CN116128834A - Rail transit platform limit rapid detection method based on three-dimensional laser scanning - Google Patents

Rail transit platform limit rapid detection method based on three-dimensional laser scanning Download PDF

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CN116128834A
CN116128834A CN202310049016.0A CN202310049016A CN116128834A CN 116128834 A CN116128834 A CN 116128834A CN 202310049016 A CN202310049016 A CN 202310049016A CN 116128834 A CN116128834 A CN 116128834A
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station
point cloud
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王宏涛
王变利
许磊
巩健
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Jiaozuo Basic Geographic Information Center
Henan University of Technology
China Railway Design Corp
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Henan University of Technology
China Railway Design Corp
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Abstract

The invention discloses a rapid detection method for rail transit platform limit based on three-dimensional laser scanning, which comprises the following steps: 1) Acquiring three-dimensional laser point cloud data of a track, a station platform nearby and surrounding buildings by using self-moving three-dimensional laser scanning equipment; 2) Judging and extracting a steel rail three-dimensional laser point cloud; 3) Constructing a left steel rail three-dimensional model and a right steel rail three-dimensional model; 4) Calculating three-dimensional coordinates of a line center line; 5) Fitting the plane of the top surface and the inner side surface of the station platform; 6) Extracting an edge line of an outer eave of a station platform; 7) Calculating the horizontal distance and the elevation difference between the outer eave of the station platform and the center of the track; 8) And (5) taking the end point of the outer eave line segment of the station as the initial top point of the next section, repeating S5-S7, and completing the comprehensive detection of the station platform limit. The method has the advantages of high detection efficiency, high precision and reliable detection result.

Description

Rail transit platform limit rapid detection method based on three-dimensional laser scanning
Technical Field
The invention relates to the field of rail transit limit detection, in particular to a rapid detection method for rail transit platform limit based on three-dimensional laser scanning.
Background
The limit refers to a contour dimension line which is defined for the rolling stock and the buildings and equipment close to the line and is not allowed to be exceeded in order to ensure the safety of the rolling stock running on the rail transit line and prevent the rolling stock from striking the buildings and equipment close to the line. The accurate detection and safety pre-warning of the limit are effective means for ensuring the running safety of the train, and have important theoretical significance and application value for improving the rail traffic operation capability. The station boundary refers to the horizontal distance and the height difference between the station platform outer eave and the line center. For the limitation of the line section (roadbed, bridge and tunnel), the platform limitation not only needs to ensure the safety distance for the rolling stock to stop, but also needs to improve the comfort level of passengers on and off the train. Therefore, the station platform limit is more demanding in the design stage and the detection precision is more accurate.
Due to construction technology and management communication problems in the construction period, the limit accident is frequently happened to the outer eave wall of the platform, the problem that the distance between the side surface of the platform wall and the center of a line does not meet the limit requirement and the top surface of the platform wall is higher than the limit requirement is found for many times, and even the safety accident that the high platform cap of the station scratches two sections of test vehicles in the joint debugging and testing period occurs. The occurrence of individual tragic accidents is not accidental, but is caused by the lack of efficient and comprehensive technical means for detecting the limit of the platform. The traditional measuring method of the platform limit is mainly contact type measurement, such as a cross section method, a comprehensive section method and a track method, and belongs to contact type detection. The limit detection based on the section shooting method belongs to non-contact measurement, and the method improves the automation degree of the limit detection, but has larger interference of light rays and higher requirement on the working environment. Along with the development of laser measurement technology, the three-dimensional laser scanning technology is used as a brand new non-contact measurement method, has the advantages of quick, high-precision and all-weather measurement, and is suitable for measuring operation lines in skylight time. However, the three-dimensional laser scanning technology only can rapidly acquire all three-dimensional point clouds of a station platform, and still needs to research laser point cloud data processing algorithms by combining station platform characteristics and limit detection contents, develop corresponding data processing software, and realize rapid detection of rail transit station platform limit based on the three-dimensional scanning technology so as to meet the requirements of rapid development of rail transit safety transportation.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a rapid detection method for the rail transit platform limit based on three-dimensional laser scanning, which can rapidly and accurately detect the station platform limit.
For this purpose, the invention adopts the following technical scheme:
a three-dimensional laser scanning-based rapid detection method for rail transit platform limit comprises the following steps:
s1, acquiring a station three-dimensional laser point cloud: acquiring three-dimensional laser point cloud data of a track, a station platform nearby and surrounding buildings by using self-moving three-dimensional laser scanning equipment;
s2, judging and extracting the three-dimensional laser point cloud of the steel rail: the method comprises the steps of utilizing a relatively stable geometric position relation of rail point cloud coordinates in a self-moving three-dimensional laser scanning equipment coordinate system to automatically identify and extract rail point cloud;
s3, constructing a left steel rail and right steel rail three-dimensional model: s2, identifying the extracted steel rail point cloud, and carrying out three-dimensional reconstruction of the steel rail model by adopting a point cloud fitting mode in combination with the geometric dimension of the steel rail model;
s4, calculating three-dimensional coordinates of a line center line: the three-dimensional coordinates of the central line of the line track are automatically calculated based on priori knowledge of the line design parameters by using the left and right steel rail three-dimensional models obtained in the step S3;
s5, plane fitting of the top surface and the inner side surface of the station platform: based on laser point cloud data obtained by platform scanning, automatically dividing laser point clouds on the top surface and the inner side surface of a station platform, and fitting out the inner side of an outer eave of the station platform and a top plane;
s6, extracting an edge line of an outer eave of a station platform: according to the fitted station platform outer eave inner side and top plane in the S5, the plane intersection algorithm in the formula (5) is utilized to realize the extraction and calculation of the station outer eave edge line, the geometric expression mode of the space plane is (P, N), wherein P is the three-dimensional coordinate of a certain point on the plane, and N is the normal vector of the plane;
Figure SMS_1
wherein:
(P 1 ，N 1 ): is the geometric expression of the plane inside the station platform;
(P 2 ，N 2 ): is the geometric expression of the top plane of the station platform;
N 3 : the normal vector of the edge line of the outer eave of the platform;
x: is the vertex on the outer cornice edge line of the platform;
s7, calculating the horizontal distance and the elevation difference value between the station platform outer eave and the track center: according to the three-dimensional coordinates of the line track center line and the top point of the station platform outer edge line, calculating the horizontal distance (L) between the station platform outer edge and the track center line by using the formula (1) i ) Difference from the elevation (H) i )；
S8, taking the ending end point of the outer eave edge line of the platform obtained in the step S6 as the initial vertex of the next section, repeating the steps S5-S7 until the complete detection of the platform limit in the range of the station is completed, and judging whether an intrusion condition exists or not according to the designed platform limit allowable value to form a detection report.
Wherein, step S5 comprises the following sub-steps:
s51, obtaining an initial value of a horizontal distance and an elevation difference value between an outer eave of a station platform and a track center: manually interacting and selecting one point P in platform external eave laser point cloud from station point cloud T Respectively selecting the center point P of the top of the left steel rail from the corresponding cross sections L And the center point P of the top of the right steel rail R Calculating an initial value of the track center from the outer eave of the platform by adopting a formula (1):
Figure SMS_2
L 0 ＝Vector2D(P T -(P L +P R )/2.0) (1)
wherein:
L 0 : initial value of horizontal distance between station platform outer eave and track center;
H 0 : initial value of elevation difference between station platform outer eave and track center;
Figure SMS_3
elevation value of laser point of outer eave of platform;
Figure SMS_4
elevation value of laser point at top of left rail;
Figure SMS_5
elevation value of laser point at right side rail top;
Vector2D(P T -(P L +P R )/2.0): the horizontal distance between the laser point of the outer eave of the platform and the center of the track;
s52, laser point cloud segmentation of the top surface and the inner side surface of the station platform: the width of the top surface of the station platform is set as delta S, the height of the side surface of the station platform is set as delta V, and the distance of the station platform along the mileage direction is set as delta D, and the steps are selected manually and interactivelyPlatform external eave vertex P T For the vertex of the cube, delta S, delta V and delta D are side lengths, delta is a threshold value of the side length, and a cube bounding box is constructed;
s53, determining whether the laser point cloud is within the cube bounding box: judging whether the station laser point cloud is in a cube or not by traversing the station laser point cloud, so that the laser point cloud of the outer eave of the station is segmented from all the station laser point clouds;
s54, plane fitting calculation of the top surface and the inner side surface of the station platform: and respectively fitting planes at the top and the inner side of the platform eave by using a plane fitting algorithm to obtain normal vectors and constants of the fitted planes, and calculating the residual error value of laser point cloud plane fitting.
In step S52, a cube bounding box is constructed according to formula (2):
Figure SMS_6
wherein:
BBox: a cube bounding box;
minx, miny, minz: the minimum value of the vertex coordinates of the cubic bounding box;
maxx, maxy, maxz: maximum value of vertex coordinates of the cubic bounding box;
P Tx 、P Ty 、P Tz : and manually selecting coordinate values of the laser point cloud of the outer eave of the platform in an interaction manner.
The formula for determining whether the laser point cloud is within the cube in step S53 is as follows:
Figure SMS_7
wherein:
pi: an ith laser spot;
Pi x 、Pi y 、Pi z : x, y, z coordinate values of the ith laser spot;
Segment Plateform 、Segment Other : the point clouds are respectively the outer eave point clouds of the platform and other point clouds except the outer eave point clouds of the platform;
BBox minx 、BBox miny 、BBox minz : respectively the minimum value of the vertex coordinates of the cube bounding box;
BBox maxx 、BBox maxy 、BBox maxz : the maximum values of the vertex coordinates of the cubic bounding box are respectively;
delta: the cube bounding box filters the threshold in meters.
In step S54, plane fitting is performed using formula (4):
N x *x+N y *y+N z *z+constVal＝0 (4)
wherein:
N x 、N y 、N z : fitting a normal vector of the plane;
ConstVal: fitting a constant value of the plane.
The invention has the following beneficial effects:
1. according to the detection method, a cubic bounding box segmentation algorithm is used, so that a small amount of effective laser point cloud data of the outer eave of the platform is rapidly segmented from mass point clouds scanned by the station, the data processing efficiency is remarkably improved, the station limit with the length of 450m is detected by using the detection method, and the automatic processing time of the data is only 2 minutes;
2. according to the invention, a plane fitting algorithm and a plane intersection straight line algorithm are adopted, so that the high-precision calculation of the horizontal distance and the elevation difference between the outer eave of the platform and the central line of the line is realized, the influence of noise point cloud can be effectively removed by the plane fitting algorithm, and the precision of a detection algorithm is improved;
3. according to the invention, the three-dimensional reconstruction of the steel rail and the outer eave of the platform is realized by utilizing the scanning laser point cloud through a point cloud fitting method, and then the center line of the steel rail and the outer eave line of the platform are extracted from a reconstruction model. The method does not directly adopt the center of the scanner to measure the coordinates of the outer eave of the platform, thereby avoiding the influence on the detection result caused by the shake of the scanner and ensuring the reliability of the detection result;
4. compared with the existing point-by-point measurement method, the detection method is quicker, more accurate and more comprehensive, is beneficial to expanding the application of the three-dimensional laser scanning technology in the field of rail transit limit detection, and improves the rapid detection level of rail transit.
Drawings
FIG. 1 is a flow chart of a detection method of the present invention;
FIG. 2 is laser point cloud data for a rail transit stop range;
FIG. 3 is a self-moving laser scanning system and its coordinate system;
FIG. 4 is a three-dimensional model of a rail constructed from a standard cross-sectional view of the rail;
FIG. 5 is a schematic illustration of calculating a line centerline from left and right rail models;
fig. 6 is a detailed dimensional view of passenger dedicated line railway building boundaries.
Detailed Description
The rapid detection method for the rail transit platform limit based on the three-dimensional laser scanning is described in detail below with reference to the accompanying drawings and the specific embodiments.
Examples
As shown in fig. 1, the method for rapidly detecting the rail transit platform limit based on three-dimensional laser scanning comprises the following steps:
s1, acquiring a three-dimensional laser point cloud of a station: and a self-moving three-dimensional laser scanning system is adopted to rapidly acquire three-dimensional laser point cloud data of a track, a nearby station platform and surrounding buildings, and the acquired laser point cloud data of the track traffic station are shown in fig. 2. The rail type used in the rail transit line is 60kg/m rail (60 rail), and the length of the detection platform is about 450 meters.
Referring to fig. 3, the self-moving three-dimensional laser scanning system integrates modules such as an odometer, a high-precision laser scanner, an inclinometer, a track gauge measuring system, a high-precision time synchronization module, a Programmable Logic Controller (PLC) and the like on a self-moving track trolley platform, can rapidly complete three-dimensional scanning measurement in a station, and has the characteristics of high efficiency, high precision, miniaturization, automation and multiple purposes. The self-moving three-dimensional laser scanning detection system automatically runs on a rail transit line, the speed setting range is 0-5 km/h, the measurement range in the vertical rail direction is 0.3-200 m, the measurement accuracy is better than 5mm, and 100 ten thousand laser points are acquired per second.
The laser scanner integrated by the self-moving laser scanning system is a 2D section and 360-degree circumference scanning mode, and the origin of coordinates of the scanning section is positioned at the center of the scanner. The forward driving direction along the scanner (namely, the line mileage direction) is set to be an X axis, the vertical ground direction is set to be a Z axis, the Y axis is respectively vertical to the X axis and the Z axis (namely, the horizontal direction is vertical to the line direction), and a right-hand coordinate system is established by using the XYZ axis. The mileage direction is the X coordinate value of the point cloud, the horizontal distance of the scanner is the Y coordinate value, and the vertical distance is the Z coordinate value, so as to obtain the three-dimensional laser point cloud data of the station range.
S2, judging and extracting the three-dimensional laser point cloud of the steel rail: and carrying out automatic identification and extraction of the rail point cloud by utilizing the relatively stable position relation of the rail point cloud coordinates in a self-moving laser scanning system coordinate system. In the embodiment, a height filtering and rectangular segmentation method is adopted to automatically extract the laser point cloud of the steel rail.
S3, constructing a left steel rail three-dimensional model and a right steel rail three-dimensional model according to a standard section diagram of a 60kg/m steel rail, wherein the model length is consistent with the length of a track line segment and is 1m, as shown in fig. 4. And (3) fitting and registering the standard steel rail model and the steel rail point cloud obtained in the step (S2) to reconstruct a line left-right steel rail three-dimensional model.
S4, calculating three-dimensional coordinates of a central line of the line track based on line design parameters by using the left and right steel rail three-dimensional models obtained in the S3, and obtaining information such as the distance of an actual track, the direction of the track and the like; according to the definition of the reference track, after the reference track is determined, the reference track is used as a basis, the standard track gauge (the standard track gauge defined in China is 1435 mm) is horizontally offset to another steel rail, track center line points are calculated in sections, the track center line points extracted in sections are sequentially connected to form a line center line, and finally the formed line center line is subjected to smoothing treatment to obtain a relatively smooth line center line, as shown in fig. 5.
S5, plane fitting of the top surface and the inner side surface of the station platform: and (5) according to the platform scanning, obtaining laser point cloud data, and fitting the plane of the top surface and the inner side surface of the station platform. The coordinates of the outer eave of the platform obtained in this step are segment extraction values, and the segment length can be set according to actual requirements, and in this embodiment, the segment length is set to be 1.0m (i.e. 1.0m is fitted along the line direction each time). The method comprises the following specific steps:
s51, obtaining an initial value of a horizontal distance and an elevation difference value between an outer eave of a station platform and a track center: the space position between the station platform outer eave and the rail center has a fixed design value, and the position relation has small-order continuous change due to construction errors or the position adjustment of the rail in the later operation process. The initial value calculation may be performed by the following method: selecting a point (P) from the station point cloud by manual interaction T ) Then respectively selecting the center point of the top of the left steel rail (left rail P L ) And the right rail top center point (right rail P) R ) And (3) calculating an initial value of the track center from the outer eave of the platform by adopting a formula (1).
Figure SMS_8
L 0 ＝Vector2D(P T -(P L +P R )/2.0) (1)
Wherein:
L 0 : initial value of horizontal distance between station platform outer eave and track center;
H 0 : initial value of elevation difference between station platform outer eave and track center;
Figure SMS_9
elevation value of laser point of outer eave of platform;
Figure SMS_10
elevation value of laser point at top of left rail;
Figure SMS_11
elevation value of laser point at right side rail top;
Vector2D(P T -(P L +P R )/2.0): the horizontal distance between the laser point of the outer eave of the platform and the centers of the left steel rail and the right steel rail.
The initial value of the horizontal distance and elevation difference between the outer eave of the station platform and the center of the track is generally selected from the scanning initial position of the station.
S52, laser point cloud segmentation of the top surface and the inner side surface of the station platform: the width of the station platform top surface is set to be delta S, the height of the station platform side surface is set to be delta V, and the distance between the station platform and the station platform along the mileage direction is set to be delta D. The step S51 is performed to select the apex P of the outer eave of the platform by manual interaction T For the cube vertices, Δs, Δv, and Δd are side lengths, δ is a threshold for side length, and a cube bounding box is constructed according to equation (2):
Figure SMS_12
wherein:
BBox: a cube bounding box;
minx, miny, minz: the minimum value of the vertex coordinates of the cubic bounding box;
maxx, maxy, maxz: maximum value of vertex coordinates of the cubic bounding box;
P Tx 、P Ty 、P Tz : and manually selecting coordinate values of the laser point cloud of the outer eave of the platform in an interaction manner.
In this embodiment, the width Δs of the top surface of the station is set to 0.5m, the Δv is set to 0.3m of the design height of the inner side surface of the station, and the distance Δd in the mileage direction is set to 0.5m, which is equal to the segment length in step S5.
S53, determining whether the laser point cloud is within the cube bounding box: and judging whether the station laser point cloud is in the cube by traversing the station laser point cloud, so that the laser point cloud of the outer eave of the station is separated from all the station laser point clouds. The method of determining whether the laser point cloud is within the cube is shown in equation (3).
Figure SMS_13
Wherein:
pi: an ith laser spot;
Pi x 、Pi y 、Pi z : x, y, z coordinate values of the ith laser spot;
Segment Plateform 、Segment Other : the outer eave point clouds and other point clouds of the platform are respectively;
BBox minx 、BBox miny 、BBox minz : respectively the minimum value of the vertex coordinates of the cube bounding box;
BBox maxx 、BBox maxy 、BBox maxz : the maximum values of the vertex coordinates of the cubic bounding box are respectively;
delta: the cube bounding box filters the threshold in meters.
In order to divide the laser point cloud to the outer eaves of all the platforms, the threshold δ in this embodiment is set to 0.03m.
S54, plane fitting calculation of the top surface and the inner side surface of the station platform: considering construction errors and deformation during operation, the top surface and the inner side surface of the platform cannot be planes with strict meanings, respectively fitting the top surface and the inner side surface of the outer eave of the platform by using a plane fitting algorithm to obtain normal vectors and constants of the fitting planes, and calculating distance residual errors from all laser point clouds to the fitting planes to judge the plane fitting precision and effect. The plane fitting formula is as follows:
N x *x+N y *y+N z *z+constVal＝0 (4)
wherein:
N x 、N y 、N z : fitting a normal vector of the plane;
ConstVal: fitting a constant value of the plane;
x, y and z are three-dimensional coordinates of the laser spot.
S6, extracting an edge line of an outer eave of a station platform: and (5) according to the fitted plane between the inner side of the station platform outer eave and the top in the step S54, utilizing a plane intersection algorithm in the formula (5) to realize the extraction and calculation of the edge line of the station outer eave. In the step S54, the formula (4) is a general algebraic expression of a spatial plane, and the other geometric expression of the spatial plane is (P, N), where P is a three-dimensional coordinate of a point on the plane, and N is a normal vector of the plane;
Figure SMS_14
wherein:
(P 1 ，N 1 ): is the geometric expression of the plane inside the station platform;
(P 2 ，N 2 ): is the geometric expression of the top plane of the station platform;
N 3 : the normal vector of the edge line of the outer eave of the platform;
x: is the apex on the outer cornice edge line of the platform.
In this embodiment, the length of the outer edge line of the platform is 0.5m, which is the same as the length Δd in step S52.
S7, calculating the horizontal distance and the elevation difference value between the station platform outer eave and the track center: according to the three-dimensional coordinates of the line track center line and the vertex of the station platform outer edge line, calculating the horizontal distance (L i ) Difference from the elevation (H) i )；
In this embodiment, the midpoint P of the outer edge line segment of the station is projected to the point P' on the center line of the track, and the horizontal distance (L) between the outer edge of the station and the center of the track is calculated according to formula (1) by using P and P i ) Difference in top elevation (H) i )。
S8, taking the ending end point of the outer eave edge line of the platform obtained in the step S6 as the initial end point of the next section, repeating the steps S5-S7 until the complete detection of the platform limit in the range of the station is completed, and judging whether an intrusion condition exists or not according to the designed platform limit allowable value as shown in fig. 6 to form a detection report.
The historical data of the limit detection can be built up into a database and plotted for horizontal distance (L i ) Difference from the top elevation (H i ) And (3) a change curve, namely, a station limiting change trend is found, and engineering improvement measures are adopted in advance when the change trend is obvious.
By using the method provided by the invention, only 2 minutes are needed for processing the laser point cloud data of the track traffic platform with the length of 450m, so that the detection efficiency is greatly improved.
And (3) experimental precision analysis:
two methods are adopted to carry out precision analysis on the limit measurement result: firstly, comparing the results of round-trip scanning detection by using the method, wherein the round-trip detection difference is smaller than 3mm; secondly, the method of the invention is verified by adopting a 'DJJ-8 limit laser detector' developed by Shandong national academy of sciences laser research institute Jinan blue dynamic laser technology Co. The DJJ-8 limit laser detector is widely used and accepted in domestic limit detection, and the measuring precision of the detector is +/-3 mm. Comparing the measurement result of the detection method with the detection result of the DJJ-8 limit laser detector, wherein the difference is smaller than 5mm, and the statistics of the comparison result are shown in the following table:
Figure SMS_15
from the above results, the measurement accuracy of the present invention meets the standard requirements of the current railway construction practical limit measurement and data format (TBT 3308-2013).

Claims (5)

1. A three-dimensional laser scanning-based rapid detection method for rail transit platform limit comprises the following steps:
s1, acquiring a station three-dimensional laser point cloud: acquiring three-dimensional laser point cloud data of a track, a station platform nearby and surrounding buildings by using self-moving three-dimensional laser scanning equipment;
s2, judging and extracting the three-dimensional laser point cloud of the steel rail: the method comprises the steps of utilizing a relatively stable geometric position relation of rail point cloud coordinates in a self-moving three-dimensional laser scanning equipment coordinate system to automatically identify and extract rail point cloud;
s3, constructing a left steel rail and right steel rail three-dimensional model: s2, identifying the extracted steel rail point cloud, and carrying out three-dimensional reconstruction of the steel rail model by adopting a point cloud fitting mode in combination with the geometric dimension of the steel rail model;
s4, calculating three-dimensional coordinates of a line center line: the three-dimensional coordinates of the central line of the line track are automatically calculated based on priori knowledge of the line design parameters by using the left and right steel rail three-dimensional models obtained in the step S3;
s5, plane fitting of the top surface and the inner side surface of the station platform: based on laser point cloud data obtained by platform scanning, automatically dividing laser point clouds on the top surface and the inner side surface of a station platform, and fitting out the inner side of an outer eave of the station platform and a top plane;
s6, extracting an edge line of an outer eave of a station platform: according to the fitted station platform outer eave inner side and top plane in the S5, the plane intersection algorithm in the formula (5) is utilized to realize the extraction and calculation of the station outer eave edge line, the geometric expression mode of the space plane is (P, N), wherein P is the three-dimensional coordinate of a certain point on the plane, and N is the normal vector of the plane;
Figure FDA0004056888320000011
wherein:
(P 1 ，N 1 ): is the geometric expression of the plane inside the station platform;
(P 2 ，N 2 ): is the geometric expression of the top plane of the station platform;
N 3 : the normal vector of the edge line of the outer eave of the platform;
x: is the vertex on the outer cornice edge line of the platform;
s7, calculating the horizontal distance and the elevation difference value between the station platform outer eave and the track center: according to the three-dimensional coordinates of the line track center line and the top point of the station platform outer edge line, calculating the horizontal distance (L) between the station platform outer edge and the track center line by using the formula (1) i ) Difference from the elevation (H) i )；
S8, taking the ending end point of the outer eave edge line of the platform obtained in the step S6 as the initial vertex of the next section, repeating the steps S5-S7 until the complete detection of the platform limit in the range of the station is completed, and judging whether an intrusion condition exists or not according to the designed platform limit allowable value to form a detection report.
2. The method for rapidly detecting a rail transit platform boundary based on three-dimensional laser scanning according to claim 1, wherein the step S5 comprises the following sub-steps:
s51, obtaining an initial value of a horizontal distance and an elevation difference value between an outer eave of a station platform and a track center: manually interacting and selecting one point P in platform external eave laser point cloud from station point cloud T Respectively selecting the center point P of the top of the left steel rail from the corresponding cross sections L And the center point P of the top of the right steel rail R Calculating an initial value of the track center from the outer eave of the platform by adopting a formula (1):
Figure FDA0004056888320000021
L 0 ＝Vector2D(P T -(P L +P R )/2.0) (1)
wherein:
L 0 : initial value of horizontal distance between station platform outer eave and track center;
H 0 : initial value of elevation difference between station platform outer eave and track center;
Figure FDA0004056888320000022
elevation value of laser point of outer eave of platform;
Figure FDA0004056888320000023
elevation value of laser point at top of left rail;
Figure FDA0004056888320000024
elevation value of laser point at right side rail top;
Vector2D(P T -(P L +P R )/2.0): horizontal distance between laser spot at outer edge of platform and center of trackSeparating;
s52, laser point cloud segmentation of the top surface and the inner side surface of the station platform: the width of the top surface of the station platform is set as delta S, the height of the side surface of the station platform is set as delta V, the distance of the station platform along the mileage direction is set as delta D, and the top point P of the outer eave of the platform is selected manually and interactively in the step S51 T For the vertex of the cube, delta S, delta V and delta D are side lengths, delta is a threshold value of the side length, and a cube bounding box is constructed;
s53, determining whether the laser point cloud is within the cube bounding box: judging whether the station laser point cloud is in a cube or not by traversing the station laser point cloud, so that the laser point cloud of the outer eave of the station is segmented from all the station laser point clouds;
s54, plane fitting calculation of the top surface and the inner side surface of the station platform: and respectively fitting planes at the top and the inner side of the platform eave by using a plane fitting algorithm to obtain normal vectors and constants of the fitted planes, and calculating the residual error value of laser point cloud plane fitting.
3. The rapid detection method for rail transit platform boundaries based on three-dimensional laser scanning according to claim 1, wherein in step S52, a cube bounding box is constructed according to formula (2):
Figure FDA0004056888320000025
wherein:
BBox: a cube bounding box;
minx, miny, minz: the minimum value of the vertex coordinates of the cubic bounding box;
maxx, maxy, maxz: maximum value of vertex coordinates of the cubic bounding box;
P Tx 、P Ty 、P Tz : and manually selecting coordinate values of the laser point cloud of the outer eave of the platform in an interaction manner.
4. The rapid detection method for rail transit platform limit based on three-dimensional laser scanning according to claim 1, wherein the formula for determining whether the laser point cloud is in the cube in step S53 is as follows:
Figure FDA0004056888320000031
wherein:
pi: an ith laser spot;
Pi x 、Pi y 、Pi z : x, y, z coordinate values of the ith laser spot;
Segment Plateform 、Segment Other : the point clouds are respectively the outer eave point clouds of the platform and other point clouds except the outer eave point clouds of the platform;
BBox minx 、BBox miny 、BBox minz : respectively the minimum value of the vertex coordinates of the cube bounding box;
BBox maxx 、BBox maxy 、BBox maxz : the maximum values of the vertex coordinates of the cubic bounding box are respectively;
delta: the cube bounding box filters the threshold in meters.
5. The rapid detection method for rail transit platform boundaries based on three-dimensional laser scanning according to claim 1, wherein in step S54, plane fitting is performed using formula (4):
N x *x+N y *y+N z *z+constVal＝0 (4)
wherein:
N x 、N y 、N z : fitting a normal vector of the plane;
ConstVal: fitting a constant value of the plane.
CN202310049016.0A 2023-02-01 2023-02-01 Rail transit platform limit rapid detection method based on three-dimensional laser scanning Pending CN116128834A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117848238A (en) * 2024-03-06 2024-04-09 上海市建筑科学研究院有限公司 Rail transit station actual limit measurement method based on laser point cloud
CN118068442A (en) * 2024-04-17 2024-05-24 四川吉埃智能科技有限公司 Method and system for realizing vehicle-mounted tunnel intrusion detection based on laser scanning

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117848238A (en) * 2024-03-06 2024-04-09 上海市建筑科学研究院有限公司 Rail transit station actual limit measurement method based on laser point cloud
CN117848238B (en) * 2024-03-06 2024-05-14 上海市建筑科学研究院有限公司 Rail transit station actual limit measurement method based on laser point cloud
CN118068442A (en) * 2024-04-17 2024-05-24 四川吉埃智能科技有限公司 Method and system for realizing vehicle-mounted tunnel intrusion detection based on laser scanning

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