CN111721250B - Real-time detection device and detection method for smoothness of railway track - Google Patents
Real-time detection device and detection method for smoothness of railway track Download PDFInfo
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- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
- G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
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- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/50—Determining position whereby the position solution is constrained to lie upon a particular curve or surface, e.g. for locomotives on railway tracks
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Abstract
The invention discloses a real-time detection device and a real-time detection method for smoothness of a railway track. The detection method comprises the following steps: in the process that the detection device moves along the track to be detected: determining position information, speed information and attitude information of each moment in real time based on an inertial navigation system; determining position information and speed information at each moment in real time based on a Beidou satellite navigation system; determining speed information at each moment in real time based on the odometer; and taking the data as an information vector in Kalman filtering to perform loose combination processing to obtain position information and attitude information which are fused and filtered at each moment. When the detection device completes the movement along the track to be detected: and determining the irregularity and the roughness of the track to be detected in the track direction in real time according to the position information and the attitude information after fusion filtering. The real-time detection device and the detection method for the smoothness of the railway track can give consideration to detection precision, detection efficiency and real-time performance.
Description
Technical Field
The invention relates to the technical field of railway track smoothness detection, in particular to a real-time railway track smoothness detection device and a detection method.
Background
The track detection method is divided into dynamic detection and static detection according to whether the line is empty or not. The dynamic detection is a method for detecting geometric parameters of a loaded track by using a dynamic track inspection vehicle, and the static detection is a method for detecting geometric parameters of an unloaded track by using a relative measurement mode or an absolute measurement mode. Although the large-scale dynamic rail inspection vehicle is high in speed, the accuracy is insufficient, the convenience is insufficient, and certain limitations are provided. The static detection of the track is divided into relative measurement and absolute measurement, wherein the relative measurement method mainly comprises a chord measurement method and an inertia reference method, and the absolute measurement method mainly comprises a polar coordinate method, a GNSS PPK method and the like. The chord measuring method is easily influenced by factors such as rail gaps and track fat edges, the inertial measurement precision is easily dispersed, the total station of the polar coordinate method has strict requirements on the external environment and is low in measurement speed, satellite signals of the PPK method are interfered and shielded by the influence of the environment, the accuracy of a positioning result is influenced, and the PPK method is free from real-time performance and has certain defects. In summary, the conventional track detection technology has the problem that the detection precision, the detection efficiency and the real-time performance are difficult to be considered.
Disclosure of Invention
The invention aims to provide a real-time detection device and a real-time detection method for smoothness of a railway track, which can give consideration to detection precision, detection efficiency and real-time property.
In order to achieve the purpose, the invention provides the following scheme:
a real-time detection device for smoothness of a railway track comprises a vehicle body, an inertia measurement unit, a Beidou receiver, a mileometer, a gauge, an FPGA board card and a 5G communication module, wherein the inertia measurement unit, the Beidou receiver, the mileometer, the gauge, the FPGA board card and the 5G communication module are carried on the vehicle body; the wheels of the train body move along a railway track to be detected, and the inertia measurement unit is positioned right above one of the railway tracks; establishing a carrier coordinate system by taking the center of the inertia measurement unit as an origin, wherein the x-axis direction of the carrier coordinate system is the advancing direction of the vehicle body, the y-axis direction of the carrier coordinate system is the right side direction of the advancing direction, and the z-axis direction of the carrier coordinate system is the direction determined according to the x-axis and the y-axis according to the right-hand theorem; the Beidou receiver is positioned on the y axis of the carrier coordinate system; the odometer is arranged on a wheel corresponding to the x axis; the gauge is arranged on a wheel on the opposite side of the odometer; the FPGA is used for carrying out time synchronization on data collected by the inertia measurement unit, the Beidou receiver, the odometer and the gauge instrument and detecting the irregularity of the railway track to be detected based on the Beidou real-time PPP-AR/INS/odometer loose combination technology; the communication module is used for transmitting the irregularity detection result.
The invention also provides a real-time detection method for the smoothness of the railway track, which is applied to the real-time detection device for the smoothness of the railway track provided by the invention and comprises the following steps:
in the process that the detection device moves along the track to be detected:
determining position information, speed information and attitude information of each moment in real time based on an inertial navigation system, wherein the position information is space coordinate information;
determining position information and speed information at each moment in real time based on a Beidou satellite navigation system, wherein an uncorrected phase delay and an inter-code deviation are obtained by adopting a 5G communication module;
determining speed information at each moment in real time based on the odometer;
performing loose combination processing on the position information and the speed information of each moment determined based on an inertial navigation system, the position information and the speed information of each moment determined based on a Beidou satellite navigation system and the speed information of each moment determined based on a odometer by using Kalman filtering to obtain the position information and the attitude information fused and filtered at each moment;
determining the motion track of the detection device according to the position information fused and filtered at each moment;
when the detection device completes the movement along the track to be detected:
determining the position coordinates of each track sleeper according to the design distance between adjacent track sleepers and the motion track of the detection device, wherein the first track sleeper is located at the starting point of the motion track;
determining an actual measurement vector of the track sleeper according to the position coordinates of the track sleeper;
calculating the direction irregularity of the track to be detected according to the actual measurement vector and the design vector of the track sleeper;
calculating the unevenness of the track to be detected according to the track gauge measured by the track gauge instrument and the roll angle information in the attitude information after the fusion filtering;
and transmitting the detection result by adopting a 5G communication module.
Optionally, before performing loose combination, the method further includes:
unifying the reference system of the position information and the speed information of each time determined by the inertial navigation system, the position information and the speed information of each time determined by the Beidou satellite navigation system and the speed information of each time determined by the odometer.
Optionally, after obtaining the position information and the posture information subjected to fusion filtering at each time, the method further includes: and smoothing the position information and the attitude information which are fused and filtered at each moment.
Optionally, the calculating the direction irregularity of the track to be detected according to the measured normal vector and the designed normal vector of the track sleeper specifically includes:
according to Δ h1＝(h25design-h33design)-(h25measure-h33measure) Calculating a 30m short wave irregularity index delta h of the track to be detected1Wherein h is25designDesign normal vector, h, corresponding to the 25 th rail sleeper of each section of chord length25measureThe measured vector h corresponding to the 25 th track sleeper of each section of chord length33designA design normal vector h corresponding to the 33 th track sleeper of each chord length section33measureThe measured vector corresponding to the 33 th track sleeper of each section of chord length;
according to Δ h2＝(h25design-h265design)-(h25measure-h265measure) Calculating 300m long wave irregularity index delta h of the track to be detected2Wherein h is265designA design normal vector h corresponding to the 265 th rail sleeper of each section of chord length265measureAnd the measured vector corresponds to the 265 th rail sleeper of each chord length.
Optionally, the calculating the unevenness of the track to be detected according to the track gauge measured by the track gauge instrument and the roll angle information in the attitude information after the fusion filtering specifically includes:
and calculating the rough smoothness index H of the track to be detected according to H-Dsin theta, wherein D is the track gauge measured by the track gauge instrument, and theta is roll angle information in the attitude information after fusion filtering.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention provides a real-time detection device and a detection method for railway track smoothness, which are based on long-term high-precision positioning stability of a Beidou satellite navigation system real-time ambiguity fixed precision positioning technology and short-term positioning stability and high autonomy of an INS (inertial navigation system). A real-time Beidou PPP-AR/INS/odometer loose combination data processing method is adopted to obtain high-precision three-dimensional position coordinates and high-precision attitude information of a railway track, reconstruct the three-dimensional geometrical shape of the track, obtain geometrical parameter information of the track and further detect the irregularity of the track. The real-time Beidou PPP-AR can provide centimeter-level real-time position information, and the real-time PPP-AR/INS loose combination technology can provide high-precision, continuous and stable real-time precise position, speed and attitude information. In order to further improve the detection precision of smoothness, RTS reverse smoothing filtering is carried out on data subjected to real-time PPP-AR/INS loose combination, the position and posture precision is further improved, and the track geometric parameters and the irregularity of a detection line are more accurately extracted.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a real-time detection device for the smoothness of a railway track in embodiment 1 of the present invention;
fig. 2 is a flowchart of a real-time detection method for railway track smoothness in embodiment 2 of the present invention.
1. An FPGA board card; 2. a gauge; 3. a mobile power supply; 4. a Beidou receiver antenna; 5. a Beidou receiver; 6. an inertial measurement unit; 7. a hardware platform; 8. a 5G communication module; 9. and (4) an odometer.
Detailed Description
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
English abbreviations referred to in the present invention:
BDS: the Beidou Satellite navigation System, BeidouNavigation Satellite System;
an IMU: an Inertial Measurement Unit, Inertial Measurement Unit;
INS: inertial navigation System, inertial navigation System;
PPP: precision single point positioning, precision PointPositioning;
PPK: post-processing dynamic Positioning, Post Positioning Kinematic;
IGS: the international Global Navigation Satellite system Service organization, Internet Global Navigation Satellite Systems Service center;
UPD: uncorrected phase Delay, unaltered phase Delay;
LAMBDA: least squares reduction correlation Adjustment, Least-square algorithm correction Adjustment;
AR: ambiguity Resolution, Ambiguity Resolution;
RT: Real-Time, Real-Time;
ODO: odometer, Odometer;
RTS: RTS optimal smoothing algorithm, Rauch-Tung-Streibel smooth;
5G: 5G Communication, The 5th Generation Mobile Communication Technology;
example 1
Fig. 1 is a schematic structural diagram of a real-time detection device for the smoothness of a railway track in embodiment 1 of the present invention, and referring to fig. 1, a real-time detection device for the smoothness of a railway track 7 provided in this embodiment includes a vehicle body, a mobile power supply 3 mounted on the vehicle body, an inertia measurement unit 6, a Beidou receiver 5, a odometer 9, a gauge 2, an FPGA board 1, and a 5G communication module 8; wheels of the train body move along a railway track to be detected; the inertia measurement unit 6 is positioned right above a certain track in the railway track; a carrier coordinate system (F-R-D, b system) established with the center of the inertial measurement unit 6 as an origin, wherein the x-axis direction of the carrier coordinate system is a Forward direction (Forward, denoted as F) of the vehicle body, the y-axis direction of the carrier coordinate system is a Right direction (Right, denoted as R) of the Forward direction, and the z-axis direction of the carrier coordinate system is a direction (Down, denoted as D) determined according to the Right-hand theorem according to the x-axis and the y-axis; the Beidou receiver 5 is positioned on the y axis of the carrier coordinate system; the odometer 9 is arranged on a wheel corresponding to the x axis; the gauge 2 is arranged on the wheel on the opposite side of the odometer 9; the FPGA board card 1 is embedded in the 5G communication and is arranged at the tail position of the left side of the detection device; the mobile power supply 3 and the Beidou receiver 5 are arranged at the position close to the Beidou receiver antenna 4; the FPGA is used for carrying out time synchronization on data collected by the inertia measurement unit 6, the Beidou receiver 5, the odometer 9 and the gauge 2 and detecting the irregularity of the railway track to be detected based on a Beidou real-time PPP-AR/INS/odometer loose combination technology; the communication module is used for transmitting the irregularity detection result.
The Beidou receiver 5 is connected with the Beidou receiver antenna 4, the mobile power supply 3 and the FPGA board card 1; the odometer 9 is connected with the FPGA board card 1 and the mobile power supply 3; the inertia measurement unit 6 is connected with the FPGA board card 1 and the mobile power supply 3; the gauge 2 is connected with the FPGA board card 1 and the mobile power supply 3; the FPGA board card 1 is connected with a mobile power supply 3.
The inertia measurement unit 6, the Beidou receiver antenna 4 and the odometer 9 are in rigid relation, so that the inertia measurement unit 6, the Beidou receiver antenna 4 and the odometer 9 are consistent in movement, and when the carrier device moves, the spatial position relation among the three is unchanged under the system b.
The Beidou receiver antenna 4 and the odometer 9 are in measurement with the inertial measurement unit 6The coordinates in the b system with the center as the origin of coordinates are
And
example 2
The method for detecting the smoothness of a railway track in real time provided in this embodiment 2 is a detection method based on the device for detecting the smoothness of a railway track in real time provided in embodiment 1, and referring to fig. 2, the method includes:
in the process that the detection device moves along the track to be detected:
step 201: determining position information, speed information and attitude information at each moment in real time based on an inertial navigation system, wherein the position information is space coordinate information;
step 202: determining position information and speed information at each moment in real time based on a Beidou satellite navigation system, wherein an uncorrected phase delay and an inter-code deviation are obtained by adopting a 5G communication module;
step 203: determining speed information at each moment in real time based on the odometer;
step 204: performing loose combination processing on the position information and the speed information of each moment determined based on an inertial navigation system, the position information and the speed information of each moment determined based on a Beidou satellite navigation system and the speed information of each moment determined based on a odometer by using Kalman filtering to obtain the position information and the attitude information fused and filtered at each moment;
step 205: determining the motion track of the detection device (namely the three-dimensional geometric shape of the railway track to be detected) according to the position information fused and filtered at each moment;
when the detection device completes the movement along the track to be detected:
step 206: determining the position coordinates of each track sleeper according to the design distance between adjacent track sleepers and the motion track of the detection device, wherein the first track sleeper is located at the starting point of the motion track;
step 207: determining an actual measurement vector of the track sleeper according to the position coordinates of the track sleeper;
step 208: calculating the direction irregularity of the track to be detected according to the actual measurement vector and the design vector of the track sleeper;
step 209: calculating the unevenness of the track to be detected according to the track gauge measured by the track gauge instrument and the roll angle information in the attitude information after the fusion filtering;
step 210: and transmitting the detection result by adopting a communication module.
According to the embodiment, the Beidou real-time PPP-AR/INS loose combination technology is adopted to accurately determine the three-dimensional geometric shape of the railway track to be detected, and the detection precision of the railway track irregularity is guaranteed. Meanwhile, due to the real-time performance of the Beidou PPP-AR, when the detection device moves along the railway track to be detected, the three-dimensional geometric shape of the railway track to be detected can be obtained, the irregularity of the railway track to be detected can be detected, and the real-time performance of detection is realized.
Wherein, step 201 is: BDS satellite real-time precise orbit/clock error data broadcasted in real time based on a BDS satellite system B2B signal frequency and BDS satellite UPD data provided by an IGS center in real time are received by a 5G communication module, real-time BDS precise point positioning ambiguity fixing (PPP-AR) resolving is carried out, and therefore the high-precision position and the high-precision speed of the Beidou receiver antenna phase center are calculated. The calculation method is as follows:
1) performing BDS PPP floating solution calculation by using dual-frequency pseudorange, carrier and Doppler observed value output by a BDS receiver integrated on a track detection hardware device and BDS satellite real-time precise track/clock difference data broadcasted by B2B signal frequency in real time to obtain floating solution ambiguity vectors of BDS B1I and B3I frequency point carrier observed values (a floating solution ambiguity vector of a BDS B1I and a BDS B3I frequency point carrier observed value
And
t represents a matrix transposition operation, m0 represents a reference satellite number, m1, m2, …, m represent numbers of observation satellites other than the reference satellite), and a corresponding variance-covarianceDifference matrix (Q)N1,fAnd QN3,f)；
2) Using received BDS satellite UPD data
in the equation, Δ represents the inter-satellite single difference calculation between the satellite m and the reference satellite m 0.
3) Variance-covariance matrix (Q) of UPD corrected single-differenced ambiguities and floating solution ambiguities calculated based on equations (1) and (2)N1,fAnd QN3,f) Constructing variance-covariance matrices corresponding to equations (1) and (2) according to the law of error propagation: (
And
)：
in the formula,
represents the ambiguity of the m-th satellite corrected by UPD at the frequency of B1I
Ambiguity with UPD corrected reference satellite (m0)
Inter-satellite single difference ambiguities between.
4) Searching integer single-difference ambiguity values corresponding to real single-difference ambiguities of (3) and (4) by adopting a least square ambiguity descending correlation adjustment LAMBDA algorithm based on the inter-satellite single-difference ambiguity vectors of the equations (3) and (4) and the variance covariance matrixes of the equations (5) and (6)
5) Substituting the integer single-difference ambiguity value obtained by calculation in the step 4) back into the inter-satellite single-difference carrier wave observation equation:
in the formula, L represents the distance from the phase center of the Beidou receiver antenna to the phase center of the Beidou satellite antenna for carrier measurement,
the carrier phase value of the Beidou receiver observation is represented, and the lambda represents the Beidou carrier wavelength. And calculating the high-precision real-time position of the BDS receiver antenna phase center based on the order inertial least square principle.
6) Based on the position of the BDS receiver antenna phase center and the Doppler observed value calculated in the step 5), calculating the BDS satellite speed by using the BDS real-time precise orbit, and calculating the high-precision real-time speed at the BDS receiver antenna based on the least square theory and the BDS speed measurement theory.
Before step 204, the method further comprises:
unifying the reference system of the position information and the speed information of each time determined by the inertial navigation system, the position information and the speed information of each time determined by the Beidou satellite navigation system and the speed information of each time determined by the odometer. The method specifically comprises the following steps:
a) linear velocity observations (f) output by accelerometers using IMUb) And angular velocity observations of gyroscope outputs (
i represents the geocentric inertial coordinate system inertia frame), according to the INS navigation equation and the attitude transformation matrix
(N represents navigation frame), North-East-Down, and is recorded as N-E-D), and the position of the IMU measurement center at the time k in the navigation frame is calculated according to the differential discrete equation in the formula (9)
Speed of rotation
And posture
In the formula,
a differential equation is expressed as a function of,
representing the projection of the angular velocity of i system relative to n system in n system;
represents the projection of the geocentric earth fixed frame (noted as e system) relative to the angular velocity of n system in n system; gnRepresenting the projection of the gravity acceleration vector in an n system; x represents a matrix cross product operation; theta, phi and psi respectively represent a roll angle, a pitch angle and a heading angle; atan is a function for calculating the arctan value in C/C + + language, and the return value is between-pi/2- + pi/2; atan2 is a function in C/C + + language for calculating the arctan values divided by quadrants, with the return value between- π and + π;
to represent
Line k1 and column k2Of (2) is used.
b) Lever arm according to quantity
And attitude transformation matrix
And the current position at the antenna of the BDS receiver
And velocity
Calculating the position of IMU center under n series
And velocity
Wherein R isMAnd RNRespectively representing the curvature radius of a meridian and a prime circle, h represents the geodetic height, and diag represents a diagonal matrix;
c) measuring the movement speed of the carrier along the x axis under the b system according to the odometer
Meanwhile, the physical fact that the carrier does not move along the directions of the y axis and the z axis under the b system when moving along the track is consideredLever arm for odometer to IMU center
And attitude transformation matrix
And installing an angle error rotation matrix, and calculating the projection of the carrier motion speed in the IMU center in n systems:
wherein,
representing a rotation matrix formed by the directional difference of coordinate axes between a carrier coordinate system established by the center of the hardware platform and a carrier coordinate system established by the center of the IMU,
represents the projection of the angular velocity of b system relative to n system in b system.
Then, in step 204, data fusion and kalman wave processing are performed, specifically:
d) constructing an innovation vector in an observation equation of Kalman filtering based on the IMU center position and the velocity information calculated by the a), the b) and the c):
according to an observation updating function model of the extended Kalman filtering, parameter resolving is carried out:
δxk＝δxk-1+Kk(Zk-Hkδxk-1) (16)
in the formula, δ x represents a parameter correction vector, KkAnd HkRespectively representing a gain matrix and a design coefficient matrix of Kalman filtering.
Real-time saving of IMU measurement center position at time k
Speed of rotation
And posture
And the state parameter correction vector δ x calculated by equation (16)kAnd δ xkCorresponding predicted value
(＝Φk/k-1δxk-1,Φk/k-1A state transition matrix representing the variation of the state vector in the time domain, determined by the kinetic function of each parameter), while preserving δ xkAnd δ xkCorresponding covariance matrix
And
after step 204, further comprising: and smoothing the roll angle information and the position information at each time. Namely: correcting the position of the INS at each moment from back to front by using the state parameter after RTS smoothing
Speed of rotation
And posture
Correcting the data to obtain the final high-precision position
Speed of rotation
And posture
The information comprises the following specific processes:
correction of a number vector deltax using real-time saved state parameterskAnd predicted value δ xkAnd corresponding variance covariance matrix
And
calculating the smoothed correction vector according to the following RTS smoothing function model
And corresponding variance covariance matrix
In the formula,
representing an RTS filter gain matrix, wherein N represents the total number of epoch state information in a smooth interval; k is N-1, N-2, …, and 0 indicates the interval epoch time.
The smoothed correction vector calculated by equation (17)
For the stored position of INS at each moment
Speed of rotation
And posture
Correcting the data to obtain the final high-precision position
Speed of rotation
And posture
And (4) information.
Step 208 specifically includes:
based on the railway track smoothness detection theory, track geometric parameters, long and short wave track directions and unevenness are calculated. Namely: the high-precision position coordinates obtained in the step 4
Converting into position coordinates under b system
And accumulating and calculating the mileage corresponding to each moment, interpolating coordinate values corresponding to each track sleeper by adopting a sliding window fitting method and taking the track sleeper corresponding to the initial moment as the 1 st track sleeper according to the standard track sleeper interval of 0.625m, calculating the interval between adjacent sleepers under the system b, and accumulating to calculate the mileage corresponding to each sleeper. Then, the rail direction and the roughness of the long wave and the short wave are calculated according to a method for detecting the roughness of the short wave of 30m (spacing of 48 rail sleepers) and the long wave of 300m (spacing of 480 rail sleepers) specified by the China railway department.
According to Δ h1＝(h25design-h33design)-(h25measure-h33measure) Calculating a 30m short wave irregularity index delta h of the track to be detected1Wherein h is25designA design normal vector (the distance from the position of the designed 25 th track sleeper to the connecting line between the 1 st track sleeper and the 49 th track sleeper), h, corresponding to the 25 th track sleeper in each chord length section25measureA measured true vector (the distance from the actual 25 th track sleeper position to the connecting line between the 1 st track sleeper and the 49 th track sleeper), h, corresponding to the 25 th track sleeper in each section of chord length33designA design positive vector (the distance from the position of the designed 33 th track sleeper to the connecting line between the 1 st track sleeper and the 49 th track sleeper), h, corresponding to the 33 th track sleeper in each chord length section33measureAn actual measurement vector corresponding to the 33 th track sleeper (the distance from the actual 33 th track sleeper position to the connecting line between the 1 st track sleeper and the 49 th track sleeper) of each chord length section;
according to Δ h2＝(h25design-h265design)-(h25measure-h265measure) Calculating 300m long wave irregularity index delta h of the track to be detected2Wherein h is265designA design normal vector (the distance from the designed 265 th rail sleeper position to the connecting line between the 1 st rail sleeper and the 481 st rail sleeper) corresponding to the 265 th rail sleeper in each chord length section h265measureAnd the measured vector corresponding to the 265 th rail sleeper (the distance from the actual 265 th rail sleeper position to the connecting line between the 1 st rail sleeper and the 481 st rail sleeper) of each chord length section.
Step 209 specifically comprises:
and calculating the irregularity index H of the track to be detected according to H-Dsin theta, wherein D is the track gauge measured by the track gauge instrument, and theta is roll angle information in the attitude information.
And finally, immediately determining the positions of the sleepers needing to be adjusted according to the real-time calculation results of the formulas (19) to (21) and the positions corresponding to all the sleepers, and transmitting the detection results through a 5G communication module. The invention adopts the Beidou real-time PPP-AR/INS/odometer loose combination technology, can simultaneously and accurately calculate the specific data of the rail irregularity and the sleeper position with the rail irregularity, and can meet the requirement of real-time fine adjustment of the rail sleeper.
Compared with the current high-speed rail smoothness detection technology, the method has the following advantages: (1) the track smoothness detection is finished in real time with high precision, and a result is obtained after the track smoothness detection is finished; (2) the method can provide real-time determination of the position and the adjustment amount of the sleeper to be adjusted.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (5)
1. A real-time detection method for railway track smoothness is characterized by being applied to a real-time detection device for railway track smoothness, wherein the detection device comprises a vehicle body, an inertia measurement unit, a Beidou receiver, a mileometer, a gauge, an FPGA board card and a 5G communication module, wherein the inertia measurement unit, the Beidou receiver, the mileometer, the gauge, the FPGA board card and the 5G communication module are carried on the vehicle body; the wheels of the train body move along a railway track to be detected, and the inertia measurement unit is positioned right above one of the railway tracks; establishing a carrier coordinate system by taking the center of the inertia measurement unit as an origin, wherein the x-axis direction of the carrier coordinate system is the advancing direction of the vehicle body, the y-axis direction of the carrier coordinate system is the right side direction of the advancing direction, and the z-axis direction of the carrier coordinate system is the direction determined according to the x-axis and the y-axis according to the right-hand theorem; the Beidou receiver is positioned on the y axis of the carrier coordinate system; the odometer is arranged on a wheel corresponding to the x axis; the gauge is arranged on a wheel on the opposite side of the odometer; the FPGA is used for carrying out time synchronization on data collected by the inertia measurement unit, the Beidou receiver, the odometer and the gauge instrument and detecting the irregularity of the railway track to be detected based on the Beidou real-time PPP-AR/INS/odometer loose combination technology; the 5G communication module is used for receiving the real-time precise orbit, clock error, inter-code deviation, uncorrected phase delay data and transmission irregularity detection result of the Beidou satellite;
the method comprises the following steps:
in the process that the detection device moves along the track to be detected:
determining position information, speed information and attitude information of each moment in real time based on an inertial navigation system, wherein the position information is space coordinate information;
determining position information and speed information at each moment based on a Beidou satellite navigation system real-time PPP-AR, wherein a 5G communication module is adopted to obtain a Beidou satellite real-time precise orbit, a clock error, an uncorrected phase delay and an inter-code deviation;
determining speed information at each moment in real time based on the odometer;
performing loose combination processing on the position information and the speed information of each moment determined based on an inertial navigation system, the position information and the speed information of each moment determined based on a Beidou satellite navigation system and the speed information of each moment determined based on a odometer by using Kalman filtering to obtain the position information and the attitude information fused and filtered at each moment;
determining the motion track of the detection device according to the position information fused and filtered at each moment;
when the detection device completes the movement along the track to be detected:
determining the position coordinates of each track sleeper according to the design distance between adjacent track sleepers and the motion track of the detection device, wherein the first track sleeper is located at the starting point of the motion track;
determining an actual measurement vector of the track sleeper according to the position coordinates of the track sleeper;
calculating the direction irregularity of the track to be detected according to the actual measurement vector and the design vector of the track sleeper;
calculating the unevenness of the track to be detected according to the track gauge measured by the track gauge instrument and the roll angle information in the attitude information after the fusion filtering;
and transmitting the detection result by adopting a 5G communication module.
2. The method of claim 1, further comprising, prior to performing loose assembly:
unifying the reference system of the position information and the speed information of each time determined by the inertial navigation system, the position information and the speed information of each time determined by the Beidou satellite navigation system and the speed information of each time determined by the odometer.
3. The method according to claim 1, wherein after obtaining the position information and the attitude information fused and filtered at each time, the method further comprises: and smoothing the position information and the attitude information which are fused and filtered at each moment.
4. The method for detecting the smoothness of the railway track in real time according to claim 1, wherein the calculating the direction irregularity of the track to be detected according to the measured normal vector and the designed normal vector of the track sleeper specifically comprises:
according to Δ h1＝(h25design-h33design)-(h25measure-h33measure) Calculating a 30m short wave irregularity index delta h of the track to be detected1Wherein h is25designDesign normal vector, h, corresponding to the 25 th rail sleeper of each section of chord length25measureThe measured vector h corresponding to the 25 th track sleeper of each section of chord length33designA design normal vector h corresponding to the 33 th track sleeper of each chord length section33measureThe measured vector corresponding to the 33 th track sleeper of each section of chord length;
according to Δ h2＝(h25design-h265design)-(h25measure-h265measure) Calculating 300m long wave irregularity index delta h of the track to be detected2Wherein h is265designA design normal vector h corresponding to the 265 th rail sleeper of each section of chord length265measureAnd the measured vector corresponds to the 265 th rail sleeper of each chord length.
5. The method according to claim 1, wherein the calculating of the roughness of the track to be detected according to the track gauge measured by the gauge and the roll angle information in the attitude information after the fusion filtering specifically comprises:
and calculating the rough smoothness index H of the track to be detected according to H-Dsin theta, wherein D is the track gauge measured by the track gauge instrument, and theta is roll angle information in the attitude information after fusion filtering.
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| CN117233818A (en) * | 2023-11-16 | 2023-12-15 | 中国铁路设计集团有限公司 | Method for enhancing stability of tamping car mileage positioning technology based on Beidou/GNSS |
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