阅读说明：本技术 一种轨道平顺性测试方法及系统 (Track ride comfort testing method and system ) 是由 白征东 陈波波 辛浩浩 黎奇 程宇航 于 2019-09-29 设计创作，主要内容包括：本发明实施例提供一种轨道平顺性测试方法及系统,该方法包括：利用采样装置在待测轨道上行走采样,获取姿态角观测序列、里程观测序列、轨距观测序列以及轨枕观测序列；将姿态角观测序列、里程观测序列和轨距观测序列进行内插融合,获取观测集合序列；并基于观测集合序列,获取采样装置的相对轨迹序列；基于GNSS静止采样点状态参数约束,根据采样轨迹的参数序列,获取待测轨道的中线绝对轨迹；根据中线绝对轨迹结合姿态角观测序列、轨距观测序列、轨枕观测序列和设计资料获取待测轨道的平顺性参数。本发明实施例提供的轨道平顺性测试方法及系统,提供了一种铁路轨道的调轨及检测途径,对于轨道平顺性,尤其是内部参数的检测更加精准。(The embodiment of the invention provides a method and a system for testing track smoothness, wherein the method comprises the following steps: the method comprises the following steps of walking and sampling on a rail to be detected by using a sampling device, and acquiring an attitude angle observation sequence, a mileage observation sequence, a track gauge observation sequence and a sleeper observation sequence; interpolating and fusing the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; acquiring a relative track sequence of the sampling device based on the observation set sequence; acquiring a midline absolute track of a track to be detected according to a parameter sequence of a sampling track based on the GNSS static sampling point state parameter constraint; and acquiring ride comfort parameters of the track to be measured according to the neutral line absolute track combined with the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data. The rail smoothness testing method and the rail smoothness testing system provided by the embodiment of the invention provide a rail adjusting and detecting way for a railway rail, and the detection of the rail smoothness, especially the internal parameters is more accurate.)

1. A method for testing track smoothness is characterized by comprising the following steps:

s1, walking and sampling on a rail to be detected by using a sampling device, and acquiring an attitude angle observation sequence, a mileage observation sequence, a track gauge observation sequence and a sleeper observation sequence on the rail to be detected;

s2, carrying out interpolation fusion on the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; acquiring a relative track sequence of the sampling device based on the observation set sequence;

s3, acquiring a midline absolute track of the track to be detected according to the relative track sequence based on the GNSS static sampling point state parameter constraint;

and S4, acquiring the smoothness parameters of the track to be measured according to the central line absolute track by combining the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data.

2. The method according to claim 1, wherein in the step S1, the acquiring a sequence of attitude angle observations on the track to be tested by using a sampling device includes:

acquiring an attitude angle observation value on the track to be detected by using the sampling device, clearing an invalid epoch value in the attitude angle observation value, and acquiring an effective attitude angle observation value set;

according to the type of the track to be detected, carrying out filtering and denoising processing on the effective attitude angle observation value set;

correcting the effective attitude angle observation value set subjected to filtering and denoising by using a calibration file;

and carrying out abnormal value restoration on the corrected effective attitude angle observation value set by using a first order difference equation so as to obtain the attitude angle observation sequence.

3. The method according to claim 1, wherein in the step S1, the acquiring a mileage observation sequence on the track to be tested by using a sampling device includes:

acquiring a mileage observation value on the track to be detected by using the sampling device, and clearing an invalid value in the mileage observation value to acquire an effective mileage observation value set;

acquiring the coordinate position of each static sampling point, and acquiring the mileage of each static sampling point by combining the design data so as to finish the correction of the mileage observation value set;

acquiring a midline coordinate of the track to be detected according to the geometric parameters of the sampling device based on a GNSS single epoch solution of mobile observation;

projecting the center line coordinate of the track to be measured onto a design curve, and acquiring a reference mileage corresponding to the GNSS single epoch solution;

and taking the reference mileage as an observed quantity, taking the modified mileage observation value set as a state quantity, and performing Kalman filtering to obtain the mileage observation sequence.

4. The method according to claim 1, wherein in S1, the obtaining a track gauge observation sequence on the track to be tested comprises:

acquiring a track gauge observation value on the track to be detected, and clearing an invalid value in the track gauge observation value to acquire an effective track gauge observation value set;

and repairing abnormal values of the effective track gauge observation value set by using a first order difference equation to obtain the track gauge observation sequence.

5. The method according to claim 1, wherein the step S2 comprises:

s21, taking a time sequence contained in the mileage observation sequence as a reference, performing Lagrange interpolation on the attitude angle observation sequence and the track gauge observation sequence, and acquiring the observation set sequence under the time sequence:

Φ_para(t_l)＝[t_lm y p r g]_n×1，

wherein, t_lRepresenting the time corresponding to the mileage observation sequence, wherein m is the mileage; y is a course angle; p is a pitch angle; r is a transverse rolling angle; g is a track gauge; phi_para(t_l) Is a parameter sequence under the time sequence; n × 1 denotes extending the submatrix to n times 1 row;

s22, respectively obtaining the coordinate increment of each segment in the observation set sequence, wherein the calculation formula is as follows:

wherein dx is_i,i+1Is a coordinate increment; dm_i,i+1Is the mileage increment; i is the point number of the mileage observation sequence;

s23, integrating the coordinate increment to obtain the relative track sequence:

Φ_para,rel(t_l)＝[t_lm y p r g X_relY_relH_rel]_n×1；

wherein (X)_rel、Y_rel、H_rel) To use the relative coordinates calculated for mileage and attitude angle, phi_para,rel(t_l) Is the relative trajectory sequence.

6. The method according to claim 5, wherein the step S3 comprises:

s31, splitting the relative track sequence according to the sampling points to obtain a split relative track subsequence set, wherein:

Φ_para,rel(t_l)＝[Φ₁(t) Φ₂(t)...Φ_k-1(t)]^T；

k is the number of stationary sampling points, T is the matrix transpose operator, phi_para,rel(t_l) The split relative track subsequence is a set;

s32, acquiring an absolute track subsequence set of the center of the antenna of the sampling device in each relative track subsequence interval by using the antenna coordinates of the first and the last two static sampling points in each split relative track subsequence interval as constraints;

s33, acquiring the course angle of the sampling device by using the absolute track subsequence set of the antenna center of the sampling device, wherein the calculation formula is as follows:

wherein (X)_abs,Y_abs,H_abs) Is the absolute coordinate of the center of the antenna of the sampling device; y is_bThe course angle of the sampling device;

s34, merging the absolute track subsequence sets based on the course angles to obtain a parameter sequence containing the absolute track of the antenna center of the sampling device:

Φ_para,abs(t_l)＝[t_lm y_bp r g X_absY_absH_abs]_n×1；

s35, acquiring the central line absolute track of the track to be measured by using the central antenna coordinate and the attitude angle of the sampling device:

(X_mid,Y_mid,H_mid)^T＝(X_abs,Y_abs,H_abs)^T+R(y_b,p,r)L₀

wherein (X)_mid,Y_mid,H_mid) Absolute coordinates of the track central line; r (y)_bP, r) is a rotation matrix determined by a course angle, a pitch angle and a roll angle; l is₀And (4) an initial vector from the center of the antenna to a central line point of the track to be detected, and mid is marked by the central line point of the track.

7. The method according to claim 6, wherein the step S32 comprises:

s321, taking the first static sampling point in each relative track subsequence interval as a reference, and carrying out comparison on the split relative track subsequence phi_para,rel(t_l) And (3) performing translation transformation:

wherein, P_tranFor translating the transformed track sequence, P_rel,iCoordinates corresponding to the relative track;

s322, using the plane coordinates of the two static sampling points in front of and behind each split relative track subsequence as a reference, and carrying out translation transformation on the track sequence P_tranAfter the plane direction rotation transformation is carried out, the elevation coordinates of the front and the back two static sampling points are taken as the reference, and then the rotation transformation in the elevation direction is carried out:

P_rotate＝R_VR_HP_tran

wherein, P_rotateFor track sequences obtained after elevation-wise rotation transformation, R_HIs a planar direction rotation matrix, R_VRotating the matrix in the elevation direction;

s323, taking the first sampling point as a center and taking the coordinates of the front and the back two static sampling points as a reference, and aligning the track sequence P_rotateThe scaling transformation is performed in each of the three directions:

P_abs,i＝k(P_rotate-P_i)+P_i

k＝(k_X,k_Y,k_H)

wherein, P_abs,iFor each absolute coordinate subsequence of the relative track sequence interval after scaling transformation, k is a scaling coefficient in three directions, and X, Y, H is respectively the north, east and vertical height directions under a Gaussian plane coordinate system;

s324, all the absolute coordinate subsequences P_abs,iAnd splicing to obtain the central line absolute track of the track to be detected.

8. The method of claim 7, wherein the ride comfort parameters comprise an outer geometry parameter and an inner geometry parameter;

the external geometric parameters include: the track testing method comprises the following steps of (1) enabling a left rail absolute coordinate, a right rail absolute coordinate, a central line absolute coordinate, a track transverse deviation and a track vertical deviation of each sleeper in a track to be tested; the internal geometric parameters include: the track gauge, the distortion and the track gauge change rate of each sleeper in the track to be detected are determined according to the track direction, the height and the height of the sleeper;

the smoothness parameter obtaining method comprises the following steps:

acquiring a sampling point left rail absolute coordinate and a sampling point right rail absolute coordinate based on the track gauge and attitude angle observation sequence of the track to be detected:

(X_left,Y_left,H_left) Is the absolute coordinate of the left rail of the sampling point, (X)_right,Y_right,H_right) The absolute coordinate of the right rail of the sampling point is shown, and g is a rail distance measurement value;

acquiring a mileage-sleeper comparison table according to the sleeper observation sequence, and acquiring the left rail absolute coordinate, the right rail absolute coordinate and a central line absolute coordinate of each sleeper by combining the sampling point left rail absolute coordinate and the sampling point right rail absolute coordinate;

and combining the design data to obtain the track transverse deviation, the track vertical deviation and the internal geometric parameters.

9. A track ride comfort test system, comprising:

the device comprises a sampling device, a first arithmetic unit, a second arithmetic unit and a third arithmetic unit;

the sampling device is provided with a GNSS receiver, an IMU, a milemeter, a gauge and a sleeper identifier, and can walk on a track to be detected;

the GNSS receiver is used for acquiring and feeding back position coordinates of the sampling device in real time, the IMU is used for acquiring an attitude angle observation sequence on the track to be detected, the odometer is used for acquiring a mileage observation sequence on the track to be detected, the track gauge measuring instrument is used for acquiring a track gauge observation sequence on the track to be detected, and the sleeper recognizer is used for acquiring a sleeper observation sequence on the track to be detected;

the first arithmetic unit is used for carrying out interpolation fusion on the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; acquiring a relative track sequence of the sampling device based on the observation set sequence;

the second operation unit is used for acquiring a midline absolute track of the track to be detected based on the GNSS static sampling point state parameter constraint and according to the relative track sequence;

and the third operation unit is used for acquiring the smoothness parameters of the track to be detected according to the central line absolute track by combining the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and design data.

10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 8 when executing the program.

Technical Field

The invention relates to the technical field of navigation and positioning, in particular to a method and a system for testing track smoothness.

Background

With the rapid development of the transportation industry in China, particularly the rapid construction of high-speed railway networks, railways are one of the most important transportation tools and play an increasingly important role in the whole transportation industry.

The measurement of the smoothness of the high-speed rail is an important link in line maintenance and repair, and determines the safety and stability of high-speed rail transportation. The existing high-speed rail track smoothness measurement technology takes a rail control network CP III as a measurement reference, adopts a track geometric state measuring instrument based on a total station instrument to carry out sleeper-by-sleeper measurement, has the problems of sensitivity to environmental conditions, low measurement efficiency, high measurement cost, serious dependence on CP III and the like, and cannot adapt to the increasingly developed requirements of high-speed rails in China. The method improves the existing high-speed rail smoothness measurement technology, becomes a problem which needs to be solved urgently in the maintenance and repair of the high-speed rail, and has obvious social value and economic benefit.

Disclosure of Invention

Aiming at the defects of the prior art, the embodiment of the invention provides a method and a system for testing the smoothness of a track, which are used for solving the problems of low efficiency, high measurement cost and serious dependence on CP III of the prior art.

In a first aspect, an embodiment of the present invention provides a method for testing track smoothness, including the following steps:

and S1, walking and sampling on the track to be detected by using the sampling device, and acquiring an attitude angle observation sequence, a mileage observation sequence, a track gauge observation sequence and a sleeper observation sequence on the track to be detected.

S2, interpolating and fusing the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; and acquiring a relative track sequence of the sampling device based on the observation set sequence.

And S3, acquiring the central line absolute track of the track to be detected according to the relative track sequence based on the GNSS static sampling point state parameter constraint.

And S4, acquiring the smoothness parameters of the track to be measured according to the central line absolute track by combining the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data.

Preferably, in step S1, the method for acquiring an attitude angle observation sequence on a track to be measured by using a sampling device specifically includes the following steps:

acquiring an attitude angle observation value on a track to be detected by using a sampling device, clearing an invalid epoch value in the attitude angle observation value, and acquiring an effective attitude angle observation value set;

carrying out filtering and denoising treatment on the effective attitude angle observation value set according to the type of the track to be detected;

correcting the effective attitude angle observation value set subjected to filtering and denoising by using a calibration file;

and restoring the abnormal value of the corrected effective attitude angle observation value set by using a first-order difference equation, thereby obtaining an attitude angle observation sequence.

Preferably, in step S1, the method for acquiring a mileage observation sequence on a track to be measured by using a sampling device specifically includes the following steps:

acquiring a mileage observation value on the track to be detected by using a sampling device, removing an invalid value in the mileage observation value, and acquiring an effective mileage observation value set;

acquiring the coordinate position of each static sampling point, and acquiring the mileage of each static sampling point by combining design data to finish correcting the mileage observation value set;

acquiring a central line coordinate of a track to be measured according to geometric parameters of a sampling device based on a GNSS single epoch solution of mobile observation;

projecting the center line coordinates of the track to be measured onto a design curve, and acquiring reference mileage corresponding to a GNSS single epoch solution;

and taking the reference mileage as an observed quantity, taking the corrected mileage observation value set as a state quantity, and performing Kalman filtering to obtain a mileage observation sequence.

Preferably, in S1, the acquiring a track gauge observation sequence on the track to be measured specifically includes the following steps:

acquiring a track gauge observation value on a track to be detected, and clearing an invalid value in the track gauge observation value to acquire an effective track gauge observation value set;

and (5) restoring the abnormal value of the effective track gauge observation value set by using a first-order difference equation to obtain a track gauge observation sequence.

Preferably, step S2 specifically includes the following sub-steps:

s21, taking the time sequence contained in the mileage observation sequence as a reference, carrying out Lagrange interpolation on the attitude angle observation sequence and the track gauge observation sequence, and obtaining an observation set sequence under the time sequence:

Φ_para(t_l)＝[t_lm y p r g]_n×1，

wherein, t_lRepresenting the time corresponding to the mileage observation sequence, wherein m is the mileage; y is a course angle; p is a pitch angle; r is a transverse rolling angle; g is a track gauge; phi_para(t_l) Is a parameter sequence under the time sequence; n × 1 denotes extending the submatrix to n times 1 row;

s22, respectively obtaining the coordinate increment of each segment in the observation set sequence, wherein the calculation formula is as follows:

wherein dx is_i,i+1Is a coordinate increment; dm_i,i+1Is the mileage increment; i is the point number of the mileage observation sequence;

s23, integrating the coordinate increment to obtain a relative track sequence:

Φ_para,rel(t_l)＝[t_lm y p r g X_relY_relH_rel]_n×1；

wherein (X)_rel、Y_rel、H_rel) To use the relative coordinates calculated for mileage and attitude angle, phi_para,rel(t_l) Is a relative track sequence.

Preferably, in step S3, the method specifically includes the following sub-steps:

s31, splitting the relative track sequence according to the static sampling point, and acquiring a split relative track subsequence set, wherein:

Φ_para,rel(t_l)＝[Φ₁(t) Φ₂(t) ... Φ_k-1(t)]^T；

k is the number of stationary sampling points, T is the matrix transpose operator, phi_para,rel(t_l) Is a split relative track subsequence;

s32, acquiring an absolute track subsequence set of the antenna center of the sampling device in each relative track subsequence interval by using the antenna coordinates of the first and the last two static sampling points in each split relative track subsequence interval as constraints;

s33, acquiring the course angle of the sampling device by using the absolute track subsequence set of the antenna center of the sampling device, wherein the calculation formula is as follows:

wherein (X)_abs,Y_abs,H_abs) Is the absolute coordinate of the center of the antenna of the sampling device; y is_bIs the course angle of the sampling device;

s34, merging the absolute track subsequences based on the heading angles to obtain a parameter sequence of the absolute track containing the antenna center of the sampling device:

Φ_para,abs(t_l)＝[t_lm y_bp r g X_absY_absH_abs]_n×1；

s35, acquiring a central line absolute track of the track to be detected by using the central antenna coordinates and the attitude angle of the sampling device:

(X_mid,Y_mid,H_mid)^T＝(X_abs,Y_abs,H_abs)^T+R(y_b,p,r)L₀

wherein (X)_mid,Y_mid,H_mid) Absolute coordinates of the track central line; r (y)_bP, r) is course angle, pitch angle and roll angleThe determined rotation matrix; l is₀And (4) an initial vector from the center of the antenna to a central line point of the track to be detected, and mid is marked by the central line point of the track.

Preferably, in the step S32, the method specifically includes the following sub-steps:

s321, taking the first sampling point in each relative track subsequence interval as a reference, and carrying out comparison on the split relative track subsequence phi_para,rel(t_l) And (3) performing translation transformation:

wherein, P_tranFor translating the transformed track sequence, P_rel,iCoordinates corresponding to the relative track;

relative coordinates corresponding to the starting points of the relative tracks; p_iAbsolute coordinates of a first sampling point in each relative track subsequence interval; i is the number of the relative track subsequence interval;

s322, using the plane coordinates of two static sampling points before and after each split relative track subsequence as a reference, and carrying out translation transformation on the track sequence P_tranAfter the plane direction rotation transformation is carried out, the elevation coordinates of the front and the back stationary sampling points are taken as the reference, and then the rotation transformation in the elevation direction is carried out:

P_rotate＝R_VR_HP_tran

wherein, P_rotateFor track sequences obtained after elevation-wise rotation transformation, R_HIs a planar direction rotation matrix, R_VRotating the matrix in the elevation direction;

s323, taking the first sampling point as the center and the coordinates of the front and the back static sampling points as the reference, and aligning the track sequence P_rotateThe scaling transformation is performed in each of the three directions:

P_abs,i＝k(P_rotate-P_i)+P_i

k＝(k_X,k_Y,k_H)

wherein, P_abs,iK is a scaling coefficient in three directions for the absolute coordinate of each relative track sequence interval after scaling transformation, and X, Y, H is the north, east and vertical height directions under a Gaussian plane coordinate system respectively;

s324, all the absolute coordinate subsequences P_abs,iAnd splicing to obtain the central line absolute track of the track to be detected.

Preferably, the smoothness parameter specifically includes: an external geometric parameter and an internal geometric parameter.

Wherein the external geometric parameters include: the method comprises the following steps that (1) the absolute coordinates of a left rail, the absolute coordinates of a right rail, the absolute coordinates of a central line, the transverse deviation of the rail and the vertical deviation of the rail of each sleeper in a rail to be detected are obtained; the internal geometric parameters include: the left rail direction, the right rail direction, the left height, the right height, the superelevation, the track gauge, the distortion, the track gauge change rate and the like of each sleeper in the track to be detected;

the smoothness parameter obtaining method comprises the following steps:

acquiring a sampling point left rail absolute coordinate and a sampling point right rail absolute coordinate based on a track gauge and attitude angle observation sequence of a track to be detected:

(X_left,Y_left,H_left) Is the absolute coordinate of the left rail of the sampling point, (X)_right,Y_right,H_right) Sampling point right rail absolute coordinates, wherein g is a rail gauge measured value;

acquiring a mileage-sleeper comparison table according to the sleeper observation sequence, and acquiring the left rail absolute coordinate, the right rail absolute coordinate and a central line absolute coordinate of each sleeper by combining the sampling point left rail absolute coordinate and the sampling point right rail absolute coordinate;

and combining the design data to obtain the track transverse deviation, the track vertical deviation and the internal geometric parameters.

In a second aspect, an embodiment of the present invention provides a track smoothness testing system, including:

the device comprises a sampling device, a first arithmetic unit, a second arithmetic unit and a third arithmetic unit;

the device comprises a sampling device, a track gauge measuring instrument and a sleeper identifier, wherein the sampling device is provided with a GNSS receiver, an IMU, a mileometer, the track gauge measuring instrument and the sleeper identifier and can walk on a track to be measured;

the GNSS receiver is used for acquiring and feeding back position coordinates of the sampling device in real time, the IMU is used for acquiring an attitude angle observation sequence on the track to be detected, the odometer is used for acquiring a mileage observation sequence on the track to be detected, the gauge measuring instrument is used for acquiring a gauge observation sequence on the track to be detected, and the sleeper recognizer is used for acquiring a sleeper observation sequence on the track to be detected.

The first arithmetic unit is used for interpolating and fusing the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; and acquiring a relative track sequence of the sampling device based on the observation set sequence.

The second operation unit is used for acquiring the central line absolute track of the track to be detected according to the relative track sequence based on the GNSS static sampling point state parameter constraint.

And the third operation unit is used for acquiring the ride comfort parameters of the track to be measured according to the central line absolute track combined attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data.

In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the track smoothness testing method according to any one of the first aspect when executing the program.

According to the track smoothness testing method and system provided by the embodiment of the invention, a sampling device provided with a plurality of sensors and a GNSS receiver is adopted, a stop-go-stop operation mode is adopted on the track to be tested, the acquired sensor moving observation data and absolute coordinates of each static sampling point are comprehensively processed by using a fusion algorithm, smoothness parameters of the track to be tested are acquired, the track smoothness testing efficiency and precision are effectively improved, the testing cost is reduced, and the adaptability to various complex environments is strong.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

Fig. 1 is a schematic flow chart of a method for testing track smoothness according to an embodiment of the present invention;

fig. 2 is a schematic structural diagram of a track smoothness testing system according to an embodiment of the present invention;

fig. 3 is a schematic flow chart of another track smoothness testing method according to an embodiment of the present invention;

FIG. 4 is a diagram illustrating a comparison of the track smoothness testing method of the present invention and the prior art track testing method;

FIG. 5 is a diagram showing a comparison between the track smoothness testing method of the present invention and the prior art track testing method;

fig. 6 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, an embodiment of the invention provides a method for testing track smoothness, including but not limited to the following steps:

step S1, walking and sampling on the rail to be detected by using a sampling device, and acquiring an attitude angle observation sequence, a mileage observation sequence, a track gauge observation sequence and a sleeper observation sequence on the rail to be detected;

s2, interpolating and fusing the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; acquiring a relative track sequence of the sampling device based on the observation set sequence;

s3, acquiring a midline absolute track of the track to be detected according to the relative track sequence based on the GNSS static sampling point state parameter constraint;

and step S4, acquiring the smoothness parameters of the track to be measured according to the central line absolute track and the combination of the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data.

Specifically, in this embodiment, the sampling device may be a T-shaped trolley capable of performing stable motion on a rail, and the trolley is provided with sensors and a data acquisition terminal, such as a GNSS receiver, an IUM, a odometer, a gauge, a tie identifier, and the like. For convenience of description, in all the implementations of the present application, a cart will be used as a sampling device, but it is not to be considered as limiting the scope of the embodiments of the present invention.

The GNSS receiver is a global satellite navigation positioning device, and is a space-based radio navigation positioning device capable of providing all-weather three-dimensional coordinates and speed and time information in real time at any place on the earth surface or in a near-earth space.

An IUM is also called an Inertial Measurement Unit (IMU), and is a device for measuring three-axis attitude angle (or angular velocity) and acceleration of an object. Generally, an IMU includes three single-axis accelerometers and three single-axis gyroscopes, the accelerometers detecting acceleration signals of the object in three independent axes of the carrier coordinate system, and the gyroscopes detecting angular velocity signals of the carrier relative to the navigation coordinate system, measuring the angular velocity and acceleration of the object in three-dimensional space, and calculating the attitude of the carrier based thereon. Has important application value in navigation. In this embodiment, the IMU may be mounted at the center of gravity of the cart.

During measurement, firstly in step S1, the trolley is placed on the rail to be measured and moves on the rail to be measured in a stop-go-stop sequential iterative motion manner. In order to further improve the test accuracy, the same-position forward and backward measurement can be adopted to calibrate the attitude angle data before the measurement is started. In the process of walking, the attitude angle observation value, the mileage observation value, the track gauge observation value and the sleeper observation value of the trolley on the rail to be measured are obtained by utilizing the sensors and the data acquisition terminal respectively, namely utilizing a GNSS receiver, an IUM, a speedometer, a track gauge measuring instrument, a sleeper recognizer and the like to sample, and all the attitude angle observation value, the mileage observation value, the track gauge observation value and the sleeper observation value are respectively constructed into an attitude angle observation sequence, a mileage observation sequence, a track gauge observation sequence and a sleeper observation sequence, wherein the method also comprises the step of obtaining accurate absolute coordinates of each static sampling point (namely a stop point) and GNSS absolute coordinates of mobile observation by utilizing the GNSS receiver and the IMU through a GNSS and IMU combined static baseline model.

Further, in step S2, based on the stop point state constraint, the attitude angle observation sequence, the mileage observation sequence, and the track gauge observation sequence acquired in step S1 are interpolated and fused to acquire a fused observation set sequence. Further, a relative track sequence of the sampling device (trolley) is obtained through calculation according to the observation set sequence.

Further, as the sampling device runs on the track, the motion track of the sampling device can directly reflect the real state of the track. In step S3, a central line absolute trajectory of the track to be measured may be calculated and obtained according to the sampling device relative trajectory sequence based on the GNSS stationary sampling point state parameter constraint.

Further, since the change of the track center line absolute track can directly reflect the smoothness of the track, in step S4, the smoothness parameter of the track to be detected is calculated and obtained based on the track center line absolute track of the track to be detected obtained in step S3, the attitude angle observation sequence, the track gauge observation sequence and the sleeper observation sequence of the detection device obtained in step S1, and the design data of the track.

According to the track smoothness testing method provided by the embodiment of the invention, a sampling device provided with a plurality of sensors and a GNSS receiver is adopted, a 'stop-go-stop' operation mode is adopted on the track to be tested, and the obtained sensor movement observation data and the absolute coordinates of each sampling point are comprehensively processed by using a fusion algorithm to obtain the smoothness parameters of the track to be tested, so that the efficiency and the precision of the track smoothness testing are effectively improved, the testing cost is reduced, and the adaptability to various complex environments is strong.

Based on the content of the foregoing embodiments, as an alternative embodiment, in step S1, the method for acquiring the observation sequence of attitude angles on the track to be measured by using the sampling device includes, but is not limited to, the following steps:

acquiring an attitude angle observation value on a track to be detected by using a sampling device, clearing an invalid epoch value in the attitude angle observation value, and acquiring an effective attitude angle observation value set;

carrying out filtering and denoising treatment on the effective attitude angle observation value set according to the type of the track to be detected;

correcting the effective attitude angle observation value set subjected to filtering and denoising by using a calibration file;

and restoring the abnormal value of the corrected effective attitude angle observation value set by using a first-order difference equation, thereby obtaining an attitude angle observation sequence.

Specifically, the present embodiment provides a method for acquiring an attitude angle observation sequence:

firstly, attitude angle observation values collected by an IMU on a detection device are read and collected, all attitude angle observation values are removed, and after unavailable epoch data such as an alignment stage, incomplete observation, data errors and the like are removed, all remaining attitude angle observation values are combined to form an effective attitude angle observation value set.

And further, performing filtering and denoising processing on all attitude angle observation values in the effective attitude angle observation value set obtained in the last step so as to further simplify the effective attitude angle observation value set. The low-pass filtering may be adopted, and the cut-off frequency of the low-pass filtering may be determined according to the type of the track to be detected, such as ballast or ballastless track.

Further, since the attitude angle observation values include parameters such as a pitch angle and a roll angle, the pitch angle and the roll angle in all the attitude angle observation values can be corrected by using a calibration file during testing, wherein the correction values can include: IMU platform installation error, zero offset, etc.

Furthermore, abnormal value detection and restoration can be performed on all the attitude angle observation values by utilizing first-order difference.

According to the track smoothness testing method provided by the embodiment of the invention, the obtained attitude angle observation value is simplified and corrected in multiple modes, so that the finally obtained attitude angle observation sequence can be more accurately used for smoothness testing of the track to be tested, the data volume of operation is effectively reduced, and the testing precision and efficiency are improved.

Based on the content of the foregoing embodiment, as an alternative embodiment, wherein in step S1, the acquiring the mileage observing sequence on the track to be tested by using the sampling device may include the following steps:

acquiring a mileage observation value on a track to be detected by using a sampling device, and clearing an invalid value in the mileage observation value to acquire an effective mileage observation value set;

acquiring coordinate positions of all sampling points, and acquiring the mileage of each sampling point by combining design data to finish correcting the mileage observation value set;

acquiring a central line coordinate of a track to be measured according to geometric parameters of a sampling device based on a GNSS single epoch solution of mobile observation;

projecting the center line coordinates of the track to be measured onto a design curve, and acquiring reference mileage corresponding to a GNSS single epoch solution;

and taking the reference mileage as an observed quantity, taking the corrected mileage observation value set as a state quantity, and performing Kalman filtering to obtain a mileage observation sequence.

Specifically, the present embodiment provides a method for acquiring a mileage observation sequence:

firstly, reading all the mileage observed values recorded by the mileometers on the acquisition devices, actively removing invalid values in the mileage observed values due to incomplete observation and the like, and then establishing an effective mileage observed value set.

Furthermore, the mileage of each stopping point is calculated by combining design data according to the coordinates of the stopping points (namely, sampling points), the effective mileage observation value set is corrected by using the mileage of the stopping points, and the measurement accuracy value of the odometer can be acquired simultaneously. And verifying and selecting the used odometer according to the measurement precision value.

Further, the track to be detected inevitably passes through a complicated road section and a road section with large external interference under a real condition, so that the road section causes large mileage measurement error and seriously affects the final detection result. In this embodiment, for a mileage observation value in a complex road segment, the mileage observation value is corrected by using a GNSS single epoch solution of mobile observation, and the specific steps may include:

firstly, a GNSS single epoch solution of mobile observation is utilized, and geometric parameters (such as vehicle width, vehicle length, wheel base and the like) of a sampling device are combined to calculate and obtain the center line coordinates of the track to be measured.

And then, projecting the center line coordinate of the track to be measured onto a design curve to acquire a reference mileage corresponding to the GNSS single epoch solution.

And further, taking the reference mileage obtained in the last step as an observed quantity, taking a mileage observed value output by the odometer as a state quantity, and obtaining a final mileage observation sequence by using Kalman filtering.

The Kalman filter (Kalman Filtering) is an algorithm that performs optimal estimation of a system state by inputting and outputting observation data through a system using a linear system state equation. Under the condition that the measurement variance is known, the state of the dynamic system can be estimated from a series of data with measurement noise, and the mileage observed value acquired on site can be updated and processed in real time.

According to the track smoothness testing method provided by the embodiment of the invention, the mileage observation value acquired on site is filtered and simplified in a multi-angle and multi-mode manner, so that the acquired mileage observation sequence can be more accurately used for smoothness testing of the track to be tested, the data volume of operation is effectively reduced, and the testing precision and efficiency are improved.

Based on the content of the foregoing embodiment, as an alternative embodiment, wherein in step S1, the acquiring a track gauge observation sequence on the track to be measured by using the sampling device may include the following steps:

acquiring a track gauge observation value on a track to be detected, and clearing an invalid value in the track gauge observation value to acquire an effective track gauge observation value set;

and (5) restoring the abnormal value of the effective track gauge observation value set by using a first-order difference equation to obtain a track gauge observation sequence.

Specifically, the present embodiment provides a method for acquiring a track gauge observation sequence, including:

firstly, a track gauge observation set is established by reading all track gauge observation values collected by a track gauge measuring instrument and clearing invalid values in all the track gauge observation values. And further, carrying out abnormal value restoration on the residual effective track gauge observation value set after the invalid value is eliminated by using a first-order difference equation to obtain a track gauge observation sequence.

Based on the content of the above embodiments, as an alternative embodiment, step S2 may include, but is not limited to, the following steps:

s21, taking the time sequence contained in the mileage observation sequence as a reference, carrying out Lagrange interpolation on the attitude angle observation sequence and the track gauge observation sequence, and acquiring an observation set sequence under the time sequence:

Φ_para(t_l)＝[t_lm y p r g]_n×1，

wherein, t_lRepresenting the time corresponding to the mileage observation sequence, m being mileage(ii) a y is a course angle; p is a pitch angle; r is a transverse rolling angle; g is a track gauge; phi_para(t_l) Is a parameter sequence under the time sequence; n × 1 denotes extending the submatrix to n times 1 row;

s22, respectively obtaining the coordinate increment of each segment in the observation set sequence, wherein the calculation formula is as follows:

wherein dx is_i,i+1Is a coordinate increment; dm_i,i+1Is the mileage increment; i is the point number of the mileage observation sequence;

s23, integrating the coordinate increment to obtain a relative track sequence:

Φ_para,rel(t_l)＝[t_lm y p r g X_relY_relH_rel]_n×1；

wherein (X)_rel、Y_rel、H_rel) To use the relative coordinates calculated for mileage and attitude angle, phi_para,rel(t_l) Is a relative track sequence.

Specifically, firstly, taking the mileage observation sequence as a reference, performing lagrangian interpolation on the attitude angle observation sequence and the track gauge observation sequence acquired by the IMU and the track gauge measuring instrument, and acquiring a parameter sequence phi containing observation values of mileage, attitude angle, track gauge and the like under the same time sequence_para(t_l)。

Further, a parameter sequence Φ is calculated_para(t_l) And then, carrying out integral calculation by using the obtained coordinate increment to obtain a parameter sequence containing the relative track of the sampling device (trolley).

According to the track smoothness testing method provided by the embodiment of the invention, the obtained attitude angle observation sequence, the track gauge observation sequence and the like are interpolated and integrated into a unified sequence, namely a parameter sequence containing observation values such as mileage, attitude angle, track gauge and the like, so that unified analysis is facilitated; and the relative track of the sampling device is obtained according to the integrated parameter sequence, so that a foundation is laid for further obtaining the smoothness parameter of the track to be detected.

Based on the content of the above embodiments, as an alternative embodiment, step S3 may include, but is not limited to, the following steps:

s31, splitting the relative track sequence according to the sampling points, and acquiring a split relative track subsequence set, wherein:

Φ_para,rel(t_l)＝[Φ₁(t) Φ₂(t) ... Φ_k-1(t)]^T；

k is the number of sampling points, T is the matrix transpose operator, phi_para,rel(t_l) The split relative track subsequence is a set;

s32, acquiring an absolute track subsequence of the center of the antenna of the sampling device in each relative track subsequence interval by using the antenna coordinates of the first and the last sampling points in each split relative track subsequence interval as constraints;

s33, acquiring the course angle of the sampling device by using the absolute track subsequence of the antenna center of the sampling device, wherein the calculation formula is as follows:

wherein (X)_abs,Y_abs,H_abs) Is the absolute coordinate of the center of the antenna of the sampling device; y is_bIs the course angle of the sampling device;

s34, based on the course angle, combining the absolute track subsequence sets obtained based on the split relative track subsequence sets, and acquiring a parameter sequence of the absolute track of the antenna center including the sampling device:

Φ_para,abs(t_l)＝[t_lm y_bp r g X_absY_absH_abs]_n×1；

s35, acquiring a central line absolute track of the track to be detected by using the central antenna coordinates and the attitude angle of the sampling device:

(X_mid,Y_mid,H_mid)^T＝(X_abs,Y_abs,H_abs)^T+R(y_b,p,r)L₀

wherein (X)_mid,Y_mid,H_mid) Absolute coordinates of the track central line; r (y)_bP, r) is a rotation matrix determined by a course angle, a pitch angle and a roll angle; l is₀And (4) an initial vector from the center of the antenna to a central line point of the track to be detected, and mid is marked by the central line point of the track.

Specifically, the positions of m sampling points are obtained according to the motion trajectory (stop-go-stop) of the sampling trolley, and the relative trajectory sequence Φ of the sampling device obtained in step S2 is obtained according to the sampling points_para,rel(t_l) Splitting is carried out, and the splitting can be carried out into m-1 splitting intervals.

Furthermore, in each splitting interval, the absolute track of the antenna center of the sampling trolley is calculated by taking the antenna coordinates of the head sampling point and the tail sampling point as constraints, so that the absolute tracks of the antenna centers of m-1 continuous sampling trolleys can be obtained.

And further, generating a course angle of the sampling device corresponding to each splitting interval by using the absolute track of the antenna center of the sampling trolley in each splitting interval, wherein the course angle is an included angle between the sampling trolley and the north pole of the earth, and is also called as a true course angle and used for marking the running direction of the sampling device.

Further, based on all the course angles, merging the processed data of each splitting interval to obtain a parameter sequence phi containing an antenna absolute track of the sampling device_para,abs(t_l)。

Furthermore, the central antenna coordinate and the attitude angle of the sampling device are combined, and the central line absolute track of the track to be measured is calculated and obtained, wherein the absolute track is composed of the absolute coordinates of the central lines of all the tracks.

Based on the content of the above embodiments, as an alternative embodiment, step S32 may include, but is not limited to, the following steps:

step S321, taking the first sampling point in each relative track subsequence interval as a reference, and carrying out comparison on the split relative track subsequence phi_para,rel(t_l) And (3) performing translation transformation:

wherein, P_tranFor translating the transformed track sequence, P_rel_,iCoordinates corresponding to the relative track;

relative coordinates corresponding to the starting points of the relative tracks; p_iAbsolute coordinates of a first sampling point in each relative track sequence interval are obtained; i is the number of the relative track sequence interval;

step S322, using the plane coordinates of the front and back two static sampling points of each relative track subsequence as a reference, and carrying out translation transformation on the track sequence P_tranAfter the plane direction rotation transformation is carried out, the elevation coordinates of the front and the back stationary sampling points are taken as the reference, and then the rotation transformation in the elevation direction is carried out:

P_rotate＝R_VR_HP_tran

wherein, P_rotateFor track sequences obtained after elevation-wise rotation transformation, R_HIs a planar direction rotation matrix, R_VRotating the matrix in the elevation direction;

s323, taking the first sampling point as the center and the coordinates of the front and the back static sampling points as the reference, and aligning the track sequence P_rotateThe scaling transformation is performed in each of the three directions:

P_abs,i＝k(P_rotate-P_i)+P_i

k＝(k_X,k_Y,k_H)

wherein, P_abs,iFor each transformed one is scaledAbsolute coordinates of the relative track sequence intervals, k is a scaling coefficient in three directions, and X, Y, H is respectively in the north, east and vertical height directions under a Gaussian plane coordinate system;

s324, all the absolute coordinate subsequences P_abs,iAnd splicing to obtain the central line absolute track of the track to be detected.

Specifically, an embodiment of the present invention provides a method for acquiring an absolute track of an antenna center of a sampling device:

firstly, taking a first stop point of each splitting interval as a reference, and carrying out translation transformation on a split relative track sequence; then, taking the coordinates of the front and rear static sampling points as a reference, and carrying out rotation transformation in the plane direction and the elevation direction on the relative track sequence processed in the previous step; further, the first sampling point of the splitting interval is taken as a center, coordinates of the front and the back static sampling points are taken as references, and the track sequence P is subjected to comparison_rotateThe three directions of (a) are respectively subjected to scaling transformation, wherein the three directions are respectively an X-axis direction (a true north direction), a Y-axis direction (a true east direction) and an H-axis direction (a vertical direction).

Finally, converting the absolute coordinate subsequence P of each relative track subsequence interval after three times_abs,iSplicing is carried out, and the central line absolute track of the track to be detected is obtained.

Based on the contents of the above embodiments. As an alternative embodiment, the smoothness parameter mainly includes an external geometric parameter and an internal geometric parameter, and the external geometric parameter and the internal geometric parameter are combined to reflect the actual condition of the track to be measured.

Wherein the external geometric parameters mainly include: the track testing method comprises the steps of obtaining left track absolute coordinates, right track absolute coordinates, central line absolute tracks, track transverse deviation, track vertical deviation and the like of each sleeper in a track to be tested. The internal geometric parameters mainly include: the track gauge comprises a left track direction, a right track direction, a left height, a right height, an ultrahigh height, a track gauge, a distortion, a track gauge change rate and the like of each sleeper in the track to be tested.

The method for acquiring the absolute coordinate of the left rail and the absolute coordinate of the right rail of each sleeper comprises the following steps:

firstly, acquiring the left rail absolute coordinates and the right rail absolute coordinates of each sampling point based on the track gauge and attitude angle observation sequence of the track to be detected:

(X_left,Y_left,H_left) As absolute coordinates of the left rail, (X)_right,Y_right,H_right) Absolute coordinates of a right rail, and g is a gauge measurement value;

and further, combining the absolute coordinates of the left rails of all the sampling points and the absolute left marks of the right rails of the sampling points, acquiring a mileage-sleeper comparison table according to a sleeper observation sequence, and combining design data to acquire the absolute coordinates of the left rails, the absolute coordinates of the right rails and the absolute coordinates of a central line of each sleeper so as to acquire transverse deviation of the rails, vertical deviation of the rails and internal geometric parameters.

As shown in fig. 2, an embodiment of the present invention further provides a track smoothness testing system, including but not limited to:

a sampling device 1, a first arithmetic unit 2, a second arithmetic unit 3, and a third arithmetic unit 4;

the sampling device 1 is provided with a GNSS receiver 11, an IMU12, a milemeter 13, a gauge 14 and a sleeper identifier 15, and the sampling device 1 can walk on a rail to be detected;

the GNSS receiver 11 is configured to obtain and feed back a position coordinate of the sampling device 1 in real time, the IMU12 is configured to obtain an attitude angle observation sequence on a track to be measured, the odometer 13 is configured to obtain a mileage observation sequence on the track to be measured, the gauge 14 is configured to obtain a gauge observation sequence on the track to be measured, and the sleeper identifier 15 is configured to obtain a sleeper observation sequence on the track to be measured;

the first arithmetic unit 2 is used for interpolating and fusing the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; acquiring a relative track sequence of the sampling device based on the observation set sequence;

the second arithmetic unit 3 is used for acquiring a midline absolute track of the track to be detected based on the GNSS sampling point state parameter constraint and according to the relative track sequence;

and the third operation unit 4 is used for acquiring the ride comfort parameter of the track to be measured according to the central line absolute track by combining the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data.

Specifically, as shown in fig. 3, in this embodiment, the sampling device 1 may be a T-shaped trolley, the T-shaped trolley is provided with a GNSS receiver 11, an IMU12, an odometer 13, a gauge 14 and a tie identifier 15, and a data acquisition device may be further added, and the data acquisition device is in communication connection with the GNSS receiver 11, the IMU12, the odometer 13, the gauge 14 and the tie identifier 15, and is used for controlling the operating states of all the devices and comprehensively processing all the acquired data.

The data acquisition device is mainly used for acquiring and storing the following data: an IMU observation, an IMU calibration, a odometer observation, a gauge observation, a GNSS observation, and a sleeper count. All data are organized into corresponding observation sequences by type.

Further, IMU data preprocessing can be performed by utilizing the IMU observation value and the IMU calibration value; preprocessing mileage data by using the odometer observation value, the GNSS observation value and design data; preprocessing the track gauge data of the track gauge observation value; and generating a sleeper and mileage comparison table by using the odometer observed value and the sleeper count.

Further, the IMU data preprocessing result, the mileage data preprocessing result and the track gauge data preprocessing result are input to the first arithmetic unit 2 to perform the relative track settlement, and the relative track sequence of the sampling device is obtained.

Further, the relative trajectory sequence of the sampling device is combined with the GNSS observation value and input to the second arithmetic unit 3 to perform absolute trajectory settlement, thereby obtaining the central line absolute trajectory of the track to be measured.

Further, the central line absolute track of the track to be measured, the sleeper and the mileage comparison table are input into a third operation unit 4, and the settlement of the sleeper coordinate is performed to obtain partial parameters of the smoothness parameters. Wherein another portion of the ride comfort parameter may be obtained based on the design data.

According to the track smoothness testing system provided by the embodiment of the invention, a multi-sensor and GNSS receiver sampling device is loaded, a stop-go-stop operation mode is adopted on the track to be tested, the acquired sensor movement observation data and the absolute coordinates of each sampling point are comprehensively processed by using a fusion algorithm, the smoothness parameter of the track to be tested is acquired, the track smoothness testing efficiency and precision are effectively improved, the testing cost is reduced, and the adaptability to various complex environments is strong.

To better illustrate the advantages of the track smoothness testing method and system provided by the embodiments of the present invention over the prior art, the following lists the results of performing the track smoothness testing by using the methods in the embodiments of the present invention and the prior art respectively, specifically:

in 11/6/2018, a JQGTSG-05 section (mileage DK117+ 880-DK 118+823) of the Jiqing GaoTeu province is tested by using the rail smoothness testing method and system provided by the embodiment of the invention. The method adopts a 'stop-go-stop' operation mode, stops once every 150m for GNSS static observation, and simultaneously collects data of sensors such as GNSS, IMU, odometer, gauge, sleeper recognizer and the like in the whole measurement operation. According to the GNSS/INS constrained by the stop point state parameters and other sensor mobile observation data fusion algorithm provided by the embodiment of the invention, the external geometric parameters and the internal geometric parameters of the track are calculated, and the transverse deviation and the vertical deviation are calculated by combining with the design data. Meanwhile, the Anbog GRP1000 trolley is adopted to measure in the same section. The lateral and vertical offsets are paired as shown in figures 4 and 5. It can be seen that the overall variation trends of the transverse deviation and the vertical deviation are basically consistent, the maximum transverse mutual difference is 2.3mm, and the maximum vertical mutual difference is 3.4 mm.

As shown in fig. 4 and 5, a precision comparison graph of the track smoothness testing method provided by the embodiment of the present invention and the track testing method in the prior art is shown, where fig. 4 is a transverse deviation comparison graph, and fig. 5 is a vertical deviation comparison graph, and it is obvious from the graphs that the track smoothness testing method provided by the embodiment of the present invention has a very close measurement result for both transverse deviation and vertical deviation compared to the conventional total station method.

Further, the external geometric parameter and the internal geometric parameter measurement accuracy of both were counted, and the results are shown in table 1. As shown in table 1, with the method according to the embodiment of the present invention, compared to the conventional total station method in the prior art, the accuracy of the external geometric parameters is equivalent, and the accuracy of the internal geometric parameters is higher. The external geometric parameter and the internal geometric parameter precision meet the requirement of the high-speed rail smoothness measurement precision, and the method can be used for rail adjustment of the high-speed rail.

Through the practical test, the track smoothness test method and the track smoothness test system provided by the embodiment of the application are fully verified, and compared with the prior art, the track smoothness test method and the track smoothness test system have the following advantages and beneficial effects:

1. the GNSS/INS and other sensor mobile observation data are adopted for fusion and calculation, and compared with a conventional total station method, the GNSS/INS based mobile observation data fusion and calculation method is high in measurement efficiency and strong in environmental adaptability.

2. Compared with the conventional method, the embodiment of the invention greatly reduces the dependence on CP III control points and reduces the operation intensity.

3. According to the method, the external geometric parameters and the internal geometric parameters of the track are accurately measured through a GNSS/INS constrained by the state parameters of the stop point and other sensor mobile observation data fusion algorithm, and the integration of absolute measurement and relative measurement is realized.

Table 1 shows the following:

TABLE 1 measurement accuracy of external and internal geometric parameters for two methods

Fig. 6 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 6: a processor (processor)610, a communication Interface (Communications Interface)620, a memory (memory)630 and a communication bus 640, wherein the processor 610, the communication Interface 620 and the memory 630 communicate with each other via the communication bus 640. The processor 610 may call logic instructions in the memory 630 to perform the following method:

and S1, walking and sampling on the track to be detected by using the sampling device, and acquiring an attitude angle observation sequence, a mileage observation sequence, a track gauge observation sequence and a sleeper observation sequence on the track to be detected.

S2, interpolating and fusing the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; and acquiring a relative track sequence of the sampling device based on the observation set sequence.

And S3, acquiring the central line absolute track of the track to be detected according to the relative track sequence based on the GNSS static sampling point state parameter constraint.

And S4, acquiring the smoothness parameters of the track to be measured according to the central line absolute track combined with the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data.

In addition, the logic instructions in the memory 630 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the transmission method provided in the foregoing embodiments when executed by a processor, for example, the method includes S1, walking a sample on a track to be measured by using a sampling device, and acquiring an attitude angle observation sequence, a mileage observation sequence, a track gauge observation sequence, and a sleeper observation sequence on the track to be measured.

S2, interpolating and fusing the attitude angle observation sequence, the mileage observation sequence and the track gauge observation sequence to obtain an observation set sequence; and acquiring a relative track sequence of the sampling device based on the observation set sequence.

And S3, acquiring the central line absolute track of the track to be detected according to the relative track sequence based on the GNSS static sampling point state parameter constraint.

And S4, acquiring the smoothness parameters of the track to be measured according to the central line absolute track by combining the attitude angle observation sequence, the track gauge observation sequence, the sleeper observation sequence and the design data.

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.