CN110658543B - High-speed railway track geometric parameter detection method based on non-contact measurement - Google Patents

High-speed railway track geometric parameter detection method based on non-contact measurement Download PDF

Info

Publication number
CN110658543B
CN110658543B CN201810700229.4A CN201810700229A CN110658543B CN 110658543 B CN110658543 B CN 110658543B CN 201810700229 A CN201810700229 A CN 201810700229A CN 110658543 B CN110658543 B CN 110658543B
Authority
CN
China
Prior art keywords
track
measurement
fitting
inertial
coordinates
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810700229.4A
Other languages
Chinese (zh)
Other versions
CN110658543A (en
Inventor
邓继权
郭玉胜
王海军
艾赢涛
马小艳
张吉先
莫明岗
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Automation Control Equipment Institute BACEI
Original Assignee
Beijing Automation Control Equipment Institute BACEI
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Automation Control Equipment Institute BACEI filed Critical Beijing Automation Control Equipment Institute BACEI
Priority to CN201810700229.4A priority Critical patent/CN110658543B/en
Publication of CN110658543A publication Critical patent/CN110658543A/en
Application granted granted Critical
Publication of CN110658543B publication Critical patent/CN110658543B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining 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
    • G01S19/42Determining position
    • G01S19/45Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • G01S19/47Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S17/00Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06Systems determining position data of a target
    • G01S17/42Simultaneous measurement of distance and other co-ordinates
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining 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
    • G01S19/42Determining position
    • G01S19/50Determining position whereby the position solution is constrained to lie upon a particular curve or surface, e.g. for locomotives on railway tracks
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Navigation (AREA)

Abstract

The invention belongs to a precise detection technology, in particular to a high-speed railway orbit geometric parameter detection method based on non-contact measurement, which comprises the steps of firstly carrying out combined navigation and calculation through an inertial navigation system and a high-precision differential satellite positioning system to obtain the space position and posture information of an inertial measurement unit, and obtaining the position and posture information of the laser range finder by calibrating the installation relation of the laser range finder and the inertial measurement unit according to the three-dimensional coordinates of orbit feature points obtained by fitting, and calculating the three-dimensional displacement information of the orbit feature points at any position relative to a starting point in the measurement process, thereby realizing high-precision, high-efficiency, dynamic and continuous measurement of the orbit geometric parameters.

Description

High-speed railway track geometric parameter detection method based on non-contact measurement
Technical Field
The invention belongs to a precise detection technology, and particularly relates to a high-speed railway track geometric parameter detection method based on non-contact measurement.
Background
In order to ensure the operation safety of rail transit, in recent years, a rail precision detection technology is rapidly developed, and a large amount of manpower and material resources are invested in a plurality of countries to develop and update various rail detection methods so as to meet the requirements of high speed and heavy load of the current railway. The vehicle-mounted dynamic detection mode has small influence on normal operation, high efficiency and high speed, truly reflects the infrastructure state under the train operation condition, and becomes one of main detection means of the safety states of railway and urban rail transit infrastructures.
The detection of the geometric parameter state of the track mainly comprises detection items such as track gauge, track direction, height and the like, wherein the track gauge refers to the distance between track gauge points at 16mm positions below the working surfaces of left and right strands of steel rails with the same cross section. The commonly used method for measuring the track gauge mainly comprises two main types of contact measurement and non-contact measurement. The contact type track gauge measuring method is characterized in that the linear displacement sensor is used for measuring the track gauge, the sensor is ensured to be in contact with the track gauge point to be measured at any moment through a mechanical structure in the detection process, the measuring efficiency is low, and the method is not suitable for high-speed measurement. The commonly used non-contact track gauge measuring method is to continuously shoot the inner side section of the track gauge by using a shooting mechanism, reproduce the curve of the inner side section of the track by using an image reconstruction method, and calculate the track gauge value. The measuring method has high measuring precision and is not influenced by the detection speed, but the method is easy to be interfered by light, has strict requirements on the use environment and has limited use range. The method for detecting the track direction and the height of the track mainly comprises a chord measurement method, an inertial reference method and the like, wherein the chord measurement method is to actually establish a chord line on the track by adopting a manual wire drawing method, and the smoothness of the track (track direction) is evaluated by measuring the relative displacement between the track top surface (track gauge point) of the track and the chord line. The wavelength of the chord measurement method is closely related to the length of the detection chord, when the track smoothness of various wavelengths needs to be analyzed, the detection device needs to be replaced for re-measurement, or the conversion of 'small pushing and large pushing' is carried out according to the current detection result, the former increases the workload of detection personnel, the working efficiency is low, and the latter has larger error. The inertial reference method is based on strapdown inertial navigation technology, and uses accelerometer to measure acceleration information of carrier in three axial directions, uses gyroscope to measure angular rate information in three axial directions, establishes an inertial reference through acceleration and angular rate information, and uses displacement sensor or image sensor to measure relative position of rail relative to reference, so as to obtain relative position of rail in inertial coordinate system.
At present, most of the world railway track detection methods are converted from a chord measurement method to an inertial reference method, and particularly in the field of high-speed railway detection, all the countries are developing advanced track detection methods with strong comprehensiveness, high precision, high speed, high intelligence and high reliability based on the inertial technology. For example, a T10 type rail inspection vehicle developed by Ensco corporation in U.S. adopts an inertial reference measurement principle and a non-contact measurement method, and can measure parameters such as geometric parameters of a rail, section of a steel rail, wave abrasion and the like. The Italy 'Archimedes' comprehensive detection train also adopts a non-contact measurement scheme based on an inertial reference method, and can detect 119 different parameters including geometric parameters of a track, a section of a steel rail, wave wear of the steel rail, contact network and current receiving state, communication and signals, acceleration of a train body and an axle box and acting force of a wheel and a rail. The French MVG comprehensive detection train is designed to have a detection speed of 320km/h, and the detection parameters comprise various infrastructure states such as track geometric parameters, rail sections, rail surfaces, communication signals, line environment digital images, fasteners, sleepers, ballast and the like. The GJ-3 type, GJ-4 type and GJ-5 type track detecting vehicles in China all adopt track detecting methods based on an inertia technology, but have strict requirements on the running speed of the detecting vehicle, and the highest measuring speed of the GJ-5 type track detecting vehicle is only 180km/h. From the technical development at home and abroad, non-contact measurement based on an inertial technology is a commonly adopted mode in a high-speed environment, and mainly comprises the steps of continuously updating a gesture matrix through gyro angular rate information, converting acceleration information into a geographic coordinate system, continuously integrating the converted acceleration signal twice, thus obtaining a space motion track of an inertial measurement unit, and reproducing track geometric parameters such as track gauge, smoothness and the like through methods such as image reconstruction and the like. However, the method has strict requirements on the running speed of the rail detection vehicle, and the method is difficult to meet the measurement requirement of high-speed rails on the long-wave smoothness of more than 150 meters. The invention provides a track geometric parameter detection method based on inertia/laser measurement, which has no strict requirement on the running speed of a train, can be applied to the train in normal operation, and can meet the measurement requirement of long-wave smoothness of 150 meters and 300 meters.
Disclosure of Invention
The invention aims to provide a high-speed railway track geometric parameter detection method based on non-contact measurement.
The technical scheme of the invention is as follows:
a high-speed railway track geometric parameter detection method based on non-contact measurement comprises the following steps:
step 1), performing inertial/satellite integrated navigation calculation to obtain position, speed and attitude information of an inertial measurement unit;
step 2) laser measurement data processing;
2.1 Time-aligning the inertial measurement data with the laser measurement data;
2.2 Judging the validity of the track characteristic point coordinates measured at different measuring moments;
2.3 Calculating to obtain three-dimensional position coordinates of the effective track feature points;
step 3), track position coordinate fitting calculation;
3.1 Calculating the displacement S of each measuring point relative to the initial point according to the track characteristic point coordinates;
S=S 0 +ΔS
Figure GDA0004192843260000031
in the method, in the process of the invention,
Figure GDA0004192843260000032
the three-dimensional coordinates of the characteristic points of the track at two adjacent moments are obtained, and delta S is the displacement variation between the two adjacent points;
3.2 Segmented coordinate fitting;
segment coordinate fitting is carried out by taking 0.625m as a fixed length, and if S is more than 0.625m, the fitted track position coordinates can be obtained;
Figure GDA0004192843260000041
in the method, in the process of the invention,
Figure GDA0004192843260000042
for fitting the obtained three-dimensional coordinates of the track characteristic points, n is the number of fitting times at intervals of 0.625 m;
step 4) utilizing the three-dimensional coordinates of the orbit characteristic points obtained by fitting
Figure GDA0004192843260000043
Determining three-dimensional displacement information of track characteristic points at any position relative to starting point in measurement process。
The step 1) specifically comprises the following steps:
1.1 Determining a state equation
Figure GDA0004192843260000044
State variables
Figure GDA0004192843260000045
w is system noise, A is system state matrix
1.2 Determining a measurement equation
The Kalman filtering measurement equation is
Z=HX+v
Wherein Z represents Kalman filtering observed quantity, H represents system observation matrix, and v represents system measurement noise;
the observed quantity is
Figure GDA0004192843260000046
Figure GDA0004192843260000047
Representing the navigation coordinate system velocity obtained by inertial navigation solution,/->
Figure GDA0004192843260000048
A navigation coordinate system velocity component representing a differential satellite positioning output;
the observation matrix H is
Figure GDA0004192843260000051
1.3 Performing Kalman filtering estimation to estimate the position error, the speed error and the attitude error of the inertial navigation system;
1.4 Error correction is carried out on the obtained state estimation value, and the position, speed and attitude information of the inertial measurement unit are obtained.
Step 2.2) judges the validity of the track characteristic point coordinates measured at different measuring moments, and specifically comprises the following steps:
the coordinates of the characteristic points of the track obtained by laser measurement at different moments are set as (x i ,y i ,z i )、(x i+1 ,y i+1 ,z i+1 )、(x i+2 ,y i+2 ,z i+2 );
If |x i+1 -x i | > ζ and |x i+2 -x i < ζ, x i+1 For abnormal coordinate values, x needs to be re-aligned i+1 Fitting, x i+1 =(x i +x i+2 )/2;
If |y i+1 -y i | > ζ and |y i+2 -y i < ζ, y i+1 For abnormal coordinate values, y needs to be re-aligned i+1 Fitting, y i+1 =(y i +y i+2 )/2;
If |z i+1 -z i | > ζ and |z i+2 -z i < ζ, z i+1 For abnormal coordinate values, Z is required to be re-aligned i+1 Fitting, z i+1 =(z i +z i+2 )/2;
Wherein ζ is a constant value of 0.1-0.5.
The step 2.3) specifically comprises the following steps:
the relative coordinates of the orbit feature points obtained by laser measurement after the validity judgment are set as (x, y, z), and the position (p) is obtained according to the inertia/satellite combination x ,p y ,p z ) Three-dimensional position coordinates of the track characteristic points can be calculated
Figure GDA0004192843260000052
Figure GDA0004192843260000053
Wherein L is b The lever arm between the laser range finder and the inertial measurement unit is obtained through calibration before test, C α For the laser measurement of the transformation matrix of the coordinate system into the carrier coordinate system,
Figure GDA0004192843260000061
is a transformation matrix from a carrier coordinate system of an inertial navigation system to a navigation coordinate system.
The invention has the remarkable effects that:
the method takes inertial measurement as a reference, and utilizes the position and attitude information of an inertial measurement unit and the coordinate information of the characteristic points of the track obtained by laser measurement to obtain the smoothness of the steel rails on the left side and the right side and the track gauge value between the left rail and the right rail. Firstly, the combined navigation solution is carried out through an inertial navigation system and a high-precision differential satellite positioning system to obtain the space position and posture information of an inertial measurement unit, and the installation relation between the laser range finder and the inertial measurement unit can be obtained through calibration, so that the position and posture information of the laser range finder can be obtained. And then combining the coordinate values of the characteristic points of the left and right rails measured by the laser range finder to obtain the position coordinates of the left and right rails, and referring to the track gauge and smoothness calculation method specified in TB/T3147-2012, the high-precision and continuous measurement of the geometric parameters of the rails can be realized.
Detailed Description
The present invention will be described in further detail with reference to specific examples.
Step 1 inertial/satellite integrated navigation computation
1.1 Determining a state equation
First, the position, speed and attitude information of an inertial measurement unit are obtained by utilizing high-precision differential satellite positioning (DGPS) information and adopting a Kalman filtering-based integrated navigation method. The SINS/DGPS integrated navigation state variables include: north, sky, east speed error δv N 、δV U 、δV E North, sky, east posture error phi N 、φ U 、φ E North, sky, east position error
Figure GDA0004192843260000062
δh, δλ, gyro drift ε in each axial direction of the carrier system x 、ε y 、ε z Zero offset of accelerometer
Figure GDA0004192843260000063
Determining system state variables
Figure GDA0004192843260000064
Determining a state equation
Figure GDA0004192843260000071
Wherein w is system noise, A is a system state matrix, and values of elements in the system state matrix can be obtained by referring to a strapdown inertial navigation system error equation according to state variables.
1.2 Determining a measurement equation
The Kalman filtering measurement equation is as follows:
Z=HX+v
wherein Z represents Kalman filtering observed quantity, H represents system observation matrix, and v represents system measurement noise.
The SINS/DGPS integrated navigation Kalman filtering adopts a speed matching mode, and the difference between the speed obtained by inertial navigation calculation and the speed measured by differential satellite positioning is used as the observed quantity of the Kalman filter. The observed quantity is:
Figure GDA0004192843260000072
in the method, in the process of the invention,
Figure GDA0004192843260000073
representing the navigation coordinate system velocity obtained by inertial navigation solution,/->
Figure GDA0004192843260000074
And a navigation coordinate system velocity component representing the differential satellite positioning output.
The corresponding measurement matrix H can be obtained according to the observed quantity
Figure GDA0004192843260000075
1.3 Filter calculation
According to the state equation and the measurement equation of the combined navigation system, the initial state estimated value X is selected 0 Initial estimation of mean square error matrix P 0 Initial variance array Q of system noise 0 Measuring noise variance matrix R k The accurate estimation of each error can be realized by referring to a Kalman filtering calculation formula, and the method belongs to the mature prior art and is not repeated.
1.4 Error correction)
And correcting the position error, the speed error and the attitude error of the inertial navigation system by using the state estimation value obtained by Kalman filtering calculation to obtain the position, the speed and the attitude information of the inertial measurement unit.
Step 2 laser measurement data processing
2.1 Time synchronization)
And according to the time stamps of the inertial measurement data and the laser measurement data, the measurement data of the inertial measurement data and the laser measurement data are aligned in time.
2.2 Abnormal data culling)
Assume that the coordinates of the characteristic points of the track obtained by laser measurement at different moments are (x i ,y i ,z i )、(x i+1 ,y i+1 ,z i+1 )、(x i+2 ,y i+2 ,z i+2 ) The validity of the measurement coordinates at each moment needs to be judged.
Taking the x coordinate as an example, if |x i+1 -x i | > ζ and |x i+2 -x i < ζ, x i+1 For abnormal coordinate values, x needs to be re-aligned i+1 Fitting, x i+1 =(x i +x i+2 ) And zeta is a constant value of 0.1-0.5.
By the same method, validity judgment needs to be carried out on the y coordinate and the z coordinate.
If |y i+1 -y i | > ζ and |y i+2 -y i < ζ, y i+1 For abnormal coordinate values, y needs to be re-aligned i+1 Fitting, y i+1 =(y i +y i+2 ) And zeta is a constant value of 0.1-0.5.
If |z i+1 -z i | > ζ and |z i+2 -z i < ζ, z i+1 For abnormal coordinate values, Z is required to be re-aligned i+1 Fitting, z i+1 =(z i +z i+2 ) And zeta is a constant value of 0.1-0.5.
2.3 Space coordinate conversion
The relative coordinates of the orbit feature points obtained by laser measurement after the validity judgment are set as (x, y, z), and the position (p) is obtained according to the inertia/satellite combination x ,p y ,p z ) Three-dimensional position coordinates of the track characteristic points can be calculated
Figure GDA0004192843260000081
Figure GDA0004192843260000082
Wherein L is b The lever arm between the laser range finder and the inertial measurement unit is obtained through calibration before test, C α The conversion matrix from the laser measurement coordinate system to the carrier coordinate system is obtained by calibration before test,
Figure GDA0004192843260000083
is a transformation matrix from a carrier coordinate system of an inertial navigation system to a navigation coordinate system.
Step 3 track position coordinate fitting calculation
Because the high-speed railway has high running speed, coordinate fitting calculation needs to be carried out among all sampling points.
3.1 Calculating the displacement S of each measuring point relative to the initial point according to the track characteristic point coordinates
S=S 0 +ΔS
Figure GDA0004192843260000091
In the method, in the process of the invention,
Figure GDA0004192843260000092
the three-dimensional coordinates of the characteristic points of the track at two adjacent moments are obtained, and delta S is the displacement variation between the two adjacent points.
3.2 Segmented coordinate fitting
Segment coordinate fitting is carried out by taking 0.625m as a fixed length, and if S is more than 0.625m, the fitted track position coordinates can be obtained
Figure GDA0004192843260000093
In the method, in the process of the invention,
Figure GDA0004192843260000094
for fitting the resulting three-dimensional coordinates of the orbit feature points, n is the number of fitting at intervals of 0.625 m.
Step 4 track geometry calculation
According to the three-dimensional coordinates of the orbit characteristic points obtained by fitting
Figure GDA0004192843260000095
The three-dimensional displacement information of the track characteristic points at any position relative to the starting point in the measurement process can be calculated, the required geometric parameters can be obtained by referring to the track gauge and ride comfort calculation method specified in the TB/T3147-2012, and the high-precision and continuous measurement of the track geometric parameters is realized.

Claims (4)

1. The method for detecting the geometric parameters of the high-speed railway track based on non-contact measurement is characterized by comprising the following steps of:
step 1), performing inertial/satellite integrated navigation calculation to obtain position, speed and attitude information of an inertial measurement unit;
step 2) laser measurement data processing;
2.1 Time-aligning the inertial measurement data with the laser measurement data;
2.2 Judging the validity of the track characteristic point coordinates measured at different measuring moments;
2.3 Calculating to obtain three-dimensional position coordinates of the effective track feature points;
step 3), track position coordinate fitting calculation;
3.1 Calculating the displacement S of each measuring point relative to the initial point according to the track characteristic point coordinates;
S=S 0 +ΔS
Figure QLYQS_1
in the method, in the process of the invention,
Figure QLYQS_2
the three-dimensional coordinates of the characteristic points of the track at two adjacent moments are obtained, and delta S is the displacement variation between the two adjacent points;
3.2 Segmented coordinate fitting;
segment coordinate fitting is carried out by taking 0.625m as a fixed length, and if S is more than 0.625m, the fitted track position coordinates can be obtained
Figure QLYQS_3
In the method, in the process of the invention,
Figure QLYQS_4
for fitting the obtained three-dimensional coordinates of the track characteristic points, n is the number of fitting times at intervals of 0.625 m;
step 4) utilizing the three-dimensional coordinates of the orbit characteristic points obtained by fitting
Figure QLYQS_5
And determining three-dimensional displacement information of the track characteristic points at any position relative to the starting point in the measuring process.
2. The method for detecting geometric parameters of a high-speed railway track based on non-contact measurement according to claim 1, wherein the step 1) specifically comprises the following steps:
1.1 Determining a state equation;
Figure QLYQS_6
state variables
Figure QLYQS_7
w is system noise, A is system state matrix;
the SINS/DGPS integrated navigation state variables include: north, sky, east speed error δv N 、δV U 、δV E North, sky, east posture error
Figure QLYQS_8
North, sky, east position error ∈>
Figure QLYQS_9
δh, δλ, gyro drift ε in each axial direction of the carrier system x 、ε y 、ε z Zero offset of accelerometer>
Figure QLYQS_10
1.2 Determining a measurement equation;
the Kalman filtering measurement equation is
Z=HX+v
Wherein Z represents Kalman filtering observed quantity, H represents system observation matrix, and v represents system measurement noise;
the observed quantity is
Figure QLYQS_11
Figure QLYQS_12
Representing the navigation coordinate system velocity obtained by inertial navigation solution,/->
Figure QLYQS_13
A navigation coordinate system velocity component representing a differential satellite positioning output;
the observation matrix H is
Figure QLYQS_14
1.3 Performing Kalman filtering estimation to estimate the position error, the speed error and the attitude error of the inertial navigation system;
1.4 Error correction is carried out on the obtained state estimation value, and the position, speed and attitude information of the inertial measurement unit are obtained.
3. The method for detecting the geometric parameters of the high-speed railway track based on non-contact measurement according to claim 1, wherein the step 2.2) is to judge the validity of the coordinates of the characteristic points of the track measured at different measurement moments, specifically:
the coordinates of the characteristic points of the track obtained by laser measurement at different moments are set as (x i ,y i ,z i )、(x i+1 ,y i+1 ,z i+1 )、(x i+2 ,y i+2 ,z i+2 );
If |x i+1 -x i | > ζ and |x i+2 -x i < ζ, x i+1 For abnormal coordinate values, x needs to be re-aligned i+1 Fitting, x i+1 =(x i +x i+2 )/2;
If |y i+1 -y i | > ζ and |y i+2 -y i < ζ, y i+1 For abnormal coordinate values, y needs to be re-aligned i+1 Fitting, y i+1 =(y i +y i+2 )/2;
If |z i+1 -z i | > ζ and |z i+2 -z i < ζ, z i+1 For abnormal coordinate values, Z is required to be re-aligned i+1 Fitting, z i+1 =(z i +z i+2 )/2;
Wherein ζ is a constant value of 0.1-0.5.
4. The method for detecting geometric parameters of a high-speed railway track based on non-contact measurement according to claim 1, wherein the step 2.3) specifically comprises the following steps:
the relative coordinates of the orbit feature points obtained by laser measurement after the validity judgment are set as (x, y, z), and the position (p) is obtained according to the inertia/satellite combination x ,p y ,p z ) Three-dimensional position coordinates of the track characteristic points can be calculated
Figure QLYQS_15
Figure QLYQS_16
Wherein L is b The lever arm between the laser range finder and the inertial measurement unit is obtained through calibration before test, C α For the laser measurement of the transformation matrix of the coordinate system into the carrier coordinate system,
Figure QLYQS_17
is a transformation matrix from a carrier coordinate system of an inertial navigation system to a navigation coordinate system.
CN201810700229.4A 2018-06-29 2018-06-29 High-speed railway track geometric parameter detection method based on non-contact measurement Active CN110658543B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810700229.4A CN110658543B (en) 2018-06-29 2018-06-29 High-speed railway track geometric parameter detection method based on non-contact measurement

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810700229.4A CN110658543B (en) 2018-06-29 2018-06-29 High-speed railway track geometric parameter detection method based on non-contact measurement

Publications (2)

Publication Number Publication Date
CN110658543A CN110658543A (en) 2020-01-07
CN110658543B true CN110658543B (en) 2023-07-14

Family

ID=69026893

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810700229.4A Active CN110658543B (en) 2018-06-29 2018-06-29 High-speed railway track geometric parameter detection method based on non-contact measurement

Country Status (1)

Country Link
CN (1) CN110658543B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114162169B (en) * 2021-10-28 2023-04-07 北京自动化控制设备研究所 Inertial and laser scanner combined online calibration method
CN114162170B (en) * 2021-10-29 2023-09-12 北京自动化控制设备研究所 Track measurement system and measurement method

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101026350B1 (en) * 2008-12-15 2011-04-04 한국철도기술연구원 System for measuring cross-level irregularity of track using inertial sensor, and method thereof
CN102252627B (en) * 2011-04-12 2012-12-26 中国航空工业第六一八研究所 Gauge detection device and detection method for high-speed railway track
CN103207403B (en) * 2013-01-15 2015-01-21 萨伏威(西安)导航技术有限公司 Satellite navigation and inertial measurement combined orbit measuring system and method
CN104634298B (en) * 2015-02-13 2017-07-04 中铁第一勘察设计院集团有限公司 Existing railway survey method based on LIDAR track cloud datas
CN107782335B (en) * 2016-08-31 2021-07-13 北京自动化控制设备研究所 Non-contact type line detection system inertial navigation and laser range finder self-calibration method

Also Published As

Publication number Publication date
CN110658543A (en) 2020-01-07

Similar Documents

Publication Publication Date Title
Chen et al. Railway track irregularity measuring by GNSS/INS integration
CN107402006B (en) Based on the matched train precision positioning method of track geometry characteristic information and system
CN103217157A (en) Inertial navigation/mileometer autonomous integrated navigation method
CN102180187B (en) High-precision height detection device and method for railway track
Zhou et al. Kinematic measurement of the railway track centerline position by GNSS/INS/odometer integration
CN107782335B (en) Non-contact type line detection system inertial navigation and laser range finder self-calibration method
CN106091951A (en) A kind of municipal rail train wheel rim parameter on-line detecting system and method
CN110106755B (en) Method for detecting irregularity of high-speed rail by reconstructing rail geometric form through attitude
CN115597535B (en) High-speed magnetic levitation track irregularity detection system and method based on inertial navigation
CN110657788B (en) Dynamic detection method for smoothness of crane track
CN112628524B (en) High-precision positioning method for small-diameter pipeline robot based on turning angle
CN110658543B (en) High-speed railway track geometric parameter detection method based on non-contact measurement
CN108195374A (en) For the integrated navigation system of track automatic measurement vehicle and integrated navigation calculation method
CN110700029A (en) Track ride comfort testing method and system
CN114719884A (en) Attitude measurement precision evaluation method and application of inertial navigation system
CN111721250B (en) Real-time detection device and detection method for smoothness of railway track
CN114046789A (en) Rail detection method based on collaborative measurement of rail inspection trolley navigation IMU
CN111895996A (en) High-speed track detection system and method
CN104047212A (en) Automatic track settlement measuring device and method based on angle measurement
CN110631573B (en) Multi-information fusion method for inertia/mileometer/total station
CN114162170B (en) Track measurement system and measurement method
Zhou et al. Onboard train localization based on railway track irregularity matching
CN114136275A (en) Track line state detection device and roadbed settlement detection method
CN111778791A (en) Low-speed track detection system and method
Dong et al. Algorithms and instrument for rapid detection of rail surface defects and vertical short-wave irregularities based on fog and odometer

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant