CN110660125A

CN110660125A - Three-dimensional modeling device for power distribution network system

Info

Publication number: CN110660125A
Application number: CN201910877249.3A
Authority: CN
Inventors: 王伟; 徐文忠; 王文荣; 朱坚军; 陈婷; 吴海涛; 徐辉; 白玉岭; 傅冬春
Original assignee: State Grid Zhejiang Xianju County Power Supply Co Ltd; Xianju Hengxin Electric Power Co Ltd; Taizhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Current assignee: State Grid Zhejiang Xianju County Power Supply Co Ltd; Xianju Hengxin Electric Power Co Ltd; Taizhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Priority date: 2019-09-17
Filing date: 2019-09-17
Publication date: 2020-01-07
Anticipated expiration: 2039-09-17
Also published as: CN110660125B

Abstract

The invention provides a three-dimensional modeling device for a power distribution network system, which specifically comprises an image acquisition unit, a three-dimensional modeling unit and a three-dimensional modeling unit, wherein the image acquisition unit is used for acquiring multi-angle images of an object to be modeled; the image data extraction unit is used for extracting height data and surface texture data of an object to be modeled from the acquired image; a structural modeling unit for constructing a structural model for the object to be modeled using the height data and the surface texture data of the object to be modeled; and the surface mapping unit is used for adding a light and shadow effect on the constructed structure model to obtain a fine three-dimensional model containing projection information. The management platform realizes standardization, digitization and scientific centralization and unification, thereby enhancing the management of the power distribution network, improving the informatization level of the whole power enterprise, reducing the cost and improving the power production efficiency and marketing work efficiency.

Description

Three-dimensional modeling device for power distribution network system

Technical Field

The invention relates to the field of power networks, in particular to a three-dimensional modeling device for a power distribution network system.

Background

The power industry is the most important basic energy industry in the development of national economy, is also the first basic industry of the national economy, is the basic industry related to the national civilization, and is the priority development focus in economic development strategies of all countries in the world. As advanced productivity and basic industry, the power industry plays an important role in promoting the development of national economy and social progress, and has a very close relationship with social economy and social development. The method is not only a strategic problem related to national economic safety, but also closely related to the daily life and social stability of people.

The distribution network is an electric power network which receives electric energy from a transmission network or a regional power plant and distributes the electric energy to various users on site or step by step according to voltage through distribution facilities. The distribution network is directly connected with power supply users and is an important component of the power system. Particularly, rural power distribution networks are widely distributed in regions, and the types and the number of electrical equipment are numerous, so that the power distribution networks are huge information carriers, and not only are a great deal of static information such as geographic features, grid structures and the attributes of the power distribution equipment involved, but also dynamic information such as the real-time running state of a power system exists in the power distribution networks.

However, with the deep progress of national power grid transformation, the power distribution network has great progress in equipment updating, technical transformation and the like, but is relatively laggard in the aspect of information management, and many power departments also have the problems of improper planning method, low application level, laggard related geographic information, difficulty in sharing information resources among the departments and the like. Electronic office platforms established by each unit department are also mutually independent, so that the spatial data updating force is different and can not be unified, hidden dangers are brought to information resource sharing and application, equipment resources and power grid architectures based on power grid operation are more and more diversified and complicated, power equipment and transmission lines are distributed outdoors, and the existing power grid development condition can not be adapted by manual and decentralized management in the original maintenance system and management mode. In the aspects of electric power marketing service business, fault emergency repair and the like, the needs of current situations such as real-time property of marketing resources and high efficiency required by marketing business are met. Meanwhile, the GIS system widely applied in the power distribution network industry at present mainly based on two-dimensional coordinates cannot simulate the field condition, the space expression and analysis capability of the GIS system are greatly limited, and the electronic map (two-dimensional) updating speed is low and the cost is high at present.

Therefore, starting from the business and management requirements of power production and marketing, a set of three-dimensional management system of distribution network equipment with abundant geographic, topographic and surface feature data information and complete functions is urgently needed to be established, so that resource information, maintenance information and the like of a power grid can be dynamically acquired and shared in real time, and corresponding power grid information query and management services are provided for power grid planning, design, construction, operation maintenance, professional application, accident emergency repair and project decision by means of a visual three-dimensional network system, so that a standardized, digitalized and scientifically centralized and unified management platform is realized, power distribution network management is enhanced, the informatization level of the whole power enterprise is improved, the cost is reduced, and the power production efficiency and the marketing work efficiency are improved.

Disclosure of Invention

The invention aims to provide a three-dimensional modeling device for a power distribution network system, establish a three-dimensional application system of a power distribution network facility, realize intensive management of multiple major fields such as distribution network scheduling, monitoring, transportation, automation and emergency repair, establish a support platform of a power distribution network regulation and control integrated system, provide effective basic data guarantee, more intuitively show the construction condition of an urban distribution network, and establish a virtual office platform for power facility maintenance, equipment digital unified management, guidance of future planning and development of the distribution network and the like.

In order to achieve the above object, the present invention adopts the following technical solution, and specifically, the three-dimensional modeling apparatus includes:

the image acquisition unit is used for acquiring multi-angle images of an object to be modeled;

the image data extraction unit is used for extracting height data and surface texture data of an object to be modeled from the acquired image;

a structural modeling unit for constructing a structural model for the object to be modeled using the height data and the surface texture data of the object to be modeled;

and the surface mapping unit is used for adding a light and shadow effect on the constructed structure model to obtain a fine three-dimensional model containing projection information.

Optionally, the image capturing unit includes:

and the equipment control subunit is used for controlling the aerial photographing equipment including the unmanned aerial vehicle to photograph and acquire videos of the object to be modeled at different distances and different angles.

Optionally, the image data extracting unit includes:

the height data acquisition subunit is used for controlling a server including a computer to acquire height data of an object to be modeled based on the acquired images including photos and videos according to different distances and in combination with corresponding proportions;

and the texture acquisition subunit is used for controlling a server comprising a computer to determine the surface texture of the object to be modeled based on the acquired images comprising the photos and the videos, and extracting surface texture data according to different colors of the surface of the object to be modeled.

Optionally, the structural modeling unit includes:

a texture extraction subunit, configured to select a structural texture in the vertical direction and the horizontal direction from the extracted surface texture data;

and the structure modeling subunit is used for adjusting the size of the structure texture according to the height data and building a structure model corresponding to the object to be modeled by using the adjusted structure texture.

Optionally, the surface mapping unit includes:

the projection information confirming subunit is used for acquiring the sun direction at the time of image acquisition and determining the projection length and the projection angle of the object to be modeled under the sun;

and the projection rendering subunit is used for performing projection rendering on the object to be modeled based on the determined projection length and angle to obtain a fine three-dimensional model containing projection information.

Optionally, the three-dimensional modeling apparatus further includes:

and the image rectification unit is used for performing geometric correction on the image acquired by the image acquisition unit and outputting the corrected image to the image data extraction unit.

Optionally, the image rectification unit includes:

the image correction unit is used for correcting the spatial position and the morphological deformation of the object to be modeled;

and the image clipping unit is used for clipping the corrected image and only keeping the image of the object part to be modeled.

Optionally, the image correction unit includes:

the object determining subunit is used for selecting a correction object in an area with disordered lines in the acquired image;

and the line correction subunit is used for performing line correction on the corrected object according to the original lines around the line disorder area.

Optionally, the image cropping unit includes:

and the size cutting subunit is used for cutting the remote sensing image line subjected to geometric correction.

Optionally, the image acquisition unit, the image data extraction unit, the structure modeling unit and the surface mapping unit are computers equipped with tool software.

After the technical scheme is adopted, the invention has the following advantages: the three-dimensional application system of the power distribution network equipment establishes a real three-dimensional terrain scene by using a remote sensing image and DEM data, replaces an abstract two-dimensional map symbol by using a visual three-dimensional model, and simultaneously directly hooks attribute information and the three-dimensional model of the equipment, thereby really achieving seamless combination of graphic data (model data) and attribute information, creating good conditions for various spatial analyses, providing real three-dimensional information services for equipment management, planning and design, equipment first-aid repair and other works, and greatly improving the information level and service level of the power distribution network. And the whole life cycle management of the distribution network equipment is realized.

Drawings

The invention will be further described with reference to the accompanying drawings in which:

fig. 1 is a schematic structural diagram of a three-dimensional modeling apparatus 1 for a power distribution network system proposed in this embodiment.

Detailed Description

Example one

The three-dimensional modeling apparatus 1 for a power distribution network system provided by the present invention is specifically shown in fig. 1, and includes:

the image acquisition unit 11 is used for acquiring multi-angle images of an object to be modeled;

an image data extraction unit 12 for extracting height data and surface texture data of an object to be modeled from the acquired image;

a structural modeling unit 13 for constructing a structural model for the object to be modeled using the height data and the surface texture data of the object to be modeled;

and the surface mapping unit 14 is used for adding a light and shadow effect on the constructed structure model to obtain a fine three-dimensional model containing projection information.

In implementation, in order to complete three-dimensional modeling of power settings including buildings in a power system, the steps of photographing, data extraction, modeling and optimization need to be sequentially performed, and each specific step is performed by the image acquisition unit 11, the image data extraction unit 12, the structure modeling unit 13 and the surface mapping unit 14.

The image capturing unit 11 for performing the image capturing step specifically includes:

and the device control subunit 111 is used for controlling the aerial photographing device including the unmanned aerial vehicle to photograph and acquire videos of the object to be modeled at different distances and different angles.

In the implementation, there are two main ways of acquiring images in the three-dimensional modeling technical scheme, which are respectively:

(1) the method comprises the steps that field photography is combined with building contour line data, and a fine model is created in 3 DSMAX;

(2) and (5) three-dimensional modeling of an aerial survey technology.

The 3DSMax modeling is mainly used for building modeling in important urban areas only by adopting 3DSMax software according to data of the bottom surface of a building under the condition that the building outline is not accurately measured by a stereo image pair. Firstly, determining an operation range and an operation design of area division needing fine modeling according to a project, then, utilizing a digital camera to carry out digital shooting on all buildings in a partitioned working area, then, establishing a model in 3DSMax software, wherein the format is max, and finally, utilizing an expansion module of the model to convert the model into the format of x.

The three-dimensional modeling of the aerial survey technology mainly comprises the steps of collecting three-dimensional data of relevant ground objects by utilizing an existing digital photogrammetric system, a ground laser scanning system and the like, wherein the three-dimensional data comprises data information such as the peripheral outline and height of a building, the outline and center line elevation of a road, the outline and height of trees, the size and height of various bridges, the size and height of a large outdoor advertising board, the position and height of a street lamp post and the like, then building the shape of the building by utilizing collected professional data in professional modeling software, carrying out a large amount of manual intervention in the process of actually collecting textures in the field and building fine classification of a model, making up the defect that an automatic classification algorithm is inaccurate in distinguishing the ground objects and the surface data, and enabling laser point cloud data subjected to the fine classification to enter the final quality. And traversing the data, using different display modes, checking classification results and ensuring the quality. The final laser point cloud classification result can be output in various data formats such as XYZ, LAS and TXT. By using the method, the coordinates and the name of the central point of each building are collected while the buildings are collected, and simultaneously, the connection service provides other extended attribute information to form the point position vector data of the buildings. And finally, integrating the building model and the vector attribute extension data, and automatically establishing the three-dimensional building model to a three-dimensional accurate scene position to form the three-dimensional urban landscape.

Therefore, the equipment control subunit 111 adopts the second three-dimensional modeling mode of the aerial survey technology, and particularly needs to control the aerial equipment including the unmanned aerial vehicle to photograph and acquire videos of objects to be modeled at different distances and at different angles. Therefore, the image acquisition is carried out at different angles, and the modeling basis is provided for establishing a full-view three-dimensional model. In addition, the purpose of taking pictures at different distances is to provide reference samples at different scales, so that better use experience can be generated when the three-dimensional model is scaled differently at a later stage.

Optionally, the image data extracting unit 12 includes:

the height data acquisition subunit 121 is configured to control a server including a computer to acquire height data of an object to be modeled based on acquired images including photos and videos according to different distances and in combination with corresponding proportions;

and the texture acquisition subunit 122 is configured to control a server including a computer to determine the surface texture of the object to be modeled based on the acquired images including the photograph and the video, and extract surface texture data according to the difference in color of the surface of the object to be modeled.

In practice, the data to be prepared before the image data is extracted includes preparation and editing of data files such as camera parameter files, POS data, image control points, and oblique photography data.

And (3) setting formats of the data of the five lenses of the oblique images acquired by aerial photography, the calculated POS data and the image control point result according to requirements, and preparing camera parameter files comprising information such as camera pixels, image frames, focal lengths, principal points, camera directions of all cameras and the like. The image control points are auxiliary positioning information in aerial triangulation, and each image control point is required to have 2 or more image puncture points.

Specifically, oblique photography data processing and results are imported into a Skyline software series platform, and the analysis is carried out to synthesize the correlation class of the distribution network facility. The Skyline software series platform is introduced as follows: the Skyline software family platform provides a full set of mature solutions from data production to editing to web publishing. No matter in a stand-alone environment or a network environment, a user can customize functions according to the requirement of the user, and a three-dimensional geographic information system of the user is established.

The height data acquiring subunit 121 is specifically configured to determine, based on the image parameters acquired by the image acquiring unit 11, the acquired height data for the object to be modeled by calculation in combination with the shooting distance and the ratio of the reference object in the image, and the texture acquiring subunit 122 is configured to extract the content of the color, the pattern, the line, and the like on the surface of the object to be modeled from the acquired image.

A texture feature is also a global feature that also describes the surface properties of the scene to which the image or image area corresponds. However, since texture is only a characteristic of the surface of an object and does not completely reflect the essential attributes of the object, high-level image content cannot be obtained by using texture features alone. Unlike color features, texture features are not based on the characteristics of the pixel points, which requires statistical calculations in regions containing multiple pixel points. In pattern matching, such regional features have great superiority, and matching is not unsuccessful due to local deviation. As a statistical feature, the texture feature often has rotation invariance and is resistant to noise. However, texture features have their disadvantages, and one obvious disadvantage is that the calculated texture may deviate significantly when the resolution of the image changes. In addition, the texture reflected from the 2-D image is not necessarily the true texture of the surface of the 3-D object, as it may be affected by illumination and reflections. It is an effective method to use texture features when searching for texture images having large differences in thickness, density, and the like. However, when the information that is easily distinguished by thickness, density, etc. of the texture is not very different, it is difficult for the general texture features to accurately reflect the difference between the textures that are visually perceived to be different by humans.

Common feature extraction and matching methods include statistical methods, geometric methods, and model methods.

The statistical method is based on the gray attribute of the pixel and the neighborhood thereof, and researches the statistical characteristics in the texture region or the first-order, second-order or high-order statistical characteristics of the gray in the pixel and the neighborhood thereof. The typical representative statistical method is a texture feature analysis method called gray level co-occurrence matrix (GLCM), Gotlieb and Kreyszig, etc. on the basis of researching various statistical features in the co-occurrence matrix, four key features of the gray level co-occurrence matrix are obtained through experiments: energy, inertia, entropy and correlation. Another typical statistical method is to extract texture features from an autocorrelation function (i.e., an energy spectrum function of an image) of the image, i.e., to extract feature parameters such as the thickness and the directionality of the texture by calculating the energy spectrum function of the image.

The geometric method is a texture feature analysis method based on the theory of texture elements (basic texture elements). Textons theory holds that a complex texture may be composed of several simple textons that are repeated in a certain regular pattern. In the geometric method, the algorithm which has a relatively influence is a Voronio checkerboard feature method. The application and development of geometric methods is extremely limited and follow-on studies are rare.

In the model method, it is assumed that a texture is formed in a distributed model mode controlled by a certain parameter, model parameters are estimated and calculated from the realization of a texture image, and image segmentation is performed by taking the parameters as features or adopting a certain classification strategy, so the estimation of the model parameters is a core problem of the family method. Typical methods are random field models such as Markov Random Field (MRF) models, Gibbs random field models, fractal models, and autoregressive models. The signal processing method is based on time, frequency analysis and multi-scale analysis, and after certain transformation is carried out in a certain region in the texture image, a characteristic value which keeps relatively stable is extracted and used as the characteristic to represent the consistency in the region and the dissimilarity between the regions.

Optionally, the structural modeling unit 13 includes:

a texture extraction subunit 131 configured to select structural textures in the vertical direction and the horizontal direction from the extracted surface texture data;

and the knot building mold unit 132 is used for adjusting the size of the structural texture according to the height data and building a structural model corresponding to the object to be modeled by using the adjusted structural texture.

In implementation, the specific three-dimensional modeling steps are divided into two steps, firstly, building a structural framework, and secondly, performing surface mapping on the structural framework. The specific mode for building the structural framework is to extract vertical direction textures and horizontal direction textures from the acquired surface texture data to serve as a framework foundation for building the framework. The structural framework is built by selecting textures in two directions, and the purpose is to ignore the influence of a glass curtain wall, a color banner or an LED display panel on the surface of the building.

After the structural framework is built, the size of the structural texture needs to be adjusted according to the height data by means of the structural modeling subunit 132, and the adjusted structural texture is used for building a structural model corresponding to an object to be modeled.

Optionally, the surface mapping unit 14 includes:

the projection information confirming subunit 141 is configured to obtain a sun position at the time of acquiring the image, and determine a projection length and an angle of the object to be modeled under the sun;

and a projection rendering subunit 142, configured to perform projection rendering on the object to be modeled based on the determined projection length and angle, so as to obtain a fine three-dimensional model including projection information.

In implementation, after the frame model built and adjusted in the foregoing is obtained, in order to obtain a more realistic modeling effect, the light and shadow effect rendering needs to be performed on the three-dimensional model in combination with the current sunshine condition.

The specific mode is to obtain the illumination condition of the current three-dimensional model, namely the sun direction at the moment of image acquisition, determine the projection length and angle of the object to be modeled under the sun, and further determine the illumination angle and the projection length and angle of the object to be modeled under the illumination angle by combining the determined parameters to perform the shadow rendering.

It should be noted that the shadow rendering is performed while the rendering of the texture details of the surface of the structural frame is also completed, and the texture on the shaded surface is not required to be rendered in order to simplify the rendering pressure.

Optionally, the three-dimensional modeling apparatus 1 further includes:

and the image rectification unit 15 is used for performing geometric correction on the image acquired by the image acquisition unit and outputting the corrected image to the image data extraction unit.

In implementation, the main steps of three-dimensional modeling can be completed through the processing of the four types of units, but in order to improve the modeling accuracy, the size rectification processing needs to be performed on the acquired image by the image rectification unit 15. The image rectification unit 15 includes:

an image correction unit 151 for correcting the spatial position and morphological deformation of the object to be modeled;

and an image cropping unit 152, configured to crop the modified image and only reserve the image of the object portion to be modeled.

The image correction unit 151 includes: an object determining subunit 1511 and a line correcting subunit 1512, where the object determining subunit is configured to select a correction object in an area where lines are disordered in the acquired image; the latter is used for carrying out line correction on the corrected object according to the original lines around the line disorder area.

2) Geometric correction of images

Geometric correction refers to a process of correcting and improving the spatial position and geometric shape deformation of a remote sensing image, so that the remote sensing image is corrected to a drawing based on certain projection property, and the method is suitable for measurement and positioning of resources and environmental investigation and composition of various drawings. Common methods for geometric correction include collinear equations, general polynomials, and spatial projection. The geometric correction mainly comprises three basic steps, namely, determining a correction model, and selecting points for matching correction; secondly, directional inspection is carried out to remove gross errors; and thirdly, performing geometric correction.

The remote sensing image fusion is a technology for compounding multi-source remote sensing images by an advanced image processing technology. In the fusion process, the optimal wave band combination and the optimal image resolution are selected, the most appropriate time phase superposition is selected, the advantages of each image are embodied by adopting the optimal algorithm, and the data sources are combined complementarily and organically to generate a new image.

After the images are fused, different characteristics of different images are utilized to the maximum extent, so that the final fused image has higher control resolution and spectrum, the geometric precision and the visual effect of the images are improved, the classification precision and the reliability of the images are improved, the multifarities, uncertainties, incompleteness and errors existing in image interpretation are reduced, and stronger information interpretation capability and more reliable analysis results are provided finally.

And an image cropping unit 152, configured to crop the modified image and only reserve the image of the object portion to be modeled. The device comprises a size clipping subunit 1521, which is used for clipping the remote sensing image line after geometric correction.

For the remote sensing image after geometric correction and fusion mosaic processing, before the remote sensing image is used by a user, due to factors such as image range, black edge, attractiveness and the like, the image needs to be cut.

It should be noted that the units and sub-units described above are merely a general term for specific execution devices for different execution steps, and each unit and sub-unit may contain one or more specific devices. Since the present embodiment mainly relates to image processing operations for three-dimensional modeling, each unit and sub-unit refers to a portable electronic device, a mobile computer, a workstation, or a server, which is installed with image processing software, and details are not repeated.

Other embodiments of the present invention than the preferred embodiments described above will be apparent to those skilled in the art from the present invention, and various changes and modifications can be made therein without departing from the spirit of the present invention as defined in the appended claims.

Claims

1. A three-dimensional modeling apparatus for a power distribution network system, the three-dimensional modeling apparatus comprising:

2. The three-dimensional modeling device for power distribution network system according to claim 1, wherein said image acquisition unit comprises:

3. The three-dimensional modeling device for power distribution network system according to claim 1, wherein said image data extraction unit comprises:

4. The three-dimensional modeling apparatus for power distribution network system according to claim 1, wherein said structural modeling unit comprises:

5. The three-dimensional modeling apparatus for power distribution network system according to claim 1, wherein said surface mapping unit comprises:

6. The three-dimensional modeling apparatus for power distribution network system according to claim 1, further comprising:

7. The three-dimensional modeling device for power distribution network system according to claim 6, wherein said image rectification unit comprises:

8. The three-dimensional modeling apparatus for power distribution network system according to claim 7, wherein said image correction unit comprises:

9. The three-dimensional modeling device for power distribution network system according to claim 7, wherein said image cropping unit comprises:

10. The three-dimensional modeling device for the power distribution network system according to any one of claims 1 to 9, wherein the image acquisition unit, the image data extraction unit, the structure modeling unit and the surface mapping unit are computers installed with tool software.