CN113884010A - Tunnel steel frame detection method - Google Patents
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Abstract
The invention provides a tunnel steel frame detection method, comprising the following steps of S1: carrying out three-dimensional scanning on the steel frame after the construction is finished to obtain original point cloud data, and cutting the original point cloud data to obtain three-dimensional coordinate data PointXYZ of the steel frame section under a measurement coordinate system; step S2: identifying all steel frame points in PointXYZ, and extracting three-dimensional coordinates ArchXYZ of all the steel frame points; step S3: calculating the number ArchNum of steel frames in ArchXYZ, and separating three-dimensional coordinates SingleArchXYZ of each steel frame from the identified steel frame points; step S4: and detecting the installation quality parameters of the steel frames according to the identified three-dimensional coordinates SingleArchXYZ of each steel frame. The invention solves the problem that the prior art can only detect the single parameter of the steel frame spacing, and the parameters such as verticality, transverse deviation, vertical deviation and the like are difficult to detect.
Description
Technical Field
The invention relates to the technical field of tunnel construction quality detection, in particular to a tunnel steel frame detection method.
Background
Due to the complexity of engineering geological conditions and the limitation of construction technology, tunnel safety accidents occur frequently, the construction period is influenced to cause property loss, and personal casualties are caused to influence social stability. Therefore, in tunnel engineering construction or operation and maintenance, tunnel measurement work is an important means for guiding construction and monitoring tunnel structure deformation to guarantee tunnel construction and operation safety.
The steel arch is divided into an H-shaped steel arch, an I-shaped steel arch, a channel steel arch, a steel support for miners and a U-shaped steel support according to manufacturing materials, wherein the I-shaped steel arch is used in the steel arch in the largest proportion in highway and railway tunnel construction, and the H-shaped steel arch is inferior; the steel bracket for miners and the U-shaped steel bracket are generally used for supporting roadways such as coal mines and the like, and are also made of I-shaped steel in the coal mines, but are very few. The channel steel arch frame is generally used for small tunnels and is rarely used. In the manufacturing process, some steel sections are manufactured by finished section steel, and some steel sections are manufactured by blanking and welding steel plates into section steel, such as H-shaped steel and I-shaped steel, wherein the proportion of the H-shaped steel is larger than that of the I-shaped steel, and the steel arch frame is used in places with higher surrounding rock grades. The steel arch has four functions: firstly, the surrounding rock is supported before the concrete spraying plays a role; secondly, the sprayed concrete is reinforced; thirdly, the supporting point is used as a supporting point of the advance support; and fourthly, the anchor rod and the sprayed concrete play a role of primary support together. The arch frame can not be taken down for reuse after construction, and is a permanent supporting structure. The steel frame installation quality detection parameters mainly comprise intervals, verticality, protective layer thickness, assembling deviation, transverse deviation, vertical deviation and the like.
In the tunneling process, the working procedures are connected tightly, the measuring time is short, the method is limited by the defects of the prior art, after the steel frame is laid, the distance measurement is carried out by a tester on site by using a tape measure, the parameters such as the verticality, the thickness of a protective layer, the transverse deviation and the vertical deviation are directly determined by the site tester during lofting, the detection measurement is not carried out on site, and the laying quality of the steel frame depends on the lofting precision of the tester and the operation level of a constructor. Therefore, the prior art means can only detect the single parameter of the steel frame spacing, which is far from the requirement of the prior specification.
In summary, in order to comprehensively and effectively detect the construction quality of the tunnel steel frame and powerfully guarantee the safety of the tunnel, a steel frame quality detection method which is simple, rapid and comprehensive in operation is urgently needed on site.
Disclosure of Invention
The invention aims to provide a tunnel steel frame detection method, which aims to solve the problem that the prior art can only detect a single parameter of steel frame spacing and is far from the prior specification requirement, and the specific technical scheme is as follows:
a tunnel steel frame detection method comprises the following steps:
step S1: carrying out three-dimensional scanning on the finished steel frame to obtain original point cloud data, and cutting the original point cloud data to obtain three-dimensional coordinate data PointXYZ of the steel frame section under a measurement coordinate system;
step S2: identifying all steel frame points in PointXYZ, and extracting three-dimensional coordinates ArchXYZ of all the steel frame points;
step S3: calculating the number ArchNum of steel frames in ArchXYZ, and separating three-dimensional coordinates SingleArchXYZ of each steel frame from the identified steel frame points;
step S4: detecting the installation quality parameters of each steel frame according to the identified three-dimensional coordinates SingleArchXYZ of each steel frame;
the method for identifying the steel frame point in the step S2 includes: the distance from each point in PointXYZ to the axis at the middle position of the steel frame is calculated firstly, and then whether each point belongs to a steel frame point or not is judged according to the distance value.
Preferably, in the above technical solution, in the step S1, the original point cloud data is cut according to formula 1), and the point cloud data satisfying the formula 1) is retained:
BeginSkn＜skni< EndSdn formula 1),
wherein BeginSkn and EndSkn are the mileage at the beginning and the end of the steel frame respectively, skniIs the first in the original point cloud dataiThe mileage of the dots.
Preferably, in the above technical solution, the distance from a point in PointXYZ to the axis at the middle position of the steel frame is calculated according to formula 2):
wherein,
is the coordinate of the center of the section at the middle position of the steel frame under the measurement coordinate system,
is a unit tangent vector of the axis at the middle position of the steel frame,
is the second order of PointXYZiDistance from point to axis at middle position of steel frame, PointXYZ [ i, 1:3]As the point cloud of PointXYZiThree-dimensional coordinates of the points.
Preferably, in the above technical solution, the point satisfying formula 3) is a steel frame point:
wherein,
respectively the inner radius and the outer radius of the steel frame, and satisfying formula 3) of PointXYZ [ i, 1: 3)]The set of (a) is ArchXYZ.
Preferably, in the above technical solution, in the step S3, the steel frame number ArchNum is calculated according to formula 4):
wherein,MidSknandMinSknrespectively the middle mileage and the minimum mileage of all identified steel frame points ArchXYZ,ArchSpacein order to design the spacing between the steel frames,ceilis an rounding-up function.
In the above technical solution, preferably, in the step S3, the method for identifying each steel frame includes:
calculate the firstjCoordinate interval of steel truss
；
To pair
And traversing each point in ArchXYZ, and classifying each point into a corresponding coordinate interval to obtain the three-dimensional coordinate SingleArchXYZ of each steel frame.
Preferably, in the above technical solution, the installation quality parameters in step S4 include a steel frame spacing, a steel frame verticality, a steel frame lateral deviation, and a steel frame vertical deviation;
wherein, the steel frame intervalSCalculate according to equation 5):
the formula 5) is shown,
verticality of steel frameVCalculate according to equation 6):
formula 6) below,
lateral deviation of steel frame
Calculate according to equation 7):
formula 7) below is given,
vertical deviation of steel frame
Calculate according to equation 8):
formula 8) below is given,
wherein,
is as followsjMileage of steel truss;TopSknis a mileage at the top of the steel frame,LeftSknis the mileage of the left lower side of the steel frame,RightSknis the mileage of the lower right side of the steel frame,hthe height from the top to the bottom of the steel frame;
respectively is an abscissa of the left side and the right side of the bottom of the steel frame in a section coordinate system where the steel frame is located;
is a vertical coordinate of the top of the steel frame in a section coordinate system where the steel frame is positioned,
and the vertical coordinate of the top of the steel frame is designed in a section coordinate system where the steel frame is located.
Preferably, in the above technical solution, the method further includes step S5: converting the steel frame point coordinate ArchXYZ into a plane coordinate system taking the tunnel mileage direction as a horizontal axis and the tunnel expansion direction as a vertical axis, and visually displaying the steel frame erection quality, wherein the specific conversion method is as follows:
wherein,
is ArchXYZiThe mileage of the point is determined by the distance,
is ArchXYZiThe azimuth of the coordinates of the point in the cross-sectional coordinate system of the point,
is ArchXYZiThe coordinates of the point in the unfolded plane coordinate system,
is the circumferential ratio.
The technical scheme of the invention has the following beneficial effects:
the invention provides a quality detection method for a tunnel steel frame, which comprises the steps of rapidly scanning a steel frame interval, then cutting original point cloud data, and further rapidly identifying all steel frames in the scanning interval; then, judging the number of steel frames according to the design information, and further separating the point cloud of each steel frame; finally, calculating steel frame quality detection parameters according to the point cloud of each steel frame; meanwhile, the identified steel frame can be converted into a tunnel unfolding plane coordinate system for visual display. The brand-new tunnel steel frame detection method provided by the invention is convenient to realize, can simply and efficiently detect each steel frame, and can provide important technical guarantee for tunnel safety. The problem of prior art means only can detect this single parameter of steelframe interval, and hang down straightness, horizontal deviation, vertical deviation isoparametric hardly detect is solved, realized carrying out multi-parameter's detection to steelframe installation quality after executing to do and accomplish, remedied prior art's not enough, ensure that the steelframe installation accords with the standard requirement, in time discover the installation and do not accord with the place of requirement.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of the detection method of the present invention;
FIG. 2 is a cloud image of original coordinates of a tunnel in example 1;
FIG. 3 is a cloud point plot of the steel frame interval after cutting in example 1;
FIG. 4 is a cloud of all steel frame points identified in example 1;
fig. 5 is a display view of the steel frame in a tunnel deployment plane coordinate system in example 1.
Detailed Description
In order that the invention may be more fully understood, a more particular description of the invention will now be rendered by reference to specific embodiments thereof that are illustrated in the appended drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
Example 1:
referring to fig. 1, a tunnel steel frame detection method includes the following steps:
step S1: carrying out three-dimensional scanning on the finished steel frame to obtain original point cloud data, and cutting the original point cloud data to obtain three-dimensional coordinate data PointXYZ of the steel frame section under a measurement coordinate system;
preferably, in step S1, the original point cloud data is cut according to formula 1), and the point cloud data satisfying the formula 1) is retained:
BeginSkn＜skni< EndSdn formula 1),
wherein BeginSkn and EndSkn are respectively the beginning and the end of the steel frameThe mileage can be obtained through a construction plan or a log; skniIs the first in the original point cloud dataiThe mileage of the points can be obtained by performing reverse calculation of the mileage of the line coordinates according to the existing method.
Step S2: identifying all steel frame points in PointXYZ, and extracting three-dimensional coordinates ArchXYZ of all the steel frame points;
the step S2 is specifically: the distance from each point in PointXYZ to the axis at the middle position of the steel frame is calculated firstly, and then whether each point belongs to a steel frame point or not is judged according to the distance value.
Preferably, the distance from a point in PointXYZ to the axis at the steel frame intermediate position is calculated according to equation 2):
wherein,
is the coordinate of the center of the section at the middle position of the steel frame under the measurement coordinate system,
is a unit tangent vector of the axis at the middle position of the steel frame,
is the second order of PointXYZiDistance from point to axis at middle position of steel frame, PointXYZ [ i, 1:3]As the point cloud of PointXYZiThree-dimensional coordinates of the points.
Further preferably, the point satisfying the formula 3) is a steel frame point:
wherein,
the inner radius and the outer radius of the steel frame can be obtained by design data to satisfy the formula3) PointXYZ [ i, 1: 3] of]The set of (a) is ArchXYZ.
Step S3: calculating the number ArchNum of steel frames in ArchXYZ, and separating three-dimensional coordinates SingleArchXYZ of each steel frame from the identified steel frame points;
specifically, in step S3, the steel frame number ArchNum is calculated according to formula 4):
wherein,MidSknandMinSknrespectively the middle mileage and the minimum mileage of all identified steel frame points ArchXYZ,ArchSpacein order to design the spacing between the steel frames,ceilis an rounding-up function.
Further, in step S3, the method for identifying each steel frame includes:
calculate the firstjCoordinate interval of steel truss
；
To pair
And traversing each point in ArchXYZ, and classifying each point into a corresponding coordinate interval to obtain the three-dimensional coordinate SingleArchXYZ of each steel frame.
Step S4: and detecting the installation quality parameters of the steel frames according to the identified three-dimensional coordinates SingleArchXYZ of each steel frame.
Preferably, the installation quality parameters in the step S4 include a steel frame spacing, a steel frame verticality, a steel frame lateral deviation and a steel frame vertical deviation;
wherein, the steel frame intervalSCalculate according to equation 5):
the formula 5) is shown,
verticality of steel frameVCalculate according to equation 6):
formula 6) below,
lateral deviation of steel frame
Calculate according to equation 7):
formula 7) below is given,
vertical deviation of steel frame
Calculate according to equation 8):
formula 8) below is given,
wherein,
is as followsjMileage of steel truss;TopSknis a mileage at the top of the steel frame,LeftSknis the mileage of the left lower side of the steel frame,RightSknis the mileage of the lower right side of the steel frame,hthe height from the top to the bottom of the steel frame;
respectively is an abscissa of the left side and the right side of the bottom of the steel frame in a section coordinate system where the steel frame is located;
is a vertical coordinate of the top of the steel frame in a section coordinate system where the steel frame is positioned,
and the vertical coordinate of the top of the steel frame is designed in a section coordinate system where the steel frame is located.
Preferably, the tunnel steel frame detection method further includes step S5: converting the steel frame point coordinate ArchXYZ into a plane coordinate system taking the tunnel mileage direction as a horizontal axis and the tunnel expansion direction as a vertical axis, and visually displaying the steel frame erection quality, wherein the specific conversion method is as follows:
wherein,
is ArchXYZiThe mileage of the point is determined by the distance,
is ArchXYZiThe azimuth of the coordinates of the point in the cross-sectional coordinate system of the point,
is ArchXYZiThe coordinates of the point in the unfolded plane coordinate system,
is the circumferential ratio.
Referring to fig. 2 to 5, the embodiment further provides a specific application case of the tunnel steel frame detection method.
The case is steel frame installation quality detection of a certain high-speed railway tunnel in Guangdong, a three-dimensional laser scanner is used for scanning an interval for installing the steel frame, original point cloud coordinates x and xyz files are obtained, and a visualization result is shown in an attached figure 2. The initial mileage and related design information between steel frame intervals are obtained through communication with field technicians, and the tunnel steel frame installation quality detection specific process is as follows:
(1) and cutting the original point cloud data according to a mileage interval [155625.7,155627.3] provided by field personnel, wherein the cutting result is shown in the attached figure 3.
(2) Calculating the distance from the point cloud after cutting to the axis of the middle position of the steel frame, and obtaining the distance according to the design information
The particle size of the nano-particles is 7.25m,
the particle size of the nano-particles is 7.40m,when in use
When the point is considered as a steel frame point, all the points are traversed to obtain ArchXYZ, as shown in FIG. 4.
(3) The design distance of the steel frame is 1 meter according to the design information, namelyArchSpaceThe number of steel frames was found to be 2 frames, i.e., ArchNum =2 frames by calculation as =1 m.
(4) And classifying the points in the ArchXYZ according to mileage intervals to obtain the point cloud SingleArchXYZ of each steel frame.
(5) The installation quality parameters of each steel frame are calculated and are shown in the following table:
steel frame installation quality detection table unit: rice and its production process
| Number of | Mileage | Distance between each other | Verticality (unit: degree) | Lateral deviation | Vertical deviation |
| 1 | DK155+626.0 | / | 4.875 | 0.256 | 0.104 |
| 2 | DK155+626.0 | 1.006 | 4.325 | 0.188 | 0.097 |
(6) The conversion of ArchXYZ to the unfolded plane coordinate system is shown in fig. 5.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A tunnel steel frame detection method is characterized by comprising the following steps:
step S1: carrying out three-dimensional scanning on the finished steel frame to obtain original point cloud data, and cutting the original point cloud data to obtain three-dimensional coordinate data PointXYZ of the steel frame section under a measurement coordinate system;
step S2: identifying all steel frame points in PointXYZ, and extracting three-dimensional coordinates ArchXYZ of all the steel frame points;
step S3: calculating the number ArchNum of steel frames in ArchXYZ, and separating three-dimensional coordinates SingleArchXYZ of each steel frame from the identified steel frame points;
step S4: detecting the installation quality parameters of each steel frame according to the identified three-dimensional coordinates SingleArchXYZ of each steel frame;
the method for identifying the steel frame point in the step S2 includes: the distance from each point in PointXYZ to the axis at the middle position of the steel frame is calculated firstly, and then whether each point belongs to a steel frame point or not is judged according to the distance value.
2. The tunnel steel frame detection method according to claim 1, wherein in step S1, the original point cloud data is cut according to formula 1), and the point cloud data satisfying the formula 1) is retained:
BeginSkn＜skni< EndSdn formula 1),
wherein BeginSkn and EndSkn are the mileage at the beginning and the end of the steel frame respectively, skniIs the first in the original point cloud dataiThe mileage of the dots.
3. The tunnel steel frame detection method of claim 1, wherein the distance from a point in PointXYZ to the axis at the steel frame intermediate position is calculated according to equation 2):
wherein,
is the coordinate of the center of the section at the middle position of the steel frame under the measurement coordinate system,
is a unit tangent vector of the axis at the middle position of the steel frame,
is the second order of PointXYZiDistance from point to axis at middle position of steel frame, PointXYZ [ i, 1:3]As the point cloud of PointXYZiThree-dimensional coordinates of the points.
4. The tunnel steel frame detection method according to claim 3, wherein the point satisfying formula 3) is a steel frame point:
wherein,
respectively the inner radius and the outer radius of the steel frame, and satisfying formula 3) of PointXYZ [ i, 1: 3)]The set of (a) is ArchXYZ.
5. The tunnel steel frame detection method according to claim 1, wherein in the step S3, the steel frame number ArchNum is calculated according to formula 4):
wherein,MidSknandMinSknrespectively the middle mileage and the minimum mileage of all identified steel frame points ArchXYZ,ArchSpacein order to design the spacing between the steel frames,ceilis an rounding-up function.
6. The method of claim 5, wherein in the step S3, the method for identifying each steel frame is as follows:
calculate the firstjCoordinate interval of steel truss
；
To pair
And traversing each point in ArchXYZ, and classifying each point into a corresponding coordinate interval to obtain the three-dimensional coordinate SingleArchXYZ of each steel frame.
7. The tunnel steel frame detection method according to claim 1, wherein the installation quality parameters in the step S4 include steel frame spacing, steel frame verticality, steel frame lateral deviation and steel frame vertical deviation;
wherein, the steel frame intervalSCalculate according to equation 5):
the formula 5) is shown,
verticality of steel frameVCalculate according to equation 6):
formula 6) below,
lateral deviation of steel frame
Calculate according to equation 7):
formula 7) below is given,
vertical deviation of steel frame
Calculate according to equation 8):
formula 8) below is given,
wherein,
is as followsjMileage of steel truss;TopSknis a mileage at the top of the steel frame,LeftSknis the mileage of the left lower side of the steel frame,RightSknis the mileage of the lower right side of the steel frame,hthe height from the top to the bottom of the steel frame;
respectively is an abscissa of the left side and the right side of the bottom of the steel frame in a section coordinate system where the steel frame is located;
is a vertical coordinate of the top of the steel frame in a section coordinate system where the steel frame is positioned,
is a steel frame roofAnd the design vertical coordinate of the steel frame in the section coordinate system.
8. The tunnel steel frame detection method according to claim 1, further comprising step S5: converting the steel frame point coordinate ArchXYZ into a plane coordinate system taking the tunnel mileage direction as a horizontal axis and the tunnel expansion direction as a vertical axis, and visually displaying the steel frame erection quality, wherein the specific conversion method is as follows:
wherein,
is ArchXYZiThe mileage of the point is determined by the distance,
is ArchXYZiThe azimuth of the coordinates of the point in the cross-sectional coordinate system of the point,
is ArchXYZiThe coordinates of the point in the unfolded plane coordinate system,
is the circumferential ratio.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11183173A (en) * | 1997-12-16 | 1999-07-09 | Kajima Corp | Structural steel guide system utilizing tracking range finder/goniometer |
| CN109407111A (en) * | 2018-09-27 | 2019-03-01 | 长沙科达智能装备股份有限公司 | A kind of tunnel three-dimensional scanner feature knowledge method for distinguishing |
| CN208734348U (en) * | 2018-07-21 | 2019-04-12 | 中铁十八局集团有限公司 | A kind of tunnel steelframe installation deviation control device |
| CN110135100A (en) * | 2019-05-23 | 2019-08-16 | 中铁二局集团有限公司 | A kind of Tunnel fast modeling method |
| CN111027484A (en) * | 2019-12-11 | 2020-04-17 | 中南大学 | Tunnel steel arch identification method based on three-dimensional imaging |
| CN111310845A (en) * | 2020-02-26 | 2020-06-19 | 广东电网有限责任公司电力科学研究院 | Substation equipment identification method, device and equipment |
| US20200342250A1 (en) * | 2019-04-26 | 2020-10-29 | Unikie Oy | Method for extracting uniform features from point cloud and system therefor |
| CN112907601A (en) * | 2021-03-30 | 2021-06-04 | 中铁工程装备集团隧道设备制造有限公司 | Automatic extraction method and device for tunnel arch point cloud based on feature transformation |
| CN113155027A (en) * | 2021-04-27 | 2021-07-23 | 中铁工程装备集团有限公司 | Tunnel rock wall feature identification method |
| CN113222416A (en) * | 2021-05-17 | 2021-08-06 | 中铁工程装备集团有限公司 | Digital evaluation method and system for tunnel whole-process construction quality |
-
2021
- 2021-12-07 CN CN202111478820.8A patent/CN113884010A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11183173A (en) * | 1997-12-16 | 1999-07-09 | Kajima Corp | Structural steel guide system utilizing tracking range finder/goniometer |
| CN208734348U (en) * | 2018-07-21 | 2019-04-12 | 中铁十八局集团有限公司 | A kind of tunnel steelframe installation deviation control device |
| CN109407111A (en) * | 2018-09-27 | 2019-03-01 | 长沙科达智能装备股份有限公司 | A kind of tunnel three-dimensional scanner feature knowledge method for distinguishing |
| US20200342250A1 (en) * | 2019-04-26 | 2020-10-29 | Unikie Oy | Method for extracting uniform features from point cloud and system therefor |
| CN110135100A (en) * | 2019-05-23 | 2019-08-16 | 中铁二局集团有限公司 | A kind of Tunnel fast modeling method |
| CN111027484A (en) * | 2019-12-11 | 2020-04-17 | 中南大学 | Tunnel steel arch identification method based on three-dimensional imaging |
| CN111310845A (en) * | 2020-02-26 | 2020-06-19 | 广东电网有限责任公司电力科学研究院 | Substation equipment identification method, device and equipment |
| CN112907601A (en) * | 2021-03-30 | 2021-06-04 | 中铁工程装备集团隧道设备制造有限公司 | Automatic extraction method and device for tunnel arch point cloud based on feature transformation |
| CN113155027A (en) * | 2021-04-27 | 2021-07-23 | 中铁工程装备集团有限公司 | Tunnel rock wall feature identification method |
| CN113222416A (en) * | 2021-05-17 | 2021-08-06 | 中铁工程装备集团有限公司 | Digital evaluation method and system for tunnel whole-process construction quality |
Non-Patent Citations (1)
| Title |
|---|
| 马自军 等: "三维激光扫描仪在隧道工程施工中的应用", 《测绘通报》 * |
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Application publication date: 20220104 |