CN114742765B - Tunnel section characteristic point accurate extraction method based on laser point cloud measurement - Google Patents
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Abstract
The invention discloses a tunnel section characteristic point accurate extraction method based on laser point cloud measurement. The section extracted from the point cloud data obtained by the existing three-dimensional laser scanning has large data volume, contains characteristic points and a large number of redundant data points, and influences the post-processing speed. Firstly, setting a section interval, a designated mileage, a cutting thickness, an offset and an angle interval, calculating three-dimensional coordinates of all section extraction positions, and establishing an array containing mileage and coordinate information; calculating normal vector and normal plane coefficient at the appointed mileage; dividing the point cloud of the tunnel section; transforming the tunnel section point cloud projection to a normal plane; converting points on the normal plane to the XOY plane; and obtaining the section characteristic points and characteristic lines until all sections are extracted. The invention can accurately extract the characteristic points and characteristic lines of various tunnels, has no redundant data, can reflect the integral deformation characteristics of the tunnels, and has high post-processing speed.
Description
Technical Field
The invention belongs to the technical field of laser point cloud measurement, and particularly relates to a tunnel section characteristic point accurate extraction method based on laser point cloud measurement.
Background
The stability and safety of the tunnel structure can be effectively ensured by monitoring and measuring in the tunnel construction and operation stages. The traditional measurement means represented by total stations, level gauges and section gauges cannot adapt to large-scale tunnel measurement tasks. The three-dimensional laser scanning measurement technology has the characteristics of high measurement speed, large data volume, high precision, high safety and non-contact, so that the measurement work is safer and more efficient. The monitoring measurement is generally carried out by extracting a section, the section extracted from point cloud data obtained by three-dimensional laser scanning is large in data quantity, and the data quantity comprises characteristic points and a large number of redundant data points, so that the post-processing speed is influenced.
Patent CN106401643a discloses a tunnel super-underexcavation detection method based on laser point cloud, which adopts a monotonic chain convex hull algorithm (Andrew's monotone chain convex hull algorithm) with strong security to automatically extract the contour line of the point cloud of the section to obtain an actually measured section line, wherein the section line is composed of characteristic points. The method has high extraction speed, and is suitable for the condition of over-excavation or under-excavation of all points, wherein the over-excavation values are normally distributed, the absolute value of the over-excavation value is smaller. The invention has the defects that characteristic points are omitted, and the distribution characteristics of the point cloud cannot be truly reflected, and the method comprises two cases: 1) If the over-digging and the under-digging exist, the feature points of the under-digging are all missed; 2) If the absolute value difference of the overexcavation values is large, the feature points between the adjacent large values are omitted.
Li et al, published paper "method for continuous extraction and deformation analysis of tunnel section based on laser point cloud", propose a method for continuously cutting any interval tunnel cross section based on central axis of tunnel, which solves the problem of subway tunnel section extraction method, is applicable to circular tunnel, and has a certain reference meaning for section extraction. The disadvantages of this method are: 1) The method for extracting the central axis is that point cloud data of a section of a tunnel is selected at will, the point cloud data are projected to an XOY plane and a YOZ plane respectively, curve fitting is carried out on the median value of the selected section by adopting a quadratic polynomial, and a central axis equation on the XOY plane and the YOZ plane is obtained, so that the method for calculating the central axis can be matched with the actual central axis only in a circular tunnel and has a certain limitation; 2) The number of the extracted cross-section points is large, and point cloud thinning and characteristic point extraction are not performed, so that the post-processing calculation speed is low.
Disclosure of Invention
In order to make up for the defects of the prior art, the invention provides a tunnel section characteristic point accurate extraction method based on laser point cloud measurement, which uses key characteristic points of a section to replace a point cloud section, solves the accurate extraction of characteristic points of various tunnel types, and improves the post-processing speed.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a tunnel section characteristic point accurate extraction method based on laser point cloud measurement comprises the following steps:
Step one: setting a section interval, a designated mileage, a cutting thickness, an offset and an angle interval according to the section extraction requirement;
Step two: calculating three-dimensional coordinates of all section extraction positions according to line data and section intervals in a tunnel line, and establishing an array A containing mileage and coordinate information;
step three: calculating normal vector and normal plane coefficient at the appointed mileage;
Step four: dividing the point cloud of the tunnel section;
Step five: transforming the tunnel section point cloud projection to a normal plane;
step six: converting points on the normal plane to the XOY plane;
step seven: acquiring section characteristic points and characteristic lines;
And (3) circulating the third step to the seventh step until the section extraction of all mileage parts needing section extraction is completed.
Specifically, the third step includes the following steps:
S3.1: acquiring a coordinate (x, y, z) at a j-th mileage L j in the array A, and calculating a coordinate (x ', y ', z ') at a L j +delta position by an interpolation method;
S3.2: calculating normal vector at the position where mileage needs to be extracted
S3.3: let ax+by+cz+d=0, and calculate the algorithm plane coefficient.
Specifically, the step four tunnel section point cloud segmentation includes the following steps:
s4.1: calculating a distance D k of a point (x k,yk,z,k) of the point cloud to a normal plane of ax+by+cz+d=0;
S4.2: p is all point clouds, P k is one point of the point set P, the coordinates are (x k,yk,zk), the point set Q in the range of the limit difference of the cutting thickness delta is obtained, and the point number of the point set Q is N.
Specifically, the projective transformation of the tunnel section point cloud to the normal plane is specifically:
And (3) projectively transforming the point cloud in the point set Q to a normal plane with ax+by+Cz+D=0, wherein the point (x i,yi,zi,) is the ith point of the point set Q, the point (x i',yi',zi') is the ith point after projection, and the projective points of all the points in the point set Q are calculated in a circulating iterative mode.
Specifically, the step six converts the point on the normal plane to the XOY plane, including the steps of:
S6.1: calculating a rotation angle theta;
S6.2: calculating a coordinate (x i"yi"zi ') of the point (x i',yi',zi') rotated by an angle θ around the z-axis;
s6.3: translating (x i"yi"zi '), and storing the translated result in (x i"yi"zi');
s6.4: converting the result after (X i"yi"zi ") translation into an XOY coordinate system, calculating (X i"yi"zi") coordinates (X iYiZi) converted into the XOY coordinate system;
the range of i in steps S6.2 to S6.4 is [1, N ], and the steps S6.2 to S6.4 are iterated to convert all the projection points into an XOY coordinate system.
Specifically, the step seven of acquiring the section characteristic points and the characteristic lines specifically includes the following steps:
S7.1: calculating a cross section gravity center abscissa x c and an ordinate y c;
s7.2: calculating a point-section gravity center connecting line included angle beta i of the point cloud;
S7.3: calculating the distance d i from the point of the point cloud to the center of gravity of the section;
S7.4: establishing a four-dimensional array B [ X i,Yi,βi,di ] by using X i,Yi,βi,di, establishing a null array C and a null array D according to a four-dimensional array B structure, wherein B i represents the ith element of the array B, C i represents the ith element of the array C, and D i represents the ith element of the array D;
s7.5: obtaining the maximum and minimum distances in the array B according to the angle interval alpha within the range of [ -pi, pi ] until the angle range is larger than pi, terminating the search, storing the obtained minimum distance in the array C, and storing the obtained maximum distance in the array D;
S7.6: merging the arrays C and D to obtain an array E, and sequencing elements in the E according to an angle beta i;
and (3) loop iteration S7.2-S7.6: and extracting the characteristic points and characteristic lines of the laser point cloud from all points in the XOY coordinate system.
The invention has the beneficial effects that:
1) The method has the advantages of simple calculation principle and wide application range, can meet the requirements of accurately extracting the characteristic points and characteristic lines of various types of tunnels such as straight wall arches, door opening types, three-center circles flat arch with inverted arches, horseshoe shapes, circles and the like, has small data quantity of the obtained result, has no redundant data, can reflect the deformation characteristics of the whole tunnel, can obviously accelerate the post-processing speed, and has accurate and reliable extracted characteristic points and characteristic lines of the section;
2) The method is applicable to deformation observation in various stages of tunnel construction, operation, maintenance and the like, and the inner contour characteristic points and the characteristic lines can be used for limit measurement; the outer contour feature points and feature lines can be used for tunnel section extraction; the method is reasonable and feasible, can simplify the calculation process, can obtain accurate data information, and has strong practicability.
Drawings
FIG. 1 is a flow chart of the operation of the present invention;
FIG. 2 is a graph showing the effect of dividing the point cloud of the tunnel section by 0.1 thickness;
fig. 3 is a characteristic line comparison diagram formed by connecting the segmented point cloud section and the characteristic points clockwise.
Detailed Description
The present invention will be described in detail with reference to the following embodiments.
The method can be applied to application scenes of tunnel construction, operation and maintenance at each stage, and parameters are set according to the requirements of projects; through reasonable parameter setting, the precision of the extraction result is reliable, the requirements of various applications such as limit measurement, tunnel section extraction, tunnel super-underexcavation calculation, completion measurement and the like can be met, and the accurate extraction of various tunnel characteristic points and characteristic lines such as straight wall arches, door opening types, three-centered circles flat arch with inverted arches, horseshoe shapes, circles and the like can be met, so that the application range is wide and the practicability is strong; in the technical scheme, tunnel laser point cloud data are obtained through a ground laser scanning mode, and an XOY plane coordinate system specifically refers to a Cartesian plane rectangular coordinate system. As shown in fig. 1, the present invention specifically includes the following steps:
Step one: setting a section interval, a designated mileage, a cutting thickness, an offset and an angle interval according to the section extraction requirement;
The section interval refers to extracting one section from the specified initial mileage with each interval phi=5m length; the cutting thickness delta refers to the thickness of a cutting section, a reasonable parameter is set according to the point cloud obtained by scanning in a sparse mode, and delta=0.1m is taken; the offset delta is a midline differential length value, which is used for calculating a vector, and the differential length value takes delta=0.01m; the angle interval alpha is an angle interval parameter, the range of [ -pi, pi ] is equally divided according to alpha, the smaller the angle interval parameter is, the more points are obtained, the angle interval is generally set to alpha=1 degree, the extracted points are enough to be used, and if higher precision is required, the minimum alpha is set to 0.5 degree;
Step two: calculating three-dimensional coordinates of all section extraction positions according to line data and section intervals in a tunnel line, and establishing an array A containing mileage and coordinate information;
Calculating corresponding mileage plane coordinates at the equidistant mileage positions according to the initial extraction mileage by using the centerline data of the tunnel design; calculating a central elevation value of a tunnel with corresponding mileage according to longitudinal section data, and setting up a four-dimensional array A [ mileage, abscissa, ordinate, elevation ] according to the mileage, plane coordinates and elevation at the rail surface by designing the relation between the tunnel center and the rail surface design elevation of a diagram, and storing the central elevation value naturalisation of the tunnel to the elevation at the rail surface;
step three: calculating normal vector and normal plane coefficient at a designated mileage, which comprises the following steps;
S3.1: acquiring coordinates (x, y, z) at a j-th mileage L j in the array A, and directly acquiring from the array A; calculating coordinates (x ', y ', z ') at the position L j +delta, namely calculating coordinate values at the appointed mileage by an interpolation method according to data in an array A [ mileage, abscissa, ordinate, elevation ].
S3.2: calculating normal vector at the position where mileage needs to be extractedCalculating according to a formula (1);
s3.3: setting the normal plane where the section is positioned as ax+by+cz+d=0, and calculating the algorithm plane coefficient; the method for calculating the normal plane coefficients is calculated according to formulas (2), (3) and (4);
step four: the method specifically comprises the following steps of dividing the point cloud of the tunnel section;
S4.1: calculating the distance of a point (x k,yk,z,k) of the point cloud to a normal plane of ax+by+cz+d=0; the distance from the set point (x k,yk,z,k) to the normal plane is d k, and the calculation is carried out according to a formula (5);
S4.2: acquiring points in the section slice range of the tunnel: p is the total point cloud, P k is one point of the point set P, coordinates are (x k,yk,zk,); acquiring a point set Q within the limit difference range of the cutting thickness delta according to a formula (6), wherein the point number of the point set Q is N;
the segmentation result of the tunnel section point cloud is shown in fig. 2, and the tunnel section point cloud is segmented according to the thickness of 0.1;
Step five: transforming the projection of the tunnel section point cloud to a normal plane, which comprises the following steps of;
Transforming the point cloud projection in the point set Q to an Ax+By+Cz+D=0 normal plane, wherein the point (x i,yi,zi,) is the ith point of the point set Q, the point (x i',yi',zi') is the ith point after projection, and the projection points of all the points in the point set Q are calculated in a cyclic iteration mode according to formulas (7) and (8);
step six: converting points on the normal plane to the XOY plane, comprising the steps of:
s6.1: calculating a rotation angle theta according to a formula (9):
θ＝arctan(y/x) (9)
Where θ represents the rotation angle around the z-axis, x designates the abscissa at mileage L i, and y designates the ordinate at mileage L i.
S6.2: calculating a coordinate (x i"yi"zi ') of the point (x i',yi',zi') rotated by an angle theta around the z-axis, and calculating according to a formula (10);
where (x i"yi"zi ") is the coordinates of (x i',yi',zi') after rotation by θ about the z axis.
S6.3: translating (x i"yi"zi '), storing the translated result in (x i"yi"zi'), and calculating according to formula (11):
Where (x, y, z) is the coordinates at the specified mileage L i.
S6.4: converting the result after (X i"yi"zi ') translation into an XOY coordinate system, calculating (X i"yi"zi') and converting into coordinates (X iYiZi) of the XOY coordinate system, wherein the calculating method is carried out according to a formula (12):
wherein, (X iYiZi) is the coordinates of (X i"yi"zi') converted to the XOY coordinate system;
the range of i in steps S6.2 to S6.4 is [1, N ], and the steps S6.2 to S6.4 are iterated to convert all the projection points into an XOY coordinate system.
Step seven: acquiring section characteristic points and characteristic lines, which specifically comprise the following steps of;
s7.1: calculating the abscissa x c and the ordinate y c of the center of gravity of the section according to the formulas (13) and (14):
Wherein X c、yc represents the abscissa and ordinate of the center of gravity, N is the number of points converted from the point cloud on the section to the XOY coordinate system, and (X i Yi) is the coordinate of the ith point converted to the XOY coordinate system;
S7.2: calculating a point-section gravity center connecting line included angle beta i of the point cloud, and calculating according to a formula (15);
βi＝arctan((Yi-yc)/(Xi-xc))*180/π (15)
Where X c、yc represents the abscissa and ordinate of the center of gravity, respectively, (X i Yi) is the coordinate of the ith point converted to the XOY coordinate system, and β i represents the included angle between the line of (X i Yi) and the center of gravity, and the value range is [ -pi, pi ].
S7.3: calculating the distance d i from the point of the point cloud to the center of gravity of the section, and calculating according to a formula (16);
Where d i represents the distance between the line connecting the center of gravity (X i Yi).
S7.4: establishing a four-dimensional array B [ X i,Yi,βi,di],Xi,Yi,βi,di ] by using X i,Yi,βi,di, storing the four-dimensional array B into an array B, establishing a null array C and a null array D according to a four-dimensional array B structure, wherein B i represents the ith element of the array B, C i represents the ith element of the array C, and D i represents the ith element of the array D;
s7.5: obtaining maximum and minimum distances according to an angle interval alpha within the range of [ -pi, pi ] until the angle range is larger than pi, terminating the search, storing the obtained minimum distance in an array C, and storing the obtained maximum distance in an array D;
Firstly, acquiring elements of beta i in the range of [ -pi, -pi+alpha) from the array B, searching for the smallest element of the elements D i to be stored in the array C 0, and storing the largest element D i in the array D 0;
Firstly, acquiring elements of beta i in the range of [ -pi+alpha, -pi+2alpha) from the array B, searching that the element with the smallest D i of the elements is stored in the array C 1, and the element with the largest D i is stored in the array D 1;
Firstly, acquiring elements of beta i in the range of [ -pi+2alpha, -pi+3alpha) from the array B, searching that the element with the smallest D i of the elements is stored in the array C 2, and the element with the largest D i is stored in the array D 2;
……
until the angular range is greater than pi, the search is terminated.
S7.6: merging the arrays C and D to obtain an array E, and sequencing elements in the E according to an angle beta i;
and (3) loop iteration S7.2-S7.6: and extracting the characteristic points and characteristic lines of the laser point cloud from all points in the XOY coordinate system.
The inner outline characteristic points of the point cloud are stored in the array C processed by the steps S7.1-S7.6, and the points are sequentially connected, namely the inner outline characteristic lines; the array D stores the outline characteristic points of the point cloud, and the points are sequentially connected to form an outline characteristic line; and storing characteristic points of the whole tunnel of the point cloud in the array E, and connecting the points sequentially to obtain the point cloud characteristic line of the whole tunnel. The tunnel limitation uses an array C, and as shown in fig. 3, a characteristic line comparison diagram formed by connecting a point cloud section result and characteristic points clockwise is shown.
And (3) circularly executing the steps three to seven until the section extraction at all mileage positions where the section needs to be extracted is completed.
The content of the invention is not limited to the examples listed, and any equivalent transformation to the technical solution of the invention that a person skilled in the art can take on by reading the description of the invention is covered by the claims of the invention.
Claims (1)
1. A tunnel section characteristic point accurate extraction method based on laser point cloud measurement is characterized by comprising the following steps of: the method comprises the following steps:
Step one: setting a section interval, a designated mileage, a cutting thickness, an offset and an angle interval according to the section extraction requirement;
Step two: calculating three-dimensional coordinates of all section extraction positions according to line data and section intervals in a tunnel line, and establishing an array A containing mileage and coordinate information;
step three: calculating normal vector and normal plane coefficient at the appointed mileage;
Step four: dividing the point cloud of the tunnel section;
Step five: transforming the tunnel section point cloud projection to a normal plane;
step six: converting points on the normal plane to the XOY plane;
step seven: acquiring section characteristic points and characteristic lines;
Circulating the third step to the seventh step until the section extraction of all mileage parts needing section extraction is completed;
the third step comprises the following steps:
S3.1: acquiring a coordinate (x, y, z) at a j-th mileage L j in the array A, and calculating a coordinate (x ', y ', z ') at a L j +delta position by an interpolation method;
S3.2: calculating normal vector at the position where mileage needs to be extracted
S3.3: setting the normal plane where the section is positioned as ax+by+cz+d=0, and calculating the algorithm plane coefficient;
The step four tunnel section point cloud segmentation comprises the following steps:
s4.1: calculating a distance D k of a point (x k,yk,z,k) of the point cloud to a normal plane of ax+by+cz+d=0;
S4.2: p is all point clouds, P k is one point of a point set P, the coordinates are (x k,yk,zk), a point set Q in the range of the limit difference of the cutting thickness delta is obtained, and the point number of the point set Q is N;
the projection transformation of the tunnel section point cloud to the normal plane is specifically as follows:
transforming the point cloud projection in the point set Q to a Ax+By+Cz+D=0 normal plane, wherein the point (x i,yi,zi,) is the ith point of the point set Q, the point (x i',yi',zi') is the ith point after projection, and the projection points of all the points in the point set Q are calculated in a cyclic iteration mode;
The step six of converting the point on the normal plane to the XOY plane comprises the following steps:
S6.1: calculating a rotation angle theta;
S6.2: calculating a coordinate (x i" yi" zi ') of the point (x i',yi',zi') rotated by an angle θ around the z-axis;
S6.3: translating (x i" yi" zi '), and storing the translated result in (x i" yi" zi');
S6.4: converting the result after (X i" yi" zi ") translation into an XOY coordinate system, calculating (X i" yi" zi") coordinates (X i Yi Zi) converted into the XOY coordinate system;
The value range of i in the steps S6.2 to S6.4 is [1, N ], and all projection points are converted into an XOY coordinate system in the steps S6.2 to S6.4 of cyclic iteration;
the step seven of acquiring the section characteristic points and the characteristic lines specifically comprises the following steps:
S7.1: calculating a cross section gravity center abscissa x c and an ordinate y c;
s7.2: calculating a point-section gravity center connecting line included angle beta i of the point cloud;
S7.3: calculating the distance d i from the point of the point cloud to the center of gravity of the section;
S7.4: establishing a four-dimensional array B [ X i,Yi,βi,di ] by using X i,Yi,βi,di, establishing a null array C and a null array D according to a four-dimensional array B structure, wherein B i represents the ith element of the array B, C i represents the ith element of the array C, and D i represents the ith element of the array D;
s7.5: obtaining the maximum and minimum distances in the array B according to the angle interval alpha within the range of [ -pi, pi ] until the angle range is larger than pi, terminating the search, storing the obtained minimum distance in the array C, and storing the obtained maximum distance in the array D;
S7.6: merging the arrays C and D to obtain an array E, and sequencing elements in the E according to an angle beta i;
and (3) loop iteration S7.2-S7.6: and extracting the characteristic points and characteristic lines of the laser point cloud from all points in the XOY coordinate system.
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