CN113514041A - Engineering construction project multi-measurement-in-one data acquisition and library building method - Google Patents
Engineering construction project multi-measurement-in-one data acquisition and library building method Download PDFInfo
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- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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Abstract
The invention discloses a data acquisition and database construction method integrating multiple measurements and integration of engineering construction projects, which is characterized in that a ground tripod, a mobile measuring vehicle, an unmanned aerial vehicle, a SLAM backpack and other multiple platforms are used for carrying sensors such as a three-dimensional laser scanner and a camera to carry out the data acquisition integrating multiple measurements and integration of all elements, measurement results are integrated and recorded into a data base integrating multiple measurements and integration based on a full life cycle geographic entity, and the data acquisition integrating multiple tests and integration of planning verification, cadastral and house property is realized through the comparison of point cloud and BIM. The invention has the advantages of high acquisition efficiency, complete measurement information, traceable achievement, support of three-dimensional integrated acceptance and the like, and has method demonstration and technical leading significance for comprehensively promoting the implementation of 'multi-measurement-in-one' landing.
Description
Technical Field
The invention relates to the technical field of surveying and mapping geographic information, in particular to a data acquisition and library construction method integrating multiple measurements of engineering construction projects.
Background
The measurement items of 'multi-measurement-in-one' comprise the most basic planning verification measurement, house property measurement, cadastral measurement, and also can be added with civil air defense measurement, greenbelt measurement, fire control measurement and the like. The prior technical scheme of 'measuring more and unifying more' has limitations: firstly, the measuring equipment is mainly also a GNSS receiver, a total station, a distance meter and other traditional single-point measuring instruments, the acquisition efficiency is low, the acquired information is less, and the traceability is not realized; for example, at present, instruments such as a total station and a GNSS receiver are mainly used for multi-measurement-in-one data acquisition, which is low in efficiency, small in information amount and not traceable. The method of 'multi-measurement-in-one' assisted by the ground static three-dimensional laser scanning technology is also utilized, but the problem of blind areas at the top of a building exists, and the problem of too many stations exist in a greening area. And secondly, the results of planning verification measurement, house property measurement, cadastral measurement and the like are stored independently, different measurement services repeatedly acquire the same ground objects and store the same ground objects in the database respectively, so that the situation that the ground objects have repetition, conflict and redundancy on spatial information cannot be avoided, and the management of result data and the dynamic maintenance of the database are not facilitated. The supporting effect of the 'multi-measurement-in-one' achievement of the existing scheme on 'multi-inspection-in-one' is not ideal, on one hand, the collected information amount is limited, on the other hand, comparison and acceptance can only be carried out on a two-dimensional layer, so that after the traditional acceptance method generally utilizes single-point measuring instruments such as a total station instrument, a GNSS receiver and the like to collect index data, two-dimensional comparison is carried out with a drawing, and the traditional acceptance method is not intuitive and has large workload.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a data acquisition and library construction method for engineering construction projects with multiple measurements and unification, which has the advantages of high acquisition efficiency, complete measurement information, traceable achievement, support of three-dimensional integrated acceptance and the like, and has method demonstration and technical leading significance for comprehensively promoting implementation of multiple measurements and unification.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the present embodiment provides an all-in-one-test data acquisition and library building method for an engineering construction project, where the method is used to generate and store current status information of a geographic entity of the engineering construction project, and the generation method includes:
s1, dividing geographic entities in the engineering construction project into four types including buildings, roads, green areas and top surfaces;
s2, control leads are comprehensively arranged in the engineering construction project range, and the arrangement of the control leads follows the following principle: the point cloud data registration of geographic entities in each area plays a role in linking and controlling error transmission;
s3, collecting point cloud data of buildings including real estate by using a wire control point frame station and a directional ground static three-dimensional laser scanner; acquiring point cloud data of roads from four to four of engineering construction projects by adopting a vehicle-mounted three-dimensional laser scanner; collecting point cloud data of a greening area by using a SLAM back-pack three-dimensional laser scanner; collecting point cloud data of a top surface area from an aerial view angle by adopting an unmanned aerial three-dimensional laser scanner;
s4, taking point cloud data of the ground static three-dimensional laser scanner as frame data, sequentially carrying out denoising, rarefying, registering, precision correction and coordinate conversion processing, and fusing all the point cloud data acquired in the step S3;
s5, analyzing the project acceptance tasks corresponding to the imported project construction projects, and obtaining all acceptance targets corresponding to the project acceptance tasks by taking the geographic entities as basic units;
and S6, dividing the fused point cloud data to generate point cloud data of each acceptance target corresponding to the current project acceptance task, constructing geometric figures of all acceptance targets in the all-in-one-to-many-test database, inputting attribute information according to measurement requirements, and generating the all-in-one-to-many-test database of the project acceptance task.
Further, in step S2, the process of fully laying control wires in the scope of the engineering construction project includes the following steps:
selecting the grade of the control net according to the distribution of known control points in a measuring area, the landform, the distribution of a scanning target object and the precision requirement, designing the net shape of the control net, and calculating to obtain an initial control point;
determining a point cloud acquisition mode of each geographic entity according to the type of the geographic entity in the survey area;
according to the point cloud collection mode and the position information of the geographic entity, the following conditions are used as constraint conditions: (1) the total number of control points is minimum, (2) the point cloud data of different areas or different acquisition sources have overlapping quantity meeting the registration requirement, the initial control points are optimized to obtain optimized control points, and control leads are distributed according to the optimized control points.
Further, in step S3, the acquiring point cloud data of a building including real property by using the wire-controlled point erecting station and the directional ground static three-dimensional laser scanner includes:
according to the characteristics of a scanning object, setting up a scanning station by taking the minimum number of the set stations and the minimum distance variance between the scanning stations as constraint conditions, wherein the scanning range of the scanning station covers all buildings including real estate;
and initializing scanning stations, and collecting point cloud data of buildings in respective scanning ranges by adopting the scanning stations, wherein the overlapping degree of effective point clouds between adjacent scanning stations is not lower than a minimum overlapping degree threshold value.
And naming the scanning station according to the project name, the scanning date and the scanning station number, storing the scanning data, and marking the position of the scanning station on the related engineering drawing of the engineering construction project.
Further, in step S3, the process of acquiring point cloud data of the road from four to four of the engineering construction project by using the vehicle-mounted three-dimensional laser scanner includes the following steps:
arranging a three-dimensional laser scanner, a GNSS receiver and an inertial navigation sensor on a mobile measuring vehicle;
starting a GNSS receiver in an open area with strong GNSS signals, locking a satellite, starting to record GNSS data, starting inertial navigation equipment to enable the inertial navigation equipment to enter a working state, and initializing to finish the mobile survey vehicle;
starting a three-dimensional laser scanner, driving a vehicle to run at a uniform speed, movably scanning a road scene, and collecting point cloud data of four roads;
turning off the three-dimensional laser scanner, parking the mobile measuring vehicle to an open area again, and turning off the inertial navigation sensor and the GNSS receiver; and solving three-dimensional laser point clouds of the four-to-four roads by utilizing inertial navigation data and GNSS data and combining with CORS data of a global navigation satellite continuously operating reference station.
Further, in step S3, the process of collecting point cloud data of a green area by using a SLAM backpack three-dimensional laser scanner includes the following steps:
arranging a three-dimensional laser scanner, a wide-angle camera and inertial navigation equipment on an SLAM backpack; starting the inertial navigation equipment under the static state of the SLAM backpack, and keeping the SLAM backpack stable and entering an initialization state after the SLAM backpack is started and enters a working state;
after initialization is completed, starting a three-dimensional laser scanner and a wide-angle camera, starting to movably scan a greening area, ensuring that more than three points of point clouds scanned by static three-dimensional laser on the ground are overlapped, finally enabling the SLAM backpack to return to a starting place, and forming a global closed ring and M local closed rings on a scanning path; m is greater than or equal to 0;
closing the three-dimensional laser scanner and the inertial navigation equipment;
and (4) solving three-dimensional laser point cloud of the greening area based on a SLAM algorithm and by combining inertial navigation data.
Further, in step S3, the process of collecting the point cloud data of the top surface area from the aerial perspective by using the three-dimensional unmanned aerial laser scanner includes the following steps:
arranging a three-dimensional laser scanner, a camera, inertial navigation equipment and a GNSS receiver on an unmanned aerial vehicle holder;
planning an unmanned aerial vehicle route according to the characteristics of the engineering construction project, and preparing the unmanned aerial vehicle for flying;
initializing the unmanned aerial vehicle and a carrying sensor thereof; after initialization is completed, starting the unmanned aerial vehicle to lift off, and simultaneously starting the three-dimensional laser scanner, the camera, the inertial navigation equipment and the GNSS receiver; enabling the unmanned aerial vehicle to carry out three-dimensional laser scanning on the engineering construction project from the air along the planned route, and acquiring point cloud data of a top surface area;
turning off the three-dimensional laser scanner, turning off inertial navigation, enabling the unmanned aerial vehicle to return to the home and land, and deriving original data;
and solving the three-dimensional laser point cloud of the top surface area by using inertial navigation data and GNSS data and combining with CORS data of a global navigation satellite continuously operating reference station.
Further, in step S4, the point cloud data of the ground static three-dimensional laser scanner is used as frame data, and the denoising, thinning, registration, precision correction, and coordinate conversion processing are sequentially performed, and the process of fusing all the point cloud data acquired in step S3 includes:
noise filtering processing is carried out on all point cloud data, and reflection points including system error points, accidental error points and dust flying birds are identified and removed;
taking point cloud data of a ground static three-dimensional laser scanner as frame data, carrying out fragment correction on the point cloud data of a greening area acquired by the SLAM backpack three-dimensional laser scanner based on overlapped point cloud data between the frame data and the frame data, and uniformly converting the point cloud data into a national 2000 geodetic coordinate system or a 3-degree Gauss Kruger projection coordinate system;
correcting the reflection intensity according to the incident angle and the transmission distance of laser scanning;
and identifying the precision of the point cloud data of the four-road and the top surface area, and when the precision of one of the point cloud data and the top surface area does not meet the corresponding minimum precision requirement, taking the point cloud data of the ground static three-dimensional laser scanner as frame data, and performing precision correction and reflection intensity correction on the point cloud data which does not meet the minimum precision requirement.
Further, in step S6, the dividing the fused point cloud data to generate point cloud data of each acceptance target corresponding to the current project acceptance task, constructing geometric figures of all acceptance targets in the all-in-one-test database, and inputting attribute information according to measurement requirements to generate the all-in-one-test database of the project acceptance task includes the following steps:
classifying the fused point cloud data into ground point cloud and non-ground point cloud by utilizing a progressive triangulation network filtering and cloth simulation filtering algorithm;
aiming at non-ground point cloud, automatically extracting plane buildings including wall surfaces by using a region growing algorithm; automatically classifying and extracting rod-shaped objects including lamp poles and electric poles by using a random sampling consistency algorithm; directly extracting a space graph corresponding to other multi-measurement-in-one elements from the three-dimensional point cloud by using a three-dimensional mapping function of CAD software;
constructing an irregular triangular grid aiming at the ground point cloud, and interpolating to form a digital elevation model;
and recording the extracted space graph, the ground digital elevation model and various attributes of the ground digital elevation model into an all-in-one database.
In a second aspect, this embodiment refers to an all-in-one experience implementation method based on a geographic entity, where the all-in-one experience implementation method includes:
constructing a building information model corresponding to the engineering design building by utilizing a plan view, an elevation view and a section view of the engineering design building and special item drawings of fire fighting, heating ventilation and water supply and drainage pipelines;
generating an all-in-one database corresponding to the project acceptance task by adopting the method;
the multi-test-in-one database and the building information model are matched and compared, the building structure and the construction precision are comprehensively checked in a three-dimensional scale, and the multi-test-in-one of the indexes required by planning verification, cadastral location and real estate is realized.
Further, the all-in-one-out implementation method further includes:
the method comprises the following steps of taking a geographic entity as a space carrier, and fusing the following data into a natural resource large platform by utilizing a network geographic information system, a three-dimensional rendering engine and an IFC data standard:
the system comprises a multi-measurement-in-one database, multi-platform point cloud data, a aviation flight orthophoto map, a digital elevation model, a digital topographic map, underground building general survey data, underground pipeline general survey data, landscaping general survey data, engineering geology general survey data, an inclined three-dimensional model, a building information model and digital documents for planning, examining and accepting.
The engineering construction project multi-measurement-in-one data acquisition and library building method disclosed by the embodiment carries sensors such as a three-dimensional laser scanner and a camera on multiple platforms such as a ground tripod, a mobile measuring vehicle, an unmanned aerial vehicle and a SLAM backpack, performs multi-measurement-in-one all-factor acquisition, integrates and records measurement results into a multi-measurement-in-one database based on a full life cycle geographic entity, and realizes planning verification, cadastral registration and multi-check-in-one of a house property by comparing point cloud and BIM.
The invention has the beneficial effects that:
1) the invention provides an all-element acquisition method of 'multi-measurement-in-one' based on multi-platform three-dimensional laser scanning, which not only realizes three-dimensional data acquisition, but also weakens blind areas through multiple visual angles and gives consideration to efficiency and precision through multiple platforms.
2) According to the data integration method based on the full-life-cycle geographic entity, spatial data have uniqueness, consistency and accuracy, and different attributes can be connected according to the requirements of various measurement services.
3) The 'all-in-one' method based on the three-dimensional laser point cloud and the building information model provided by the invention is used for carrying out three-dimensional full-coverage comparison on various indexes such as building structures, construction precision and the like, and realizing 'all-in-one' of various checks and receipts such as planning verification, cadastral, real estate and the like.
Drawings
Fig. 1 is a flowchart of the engineering construction project multi-test-in-one data acquisition and library building method according to the embodiment.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings.
It should be noted that the terms "upper", "lower", "left", "right", "front", "back", etc. used in the present invention are for clarity of description only, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the terms is not limited by the technical contents of the essential changes.
Detailed description of the preferred embodiment
Fig. 1 is a flowchart of the engineering construction project multi-test-in-one data acquisition and library building method according to the embodiment. Referring to fig. 1, the method for generating an all-in-one database is used for generating and storing the current status information of the geographic entity of an engineering construction project, and includes:
and S1, dividing the geographic entities in the engineering construction project into four types including buildings, roads, green areas and top surfaces of real estate respectively.
The "all-in-one-by-all" database of this embodiment breaks through the existing database structure separately defined by the measurement service, integrates the repeated items of the original planning verification measurement, the property measurement, and the cadastral measurement, and divides them into various geographic entities, such as the engineering construction project geographic entity, the real property geographic entity, other planning geographic entities, and basic geographic information elements, and organizes and expresses the attributes by using spatial positioning, geometric shape, special attributes, interrelation, evolution process, and semantic description (six elements of the geographic entities). The aforementioned geographic entities may also be subdivided, for example, real estate geographic entities are divided by subordination from large to small into: cadastral area, cadastral sub-area, land parcel, house, unit, layer, individual household. The land parcel can be subdivided into land parcel, address line, three kinds of address point, the house can be subdivided into five kinds of house, hierarchical house, basement, large ground storehouse, structure. Other planning geographic entities include: interior greenhouses, interior roads, parking spaces, enclosures, basement exits, and the like. Basic geographic information elements are divided into eight categories: location foundation, water system, residential area and facilities, traffic, pipelines, border and administrative area, landform, vegetation and soil property, place name and notes.
It should be understood that the geographic entity dividing method of the present embodiment may be set according to actual requirements, and particularly according to project acceptance tasks, so as to achieve all-in-one experience. In the present embodiment, only the geographical entities included in the common engineering construction projects are taken as examples for explanation, namely, the buildings including real estate, the four roads, the green areas and the top surface. The top surface simply looks down from an aerial perspective the top area of each building, such as a roof or the like.
S2, control leads are comprehensively arranged in the engineering construction project range, and the arrangement of the control leads follows the following principle: and the point cloud data registration of the geographic entities in each region plays a role in linking and controlling error transmission. For example, for static three-dimensional laser scanning on the ground, a three-dimensional laser scanner and a target are directly erected on a wire control point, so that point cloud error accumulation caused by multiple station supporting can be avoided, and the precision is improved. For SLAM backpack three-dimensional laser scanning, the control wire can directly or indirectly provide spatial reference for SLAM point cloud through ground static point cloud, and further point cloud data registration is achieved. For vehicle-mounted mobile three-dimensional laser scanning and unmanned vehicle-mounted three-dimensional laser scanning, the accuracy of the vehicle-mounted mobile three-dimensional laser scanning and the unmanned vehicle-mounted three-dimensional laser scanning is improved by using ground static point clouds, and the control wire can control the error transmission of the ground static point clouds, so that the accuracy of result data is indirectly improved. Therefore, the arrangement of the control wire is mainly considered for the frame station of the ground static three-dimensional laser scanning, the control point is overlapped with the scanning frame station as far as possible, the number of branch stations is reduced, and the accumulation of errors is controlled.
Specifically, the process of comprehensively arranging the control wires in the engineering construction project range comprises the following steps:
and selecting the grade of the control net according to the distribution of the known control points in the measuring area, the landform, the distribution of the scanning target object and the precision requirement, designing the net shape of the control net, and calculating to obtain the initial control points.
And determining a point cloud acquisition mode of each geographic entity according to the types of the geographic entities in the survey area.
According to the point cloud collection mode and the position information of the geographic entity, the following conditions are used as constraint conditions: (1) the total number of control points is minimum, (2) the point cloud data of different areas or different acquisition sources have overlapping quantity meeting the registration requirement, the initial control points are optimized to obtain optimized control points, and control leads are distributed according to the optimized control points.
The control wires may also be set according to the characteristics of the engineering construction project, for example, the control wires are mainly laid for real estate, and the wires basically cover important areas of the engineering construction project. The basic requirements of the control conductors are then as follows:
1) the control net should select the grade of the control net and design the net shape of the control net according to the distribution of the known control points in the measuring area, the topography and the distribution and the precision requirement of the scanning target object.
2) The control point is preferably selected to be near the main scanning target and have a wide field of view.
3) The control network should comprehensively control the scanning area and should also play a role in linking and controlling error transmission in the point cloud data registration of each area when scanning operation is performed in the subareas.
4) In the scanning of small areas or single target objects, a control net can not be laid when the target is closed, but the scanning result is in contact with the existing space reference system. For example, based on the aforementioned control wire example, a small area or single object scanning result point cloud, and a ground static three-dimensional point cloud, a SLAM three-dimensional point cloud, or an unmanned aerial vehicle three-dimensional point cloud (with a definite spatial reference system) find three or more homonymy point pairs for calculating a translation and rotation matrix of spatial transformation between the two point clouds, and finally indirectly establish a connection with the existing spatial reference system.
S3, collecting point cloud data of buildings including real estate by using a wire control point frame station and a directional ground static three-dimensional laser scanner; acquiring point cloud data of roads from four to four of engineering construction projects by adopting a vehicle-mounted three-dimensional laser scanner; collecting point cloud data of a greening area by using a SLAM back-pack three-dimensional laser scanner; and collecting point cloud data of the top surface area from an aerial view angle by adopting an unmanned aerial three-dimensional laser scanner.
Static three-dimensional laser scanner on ground
The process of collecting point cloud data of buildings including real estate by utilizing a lead wire control point erecting station and a directional ground static three-dimensional laser scanner comprises the following steps:
and according to the characteristics of the scanning object, setting up the scanning station by taking the minimum number of the set stations and the minimum distance variance between the scanning stations as constraint conditions, wherein the scanning range of the scanning station covers all buildings including real estate. And initializing scanning stations, and collecting point cloud data of buildings in respective scanning ranges by adopting the scanning stations, wherein the overlapping degree of effective point clouds between adjacent scanning stations is not lower than a minimum overlapping degree threshold value. And naming the scanning station according to the project name, the scanning date and the scanning station number, storing the scanning data, and marking the position of the scanning station on the related engineering drawing of the engineering construction project.
The following is one of the related settings of point cloud data acquisition for the building group of the commercial community:
1) and (3) laying scanning stations:
(a) the scanning station should be located in a safe area with wide view and stable ground.
(b) The scanning range of the scanning station should cover the whole scanning target object, and the scanning station is uniformly distributed, and the number of the stations is as small as possible.
(c) The scanning stations are added when the structure of the target object is complex, the visibility is difficult or the route has corners.
(d) If necessary, a platform can be set up to erect the scanning station.
2) Target layout and coordinate observation:
(a) the targets should be uniformly arranged in the scanning range and have different heights.
(b) The number of targets of each scanning station is not less than 4, and the number of common targets of two adjacent scanning stations is not less than 3.
(c) The distinct feature points may be used as targets.
3) Point cloud data acquisition:
(a) before the operation, the instrument was placed in an observation environment for 30 minutes or more.
(b) The overlapping degree of effective point clouds between adjacent scanning stations is not less than 30%, and the overlapping degree of the effective point clouds between adjacent scanning stations is not less than 15%.
(c) And naming a scanning station according to information such as a project name, a scanning date, a scanning station number and the like, storing scanning data, and marking the position of the scanning station on a large-scale topographic map, a plan map or a sketch.
(d) The scanning station provided with the target is required to identify and accurately scan the target.
(II) vehicle-mounted three-dimensional laser scanner
The vehicle-mounted three-dimensional laser scanner is mainly used for collecting point cloud data of roads from four sides of engineering construction projects, and comprises the following components:
the three-dimensional laser scanner, the GNSS receiver and the inertial navigation sensor are arranged on the mobile surveying vehicle. Before operation, the mobile measuring vehicle is parked in an open area with good GNSS signals, the power supply is switched on, the inertial navigation equipment is started after the satellite is determined to be locked and data recording is started, and after the inertial navigation equipment enters a working state, the vehicle body is kept stable and timing is started, and the inertial navigation equipment enters an initialization state. After initialization is completed, the three-dimensional laser scanner is started, the vehicle runs at a uniform speed, the road scene starts to be scanned in a moving mode, and point cloud data are collected. And after the data acquisition is finished, the three-dimensional laser scanner is closed, the mobile measuring vehicle is parked to the open area again to finish initialization, and then the inertial navigation receiver and the GNSS receiver are closed. And solving three-dimensional laser point cloud by using inertial navigation data and GNSS data and combining with CORS data of a global navigation satellite continuously operating reference station. The correction process of the vehicle-mounted mobile three-dimensional point cloud data and the static three-dimensional point cloud data comprises the following steps: carrying out three-dimensional feature point detection and feature description on the ground static point cloud; for vehicle-mounted mobile laser scanning point clouds, extracting a series of point cloud segments, and detecting three-dimensional characteristic points and describing the characteristics of the three-dimensional characteristic points; matching characteristic points between a point cloud segment at a certain moment and the ground static laser scanning point cloud to find out a plurality of pairs of homonymous points, and further correcting POS data at the moment; and recalculating the vehicle-mounted mobile laser scanning point cloud according to the corrected POS data so as to achieve the purpose of improving the precision.
(III) SLAM back-pack three-dimensional laser scanner
SLAM back of body package three-dimensional laser scanner is used for gathering the point cloud data in afforestation area, includes:
a three-dimensional laser scanner, wide-angle camera, and inertial navigation device are positioned on the SLAM backpack. Before operation, the SLAM backpack is started in a static state, and after the SLAM backpack is started and enters a working state, the backpack is kept stable and enters an initialization state. After initialization is completed, sensors such as a three-dimensional laser scanner and a camera are started, areas with serious shielding conditions such as mobile scanning greening and the like are started, and more than three points of cloud scanned by static three-dimensional laser on the ground are overlapped. And (4) returning the SLAM backpack to the starting place before the data acquisition is finished, so that the scanning path forms a global closed loop. Under the condition that the condition allows, a plurality of local closed rings can be formed in the scanning process, and the data quality is improved. And after the data acquisition is finished, closing the three-dimensional laser scanner, finishing initialization and closing inertial navigation after the initialization is finished. And (4) utilizing an SLAM algorithm and combining inertial navigation data to calculate three-dimensional laser point cloud. And (3) improving the precision of the SLAM three-dimensional laser point cloud by using the ground static laser point cloud, and uniformly converting the SLAM three-dimensional laser point cloud into a national 2000 geodetic coordinate system or a 3-degree strip Gaussian Krigger projection coordinate system. The SLAM three-dimensional point cloud data and the static three-dimensional point cloud data are corrected: carrying out three-dimensional characteristic point detection and characteristic description on the ground static laser scanning point cloud; for SLAM three-dimensional point cloud, extracting a series of point cloud frames according to distance intervals or time intervals, and detecting three-dimensional characteristic points and describing the characteristics of the three-dimensional characteristic points; matching characteristic points between each frame of point cloud and the ground static laser scanning point cloud, finding out a plurality of pairs of homonymous points, and further correcting the pose information of the scanner at the frame time; and recalculating the SLAM three-dimensional laser point cloud according to the corrected sensor pose information to achieve the purpose of improving the precision.
(IV) unmanned aerial vehicle carries three-dimensional laser scanner
The unmanned aerial three-dimensional laser scanner is used for gathering the point cloud data of top surface region from aerial visual angle, includes: and arranging the three-dimensional laser scanner, the camera, the inertial navigation equipment and the GNSS receiver on an unmanned aerial vehicle holder. And planning an unmanned aerial vehicle air route according to the characteristics of the engineering construction project, and preparing the unmanned aerial vehicle for flying. Before taking off, the unmanned aerial vehicle and the carrying sensor thereof are initialized. After initialization is completed, the unmanned aerial vehicle is started to lift off, and meanwhile, sensors such as a three-dimensional laser scanner and a camera are started. And the unmanned aerial vehicle carries out three-dimensional laser scanning from the air along the planned air route to obtain point cloud data. And after the data acquisition is finished, closing the three-dimensional laser scanner, finishing initialization and closing inertial navigation after the initialization is finished. And the unmanned plane returns to the ground and lands, and the original data is derived. And solving three-dimensional laser point cloud by using inertial navigation data and GNSS data and combining with CORS data of a global navigation satellite continuously operating reference station. The correction process of the unmanned aerial vehicle-mounted three-dimensional point cloud data and the static three-dimensional point cloud data comprises the following steps: carrying out three-dimensional characteristic point detection and characteristic description on the ground static laser scanning point cloud; extracting a series of point cloud segments for the unmanned aerial vehicle-mounted laser scanning point cloud, and detecting and describing three-dimensional characteristic points in the same way; matching characteristic points between a point cloud segment at a certain moment and the ground static laser scanning point cloud to find out a plurality of pairs of homonymous points, and further correcting POS data at the moment; and recalculating the unmanned aerial vehicle laser scanning point cloud according to the corrected POS data so as to achieve the purpose of improving the precision.
The embodiment provides four three-dimensional point cloud data acquisition modes and corresponding multi-platform fusion, and the technical effects are as follows: (a) a plurality of observation angles acquire point cloud data, and measurement blind areas are avoided to the maximum extent. (b) The ground static three-dimensional laser scanning is focused on real estate and important areas, and the precision requirement is guaranteed. (c) The vehicle-mounted mobile three-dimensional laser scanning key points aim at the four-road engineering construction project, and the timeliness of data is guaranteed. (d) SLAM knapsack three-dimensional laser scanning is emphatic to afforestation areas such as trees, has guaranteed efficiency and speed. (e) The unmanned aerial vehicle carries three-dimensional laser scanning and focuses on areas such as a roof, and the integrity of data is guaranteed.
And S4, taking the point cloud data of the ground static three-dimensional laser scanner as frame data, sequentially carrying out denoising, rarefying, registering, precision correction and coordinate conversion processing, and fusing all the point cloud data acquired in the step S3.
In the embodiment, a ground static scanning point cloud is taken as a framework, and vehicle-mounted mobile scanning point cloud, SLAM backpack scanning point cloud and unmanned aerial vehicle-mounted scanning point cloud are fused by methods such as denoising, rarefying and registering to form integrated point cloud data integrating air, ground and mobile multiple platforms. The method comprises the following steps:
(a) noise filtering: reflecting points such as system error points, accidental error points, dust birds and the like are identified and removed.
(b) And (3) geometric correction: the SLAM backpack scanning point cloud is easily influenced by self algorithm and inertial navigation accumulated error along with the increase of mileage, deviation and deformation occur, the static scanning point cloud of the ground is used as a correction frame, and the geometric accuracy of the SLAM backpack scanning point cloud is improved in a slicing mode. The vehicle-mounted mobile scanning point cloud and the unmanned vehicle-mounted scanning point cloud can also be processed in the same way when the precision does not meet the requirement.
(c) Intensity correction: and correcting the reflection intensity according to the incidence angle and the transmission distance of the laser scanning.
(d) And (3) coordinate correction: the SLAM backpack is not provided with a GNSS receiver, so that the point cloud obtained by scanning is only of a local coordinate system, and the coordinate conversion is carried out by utilizing a common part between the point cloud and a ground static scanning point cloud.
And S5, analyzing the project acceptance tasks corresponding to the imported project construction projects, and obtaining all acceptance targets corresponding to the project acceptance tasks by taking the geographic entities as basic units.
S6, dividing the fused point cloud data to generate point cloud data of each acceptance target corresponding to the current project acceptance task, constructing geometric figures of all acceptance targets in an all-in-one-measuring database, inputting attribute information according to measurement requirements, and generating an all-in-one-measuring database of the project acceptance task; the method comprises the following steps:
the three-dimensional point cloud data is composed of disordered mass discrete laser points, and can be divided and classified most basically for convenience and fluency of use.
For the generation of the database, one of the important steps is to continue the extraction of the "all-in-one-measurement" element, i.e. to extract the information required for the measurement service from the point cloud.
In the steps, the point cloud is subjected to noise filtering, splicing, resampling, precision correction, coordinate conversion and other preprocessing, so that the directly usable standard format point cloud is formed. For the part of the standard format point cloud, the embodiment can perform batch automatic processing:
firstly, classifying point clouds into ground point clouds and non-ground point clouds by utilizing a progressive triangulation network filtering and cloth simulation filtering algorithm; the non-ground point cloud can be subdivided into a building point cloud, a vegetation point cloud, an independent facility point cloud and the like. Secondly, automatically extracting the equal planes of the wall surface by using a region growing algorithm aiming at non-ground point clouds; automatically classifying and extracting the rod-shaped objects such as lamp poles, electric poles and the like by using a random sampling consistency algorithm; and directly extracting a space graph corresponding to other 'multi-measurement-in-one' elements from the three-dimensional point cloud by using a three-dimensional measurement function of CAD software. And (3) constructing an irregular triangular grid aiming at the ground point cloud, and then interpolating to form a DEM (Digital Elevation Model). And finally, inputting the space graph and various attributes of the 'all-in-one-test' element into an 'all-in-one-test' database to generate an all-in-one-test database required by all-in-one-test. In some examples, the point cloud may also be used to construct a BIM in situations where application requirements and costs are affordable.
Detailed description of the invention
The embodiment provides an all-in-one experience implementation method based on a geographic entity, which includes:
and constructing a building information model corresponding to the engineering design building by utilizing a plan view, a vertical view and a section view of the engineering design building and special item views of fire fighting, heating ventilation and water supply and drainage pipelines, and comprehensively expressing the planning and design condition in three dimensions.
The method is adopted to generate the multi-test-in-one database corresponding to the project acceptance tasks, and the construction current situation is comprehensively expressed in a three-dimensional mode.
The multi-test-in-one database and the building information model are matched and compared, the building structure and the construction precision are comprehensively checked in a three-dimensional scale, and the multi-test-in-one of the indexes required by planning verification, cadastral location and real estate is realized. For example, the contents of the inspection of the building structure include: whether walls, columns, beams, doors, windows, floors and roofs meet the requirements of building design and structural design; the construction precision inspection content comprises the following steps: length, width, thickness, plane position, elevation, layer height, spacing and the like meet the design requirements.
In some examples, the all-in-one implementation method further comprises: and integrating the results of multiple measurements into one to share the three-dimensional integrated data of the ground and the ground. Specifically, aiming at 'multi-measurement-in-one' result, multi-platform point cloud data, a aviation flight orthophoto map, a digital elevation model, a digital topographic map, underground building (structure) general survey data, underground pipeline general survey data, landscaping general survey data, engineering geological general survey data, an inclined three-dimensional model, a building information model and digital documents for planning, examining, approving and checking, a geographical entity is taken as a space carrier, and technologies such as a network geographical information system, a three-dimensional rendering engine, an IFC data standard and the like are integrated into a natural resource large platform, so that the purpose of three-dimensional integrated sharing is achieved.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (10)
1. A project construction project multi-test integrated data acquisition and library building method is used for generating and storing the current situation information of a geographic entity of a project construction project, and is characterized in that the generation method comprises the following steps:
s1, dividing geographic entities in the engineering construction project into four types including buildings, roads, green areas and top surfaces;
s2, control leads are comprehensively arranged in the engineering construction project range, and the arrangement of the control leads follows the following principle: the point cloud data registration of geographic entities in each area plays a role in linking and controlling error transmission;
s3, collecting point cloud data of buildings including real estate by using a wire control point frame station and a directional ground static three-dimensional laser scanner; acquiring point cloud data of roads from four to four of engineering construction projects by adopting a vehicle-mounted three-dimensional laser scanner; collecting point cloud data of a greening area by using a SLAM back-pack three-dimensional laser scanner; collecting point cloud data of a top surface area from an aerial view angle by adopting an unmanned aerial three-dimensional laser scanner;
s4, taking point cloud data of the ground static three-dimensional laser scanner as frame data, sequentially carrying out denoising, rarefying, registering, precision correction and coordinate conversion processing, and fusing all the point cloud data acquired in the step S3;
s5, analyzing the project acceptance tasks corresponding to the imported project construction projects, and obtaining all acceptance targets corresponding to the project acceptance tasks by taking the geographic entities as basic units;
and S6, dividing the fused point cloud data to generate point cloud data of each acceptance target corresponding to the current project acceptance task, constructing geometric figures of all acceptance targets in the all-in-one-to-many-test database, inputting attribute information according to measurement requirements, and generating the all-in-one-to-many-test database of the project acceptance task.
2. The engineering construction project multiple-test-integration data acquisition and library construction method as claimed in claim 1, wherein in the step S2, the process of fully laying control wires in the engineering construction project scope comprises the following steps:
selecting the grade of the control net according to the distribution of known control points in a measuring area, the landform, the distribution of a scanning target object and the precision requirement, designing the net shape of the control net, and calculating to obtain an initial control point;
determining a point cloud acquisition mode of each geographic entity according to the type of the geographic entity in the survey area;
according to the point cloud collection mode and the position information of the geographic entity, the following conditions are used as constraint conditions: (1) the total number of control points is minimum, (2) the point cloud data of different areas or different acquisition sources have overlapping quantity meeting the registration requirement, the initial control points are optimized to obtain optimized control points, and control leads are distributed according to the optimized control points.
3. The method for collecting and warehousing data of engineering construction projects according to claim 1, wherein in step S3, the collecting of point cloud data of buildings including real property by using the wire-controlled point erecting station and the directional ground static three-dimensional laser scanner comprises:
according to the characteristics of a scanning object, setting up a scanning station by taking the minimum number of the set stations and the minimum distance variance between the scanning stations as constraint conditions, wherein the scanning range of the scanning station covers all buildings including real estate;
initializing scanning stations, and collecting point cloud data of buildings in respective scanning ranges by adopting the scanning stations, wherein the overlapping degree of effective point clouds between adjacent scanning stations is not lower than a minimum overlapping degree threshold value;
and naming the scanning station according to the project name, the scanning date and the scanning station number, storing the scanning data, and marking the position of the scanning station on the related engineering drawing of the engineering construction project.
4. The engineering construction project multi-test integration data acquisition and library construction method as claimed in claim 1, wherein in step S3, the process of acquiring point cloud data of the four-to-one road of the engineering construction project by using the vehicle-mounted three-dimensional laser scanner comprises the following steps:
arranging a three-dimensional laser scanner, a GNSS receiver and an inertial navigation sensor on a mobile measuring vehicle;
starting a GNSS receiver in an open area with strong GNSS signals, locking a satellite, starting to record GNSS data, starting inertial navigation equipment to enable the inertial navigation equipment to enter a working state, and initializing to finish the mobile survey vehicle;
starting a three-dimensional laser scanner, driving a vehicle to run at a uniform speed, movably scanning a road scene, and collecting point cloud data of four roads;
turning off the three-dimensional laser scanner, parking the mobile measuring vehicle to an open area again, and turning off the inertial navigation sensor and the GNSS receiver; and solving three-dimensional laser point clouds of the four-to-four roads by utilizing inertial navigation data and GNSS data and combining with CORS data of a global navigation satellite continuously operating reference station.
5. The engineering construction project multi-measurement-in-one data acquisition and library construction method as claimed in claim 1, wherein in step S3, the process of acquiring point cloud data of a green area by using a SLAM backpack three-dimensional laser scanner comprises the following steps:
arranging a three-dimensional laser scanner, a wide-angle camera and inertial navigation equipment on an SLAM backpack; starting the inertial navigation equipment under the static state of the SLAM backpack, and keeping the SLAM backpack stable and entering an initialization state after the SLAM backpack is started and enters a working state;
after initialization is completed, starting a three-dimensional laser scanner and a wide-angle camera, starting to movably scan a greening area, ensuring that more than three points of point clouds scanned by static three-dimensional laser on the ground are overlapped, finally enabling the SLAM backpack to return to a starting place, and forming a global closed ring and M local closed rings on a scanning path; m is greater than or equal to 0;
closing the three-dimensional laser scanner and the inertial navigation equipment;
and (4) solving three-dimensional laser point cloud of the greening area based on a SLAM algorithm and by combining inertial navigation data.
6. The project construction project all-in-one data acquisition and library construction method as claimed in claim 1, wherein in step S3, the process of acquiring the point cloud data of the top surface area from the aerial perspective by using the unmanned on-board three-dimensional laser scanner comprises the following steps:
arranging a three-dimensional laser scanner, a camera, inertial navigation equipment and a GNSS receiver on an unmanned aerial vehicle holder;
planning an unmanned aerial vehicle route according to the characteristics of the engineering construction project, and preparing the unmanned aerial vehicle for flying;
initializing the unmanned aerial vehicle and a carrying sensor thereof; after initialization is completed, starting the unmanned aerial vehicle to lift off, and simultaneously starting the three-dimensional laser scanner, the camera, the inertial navigation equipment and the GNSS receiver; enabling the unmanned aerial vehicle to carry out three-dimensional laser scanning on the engineering construction project from the air along the planned route, and acquiring point cloud data of a top surface area;
turning off the three-dimensional laser scanner, turning off inertial navigation, enabling the unmanned aerial vehicle to return to the home and land, and deriving original data;
and solving the three-dimensional laser point cloud of the top surface area by using inertial navigation data and GNSS data and combining with CORS data of a global navigation satellite continuously operating reference station.
7. The engineering construction project multiple-measurement-in-one data acquisition and library construction method as claimed in claim 1, wherein in step S4, the point cloud data of the ground static three-dimensional laser scanner is used as frame data, and the denoising, thinning, registration, precision correction and coordinate conversion processing are sequentially performed, and the process of fusing all the point cloud data acquired in step S3 comprises:
noise filtering processing is carried out on all point cloud data, and reflection points including system error points, accidental error points and dust flying birds are identified and removed;
taking point cloud data of a ground static three-dimensional laser scanner as frame data, carrying out fragment correction on the point cloud data of a greening area acquired by the SLAM backpack three-dimensional laser scanner based on overlapped point cloud data between the frame data and the frame data, and uniformly converting the point cloud data into a national 2000 geodetic coordinate system or a 3-degree Gauss Kruger projection coordinate system;
correcting the reflection intensity according to the incident angle and the transmission distance of laser scanning;
and identifying the precision of the point cloud data of the four-road and the top surface area, and when the precision of one of the point cloud data and the top surface area does not meet the corresponding minimum precision requirement, taking the point cloud data of the ground static three-dimensional laser scanner as frame data, and performing precision correction and reflection intensity correction on the point cloud data which does not meet the minimum precision requirement.
8. The engineering construction project all-in-one measurement and data acquisition and library construction method according to claim 1, wherein in step S6, the process of dividing the fused point cloud data to generate the point cloud data of each acceptance target corresponding to the current engineering acceptance task, constructing geometric figures of all acceptance targets in the all-in-one measurement and database, inputting attribute information according to measurement requirements, and generating the all-in-one measurement and database of the engineering acceptance task comprises the following steps:
classifying the fused point cloud data into ground point cloud and non-ground point cloud by utilizing a progressive triangulation network filtering and cloth simulation filtering algorithm;
aiming at non-ground point cloud, automatically extracting plane buildings including wall surfaces by using a region growing algorithm; automatically classifying and extracting rod-shaped objects including lamp poles and electric poles by using a random sampling consistency algorithm; directly extracting a space graph corresponding to other multi-measurement-in-one elements from the three-dimensional point cloud by using a three-dimensional mapping function of CAD software;
constructing an irregular triangular grid aiming at the ground point cloud, and interpolating to form a digital elevation model;
and recording the extracted space graph, the ground digital elevation model and various attributes of the ground digital elevation model into an all-in-one database.
9. An all-in-one experience implementation method based on a geographic entity is characterized by comprising the following steps:
constructing a building information model corresponding to the engineering design building by utilizing a plan view, an elevation view and a section view of the engineering design building and special item drawings of fire fighting, heating ventilation and water supply and drainage pipelines;
generating an all-in-one database corresponding to the project acceptance task by adopting the method of any one of claims 1 to 8;
the multi-test-in-one database and the building information model are matched and compared, the building structure and the construction precision are comprehensively checked in a three-dimensional scale, and the multi-test-in-one of the indexes required by planning verification, cadastral location and real estate is realized.
10. The method of claim 9, further comprising:
the method comprises the following steps of taking a geographic entity as a space carrier, and fusing the following data into a natural resource large platform by utilizing a network geographic information system, a three-dimensional rendering engine and an IFC data standard:
the system comprises a multi-measurement-in-one database, multi-platform point cloud data, a aviation flight orthophoto map, a digital elevation model, a digital topographic map, underground building general survey data, underground pipeline general survey data, landscaping general survey data, engineering geology general survey data, an inclined three-dimensional model, a building information model and digital documents for planning, examining and accepting.
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