lateral resistance, the lateral resistance of the to-be-tested track bed is calculated:

[0086] f=∑ω i ·f i ;

[0087] In the formula: f is the lateral resistance of the to-be-tested track bed; ω i is the proportion of the sleeper bottom roughness index of the to-be-tested sleeper at the i-th index value; f i is the lateral resistance value corresponding to the i-th index value in the reference standard of lateral resistance.

[0088] In this embodiment, the scanning data can include several groups, and a group of sleeper bottom roughness indexes is extracted from each group of scanning data, and a sleeper bottom roughness index curve is drawn accordingly. After calculating the lateral resistance corresponding to each sleeper bottom roughness index curve and taking the average value, a more accurate lateral resistance of the to-be-tested track bed can be obtained.

[0089] Embodiment 2:

[0090] A method for estimating the lateral resistance of the track bed based on the sleeper bottom roughness, based on embodiment 1, this embodiment takes the sleeper bottom roughness amplitude as an example to illustrate:

[0091] In this embodiment, first, in the range of 5-10 mm, take different sleeper bottom roughness amplitudes at intervals of 1 mm to establish sleeper models respectively; for example, establish a sleeper model with a sleeper bottom roughness amplitude of 5 mm, then establish a sleeper model with a sleeper bottom roughness amplitude of 6 mm, and so on, a total of 6 sleeper models. Figure 2 The schematic diagram of two sleeper models is shown in the figure, and it can be seen that the sleeper bottom roughness of the two sleeper models is obviously different.

[0092] Then, according to the type and related parameters of the track bed to be measured, a track bed model is established; each sleeper model is assembled to the track bed model, and is introduced into the discrete element software, as shown in the figure. Figure 3 The lateral resistance f i of the sleeper with a single amplitude as the roughness is obtained through simulation; at this time, i = 1, 2, …, 6. Interpolation operation is performed on the six f i , and the lateral resistance determination curve can be obtained; as shown in the figure. Figure 4 The local area of the lateral resistance determination curve is shown in the figure.

[0093] In this embodiment, the sleeper bottom surface to be measured is scanned by a plurality of laser displacement sensors. Taking a single laser displacement sensor as an example, the sleeper bottom roughness amplitude is extracted through the scanning data, and the sleeper bottom roughness index curve can be drawn, as shown in the figure. Figure 5

[0094] It should be noted that: Figure 5 The abscissa in the figure represents the length of the sleeper in the axial direction, and the unit is millimeter (mm); the ordinate represents the amplitude, and the unit is millimeter (mm).

[0095] Then, the sleeper bottom roughness index curve is divided into a plurality of half-period intervals by modal decomposition technology, the end points, wavelength, extreme value and other parameters are determined, then a sine function is used for fitting to obtain the amplitude of each half-period interval, and an amplitude data set is established. All values in the amplitude data set are counted, and the lateral resistance value corresponding to each value in the amplitude data set is obtained based on the lateral resistance determination curve; finally, the weighted sum is obtained, and the estimated track bed lateral resistance is obtained.

[0096] Embodiment 3:

[0097] A method for estimating the lateral resistance of a track bed based on the sleeper bottom roughness, the difference between this embodiment and embodiment 2 is that, in this embodiment, the sleeper bottom roughness index includes the sleeper bottom roughness amplitude and the sleeper bottom roughness wavelength; that is, the sleeper bottom roughness amplitude and the sleeper bottom roughness wavelength are used as the sleeper bottom roughness index together. For example:

[0098] ​Different sleeper bottom roughness amplitudes are taken at intervals of 1 mm in the range of 5-10 mm, and there are 6 point values of sleeper bottom roughness amplitude. Different sleeper bottom roughness wavelengths are taken at intervals of 1 mm in the range of 5-10 mm, and there are 6 point values of sleeper bottom roughness wavelength. Then 6x6 sleeper models need to be established in this embodiment.

[0099] Correspondingly, interpolation is performed on the sleeper bottom roughness amplitude and the sleeper bottom roughness wavelength respectively, and a plurality of lateral resistance determination curves can be obtained. All the lateral resistance determination curves are combined to obtain the lateral resistance determination curve group. The more the number of interpolation points, the higher the estimation accuracy of the lateral resistance in this embodiment.

[0100] In the subsequent modal decomposition process, the amplitude and wavelength data of each half-period interval are obtained, denoted as (A i ,λ i );

[0101] Then, the data set of amplitude and wavelength is established as follows: {(A1,λ1),(A2,λ2),(A3,λ3)…(A i ,λ i )…(A m ,λ m )}. Each group of data in the data set is substituted into the lateral resistance determination curve group, and the corresponding lateral resistance determination curve is found, so that the value of the lateral resistance corresponding to the group of data is obtained.

[0102] Embodiment 4:

[0103] On the basis of any of the above embodiments, in the process of estimating the lateral resistance of the track bed, the sleeper bottom roughness index is also calculated by the following method:

[0104] The surface roughness corresponding to each sleeper bottom roughness index curve is calculated.

[0105]

[0106] In the formula, q represents the qth sleeper bottom roughness index curve, R q is the surface roughness corresponding to the qth sleeper bottom roughness index curve, m represents the mth half-period interval, n1 is the total number of half-period intervals in the qth sleeper bottom roughness index curve, A m is the sleeper bottom roughness amplitude corresponding to the mth half-period interval, and λ m is the wavelength corresponding to the mth half-period interval.

[0107] Based on the surface roughness corresponding to all the sleeper bottom roughness index curves, the sleeper bottom roughness index of the sleeper to be measured is calculated.

[0108] Based on the surface roughness corresponding to all the sleeper bottom roughness index curves, the sleeper bottom roughness index of the sleeper to be measured is calculated.

[0109] In the formula: R avg ω represents the surface roughness index of the sleeper bottom; i is the percentage of the bottom roughness of the sleeper under test at the i-th index value; n2 is the total number of bottom roughness index curves.

[0110] Example 5:

[0111] Based on any of the above embodiments, the bottom surface of the sleeper to be tested is scanned using the following scanning device:

[0112] like Figure 6 to Figure 8 As shown, the scanning device includes a bracket 1, a sliding frame 2 that slides laterally on the bracket 1, and a scanning device 3 mounted on the sliding frame 2, with the scanning direction of the scanning device 3 being downward; it also includes a displacement monitoring device 4 mounted on the bracket 1, which is used to monitor the lateral displacement of the sliding frame 2.

[0113] The support 1 is a rectangular frame, and the sliding direction of the sliding frame 2 is parallel to the long axis of the support 1.

[0114] Optical axes 5 are provided on both sides of the top of the bracket 1. The optical axes 5 are parallel to the sliding direction of the sliding frame 2. The two ends of the sliding frame 2 are respectively slidably engaged with the optical axes 5 on both sides. There is a gap between the optical axis 5 and the inner side wall of the bracket on the same side to accommodate the sliding bearing 6. Sliding bearings 6 are provided at both ends of the sliding frame 2, and the sliding bearings 6 are sleeved on the corresponding optical axes 5.

[0115] In this embodiment, the scanning device 3 can be a laser displacement sensor or a distance sensor, preferably a laser displacement sensor.

[0116] In this embodiment, the sleeper to be tested is placed upside down inside the bracket 1, and the scanning device 3 and displacement monitoring device 4 are started, so that the sliding frame 2 can slide from one end of the travel to the other end.

[0117] In a more preferred embodiment, the height of the bracket 1 is adjustable. A level can also be installed on the bracket 1 to ensure that its top surface remains horizontal after height adjustment, thereby ensuring that the axis of the optical axis 5 is horizontal.

[0118] In a more preferred embodiment, at least three scanning devices 3 are installed at the bottom of the sliding frame 2. The three scanning devices 3 are evenly distributed along a straight line, and the direction of the line connecting all the scanning devices 3 is perpendicular to the sliding direction of the sliding frame 2.

[0119] In a more preferred embodiment, a power device for driving the sliding frame 2 to slide is also included.

[0120] Preferably, the power device comprises a pull rope 7 connected to the sliding frame 2; the displacement monitoring device 4 is a pull rope displacement sensor connected to the pull rope 7, and the pull rope displacement sensor is installed on the inner wall of the long axis direction of the support 1 at one end.

[0121] Preferably, the pull rope 7 is connected to one end of the sliding frame 2 and an elastic rope is connected to the other end; when the sliding frame 2 slides to the end close to the pull rope displacement sensor, the pull rope displacement sensor is released from driving, and the sliding frame 2 is reset to the other end by the elastic rope, facilitating the test of the next sleeper.

[0122] Preferably, the pull rope 7 is connected to one end of the sliding frame 2, and the pull rope 7 is connected to the pull rope displacement sensor, and the other end of the sliding frame 2 is not connected; after the test of one sleeper is completed, the sliding frame 2 is manually reset by the on-site staff.

[0123] The surface roughness of the bottom of the railway sleeper is an important quality index in railway construction and maintenance. The traditional test method mostly needs a contact type measuring device to work on the sleeper bottom surface, and this test method has the risk of damaging the sleeper bottom surface. Compared with the prior art, the test device of the embodiment does not need to contact the sleeper, and realizes truly non-contact testing, so as to avoid the direct contact between the test device and the sleeper bottom surface, and significantly reduce the risk of sleeper damage. At the same time, the use process of the embodiment is simple and convenient, and the accuracy and test efficiency of the roughness test are improved.

[0124] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0125] It should be noted that in this document, terms such as "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. In addition, the term "connected" used in this document can be directly connected or indirectly connected via other components without special description.

Claims

1. A method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom, characterized in that, include: Determine the roughness index of the sleeper bottom and establish several sleeper models under different index values; Based on sleeper and track bed models with different index values, a reference standard for lateral resistance is obtained; The sleepers on the track bed to be tested are defined as sleepers to be tested, and the roughness index of the sleeper bottom is collected. The percentage of the bottom roughness index of the sleeper under test under different index values ​​was statistically analyzed. Based on the proportion of the roughness index of the sleeper bottom under different index values ​​and the reference standard of the lateral resistance, the lateral resistance of the track bed under test is calculated. The methods for obtaining the reference standard for lateral resistance include: Simulations were performed on sleeper models under different index values ​​to obtain the lateral resistance experienced by the sleepers under different index values. Interpolation calculations are performed on the lateral resistance experienced by the sleepers under different index values ​​to obtain a set of lateral resistance determination curves. The aforementioned set of lateral resistance determination curves is used as a reference standard for lateral resistance.

2. The method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom according to claim 1, characterized in that, The pillow bottom roughness indicators include: pillow bottom roughness amplitude and pillow bottom roughness wavelength.

3. The method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom according to claim 2, characterized in that, The sleeper models under different index values ​​are: taking several different values ​​of sleeper bottom roughness amplitude in the range of 5 to 10 mm, taking several different values ​​of sleeper bottom roughness wavelength in the range of 5 to 10 mm, and arranging and combining different sleeper bottom roughness amplitude and sleeper bottom roughness wavelength to obtain several sleeper models.

4. The method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom according to claim 1, characterized in that, Methods for collecting the surface roughness index of the sleeper under test include: Scan the bottom surface of the sleeper to be tested to obtain scan data; Extract the pillow bottom roughness index from the scan data.

5. The method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom according to claim 4, characterized in that, The scanning data is obtained using a laser displacement sensor or a distance sensor through a non-contact scanning process.

6. The method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom according to claim 4, characterized in that, Methods for statistically analyzing the percentage of different index values ​​for the bottom roughness index of the sleeper under test include: Based on the extracted pillow bottom roughness index, a pillow bottom roughness index curve is plotted. Based on modal decomposition, the pillow bottom roughness index curve is divided into several half-cycle intervals, and the start and end points of each half-cycle interval are marked. Peak detection is performed on each half-cycle interval to determine the wavelength of each half-cycle interval, as well as the maximum and minimum values ​​within each half-cycle interval; Based on the start point, end point, wavelength, maximum and minimum values ​​of each half-cycle interval, fit each half-cycle interval to obtain the fitting function for each half-cycle interval. Based on the fitting function of all half-cycle intervals, the amplitude of the pillow bottom roughness is statistically analyzed to obtain a dataset of amplitude and wavelength; The proportion of different combinations of amplitude and wavelength of pillow bottom roughness in the data set for calculating amplitude and wavelength.

7. The method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom according to claim 1, characterized in that, The lateral resistance of the track bed to be tested is calculated using the following formula: f=∑ω i ·f i ; In the formula: f is the lateral resistance of the track bed to be measured; ω i f represents the percentage of the surface roughness index of the sleeper bottom under the i-th index value; i In the reference standard for lateral resistance, the lateral resistance value corresponding to the i-th index value.

8. The method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom according to claim 6, characterized in that, It also includes calculating the pillow bottom roughness index using the following method: Calculate the surface roughness corresponding to each pillow bottom roughness index curve; Based on the surface roughness corresponding to all the sleeper bottom roughness index curves, the sleeper bottom roughness index of the sleeper under test is calculated.

9. A method for estimating the lateral resistance of a track bed based on the roughness of the sleeper bottom, as described in claim 8, is characterized in that... The formula for calculating the surface roughness corresponding to each pillow bottom roughness index curve is as follows: In the formula: q represents the q-th pillow bottom roughness index curve; R q Let A represent the surface roughness corresponding to the qth pillow bottom roughness index curve; m represents the mth half-cycle interval; n1 is the total number of half-cycle intervals in the qth pillow bottom roughness index curve; A m λ represents the roughness amplitude of the pillow bottom corresponding to the m-th half-cycle interval; m This represents the wavelength corresponding to the m-th half-cycle interval; The formula for calculating the roughness index of the sleeper bottom is as follows: In the formula: R avg ω represents the surface roughness index of the sleeper bottom; i is the percentage of the bottom roughness of the sleeper under test at the i-th index value; n2 is the total number of bottom roughness index curves.

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