CN110986877A

CN110986877A - Railway engineering clearance detection method based on high-precision vehicle-mounted laser mobile measurement system

Info

Publication number: CN110986877A
Application number: CN201911220541.4A
Authority: CN
Inventors: 任晓春; 王玮; 武瑞宏
Original assignee: China Railway First Survey and Design Institute Group Ltd
Current assignee: China Railway First Survey and Design Institute Group Ltd
Priority date: 2019-12-03
Filing date: 2019-12-03
Publication date: 2020-04-10
Anticipated expiration: 2039-12-03
Also published as: CN110986877B

Abstract

The invention relates to a railway engineering clearance detection method based on a high-precision vehicle-mounted laser mobile measurement system, which is characterized in that railway engineering clearance data are measured according to high-precision three-dimensional laser point cloud through the steps of collecting field data, resolving fused point cloud data, importing, loading and displaying engineering, constructing a reference multi-segment line, dividing the reference multi-segment line, editing mileage of the reference multi-segment line, measuring a roadbed segment clearance, measuring a bridge segment clearance, measuring a tunnel segment clearance, measuring an in-station segment clearance, measuring a special point clearance and automatically outputting results, and the key problems of automation and rapid output of measurement results in the engineering clearance measurement process of the new technology of the high-precision vehicle-mounted mobile measurement system are solved in the construction process of a high-speed railway.

Description

Railway engineering clearance detection method based on high-precision vehicle-mounted laser mobile measurement system

Technical Field

The invention relates to the technical field of railway engineering clearance measurement, in particular to a railway engineering clearance detection method based on a high-precision vehicle-mounted laser mobile measurement system.

Background

In the construction process of a high-speed railway, high-precision engineering measurement needs to be carried out for multiple times in stages in order to evaluate the construction limit quality of engineering and guarantee smooth operation of the next stage. At present, the main method for measuring the engineering clearance of the high-speed rail is to use equipment such as a tape measure, a total station, a level gauge, a GPS and the like to manually measure the clearance. The traditional measurement scheme mainly has the characteristics of low operation efficiency and long operation period. How to realize automation of the measurement process and quick output of measurement results by using a novel measurement technology becomes a research focus in recent years.

The three-dimensional laser scanning technology is also called as real scene replication technology, and three-dimensional coordinate data and other key information of the surface of a measured object are rapidly acquired by a laser scanning measurement method. The three-dimensional laser scanning technology breaks through a single-point acquisition mode of conventional measurement, has the advantages of non-contact, high efficiency and the like, and provides a new thought and technical means for railway engineering clearance measurement.

The vehicle-mounted laser radar system obtains high-precision and high-density laser point cloud data of a measured target by carrying the laser scanner on the mobile platform, represents the latest development trend of the measurement technology, applies the high-precision vehicle-mounted laser mobile measurement system to the railway engineering clearance measurement process, combines developed measurement post-processing software, and can greatly improve the detection efficiency and reliability, reduce the labor intensity and improve the accuracy and precision of detection. At present, the railway engineering clearance detection by adopting a high-precision vehicle-mounted laser mobile measurement system is rarely reported.

Disclosure of Invention

The invention aims to provide a railway engineering clearance detection method based on a high-precision vehicle-mounted laser mobile measurement system, which is used for measuring railway engineering clearance data according to high-precision three-dimensional laser point cloud and solving the key problems of automation and rapid output of measurement results of a new technology of the high-precision vehicle-mounted mobile measurement system in the engineering clearance measurement process in the construction process of a high-speed railway.

The technical scheme adopted by the invention is as follows:

a railway engineering clearance detection method based on a high-precision vehicle-mounted laser mobile measurement system is characterized by comprising the following steps of:

the method is realized by the following steps:

1) acquiring field data: the RMMS high-precision vehicle-mounted mobile measurement system acquires point cloud data and navigation data along a railway; the acquired data comprises a GPS base station data acquired by an erection base station, and three-dimensional laser point cloud data, DMI data, DMR data and GPS data acquired by an RMMS high-precision vehicle-mounted mobile measurement system;

2) solving fused point cloud data: firstly, carrying out dead reckoning according to the principle of combined navigation, resolving POS track data, and then fusing point cloud data and POS track data to obtain point cloud data with absolute coordinates;

3) and (3) engineering import loading display: loading and displaying the fused data in the step 2);

4) constructing a reference multi-segment line: reading the track data of the three-dimensional laser scanning system, and performing extraction smoothing on the track data to generate three-dimensional multi-segment line data; the reference multi-segment line is used for extracting important reference information of the limit points automatically or semi-automatically;

5) dividing the reference multi-segment line: according to the coordinates of the starting and ending points of various railway types including a roadbed section, a bridge section, a tunnel section and an in-station section, which are provided by field collection, making a vertical line perpendicular to a reference multi-segment line, and cutting the multi-segment line according to the vertical point;

6) editing the reference multi-segment mileage: judging whether the mileage direction is a big mileage or a small mileage according to the running direction of the mobile vehicle-mounted system, setting the starting mileage or the ending mileage of the multi-segment line according to the field record, and automatically calculating the starting mileage, the ending mileage and the two-dimensional length of the multi-segment line;

7) measuring the limit of the roadbed section: extracting in a semi-automatic mode, capturing the bottom center point of a contact net rod in three-dimensional laser point cloud, calculating a direction vector and mileage information of a vertical point and a forward direction of a reference line, automatically extracting left and right center points of a left rail surface according to calculated parameters, constructing a rail surface coordinate system by using the extracted left and right center points of the rail surface, then automatically extracting contact net points, finally projecting the captured bottom center point into the rail surface coordinate system, wherein the horizontal distance of a roadbed section limit point is the horizontal distance from the bottom center of the contact net rod to the center of a steel rail, the vertical distance is the vertical distance from the lowest point of a contact net corresponding to the contact net rod to the center of the steel rail, finally assigning corresponding attribute information to the roadbed limit point, and sequentially extracting all engineering limit data on the left side and the right side of the whole;

8) bridge segment clearance measurement: extracting in a full-automatic mode, segmenting and calculating the central point of each section, the direction vector of the advancing direction, the rolling angle and the mileage information according to the step length, the selected reference line and the point cloud trajectory line data, automatically extracting the left and right central points of the left and right rail surfaces according to the calculated parameters, constructing a rail surface coordinate system by using the extracted left and right central points of the rail surface, then segmenting point cloud data of the current rail of the section, projecting the point cloud data into the rail surface coordinate system, automatically extracting coordinates of the contact points and the ballast wall blocking points at the position according to an algorithm, wherein the horizontal distance of the bridge section limit points is the horizontal distance from the extracted contact points to the center of the steel rail, the vertical distance is the vertical distance from the extracted contact points to the center of the steel rail, and finally assigning corresponding attribute information to the bridge limit points to sequentially and automatically extract all engineering limit data on the left side and the right side of the whole bridge section;

9) measuring the limit of the tunnel section: extracting in a full-automatic mode, segmenting and calculating the central point of each section, the direction vector of the advancing direction, the rolling angle and the mileage information according to the step length, the selected reference line and the point cloud trajectory line data, automatically extracting the left and right central points of the left and right rail surfaces according to the calculated parameters, constructing a rail surface coordinate system by using the extracted left and right central points of the rail surface, then segmenting point cloud data of the current rail of the section, projecting the point cloud data into the rail surface coordinate system, automatically extracting coordinates of contact points and inner side points of the cable groove at the position according to an algorithm, wherein the horizontal distance of the limit points of the tunnel section is the horizontal distance from the extracted inner side points of the cable groove to the center of the steel rail, the vertical distance is the vertical distance from the extracted contact points to the center of the steel rail, and finally assigning corresponding attribute information to the limit points of the tunnel, and automatically extracting all engineering limit data of the left side and the right side of the whole tunnel section in sequence;

10) measuring the limit of the in-station section: measuring by referring to the limit of a roadbed section, only the measured target points are different, measuring objects of the in-station section are canopy columns and contact net columns on two sides of an in-station track, and the specific step of the step 10) refers to the specific step of the step 7);

11) special point limit measurement: extracting by adopting a semi-automatic mode, capturing a special position in three-dimensional laser point cloud, comprising a signal machine and communication equipment, calculating a direction vector and mileage information of a vertical point and an advancing direction of a reference line, automatically extracting left and right central points of a left rail surface according to calculated parameters, constructing a rail surface coordinate system by using the extracted left and right central points of the rail surface, projecting a captured special position point coordinate into the rail surface coordinate system, assigning corresponding attribute information to the special point, and sequentially extracting all special point limit data of the left and right sides of the whole line, wherein the horizontal distance of a special point limit point is the horizontal distance from the captured special position point to the center of a steel rail, and the vertical distance is the vertical distance from the captured special position point coordinate to the center of the steel rail;

12) and (3) automatic outcome output: and automatically outputting the engineering limit measurement data of the railway bridge section, the roadbed section, the tunnel section, the in-station section and the special points according to a pre-designed format.

The specific process of the step 2) is as follows:

step 2.1, calculating POS data: in the tunnel and the station, GPS, DMI and DMR data are subjected to integrated navigation calculation by using autonomously developed dead reckoning software to obtain POS information, and other data including a roadbed and a bridge are subjected to calculation by using IE calculation software;

step 2.2, point cloud data fusion: and (3) fusing the three-dimensional laser point cloud scanned by the scanner with the POS data calculated in the step (2.1) to obtain three-dimensional laser point cloud data with absolute coordinates.

In step 4), performing extraction smoothing on the read track data of the three-dimensional laser scanning system, wherein parameters required to be used in the process include:

① extraction threshold value, the threshold value threshold range for extracting the track data is set as [0.0, 0.05 ];

② the threshold t range of the number of points near each vertex during smoothing is set to [20, 50 ];

③ smoothing distance threshold D range is set to [0.2, 0.8 ];

the specific process of the step 4) is as follows:

step 4.1, performing extraction processing on the track data of the three-dimensional laser scanning system, wherein the extraction algorithm is described in detail as follows:

① a straight line AB is connected between the first and the last points A, B of the multi-segment line, the straight line is a chord of the multi-segment line;

② obtaining the point C with the maximum distance from the straight line segment on the multi-segment line, and calculating the distance d between the point C and the AB;

③ comparing the distance with a predetermined threshold value threshold, if the distance is less than the threshold value, the straight line segment is used as the approximation of the multi-segment line, and the multi-segment line is taken out;

④ if the distance is larger than the threshold, dividing the multi-segment line into two segments of AC and BC by C, and processing the two segments of multi-segment line ① - ③ respectively;

after all the multi-segment lines are processed, sequentially connecting the multi-segment lines formed by the segmentation points, namely the approximate lines which are taken as the original multi-segment lines after the extraction processing;

step 4.2, the extracted point cloud track data P { P }₁，P₂，P₃...P_nCarry out smoothing processing, only use the plane coordinate of the tracing point, namely P_n(x_n，y_n) The smoothing algorithm is specifically as follows:

① beginning with the start of the polyline;

② finding the vertex P_c(x_c，y_c) Point data P of t/2 before and after index_tDetermining the distance D between each point and the previous point_tIn relation to a threshold value D, if D_tIf the number of the reserved points k is less than 3, searching the next vertex and continuing the step ②;

③ constructing rotation parameters with the farthest point and the nearest point, and rotating and translating all point coordinates according to the rotation parameters to obtain P_k(x_k，Y_k) The formula is as follows:

X_k＝dCos*(x_k-x₀)+dSin*(y_k-y₀) (3)

Y_k＝-dSin*(x_k-x₀)+dcos*(y_k-y₀) (4)

④ parabolic fits are made to all points, and the formula is y ═ a × x²+ B x + C, of formula:

⑤ the selected vertex coordinates are modified according to the step ④ fitting parameters:

y_c＝A*(x_c)²+B*x_c+C (6)

⑥ according to the formulas (1), (2) and (6), the vertex is reversely rotated to obtain a point P_d(x_d，y_d)：

x_d＝dCos*x_c-dSin*y_c+x₀(7)

y_d＝dSin*x_c+dCos*y_c+y₀(8)

And finally, processing all the vertexes according to steps ② - ⑥ to obtain the smoothed polyline.

The specific process of the step 7) is as follows:

7.1, loading three-dimensional laser point cloud data of field scanning engineering;

step 7.2, selecting the reference multi-segment line data of the certain road base segment segmented in the step 6) or self-defining the reference multi-segment line;

step 7.3, setting parameters, wherein the parameters required to be set in the process comprise:

① measuring with mobile scanning system or in point cloud data with reference to the horizontal distance between the multiple lines and the center of the left rail;

② measuring with mobile scanning system or in point cloud data with reference to the horizontal distance between the multiple lines and the center of the right rail;

③ referring to the vertical distance between the multiple lines and the center of the left rail or the right rail at the position of straightness, measuring by adopting a mobile scanning system or in point cloud data;

④ moving scanning system carrier type, including rail car type and trolley type;

⑤ reference multi-segment line type, there are two types of mobile scanning system track line and self-defined reference line;

⑥ line type, positive line, the current line scanned by the scanning system, the adjacent left line, the adjacent right line, the adjacent left line scanned by the mobile scanning system, the adjacent right line scanned by the mobile scanning system;

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;

step 7.4, capturing a central point P of the bottom of a contact net rod along the railway line in the three-dimensional laser point cloud data_c(x，y，z)；

Step 7.5 calculates its projected coordinates P on the reference polyline from the point data selected in step 7.4₀(X, Y, Z) and calculating P according to the accumulated plane distance from the projection coordinates to the reference multi-segment line and the initial mileage set by the reference multi-segment line_cThe mileage value;

step 7.6, extracting left and right rail surface points, which comprises the following steps:

① calculating point P₀(X, Y, Z) projection coordinate point P on the scanner lin file trajectory_tSearching a POS position closest to the projection coordinate point in the lin file, acquiring a Z value and a rolling angle Roll of the POS position, and assigning the Z value of the POS position to a point P₀；

② calculating distance point P along the direction of the reference polyline₀Point P on the reference polyline at a position of 0.5 m planar distance₁(X, Y, Z), calculating the point P with reference to the step₁Z coordinate of (a);

③ calculating point P₀To P₁Normal vector of (1), according to point P₀Direction vector NoCalculating the derailment surface point P from the parameters of model, Roll angle Roll and set in step 7.3_L1，P_R1；

④ calculating distance point P along the direction of the reference polyline₀Point P on the reference polyline at the position of 0.5 m₃(X, Y, Z), calculating the rail plane coordinate P according to the steps of ① - ③_L2，P_R2；

7.7, constructing a rail surface coordinate system according to the rail surface point P extracted in the step 7.6_L1，P_R1And a track point P_L2，P_R2Constructing a rail surface coordinate system, which comprises the following specific steps:

① calculating the track point P_L1、P_R1Central point P of_c1(x_c1，y_c1，z_c1) And a track point P_L2、P_R2Central point P of_c2(x_c2，y_c2，z_c2)；

② calculating point P_c1To P_c2Direction vector N (x)_n，y_n，z_n)；

③ A rail plane coordinate system is constructed from the calculated Roll angle values in steps ①, ② and step 7.6, the rail plane coordinate system including a 3 × 3 rotation matrix M1 and a 3 × 1 shift matrix M2, which are specified by the following equations:

the offset matrix M1 is formulated as:

the calculation steps of the rotation matrix M2 are as follows:

respectively calculating the rotation angles R around the X, Y and Z axes_x，R_y，R_z：

R_z＝tan^-1(y_n/x_n) (12)

T＝sin R_x*sin R_y(13)

R＝cos R_x*sin R_y(14)

Step 7.8, constructing a bounding box according to the parameters ①②③⑧ set in the step 7.3, cutting to obtain point clouds near a contact network in the bounding box, converting all point cloud coordinates into the coordinate system constructed in the step 7.7, obtaining point cloud data coordinates under a new coordinate system, and projecting all point cloud coordinates to a YOZ plane;

7.9, filtering the point cloud, namely filtering noise points of the point cloud data near the contact network obtained in the step 7.8 by adopting a distance threshold filtering method and a mean square error filtering method, so as to conveniently eliminate the influence of the noise points on the automatic extraction of contact points;

step 7.10 obtaining contact points: if the coordinate y ∈ [ -0.01, 0.01]If nearby point cloud data exists, point cloud data in the range are obtained, point coordinates of the point cloud data are sorted according to Z coordinates, and the lowest point Z value is taken as the vertical distance of the engineering limit; if the coordinate y ∈ [ -0.01, 0.01]If no point cloud data exists in the range, taking y E [ -2.5, 2.5 [)]Point cloud P within range_i(x_i，y_i，z_i) The number of point cloud points is n, a straight line is fitted, and a straight line parameter A, B, C is calculated, wherein the formula is as follows:

A＝(∑x_i*y_i*n-∑x_i*∑y_i)/(∑(x_i)²*n-∑x_i*∑x_i) (16)

C＝(∑(x_i)²*∑y_i-∑x_i*y_i*∑x_i)/(∑(x_i)²*n-∑x_i*∑x_i) (17)

B＝-1.0 (18)

and acquiring a Z-axis direction value according to the y-0.0, and taking an absolute value as a vertical distance of an engineering limit, wherein the formula is as follows:

Z＝C

step 7.11 obtaining coordinates P of the contact net rod from step 7.4_c(x, y, z) is projected into the rail surface coordinate system constructed in the step 7.7, and the x coordinate value is the horizontal distance of the engineering limit;

step 7.12 combining the values calculated in steps 7.4, 7.5, 7.10 and 7.11 are the coordinate point position, mileage information, vertical distance and horizontal distance of the engineering limit;

step 7.13, inputting attribute data, wherein the attribute data comprises parameters such as ground feature types, line types, names, directions, line bases, linear attributes and the like except the four attribute data in the step 7.12;

step 7.14, extracting all engineering limit data of one side of the selected railway line according to steps 7.4-7.13 of the flow chart in sequence;

step 7.15 extracts all engineering clearance data on the other side of the railway line according to steps 7.2-7.14.

The specific process of the step 8) is as follows:

step 8.1, loading three-dimensional laser point cloud data of field scanning engineering;

step 8.2 selecting the reference multi-segment line data of the certain road base segment segmented in the step 6);

step 8.3, setting parameters, wherein the parameters required to be set in the process comprise:

① reference horizontal distance of multiple lines from left rail center, measurement D is performed by using mobile scanning system or in point cloud data_L；

② reference horizontal distance of multiple lines from right rail center, measurement D is performed by using mobile scanning system or in point cloud data_R；

③ referring to the vertical distance H between the multi-line and the center of the left or right rail at the position of the straight line segment, measuring by using a mobile scanning system or in point cloud data;

⑥ line type, positive line, the current line scanned by the scanning system, the adjacent left line scanned along the mobile scanning system, and the adjacent right line, the adjacent right line scanned along the mobile scanning system;

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;

⑨ blocking and smashing the wall to automatically extract the step length;

⑩ start calculating mileage and end calculating mileage;

the direction of the ballast blocking wall is as follows: along the direction of the reference multi-section line, the ballast retaining wall is arranged on the selected reference line;

and the distance D between the ballast retaining wall and the reference multi-section line is as follows: actual measurement is needed in point cloud data;

section thickness T: the carrier is set according to actual conditions, and the carrier sets a range T epsilon [1.0, 1.5 ] for a mobile scanning system of the trolley]In meters;

step 8.4, projecting the selected reference multi-segment line on an XOY plane, dividing the projected two-dimensional multi-segment line according to the set step value, and acquiring all section center point coordinates P_i(x_i，y_i，z_i) i belongs to [0, n), wherein n is the number of the division points;

step 8.5 according to the coordinates P of the center points of all the sections calculated in step 8.4_i(x_i，y_i，z_i) i belongs to [0, n), and the calculation is started from the starting point;

step 8.6 calculate the segmentation point P_i(x_i，y_i，z_i) Referring to step 7.5;

8.7, extracting left and right track surface points, and referring to the step 7.6;

step 8.8, constructing a rail surface coordinate system which is specifically described as an offset matrix M1 and a rotation matrix M2, referring to step 7.7;

step 8.9, point cloud near the overhead line system is obtained, the coordinates of the point cloud are projected into the rail surface coordinate system constructed in the step 8.8, and the step 7.8 is referred;

step 8.10, filtering the point cloud, and referring to step 7.9;

step 8.11, acquiring a contact net point, acquiring the vertical distance of the engineering limit, and referring to step 7.10;

step 8.12 according to the coordinate P of the center point of the current section_i(x_i，y_i，z_i) And the next section center point coordinate P_i+1(x_i+1，y_i+1，z_i+1) To construct a custom coordinate system, specifically described as an offset matrix M3 and a rotation matrix M4;

step 8.13, acquiring the specified point cloud data according to the set parameters, wherein the specific steps are as follows:

①, constructing a bounding box according to the vertical distance H between the reference multi-segment line and the center of the left rail or the center of the right rail, the direction of the ballast blocking wall, the distance D between the ballast blocking wall and the reference multi-segment line and the section thickness T at the parameter straight-line segment position set in the step 7.3:

if the ballast retaining wall is on the left side, the bounding box is described as:

x∈[-D-0.3，-D+0.1]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+0.5]

if the ballast retaining wall is on the right side, the bounding box is described as:

x∈[[D-0.1，D+0.3]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+0.5]

② converting the bounding box constructed in step ① into point cloud coordinate system coordinates according to the matrix constructed in step 8.12;

③, cutting out point cloud data in a specified range according to the bounding box, and converting the acquired point cloud data into the custom coordinate system constructed in the step 8.12;

8.14, filtering and denoising the point cloud, wherein the specific operation steps are as follows:

①, firstly, filtering out point cloud outlier scattered noise points by using an outlier filtering method, and then filtering out point cloud data which are fragmented and sparse according to a mean square error filtering method;

② calculating the maximum and minimum values of the point cloud data in Y-axis direction, and dividing the point cloud into grids according to Y-axis direction and distance of 0.1 m, and calculating from the initial grid;

③ point cloud data in the designated grid is obtained, the point cloud data is sorted from small to large according to the Z coordinate of the point cloud data, and the Z-axis direction median value Z is obtained from 20-80% range of point cloud index_cFiltering out z e (z)_c+0.01, + ∞);

④ obtaining the point cloud data filtered in the step, sorting the point cloud data from small to large according to the X coordinate of the point cloud data, and obtaining the median X of the point cloud data in the X direction_cAnd a minimum value;

⑤ calculating according to the directions of the ballast walls, if the ballast walls are on the left side of the reference multi-segment line, sequentially processing all point cloud data P_n(x_n，y_n，z_n) Calculating, and recording an index value n if the X-direction value of the point cloud point coordinate meets the following two conditions;

|x_n-x_n+1|≥0.01

x_n≤x_m

if the ballast retaining wall is on the left side of the reference multi-segment line, sequentially calculating all point cloud data, and if the X-direction value of the point cloud point coordinates meets the following two conditions, recording an index value n;

|x_n-x_n+1|≥0.01

x_n≥x_m

filtering out all point cloud data in the range of 0-n of the point cloud index;

⑥ go through all point cloud data P in turn_t(x_t，y_t，z_t) Filtering out satisfying | x_t-x_m|∈[0.193, + ∞) point cloud data;

⑦, continuously filtering the point cloud data in each grid according to steps ③ - ⑥, wherein the rest point cloud data are the filtered point cloud data;

and 8.15, searching and acquiring the position of the ballast retaining wall, wherein the specific operation steps are as follows:

① calculating the maximum and minimum values of the point cloud data in Y-axis direction, and dividing the point cloud into grids according to Y-axis direction and distance of 0.1 m, and calculating from the initial grid;

② obtaining point cloud data in the appointed mesh, if no point cloud data exists in the mesh, continuing to calculate the next mesh according to step ②, otherwise, proceeding the next step;

③ sorting the point cloud data according to the X coordinate from small to large, and taking the maximum value and the minimum value X of the point cloud point coordinate in the X direction_max，x_minIf | x is satisfied_max-x_minIf < 0.17, continue to calculate the next grid according to step ②, otherwise calculate the threshold, calculate threshold D_tThe calculation is carried out according to the direction of the ballast retaining wall:

if the ballast retaining wall is on the left side of the reference multi-segment line, the distance threshold is as follows:

D_t＝x_min+4.0/5.0*|x_max-x_min|

if the ballast retaining wall is arranged on the right side of the reference multi-section line, the distance threshold is as follows:

D_t＝x_min+1.0/5.0*|x_max-x_min|

④ sorting all point cloud data coordinates according to the Z direction of the point cloud coordinates to obtain the maximum value and the minimum value Z of the point cloud coordinates in the Z direction_max，z_minAnd z-value minimum point coordinate is P_m(x_m，y_m，z_m) If no point cloud data exists, calculating the next grid according to step ②, otherwise, carrying out the next step;

⑤ if z_max-z_minIf < 0.01, continue to calculate the next grid according to step ②, otherwise according toCalculating the coordinates of the limit points according to the direction of the ballast retaining wall:

if the ballast retaining wall is on the left side of the reference multi-section line, if x is met_m＞D_tThen limit point P_t(x_t，y_t，z_t) The coordinates are:

x_t＝x_m

y_t＝0.0

z_t＝(z_max+z_min)/2.0

if the ballast retaining wall is on the right side of the reference multi-section line, if x is met_m＜D_tThen limit point P_t(x_t，y_t，z_t) The coordinates are:

x_t＝x_m

y_t＝0.0

z_t＝(z_max+z_min)/2.0

⑥ calculating all in-grid limit points according to steps ② - ⑤, and finally selecting the limit point calculated by the grid closest to y-0 as the limit point at the mileage, wherein | x_tIf is, the horizontal distance of the limit point of the mileage;

step 8.16, converting the ballast retaining wall coordinates obtained in the step 8.15 into coordinates in a point cloud coordinate system according to the matrix constructed in the step 8.12, and converting the converted coordinates into a rail surface coordinate center constructed in the step 8.8, wherein the coordinate X direction value is the horizontal distance of the engineering limit;

step 8.17 combining the values calculated in steps 8.6, 8.11 and 8.16 to obtain the coordinate point position, mileage information, vertical distance and horizontal distance of the engineering limit;

step 8.18 extracts all engineering limit data of the side according to steps 8.6-8.17 of the flow chart in sequence;

step 8.19 extracts all the engineering limit data of the other side according to steps 8.2-8.17 of the flow chart in sequence;

and 8.20, inputting attribute data, wherein the attribute data comprises the attributes of the ground feature type, the line type, the name, the direction, the line foundation and the line shape except the four attribute data in the step 8.17.

Step 9) the concrete operation steps of measuring the tunnel section limit are as follows:

step 9.1, loading three-dimensional laser point cloud data of field scanning engineering;

step 9.2 selecting the reference multi-segment line data of the certain road base segment segmented in the step 6);

step 9.3, setting parameters, wherein the parameters required to be set in the process comprise:

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;

⑨ cable slot automatic extraction step length;

⑩ start calculating mileage and end calculating mileage;

direction of cable trough: along the direction of the reference multi-segment line, the cable groove is arranged on the selected reference line;

distance D of the cable groove from the reference multi-segment line: actual measurement is needed in point cloud data;

section thickness T: the carrier is set according to actual conditions, and the carrier sets a range T epsilon [0.04, 0.06 ] for a mobile scanning system of the trolley]In meters;

step 9.4, projecting the selected reference multi-segment line on an XOY plane, segmenting the projected two-dimensional multi-segment line according to the set step value, and acquiring all section center point coordinates P_i(x_i，y_i，z_i) i belongs to [0, n), wherein n is the number of the division points;

step 9.5 according to all section center point coordinates P calculated in step 9.4_i(x_i，y_i，z_i) i belongs to [0, n), and the calculation is started from the starting point;

step 9.6 calculate the segmentation point P_i(x_i，y_i，z_i) Referring to step 7.5;

9.7, extracting left and right track surface points, and referring to the step 7.6;

step 9.8, constructing a rail surface coordinate system which is specifically described as an offset matrix M1 and a rotation matrix M2, referring to step 7.7;

9.9, acquiring point cloud near the overhead line system, projecting the point cloud coordinates into the rail surface coordinate system constructed in the step 8.8, and referring to the step 7.8;

9.10, filtering the point cloud, and referring to the step 7.9;

step 9.11, acquiring contact points, acquiring the vertical distance of the engineering limit, and referring to step 7.10;

9.12, constructing a custom coordinate system, and referring to the step 8.12;

step 9.13, acquiring the specified point cloud data according to the set parameters, wherein the specific steps are as follows:

①, according to the vertical distance H from the reference multi-segment line to the center of the left rail or the right rail, the direction of the cable groove, the distance D from the cable groove to the reference multi-segment line and the section thickness T at the parameter straight-line segment position set in the step 9.3, constructing a bounding box:

if the cable trough is left, the bounding box is described as:

x∈[-D-0.5，-D+0.5]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+1.0]

if the cable trough is the right side, the bounding box is described as:

x∈[D-0.5，D+0.5]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+1.0]

② converting the bounding box constructed in step ① into point cloud coordinate system coordinates according to the matrix constructed in step 9.12;

③, cutting out point cloud data in a specified range according to the bounding box, and converting the acquired point cloud data into the custom coordinate system constructed in the step 9.13;

9.13, filtering and denoising the point cloud, wherein the specific operation steps are as follows:

① filtering out scattered noise points by clustering;

② Point cloud P_o(x_o，y_o，z_o) The data Z coordinates are sorted from small to large to obtain the maximum value and the minimum value Z in the Z direction of the point cloud coordinates_max，z_minCalculating the filtering value T ═ z_max0.14, calculating all point cloud coordinates in a traversal mode, and if x is satisfied_oIf the point index value is more than T, recording the point index value n, and filtering out all point cloud point coordinates within the range of index 0-n;

step 9.14, searching and acquiring the position of the cable groove, wherein the cable groove is understood to be composed of a transverse section line and a longitudinal section line, the position of the cable groove is the intersection point of the transverse section line and the longitudinal section line, and the specific operation steps are as follows:

① obtaining the maximum and minimum values X in the X direction_max，x_minThe point cloud is in the X-axis direction according to N_t0.003 m distance meshGrid, setting initial height threshold H₀-10000.0, calculated from the starting grid;

② obtaining point cloud data in the appointed mesh, sorting the data of the initial mesh according to Z direction to obtain the maximum value and the minimum value Z in Z direction of point cloud coordinate_max，Z_minIf the point cloud data does not exist in the grid, the next grid is calculated according to the step ②, otherwise, the next step is carried out;

③ if the point cloud data in the grid satisfies | Z |_max-Z_min|≥H₀Then record its grid index value G₀And recording the height threshold as H₀＝|Z_max-Z_minMaximum value Z of Z value_m＝Z_max；

④ calculating all grids to get the final grid index value G according to steps ② - ③₀Distance threshold value H₀And Z maximum value Z_m；

⑤ calculating to obtain point cloud data on longitudinal section line, and traversing all point cloud data P_i(x_i，y_i，z_i) Satisfy x_i∈[x_min+G₀*N_t-N_t，x_min+G₀*N_t+N_t]The point cloud data in the range is point cloud data on a longitudinal section line;

⑥ calculating to obtain point cloud data on cross section line, and traversing all point cloud data P_i(x_i，y_i，z_i) Satisfy the following requirements

x_i∈[x_min+G₀*N_t-N_t-0.05，x_min+G₀*N_t+N_t+0.05]

z_i＞(Z_max-0.01)

⑦ obtaining parameters A of two straight lines by fitting the vertical section lines and fitting the horizontal section lines according to the formulas (16), (17) and (18)_v，B_v，C_vAnd A_h，B_h，C_h；

⑧ calculating the intersection point P of the horizontal section line and the vertical section line_c(x_c，y_c，z_c) The position coordinates of the cable groove are obtained;

step 9.15, converting the cable duct coordinates obtained in the step 9.14 into point cloud coordinate system coordinates according to the matrix constructed in the step 9.12, and converting the converted coordinates into the rail surface coordinate center constructed in the step 9.8, wherein the coordinate X direction value is the horizontal distance of the engineering limit;

step 9.16 combining the values calculated in steps 9.6, 9.11 and 9.15 to obtain the coordinate point position, mileage information, vertical distance and horizontal distance of the engineering limit;

step 9.17, extracting all engineering limit data of the side according to steps 9.6-9.16 of the flow chart in sequence;

step 9.18, extracting all engineering limit data on the other side according to steps 9.2-9.16 of the flow chart in sequence;

and 9.19, inputting attribute data, wherein the attribute data comprises the attributes of the ground feature type, the line type, the name, the direction, the line foundation and the line shape except the four attribute data in the step 9.16.

The specific steps of step 11) are as follows:

step 11.1, loading three-dimensional laser point cloud data of field scanning engineering;

step 11.2, selecting the reference multi-segment line data of the certain road base segment segmented in the step 6) or self-defining the reference multi-segment line;

step 11.3, setting parameters, wherein the parameters required to be set in the process comprise:

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;

step 11.4 capturing special point positions P along the railway line in the three-dimensional laser point cloud data_c(x，y，z)；

Step 11.5 calculates its projected coordinates P on the reference polyline from the point data selected in step 11.4₀(X, Y, Z) and calculating P according to the accumulated plane distance from the projection coordinates to the reference multi-segment line and the initial mileage set by the reference multi-segment line_cThe mileage value;

11.6, extracting left and right rail surface points, wherein the step refers to 7.6;

step 11.7, constructing a rail surface coordinate system, wherein the specific steps refer to 7.7;

step 11.8 obtaining coordinates P of the contact net rod from step 11.4_c(x, y, z) is converted into the rail surface coordinate system constructed in the step 11.7, and the converted coordinate is P_c(X, Y, Z) with a | X | value being the horizontal distance of the engineering clearance and a | Y | value being the vertical distance of the engineering clearance; the special points are classified into medium types, and only horizontal distances, only vertical distances, horizontal distances and vertical distances exist;

step 11.9 combining the values calculated in steps 11.4 and 11.8 to obtain the coordinate point position, mileage information, vertical distance and horizontal distance of the engineering limit;

step 11.10, inputting attribute data, wherein the attribute data comprises the attributes of the ground feature type, the line type, the name, the direction, the line foundation and the line shape except the four attribute data in the step 11.9;

step 11.11, extracting all engineering limit data of one side of the selected railway line according to steps 11.4-11.10 of the flow chart in sequence;

step 11.12 extracts all engineering clearance data on the other side of the railway line according to steps 11.2-11.11.

The invention has the following advantages:

the technical scheme based on the invention can realize the following technical functions:

1) acquiring field data: the RMMS high-precision vehicle-mounted mobile measurement system collects point cloud data and navigation data along the railway.

2) And resolving fused point cloud data.

3) And (3) engineering import loading display: and (3) loading and displaying the fused data in the step 2 in the second step by adopting developed post-processing software.

4) Constructing a reference multi-segment line: and reading the track data of the three-dimensional laser scanning system, and performing extraction smoothing on the track data to generate three-dimensional multi-segment line data. And the reference multi-segment line is used for extracting important reference information of the limit points automatically or semi-automatically.

5) Dividing the reference multi-segment line: according to the starting and ending point coordinates of various railway types (roadbed sections, bridge sections, tunnel sections and in-station sections) provided by field collection, making a vertical line perpendicular to the reference multi-segment line, and cutting the multi-segment line according to the vertical point.

6) Editing the reference multi-segment mileage: and judging the mileage direction to be a big mileage or a small mileage according to the running direction of the mobile vehicle-mounted system, setting the starting mileage or the ending mileage of the multi-segment line according to the field record, and automatically calculating the starting mileage, the ending mileage and the two-dimensional length of the multi-segment line.

7) Measuring the limit of the roadbed section: the method comprises the steps of extracting in a semi-automatic mode, capturing a bottom center point of a contact net rod in three-dimensional laser point cloud, calculating a direction vector and mileage information of a vertical point and a forward direction of a reference line, automatically extracting left and right center points of a left rail surface according to calculated parameters, constructing a rail surface coordinate system according to the extracted left and right center points of the rail surface, then automatically extracting contact net points, finally projecting the captured bottom center point into the rail surface coordinate system, assigning corresponding attribute information to the road base limit points, and sequentially extracting all engineering limit data of the left and right sides of the whole road base section, wherein the horizontal distance of the road base limit points is the horizontal distance from the bottom center of the contact net rod to the center of a steel rail, the vertical distance is the vertical distance from the lowest point of a contact net corresponding to the rail surface, and the.

8) Bridge segment clearance measurement: extracting in a full-automatic mode, segmenting and calculating the central point of each section, the direction vector of the advancing direction, the rolling angle and the mileage information according to the step length, the selected reference line and the point cloud trajectory line data, automatically extracting the left and right central points of the left and right rail surfaces according to the calculated parameters, constructing a rail surface coordinate system by using the extracted left and right central points of the rail surface, then segmenting point cloud data of the current rail of the section, projecting the point cloud data into the rail surface coordinate system, and automatically extracting coordinates of the contact points and inner side points of the ballast wall at the position according to an algorithm, wherein the horizontal distance of the bridge section limit points is the horizontal distance from the extracted contact points to the center of the steel rail, the vertical distance is the vertical distance from the extracted contact points to the surface of the railway rail, and finally, corresponding attribute information is assigned to the bridge limit points, so that all engineering limit data on the left side and the right side of the whole bridge section can be automatically extracted in sequence.

9) Measuring the limit of the tunnel section: extracting in a full-automatic mode, segmenting and calculating the central point of each section, the direction vector of the advancing direction, the rolling angle and the mileage information according to the step length, the selected reference line and the point cloud trajectory line data, automatically extracting the left and right central points of the left and right rail surfaces according to the calculated parameters, constructing a rail surface coordinate system by using the extracted left and right central points of the rail surface, then segmenting point cloud data of the current rail of the section, projecting the point cloud data into the rail surface coordinate system, and automatically extracting coordinates of the contact points and the inner side points of the cable groove at the position according to an algorithm, wherein the horizontal distance of the limit points of the tunnel section is the horizontal distance from the extracted inner side points of the cable groove to the center of the steel rail, the vertical distance is the vertical distance from the extracted contact points to the rail surface, and finally, corresponding attribute information is assigned to the limit points of the tunnel, so that all engineering limit data on the left side and the right side of the whole tunnel section can be automatically extracted in sequence.

10) Measuring the limit of the in-station section: and measuring by referring to the limit of the roadbed section, only the measured target points are different, and measuring objects of the in-station section are canopy columns and contact net columns on two sides of the in-station track.

11) Special point limit measurement: the method comprises the steps of extracting in a semi-automatic mode, capturing special positions (such as a signal machine, communication equipment and the like) in three-dimensional laser point cloud, calculating direction vectors and mileage information of a vertical point and an advancing direction of a reference line, automatically extracting left and right central points of a left rail surface according to calculated parameters, constructing a rail surface coordinate system according to the extracted left and right central points of the rail surface, converting coordinates of captured special position points into the rail surface coordinate system, assigning corresponding attribute information to the special points, and sequentially extracting engineering limit data of all the special points on the left and right sides of the whole line, wherein the horizontal distance of the special point limit points is the horizontal distance from the captured special position points to the center of a steel rail, the vertical distance is the vertical distance from the captured special position point coordinates to the center of the steel rail.

Drawings

FIG. 1 is a flow chart of a high-precision vehicle-mounted laser mobile measurement system-based railway engineering clearance detection method.

Fig. 2 is a flow chart of the roadbed section clearance measurement in step 7) of the railway engineering clearance detection method based on the high-precision vehicle-mounted laser mobile measurement system.

FIG. 3 is a flow chart of bridge segment clearance measurement in step 8) of the flow of the railway engineering clearance detection method based on the high-precision vehicle-mounted laser mobile measurement system.

FIG. 4 is a flow chart of tunnel segment clearance measurement in step 9) of the flow of the railway engineering clearance detection method based on the high-precision vehicle-mounted laser mobile measurement system.

FIG. 5 is a flow chart of special point clearance measurement in step 11) of the railway engineering clearance detection method based on the high-precision vehicle-mounted laser mobile measurement system.

Detailed Description

The present invention will be described in detail with reference to specific embodiments.

The invention relates to a railway engineering clearance detection method based on a high-precision vehicle-mounted laser mobile measurement system, which comprises the following steps of:

1) acquiring field data: the RMMS high-precision vehicle-mounted mobile measurement system collects point cloud data and navigation data along the railway. The collected data comprises a GPS base station data collected by an erection base station, and three-dimensional laser point cloud data, DMI data (encoder data), DMR data (inertial navigation data) and GPS data collected by an RMMS high-precision vehicle-mounted mobile measurement system.

2) Solving fused point cloud data

In the step 2), dead reckoning is required to be performed according to the principle of integrated navigation, POS track data is calculated, and then the point cloud data and the POS track data are fused to obtain point cloud data with absolute coordinates.

The specific process of step 2) is as follows:

step 2.1, calculating POS data: in the tunnel and the station, GPS, DMI and DMR data are combined and navigated by using self-developed dead reckoning software to be resolved into POS information, and other data (roadbed and bridge) are resolved into POS data by using IE resolving software.

3) And (3) engineering import loading display: and loading and displaying the fused data in the step 2) by adopting development post-processing software.

Performing extraction smoothing on the read track data of the three-dimensional laser scanning system, wherein the parameters required to be used in the process are as follows:

③ smoothing distance threshold D range is set to [0.2, 0.8 ].

The specific process of the step 4) is as follows:

④ if the distance is greater than the threshold, dividing the multi-segment line into two segments, AC and BC, by C and processing the two segments ① - ③ separately.

And after all the multi-segment lines are processed, sequentially connecting the multi-segment lines formed by the segmentation points, namely the approximate lines which can be used as the original multi-segment lines after the extraction processing.

① beginning with the start of the polyline;

② finding the vertex P_c(x_c，y_c) Point data P of t/2 before and after index_tDetermining the distance D between each point and the previous point_tIn relation to a threshold value D, if D_tIf the number of the reserved points k is less than 3, the next vertex is searched for and the step ② is continued.

③ is constructed with the farthest point and the nearest pointRotating the parameters, and rotationally translating all the point coordinates according to the rotating parameters to obtain P_k(X_k，Y_k) The formula is as follows:

X_k＝dCos*(x_k-x₀)+dSin*(y_k-y₀) (3)

Y_k＝-dSin*(x_k-x₀)+dcos*(y_k-y₀) (4)

y_c＝A*(x_c)²+B*x_c+C (6)

x_d＝dCos*x_c-dSin*y_c+x₀(7)

y_d＝dSin*x_c+dCos*y_c+y₀(8)

⑦ the final loop is completed for all vertices by processing steps ② - ⑥.

7) Measuring the limit of the roadbed section: the method comprises the steps of extracting in a semi-automatic mode, capturing a bottom center point of a contact net rod in three-dimensional laser point cloud, calculating a direction vector and mileage information of a vertical point and a forward direction of a reference line, automatically extracting left and right center points of a left rail surface according to calculated parameters, constructing a rail surface coordinate system according to the extracted left and right center points of the rail surface, then automatically extracting contact net points, finally projecting the captured bottom center point into the rail surface coordinate system, assigning corresponding attribute information to road foundation limit points, and sequentially extracting all engineering limit data of the left and right sides of the whole road foundation section, wherein the horizontal distance of the road foundation limit points is the horizontal distance from the bottom center of the contact net rod to the center of a steel rail, the vertical distance is the vertical distance from the lowest point of a contact net corresponding to the contact net rod to the.

The specific process of step 7) is as follows with reference to the description flow chart 2:

and 7.1, loading three-dimensional laser point cloud data of the field scanning project.

And 7.2, selecting the reference multi-segment line data of the certain road base segment segmented in the step 6) or self-defining the reference multi-segment line.

① refer to the horizontal distance of the multiple lines from the center of the left rail, and the measurement can be performed by using a mobile scanning system or in point cloud data.

② refer to the horizontal distance of the multiple lines from the center of the right rail, which can be measured by a mobile scanning system or in point cloud data.

③ the position of straightness refers to the vertical distance between the multiple lines and the center of the left rail or the right rail, and the measurement can be carried out by adopting a mobile scanning system or in point cloud data.

④ moving scanning system carrier types, rail car and trolley.

⑤ refer to multiple segment types there are two types of moving scanning system trajectories and custom reference lines.

⑥ line types, positive line (current line scanned by the scanning system), adjacent left line (adjacent left line scanned along the mobile scanning system for the current line), and adjacent right line (adjacent right line scanned along the mobile scanning system for the current line).

⑦ rail types there are two standard types 60 and 50.

⑧ catenary distance is measured in the point cloud data from the reference polyline height.

Step 7.4, capturing a central point P of the bottom of a contact net rod along the railway line in the three-dimensional laser point cloud data_c(x，y，z)。

Step 7.5 calculates its projected coordinates P on the reference polyline from the point data selected in step 7.4₀(X, Y, Z) and calculating P according to the accumulated plane distance from the projection coordinates to the reference multi-segment line and the initial mileage set by the reference multi-segment line_cThe mileage value.

① calculating point P₀(X, Y, Z) projection coordinate point P on the scanner lin file trajectory_tSearching a POS position closest to the projection coordinate point in the lin file, acquiring a Z value and a rolling angle Roll of the POS position, and assigning the Z value of the POS position to a point P₀。

② calculating distance point P along the direction of the reference polyline₀Point P on the reference polyline at a position of 0.5 m planar distance₁(X, Y, Z), calculating the point P with reference to the step₁Z coordinate of (a).

③ calculating point P₀To P₁Normal vector of (1), according to point P₀Calculating the derailing surface point P by the direction vector Normal, the Roll angle Roll and the parameters set in the step 7.3_L1，P_R1。

④ calculating distance point P along the direction of the reference polyline₀Reference at 0.5 meter positionPoint P on a multi-segment line₃(X, Y, Z), calculating the rail plane coordinate P according to the steps of ① - ③_L2，P_R2。

① calculating the track point P_L1、P_R1Central point P of_c1(x_c1，y_c1，z_c1) And a track point P_L2、P_R2Central point P of_c2(x_c2，Y_c2，z_c2)。

② calculating point P_c1To P_c2Direction vector N (x)_n，y_n，z_n)。

the offset matrix M1 is formulated as:

the calculation steps of the rotation matrix M2 are as follows:

R_z＝tan^-1(y_n/x_n) (12)

T＝sin R_x*sin R_y(13)

R＝cos R_x*sin R_y(14)

And 7.8, constructing a bounding box according to the parameters ①②③⑧ set in the step 7.3, cutting to obtain point clouds near a contact network in the bounding box, converting all point cloud coordinates into the coordinate system constructed in the step 7.7, obtaining point cloud data coordinates under a new coordinate system, and projecting all point cloud coordinates to a YOZ plane.

And 7.9, filtering the point cloud, namely filtering noise points of the point cloud data near the contact network obtained in the step 7.8 by adopting a distance threshold filtering method and a mean square error filtering method, so that the influence of the noise points on the automatic extraction of the contact network points is conveniently eliminated.

A＝(∑x_i*y_i*n-∑x_i*∑y_i)/(∑(x_i)²*n-∑x_i*∑x_i) (16)

C＝(∑(x_i)²*∑y_i-∑x_i*y_i*∑x_i)/(∑(x_i)²*n-∑x_i*∑x_i) (17)

B＝-1.0 (18)

Z＝C

step 7.11 obtaining coordinates P of the contact net rod from step 7.4_c(x, y, z) is projected into the rail plane coordinate system constructed in step 7.7 with the x coordinate value being the horizontal distance of the engineering limit.

Step 7.12 combines the values calculated in steps 7.4, 7.5, 7.10 and 7.11 to form the coordinate point position, mileage information, vertical distance and horizontal distance of the engineering limit.

Step 7.13 enters the attribute data. The attribute data includes parameters such as the type of the ground feature, the type of the line, the name, the direction, the line base, the linear attribute, and the like, in addition to the four attribute data in step 7.12.

Step 7.14 extracts all the engineering limit data of one side of the selected railway line in turn according to the steps 7.4-7.13 of the flow chart.

8) Bridge segment clearance measurement: extracting in a full-automatic mode, segmenting and calculating the central point of each section, the direction vector of the advancing direction, the rolling angle and the mileage information according to the step length, the selected reference line and the point cloud trajectory line data, automatically extracting the left and right central points of the left and right rail surfaces according to the calculated parameters, constructing a rail surface coordinate system by using the extracted left and right central points of the rail surface, then segmenting point cloud data of the current rail of the section, projecting the point cloud data into the rail surface coordinate system, and automatically extracting coordinates of the contact points and the ballast wall stopping points at the position according to an algorithm, wherein the horizontal distance of the bridge section limit points is the horizontal distance from the extracted contact points to the center of the steel rail, the vertical distance is the vertical distance from the extracted contact points to the center of the steel rail, and finally, corresponding attribute information is assigned to the bridge limit points, so that all engineering limit data on the left side and the right side of the whole bridge section can be automatically extracted in sequence.

The specific process of step 8) is as follows with reference to the description flow chart 3:

and 8.1, loading three-dimensional laser point cloud data of the field scanning engineering.

Step 8.2 selects reference multi-segment line data of a certain base segment segmented in step 6).

① reference horizontal distance between multiple lines and left rail center, and measurement D can be performed in point cloud data by using mobile scanning system_L。

② reference horizontal distance between multiple lines and right rail center, and measurement D can be performed in point cloud data by using mobile scanning system_R。

③ the vertical distance H between the multiple lines and the center of the left or right track is referred to at the position of the straight line segment.

④ moving scanning system carrier types, rail car and trolley.

⑦ rail types there are two standard types 60 and 50.

⑨ wall-breaking automatic extraction of step length.

⑩ start calculating mileage and end calculating mileage.

The direction of the ballast blocking wall is as follows: and along the direction of the reference multi-section line, the ballast retaining wall is arranged on the selected reference line.

And the distance D between the ballast retaining wall and the reference multi-section line is as follows: it needs to be measured in point cloud data.

Section thickness T: the carrier is set according to actual conditions, and the carrier sets a range T epsilon [1.0, 1.5 ] for a mobile scanning system of the trolley]In meters.

Step (ii) of8.4 projecting the selected reference multi-segment line on the XOY plane, dividing the projected two-dimensional multi-segment line according to the set step value, and acquiring all section center point coordinates P_i(x_i，y_i，z_i) i ∈ [0, n), where n is the number of segmentation points.

Step 8.5 according to the coordinates P of the center points of all the sections calculated in step 8.4_i(x_i，y_i，z_i) i ∈ [0, n)), starting from the starting point.

Step 8.6 calculate the segmentation point P_i(x_i，y_i，z_i) Refer to step 7.5.

And 8.7, extracting left and right track surface points, and referring to the step 7.6.

Step 8.8 constructs a rail-plane coordinate system, which is specifically described as an offset matrix M1 and a rotation matrix M2,

refer to step 7.7.

And 8.9, acquiring point cloud near the overhead line system, and projecting the point cloud coordinates to the rail surface coordinate system constructed in the step 8.8. See step 7.8.

And 8.10, filtering the point cloud, and referring to the step 7.9.

And 8.11, acquiring the contact points and acquiring the vertical distance of the engineering limit at the contact points. Refer to step 7.10.

Step 8.12 according to the coordinate P of the center point of the current section_i(x_i，y_i，z_i) And the next section center point coordinate P_i+1(x_i+1，y_i+1，z_i+1) To construct a custom coordinate system, specifically described as an offset matrix M3 and a rotation matrix M4.

And 8.13, acquiring the specified point cloud data according to the set parameters. The method comprises the following specific steps:

x∈[-D-0.3，-D+0.1]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+0.5]

x∈[D-0.1，D+0.3]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+0.5]

② the bounding box constructed in step ① is converted to point cloud coordinate system coordinates according to the matrix constructed in step 8.12.

③, cutting out the point cloud data in the designated range according to the bounding box, and converting the acquired point cloud data into the custom coordinate system constructed in step 8.12.

① filtering out the scattered noise points by the outlier filtering method, and filtering out the point cloud data with sparse pieces by the mean square error filtering method.

② calculating the maximum and minimum values of the point cloud data in Y-axis direction, and meshing the point cloud according to Y-axis direction and distance of 0.1 m.

③ point cloud data in the designated grid is obtained, the point cloud data is sorted from small to large according to the Z coordinate of the point cloud data, and the Z-axis direction median value Z is obtained from 20-80% range of point cloud index_cFiltering out z e (z)_c+0.01, + ∞).

④ obtaining the point cloud data filtered in the step, sorting the point cloud data from small to large according to the X coordinate of the point cloud data, and obtaining the median X of the point cloud data in the X direction_cAnd a minimum value x_m。

⑤ calculating according to the directions of the ballast walls, if the ballast walls are on the left side of the reference multi-segment line, sequentially processing all point cloud data P_n(x_n，y_n，z_n) And calculating, and recording an index value n if the X-direction value of the point cloud point coordinate meets the following two conditions.

|x_n-x_n+1|≥0.01

x_n≤x_m

And if the ballast retaining wall is positioned on the left side of the reference multi-segment line, sequentially calculating all point cloud data, and if the X-direction value of the point cloud point coordinates meets the following two conditions, recording an index value n.

[x_n-x_n+1|≥0.01

x_n≥x_m

And filtering out all point cloud data in the range of the point cloud index 0-n.

⑥ go through all point cloud data P in turn_t(x_t，y_t，z_t) Filtering out satisfying | x_t-x_m| ∈ [0.193, + ∞) point cloud data.

⑦ continue to filter the point cloud data within each grid in accordance with steps ③ - ⑥, with the remaining point cloud data being filtered point cloud data.

① calculating the maximum and minimum values of the point cloud data in Y-axis direction, and meshing the point cloud according to Y-axis direction and distance of 0.1 m.

②, point cloud data in the appointed mesh is obtained, if no point cloud data exists in the mesh, the next mesh is calculated according to step ②, otherwise, the next step is carried out.

D_t＝x_min+4.0/5.0*|x_max-x_min|

D_t＝x_min+1.0/5.0*|x_max-x_min|

④ sorting all point cloud data coordinates according to the Z direction of the point cloud coordinates to obtain the maximum value and the minimum value Z of the point cloud coordinates in the Z direction_max，z_minAnd z-value minimum point coordinate is P_m(x_m，y_m，z_m) And point cloud data within 0.01 centimeter around the minimum value of the Z coordinate is obtained, if no point cloud data exists, the next grid is calculated according to the step ②, and if not, the next step is carried out.

⑤ if z_max-z_minIf the absolute value is less than 0.01, the next grid is calculated according to the step ②, otherwise, the coordinates of the limit points are calculated according to the direction of the ballast retaining wall:

if the ballast retaining wall is on the left side of the reference multi-section line, if x is met_m＞D_tThen limit point P_t(x_t，y_t，z_t) Coordinate is x_t＝x_m

y_t＝0.0

z_t＝(z_max+z_min)/2.0

If the ballast retaining wall is on the right side of the reference multi-section line, if x is met_m＜D_tThen limit point P_t(x_t，y_t，z_t) Coordinate is x_t＝x_m

y_t＝0.0

z_t＝(z_max+z_min)/2.0

⑥ calculating all in-grid limit points according to steps ② - ⑤, and finally selecting the limit point calculated by the grid closest to y-0 as the limit point at the mileage, wherein | x_tAnd | is the horizontal distance of the limit point at the mileage.

And 8.16, converting the ballast retaining wall coordinates obtained in the step 8.15 into coordinates in a point cloud coordinate system according to the matrix constructed in the step 8.12, and converting the converted coordinates into a rail surface coordinate center constructed in the step 8.8, wherein the coordinate X direction value is the horizontal distance of the engineering limit.

Step 8.17 combines the values calculated in steps 8.6, 8.11, 8.16 to be the coordinate point position, mileage information, vertical distance, horizontal distance of the engineering limit.

Step 8.18 extracts all engineering limit data for that side in turn according to the flow chart steps 8.6-8.17.

Step 8.19 extracts all engineering limit data on the other side in turn according to steps 8.2-8.17 of the flow chart.

Step 8.20 enters attribute data. The attribute data includes parameters such as ground feature type, line type, name, direction, line base, line shape attribute, and the like, in addition to the four attribute data in step 8.17.

9) Measuring the limit of the tunnel section: extracting in a full-automatic mode, segmenting and calculating the central point of each section, the direction vector of the advancing direction, the rolling angle and the mileage information according to the step length, the selected reference line and the point cloud trajectory line data, automatically extracting the left and right central points of the left and right rail surfaces according to the calculated parameters, constructing a rail surface coordinate system by using the extracted left and right central points of the rail surface, then segmenting point cloud data of the current rail of the section, projecting the point cloud data into the rail surface coordinate system, and automatically extracting coordinates of the contact points and the inner side points of the cable groove at the position according to an algorithm, wherein the horizontal distance of the limit points of the tunnel section is the horizontal distance from the extracted inner side points of the cable groove to the center of the steel rail, the vertical distance is the vertical distance from the extracted contact points to the center of the steel rail, and finally, corresponding attribute information is assigned to the limit points of the tunnel, so that all engineering limit data on the left side and the right side of the whole tunnel section can be automatically extracted in sequence.

In combination with the flowchart of the specification and fig. 4, step 9) the specific operation steps of the tunnel segment boundary measurement are as follows:

and 9.1, loading three-dimensional laser point cloud data of the field scanning project.

Step 9.2 selects reference multi-segment line data of a certain base segment segmented in step 6).

① left rail with multiple reference line distancesHorizontal distance of center: the measurement D can be carried out by adopting a mobile scanning system and also in point cloud data_L。

④ moving scanning system carrier types, rail car and trolley.

⑦ rail types there are two standard types 60 and 50.

⑨ the cable slot automatically extracts the step size.

⑩ start calculating mileage and end calculating mileage.

Direction of cable trough: the cable trough is on which side of the selected reference line, in the direction of the reference polyline.

Distance D of the cable groove from the reference multi-segment line: it needs to be measured in point cloud data.

Section thickness T: set according to actual conditions, and the carrier is the mobile scanning of a trolleySystem setting range T epsilon [0.04, 0.06 ∈ ]]In meters.

Step 9.4, projecting the selected reference multi-segment line on an XOY plane, segmenting the projected two-dimensional multi-segment line according to the set step value, and acquiring all section center point coordinates P_i(x_i，y_i，z_i) i ∈ [0, n), where n is the number of segmentation points.

Step 9.5 according to all section center point coordinates P calculated in step 9.4_i(x_i，y_i，z_i) i ∈ [0, n)), starting from the starting point.

Step 9.6 calculate the segmentation point P_i(x_i，y_i，z_i) Refer to step 7.5.

And 9.7, extracting left and right track surface points, and referring to the step 7.6.

Step 9.8 constructs a rail-plane coordinate system, which is specifically described as an offset matrix M1 and a rotation matrix M2, in reference to step 7.7.

And 9.9, acquiring point cloud near the overhead line system, and projecting the point cloud coordinates to the rail surface coordinate system constructed in the step 8.8. See step 7.8.

And 9.10, filtering the point cloud, and referring to the step 7.9.

And 9.11, acquiring the contact points and acquiring the vertical distance of the engineering limit at the contact points. Refer to step 7.10.

And 9.12, constructing a custom coordinate system, and referring to the step 8.12.

And 9.13, acquiring the specified point cloud data according to the set parameters. The method comprises the following specific steps:

if the cable trough is left, the bounding box is described as:

x∈[-D-0.5，-D+0.5]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+1.0]

if the cable trough is the right side, the bounding box is described as:

x∈[D-0.5，D+0.5]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+1.0]

② the bounding box constructed in step ① is converted to point cloud coordinate system coordinates according to the matrix constructed in step 9.12.

③, cutting out the point cloud data in the designated range according to the bounding box, and converting the acquired point cloud data into the custom coordinate system constructed in step 9.13.

9.13 point cloud filtering and denoising, wherein the specific operation steps are as follows:

③ the method firstly filters the scattered noise points of point cloud outliers by using an outlier filtering method.

④ Point cloud P_o(x_o，y_o，z_o) The data Z coordinates are sorted from small to large to obtain the maximum value and the minimum value Z in the Z direction of the point cloud coordinates_max，z_minCalculating the filtering value T ═ z_max0.14, calculating all point cloud coordinates in a traversal mode, and if x is satisfied_oIf the point coordinate is more than T, recording the point index value n, and filtering out all point cloud point coordinates within the range of the index 0-n.

① obtaining the maximum and minimum values X in the X direction_max，x_minThe point cloud is in the X-axis direction according to N_tDividing the grid into 0.003 m distance, and setting an initial height threshold H₀-10000.0, calculated from the starting grid.

② obtaining point cloud data in the appointed mesh, sorting the data of the initial mesh according to Z direction to obtain the maximum value and the minimum value Z in Z direction of point cloud coordinate_max，Z_minIf no point cloud data exists in the grid, the next grid is calculated according to the step ②, otherwise, the next step is carried out.

③ if the point cloud data in the grid satisfies | Z |_max-Z_min|≥H₀Then record its grid index value G₀And recording the height threshold as H₀＝|Z_max-Z_minMaximum value Z of Z value_m＝Z_max。

④ calculating all grids to get the final grid index value G according to steps ② - ③₀Distance threshold value H₀And Z maximum value Z_m。

⑤ calculating to obtain point cloud data on longitudinal section line, and traversing all point cloud data P_i(x_i，y_i，z_i) Satisfy x_i∈[x_min+G₀*N_t-N_t，x_min+G₀*N_t+N_t]The point cloud data in the range is the point cloud data on the vertical section line.

x_i∈[x_min+G₀*N_t-N_t-0.05，x_min+G₀*N_t+N_t+0.05]

z_i＞(Z_max-0.01)

⑦ obtaining parameters A of two straight lines by fitting the vertical section lines and fitting the horizontal section lines according to the formulas (16), (17) and (18)_v，B_v，C_vAnd A_h，B_h，C_h。

⑧ calculating the intersection point P of the horizontal section line and the vertical section line_c(x_c，y_c，z_c) I.e. the position coordinates of the cable tray.

And 9.15, converting the cable duct coordinates obtained in the step 9.14 into point cloud coordinate system coordinates according to the matrix constructed in the step 9.12, and converting the converted coordinates into the rail surface coordinate center constructed in the step 9.8, wherein the coordinate X direction value is the horizontal distance of the engineering limit.

Step 9.16 combines the values calculated in steps 9.6, 9.11, and 9.15 to be the coordinate point position, mileage information, vertical distance, and horizontal distance of the engineering limit.

Step 9.17 extracts all engineering limit data for that side in turn according to the flow chart steps 9.6-9.16.

Step 9.18 extracts all engineering limit data on the other side in turn according to steps 9.2-9.16 of the flow chart.

Step 9.19 enters the attribute data. The attribute data includes parameters such as ground feature type, line type, name, direction, line base, line shape attribute, and the like, in addition to the four attribute data in step 9.16.

10) Measuring the limit of the in-station section: and (3) measuring by referring to the limit of the roadbed section, only the measured target points are different, the objects of measuring the in-station section are canopy columns and contact net columns on two sides of the in-station track, and the specific step of the step 10) refers to the specific step of the step 7).

11) Special point limit measurement: the method comprises the steps of extracting in a semi-automatic mode, capturing special positions (such as a signal machine, communication equipment and the like) in three-dimensional laser point cloud, calculating direction vectors and mileage information of a vertical point and an advancing direction of a reference line, automatically extracting left and right central points of a left rail surface according to calculated parameters, constructing a rail surface coordinate system according to the extracted left and right central points of the rail surface, projecting coordinates of the captured special position points into the rail surface coordinate system, assigning corresponding attribute information to the special points, and sequentially extracting limit data of all the special points on the left and right sides of the whole line, wherein the horizontal distance of the limit points of the special points is the horizontal distance from the captured special position points to the center of a steel rail, the vertical distance is the vertical distance from the captured special position points to the center of the steel rail.

The specific steps of step 11) are shown as follows in conjunction with the instruction flow chart 5:

and 11.1, loading three-dimensional laser point cloud data of the field scanning project.

Step 11.2 selects the reference multi-segment line data or the self-defined reference multi-segment line of the certain road base segment segmented in the step 6).

④ moving scanning system carrier types, rail car and trolley.

⑦ rail types there are two standard types 60 and 50.

Step 11.4 capturing special point positions P along the railway line in the three-dimensional laser point cloud data_c(x，y，z)。

Step 11.5 calculates its projected coordinates P on the reference polyline from the point data selected in step 11.4₀(X, Y, Z) and calculating P according to the accumulated plane distance from the projection coordinates to the reference multi-segment line and the initial mileage set by the reference multi-segment line_cThe mileage value.

Step 11.6 extracts the left and right track surface points, which is specifically the step referred to 7.6.

Step 11.7 constructs a rail plane coordinate system, the specific steps of which refer to 7.7.

Step 11.8 obtaining coordinates P of the contact net rod from step 11.4_c(x, y, z) is converted into the rail surface coordinate system constructed in the step 11.7, and the converted coordinate is P_c(X, Y, Z) having a value of | X |, isThe Y value of the horizontal distance of the engineering limit is the vertical distance of the engineering limit. The special points are classified into medium types, and only horizontal distance, only vertical distance, horizontal distance and vertical distance are available.

Step 11.9 combines the values calculated in steps 11.4 and 11.8 to obtain the coordinate point position, mileage information, vertical distance and horizontal distance of the engineering limit.

Step 11.10 enters the attribute data. The attribute data includes parameters such as ground feature type, line type, name, direction, line base, line shape attribute, and the like, in addition to the four attribute data in step 11.9.

Step 11.11 extracts all engineering limit data of one side of the selected railway line in turn according to the steps 11.4-11.10 of the flow chart.

The railway engineering clearance data are measured according to the high-precision three-dimensional laser point cloud, wherein the steps of constructing the reference multi-segment line, measuring the roadbed segment clearance, measuring the tunnel segment clearance, measuring the bridge segment clearance, measuring the tunnel segment clearance, measuring the in-station segment clearance, measuring the special point clearance and automatically outputting results are firstly proposed, and the key problems of automation and rapid output of measurement results in the engineering clearance measuring process of a new technology of a high-precision vehicle-mounted mobile measuring system are solved.

The invention is not limited to the examples, and any equivalent changes to the technical solution of the invention by a person skilled in the art after reading the description of the invention are covered by the claims of the invention.

Claims

1. A railway engineering clearance detection method based on a high-precision vehicle-mounted laser mobile measurement system is characterized by comprising the following steps of:

the method is realized by the following steps:

2. The high-precision vehicle-mounted laser mobile measurement system-based railway engineering clearance detection method according to claim 1, characterized in that:

the specific process of the step 2) is as follows:

3. The high-precision vehicle-mounted laser mobile measurement system-based railway engineering clearance detection method according to claim 2, characterized in that:

③ smoothing distance threshold D range is set to [0.2, 0.8 ];

the specific process of the step 4) is as follows:

① beginning with the start of the polyline;

X_k＝dCos*(x_k-x₀)+dSin*(y_k-y₀) (3)

Y_k＝-dSin*(x_k-x₀）+dcos*(y_k-y₀) (4)

y_c＝A*(x_c)²+B*xc+C (6)

x_d＝dCos*x_c-dSin*y_c+x₀(7)

y_d＝dSin*x_c+dCos*y_c+y₀(8)

4. The high-precision vehicle-mounted laser mobile measurement system-based railway engineering clearance detection method according to claim 3, characterized in that:

the specific process of the step 7) is as follows:

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;

Step 7.5 selection according to step 7.4The point data of (a) calculates its projection coordinates P on the reference polyline₀(X, Y, Z) and calculating P according to the accumulated plane distance from the projection coordinates to the reference multi-segment line and the initial mileage set by the reference multi-segment line_cThe mileage value;

③ calculating point P₀To P₁Normal vector of (1), according to point P₀Calculating the derailing surface point P by the direction vector Normal, the Roll angle Roll and the parameters set in the step 7.3_L1,P_R1；

④ calculating distance point P along the direction of the reference polyline₀Point P on the reference polyline at the position of 0.5 m₃(X, Y, Z), calculating the rail plane coordinate P according to the steps of ① - ③_L2,P_R2；

7.7, constructing a rail surface coordinate system according to the rail surface point P extracted in the step 7.6_L1,P_R1And a track point P_L2,P_R2Constructing a rail surface coordinate system, which comprises the following specific steps:

② calculating point P_c1To P_c2Direction vector N (x)_n，y_n，z_n)；

the offset matrix M1 is formulated as:

the calculation steps of the rotation matrix M2 are as follows:

R_z＝tan^-1(y_n/x_n) (12)

T＝sinR_x*sinR_y(13)

R＝cosR_x*sinR_y(14)

step 7.10 obtaining contact points: if the coordinate y ∈ [ -0.01, 0.01]If nearby point cloud data exists, point cloud data in the range is acquiredSorting the point coordinates according to Z coordinates, and taking the lowest point Z value as the vertical distance of the engineering limit; if the coordinate y ∈ [ -0.01, 0.01]If no point cloud data exists in the range, taking y E [ -2.5, 2.5 [)]Point cloud P within range_i(x_i，y_i，z_i) The number of point cloud points is n, a straight line is fitted, and a straight line parameter A, B, C is calculated, wherein the formula is as follows:

A＝(∑x_i*y_i*n-∑x_i*∑y_i)/(∑(x_i)²*n-∑x_i*∑x_i) (16)

C＝(∑(x_i)²*∑y_i-∑x_i*y_i*∑x_i)/(∑(x_i)²*n-∑x_i*∑x_i) (17)

B＝-1.0 (18)

Z＝C

5. The high-precision vehicle-mounted laser mobile measurement system-based railway engineering clearance detection method according to claim 4, characterized in that:

the specific process of the step 8) is as follows:

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;

⑨ blocking and smashing the wall to automatically extract the step length;

⑩ start calculating mileage and end calculating mileage;

step 8.10, filtering the point cloud, and referring to step 7.9;

x∈[-D-0.3，-D+0.1]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+0.5]

x∈[D-0.1，D+0.3]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+0.5]

④ obtaining the point cloud data filtered in the step, sorting the point cloud data from small to large according to the X coordinate of the point cloud data, and obtaining the X direction of the point cloud dataMedian value x of_cAnd a minimum value;

|x_n-x_n+1|≥0.01

x_n≤x_m

|x_n-x_n+1|≥0.01

x_n≥x_m

⑥ go through all point cloud data P in turn_t(x_t，y_t，z_t) Filtering out satisfying | x_t-x_mPoint cloud data for | ∈ [0.193, + ∞);

③ sorting the point cloud data according to the X coordinate from small to large, and taking the maximum value and the minimum value X of the point cloud point coordinate in the X direction_max，x_minIf | x is satisfied_max-x_minIf | is less than 0.17, then proceed to compute the next grid according to step ②Otherwise, calculating a threshold value D_tThe calculation is carried out according to the direction of the ballast retaining wall:

D_t＝x_min+4.0/5.0*|x_max-x_min|

D_t＝x_min+1.0/5.0*|x_max-x_min|

x_t＝x_m

y_t＝0.0

z_t＝(z_max+z_min)/2.0

x_t＝x_m

y_t＝0.0

z_t＝(z_max+z_min)/2.0

⑥ calculating all in-grid bounding points according to steps ② - ⑤, and finally selecting y as the distanceThe limit point calculated by the grid with 0 nearest is taken as the limit point at the mileage where | x_tIf is, the horizontal distance of the limit point of the mileage;

6. The high-precision vehicle-mounted laser mobile measurement system-based railway engineering clearance detection method according to claim 5, characterized in that:

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;

⑨ cable slot automatic extraction step length;

⑩ start calculating mileage and end calculating mileage;

step 9.4, projecting the selected reference multi-segment line on an XOY plane, segmenting the projected two-dimensional multi-segment line according to the set step value, and acquiring all section center point coordinates P_i(x_i，y_i，z_i) i ∈ [0, n), whereinn is the number of the division points;

9.10, filtering the point cloud, and referring to the step 7.9;

9.12, constructing a custom coordinate system, and referring to the step 8.12;

if the cable trough is left, the bounding box is described as:

x∈[-D-0.5，-D+0.5]

y∈[-T/2.0，T/2.0]

z∈[-H-0.5，-H+1.0]

if the cable trough is the right side, the bounding box is described as:

x∈[D-0.5，D+0.5]

y∈[-T/2.0，T/2.0]

z is an element of [ H-0.5, -H +1.0]

① filtering out scattered noise points by clustering;

① obtaining the maximum and minimum values X in the X direction_max，x_minThe point cloud is in the X-axis direction according to N_tDividing the grid into 0.003 m distance, and setting an initial height threshold H₀-10000.0, calculated from the starting grid;

④ calculating all grids to get the final grid index value G according to steps ② - ③₀Distance ofFrom threshold H₀And Z maximum value Z_m；

x_i∈[x_min+G₀*N_t-N_t-0.05，x_min+G₀*N_t+N_t+0.05]

z_i＞(Z_max-0.01)

7. The high-precision vehicle-mounted laser mobile measurement system-based railway engineering clearance detection method according to claim 6, characterized in that:

the specific steps of step 11) are as follows:

⑦ the types of steel rails are 60 rails and 50 rails in two types;

⑧ height of catenary from reference polyline measured in point cloud data;