CN115203778A - Tunnel overbreak and underexcavation detection method and device, terminal equipment and storage medium - Google Patents
Tunnel overbreak and underexcavation detection method and device, terminal equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a tunnel overbreak and undermine detection method, a device, terminal equipment and a storage medium, which belong to the technical field of building construction, and the method comprises the following steps: carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data; simplifying the point cloud data, and reversely constructing an actually measured BI M model of a construction site based on the simplified point cloud data; and carrying out color spectrum visual comparison on the actually measured BI M model and the tunnel design BI M model to calculate the degree of the tunnel overbreak and underexcavation. According to the method, the point cloud data obtained by three-dimensional laser scanning is subjected to reverse modeling, the model is directly fused and compared with the BI M model, and the actual point cloud model in the construction stage and the BI M model in the design stage are subjected to comparative analysis. Therefore, the positions of the overbreak and underbreak are accurately positioned, the number of the overbreak and underbreak is calculated in detail, and overbreak and underbreak data at any section of the tunnel are obtained.
Description
Technical Field
The invention relates to the field of building construction, in particular to a tunnel overbreak and underexcavation detection method and device, terminal equipment and a computer readable storage medium.
Background
The tool mainly used in the tunnel engineering design stage is CAD (Computer aided design) or related software developed based on CAD, and although the design efficiency can be greatly improved compared with manual drawing, the information expression and exchange capability of the tool cannot meet the requirements of the current tunnel project. In addition, the expression of the CAD to the tunnel engineering information is two-dimensional, the abstract expression mode is difficult to intuitively display the geometric information and the position relation of the tunnel structure, and particularly when a complex structure is processed, local design change usually means that the whole model needs to be adjusted, so that designers need to manually change all two-dimensional drawings, and the design efficiency is seriously influenced. Similarly, in the stage of tunnel design, information interaction behaviors such as information extraction and modification can frequently occur among all the professionals, information redundancy can be generated due to information interaction based on the two-dimensional drawing, repeated work is increased, efficiency is low, and the like. The existing tunnel deformation monitoring technology comprises a traditional ground monitoring technology and a measuring robot monitoring technology, wherein the monitoring points which can be acquired within a limited time have low density, only preset point positions of monitoring targets can be acquired, automation is not easy to realize, and the measuring efficiency is low; the latter measures that the distance of the automatic recognition of the target of the robot is short, and the monitoring range is small. When the existing tunnel deformation monitoring technology is applied to long and narrow tunnel engineering, a group of section points are generally required to be arranged in a tunnel at certain intervals, observation is then carried out to obtain section data, and comparison of multi-period data is carried out by observing multiple periods.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a tunnel over-under-excavation detection method, a tunnel over-under-excavation detection device, terminal equipment and a computer readable storage medium, and aims to achieve the technical effects of accurately positioning over-under-excavation positions, calculating the number of over-under-excavation in detail and obtaining over-under-excavation data at any section of a tunnel.
In order to achieve the aim, the invention provides a tunnel over-under-excavation detection method, which comprises the following steps:
carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data;
simplifying the point cloud data, and reversely constructing an actually measured BIM model of a construction site based on the simplified point cloud data;
and carrying out color spectrum visual comparison on the actually measured BIM and the tunnel design BIM so as to calculate the degree of overbreak and underbreak of the tunnel.
Optionally, before the step of performing three-dimensional laser scanning on the tunnel to obtain point cloud data, the method further includes:
and establishing a tunnel design BIM model based on an engineering independent coordinate system and an elevation system, and extracting the control point coordinates and the control point elevation of the key nodes of the tunnel engineering in the tunnel design BIM model.
Optionally, after the step of extracting the control point coordinates and the control point elevations of the key nodes of the tunnel engineering in the tunnel design BIM model, the method further includes:
and acquiring a construction drawing design file, analyzing the construction drawing design file to obtain a target coordinate and a target elevation, and comparing the control point coordinate, the control point elevation, the target coordinate and the target elevation.
Optionally, after the step of comparing the control point coordinates, the control point elevation and the target coordinates, the target elevation, further includes:
and when the control point coordinates, the control point elevation, the target coordinates and the target elevation are correspondingly the same, selecting tunnel control points.
Optionally, the step of performing three-dimensional laser scanning on the tunnel to obtain point cloud data includes:
and carrying out three-dimensional laser scanning on the formed tunnel on the tunnel control point to obtain the point cloud data of the actual space shape of the tunnel.
Optionally, the step of compacting the point cloud data includes:
and registering and merging the point cloud data based on the tunnel control points, eliminating the noise of the point cloud data, and simplifying the point cloud data after the noise is eliminated by using a uniform grid method.
Optionally, the method for detecting tunnel overbreak and underexcavation further includes:
leading in a tunnel central axis and a design section, and generating the tunnel design BIM;
when the actually measured BIM model and the tunnel design BIM model are subjected to color spectrum visual comparison, the section is divided at any position at any interval, a section analysis chromatogram is generated for section analysis, color spectrum visual comparison is carried out, and tunnel construction lofting is carried out at the position of the super-underpit excavation for actually measured verification.
In addition, in order to achieve the above object, the present invention further provides a tunnel under-run detection device, including:
the scanning module is used for carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data;
the building module is used for simplifying the point cloud data and reversely building an actually-measured BIM model of a construction site based on the simplified point cloud data;
and the comparison module is used for carrying out color spectrum visual comparison on the actually measured BIM model and the tunnel design BIM model so as to calculate the degree of overbreak and underbreak of the tunnel.
In addition, to achieve the above object, the present invention also provides a terminal device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the tunnel under-run detection method as described above.
In addition, to achieve the above object, the present invention further provides a computer readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the tunnel under-run detection method as described above.
The embodiment of the invention provides a tunnel over-under-excavation detection method, a tunnel over-under-excavation detection device, terminal equipment and a computer readable storage medium, wherein the tunnel over-under-excavation detection method comprises the following steps: carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data; simplifying the point cloud data, and reversely constructing an actually measured BIM model of a construction site based on the simplified point cloud data; and carrying out color spectrum visual comparison on the actually measured BIM model and the tunnel design BIM model so as to calculate the degree of the tunnel overbreak and the underpreak.
According to the method, the point cloud data obtained by three-dimensional laser scanning is subjected to reverse modeling, the model is directly subjected to fusion comparison with the BIM, or the point cloud data is subjected to model display, and the actual point cloud model in the construction stage and the BIM in the design stage are subjected to comparative analysis. Secondly, a three-dimensional scanning technology is used for scanning the site, the site is connected with a PC (personal computer) end or a manual book platform for analysis, the site measurement situation is quickly reflected, and the automatic total station is controlled through the platform to perform regional lofting, so that the quick entity detection and the deviation marking are completed, the limit invasion or underexcavation part is completely eliminated, and the large-area overunderexcavation is avoided.
Therefore, the problems that the existing tunnel ultra-under excavation detection technology is low in precision and density, needs a cooperative target, cannot acquire three-dimensional data, does not have three-dimensional space analysis capability, cannot integrate data acquisition and processing, and is low in detection efficiency are solved. And then accurately positioning the over-under excavation positions, calculating the over-under excavation quantity in detail, and obtaining over-under excavation data at any section of the tunnel.
Drawings
Fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating an embodiment of a method for detecting under-run tunneling according to the present invention;
FIG. 3 is a schematic diagram of a generation apparatus according to an embodiment of a tunnel under-run detection method of the present invention;
fig. 4 is a schematic configuration diagram of a tunnel under-run detection method according to an embodiment of the present invention;
fig. 5 is a schematic view of a tunnel engineering measurement application of an embodiment of a tunnel under-run detection method of the present invention;
fig. 6 is a schematic cross-sectional view of an embodiment of a tunnel under-run detection method according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Referring to fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the terminal device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a network interface 1003, and a memory 1004. The communication bus 1002 is used to implement connection communication among these components. The network interface 1003 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1004 may be a high-speed Random Access Memory (RAM) Memory, or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1004 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the terminal device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, the memory 1004, which is a storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and an adaptive adjustment program of ANC parameters.
In the terminal device shown in fig. 1, the network interface 1003 is mainly used for data communication with other devices; the processor 1001 and the memory 1004 in the terminal device of the present invention may be provided in the terminal device, and the terminal device calls the computer program stored in the memory 1004 through the processor 1001 and performs the following operations:
carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data;
simplifying the point cloud data, and reversely constructing an actual measurement BIM model of a construction site based on the simplified point cloud data;
and carrying out color spectrum visual comparison on the actually measured BIM model and the tunnel design BIM model so as to calculate the degree of the tunnel overbreak and the underpreak.
Further, the processor 1001 may call the computer program stored in the memory 1004, and further perform the following operations:
the tunnel overbreak and undermine detection method further comprises the following steps:
before the step of performing three-dimensional laser scanning on the tunnel to obtain point cloud data, the method further comprises the following steps:
and establishing a tunnel design BIM model based on an engineering independent coordinate system and an elevation system, and extracting the control point coordinates and the control point elevation of the key nodes of the tunnel engineering in the tunnel design BIM model.
Further, the processor 1001 may call the computer program stored in the memory 1004, and further perform the following operations:
after the step of extracting the control point coordinates and the control point elevations of the key nodes of the tunnel engineering in the tunnel design BIM model, the method further comprises the following steps of:
and acquiring a construction drawing design file, analyzing the construction drawing design file to obtain a target coordinate and a target elevation, and comparing the control point coordinate, the control point elevation, the target coordinate and the target elevation.
Further, the processor 1001 may call the computer program stored in the memory 1004, and further perform the following operations:
after the step of comparing the control point coordinates, the control point elevation and the target coordinates, the target elevation, further comprising:
and when the control point coordinates, the control point elevation, the target coordinates and the target elevation are correspondingly the same, selecting tunnel control points.
Further, the processor 1001 may call the computer program stored in the memory 1004, and further perform the following operations:
the step of performing three-dimensional laser scanning on the tunnel to obtain point cloud data comprises the following steps:
and carrying out three-dimensional laser scanning on the formed tunnel on the tunnel control point to obtain the point cloud data of the actual space shape of the tunnel.
Further, the processor 1001 may call the computer program stored in the memory 1004, and further perform the following operations:
the step of compacting the point cloud data comprises:
and registering and merging the point cloud data based on the tunnel control points, eliminating the noise of the point cloud data, and simplifying the point cloud data after the noise is eliminated by using a uniform grid method.
Further, the processor 1001 may call the computer program stored in the memory 1004, and further perform the following operations:
the tunnel overbreak and underexcavation detection method further comprises the following steps:
leading in a tunnel central axis and a design section, and generating the tunnel design BIM;
when the actually measured BIM model and the tunnel design BIM model are subjected to chromatogram visualization comparison, the section is divided at any position at any interval, a section analysis chromatogram is generated to perform section analysis so as to perform chromatogram visualization comparison, and tunnel construction lofting is performed at the position of overbreak to perform actual measurement verification.
An embodiment of the present invention provides a tunnel under-run detection method, and referring to fig. 2, fig. 2 is a schematic flow diagram of a first embodiment of the tunnel under-run detection method according to the present invention.
In this embodiment, the tunnel under-excavation detection method includes the following steps:
step S10: and carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data.
The three-dimensional laser scanning technology is also called as a real scene copying technology, and by utilizing a laser ranging principle, a point cloud is formed by recording three-dimensional coordinate information of a large number of dense points on the surface of a measured object, and various drawing data such as a three-dimensional model, a line, a surface and a body of the measured object are quickly copied and established. That is, by recording information such as three-dimensional coordinates, reflectivity, texture and the like of a large number of dense points on the surface of the measured object through high-speed measurement, a three-dimensional model of the measured object and various drawing data such as lines, surfaces, bodies and the like can be quickly constructed.
Point cloud data (point cloud data) refers to a collection of vectors in a three-dimensional coordinate system. The scan data is recorded in the form of dots, each dot containing three-dimensional coordinates, some of which may contain color information (RGB) or Intensity information (Intensity).
Compared with the traditional tunnel measurement means, the three-dimensional laser scanner can rapidly acquire high-density point cloud data with higher precision to form a complete and fine tunnel model formed by point clouds, so that the locality of traditional deformation monitoring data can be effectively avoided. Meanwhile, the measurement accuracy of the three-dimensional laser scanner is higher and higher, the working distance is longer and longer, and the scanning technology is continuously developed and promoted. The ground three-dimensional laser scanner equipment is small in size, easy to carry, free of influence of weather changes, simple to operate, flexible and convenient, fast in data acquisition speed and free of contact measurement.
Step S20: and simplifying the point cloud data, and reversely constructing an actual measurement BIM model of the construction site based on the simplified point cloud data.
The BIM (Building Information Modeling) is proposed in 2002 by Autodesk company, mainly uses a digital method to express physical characteristics and functional characteristics of a construction project, different interest correlators modify, extract, insert and update Information in the BIM to provide reliable basis for all decisions in the whole life cycle of the construction project, so as to improve the design, construction and management efficiency of the engineering project.
Referring to fig. 4, fig. 4 is a schematic diagram of an architecture of a tunnel under-run detection method according to an embodiment of the present invention. The application of the fusion of the BIM and the three-dimensional laser scanning technology in the building engineering is mainly shown in the following aspects: the method comprises the steps of rapidly acquiring construction site data, rapidly and reversely modeling the construction site, carrying out construction quality comparative analysis, tracking engineering progress, detecting quality and the like.
(1) Quickly acquiring construction site data
The three-dimensional laser scanning technology is an effective mode for actually measured data acquisition, can ensure the scanning precision, and completely and objectively acquires the three-dimensional data of a selected engineering part or a key part to be stored as data information.
(2) Fast reverse modeling of construction site
For complex engineering construction projects, detailed and accurate topographic data are often needed during design and construction, and most of the traditional surveying and mapping methods adopt a discrete single-point data acquisition mode, so that acquired data points are limited, the measurement precision is low, the period is long, the efficiency is low, and the requirements of the design precision and the engineering progress cannot be met.
The three-dimensional laser scanning technology can realize multi-angle scanning measurement on a measured object by selecting reasonable station positions and the number of measuring stations and setting a proper scanning route, acquire complete and fine point cloud data, convert the point cloud data into geographic coordinates by a coordinate conversion method after preprocessing such as denoising and splicing, and perform three-dimensional modeling by a proper method, thereby providing a good basis for subsequent engineering design planning and building information model creation.
(3) Comparative analysis of construction quality
The BIM technology can provide a basis for the decision of the whole life cycle of an engineering project, but due to the fact that the project is complex in the construction process, the problems of design change, construction defects and the like can often occur, and deviation is generated between actual construction and design of a BIM model. In order to check the quality of engineering construction, a three-dimensional scanning technology is adopted to obtain point cloud data, after software processing, a BIM model of a construction site is constructed, namely, an actual measurement BIM model of the construction site is reversely constructed based on the simplified point cloud data, then, the actual measurement BIM model is compared and analyzed with a designed BIM model, namely, a tunnel design BIM model or a CAD model, the deviation between a digital model and the designed model of the construction site is found, and the reliability and the accuracy of details in the construction process are ensured.
(4) Engineering progress tracking and quality detection
The traditional engineering construction progress tracking and quality detection mostly adopt a sampling detection method, and the problems of more time consumption, low efficiency and the like can occur to large-scale engineering projects with complex terrain, large investment scale, more participants, large construction difficulty and high construction target requirement. And the detection mode based on the three-dimensional laser scanning and BIM fusion technology can realize all the detection, thereby avoiding the randomness of sampling detection, ensuring the objectivity and trueness of data and improving the efficiency of quality detection. The method can optimize the working mode, complete the measurement work with high risk and time consumption by scanning, and greatly reduce the workload and the measurement difficulty; after the scanning measurement work is finished, comparison analysis and measurement can be carried out indoors, and the overall quality of the project can be intuitively known; the traditional text and data information can be replaced by visual three-dimensional models, images, videos and the like, and the communication mode with all the parties participating in the project is changed.
Step S30: and carrying out color spectrum visual comparison on the actually measured BIM and the tunnel design BIM so as to calculate the degree of overbreak and underbreak of the tunnel.
The fusion application of the BIM and the three-dimensional laser scanning technology means that the three-dimensional laser scanning technology and the BIM technology are used for respectively and rapidly modeling an engineering construction object, and format conversion and data comparison analysis are carried out on the established model, so that the purposes of assisting in engineering quality inspection, reducing engineering rework, improving working procedure efficiency and the like are achieved.
In the construction excavation process of the tunnel, if the actually excavated section line exceeds the designed excavation contour line, the method is called overexcavation, and conversely, the method is called underexcavation. And analyzing and presenting an over-under-excavation analysis chromatographic model through three-dimensional point cloud data, visually presenting an over-under-excavation condition, performing data analysis on the over-under-excavation condition through section comparison, and analyzing the secondary lining three-dimensional model to form a tunnel clearance quality detection model.
In this embodiment, the method for detecting the tunnel under-excavation includes the following steps: carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data; simplifying the point cloud data, and reversely constructing an actually measured BIM model of a construction site based on the simplified point cloud data; and carrying out color spectrum visual comparison on the actually measured BIM model and the tunnel design BIM model so as to calculate the degree of the tunnel overbreak and the underpreak.
The point cloud data obtained by three-dimensional laser scanning is subjected to reverse modeling, the model is directly fused and compared with the BIM, or the point cloud data is subjected to model display, and the actual point cloud model in the construction stage and the BIM in the design stage are subjected to comparative analysis. Secondly, a three-dimensional scanning technology is used for scanning the site, the site is connected with a PC (personal computer) end or a manual book platform for analysis, the site measurement situation is quickly reflected, and the automatic total station is controlled through the platform to perform regional lofting, so that the quick entity detection and the deviation marking are completed, the limit invasion or underexcavation part is completely eliminated, and the large-area overunderexcavation is avoided.
Therefore, the problems that the existing tunnel ultra-under excavation detection technology is low in precision and density, needs a cooperative target, cannot acquire three-dimensional data, does not have three-dimensional space analysis capability, cannot integrate data acquisition and processing, and is low in detection efficiency are solved. And then accurately positioning the positions of the over-under excavation, calculating the number of the over-under excavation in detail, and obtaining the over-under excavation data at any section of the tunnel.
Optionally, based on the first embodiment of the method for detecting excessive and insufficient excavation of a tunnel of the present invention, a second embodiment of the method for detecting excessive and insufficient excavation of a tunnel of the present invention is provided.
In this embodiment, before performing three-dimensional laser scanning on the tunnel to obtain the point cloud data in step S10, the method for detecting tunnel under-run excavation according to the present invention may further include:
step S101, establishing a tunnel design BIM model based on an engineering independent coordinate system and an elevation system, and extracting control point coordinates and control point elevations of key nodes of tunnel engineering in the tunnel design BIM model.
And establishing a tunnel design BIM model based on an engineering independent coordinate system and an elevation system, extracting the control point coordinates and the control point elevations of the key nodes of the tunnel engineering, and comparing the control point coordinates and the control point elevations with the analyzed coordinates of the construction drawing design file, wherein the coordinates and the elevations should be the same. The elevation refers to the distance from a certain point to an absolute base plane along the direction of a plumb line, and is called absolute elevation, and is called elevation for short.
In this embodiment, the point cloud data acquisition and scanning adopts two methods, namely a known point frame station and a free station setting of any point, and the specific acquisition process is as follows: (1) known point-to-rack station: the three-dimensional laser scanner has the centering and orienting functions of a total station, the station is set on a known point, the point orientation is controlled by using the rearview, and the scanned point cloud data can be automatically spliced. (2) freely setting a station at any point: in some cases, it is impossible to set a station at a known point, and the scanning operation can be directly performed at any position, and during the scanning process, the scanning area includes a known coordinate point (target ball or target), so that the point cloud can be post-corrected and introduced into the coordinate system during the field processing.
Before an instrument is erected on a known point to acquire point cloud data, the height of the instrument needs to be measured and used as calculation data of elevation lap joint, and the elevation of the known point is measured by adopting an elevation control network established by the elevation measurement precision of a photoelectric ranging triangle which is not lower than four times, so that the measurement precision is ensured.
Optionally, based on the second embodiment of the method for detecting a tunnel under-run excavation, a third embodiment of the method for detecting a tunnel under-run excavation is provided.
In this embodiment, after the step S101 of extracting the control point coordinates and the control point elevations of the key nodes of the tunnel engineering in the tunnel design BIM model, the method for detecting the over-under excavation of the tunnel according to the present invention may further include:
step S102, a construction drawing design file is obtained, the construction drawing design file is analyzed to obtain a target coordinate and a target elevation, and the control point coordinate, the control point elevation, the target coordinate and the target elevation are compared.
In the design of the traditional two-dimensional drawing, if unreasonable and inconsistent conditions are found in the design, the modification is difficult, so that the whole construction progress of the project is influenced. The three-dimensional visualization technology such as key tunnel procedures, construction schemes, special technologies and the like is completed by means of the BIM three-dimensional visualization technology, so that the difficulty of understanding drawings by construction operators is reduced, construction errors caused by unclear understanding of the drawings are effectively avoided, the efficiency and effect of technical background communication are improved, the construction quality is ensured, problems can be predicted in advance, the visualization and the understanding are facilitated, and the background communication is more thorough; the application effect of three-dimensional visualization of key and difficult entity parts of tunnel engineering is realized.
Optionally, based on the third embodiment of the method for detecting a tunnel under-run excavation, a fourth embodiment of the method for detecting a tunnel under-run excavation is provided.
In this embodiment, after acquiring the construction drawing design file, analyzing the construction drawing design file to obtain a target coordinate and a target elevation, and comparing the control point coordinate, the control point elevation, the target coordinate, and the target elevation, the method for detecting the over-under excavation of the tunnel according to the present invention may further include:
and S103, selecting a tunnel control point when the control point coordinates, the control point elevation, the target coordinates and the target elevation are correspondingly the same.
And when the control point coordinates and the control point elevation are the same as the target coordinates and the target elevation, selecting the tunnel control points and then performing tunnel construction lofting. The built BIM model is adopted during lofting, the BIM model is guided into the handbook, the full-automatic total station is driven by the handbook, points needing lofting only need to be clicked on the BIM model, the full-automatic total station can perform lofting rapidly, the connection distance between the handbook and the total station is about 100 meters, lofting can be directly performed on the face, points are made while lofting is performed, resources are saved to a great extent, and efficiency is improved.
The manual book carrying the relevant software platform is directly connected with the three-dimensional laser scanner, the primary support section can be rapidly obtained, then BIM analysis is carried out on the software platform, the ultra-under excavation surface areas of different chromatograms are formed, and the ultra-under excavation condition can be visually analyzed. The disconnection three-dimensional laser scanner connects automatic total powerstation, selects through manual frame and owes to dig the position, can loft out and owe and dig regional boundary, when defect repair handles, can effectively eliminate and owe to dig the position, also avoids surpassing the boundary simultaneously, and too big region is handled and is owed to dig the position and form and surpass and dig and cause the wasting of resources.
Optionally, based on the first embodiment of the method for detecting excessive and insufficient excavation of a tunnel of the present invention, a fifth embodiment of the method for detecting excessive and insufficient excavation of a tunnel of the present invention is provided.
In this embodiment, in the step S10, the step of performing three-dimensional laser scanning on the tunnel to obtain the point cloud data may include:
and S10A, performing three-dimensional laser scanning on the formed tunnel on the tunnel control point to obtain the point cloud data of the actual space shape of the tunnel.
And scanning the formed tunnel by using a three-dimensional laser scanner at a control point in the tunnel to obtain point cloud data of the actual space shape of the tunnel.
Optionally, based on the fifth embodiment of the method for detecting excessive and insufficient excavation of a tunnel of the present invention, a sixth embodiment of the method for detecting excessive and insufficient excavation of a tunnel of the present invention is provided.
In this embodiment, the method for detecting tunnel under-excavation according to the present invention, in step S20, the step of simplifying the point cloud data, may further include:
and S20A, registering and merging the point cloud data based on the tunnel control points, eliminating noise of the point cloud data, and simplifying the point cloud data after the noise is eliminated by using a uniform grid method.
And (3) registering and merging point cloud data: when the three-dimensional laser scanning measurement technology is used for scanning measurement, various factors such as the scanning distance, the scanning resolution and the scanning incidence angle can generate comprehensive influence on the scanning measurement precision. In addition, if the measured building has a large scale and a complex structure, different structures of the building are mutually shielded, and substation scanning is required for obtaining complete measurement information of the measured building. And after partial point cloud data of the building acquired by different observation stations are registered, the complete three-dimensional point cloud data of the surface of the measured building can be obtained. Therefore, in order to reduce errors in data acquisition and point cloud registration, proper operation and scientific measurement work methods must be taken. In addition, the problems of noise, overlapping of point cloud data, redundancy and the like of the point cloud data need to be processed in time so as to obtain high-quality point cloud data.
When utilizing three-dimensional laser scanner to scan the measuring object, because the restriction of laser scanner visual angle to and the mutual shielding between the object, to the measuring object that the scope is great, the structure is more complicated, can not obtain the whole point cloud data of this object through single-station scanning very likely, consequently, must establish the station in a plurality of directions and angle, carry out the scanning of multistation to an object, just can obtain the complete many looks point cloud data of this object. The point cloud data acquired by different stations are based on the local coordinate system of the station, and the directions of the origin of coordinates and the coordinate axes are different, so that the point cloud data under the mutually independent coordinate systems need to be unified into one coordinate system in a coordinate conversion mode, and the point cloud data acquired from the stations can be spliced into a complete three-dimensional point cloud model. This process of transformation of spatial data is called point cloud data registration or stitching.
Point cloud data registration (stitching) is to convert three-dimensional space point cloud data in different coordinate systems into a preset coordinate system, and the process needs two steps: the selection of the corresponding point and the rotation and translation transformation of the coordinate system are carried out. There are three main algorithms, namely: (1) an Iterative Closest Point (ICP) algorithm; (2) a registration algorithm based on geometric features; and (3) a registration algorithm based on the curved surface features. In the actual point cloud data registration process, a joint registration method based on the geometric features and iterative computation can be adopted according to the characteristics of the point cloud data and the contained geometric features, so that the iterative computation times can be reduced, and the accuracy of point cloud data registration can be improved. In this embodiment, the point cloud data registration and merging method and the adopted algorithm are not limited.
Denoising the point cloud data: due to the influence of the measuring instrument and the external environment, the point cloud data obtained by scanning and measuring inevitably contains noise, and the noise of the point cloud data is the comprehensive influence of factors such as measuring equipment, scanning conditions, the surface property of the measured object, the external measuring environment and the like. The causes of noise generation are mainly classified into four major categories: (1) When scanning measurement is performed, the absorption intensity of the material of the surface of the object to be measured to laser, the roughness of the surface, the color, texture, reflectivity and the like of the surface of the object to be measured all bring errors to the scanning measurement. (2) The system error of the scanning and measuring instrument is mainly an error generated by defects on the system of the scanner or insufficient performance, such as the distance measurement precision, the size of a scanning angle and the like, which bring corresponding errors to point cloud data. (3) The error caused by the influence of accidental factors mainly refers to the error caused by the occlusion of pedestrians, vehicles or other moving objects during scanning measurement. (4) And the splicing error of the point cloud data is that when the multi-station point cloud data is subjected to registration splicing, if a common measurement target is not arranged and the number of superposed point clouds among the point cloud data sets is small, the situation of low splicing accuracy occurs, and thus, error points can be generated. In this embodiment, similarly, the point cloud data noise reduction method and the adopted algorithm are not limited.
Simplifying point cloud data: the three-dimensional laser scanning measurement can obtain massive point cloud data, and although the elimination of miscellaneous points and the filtering processing of noise can be performed in the data processing process, the amount of the processed point cloud data is very large. The processing of massive point cloud data can cause the phenomena of large calculated amount, large occupied memory, slow processing speed and even crash. How to reduce the number of point cloud data on the premise of keeping the point cloud data features is very important for improving the efficiency of point cloud data feature extraction and modeling. At present, methods for compacting and compressing point cloud data are divided into three categories:
(1) Traditional data reduction method
The bounding box method is a traditional point cloud data simplification method, and the method adopts a cubic bounding box to constrain the whole point cloud data, then carries out hierarchical progressive division on the bounding box, decomposes the bounding box at the periphery of the point cloud data into a plurality of small bounding boxes with uniform size, searches the point cloud data in each small bounding box, only keeps the point closest to the center of the bounding box, and deletes other points in the small bounding box, so as to achieve the purpose of simplifying the point cloud data. The method has high simplification efficiency, but easily causes the feature loss of the point cloud data, and influences the subsequent modeling and feature extraction.
(2) Data reduction algorithm based on scanning lines
The algorithm is a point cloud data reduction method generated according to the line scanning characteristics of a laser scanner, when the scanner performs line scanning, points on each scanning line can be in the same scanning plane, the scanning lines have a sequence, and the scanning line reduction algorithm judges whether reduction is possible or not by calculating the slope change conditions of front and back points on the scanning lines.
(3) Method for reducing number of polygons
For point cloud data, if a TIN (triangular Irregular Network) model is constructed, data can be simplified by reducing a polygonal data method in the model, and a common vertex compression method based on TIN is a more common method.
In this embodiment, on the premise of satisfying the requirements of data calculation and three-dimensional modeling, the point cloud data of the tunnel model is simplified by using a uniform grid method, so as to improve the efficiency of data processing. The uniform grid method utilizes a median filtering method widely adopted in graphic processing, firstly establishes a uniform grid, then distributes all data points into corresponding grids, and selects a median point to replace all points in the grid for all points in the same grid, thereby achieving the purpose of simplifying point cloud data.
Optionally, based on the foregoing embodiments of the method for detecting excessive and insufficient excavation of a tunnel according to the present invention, a seventh embodiment of the method for detecting excessive and insufficient excavation of a tunnel according to the present invention is provided.
In this embodiment, the method for detecting excessive under-excavation of a tunnel according to the present invention may further include:
step a, importing a tunnel central axis and a design section to generate the tunnel design BIM;
and b, when the actually measured BIM model and the tunnel design BIM model are subjected to chromatogram visualization comparison, segmenting the section at any position at any interval, generating a section analysis chromatogram for section analysis, performing chromatogram visualization comparison, and performing tunnel construction lofting at the overbreak position for actual measurement verification.
In this embodiment, referring to fig. 5, fig. 5 is a schematic view of a tunnel engineering measurement application according to an embodiment of a tunnel under-run detection method of the present invention.
And leading in the central axis and the design section of the tunnel to generate a BIM model for tunnel design. At the moment, tunnel actual measurement point cloud data and a design model are overlapped, a section can be divided at any position at any interval by using a section analysis function, a section analysis chromatogram is generated, and a result can be opened in CAD.
The tunnel axis extraction technique is as follows. The central axis of the tunnel can express the space posture of the tunnel, and the axis extraction method mainly comprises two types. One is to fit the axis hypothesis first, and then to carry out iterative fitting again on the cut section centroid; the other method is to use points in the tunnel point cloud data to directly perform axis fitting. The tunnel axis extraction is usually performed by a second method, which is characterized in that the tunnel direction is adjusted firstly, then the adjusted tunnel point cloud data is projected on an XOY plane and a YOZ plane, the sidelines of the tunnels on the two projection planes are determined, finally the midpoint of the corresponding point pair of the two boundary lines is calculated, and the midpoint is used as the fitting centerline of the tunnel central axis on each projection plane. The method comprises the following concrete implementation steps:
(1) And establishing a bounding box for the tunnel point cloud data, taking the direction of the tunnel as the longest edge of the bounding box, and adjusting the direction of the tunnel to be parallel to the Y axis in the rectangular coordinate system, namely ensuring that the long edge of the bounding box is approximately along the Y axis direction of the coordinate system.
(2) The tunnel point cloud data are projected on an XOY surface, the boundary points of the projected tunnel point cloud are extracted by a two-dimensional boundary searching method, and the extracted boundary points positioned on the left and the right of the projection surface are respectively stored in point sets A and B.
(3) And calculating the Z-axis coordinate corresponding to the boundary point by using the X and Y coordinates of the boundary point in the A and B point sets to obtain the corresponding point cloud data three-dimensional coordinates which are respectively marked as point sets M and N.
(4) And calculating the average value of corresponding points in the point sets M and N according to the sequence until the number of data points in the minimum data set is reached, and obtaining coordinates of a series of middle points, wherein the coordinates are marked as a point set P.
(5) And performing axis estimation on the data points in the point set P by adopting a least square fitting method to obtain a three-dimensional central axis of the tunnel.
The tunnel section extraction technique is as follows. The method comprises the following steps of extracting a tunnel section based on a central axis of the tunnel, determining the position of the tunnel section according to point positions on the central axis, and taking a direction vector of the central axis of the tunnel as a normal vector of the section, wherein the method comprises the following specific steps:
(1) Determination of a section equation: selecting a starting point p = (x) of the tunnel on the central axis of the tunnel 1 ,y 1 ,z 1 ) From the direction vector N = (a, b, c) of the axis, the plane equation of the point is obtained: a (x-x) 1 )+b·(y-y 1 )+c·(z-z 1 )＝0
(2) And (3) distance calculation: calculating points (x) in tunnel point cloud data i ,y i ,z i ) Distance d to the plane.
(3) Determining the section thickness: tunnel point cloud data obtained by three-dimensional laser scanning measurement are discrete points without a spatial topological relation, so that no point or a small number of data points may exist on a plane determined according to an axis normal vector, in order to ensure that intercepted section data are complete, a certain thickness l needs to be given to the plane to form a thin spatial cube, and then the point cloud data in the cube is regarded as points in the plane.
(4) Judging the section points: a threshold value is set for the distance calculated in step (3), and when the distance d is smaller than a given threshold value, the corresponding point is considered to belong to the plane, as shown in fig. 6.
(5) In order to obtain the section data of other positions, points on the central axis of the tunnel are selected at fixed distance intervals, the operation steps from (1) to (4) are repeated, the tunnel section corresponding to the central axis is obtained, and then continuous section extraction can be achieved.
In addition, an embodiment of the present invention further provides a device for detecting over and under excavation of a tunnel, referring to fig. 3, and fig. 3 is a schematic diagram of a generating device according to a first embodiment of a method for detecting over and under excavation of a tunnel according to the present invention.
The tunnel is surpassed and is owed and dig detection device includes:
the scanning module 10 is used for performing three-dimensional laser scanning on the tunnel to obtain point cloud data;
the construction module 20 is used for simplifying the point cloud data and reversely constructing an actual measurement BIM model of a construction site based on the simplified point cloud data;
and the comparison module 30 is used for carrying out color spectrum visual comparison on the actual measurement BIM model and the tunnel design BIM model so as to calculate the degree of the tunnel overbreak.
Optionally, the tunnel under-excavation detection device further includes:
and the extraction module is used for establishing the tunnel design BIM model based on an engineering independent coordinate system and an elevation system and extracting the control point coordinates and the control point elevation of the key node of the tunnel engineering in the tunnel design BIM model before the step of performing three-dimensional laser scanning on the tunnel to obtain point cloud data.
Optionally, the tunnel under-excavation detection device further includes:
and the comparison module is used for acquiring a construction drawing design file after extracting the control point coordinates and the control point elevations of the key nodes of the tunnel engineering in the tunnel design BIM model, analyzing the construction drawing design file to obtain target coordinates and target elevations, and comparing the control point coordinates with the control point elevations and the target coordinates with the target elevations.
Optionally, the tunnel under-excavation detection device further includes:
and the selection module is used for selecting a tunnel control point when the control point coordinates, the control point elevation, the target coordinates and the target elevation are correspondingly the same after comparing the control point coordinates, the control point elevation, the target coordinates and the target elevation.
Optionally, the scanning module further comprises:
and the control point scanning unit is used for carrying out three-dimensional laser scanning on the formed tunnel on the tunnel control point to obtain the point cloud data of the actual space shape of the tunnel.
Optionally, the building module further comprises:
and the simplifying unit is used for registering and combining the point cloud data based on the tunnel control points, eliminating the noise of the point cloud data and simplifying the point cloud data after the noise is eliminated by using a uniform grid method.
Optionally, the tunnel under-excavation detection device further includes:
the section analysis module is used for leading in a tunnel central axis and a design section and generating the tunnel design BIM; when the actually measured BIM model and the tunnel design BIM model are subjected to color spectrum visual comparison, the section is divided at any position at any interval, a section analysis chromatogram is generated for section analysis, color spectrum visual comparison is carried out, and tunnel construction lofting is carried out at the position of the super-underpit excavation for actually measured verification.
By adopting the tunnel under-run excavation detection method in the embodiment, the tunnel under-run excavation detection device provided by the invention solves the technical problems that the tunnel under-run excavation detection technology in the prior art is low in precision and density, requires a cooperative target, cannot acquire three-dimensional data, does not have three-dimensional space analysis capability, cannot integrate data acquisition and processing, and is low in detection efficiency. Compared with the prior art, the beneficial effects of the tunnel over-under-excavation detection device provided by the embodiment of the invention are the same as those of the tunnel over-under-excavation detection method provided by the embodiment, and other technical characteristics of the tunnel over-under-excavation detection device are the same as those disclosed by the embodiment method, which are not repeated herein.
In addition, an embodiment of the present invention further provides a terminal device, where the terminal device includes: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the tunnel under-run detection method as described above.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the tunnel under-run detection method described above are implemented.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) as described above and includes several instructions for enabling a terminal device (which may be a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are also included in the scope of the present invention.
Claims (10)
1. The tunnel overbreak and underexcavation detection method is characterized by comprising the following steps of:
carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data;
simplifying the point cloud data, and reversely constructing an actually measured BIM model of a construction site based on the simplified point cloud data;
and carrying out color spectrum visual comparison on the actually measured BIM and the tunnel design BIM so as to calculate the degree of overbreak and underbreak of the tunnel.
2. The method for detecting tunnel under run of claim 1, wherein before the step of performing three-dimensional laser scanning on the tunnel to obtain point cloud data, the method further comprises:
and establishing a tunnel design BIM model based on an engineering independent coordinate system and an elevation system, and extracting control point coordinates and control point elevations of the key nodes of the tunnel engineering in the tunnel design BIM model.
3. The method for detecting tunnel under run according to claim 2, wherein after the step of extracting the control point coordinates and control point elevations of the key nodes of the tunnel engineering in the tunnel design BIM model, the method further comprises:
and acquiring a construction drawing design file, analyzing the construction drawing design file to obtain a target coordinate and a target elevation, and comparing the control point coordinate, the control point elevation, the target coordinate and the target elevation.
4. The method of detecting tunnel under run of claim 3, further comprising, after the step of comparing the control point coordinates, the control point elevation and the target coordinates, the target elevation:
and when the control point coordinates, the control point elevation, the target coordinates and the target elevation are correspondingly the same, selecting tunnel control points.
5. The method for detecting tunnel under run of claim 4, wherein the step of performing three-dimensional laser scanning on the tunnel to obtain point cloud data comprises:
and carrying out three-dimensional laser scanning on the formed tunnel on the tunnel control point to obtain the point cloud data of the actual space shape of the tunnel.
6. The method of claim 5, wherein the step of compacting the point cloud data comprises:
and registering and merging the point cloud data based on the tunnel control points, eliminating the noise of the point cloud data, and simplifying the point cloud data after the noise is eliminated by using a uniform grid method.
7. The method for detecting excessive and insufficient excavation of a tunnel according to any one of claims 1 to 6, further comprising:
leading in a tunnel central axis and a design section, and generating the tunnel design BIM;
when the actually measured BIM model and the tunnel design BIM model are subjected to chromatogram visualization comparison, the section is divided at any position at any interval, a section analysis chromatogram is generated to perform section analysis so as to perform chromatogram visualization comparison, and tunnel construction lofting is performed at the position of overbreak to perform actual measurement verification.
8. The utility model provides a tunnel surpasses owes to dig detection device which characterized in that, tunnel surpasses owes to dig detection device includes:
the scanning module is used for carrying out three-dimensional laser scanning on the tunnel to obtain point cloud data;
the construction module is used for simplifying the point cloud data and reversely constructing an actual measurement BIM model of a construction site based on the simplified point cloud data;
and the comparison module is used for carrying out color spectrum visual comparison on the actually measured BIM model and the tunnel design BIM model so as to calculate the degree of overbreak and underbreak of the tunnel.
9. A terminal device, characterized in that the terminal device comprises: memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the tunnel under-run detection method according to any of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of detecting tunnel overbreak according to any one of claims 1 to 7.
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