CN117237873A - Power grid engineering supervision method and device based on machine vision - Google Patents
Power grid engineering supervision method and device based on machine vision Download PDFInfo
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Abstract
A power grid engineering supervision method and device based on machine vision relate to the field of power grid engineering supervision; the method comprises the following steps: acquiring target monitoring data, wherein the target monitoring data are monitoring data acquired in a target time period; the target monitoring data comprise target power grid pictures shot in a preset supervision area through the camera equipment; judging whether a power grid system threat exists or not through the target monitoring data, wherein the power grid system threat comprises at least one of weather threat, plant threat, personnel threat and temperature threat; and if the power grid system threat is judged to exist through the target monitoring data, displaying target processing information to the user, wherein the target processing information is used for prompting the user that the power grid engineering has the power grid system threat in a target time period. By implementing the technical scheme provided by the application, the problem of low efficiency of manually supervising the power grid system can be solved.
Description
Technical Field
The application relates to the field of power grid engineering supervision, in particular to a power grid engineering supervision method and device based on machine vision.
Background
Power grid engineering supervision is an important means for safe operation of a power grid system.
In the process of power grid engineering supervision, the power transmission line needs to be ensured to run safely and smoothly, but because the power transmission line is often longer, the involved area is possibly more, and the speed of confirming the fault position or the potential threat of a worker facing some emergency or some potential threat of the power transmission line is lower, more efforts are required to perform real-time supervision, and the problem of the power transmission line is found in time, namely the efficiency of the manual supervision power grid system is lower.
Therefore, there is a need for a machine vision-based power grid engineering management method and apparatus.
Disclosure of Invention
The application provides a power grid engineering supervision method and device based on machine vision, which can solve the problem of lower efficiency of a manual supervision power grid system.
The application provides a power grid engineering supervision method based on machine vision in a first aspect, which is applied to a server and comprises the following steps: acquiring target monitoring data, wherein the target monitoring data are monitoring data acquired in a target time period; the target monitoring data comprise target power grid pictures shot in a preset supervision area through the camera equipment; judging whether a power grid system threat exists or not through the target monitoring data, wherein the power grid system threat comprises at least one of weather threat, plant threat, personnel threat and temperature threat; and if the power grid system threat is judged to exist through the target monitoring data, displaying target processing information to the user, wherein the target processing information is used for prompting the user that the power grid engineering has the power grid system threat in a target time period.
By adopting the technical scheme, the server can detect various possible power grid system threats, such as weather threats, plant threats, personnel threats and temperature threats by analyzing the power grid pictures acquired by the camera equipment, and can reduce the monitoring pressure of users and improve the efficiency and safety of power grid engineering by automatic monitoring and threat detection; if a threat exists, the user can immediately take corresponding measures, even if the threat of the power grid is solved.
Optionally, judging whether the threat of the power grid system exists according to the target monitoring data specifically includes: judging whether weather threats exist or not through the target monitoring data; judging whether weather threats exist or not through the target monitoring data specifically comprises the following steps: acquiring weather information, wherein the weather information is weather information of a preset supervision area in a target time period; judging whether weather information comprises extreme weather, wherein the extreme weather comprises extreme storm, snow storm, thunderstorm and sand storm; and if the weather information comprises extreme weather, confirming that the weather threat exists in the preset supervision area in the target time period.
Through adopting above-mentioned technical scheme, the weather information of preset supervision area at the target time quantum can be obtained to the server, including but not limited to extreme weather phenomena such as extra heavy storm, snow storm, thunderstorm and sand storm, can in time send out the early warning after confirming that there is the weather threat for the user can in time know and deal with the extreme weather condition that probably appears.
Optionally, judging whether the threat of the power grid system exists according to the target monitoring data specifically includes: judging whether plant threats exist or not through the target monitoring data; judging whether the plant threat exists through the target monitoring data specifically comprises the following steps: acquiring target plant height according to the target monitoring data, wherein the target plant height is the actual height of the plant in the target power grid picture; judging whether the height of the target plant is greater than or equal to a preset height threshold value; and if the target plant height is greater than or equal to the preset height threshold value, confirming that the plant threat exists in the preset supervision area in the target time period.
By adopting the technical scheme, the server acquires the actual height of the plant in the picture by analyzing the target power grid picture, and if the actual height of the plant is greater than or equal to the preset height threshold value, the server confirms that the plant possibly affects even damages the power grid system, and under the condition, the server can give an early warning to the user to remind the user to take countermeasures in time so as to reduce the possibility of plant interference or damage to the power grid.
Optionally, judging whether the threat of the power grid system exists according to the target monitoring data specifically includes: judging whether personnel threat exists or not through the target monitoring data; judging whether personnel threat exists or not through the target monitoring data specifically comprises the following steps: when the preset supervision area does not allow personnel to stay, judging whether the target power grid picture contains stay personnel or not through a preset image recognition technology; if the target power grid picture contains the stay person, acquiring the picture of the stay person, and capturing the picture of the stay person from the target power grid picture; and adding the pictures of the stay personnel into the target processing information, and confirming that personnel threat exists in the preset supervision area in the target time period.
Through adopting above-mentioned technical scheme, the server can automatic control and personnel threat detection, judges whether there is the person of stay in the preset supervision area in the target electric wire netting picture, when finding that there is the person of stay, can add the picture of the person of stay who obtains into target processing information to show the user.
Optionally, after adding the picture of the stay person to the target processing information and confirming that the preset supervision area has the threat of the person in the target time period, the method further includes: acquiring a resident-allowed personnel list, wherein the resident-allowed personnel list comprises face information of resident-allowed personnel; acquiring the facial similarity of the pictures of the stay personnel and the facial information; judging whether the face similarity is larger than or equal to a preset similarity threshold value; if the face similarity is greater than or equal to a preset similarity threshold, confirming that the stay person is a person allowed to stay, and canceling the threat of the person allowed to stay person; recording the stay time allowed for the stay personnel and displaying the stay time to the user.
By adopting the technical scheme, the server automatically compares whether the stay personnel in the preset supervision area belong to the personnel in the list of the allowed stay personnel, if so, the stay personnel can be allowed to stay, and the stay time is recorded for the subsequent processing and analysis of the user.
Optionally, judging whether the temperature threat exists according to the target monitoring data specifically includes: judging whether temperature threat exists or not through target monitoring data; judging whether the temperature threat exists or not through the target monitoring data specifically comprises the following steps: acquiring a current temperature value in target monitoring data, wherein the current temperature value is acquired by a thermal infrared imager carried in the camera equipment, and the current temperature value is a temperature value of power grid equipment; judging whether the current temperature value is greater than or equal to a preset temperature threshold value; and if the current temperature value is greater than or equal to the preset temperature threshold value, confirming that the preset supervision area has temperature threat in the target time period.
Through adopting above-mentioned technical scheme, the server can obtain the current temperature value of electric wire netting equipment through thermal infrared imager for the user can know the real-time temperature information of electric wire netting equipment in the target time quantum, and then can in time be greater than the condition of predetermineeing the temperature threshold value to current temperature and take corresponding measure, with the safe and steady operation of guarantee electric wire netting system.
Optionally, after determining whether there is a threat of the grid system by the target monitoring data, the method further includes: acquiring a target progress standard picture of a time point where a target time period is located, wherein the target progress standard picture is a preset picture of the construction progress of the power grid project; acquiring the progress similarity of a target progress standard picture and a target power grid picture; judging whether the progress similarity is larger than or equal to a preset progress similarity threshold value; if the progress similarity is greater than or equal to a preset progress similarity threshold, the construction progress of the target time period meets the user requirement.
By adopting the technical scheme, the server can automatically evaluate the construction progress of the target time period and display the construction progress to the user so that the user can better make decisions and ensure that the power grid engineering is finished according to the quality on time.
The application provides a power grid engineering supervision device based on machine vision in a second aspect, wherein the device is a server, and the server comprises an acquisition unit and a processing unit;
the acquisition unit is used for acquiring target monitoring data, wherein the target monitoring data are monitoring data acquired in a target time period; the target monitoring data comprise target power grid pictures shot in a preset supervision area through the camera equipment.
The processing unit is used for judging whether a power grid system threat exists or not through the target monitoring data, wherein the power grid system threat comprises at least one of weather threat, plant threat, personnel threat and temperature threat; and if the target monitoring data is used for judging that the power grid system threat exists, displaying target processing information to the user, wherein the target processing information is used for prompting the user that the power grid engineering has the power grid system threat in a target time period.
Optionally, the acquiring unit is configured to acquire weather information, where the weather information is weather information of a preset supervision area in a target time period; the processing unit is used for judging whether the weather information comprises extreme weather, wherein the extreme weather comprises extreme storm, snow storm, thunderstorm and sand storm; and if the weather information comprises extreme weather, confirming that the weather threat exists in the preset supervision area in the target time period.
Optionally, the acquiring unit is configured to acquire a target plant height according to the target monitoring data, where the target plant height is an actual plant height in the target power grid picture; the processing unit is used for judging whether the height of the target plant is greater than or equal to a preset height threshold value; and if the target plant height is greater than or equal to the preset height threshold value, confirming that the plant threat exists in the preset supervision area in the target time period.
Optionally, the processing unit is configured to determine whether a person in the target power grid picture exists or not through a preset image recognition technology when the preset supervision area does not allow the person to stay; adding pictures of the stay personnel into target processing information, and confirming that personnel threat exists in a preset supervision area in a target time period; the acquisition unit is used for acquiring pictures of the stay personnel if the stay personnel exist in the target power grid picture, and the pictures of the stay personnel are acquired by intercepting the target power grid picture.
Optionally, the acquiring unit is configured to acquire a list of allowed stay people, where the list of allowed stay people includes face information of allowed stay people; acquiring the facial similarity of the pictures of the stay personnel and the facial information; the processing unit is used for judging whether the face similarity is larger than or equal to a preset similarity threshold value; if the face similarity is greater than or equal to a preset similarity threshold, confirming that the stay person is a person allowed to stay, and canceling the threat of the person allowed to stay person; recording the stay time allowed for the stay personnel and displaying the stay time to the user.
Optionally, the acquiring unit is configured to acquire a current temperature value in the target monitoring data, where the current temperature value is acquired by a thermal infrared imager carried in the image capturing device, and the current temperature value is a temperature value of the power grid device; the processing unit is used for judging whether the current temperature value is greater than or equal to a preset temperature threshold value; and if the current temperature value is greater than or equal to the preset temperature threshold value, confirming that the preset supervision area has temperature threat in the target time period.
Optionally, the acquiring unit is configured to acquire a target progress standard picture of a time point where the target time period is located, where the target progress standard picture is a preset picture of a power grid engineering construction progress; acquiring the progress similarity of a target progress standard picture and a target power grid picture; the processing unit is used for judging whether the progress similarity is larger than or equal to a preset progress similarity threshold value; if the progress similarity is greater than or equal to a preset progress similarity threshold, the construction progress of the target time period meets the user requirement.
The present application provides in a third aspect an electronic device comprising a processor, a memory for storing instructions, a user interface and a network interface for communicating with other devices, the processor for executing instructions stored in the memory to cause the electronic device to perform any one of the possible implementation methods of the first aspect or the first aspect above.
The present application provides in a fourth aspect a computer readable storage medium storing a computer program for execution by a processor as described above or any one of the possible implementation manners of the first aspect.
In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. the server can detect various possible power grid system threats, such as weather threats, plant threats, personnel threats and temperature threats, through analyzing the power grid pictures acquired by the camera equipment, and through automatic monitoring and threat detection, the monitoring pressure of a user can be reduced, and the efficiency and the safety of power grid engineering are improved; if a threat exists, the user can immediately take corresponding measures, even if the threat of the power grid is solved.
2. The server can acquire weather information of a preset supervision area in a target time period, including but not limited to extreme weather phenomena such as extremely heavy storm, snow storm, thunderstorm, sand storm and the like, and can timely send out early warning after confirming that weather threat exists, so that a user can timely know and cope with the extreme weather conditions possibly occurring.
3. The server acquires the actual height of the plant in the picture by analyzing the target power grid picture, and if the actual height of the plant is greater than or equal to the preset height threshold value, the server confirms that the plant possibly affects even damages the power grid system, and in the case, the server can send an early warning to the user to remind the user to take countermeasures in time so as to reduce the possibility of plant interference or damage to the power grid.
Drawings
Fig. 1 is a schematic flow chart of a power grid engineering supervision method based on machine vision according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a power grid engineering supervision device based on machine vision according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Reference numerals illustrate: 201. an acquisition unit; 202. a processing unit; 300. an electronic device; 301. a processor; 302. a communication bus; 303. a user interface; 304. a network interface; 305. a memory.
Description of the embodiments
In order that those skilled in the art will better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments.
In describing embodiments of the present application, words such as "for example" or "for example" are used to mean serving as examples, illustrations, or descriptions. Any embodiment or design described herein as "such as" or "for example" in embodiments of the application should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.
In the description of embodiments of the application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
In the process of power grid engineering supervision, the power transmission line needs to be ensured to run safely and smoothly, but because the power transmission line is often longer, the involved area is possibly more, and the speed of confirming the fault position or the potential threat of a worker facing some emergency or some potential threat of the power transmission line is lower, more efforts are required to perform real-time supervision, and the problem of the power transmission line is found in time, namely the efficiency of the manual supervision power grid system is lower. Therefore, the embodiment provides a power grid engineering supervision method based on machine vision.
The machine vision-based power grid engineering supervision method provided by the application can refer to fig. 1, and fig. 1 is a schematic flow chart of the machine vision-based power grid engineering supervision method provided by the embodiment of the application, and is applied to a server. The embodiment of the application takes a scene that a server acquires monitoring data through an imaging device of an imaging power grid system as an example. The method includes steps S101 to S103.
S101, acquiring target monitoring data, wherein the target monitoring data are monitoring data acquired in a target time period; the target monitoring data comprise target power grid pictures shot in a preset supervision area through the camera equipment.
In the step, the server acquires target monitoring data of a preset supervision area in a target time period through the camera equipment; the camera equipment can be a camera installed on a telegraph pole or an unmanned aerial vehicle with the camera equipment planned in advance, and the camera equipment installed on the telegraph pole has the advantages that a fixed area can be monitored in real time, but as the area of the area needing to be monitored is increased, the equipment needing to be installed on the telegraph pole is increased, and the supervision cost is increased; the unmanned aerial vehicle can change in real time because of the condition of the inspection power grid engineering, and can be conveniently removed for the built power grid engineering, and the unmanned aerial vehicle does not need to be detached one by one like a camera, namely has higher flexibility, but has the defect that if the number of unmanned aerial vehicles is less, the whole power grid engineering cannot be monitored in real time; the embodiment specifically uses a camera to illustrate, and the specific scene is that a server monitors power grid equipment in a fixed area region through the camera on a telegraph pole, and the power grid equipment is exemplified by a wire; the target time period length can be set according to the user requirement, in the target time period, the camera can shoot a plurality of live photos (namely, target power grid pictures) instead of being limited to one, and in the embodiment, for convenience of explanation, one live photo acquired in the target time period length is used for explanation; the target monitoring data are not limited to target power grid pictures, various data can be monitored according to user requirements, and corresponding monitoring equipment is required to be installed, for example, an insulation resistance tester is installed to obtain an insulation resistance value, and the corrosion condition of a power transmission wire can be rapidly known through the insulation resistance value.
S102, judging whether a power grid system threat exists through target monitoring data, wherein the power grid system threat comprises at least one of weather threat, plant threat, personnel threat and temperature threat.
In the above step, after the server acquires the target monitoring data, judging whether there is a threat of the power grid system, and many factors threaten the power grid system and the power grid equipment, for example, weather threat, plant threat, personnel threat and temperature threat listed in the step, for example, weather threat, heavy rainfall weather, strong wind weather and the like may cause serious damage to the power grid system; in addition, the corrosion of the electric wire and the bird perch and the short circuit caused on the electric wire are all factors which can threaten the power grid system, so the threat factors are not limited to the four listed in the steps, and the electric wire can be supplemented according to the requirements of users.
In one possible implementation manner, the method for judging whether the threat of the grid system exists according to the target monitoring data specifically includes: judging whether weather threats exist or not through the target monitoring data; judging whether weather threats exist or not through the target monitoring data specifically comprises the following steps: acquiring weather information, wherein the weather information is weather information of a preset supervision area in a target time period; judging whether weather information comprises extreme weather, wherein the extreme weather comprises extreme storm, snow storm, thunderstorm and sand storm; and if the weather information comprises extreme weather, confirming that the weather threat exists in the preset supervision area in the target time period.
Specifically, the server can acquire weather information of a preset supervision area, the weather information can be adjusted in precision according to the size of the area, and the weather information of the area with the smallest range can be acquired, for example, the weather information of a street from 12 points to 13 points on 1 month and 1 day; judging whether extreme weather exists or not through the weather information, preferably, the server can also acquire the weather information of a preset length time period after a target time period so as to early warn the extreme weather; extreme weather includes heavy storm, snow storm, thunderstorm, sand storm, typhoon, etc.; in these weather conditions, the probability of the grid system being destroyed is high, and extreme weather is monitored and confirmed.
In one possible implementation manner, the method for judging whether the threat of the grid system exists according to the target monitoring data specifically includes: judging whether plant threats exist or not through the target monitoring data; judging whether the plant threat exists through the target monitoring data specifically comprises the following steps: acquiring target plant height according to the target monitoring data, wherein the target plant height is the actual height of the plant in the target power grid picture; judging whether the height of the target plant is greater than or equal to a preset height threshold value; and if the target plant height is greater than or equal to the preset height threshold value, confirming that the plant threat exists in the preset supervision area in the target time period.
Specifically, the server judges whether plants exist in a preset supervision area or not by identifying target power grid pictures in target monitoring data, and the specific identification mode can be an image identification method or a similarity comparison method to judge and identify; under the condition that the existence of plants is judged, acquiring the target plant height in the target power grid picture through a plant height judging model which is built in advance; when the height of the target plant is greater than or equal to the preset height threshold value, the plant is more likely to threaten the power grid equipment, and when the tree below the electric wire grows to the height of the electric wire, the branches probably interfere and influence the electric wire, birds and insects can perch on the tree, and the probability of damaging the electric wire is increased.
In one possible implementation manner, the method for judging whether the threat of the grid system exists according to the target monitoring data specifically includes: judging whether personnel threat exists or not through the target monitoring data; judging whether personnel threat exists or not through the target monitoring data specifically comprises the following steps: when the preset supervision area does not allow personnel to stay, judging whether the target power grid picture contains stay personnel or not through a preset image recognition technology; if the target power grid picture contains the stay person, acquiring the picture of the stay person, and capturing the picture of the stay person from the target power grid picture; and adding the pictures of the stay personnel into the target processing information, and confirming that personnel threat exists in the preset supervision area in the target time period.
Specifically, the preset supervision area sometimes prohibits personnel other than the professional from stay for safety; therefore, the server can judge whether personnel threat exists or not by identifying whether the stay personnel exists in the target power grid picture; the specific recognition mode can acquire human features through an image recognition technology so as to further recognize whether an object with the human features is human or not, and preferably, auxiliary judgment can be carried out through a thermal infrared imager; when the existence of the stay personnel is judged, the picture of the stay personnel part in the target power grid picture is intercepted, and the picture of the stay personnel part is added into target processing information, so that a user can further judge whether the personnel can stay according to the picture of the stay personnel when confirming that the threat of the personnel exists.
In one possible implementation manner, after adding the picture of the stay person to the target processing information and confirming that the preset supervision area has a personal threat in the target time period, the method further includes: acquiring a resident-allowed personnel list, wherein the resident-allowed personnel list comprises face information of resident-allowed personnel; acquiring the facial similarity of the pictures of the stay personnel and the facial information; judging whether the face similarity is larger than or equal to a preset similarity threshold value; if the face similarity is greater than or equal to a preset similarity threshold, confirming that the stay person is a person allowed to stay, and canceling the threat of the person allowed to stay person; recording the stay time allowed for the stay personnel and displaying the stay time to the user.
Specifically, the server can acquire a list of allowed stay people, wherein the list stores the corresponding relation between face information and allowed stay permission; the server can compare the facial information with the pictures of the stay personnel to obtain facial similarity, and when the facial similarity is greater than or equal to a preset similarity threshold, the stay personnel are indicated to be the personnel in the list of the allowed stay personnel, and the personnel threat to the stay personnel is cancelled; it should be noted that, only a single person is identified and compared, and when a plurality of persons appear in the picture, the step is performed on the identified plurality of persons one by one; after allowing the person to stay, the stay time of the person is recorded so as to be available for the user to make subsequent reference.
In one possible implementation manner, the method for judging whether the temperature threat exists through the target monitoring data specifically comprises the following steps: judging whether temperature threat exists or not through target monitoring data; judging whether the temperature threat exists or not through the target monitoring data specifically comprises the following steps: acquiring a current temperature value in target monitoring data, wherein the current temperature value is acquired by a thermal infrared imager carried in the camera equipment, and the current temperature value is a temperature value of power grid equipment; judging whether the current temperature value is greater than or equal to a preset temperature threshold value; and if the current temperature value is greater than or equal to the preset temperature threshold value, confirming that the preset supervision area has temperature threat in the target time period.
Specifically, the server acquires a current temperature value of a power grid system through a thermal infrared imager carried in the image pickup equipment, wherein the power grid system consists of different parts, so that the situation that the temperatures of the different parts are different exists, and in the situation, the temperature of the part with the highest temperature is taken as the current temperature value; the staff can also assign the temperature value as the temperature of a part of the power grid system which is easy to cause problems according to the requirements; when the current temperature value is greater than or equal to the preset temperature threshold value, the current temperature value is too high, and the preset supervision area has temperature threat in the target time period.
In one possible embodiment, after determining whether there is a threat to the grid system by the target monitoring data, the method further comprises: acquiring a target progress standard picture of a time point where a target time period is located, wherein the target progress standard picture is a preset picture of the construction progress of the power grid project; acquiring the progress similarity of a target progress standard picture and a target power grid picture; judging whether the progress similarity is larger than or equal to a preset progress similarity threshold value; if the progress similarity is greater than or equal to a preset progress similarity threshold, the construction progress of the target time period meets the user requirement.
Specifically, the server can acquire a target progress standard picture and compare the target progress standard picture with a target power grid picture shot at present to obtain progress similarity, and when the progress similarity is greater than or equal to a preset progress similarity threshold value, the actual construction progress of the power grid system is indicated to reach a preset progress target, namely, the actual construction progress meets the requirements of users; when the progress similarity is smaller than a preset progress similarity threshold, the current construction progress is indicated to be faster or slower, and the target power grid picture is displayed to the user at the moment so as to assist the user in judging the actual condition of the progress.
And S103, if the power grid system threat is judged to exist through the target monitoring data, displaying target processing information to a user, wherein the target processing information is used for prompting the user that the power grid engineering has the power grid system threat in a target time period.
In the above steps, after judging that at least one power grid system threat exists, the server displays prompt information (i.e. target processing information) corresponding to the existing power grid system threat to the user, where the prompt information may include coordinates and time periods of the occurrence of the power grid system threat, and may also include a photograph for judgment when the threat is identified; the user can solve the threat after looking at the prompt information, so as to avoid the problem that the prompt information is always displayed due to misjudgment of the threat.
The application also provides a power grid engineering supervision device based on machine vision, which comprises an acquisition unit 201 and a processing unit 202, and is shown in fig. 2.
An acquiring unit 201, configured to acquire target monitoring data, where the target monitoring data is monitoring data acquired in a target time period; the target monitoring data comprise target power grid pictures shot in a preset supervision area through the camera equipment.
A processing unit 202, configured to determine whether a power grid system threat exists according to the target monitoring data, where the power grid system threat includes at least one of a weather threat, a plant threat, a personnel threat, and a temperature threat; and if the target monitoring data is used for judging that the power grid system threat exists, displaying target processing information to the user, wherein the target processing information is used for prompting the user that the power grid engineering has the power grid system threat in a target time period.
In a possible implementation manner, the obtaining unit 201 is configured to obtain weather information, where the weather information is weather information of a preset supervision area in a target period; the processing unit 202 is configured to determine whether the weather information includes extreme weather, where the extreme weather includes extreme storm, snow storm, thunderstorm, and sand storm; and if the weather information comprises extreme weather, confirming that the weather threat exists in the preset supervision area in the target time period.
In a possible implementation manner, the obtaining unit 201 is configured to obtain a target plant height according to the target monitoring data, where the target plant height is an actual plant height in the target grid picture; the processing unit 202 is configured to determine whether the target plant height is greater than or equal to a preset height threshold; and if the target plant height is greater than or equal to the preset height threshold value, confirming that the plant threat exists in the preset supervision area in the target time period.
In a possible implementation manner, the processing unit 202 is configured to determine, when the preset supervision area does not allow the person to stay, whether the person to stay exists in the target power grid picture through a preset image recognition technology; adding pictures of the stay personnel into target processing information, and confirming that personnel threat exists in a preset supervision area in a target time period; the obtaining unit 201 is configured to obtain a picture of a stay person if the target power grid picture includes the stay person, and the picture of the stay person is obtained by capturing the target power grid picture.
In a possible embodiment, the obtaining unit 201 is configured to obtain a list of allowed stay people, where the list of allowed stay people includes face information of allowed stay people; acquiring the facial similarity of the pictures of the stay personnel and the facial information; the processing unit 202 is configured to determine whether the facial similarity is greater than or equal to a preset similarity threshold; if the face similarity is greater than or equal to a preset similarity threshold, confirming that the stay person is a person allowed to stay, and canceling the threat of the person allowed to stay person; recording the stay time allowed for the stay personnel and displaying the stay time to the user.
In a possible implementation manner, the obtaining unit 201 is configured to obtain a current temperature value in the target monitoring data, where the current temperature value is obtained by a thermal infrared imager mounted in the image capturing device, and the current temperature value is a temperature value of the power grid device; the processing unit 202 is configured to determine whether the current temperature value is greater than or equal to a preset temperature threshold; and if the current temperature value is greater than or equal to the preset temperature threshold value, confirming that the preset supervision area has temperature threat in the target time period.
In a possible implementation manner, the obtaining unit 201 is configured to obtain a target progress standard picture of a time point where the target time period is located, where the target progress standard picture is a preset picture of a construction progress of the power grid project; acquiring the progress similarity of a target progress standard picture and a target power grid picture; the processing unit 202 is configured to determine whether the progress similarity is greater than or equal to a preset progress similarity threshold; if the progress similarity is greater than or equal to a preset progress similarity threshold, the construction progress of the target time period meets the user requirement.
It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.
The application also discloses a computer readable storage medium storing a computer program which is executed by a processor to perform the machine vision-based power grid engineering supervision method disclosed in the above specification.
The application also discloses electronic equipment. Referring to fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one communication bus 302, at least one user interface 303, a network interface 304, a memory 305.
Wherein the communication bus 302 is used to enable connected communication between these components.
The user interface 303 may include a Display screen (Display), a Camera (Camera), and the optional user interface 303 may further include a standard wired interface, and a wireless interface.
The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and lines to connect various portions of the overall server, perform various functions of the server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and invoking data stored in the memory 305. Alternatively, the processor 301 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 301 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 301 and may be implemented by a single chip.
The Memory 305 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 305 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. Memory 305 may also optionally be at least one storage device located remotely from the aforementioned processor 301. Referring to fig. 3, an operating system, a network communication module, a user interface module, and a machine vision based grid engineering management application may be included in memory 305 as one type of computer storage medium.
In the electronic device 300 shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 301 may be configured to invoke the machine vision based grid engineering management application stored in the memory 305, which when executed by the one or more processors 301, causes the electronic device 300 to perform the method as in one or more of the embodiments described above. It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all of the preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in whole or in part in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The above are merely exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure.
This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.
Claims (10)
1. The power grid engineering supervision method based on machine vision is characterized by comprising the following steps of:
acquiring target monitoring data, wherein the target monitoring data are monitoring data acquired in a target time period; the target monitoring data comprise target power grid pictures shot in a preset supervision area through the camera equipment;
judging whether a power grid system threat exists or not according to the target monitoring data, wherein the power grid system threat comprises at least one of weather threat, plant threat, personnel threat and temperature threat;
and if the power grid system threat is judged to exist through the target monitoring data, displaying target processing information to a user, wherein the target processing information is used for prompting the user that the power grid engineering has the power grid system threat in the target time period.
2. The method according to claim 1, wherein the determining whether there is a threat of the grid system by the target monitoring data specifically comprises: judging whether the weather threat exists or not according to the target monitoring data; the determining whether the weather threat exists according to the target monitoring data specifically includes:
acquiring weather information, wherein the weather information is weather information of the preset supervision area in the target time period;
judging whether the weather information comprises extreme weather or not, wherein the extreme weather comprises extreme storm, snow storm, thunderstorm and sand storm;
and if the weather information comprises the extreme weather, confirming that the weather threat exists in the preset supervision area in the target time period.
3. The method according to claim 1, wherein the determining whether there is a threat of the grid system by the target monitoring data specifically comprises: judging whether the plant threat exists or not according to the target monitoring data; the determining whether the plant threat exists according to the target monitoring data specifically includes:
acquiring target plant height according to the target monitoring data, wherein the target plant height is the actual height of the plant in the target power grid picture;
Judging whether the height of the target plant is greater than or equal to a preset height threshold value;
and if the target plant height is greater than or equal to the preset height threshold value, confirming that the plant threat exists in the preset supervision area in the target time period.
4. The method according to claim 1, wherein the determining whether there is a threat of the grid system by the target monitoring data specifically comprises: judging whether the personnel threat exists or not according to the target monitoring data; the determining whether the personal threat exists according to the target monitoring data specifically includes:
when the preset supervision area does not allow personnel to stay, judging whether the target power grid picture contains stay personnel or not through a preset image recognition technology;
if the stay person exists in the target power grid picture, acquiring the picture of the stay person, and intercepting the picture of the stay person from the target power grid picture;
and adding the pictures of the stay personnel into the target processing information, and confirming that the personnel threat exists in the preset supervision area in the target time period.
5. The method of claim 4, wherein after said adding a picture of said linger to said target process information confirming that said preset supervision area is in existence of said person threat for said target period of time, said method further comprises:
Acquiring a resident-allowed personnel list, wherein the resident-allowed personnel list comprises face information of resident-allowed personnel;
acquiring the facial similarity between the pictures of the stay personnel and the facial information;
judging whether the face similarity is larger than or equal to a preset similarity threshold value;
if the face similarity is greater than or equal to the preset similarity threshold, confirming that the stay person is the allowed stay person, and cancelling the person threat to the allowed stay person;
recording the stay time of the allowed stay personnel, and displaying the stay time to the user.
6. The method according to claim 1, wherein said determining whether a temperature threat exists by said target monitoring data comprises: judging whether the temperature threat exists or not according to the target monitoring data; the determining whether the temperature threat exists according to the target monitoring data specifically includes:
acquiring a current temperature value in the target monitoring data, wherein the current temperature value is acquired by a thermal infrared imager carried in the camera equipment, and the current temperature value is a temperature value of power grid equipment;
judging whether the current temperature value is greater than or equal to a preset temperature threshold value;
And if the current temperature value is greater than or equal to the preset temperature threshold value, confirming that the preset supervision area has the temperature threat in the target time period.
7. The method of claim 1, wherein after said determining whether a grid system threat exists from said target monitoring data, the method further comprises:
obtaining a target progress standard picture of a time point where the target time period is located, wherein the target progress standard picture is a preset picture of the construction progress of the power grid project;
acquiring the progress similarity of the target progress standard picture and the target power grid picture;
judging whether the progress similarity is larger than or equal to a preset progress similarity threshold value or not;
and if the progress similarity is greater than or equal to the preset progress similarity threshold, the construction progress of the target time period meets the user requirement.
8. Machine vision-based power grid engineering supervision device is characterized in that the device is a server, and the server comprises an acquisition unit (201) and a processing unit (202):
the acquisition unit (201) is configured to acquire target monitoring data, where the target monitoring data is monitoring data acquired in a target time period; the target monitoring data comprise target power grid pictures shot in a preset supervision area through the camera equipment;
The processing unit (202) is configured to determine whether a power grid system threat exists according to the target monitoring data, where the power grid system threat includes at least one of a weather threat, a plant threat, a personnel threat, and a temperature threat;
and the processing unit (202) is further configured to display target processing information to a user if the target monitoring data determines that the power grid system threat exists, where the target processing information is used to prompt the user that the power grid engineering has the power grid system threat in the target time period.
9. An electronic device comprising a processor (301), a memory (305), a user interface (303) and a network interface (304), the memory (305) being for storing instructions, the user interface (303) and the network interface (304) being for communicating to other devices, the processor (301) being for executing the instructions stored in the memory (305) for causing the electronic device (300) to perform the method according to any one of claims 1 to 7.
10. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the method of any of the preceding claims 1 to 7.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102013147A (en) * | 2010-09-29 | 2011-04-13 | 北京航空航天大学 | Intelligent burglary prevention monitoring method and device for high-voltage power transmission tower |
| CN105976117A (en) * | 2016-05-10 | 2016-09-28 | 国家电网公司 | Reliability evaluation method for power distribution network and expanded reliability evaluation method for different scales of power distribution networks |
| CN108510097A (en) * | 2017-02-27 | 2018-09-07 | 国网山西省电力公司 | Power transmission line corridor Snow Disaster monitoring method based on satellite remote sensing and system |
| CN111985401A (en) * | 2020-08-20 | 2020-11-24 | 重庆中科云从科技有限公司 | Area monitoring method, system, machine readable medium and equipment |
| CN112560745A (en) * | 2020-12-23 | 2021-03-26 | 南方电网电力科技股份有限公司 | Method for discriminating personnel on electric power operation site and related device |
| CN113904438A (en) * | 2020-07-06 | 2022-01-07 | 北京桔智物联科技有限责任公司 | Power distribution network monitoring device |
| CN116468392A (en) * | 2023-04-11 | 2023-07-21 | 国网上海市电力公司 | Method, device, equipment and storage medium for monitoring progress of power grid engineering project |
-
2023
- 2023-09-27 CN CN202311258278.4A patent/CN117237873A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102013147A (en) * | 2010-09-29 | 2011-04-13 | 北京航空航天大学 | Intelligent burglary prevention monitoring method and device for high-voltage power transmission tower |
| CN105976117A (en) * | 2016-05-10 | 2016-09-28 | 国家电网公司 | Reliability evaluation method for power distribution network and expanded reliability evaluation method for different scales of power distribution networks |
| CN108510097A (en) * | 2017-02-27 | 2018-09-07 | 国网山西省电力公司 | Power transmission line corridor Snow Disaster monitoring method based on satellite remote sensing and system |
| CN113904438A (en) * | 2020-07-06 | 2022-01-07 | 北京桔智物联科技有限责任公司 | Power distribution network monitoring device |
| CN111985401A (en) * | 2020-08-20 | 2020-11-24 | 重庆中科云从科技有限公司 | Area monitoring method, system, machine readable medium and equipment |
| CN112560745A (en) * | 2020-12-23 | 2021-03-26 | 南方电网电力科技股份有限公司 | Method for discriminating personnel on electric power operation site and related device |
| CN116468392A (en) * | 2023-04-11 | 2023-07-21 | 国网上海市电力公司 | Method, device, equipment and storage medium for monitoring progress of power grid engineering project |
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