CN116993923B - Three-dimensional model making method, system, computer equipment and storage medium for converter station - Google Patents
Three-dimensional model making method, system, computer equipment and storage medium for converter station Download PDFInfo
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Abstract
The invention provides a three-dimensional model making method, a system, computer equipment and a storage medium of a converter station, which are characterized in that through carrying out repeated processing on point cloud data, a more accurate point cloud model and data of each aspect of the point cloud model are obtained, preliminary preparation is carried out for the subsequent 3d modeling, and then the three-dimensional modeling is carried out after carrying out contour correction on the point cloud model according to a 2d drawing.
Description
Technical Field
The application relates to the technical field of visualization of converter stations, in particular to a three-dimensional model manufacturing method of a converter station.
Background
Converter stations are important facilities in electrical power systems for achieving a mutual conversion between alternating current and direct current. Since the converter station is a complex electric facility, it is difficult to fully understand and present its complex structure and arrangement using conventional two-dimensional plan views. The three-dimensional acquisition modeling technology can present the converter station in a three-dimensional form, so that operation and maintenance personnel, designers and decision makers can more intuitively know the spatial structure of the converter station, the relation among components and the operation flow. Through the virtualization mode, different operation scenes can be simulated, and people can be helped to make more accurate and effective decisions.
While the performance and operating conditions of the converter station are closely related to its spatial arrangement and structure. Accurate spatial data of the converter station can be obtained through a three-dimensional acquisition modeling technology, and analysis is carried out by combining sensor data, so that potential problems can be identified and operation can be optimized. For example, thermal analysis may be performed to determine hot spot areas and improve heat exchange efficiency; performing electromagnetic field analysis, optimizing the device arrangement to reduce interference; impact analysis is performed to evaluate the shock resistance of the apparatus, etc. The three-dimensional acquisition modeling technology provides a more accurate foundation for the design and construction of the converter station. By acquiring the real space information of the converter station, simulation and optimization of design and construction can be performed, and design defects and construction conflicts are avoided. In addition, the models can be used for visual display and collaboration, facilitating communication and collaboration among designers, engineers and constructors. Operation and maintenance of the converter stations requires monitoring and analysis of the status of the equipment. The three-dimensional acquisition modeling technology can provide high-precision equipment geometric and texture information, and equipment state monitoring and prediction can be carried out by combining sensor data. Therefore, intelligent operation and maintenance management can be realized, and the reliability and maintenance efficiency of the equipment are improved.
In summary, the development of the three-dimensional acquisition modeling technology of the converter station can provide comprehensive visual representation, accurate spatial data and virtualized analysis capability, is beneficial to work in the aspects of design, construction, operation, maintenance and the like, and improves the efficiency and reliability of the converter station.
However, when the existing 3d modeling technology is used for modeling the converter station, because the environment of the converter station is complex, the existing facility also has modeling objects with irregular sizes, positions and shapes such as buildings, so that the difficulty of modeling the 3d of the converter station is high, and the cost of manpower and time is high when the existing 3d modeling technology is used for modeling, the technology capable of rapidly realizing the modeling of the converter station is urgently needed.
Disclosure of Invention
The embodiment of the invention provides a three-dimensional model manufacturing method of a converter station, which is used for at least solving the problem of high cost of building the three-dimensional model of the converter station in the related technology.
According to an embodiment of the present invention, there is provided a three-dimensional model production method of a converter station, the method including:
acquiring point cloud data obtained after measuring the converter station through measuring equipment;
performing data accuracy processing on the point cloud data to obtain first point cloud data;
3d preprocessing is carried out on the first point cloud data, and the first point cloud data is output as a point cloud model;
outputting the point cloud model into a 3d software first format file;
carrying out contour correction on the point cloud model based on preset 2d contour data to obtain a target model after contour correction, wherein the 2d contour data is obtained by carrying out graph-to-digital conversion on 2d drawing data, and the target contour data included in the 2d contour data are mutually constrained;
and carrying out three-dimensional modeling according to the target model after contour correction.
Further, the performing contour correction on the modeled three-dimensional model based on the preset 2d contour data specifically includes:
acquiring multidirectional 2d drawing data of the converter station;
performing graph-digital conversion processing on the 2d drawing data from a first direction to obtain 2d profile data of the converter station in the first direction;
adjusting the position data of the three-dimensional model to enable the coincidence ratio of the position data of the three-dimensional model and the 2d profile data to meet a first condition, wherein the first condition comprises the highest coincidence ratio;
and under the condition that the contact ratio meets a first condition, correcting the three-dimensional model according to the 2d contour data.
Further, the processing the data accuracy of the point cloud data specifically includes:
registering and registering the point cloud data;
filtering and denoising the point cloud data;
and carrying out segmentation and feature extraction processing on the point cloud data.
Further, the method comprises the steps of,
the 3d preprocessing of the point cloud data after the data accuracy processing specifically comprises the following steps:
performing model generation and reconstruction on the point cloud data subjected to data accuracy processing by using 3d software to generate a point cloud model;
and analyzing the point cloud model generated and reconstructed by the model to obtain specific parameter data of the point cloud model.
Further, the method comprises the steps of,
analyzing the point cloud model after the model generation and reconstruction to obtain specific parameter data of the point cloud model comprises the following steps:
acquiring acquisition characteristics and cloud point characteristics of the point cloud data, wherein the acquisition characteristics comprise energy characteristics in the process of acquiring the point cloud data, and the cloud point characteristics comprise brightness and/or thickness degree of cloud points in the point cloud data;
and determining model features of a point cloud model according to the energy features, wherein the model features at least comprise any one of surface roughness and texture features of the converter station, and the specific parameter data comprise the model features.
Further, the adjusting the position of the three-dimensional model until the position with the highest degree of coincidence with the 2d contour specifically includes:
adjusting the proportion of the 2d profile and the proportion of the three-dimensional model to the same proportion;
when the three-dimensional model is adjusted according to the drawing in the horizontal direction, horizontally rotating the three-dimensional model, judging the real-time superposition percentage of the 2d contour and the contour of the three-dimensional model, and judging the angle with the highest superposition percentage to be the position with the highest superposition ratio of the 2d contour of the three-dimensional model after 360-degree rotation of the three-dimensional model;
when the three-dimensional model is adjusted according to the drawing in the vertical direction, the three-dimensional model is horizontally rotated in a overlooking view angle, the real-time superposition percentage of the 2d contour and the contour of the three-dimensional model is judged, and after the three-dimensional model is rotated by 360 degrees, the angle with the highest superposition percentage is found, namely the position with the highest superposition ratio of the position of the three-dimensional model and the 2d contour.
Further, the automatic correction of the three-dimensional model according to the 2d contour specifically includes:
and comparing the 2d contour with the three-dimensional model, and correcting the redundant part positioned outside the 2d contour in the three-dimensional model.
Further, before performing adjustment processing on the position data of the three-dimensional model so that the coincidence ratio of the position data of the three-dimensional model and the 2d contour data satisfies a first condition, the method further includes:
Acquiring first profile data and second profile data, wherein the target profile data comprises the first profile data and the second profile data, and the first profile data and the second profile data are constrained; detecting the degree of freedom of the first profile data and the second profile data to obtain detection data between the first profile data and the second profile data;
and carrying out relation detection judgment on the detection data to determine whether the first contour data and the second contour data are accurate or not.
According to another embodiment of the present invention, there is provided a system for three-dimensional modeling of a converter station, the system comprising:
and a data acquisition module: acquiring point cloud data obtained by measuring a converter station by using measuring equipment;
and a data processing module: performing data accuracy processing on the point cloud data; 3d preprocessing is carried out on the point cloud data subjected to the data accuracy processing, and the point cloud data is output as a point cloud model; outputting the point cloud model into a 3d software first format file;
and (3) a correction module: carrying out contour correction on the point cloud model in 3d software based on preset 2d contour data to obtain a target model after contour correction, wherein the 2d contour data is obtained by carrying out image-to-digital conversion on 2d drawing data, and the target contour data included in the 2d contour data are mutually constrained;
And a three-dimensional modeling module: and 3d, performing three-dimensional modeling according to the object model after contour correction by using 3d software.
According to yet another embodiment of the present invention, there is also provided a computer device including a memory and a processor coupled to the memory, the memory having stored therein at least one program instruction or code that is loaded and executed by the processor to cause the computer device to implement all of the three-dimensional modeling method of a converter station.
According to yet another embodiment of the present invention, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed, implements the steps of the method of three-dimensional modeling of a converter station.
According to the invention, through carrying out multiple processing on point cloud data, a more accurate point cloud model and data of all aspects of the point cloud model are obtained, preliminary preparation is carried out for the subsequent 3d modeling, and then the three-dimensional modeling is carried out after carrying out contour correction on the point cloud model according to a 2d drawing.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a schematic flow chart of a three-dimensional model making method of a converter station according to an embodiment of the present application;
FIG. 2 is a schematic block diagram of a three-dimensional modeling system of a converter station in one embodiment;
fig. 3 is a schematic block diagram of a computer device in one embodiment.
Detailed Description
The following description of the technical solutions in the embodiments of the present application will be made with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Referring to fig. 1, a flow chart of a three-dimensional model making method of a converter station according to an embodiment of the present application is shown, where the method includes the following steps:
s1, acquiring point cloud data obtained by measuring a converter station by using measuring equipment;
Specifically, because the special of the converter station cannot be measured by using the unmanned aerial vehicle, the measuring device can use a laser scanner, a total station and other devices, in this embodiment, the laser scanner is preferable as the measuring device, and the data acquisition needs to determine the range and the object of the converter station to be acquired. And then the measuring equipment, namely a laser scanner, is used for measuring the convertor station, so as to acquire point cloud data and accurate position information. And then, on-site shooting or collecting related files such as available 2D drawings, technical specifications and the like is needed to ensure that the subsequent modeling situation is corrected.
S2, performing data accuracy processing on the point cloud data to obtain first point cloud data; 3d preprocessing is carried out on the first point cloud data, and the first point cloud data is output as a point cloud model;
since the above processing steps can be performed in the same software or in separate steps, in this embodiment, for convenience of processing, the above processing is performed in the FARO SCENE software.
Specifically, the method further comprises the following steps:
s21: data importing is carried out;
in this embodiment, the point cloud data obtained by measuring the converter station by using the measuring device is imported into the far SCENE software, and further, the subsequent processing is performed;
S22: registering and registering the imported point cloud data;
in this embodiment, the registration and registration are performed on the imported point cloud data, and since the converter station is larger, the positions scanned by the laser scanner are plural, so that the scanned point cloud data needs to be subjected to data alignment processing, specifically, the data of plural scanned positions are aligned, so as to generate an integral point cloud model. The automatic registration is firstly carried out by using a built-in software function in the FARO SCENE, and if the automatic registration access is larger, the manual registration processing can be used; it should be noted that, the process also needs to perform format unification processing on the related data, so as to ensure that the format unification of the related data can be accurately identified by subsequent processing.
S23: filtering and denoising the point cloud data subjected to registration and registration;
in this embodiment, because the converter station is larger, the environment is complex, and the interference factors are more, so that the accuracy of the obtained point cloud data is poor, and therefore, filtering and denoising processing is required to be performed on the registered point cloud data to reduce noise and interference and improve the data quality, the step can also use the function of the FARO SCENE to perform the above-mentioned automatic filtering and denoising processing to obtain the point cloud data with higher quality, and in addition, according to different situations of each converter station, the filtering and denoising processing conditions can be set automatically.
S24: and (3) dividing and extracting the point cloud data subjected to filtering and denoising treatment:
in this embodiment, since the converter station is large, the extracted point cloud data is complex, and therefore the point cloud data can be divided and extracted according to the need, and the point cloud data can be separated into different objects or parts. For example, the walls, roof, floor, etc. of a building may be segmented, and the process may be automated through a K-means series of point cloud classification recognition algorithm models.
S25, performing model generation and reconstruction on the segmented and extracted point cloud data;
in this embodiment, the above-mentioned operations of segmenting and extracting the point cloud data may segment the point cloud data into contents of a certain part of each device in the converter station, and then use tools and algorithms carried by the far SCENE software to generate a three-dimensional model, such as a triangle mesh model or a voxel model, according to the processed point cloud data. In this embodiment, the method for generating a model is implemented by a curved surface reconstruction or voxel reconstruction algorithm.
S26, carrying out data analysis on the point cloud data generated by the model;
in this embodiment, in order to facilitate the subsequent 3d modeling, tools and functions provided by the far service may be used, so that the processed point cloud data and the generated model may be analyzed, and operations such as measurement, volume calculation, and profile analysis may be performed to obtain corresponding volume, profile, and other data of the point cloud model; the analysis process can comprehensively analyze information such as the number of point clouds of a point cloud set in the point cloud data, the density of the point clouds, the distance between the point clouds, the spatial distribution of the point clouds, energy characteristics (specifically, brightness of the point clouds when three-dimensional display is performed, thickness degree of cloud points, reflectivity and reflection intensity of laser, and the characteristics are influenced by model characteristics of a converter station such as surface roughness degree and texture performance of an object to be detected) and the like.
S27, outputting the point cloud model subjected to 3d pretreatment into a first format file of 3d software:
in this embodiment, the processed point cloud data and the data of the point cloud model obtained by analyzing the processed point cloud data need to be modeled in the 3d software, so that the processed point cloud data and the data of the point cloud model need to be modeled in the 3d software, and thus the processed point cloud data and the data of the point cloud model need to be output into a file format required by the 3d software, such as LAS, PLY, OBJ. These files can be used for subsequent applications and sharing, such as 3Dmax, etc. in three-dimensional software.
S3, carrying out contour correction on the 3d software first format file based on preset 2d contour data to obtain a target model after contour correction, wherein the 2d contour data is obtained by carrying out image-to-digital conversion on 2d drawing data, and the target contour data included in the 2d contour data are mutually constrained;
in this embodiment, preprocessing is performed first, and the processed and verified point cloud model is imported into modeling software as a base map or background, and relevant data of the converter station, including 2D drawing data, technical specifications, field measurement data, and the like, is collected. And then carrying out format unification on the data, and establishing a basic structure and layout after sequentially importing the data into a data platform, wherein the basic structure and layout are specifically as follows:
according to the 2D drawing and technical specifications, basic structures and layouts of the converter stations, including buildings, equipment, pipelines and the like, are automatically created through a model creation algorithm. Using the 3Dmax modeling tool and commands, the exterior contours, rooms, floors, etc. of the building are drawn in the model. The position and size of the device are added to the model according to the point cloud data formed by the field measurement data, and the accuracy of the device is ensured.
Details and elements are then added: details and elements are added on the basis of basic structures and layouts to increase the realism and accuracy of the model. Details of the equipment, such as connection pipes, valves, cables, etc., are drawn based on the field measurement data and specifications. Details of the building such as doors, windows, stairs, wall texture, etc. are added.
And then organizing and layering the model to facilitate subsequent analysis, display and management. The different parts and components are distributed into different layers or groups, so that the display, the hiding and the editing are convenient. Proper naming and annotation are set, so that the model structure is clear and easy to understand.
After the model is built, verifying and correcting the model: and verifying the generated three-dimensional model, comparing the three-dimensional model with an actual converter station, and checking whether errors or omission exists. And correcting and adjusting the model according to the verification result to ensure that the model is consistent with the actual converter station.
The method specifically comprises the following steps:
s31, acquiring new project or model file information by using three-dimensional modeling software (such as 3Dmax, revit, maya).
S32, acquiring multidirectional 2d drawing data of the converter station;
in this embodiment, because the engineering drawing is difficult to extract accurate 8 directions, the 2d drawing data in 8 different directions on the horizontal direction of the converter station and the overlooking drawing data in the vertical direction of the converter station are preferably selected and obtained, the 8 horizontal directions can be selected to be 360-degree equidistant 8 directions on the horizontal direction, in this embodiment, the 8 directions of the east, south, west, north, southeast, southwest, northwest and northeast are preferably selected for facilitating the alignment of the drawing and the point cloud model, so as to complete the subsequent contour correction operation and ensure that the contour in each direction is corrected to the greatest extent.
S33, performing image-digital conversion processing on the 2d drawing data from a first direction to obtain 2d profile data of the converter station in the first direction, wherein target profile data included in the 2d profile data are constrained with each other;
in this embodiment, because the 2d drawing is a preferable field photograph, image processing software is required to perform image-to-digital conversion processing on 8 field photographs in the horizontal direction and in the top view to obtain an accurate 2d profile, so as to facilitate subsequent comparison with a point cloud model, where the image-to-digital conversion processing may be to automatically perform image capturing or matting on drawing data through an image capturing algorithm; in order to ensure the accuracy of the data, it is necessary to perform constraint processing on the target profile data at some important positions, so that when one profile data changes, the other profile data also changes, and at this time, whether the graph-to-digital conversion is reasonable can be determined by detecting whether the target profile data is normal.
Specifically, the process for detecting the mutually constrained target contour data includes:
s331, acquiring first profile data and second profile data, wherein the target profile data comprises the first profile data and the second profile data, and the first profile data and the second profile data are constrained;
The mutually constrained profile data includes, but is not limited to, profile tilt angle data, profile parallel/perpendicular relationship data, profile center data, profile symmetry data, profile radian data, and the like.
S332, detecting the degree of freedom of the first profile data and the second profile data to obtain detection data between the first profile data and the second profile data;
when one of the two pieces of mutually constrained contour data changes, the other piece of data also changes, and at this time, the degree of freedom of the two pieces of data is detected, that is, one piece of data is changed, the change condition of the other piece of data is obtained, then (but not limited to) the change pieces of data can be formed into a detection matrix, and then the detection matrix is subjected to subsequent processing, so that whether the two pieces of contour data are in a normal constraint relation or not can be judged, and it can be understood that the detection data comprise the detection matrix.
S333, performing relation detection judgment on the detection data to judge whether the first contour data and the second contour data are accurate.
The relation detection method for the detection data can (but is not limited to) directly compare the 2d contour data with standard data such as national standard or design data, so as to judge whether the 2d contour data is accurate, or can also perform low-dimensional conversion on the detection matrix, judge whether the detection matrix meets the requirements by calculating the variance of the low-dimensional matrix and the correlation between the low-dimensional matrices, so as to determine whether the first contour data and the second contour data are correct, then perform subsequent processing under the condition that the data are correct, otherwise perform alarm or re-acquire the 2d contour data. S34, adjusting the position data of the three-dimensional model so that the coincidence ratio of the position data of the three-dimensional model and the 2d contour data meets a first condition, wherein the first condition comprises the highest coincidence ratio;
In this embodiment, since the extracted 2d profile is different from the point cloud model in proportion and angle, the proportion and position need to be adjusted preferentially. Firstly, adjusting the proportion of the 2d profile and the proportion of the point cloud model to the same proportion;
and adjusting the ratio, namely, taking the ratio of the point cloud model to the actual converter station as the reference, and further adjusting the ratio of the 2d profile to the actual converter station until the ratio of the point cloud model to the actual converter station is the same.
When the position is adjusted according to the drawing in the horizontal direction, horizontally rotating the three-dimensional model, judging the real-time superposition percentage of the 2d contour data and the contour data of the three-dimensional model, and judging the angle with the highest superposition percentage to be the position of the three-dimensional model until the position with the highest superposition ratio with the 2d contour data after 360-degree rotation of the three-dimensional model;
when the three-dimensional model is adjusted according to the drawing in the vertical direction, the three-dimensional model is horizontally rotated from a overlooking view angle, the real-time superposition percentage of the 2d contour data and the contour data of the three-dimensional model is judged, after the three-dimensional model is rotated for 360 degrees, the angle with the highest superposition percentage is found, namely the position of the three-dimensional model is the position with the highest superposition degree with the 2d contour data.
And S34, when the contact ratio meets a first condition, correcting the three-dimensional model according to the 2d contour data.
In this embodiment, after the above-mentioned adjustment ratio and position, the 2d contour and the three-dimensional model are automatically compared by software, for example, the portion of the point cloud model located outside the 2d contour is the redundant portion, and then two determinations are performed, wherein the first determination is to determine the density of the point cloud data of the redundant portion, and if the density is greater than the threshold value, the second determination is to push to the administrator to determine whether the correction is performed, and if the density is not greater than the threshold value, the second determination is to determine whether the point cloud data of the redundant portion has a dense connection relationship with the non-redundant portion, and if the second determination is to push to the administrator to determine whether the correction is performed. In the method for determining the dense connection relationship, in this embodiment, the distance positions between the point clouds of the redundant portion and the non-redundant portion of the 2d contour edge are adopted, and if the distance positions are too close, the dense connection is determined.
In another embodiment, the three-dimensional model of the converter station may also be obtained by:
step S11, collecting model data related to a converter station, wherein the model data can be laser point cloud data acquired through laser scanning equipment and drawing specification data obtained through scanning and data conversion of a 2d drawing and a construction specification;
Step S12, screening the collected laser point cloud data and drawing standard data to remove abnormal values, randomly compensating the missing data, and simultaneously, labeling the randomly compensated data to facilitate the subsequent identification of the part of data, wherein the data compensation is performed to ensure the integrity of the data, so that the collected data can be identified and the data screening caused by incomplete data is avoided; then carrying out unified preprocessing on the data to ensure the quality and consistency of the data;
step S13, the cleaned and preprocessed data is stored in a proper database or data warehouse for subsequent modeling and analysis;
step S14, carrying out feature extraction processing on the laser point cloud data according to drawing specification data to obtain target feature data, wherein the feature extraction process comprises the steps of feature selection, feature construction, feature conversion and the like, and the target feature data comprises data such as model textures, surface roughness, model curvature, structure density and the like;
and S15, carrying out model adjustment on the created three-dimensional model through a preset model algorithm according to the drawing specification data and the target feature data, wherein the adjustment content comprises the characteristics of model angles, various structure proportions and the like, so that a final three-dimensional model meeting the requirements is obtained, and the process can be realized through the model adjustment algorithm, such as a greedy algorithm and the like.
In another embodiment, the verification and correction of the model specifically comprises the steps of:
and verifying the generated three-dimensional model, importing the scanned point cloud data into 3Dmax, checking whether the built model is completely overlapped with the point cloud data, checking whether errors or omission exists, and checking whether the texture of the model is consistent with the scene through the data such as drawings, pictures and the like acquired on the scene.
And correcting and adjusting the model according to the verification result to ensure that the model is consistent with the actual converter station.
And then, generating model output with different formats, such as a 3D model file, visual rendering, animation and the like, wherein the generated model can be applied to different fields, such as engineering design, equipment maintenance planning, simulation, safety evaluation and the like.
In one embodiment, a system for three-dimensional modeling of a converter station is provided, as shown in fig. 2, comprising:
the data acquisition module 21: acquiring point cloud data obtained by measuring a converter station by using measuring equipment;
the data processing module 22: performing data accuracy processing on the point cloud data; 3d preprocessing is carried out on the point cloud data subjected to the data accuracy processing, and the point cloud data is output as a point cloud model; outputting the point cloud model into a 3d software first format file;
Correction module 23: carrying out contour correction on the point cloud model in 3d software based on preset 2d contour data to obtain a target model after contour correction, wherein the 2d contour data is obtained by carrying out image-to-digital conversion on 2d drawing data, and the target contour data included in the 2d contour data are mutually constrained;
three-dimensional modeling module 24: and 3d, performing three-dimensional modeling according to the target model subjected to contour correction by using 3d software.
For specific limitations regarding the system for three-dimensional modeling of a converter station, reference is made to the above limitations regarding the method for three-dimensional modeling of a converter station, and no further description is given here. The various modules in the system for three-dimensional modeling of a converter station described above may be implemented in whole or in part in software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, where the computer device provided in the embodiment of the present application may be a server or a client: fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Processor 1701, memory 1702, bus 1705, interface 1704, processor 1701 being coupled to memory 1702, interface 1704, bus 1705 being coupled to processor 1701, memory 1702 and interface 1704, respectively, interface 1704 being for receiving or transmitting data, processor 1701 being a single or multi-core central processing unit, or being a specific integrated circuit, or being one or more integrated circuits configured to implement embodiments of the present invention. The memory 1702 may be a random access memory (random access memory, RAM) or a non-volatile memory (non-volatile memory), such as at least one hard disk memory. The memory 1702 is used to store computer-executable instructions. Specifically, the program 1703 may be included in the computer-executable instructions.
In this embodiment, when the processor 1701 invokes the program 1703, the management server in X of the three-dimensional model of the converter station can be caused to execute the X operation of the three-dimensional model of the converter station, which is not described herein.
It should be appreciated that the processor provided by the above embodiments of the present application may be a central processing unit (central processing unit, CPU), but may also be other general purpose processors, digital signal processors (digital signal processor, DSP), application specific integrated circuits (application-specific integrated circuit, ASIC), off-the-shelf programmable gate arrays (field programmable gate array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It should also be understood that the number of processors in the computer device in the above embodiment in the present application may be one or plural, and may be adjusted according to the actual application scenario, which is merely illustrative and not limiting. The number of the memories in the embodiment of the present application may be one or more, and may be adjusted according to the actual application scenario, which is merely illustrative and not limiting.
It should be further noted that, when the computer device includes a processor (or a processing unit) and a memory, the processor in the present application may be integrated with the memory, or the processor and the memory may be connected through an interface, which may be adjusted according to an actual application scenario, and is not limited.
The present application provides a chip system comprising a processor for supporting a computer device (client or server) to implement the functions of the controller involved in the above method, e.g. to process data and/or information involved in the above method. In one possible design, the chip system further includes memory to hold the necessary program instructions and data. The chip system can be composed of chips, and can also comprise chips and other discrete devices.
In another possible design, when the chip system is a chip in a user equipment or an access network or the like, the chip comprises: the processing unit may be, for example, a processor, and the communication unit may be, for example, an input/output interface, pins or circuitry, etc. The processing unit may execute the computer-executable instructions stored in the storage unit to cause the chip within the client or the management server or the like to perform the steps of the three-dimensional model creation method of the converter station. Alternatively, the storage unit is a storage unit in the chip, such as a register, a cache, or the like, and the storage unit may also be a storage unit located outside the chip in a client or a management server, such as a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory, RAM), or the like.
The present application further provides a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a computer implements a method flow executed by a controller of a client or a management server in any of the method embodiments. Correspondingly, the computer may be the above-mentioned computer device (client or server).
It should be appreciated that the controllers or processors referred to in the above embodiments of the present application may be central processing units (central processing unit, CPU), but may also be other general purpose processors, digital signal processors (digital signal processor, DSP), application specific integrated circuits (application specific integrated circuit, ASIC), off-the-shelf programmable gate arrays (field programmable gate array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It should also be understood that the number of processors or controllers in the computer device (client or server) or the chip system and the like in the above embodiments in this application may be one or more, and may be adjusted according to the actual application scenario, which is merely illustrative and not limiting. The number of the memories in the embodiment of the present application may be one or more, and may be adjusted according to the actual application scenario, which is only illustrative and not limiting.
It should also be understood that the memory or readable storage medium mentioned in the computer device (client or server) or the like in the above embodiments in the embodiments of the present application may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. The volatile memory may be random access memory (random access memory, RAM) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous DRAM (SLDRAM), and direct memory bus RAM (DR RAM).
Those of ordinary skill in the art will appreciate that steps performed by a computer device (client or server) or processor in whole or in part to implement the above described embodiments may be implemented by hardware or program instructions. The program may be stored in a computer readable storage medium, which may be a read-only memory, a random access memory, or the like. Specifically, for example: the processing unit or processor may be a central processing unit, a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
When implemented in software, the method steps described in the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.) means from one website, computer, server, or data center. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc., that contain an integration of one or more available media. Usable media may be magnetic media (e.g., floppy disks, hard disks, magnetic tape), optical media (e.g., DVD), or semiconductor media, among others.
The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances and are merely illustrative of the manner in which the embodiments of the application described herein have been described for objects of the same nature. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The terminology used in the embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the embodiments of the present application, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that in the description of the present application, unless otherwise indicated, "/" means that the associated object is an "or" relationship, e.g., A/B may represent A or B; the term "and/or" in this application is merely an association relation describing an association object, and means that three kinds of relations may exist, for example, a and/or B may mean: there are three cases, a alone, a and B together, and B alone, wherein a, B may be singular or plural.
The word "if" or "if" as used herein may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to detection", depending on the context. Similarly, the phrase "if determined" or "if detected (stated condition or event)" may be interpreted as "when determined" or "in response to determination" or "when detected (stated condition or event)" or "in response to detection (stated condition or event), depending on the context.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (7)
1. A method for three-dimensional modeling of a converter station, the method comprising:
acquiring point cloud data obtained after measuring the converter station through measuring equipment;
Performing data accuracy processing on the point cloud data to obtain first point cloud data;
3d preprocessing is carried out on the first point cloud data, and the first point cloud data is output as a point cloud model;
outputting the point cloud model into a 3d software first format file;
carrying out contour correction on the 3d software first format file based on preset 2d contour data to obtain a target model after contour correction, wherein the 2d contour data is obtained by carrying out image-to-digital conversion on 2d drawing data, and the target contour data included in the 2d contour data are mutually constrained; performing three-dimensional modeling according to the target model after contour correction to obtain a three-dimensional model of the target converter station;
the 3d preprocessing comprises model generation and reconstruction of the first point cloud data and output as a point cloud model;
analyzing the point cloud model generated and reconstructed by the model to obtain specific parameter data of the point cloud model;
analyzing the point cloud model after the model generation and reconstruction to obtain specific parameter data of the point cloud model comprises the following steps:
acquiring acquisition characteristics and cloud point characteristics of the point cloud data, wherein the acquisition characteristics comprise energy characteristics in the process of acquiring the point cloud data, and the cloud point characteristics comprise brightness and/or thickness degree of cloud points in the point cloud data;
Determining model features of a point cloud model according to the energy features, wherein the model features at least comprise any one of surface roughness and texture features of the converter station, and the specific parameter data comprise the model features;
the contour correction of the modeled three-dimensional model based on the preset 2d contour data specifically comprises the following steps:
acquiring multidirectional 2d drawing data of the converter station;
performing graph-digital conversion processing on the 2d drawing data from a first direction to obtain 2d profile data of the converter station in the first direction, wherein target profile data included in the 2d profile data are constrained with each other;
adjusting the position data of the three-dimensional model to enable the coincidence ratio of the position data of the three-dimensional model and the 2d profile data to meet a first condition, wherein the first condition comprises the highest coincidence ratio;
and under the condition that the contact ratio meets a first condition, correcting the three-dimensional model according to the 2d contour data.
2. A three-dimensional modeling method for a converter station according to claim 1, wherein,
the adjusting processing is performed on the position data of the three-dimensional model, so that the coincidence ratio of the position data of the three-dimensional model and the 2d contour data meets a first condition, and the method specifically comprises the following steps:
Adjusting the proportion of the 2d contour data and the proportion of the three-dimensional model to the same proportion;
when the three-dimensional model is adjusted according to the drawing in the horizontal direction, horizontally rotating the three-dimensional model, judging the real-time superposition percentage of the 2d contour data and the contour data of the three-dimensional model, and judging the angle with the highest superposition percentage to be the position with the highest superposition degree of the 2d contour data of the three-dimensional model after 360-degree rotation of the three-dimensional model;
when the three-dimensional model is adjusted according to the drawing in the vertical direction, the three-dimensional model is horizontally rotated in a overlooking view angle, the real-time superposition percentage of the 2d contour and the contour of the three-dimensional model is judged, and after the three-dimensional model is rotated by 360 degrees, the angle with the highest superposition percentage is found, namely the position with the highest superposition ratio of the position of the three-dimensional model and the 2d contour.
3. A three-dimensional modeling method for a converter station according to claim 1, wherein,
the correcting process for the three-dimensional model according to the 2d contour data specifically comprises the following steps:
and comparing the 2d contour with the three-dimensional model, and correcting the redundant part positioned outside the 2d contour in the three-dimensional model.
4. A three-dimensional modeling method for a converter station according to claim 1, wherein,
Before the position data of the three-dimensional model is subjected to adjustment processing so that the coincidence ratio of the position data of the three-dimensional model and the 2d contour data meets a first condition, the method further comprises:
acquiring first profile data and second profile data, wherein the target profile data comprises the first profile data and the second profile data, and the first profile data and the second profile data are constrained;
detecting the degree of freedom of the first profile data and the second profile data to obtain detection data between the first profile data and the second profile data;
and carrying out relation detection judgment on the detection data to determine whether the first contour data and the second contour data are accurate or not.
5. A three-dimensional modeling method for a converter station according to claim 1, wherein,
the data accuracy processing for the point cloud data specifically includes:
registering and registering the point cloud data;
filtering and denoising the point cloud data;
and carrying out segmentation and feature extraction processing on the point cloud data.
6. A system for three-dimensional modeling of a converter station, the system comprising:
And a data acquisition module: acquiring point cloud data obtained by measuring a converter station by using measuring equipment;
and a data processing module: performing data accuracy processing on the point cloud data; 3d preprocessing is carried out on the point cloud data subjected to the data accuracy processing, and the point cloud data is output as a point cloud model; outputting the point cloud model into a 3d software first format file;
and (3) a correction module: carrying out contour correction on the point cloud model in 3d software based on preset 2d contour data to obtain a target model after contour correction, wherein the 2d contour data is obtained by carrying out image-to-digital conversion on 2d drawing data, and the target contour data included in the 2d contour data are mutually constrained;
and a three-dimensional modeling module: and 3d, performing three-dimensional modeling according to the object model after contour correction by using 3d software.
7. A computer device comprising a memory and a processor coupled to the memory, wherein the memory has stored therein at least one program instruction or code that is loaded and executed by the processor to cause the computer device to implement the three-dimensional model production method of a converter station of any one of claims 1-5.
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