CN111553017A - BIM-based pavement disease analysis display method and system - Google Patents
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Abstract
The invention discloses a BIM-based pavement disease analysis display method and system, wherein the method comprises the following steps: acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and performing associated storage with the lane and pile number intervals corresponding to the BIM of the highway engineering; acquiring actual elevation data of road surface textures of a road section to be detected, and associating the actual elevation data with corresponding lane and pile number intervals; comparing and analyzing the acquired actual elevation data of the road section to be detected with the stored original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and pile number intervals; and when a pavement disease query request is received, calling an analysis result of the pavement diseases corresponding to the lane and pile number intervals, and displaying the analysis result by combining with the BIM of the highway engineering. The invention realizes the analysis and display of the road surface diseases based on the BIM of the highway engineering and provides convenience for the informatization management of the highway engineering.
Description
Technical Field
The invention relates to highway engineering informatization management, in particular to a pavement disease analysis and display method and system based on BIM.
Background
The highway is an important traffic infrastructure and plays an important role in economic development. After the road is finished and put into use, the service performance of the road is gradually reduced under the action of repeated traffic load and various irresistible natural factors, particularly the continuous increase of traffic volume, the aging of building materials, and defects in construction and design along with the lapse of time.
Many disease problems can occur in the operation of all levels of roads, such as the used asphalt pavement structure, and common diseases such as cracks, ruts, looseness, frost heaving, slurry turning, settlement, crowding, oil bleeding, cracking and slurry pumping and the like under various factors. These problems affect the operation and use of roads, and directly or indirectly affect the development of social economy, such as seriously affecting the driving speed and driving safety, increasing the degree of automobile wear, shortening the service life of asphalt pavements, and the like.
Therefore, the road surface diseases of the road need to be regularly checked and monitored in real time, and the road surface condition is timely determined to ensure the normal operation of the road. With the promotion of the national 'internet plus' strategic demand, digital technologies such as the BIM internet of things and the like are rapidly popularized in the field of civil engineering, and the BIM technology is utilized to analyze and display pavement diseases, so that the improvement of the informatization management of roads is facilitated.
Disclosure of Invention
The embodiment of the invention provides a BIM-based pavement disease analysis and display method, which is used for realizing pavement disease analysis and display and providing convenience for highway engineering information management.
A pavement disease analysis display method based on BIM comprises the following steps: acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and associating the original elevation data with the lane and pile number intervals corresponding to the BIM of the highway engineering; acquiring actual elevation data of road surface textures of a road section to be detected, and associating the actual elevation data with corresponding lane and pile number intervals; comparing and analyzing the acquired actual elevation data of the road section to be detected with the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and the pile number interval; and when a pavement disease query request is received, retrieving a pavement disease analysis result corresponding to the lane and the pile number interval, and displaying by combining with the BIM of the highway engineering.
Further, acquiring the original elevation data of the road surface texture specifically comprises: scanning the road surface of the newly built or maintained road section, and extracting a highway sideline, a lane line, road surface elevation data and image data to form three-dimensional graphic data of the road surface of each road section; and taking the obtained road surface elevation data as original elevation data of the road surface texture, and defining the plane coordinates of the road surface texture according to the actual geographic position coordinates in the scanning process.
Further, the original elevation data are divided according to the lane and pile number intervals, and are associated with the lane and pile number intervals corresponding to the BIM of the highway engineering, and the method specifically comprises the following steps: lane division is carried out according to the extracted highway sidelines and lane lines; dividing pile number intervals according to adjacent pile numbers of the highway and the geographical position coordinates of the pile numbers; and performing associated storage on the original elevation data of the road surface texture and the lane and pile number intervals.
Further, still include: dividing m grids on the road surface of the lane and the pile number interval according to the longitudinal direction and the transverse direction to obtain grid data of the original elevation data of the road surface texture of the lane and the pile number interval; the gridding data of the raw elevation data of all the sampling points in each grid is represented by solving the average value of the raw elevation data of all the sampling points, and the formula is as follows:
wherein,
is the average value of the raw elevation data of the jth grid, j is 1, 2, …, m, n is the number of all sampling points in the jth grid,
i is the raw elevation data of the ith sample point in the jth grid, i is 1, 2, 3, …, n.
Further, obtaining the planar coordinate gridding data of the road surface texture, wherein the planar coordinate gridding data of each grid is represented by solving the average value of the planar coordinates of all sampling points, and the formula is as follows:
wherein,
is the average of the plane coordinates of the jth grid, ((
) Is the plane coordinate of the ith sample point in the jth grid.
Further, the elevation data of the road surface of the road section to be detected is obtained, and is associated with the corresponding lane and pile number interval of the highway engineering BIM, and the method specifically comprises the following steps: the method comprises the steps of scanning the road surface of a road section to be detected, extracting road side lines, lane lines, road surface elevation data and image data, and forming three-dimensional graphic data of the road surface of the road section to be detected; lane division is carried out according to the extracted highway sidelines and lane lines; dividing pile number intervals according to adjacent pile numbers of the highway and the geographical position coordinates of the pile numbers; and performing correlation storage on the elevation data of the road surface texture and the lane and pile number intervals.
Furthermore, dividing m grids on the road surface of the lane and the pile number interval according to the longitudinal direction and the transverse direction to obtain gridded data of the elevation data of the lane and the pile number interval to be detected; the gridding data of the elevation data of all the sampling points in each grid is expressed by calculating the average value of the elevation data of all the sampling points, and the formula is as follows:
wherein,
is the average value of the elevation data of the jth grid, j is 1, 2, …, m, n is the number of all sampling points in the jth grid,
the elevation data of the ith sampling point in the jth grid is shown, i is 1, 2, 3, …, n.
Further, comparing and analyzing the acquired road surface elevation data of the road section to be detected with the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and the pile number interval, which specifically comprises the following steps: comparing and analyzing the average value of the gridding data of the elevation data of a certain lane and a certain pile number interval with the average value of the gridding number of the original elevation data of the certain lane and the certain pile number interval, and if the difference value of the two is greater than a preset threshold value, generating an analysis result that diseases exist in the certain lane and the certain pile number interval; wherein the average value of the gridding number of the original elevation data is obtained by averaging the original elevation data of each grid
Averaging to obtain; mean value of gridded data of elevation data by averaging elevation data for each grid
And averaging to obtain the average value.
Further, comparing and analyzing the acquired road surface elevation data of the road section to be detected with the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and the pile number interval, which specifically comprises the following steps: gridding data of elevation data of a certain lane and a certain pile number interval
Gridding data of the original elevation data between the lane and the pile number
And comparing and analyzing, and if the difference value of the two is greater than a preset threshold value, generating an analysis result that the disease exists in the jth grid of a certain lane and a certain stake interval.
The invention further provides a BIM-based pavement disease analysis display system, which comprises a client and a server, wherein the client is used for sending a pavement disease query request to the server, receiving a corresponding pavement disease analysis result fed back by the server and displaying the pavement disease analysis result; the server is used for storing original elevation data of road surface textures associated with lanes and pile number intervals corresponding to the BIM of the highway engineering; comparing and analyzing the obtained actual road surface texture elevation data associated with the lane and pile number intervals of the road surface of the road section to be detected with the corresponding original road surface texture elevation data to generate an analysis result of the road surface diseases of the lane and pile number intervals; and according to the received pavement disease query request, calling the analysis result of the pavement diseases corresponding to the lane and the pile number interval and pushing the analysis result to the client.
Further, the server includes: the storage module is used for acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and performing associated storage with the lane and pile number intervals corresponding to the BIM of the highway engineering; the analysis module is used for comparing and analyzing the acquired gridded data of the actual elevation data associated with the lane and pile number intervals of the road section to be detected with the gridded data of the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and pile number intervals; and the query response module is used for calling the analysis results of the road surface diseases corresponding to the lane and the pile number interval according to the received road surface disease query request and pushing the analysis results to the client.
Comparing and analyzing the road surface texture elevation data of the section of the lane and the section of the pile number to be detected with the original elevation data of the road surface texture to generate a road surface disease analysis result, and displaying the road surface disease analysis result by combining with the BIM of the highway engineering; the analysis and display of the road surface diseases are realized, and convenience is provided for the information management of the highway engineering.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a system architecture for analyzing and displaying pavement diseases based on BIM in the embodiment of the present invention;
FIG. 2 is a schematic flow chart of a BIM-based pavement disease analysis display method in the embodiment of the invention;
FIG. 3 is a schematic flow chart illustrating a process for acquiring raw elevation data of a road surface according to an embodiment of the present invention;
FIG. 4 is a schematic view of a pavement damage analysis process according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of a road surface condition display according to an embodiment of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention. As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Building Information Modeling (BIM) is an Information model applied to Building full-life cycle management, and based on various relevant Information data of a Building engineering project, data of a Building in each stage of design, construction, operation and the like can be stored in the BIM so as to realize fine and Information management of the Building industry. The Geographic Information System (GIS) is a spatial Information System that can collect, store, manage, compute, analyze, display, and describe relevant Geographic distribution data in the whole or part of the earth's surface space, and display and analyze spatial Information in a large scene, and has the advantages of rapidness and intuition.
The BIM may also be called other names, such as Building Information management (Building Information management) or Building Information manufacturing (Building Information management), etc., and the present application is not limited thereto. The BIM is based on various relevant information data of a construction project, simulates real information of a building such as a highway through digital information simulation and a three-dimensional building model, and achieves functions of project supervision, equipment management, digital processing and the like. GIS may also be referred to by other names, such as geographic Information systems (Geo-Information systems), geosciences Information systems, and the like.
In this embodiment, the road engineering BIM system generally refers to: aiming at the whole period of highway engineering design, the digital, informationized and intelligent integrated solution system for highway engineering design and management based on technologies such as GIS, BIM and internet provides a platform and data support for construction, operation and maintenance BIM application and value mining. In order to realize the consistency of the highway engineering BIM and the real environment, a highway engineering BIM model can be generally established by oblique photography or forward projection technology.
Referring to fig. 1, a system architecture of an embodiment of the present invention is schematically illustrated, and the system architecture includes: the system comprises a highway engineering BIM system client and a highway engineering BIM system server; the BIM system server for the highway engineering comprises a server and a database, wherein the database stores original elevation data of road surface textures, and the original elevation data are associated with a lane and a pile number interval. The server disclosed in this embodiment may be specifically a workstation, a super computer, or a server cluster for data processing, which is composed of multiple servers. The client in this embodiment may access the server through a WEB end or app end application. The database of the original elevation data of the road surface textures is used for storing the original elevation data of the road surface textures, and the original elevation data are the elevation data of a healthy road surface. In this embodiment, the highway engineering BIM system refers to: aiming at the whole period of highway engineering design, the integrated solution of digital, informationized and intelligent highway engineering design and management based on the technologies such as BIM, GIS, Internet and the like. Highway engineering GIS systems generally refer to: a road engineering management informatization system integrated with a Geographic Information System (GIS) technology. In order to realize the consistency of the highway engineering BIM and the real environment, a highway engineering BIM model can be generally established by oblique photography or forward projection technology.
As shown in fig. 2, the method for analyzing and displaying pavement diseases based on BIM in the embodiment of the present invention includes: acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and associating the original elevation data with the lane and pile number intervals corresponding to the BIM of the highway engineering; acquiring actual elevation data of road surface textures of a road section to be detected, and associating the actual elevation data with corresponding lane and pile number intervals; comparing and analyzing the acquired actual elevation data of the road section to be detected with the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and the pile number interval; and when a pavement disease query request is received, retrieving a pavement disease analysis result corresponding to the lane and the pile number interval, and displaying by combining with the BIM of the highway engineering.
Referring to fig. 3, the present embodiment obtains raw elevation data of a road surface texture. And scanning the road surface of the newly built or maintained road section through a laser radar and/or a camera, extracting a road side line, a lane line, road surface elevation data and image data, and forming three-dimensional graphic data (a road surface BIM (building information model) map layer) of the road surface of each road section. The extraction of the road surface elevation data can be realized by the following steps: and acquiring three-dimensional coordinates of each sampling point in the road surface point cloud data, wherein the point cloud data comprises three-dimensional coordinate information of each sampling point, the three-dimensional coordinates comprise X-axis coordinates, Y-axis coordinates and Z-axis coordinates, and the Z-axis coordinates are used for expressing the height of the road surface to be extracted, namely the Z-axis coordinates of each sampling point are the elevation data of the sampling point. The point cloud data may be obtained by a laser measurement principle, may be obtained by a photogrammetry principle, or may be obtained by combining a laser measurement principle and a photogrammetry principle. And judging whether the sampling point belongs to the road surface or not according to the three-dimensional coordinates of each sampling point in the point cloud data. For example, whether the structural relationship between the sampling point and other surrounding sampling points satisfies a condition for constituting the road surface or not may be determined, or whether a plane constituted by a certain portion of the sampling points in the point cloud data satisfies the condition for constituting the road surface may be determined, where the condition for constituting the road surface may be a plurality of preset conditions, for example, whether elevation data of a certain portion of a plurality of sampling points are average and continuous or whether changes in elevation data of a certain portion of a plurality of sampling points are linear, and the average is continuously increased or average is continuously decreased. And in the point cloud number of the road surface obtained by the vehicle-mounted laser radar, the road and the lane line can be distinguished and extracted according to the lane line detection performed by the reflection intensity value. Removing noise points from the road surface image data, packaging, splicing, filling and repairing to form road surface three-dimensional graphic data (a road surface BIM layer); and associating the three-dimensional road graphic data with the lane and the stake mark interval.
And taking the extracted elevation data of the road surface texture as original elevation data of the road surface texture, wherein the original elevation data can be taken as elevation data of a healthy road surface. The actual geographic position coordinates acquired in the scanning process can be converted into plane coordinates (position coordinates) of the original elevation data of the road surface texture, so that the original elevation data of the road surface texture can be correspondingly associated with the lane and the stake mark interval and correspond to the subsequent road surface position coordinates of the road section to be detected. In addition, the road surface three-dimensional graphics (road surface BIM graphic layers) of each acquired road section can be divided and stored according to the lane and stake mark sections according to the actual geographic position coordinates, and are superposed on the road surface of the corresponding lane and stake mark sections of the road engineering BIM generated by oblique photography or orthographic photography.
The original elevation data of the road texture can be divided as required, for example, the original elevation data can be divided according to the lane and the pile number interval, and is associated with the lane and the pile number interval corresponding to the BIM of the highway engineering. Lane division is carried out according to the extracted highway sidelines and lane lines; the method can divide the pile number interval according to the adjacent pile numbers of the highway and the geographical position coordinates of the pile numbers; and performing associated storage on the original elevation data of the road surface texture and the lane and pile number intervals.
The method comprises the steps of establishing gridding data for original elevation data of sampled road surface textures, and carrying out gridding division on the original elevation data in the longitudinal direction and the transverse direction of a road by adopting a data gridding algorithm according to a certain grid size to obtain gridding data of the original elevation data of the road surface textures. One or more sampling points in the point cloud data are respectively included in each grid. The grid size can be set as required, for example, a size of 0.25m × 0.25 m. In one example, m grids are divided longitudinally and transversely on the road surface of a certain lane and a certain pile number section to obtain grid data of original elevation data of the road surface texture of the lane and the pile number section; the gridding data of the raw elevation data of all the sampling points in each grid is represented by solving the average value of the raw elevation data of all the sampling points, and the formula is as follows:
wherein,
is the average value of the raw elevation data of the jth grid, j is 1, 2, …, m, n is the number of all sampling points in the jth grid,
i is the raw elevation data of the ith sample point in the jth grid, i is 1, 2, 3, …, n.
Obtaining the plane coordinate gridding data of the road surface texture, wherein the plane coordinate gridding data of each grid is represented by solving the average value of plane coordinates of all sampling points, and the formula is as follows:
wherein,
is the average of the plane coordinates of the jth grid, ((
) Is the plane coordinate of the ith sample point in the jth grid.
M grids can be divided in a certain lane and pile number interval, and the elevation data of the certain lane and pile number interval can be obtained by averaging the elevation data of each grid in the m grids
(j is a natural number of 1, 2, 3, …, m), and the average value is taken to represent the average value. The formula is as follows:
wherein
The average value of the original elevation data of a certain lane and pile number interval is obtained.
Referring to fig. 4, in the present embodiment, actual elevation data of a road surface of a road section to be detected is obtained and associated with a corresponding lane and a corresponding pile number interval. Specifically, scanning the road surface of the road section to be detected through a laser radar and/or a camera, extracting a road side line, a lane line, road surface elevation data and image data, and forming three-dimensional graphic data (a road surface BIM layer) of the road surface of the road section to be detected; lane division is carried out according to the extracted highway sidelines and lane lines; dividing pile number intervals according to adjacent pile numbers of the highway and the geographical position coordinates of the pile numbers; and performing associated storage on the elevation data of the road surface texture of the road section to be detected and the lane and pile number interval. Dividing and storing the acquired road surface three-dimensional graph (road surface BIM layer) of the road section to be detected according to the lane and pile number intervals.
Establishing gridded data for the sampled elevation data of the road surface texture of the road section to be detected, and carrying out gridding division on the elevation data in the longitudinal direction and the transverse direction of the road by adopting a data gridding algorithm according to a certain grid size to obtain gridded data of the elevation data of the road surface texture. The grid size is set according to actual needs, for example, the original height number grid size is adopted, so that the comparison and analysis between the elevation data of the road surface texture of the road section to be detected and the original elevation data are facilitated.
In one example, a road surface of a lane and a pile number section to be detected is divided into m grids according to the longitudinal direction and the transverse direction, and gridded data of elevation data of road surface textures of the lane and the pile number section to be detected is obtained; the gridding data of the elevation data of all the sampling points in each grid is expressed by calculating the average value of the elevation data of all the sampling points, and the formula is as follows:
wherein,
is the average value of the elevation data of the jth grid, j is 1, 2, …, n is the number of all sampling points in the jth grid,
the elevation data of the ith sampling point in the jth grid is shown, i is 1, 2, 3, …, n.
Obtaining the grid data of the plane coordinates of the road surface to be detected, wherein the grid data of the plane coordinates of each grid is represented by solving the average value of the plane coordinates of all sampling points, and the formula is as follows:
wherein,
is the average of the plane coordinates of the jth grid, ((
) Is the plane coordinate of the ith sample point in the jth grid.
In this example, by
And
the comparison between the original data and the standard data can be used for correlating the corresponding relation between the gridding data of the elevation data of the road surface to be detected and the gridding data of the original elevation data.
In one example, m grids can be divided in a certain lane and pile number interval, and the elevation data of the certain lane and pile number interval can be obtained by averaging the elevation data of each grid in the m grids
(j is a natural number of 1, 2, 3, …, m), and the average value is taken to represent the average value. The formula is as follows:
wherein,
the average value of the elevation data of a certain lane and a certain stake mark interval to be detected is obtained.
In this example, the obtained road surface elevation data of the road section to be detected is compared with the original elevation data for analysis, and an analysis result of the road surface diseases corresponding to the lane and the pile number interval is generated. In one example, the average value of the gridding data of the elevation data of a certain lane and a certain pile number interval is compared with the average value of the gridding number of the original elevation data of the certain lane and the certain pile number interval for analysis, and if the difference value between the average value and the gridding number of the original elevation data of the certain lane and the pile number interval is greater than a preset threshold value, an analysis result that a disease exists in the certain lane and the certain pile number interval is generated; wherein the average value of the gridding number of the original elevation data is obtained by averaging the original elevation data of each grid
Averaging to obtain; mean value of gridded data of elevation data by averaging elevation data for each grid
And averaging to obtain the average value. In another example, the grid data of the elevation data of a certain lane and a certain stake mark interval
Gridding data of the original elevation data between the lane and the pile number
And comparing and analyzing, and if the difference value of the two is greater than a preset threshold value, generating an analysis result that the disease exists in the jth grid of a certain lane and a certain stake interval. The disease types of the grids can be further distinguished according to a preset threshold interval.
In this embodiment, when a pavement disease query request is received, a pavement disease analysis result corresponding to a lane and a pile number interval is obtained, and the road disease analysis result is displayed by combining with the highway engineering BIM. Specifically, when a pavement disease query request is received, correlating an analysis result of a corresponding road segment pavement disease according to road segment pavement information to be queried in the pavement disease query request, wherein the road segment pavement information comprises a lane and a stake mark interval; and loading the corresponding road surface disease analysis result to the road surface of the corresponding lane and pile number section of the BIM of the highway engineering for displaying according to the lane and pile number section of the road section road surface information. And when the analysis result of the diseases exists, acquiring three-dimensional graphic data of the road surface of the road section to be detected in the lane and pile number section, and displaying the three-dimensional graphic data by superimposing the three-dimensional graphic data on the road surface in the corresponding lane and pile number section of the highway engineering BIM generated by oblique photography or orthographic photography.
Inputting a pavement damage query request in a client query interface of a highway engineering BIM system, or clicking a lane in a certain stake mark interval in a highway engineering BIM display interface of the highway engineering BIM system to trigger the pavement damage query request, wherein the damage query request comprises road section pavement information such as lanes, stake mark intervals and the like; and the highway engineering BIM system server calls corresponding highway section pavement disease analysis results according to the highway section pavement information of the received pavement disease query request, and pushes the corresponding highway section pavement disease analysis results to the client, wherein the highway section pavement information comprises lane and pile number intervals. When the analysis result of the diseases exists, the three-dimensional graphic data of the road surface of the road section to be detected in the lane and pile number interval can be further obtained and pushed to the client side for loading and displaying.
Please refer to fig. 5, which shows a schematic view of a road surface condition; the obtained parameters such as the road surface service performance index PQI, the road surface damage condition index PCI, the road surface rutting depth index RDI, the measured road surface structural strength index PSSI, the road surface driving quality evaluation RQI, the road surface anti-skid performance index SRI and the like can be displayed in an interface of a BIM system of the highway engineering.
Another embodiment of the invention provides a BIM-based pavement disease analysis and display system, which comprises a client and a server. And the client is used for sending a pavement disease query request to the server, receiving a corresponding road pavement disease analysis result fed back by the server, and displaying the road pavement disease analysis result by combining with the BIM of the highway engineering. The server is used for acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and performing associated storage with the lane and pile number intervals corresponding to the BIM of the highway engineering; comparing and analyzing the acquired actual elevation data associated with the lane and pile number intervals of the road section to be detected with the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and pile number intervals; and according to the received pavement disease query request, calling the analysis result of the pavement diseases corresponding to the lane and the pile number interval and pushing the analysis result to the client. In this embodiment, the laser radar and/or the camera may be used to scan the road surface of the road section, extract the side line of the road, the lane line, the road surface elevation data, and the image data, and form three-dimensional graphic data (the BIM map layer of the road surface) of each road section. The method comprises the steps of establishing gridding data for original elevation data of sampled road surface textures, and carrying out gridding division on the original elevation data in the longitudinal direction and the transverse direction of a road by adopting a data gridding algorithm according to a certain grid size to obtain gridding data of the original elevation data of the road surface textures. One or more sampling points in the point cloud data are respectively included in each grid. The grid size can be set as required, for example, a size of 0.25m × 0.25 m. Establishing gridded data for the sampled elevation data of the road surface texture of the road section to be detected, and carrying out gridding division on the elevation data in the longitudinal direction and the transverse direction of the road by adopting a data gridding algorithm according to a certain grid size to obtain gridded data of the elevation data of the road surface texture. The grid size is set according to actual needs, for example, the original height number grid size is adopted, so that the comparison and analysis between the elevation data of the road surface texture of the road section to be detected and the original elevation data are facilitated. The gridding data of the road surface texture elevation data of the section of the lane and the section of the pile number to be detected and the gridding data of the original elevation data of the road surface texture are compared and analyzed, a road surface disease analysis result is generated and displayed in combination with the highway engineering BIM, the analysis and the display of the road surface disease are realized, and convenience is provided for the highway engineering information management. The concrete flow of the pavement disease analysis in this embodiment can be referred to in detail in the method embodiment above.
The server side comprises: the storage module is used for acquiring original elevation data of the texture of the healthy road surface, dividing the original elevation data of the texture of the road surface according to the lane and pile number intervals, and performing associated storage with the lane and pile number intervals corresponding to the BIM of the highway engineering; the analysis module is used for comparing and analyzing the acquired gridded data of the actual elevation data associated with the lane and pile number intervals of the road section to be detected with the gridded data of the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and pile number intervals; and the query response module is used for calling the analysis results of the road surface diseases corresponding to the lane and the pile number interval according to the received road surface disease query request and pushing the analysis results to the client.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A pavement disease analysis display method based on BIM is characterized by comprising the following steps:
acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and performing associated storage with the lane and pile number intervals corresponding to the BIM of the highway engineering;
acquiring actual elevation data of road surface textures of a road section to be detected, and associating the actual elevation data with corresponding lane and pile number intervals; comparing and analyzing the acquired actual elevation data of the road section to be detected with the stored original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and pile number intervals;
when a pavement disease inquiry request is received, the analysis result of the pavement diseases corresponding to the lane and the pile number interval is called and displayed by combining with the BIM of the highway engineering,
acquiring original elevation data of road surface textures, specifically comprising:
scanning the road surface of the newly built or maintained road section, and extracting a highway sideline, a lane line, road surface elevation data and image data to form three-dimensional graphic data of the road surface of each road section;
the obtained road surface elevation data is used as the original elevation data of the road surface texture, the plane coordinates of the road surface texture are defined according to the actual geographic position coordinates obtained in the scanning process,
the original elevation data are divided according to the lane and pile number intervals, and are associated with the lane and pile number intervals corresponding to the BIM of the highway engineering, and the method specifically comprises the following steps:
lane division is carried out according to the extracted highway sidelines and lane lines; dividing pile number intervals according to adjacent pile numbers of the highway and the geographical position coordinates of the pile numbers; the original elevation data of the road surface texture is stored in association with the lane and the pile number interval,
further comprising:
dividing m grids on the road surface of the lane and the pile number interval according to the longitudinal direction and the transverse direction to obtain grid data of the original elevation data of the road surface texture of the lane and the pile number interval;
the gridding data of the raw elevation data of all the sampling points in each grid is represented by solving the average value of the raw elevation data of all the sampling points, and the formula is as follows:
wherein,
is the average value of the raw elevation data of the jth grid, j is 1, 2, …, m, n is the number of all sampling points in the jth grid,
i is the raw elevation data of the ith sample point in the jth grid, i is 1, 2, 3, …, n.
2. The BIM-based pavement disease analysis and display method according to claim 1, further comprising:
obtaining the plane coordinate gridding data of the road surface texture, wherein the plane coordinate gridding data of each grid is represented by solving the average value of plane coordinates of all sampling points, and the formula is as follows:
wherein,
is the average of the plane coordinates of the jth grid, ((
) Is the plane coordinate of the ith sample point in the jth grid.
3. The BIM-based pavement disease analysis and display method according to claim 2, wherein the actual elevation data of the road surface of the road section to be detected is obtained and associated with the corresponding lane and pile number interval, specifically comprising,
the method comprises the steps of scanning the road surface of a road section to be detected, extracting road side lines, lane lines, road surface elevation data and image data, and forming three-dimensional graphic data of the road surface of the road section to be detected;
lane division is carried out according to the extracted highway sidelines and lane lines; dividing pile number intervals according to adjacent pile numbers of the highway and the geographical position coordinates of the pile numbers; and performing correlation storage on the actual elevation data and the lane and pile number intervals.
4. The BIM-based pavement disease analysis and display method according to claim 3, further comprising:
dividing m grids on the road surface of the lane and the pile number interval according to the longitudinal direction and the transverse direction to obtain gridding data of the elevation data of the lane and the pile number interval to be detected;
the gridding data of the elevation data of all the sampling points in each grid is expressed by calculating the average value of the elevation data of all the sampling points, and the formula is as follows:
wherein,
is the average value of the elevation data of the jth grid, j is 1, 2, …, m, n is the number of all sampling points in the jth grid,
the elevation data of the ith sampling point in the jth grid is shown, i is 1, 2, 3, …, n.
5. The BIM-based pavement disease analysis and display method according to claim 4, wherein the analysis of the obtained pavement elevation data of the road section to be detected and the original elevation data is performed by comparison, so as to generate an analysis result of the pavement disease corresponding to the lane and pile number interval, and the analysis method specifically comprises the following steps:
comparing and analyzing the average value of the gridding data of the elevation data of a certain lane and a certain pile number interval with the average value of the gridding number of the original elevation data of the certain lane and the certain pile number interval, and if the difference value of the two is greater than a preset threshold value, generating an analysis result that diseases exist in the certain lane and the certain pile number interval;
wherein the average value of the gridding number of the original elevation data is obtained by averaging the original elevation data of each grid
Averaging to obtain; mean value of gridded data of elevation data by averaging elevation data for each grid
And averaging to obtain the average value.
6. The BIM-based pavement disease analysis and display method according to claim 4, wherein the analysis of the obtained pavement elevation data of the road section to be detected and the original elevation data is performed by comparison, so as to generate an analysis result of the pavement disease corresponding to the lane and pile number interval, and the analysis method specifically comprises the following steps:
gridding data of elevation data of a certain lane and a certain pile number interval
Gridding data of the original elevation data between the lane and the pile number
And comparing and analyzing, and if the difference value of the two is greater than a preset threshold value, generating an analysis result that the disease exists in the jth grid of a certain lane and a certain stake interval.
7. The BIM-based pavement disease analysis and display method according to claim 5, wherein when a pavement disease query request is received, obtaining a pavement disease analysis result corresponding to a lane and a pile number interval, and displaying by combining with a highway engineering BIM, specifically comprising:
receiving a pavement disease query request, and associating a corresponding road segment pavement disease analysis result according to road segment pavement information to be queried in the pavement disease query request, wherein the road segment pavement information comprises a lane and a pile number interval;
and loading the corresponding road surface disease analysis result to the road surface of the corresponding lane and pile number section of the BIM of the highway engineering for displaying according to the lane and pile number section of the road section road surface information.
8. The utility model provides a road surface disease analysis display system based on BIM which characterized in that, includes client and server:
the client is used for sending a pavement disease query request to the server, receiving a corresponding road pavement disease analysis result fed back by the server and displaying the road pavement disease analysis result;
the server is used for acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and performing associated storage with the lane and pile number intervals corresponding to the BIM of the highway engineering; comparing and analyzing the acquired actual elevation data associated with the lane and pile number intervals of the road section to be detected with the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and pile number intervals; and according to the received pavement disease query request, calling the analysis result of the pavement diseases corresponding to the lane and the pile number interval and pushing the analysis result to the client.
9. The BIM-based pavement damage analysis and display system of claim 8, wherein the server specifically comprises:
the storage module is used for acquiring original elevation data of the road surface texture, dividing the original elevation data of the road surface texture according to the lane and pile number intervals, and performing associated storage with the lane and pile number intervals corresponding to the BIM of the highway engineering;
the analysis module is used for comparing and analyzing the acquired gridded data of the actual elevation data associated with the lane and pile number intervals of the road section to be detected with the gridded data of the original elevation data to generate an analysis result of the road surface diseases corresponding to the lane and pile number intervals;
and the query response module is used for calling the analysis results of the road surface diseases corresponding to the lane and the pile number interval according to the received road surface disease query request and pushing the analysis results to the client.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112783997A (en) * | 2021-01-12 | 2021-05-11 | 东北大学 | Highway pavement auditing system and method |
| CN113537526A (en) * | 2021-07-26 | 2021-10-22 | 江苏燕宁工程科技集团有限公司 | BIM-based highway engineering inspection processing method and system |
| CN114004950A (en) * | 2021-10-29 | 2022-02-01 | 深圳大学 | Intelligent pavement disease identification and management method based on BIM and LiDAR technology |
| CN114049618A (en) * | 2022-01-12 | 2022-02-15 | 河北工业大学 | Graph-point-graph transformation-based pavement three-dimensional disease PCI calculation method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106123845A (en) * | 2015-05-07 | 2016-11-16 | 国家测绘地理信息局第六地形测量队 | Slope displacement monitoring method based on three-dimensional laser scanning technique |
| CN108595677A (en) * | 2018-04-28 | 2018-09-28 | 四川隧唐科技股份有限公司 | Road disease methods of exhibiting and device, electronic equipment, computer read/write memory medium |
| CN109800502A (en) * | 2019-01-17 | 2019-05-24 | 重庆交通大学 | A kind of zone marker method, apparatus and electronic equipment |
| CN110700056A (en) * | 2019-10-18 | 2020-01-17 | 长安大学 | Asphalt pavement disease monitoring system and monitoring method |
-
2020
- 2020-07-09 CN CN202010655690.XA patent/CN111553017B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106123845A (en) * | 2015-05-07 | 2016-11-16 | 国家测绘地理信息局第六地形测量队 | Slope displacement monitoring method based on three-dimensional laser scanning technique |
| CN108595677A (en) * | 2018-04-28 | 2018-09-28 | 四川隧唐科技股份有限公司 | Road disease methods of exhibiting and device, electronic equipment, computer read/write memory medium |
| CN109800502A (en) * | 2019-01-17 | 2019-05-24 | 重庆交通大学 | A kind of zone marker method, apparatus and electronic equipment |
| CN110700056A (en) * | 2019-10-18 | 2020-01-17 | 长安大学 | Asphalt pavement disease monitoring system and monitoring method |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112783997A (en) * | 2021-01-12 | 2021-05-11 | 东北大学 | Highway pavement auditing system and method |
| CN113537526A (en) * | 2021-07-26 | 2021-10-22 | 江苏燕宁工程科技集团有限公司 | BIM-based highway engineering inspection processing method and system |
| CN114004950A (en) * | 2021-10-29 | 2022-02-01 | 深圳大学 | Intelligent pavement disease identification and management method based on BIM and LiDAR technology |
| CN114004950B (en) * | 2021-10-29 | 2024-01-19 | 深圳大学 | BIM and LiDAR technology-based intelligent pavement disease identification and management method |
| CN114049618A (en) * | 2022-01-12 | 2022-02-15 | 河北工业大学 | Graph-point-graph transformation-based pavement three-dimensional disease PCI calculation method |
| CN114049618B (en) * | 2022-01-12 | 2022-03-22 | 河北工业大学 | Graph-point-graph transformation-based pavement three-dimensional disease PCI calculation method |
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