Multi-dimensional visual display method for power grid field operation

Abstract

The invention relates to a multi-dimensional visual display method for power grid field operation. The method comprises the following steps: acquiring multi-dimensional data of power grid field operation; preprocessing the multi-dimensional data of the electric power field operation; the method comprises the following steps: constructing a display scene of time and space dimensions, and constructing the display scene of the space dimension according to the following mode: carrying out construction operation site virtual display of environment information data, personnel form data and equipment appearance data of a three-dimensional model through electric power field operation multi-dimensional data in combination with three-dimensional positioning anchor point coordinates; the display scene of the time dimension is constructed according to the following mode: by obtaining the personnel positioning coordinates, the equipment positioning coordinates and the three-dimensional positioning anchor point coordinate data of the electric power operation field, the animation technology is adopted to simulate the motion trail and the form change of an object, and a more real animation effect and visual perception are generated. According to the invention, the field operation data is combined with a video recognition algorithm to carry out field visualization three-dimensional display, and the cloud perception of the whole process of the operation field is realized.

Description

Technical Field

[0001] The present invention relates to a multi-dimensional visualization display method for power grid field operations, and belongs to the technical field of power operation field safety management and control. Background Art

[0002] The power grid structure is becoming increasingly complex, new equipment and new technologies are widely used, and the power grid operation and maintenance and construction tasks are heavy. There are nearly 30,000 operating projects per week at the peak, and more than 400,000 on-site personnel. There are many on-sites, many operating personnel, and many professional cooperation. Various safety risks and potential accidents are intertwined and superimposed, making safety management and control difficult. Traditional safety management methods and capabilities cannot keep up with the requirements of the development of the new situation. Although the existing data has been gathered, there is no visual multi-dimensional monitoring, and it is impossible to intuitively understand the progress of on-site construction and personnel conditions.

[0003] Therefore, it is necessary to carry out research on multi-dimensional visualization display methods, combine the positioning information of various equipment on the operation site, video recognition, Beidou satellite maps, and power grid operation site business information and other data to build a three-dimensional visualization operation site, promote the cloud display of virtual scenes on the operation site, improve the comprehensiveness, timeliness, and intuitiveness of on-site operations, and provide support for operation safety management and decision-making.

[0004] A Chinese patent application with application number CN202211408330.5 discloses a power grid operation site safety management and control system, which includes a data acquisition intelligent terminal, a power grid operation site safety management and control device, and a remote monitoring platform; the data acquisition intelligent terminal obtains the operation site monitoring data, and transmits the data to the power grid operation site safety management and control device for real-time analysis; the power grid operation site safety management and control device transmits the analysis results to the remote monitoring platform for display.

[0005] The power grid operation site safety management and control system constructed by this method only involves the aggregation of data, and does not form cloud-based analysis, virtual display and other services at the operation site. The power grid operation site safety management and control has certain limitations and time series, and it is impossible to intuitively understand the situation of on-site construction operations. Summary of the invention

[0006] In order to overcome the above problems, the present disclosure provides a multi-dimensional visualization display method for power grid field operations.

[0007] The technical solution of the present disclosure is as follows:

[0008] A multi-dimensional visualization display method for power grid field operations includes the following steps:

[0009] Acquire multi-dimensional data of power field operation, wherein the multi-dimensional data of power field operation includes text data, image data and video data, wherein the text data includes operation content and operation status feedback, and the image data and video data are collected by equipment of power field operation;

[0010] Preprocessing the multi-dimensional data of the power field operation to obtain data for three-dimensional display;

[0011] Construct the display scenes of time and space dimensions. The display scenes of space dimension are constructed as follows:

[0012] Through the multi-dimensional data of power field operations, combined with the coordinates of three-dimensional positioning anchor points, a virtual display of the construction site with environmental information data, personnel form data and equipment appearance data of the three-dimensional model is carried out, and the form of each factor is displayed through polygonal modeling, surface modeling and parametric modeling;

[0013] The display scenario of the time dimension is constructed as follows:

[0014] By obtaining the personnel positioning coordinates, equipment positioning coordinates and three-dimensional positioning anchor point coordinate data at the power operation site, animation technology is used to simulate the movement trajectory and shape changes of objects, producing more realistic animation effects and visual perception.

[0015] Furthermore, obtaining data of power field operations includes the following steps:

[0016] Define the data structure of text data, image data and video data;

[0017] Acquire text data, image data and video data of power field operation as multi-dimensional data of power field operation;

[0018] Obtain operation information, site fence information and equipment positioning information through multi-dimensional data of power field operations.

[0019] Furthermore, in preprocessing the multi-dimensional data of the power field operation, the video data is preprocessed in the following manner:

[0020] Identify video image content and obtain identification objects;

[0021] Obtain the size and height information of the identified object;

[0022] Obtaining distance information between different identified objects;

[0023] Output the three-dimensional data information between each identified object.

[0024] Furthermore, obtaining the size and height information of the identified object includes the following steps:

[0025] Use feature point detection algorithm to obtain key feature points of objects in the video;

[0026] By comparing the position changes of the feature points of the same object in different frames, the relative values ​​of the size and height changes of the object are obtained. According to the size of the calibrated object in the video, the relative values ​​of the object are converted into estimated values.

[0027] Furthermore, obtaining the size and height information of the identified object includes the following steps:

[0028] Use convolutional neural networks to detect and classify objects. The convolutional neural network trained with labeled data can identify each object in the video and provide the bounding box information of the object.

[0029] The size of the bounding box is used to estimate the size and height of the object.

[0030] Furthermore, the convolutional neural network is YOLO or SSD.

[0031] Furthermore, obtaining distance information between different identification objects includes the following steps:

[0032] When collecting video data, the video data is collected through two cameras at preset positions;

[0033] Extract feature points from the video data and match them in the video data of the two cameras. Calculate the distance from the object to the camera based on the position difference of the matched feature points in the two video data and the parameters of the camera.

[0034] According to the distance from each identified object to the camera and the position information of the camera, the distance information between different identified objects is obtained.

[0035] Furthermore, obtaining distance information between different identification objects includes the following steps:

[0036] Get the actual size of the identified object;

[0037] According to the actual size of the identified object and the size in the video data, the distance relationship between the identified object and the video data acquisition device is obtained;

[0038] The spatial position of the identified object is obtained according to the distance between the identified object and different acquisition devices;

[0039] The distance information between different identification objects is obtained according to the spatial position of the identification object.

[0040] Furthermore, obtaining distance information between different identification objects includes the following steps:

[0041] Calculate the trajectory and speed of the identified object in the video;

[0042] The distance between the objects is obtained by comparing their motion trajectories and speeds.

[0043] Furthermore, the optical flow method is used to track the movement of the identified object, and the movement trajectory and speed of the identified object are calculated.

[0044] The present disclosure has the following beneficial effects:

[0045] This disclosure uses on-site operation control rules and regulations, operation work tickets, personnel and equipment information, operation monitoring videos, and operation violation images as the basis, combined with video recognition algorithms, to conduct on-site visual three-dimensional stereoscopic display, realize cloud-based perception of the entire operation site, and allow cloud-based personnel to have an in-depth understanding of the safety risks at the power operation site, solving the problem of opaque and unclear supervision of power site operations by cloud-based safety inspectors. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 The present invention is a method flow chart of an embodiment of the present invention.

[0047] Figure 2 This is the video data preprocessing process of the embodiment of the present disclosure. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0049] Unless otherwise defined, the technical terms or scientific terms used in the present disclosure should be understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly. In order to keep the following description of the embodiments of the present disclosure clear and concise, the present disclosure omits the detailed description of some known functions and known components.

[0050] The present disclosure is described in detail below with reference to the accompanying drawings and specific embodiments.

[0051] refer to Figure 1 , a multi-dimensional visualization display method for power grid field operations, comprising the following steps:

[0052] Acquire multi-dimensional data of power field operation, wherein the multi-dimensional data of power field operation includes text data, image data and video data, wherein the text data includes operation content and operation status feedback, and the image data and video data are collected by equipment of power field operation;

[0053] Preprocessing the multi-dimensional data of the power field operation to obtain data for three-dimensional display;

[0054] Construct the display scenes of time and space dimensions. The display scenes of space dimension are constructed as follows:

[0055] Through the multi-dimensional data of power field operations, combined with the coordinates of three-dimensional positioning anchor points, a virtual display of the construction site with environmental information data, personnel form data and equipment appearance data of the three-dimensional model is carried out, and the form of each factor is displayed through polygonal modeling, surface modeling and parametric modeling;

[0056] The display scenario of the time dimension is constructed as follows:

[0057] By obtaining the personnel positioning coordinates, equipment positioning coordinates and three-dimensional positioning anchor point coordinate data at the power operation site, animation technology is used to simulate the movement trajectory and shape changes of objects, producing more realistic animation effects and visual perception.

[0058] In one embodiment of the present invention, obtaining power field operation data includes the following steps:

[0059] Define the data structure of text data, image data and video data;

[0060] Acquire text data, image data and video data of power field operation as multi-dimensional data of power field operation;

[0061] Obtain operation information, site fence information and equipment positioning information through multi-dimensional data of power field operations.

[0062] refer to Figure 2 In one embodiment of the present invention, in preprocessing the multi-dimensional data of the power field operation, the video data is preprocessed in the following manner:

[0063] Identify video image content and obtain identification objects;

[0064] Obtain the size and height information of the identified object;

[0065] Obtaining distance information between different identified objects;

[0066] Output the three-dimensional data information between each identified object.

[0067] In one embodiment of the present invention, obtaining the size and height information of the identification object includes the following steps:

[0068] Use feature point detection algorithm to obtain key feature points of objects in the video;

[0069] By comparing the position changes of the feature points of the same object in different frames, the relative values ​​of the size and height changes of the object are obtained. According to the size of the calibrated object in the video, the relative values ​​of the object are converted into estimated values.

[0070] In one embodiment of the present invention, obtaining the size and height information of the identification object includes the following steps:

[0071] Use convolutional neural networks to detect and classify objects. The convolutional neural network trained with labeled data can identify each object in the video and provide the bounding box information of the object.

[0072] The size of the bounding box is used to estimate the size and height of the object.

[0073] In one embodiment of the present invention, the convolutional neural network is YOLO or SSD.

[0074] In one embodiment of the present invention, obtaining distance information between different identification objects includes the following steps:

[0075] When collecting video data, the video data is collected through two cameras at preset positions;

[0076] Extract feature points from the video data and match them in the video data of the two cameras. Calculate the distance from the object to the camera based on the position difference of the matched feature points in the two video data and the parameters of the camera.

[0077] According to the distance from each identified object to the camera and the position information of the camera, the distance information between different identified objects is obtained.

[0078] In one embodiment of the present invention, obtaining distance information between different identification objects includes the following steps:

[0079] Get the actual size of the identified object;

[0080] According to the actual size of the identified object and the size in the video data, the distance relationship between the identified object and the video data acquisition device is obtained;

[0081] The spatial position of the identified object is obtained according to the distance between the identified object and different acquisition devices;

[0082] The distance information between different identification objects is obtained according to the spatial position of the identification object.

[0083] In one embodiment of the present invention, obtaining distance information between different identification objects includes the following steps:

[0084] Calculate the trajectory and speed of the identified object in the video;

[0085] The distance between the objects is obtained by comparing their motion trajectories and speeds.

[0086] In one embodiment of the present invention, the optical flow method is used to track the movement of the identified object, and the movement trajectory and speed of the identified object are calculated.

[0087] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0088] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0089] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0090] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0091] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0092] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

[0093] There are a few points to note about this disclosure:

[0094] (1) The drawings of the embodiments of the present disclosure only relate to the structures related to the embodiments of the present disclosure, and other structures may refer to the general design.

[0095] (2) In the absence of conflict, the embodiments of the present disclosure and the features therein may be combined with each other to obtain new embodiments.

[0096] The above descriptions are merely embodiments of the present disclosure and are not intended to limit the patent scope of the present disclosure. Any equivalent structures made using the contents of the present disclosure and the drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present disclosure.

Claims

1. A multi-dimensional visualization display method for power grid field operations, characterized in that: The following steps are involved: Acquire multi-dimensional data of power field operations, wherein the multi-dimensional data of power field operations include text data, image data and video data, wherein the text data includes field operation management and control rules and regulations, operation work tickets, personnel and equipment information, and the image data and video data are collected by equipment for power field operations; Preprocessing the multi-dimensional data of the power field operation to obtain data for three-dimensional display; Construct the display scenes of time and space dimensions. The display scenes of space dimension are constructed as follows: Through the multi-dimensional data of power field operations, combined with the coordinates of three-dimensional positioning anchor points, a virtual display of the construction site with environmental information data, personnel form data and equipment appearance data of the three-dimensional model is carried out, and the form of each factor is displayed through polygonal modeling, surface modeling and parametric modeling; The display scenario of the time dimension is constructed as follows: By obtaining the personnel positioning coordinates, equipment positioning coordinates and three-dimensional positioning anchor point coordinate data at the power operation site, animation technology is used to simulate the movement trajectory and shape changes of objects, producing more realistic animation effects and visual perception.

2. The multi-dimensional visualization display method for power grid field operations according to claim 1 is characterized in that: Acquiring data from power field operations includes the following steps: Define the data structure of text data, image data and video data; Acquire text data, image data and video data of power field operation as multi-dimensional data of power field operation; Obtain operation information, site fence information and equipment positioning information through multi-dimensional data of power field operations.

3. The multi-dimensional visualization display method for power grid field operations according to claim 2 is characterized in that: In preprocessing the multi-dimensional data of the power field operation, the video data is preprocessed in the following manner: Identify video image content and obtain identification objects; Obtain the size and height information of the identified object; Obtaining distance information between different identified objects; Output the three-dimensional data information between each identified object.

4. The multi-dimensional visualization display method for power grid field operations according to claim 3 is characterized in that: Obtaining the size and height information of the identified object includes the following steps: Use feature point detection algorithm to obtain key feature points of objects in the video; By comparing the position changes of the feature points of the same object in different frames, the relative values ​​of the size and height changes of the object are obtained. According to the size of the calibrated object in the video, the relative values ​​of the object are converted into estimated values.

5. The multi-dimensional visualization display method for power grid field operations according to claim 3 is characterized in that: Obtaining the size and height information of the identified object includes the following steps: Use convolutional neural networks to detect and classify objects. The convolutional neural network trained with labeled data can identify each object in the video and provide the bounding box information of the object. The size of the bounding box is used to estimate the size and height of the object.

6. The multi-dimensional visualization display method for power grid field operations according to claim 3 is characterized in that: The convolutional neural network is YOLO or SSD.

7. The multi-dimensional visualization display method for power grid field operations according to claim 3 is characterized in that: Obtaining distance information between different objects includes the following steps: When collecting video data, the video data is collected through two cameras at preset positions; Extract feature points from the video data and match them in the video data of the two cameras. Calculate the distance from the object to the camera based on the position difference of the matched feature points in the two video data and the parameters of the camera. According to the distance from each identified object to the camera and the position information of the camera, the distance information between different identified objects is obtained.

8. The multi-dimensional visualization display method for power grid field operations according to claim 3 is characterized in that: Obtaining distance information between different objects includes the following steps: Get the actual size of the identified object; According to the actual size of the identified object and the size in the video data, the distance relationship between the identified object and the video data acquisition device is obtained; The spatial position of the identified object is obtained according to the distance between the identified object and different acquisition devices; The distance information between different identification objects is obtained according to the spatial position of the identification object.

9. The multi-dimensional visualization display method for power grid field operations according to claim 3, characterized in that: Obtaining distance information between different objects includes the following steps: Calculate the trajectory and speed of the identified object in the video; The distance between the objects is obtained by comparing their motion trajectories and speeds.

10. The multi-dimensional visualization display method for power grid field operations according to claim 9, characterized in that: The optical flow method is used to track the movement of the identified object and calculate the movement trajectory and speed of the identified object.

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