CN117765451B - Joint control analysis method and system based on AI intelligent auxiliary control system equipment - Google Patents
Joint control analysis method and system based on AI intelligent auxiliary control system equipment Download PDFInfo
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Abstract
The invention provides a joint control analysis method and a system based on AI intelligent auxiliary control system equipment, which are used for acquiring an initial twin space corresponding to a patrol target, updating the initial twin space based on patrol configuration information of a management end to acquire the patrol twin space, wherein the patrol configuration information comprises a virtual patrol track and a virtual patrol node positioned on the virtual patrol track; receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node; the combined control analysis strategy is called to control the combined control equipment, and data acquisition is carried out based on the acquisition gesture group corresponding to the trigger inspection node, so that inspection data corresponding to the corresponding trigger inspection node is obtained; and receiving a triggering carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to the carding strategy to obtain carding data to be generated to the management end.
Description
Technical Field
The invention relates to a joint control technology, in particular to a joint control analysis method and system based on AI intelligent auxiliary control system equipment.
Background
The transformer substation is an important hub in the power system, and often has a large amount of power equipment, so that the transformer substation needs to be patrolled and inspected in order to know the working condition of the transformer substation in time, and the running state of the equipment is monitored.
At present, when a substation is patrolled and examined, manual work is generally sent to patrol and examine a plurality of transformer equipment in the substation, but because the range of patrolling and examining of the substation is big, the cost of manual work patrols and examines is higher and inefficiency.
Therefore, how to automatically generate the inspection strategy of the transformer substation and improve the inspection efficiency becomes a problem to be solved urgently.
Disclosure of Invention
The embodiment of the invention provides a joint control analysis method and a joint control analysis system based on AI intelligent auxiliary control system equipment, which can automatically generate a patrol strategy of a transformer substation and improve patrol efficiency.
In a first aspect of the embodiment of the present invention, a joint control analysis method based on an AI intelligent auxiliary control system device is provided, including:
Acquiring an initial twin space corresponding to an inspection target, and updating the initial twin space based on inspection configuration information of a management end to obtain an inspection twin space, wherein the inspection configuration information comprises a virtual inspection track and a virtual inspection node positioned on the virtual inspection track;
Receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node;
the combined control analysis strategy is called to control the combined control equipment, and data acquisition is carried out based on the acquisition gesture group corresponding to the trigger inspection node, so that inspection data corresponding to the trigger inspection node is obtained;
And receiving a triggering and carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to the carding strategy to obtain carding data to be generated to the management end.
Optionally, in one possible implementation manner of the first aspect, an initial twin space corresponding to the inspection target is obtained, the initial twin space is updated based on inspection configuration information of a management end, so as to obtain an inspection twin space, the inspection configuration information includes a virtual inspection track and a virtual inspection node located on the virtual inspection track, and the method includes:
analyzing the routing inspection configuration information to obtain a virtual routing inspection track corresponding to the actual routing inspection track, wherein virtual routing inspection nodes corresponding to the actual routing inspection nodes are arranged on the virtual routing inspection track;
acquiring actual numbers corresponding to the actual routing inspection nodes, numbering virtual routing inspection nodes corresponding to the actual routing inspection nodes according to the actual numbers, and acquiring virtual numbers corresponding to the virtual routing inspection nodes;
and updating the initial twin space according to the virtual tour-inspection track and the virtual tour-inspection node to obtain a tour-inspection twin space.
Optionally, in one possible implementation manner of the first aspect, receiving track trigger information of the inspection device, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and obtaining a joint control device corresponding to the trigger inspection node, where the joint control device includes:
Receiving track trigger information of the patrol equipment on the corresponding actual patrol nodes on the actual patrol track;
Obtaining a virtual number corresponding to the actual number of the actual routing inspection node in the routing inspection twin space as a target number;
And determining the virtual inspection node corresponding to the target number as a trigger inspection node, and acquiring the joint control equipment corresponding to the trigger inspection node.
Optionally, in one possible implementation manner of the first aspect, the invoking the joint control analysis policy controls the joint control device, and performs data acquisition based on the acquisition gesture group corresponding to the trigger patrol node to obtain patrol data corresponding to the trigger patrol node, including:
Controlling the inspection equipment to acquire images for one time according to the acquisition gesture group corresponding to the triggering inspection node to obtain a first image;
The joint control analysis strategy is called to perform joint control analysis on the first image to obtain joint control analysis data, the joint control equipment is controlled according to the joint control analysis data, and secondary image acquisition is performed based on the acquisition gesture group to obtain a second image;
acquiring a summarizing template corresponding to the trigger inspection node to summarize the first image and/or the second image, so as to obtain summarizing data corresponding to the trigger inspection node;
And carrying out abnormal object feedback processing on the summarized data to obtain feedback data, and obtaining corresponding inspection data corresponding to the trigger inspection node according to the summarized data and the feedback data.
Optionally, in one possible implementation manner of the first aspect, invoking a joint control analysis policy to perform joint control analysis on the first image to obtain joint control analysis data, controlling the joint control device according to the joint control analysis data, and performing secondary image acquisition based on the acquisition gesture group to obtain a second image, including:
Acquiring an image brightness value of the first image, and acquiring joint control analysis data according to a comparison result of the image brightness value and a preset image brightness value;
Determining a first image with the image brightness value smaller than the preset image brightness value as a deleted image according to the joint control analysis data;
starting the combined control equipment, acquiring a preset gesture corresponding to the deleted image, controlling the inspection equipment to acquire a secondary image based on the preset gesture, acquiring a second image corresponding to the corresponding preset gesture, deleting the deleted image, and acquiring a gesture group comprising a plurality of preset gestures.
Optionally, in one possible implementation manner of the first aspect, acquiring a summary template corresponding to the trigger patrol node to summary the first image and/or the second image, to obtain summary data corresponding to the trigger patrol node, includes:
a summary template corresponding to the trigger inspection node is called, wherein the summary template comprises a plurality of filling areas, and the filling areas are in one-to-one correspondence with the preset gestures;
and acquiring a first image or a second image corresponding to each preset gesture, and filling the first image or the second image into the corresponding filling area to obtain summarized data corresponding to the trigger inspection node.
Optionally, in one possible implementation manner of the first aspect, performing anomaly feedback processing on the summarized data to obtain feedback data, and obtaining, according to the summarized data and the feedback data, patrol data corresponding to the triggered patrol node includes:
A preset abnormal object is called to carry out feedback analysis on the first image and/or the second image corresponding to the summarized data, and the first image or the second image with the preset abnormal object is obtained to be used as a feedback image;
Determining a preset gesture corresponding to the feedback image as a feedback gesture, and controlling the inspection equipment to acquire data based on a preset duration and the feedback gesture to obtain feedback data corresponding to the corresponding trigger inspection node;
And obtaining inspection data according to the summarized data and the feedback data, and binding the inspection data with the corresponding trigger inspection node.
Optionally, in one possible implementation manner of the first aspect, receiving a trigger combing request of the management end for the virtual inspection track, combing inspection data of the virtual inspection track according to a combing policy, and obtaining combing data to occur to the management end, where the step includes:
Responding to the triggering carding request, and calling a preset patrol diagram, wherein the preset patrol diagram comprises a plurality of initial twin spaces corresponding to preset patrol targets;
calling a first preset pixel value to highlight an initial twin space corresponding to the patrol target in the preset patrol diagram, so as to obtain a patrol indication diagram;
acquiring a preset track map corresponding to the virtual inspection track, wherein the preset track map comprises display tracks corresponding to the virtual inspection track, and the display tracks comprise display nodes corresponding to the virtual inspection nodes;
Sequentially acquiring display nodes corresponding to the virtual inspection nodes in the preset track map as check nodes, and calling a second preset pixel value to perform protruding display on the check nodes to obtain node indication maps corresponding to the virtual inspection nodes;
And calling an initial display shaft, and updating the initial display shaft according to the inspection indication diagram, the node indication diagram and the inspection data to obtain carding data to the management end.
Optionally, in one possible implementation manner of the first aspect, the calling an initial display axis, updating the initial display axis according to the patrol indication map, the node indication map and the patrol data to obtain carded data, and generating the carded data to the management end includes:
Inserting each node indication graph into the forefront of the inspection data corresponding to the corresponding virtual inspection node to obtain filling data corresponding to each virtual inspection node;
Filling a groove position on the initial display shaft with a node corresponding to each virtual inspection node, and filling a groove position in a space corresponding to the initial twin space;
filling each filling data into a node filling slot corresponding to the corresponding virtual inspection node, filling the inspection indication map into the space filling slot, and obtaining carding data to the management end.
In a second aspect of the embodiment of the present invention, there is provided a joint control analysis system based on an AI intelligent auxiliary control system device, including:
The configuration module is used for acquiring an initial twin space corresponding to the patrol target, updating the initial twin space based on patrol configuration information of a management end to obtain a patrol twin space, wherein the patrol configuration information comprises a virtual patrol track and a virtual patrol node positioned on the virtual patrol track;
The trigger module is used for receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node;
The acquisition module is used for calling a joint control analysis strategy to control the joint control equipment, and acquiring data based on an acquisition gesture group corresponding to the trigger inspection node to obtain inspection data corresponding to the trigger inspection node;
and the carding module is used for receiving a triggering carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to the carding strategy to obtain carding data to be generated to the management end.
The beneficial effects of the invention are as follows:
1. The invention can automatically generate the inspection strategy of the transformer substation and improve the inspection efficiency. When the substation is inspected, the inspection twin space of the inspection equipment is firstly configured, so that the inspection data at each inspection node can be uploaded through the inspection twin space, the inspection data corresponding to each inspection node can be quickly acquired, and the efficiency of a user in inspecting the inspection data is improved. When the inspection data corresponding to the inspection nodes are acquired, the method can firstly determine the corresponding triggering inspection nodes in the inspection twin space according to the triggering information of the inspection equipment on the actual inspection nodes, then acquire the inspection data according to the combined control equipment and the acquisition gesture group corresponding to the triggering inspection nodes, and the accuracy in data acquisition can be improved through the combined control equipment and the acquisition gesture group. After the inspection data are acquired, the invention also carries out carding on the inspection data, so that the inspection data corresponding to the inspection nodes can be intuitively displayed for a user.
2. When the inspection equipment is controlled to collect data, the corresponding trigger inspection node is firstly determined, then the inspection equipment is controlled to collect the primary image according to the collection gesture group corresponding to the trigger inspection node, then the primary collected image is analyzed, and when the collected image is too dark in light, the combined control equipment is started to collect the secondary image of the too dark image, so that the definition of the collected image data can be improved, the inspection data at the trigger inspection node can be collected in all directions through the collection gesture group, and the comprehensiveness and accuracy of the inspection data collection are improved. In addition, the invention also generates corresponding feedback data when abnormal objects appear on the trigger inspection nodes, and the inspection conditions in the corresponding inspection areas are fed back through the feedback data, so that staff can process the corresponding inspection areas in time.
3. When the inspection data are carded, the inspection data corresponding to the virtual inspection nodes are carded and filled through the initial display shaft, so that the carded data can be intuitively displayed for users. The invention also generates the indication graph corresponding to the inspection target and the indication graph corresponding to each virtual inspection node, so that the specific inspection target and the virtual inspection node corresponding to the user inspection data can be indicated through the indication graph.
Drawings
FIG. 1 is a schematic flow chart of a joint control analysis method based on AI intelligent auxiliary control system equipment provided by the embodiment of the invention;
fig. 2 is a schematic structural diagram of a joint control analysis system based on an AI intelligent auxiliary control system device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flow chart of a joint control analysis method based on an AI intelligent auxiliary control system device according to an embodiment of the present application is shown, and an execution subject of the method shown in fig. 1 may be a software and/or hardware device. The execution body of the present application may include, but is not limited to, at least one of: user equipment, network equipment, etc. The user device may include, but is not limited to, a computer, a smart phone, a Personal Digital Assistant (PDA) DIGITAL ASSISTANT, and the above-mentioned electronic device. The network device may include, but is not limited to, a single network server, a server group of multiple network servers, or a cloud of a large number of computers or network servers based on cloud computing, where cloud computing is one of distributed computing, and a super virtual computer consisting of a group of loosely coupled computers. This embodiment is not limited thereto. The method comprises the steps S1 to S4, and specifically comprises the following steps:
S1, acquiring an initial twin space corresponding to an inspection target, and updating the initial twin space based on inspection configuration information of a management end to obtain the inspection twin space, wherein the inspection configuration information comprises a virtual inspection track and a virtual inspection node positioned on the virtual inspection track.
When the transformer substation is inspected, the inspection equipment is controlled to carry out corresponding inspection according to the actual inspection track, inspection data collected by the inspection equipment at each actual inspection node are uploaded to the inspection twin space, so that the inspection data can be summarized and carded through the inspection twin space, the inspection efficiency is improved, and the carded data can be intuitively displayed for a user.
The virtual inspection tracks and the actual inspection tracks are in one-to-one correspondence, and the virtual inspection nodes and the actual inspection nodes are also in one-to-one correspondence. The initial twin space is a twin space which is not configured with a virtual inspection track, and can comprise an area which needs to be inspected in a transformer substation.
In some embodiments, the above-described patrol twin-space may be obtained by:
S11, analyzing the routing inspection configuration information to obtain a virtual routing inspection track corresponding to the actual routing inspection track, wherein virtual routing inspection nodes corresponding to the actual routing inspection nodes are arranged on the virtual routing inspection track.
The actual inspection nodes refer to position points when the inspection equipment inspects the transformer substation, the position points can be correspondingly set by staff, for example, each actual inspection node can correspond to a corresponding data acquisition area, and when the inspection equipment reaches the actual inspection node, data in the corresponding area can be acquired.
S12, obtaining the actual numbers corresponding to the actual inspection nodes, numbering the virtual inspection nodes corresponding to the actual inspection nodes according to the actual numbers, and obtaining the virtual numbers corresponding to the virtual inspection nodes.
In practical application, when the actual routing inspection node and the virtual routing inspection node are corresponding, the corresponding virtual routing inspection node can be numbered through the actual number of the actual routing inspection node, for example, the actual number and the virtual number of the corresponding actual routing inspection node and virtual routing inspection node can be set to be the same.
And S13, updating the initial twin space according to the virtual tour inspection track and the virtual tour inspection node to obtain a tour inspection twin space.
Through the mode, visual inspection can be performed on the virtual inspection nodes corresponding to the actual inspection nodes through the inspection twin space, and efficiency of a user in data inspection is improved.
S2, receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node.
It can be appreciated that in practical application, the inspection device may inspect a plurality of inspection nodes, so in order to enable inspection data collected by the inspection device to correspond to corresponding inspection nodes, the scheme can determine the trigger inspection node for data collection through track trigger information of the inspection device, and acquire the combined control device for triggering the inspection node, so that corresponding collection can be carried out on data for triggering the inspection node through the combined control device. Wherein, the inspection equipment can be an inspection robot.
Specifically, step S2 may be implemented through steps S21 to S23, which are specifically as follows:
S21, receiving track trigger information of the patrol equipment on the corresponding actual patrol nodes on the actual patrol tracks.
In practical application, when the inspection device triggers an actual inspection node on an actual inspection track, corresponding track trigger information can be generated through a sensor arranged at the actual inspection node. The sensor arranged at the actual inspection node can be an infrared sensor, and when the inspection equipment triggers the corresponding infrared sensor, track trigger information corresponding to the corresponding actual inspection node can be generated.
S22, obtaining a virtual number corresponding to the actual number of the actual inspection node in the inspection twin space as a target number.
Because the scheme is that the actual numbers and the virtual numbers are used for carrying out one-to-one correspondence on the actual inspection nodes and the virtual inspection nodes, the virtual inspection nodes corresponding to the corresponding actual inspection nodes can be obtained through the actual numbers.
S23, determining the virtual inspection node corresponding to the target number as a trigger inspection node, and acquiring the combined control equipment corresponding to the trigger inspection node.
By the method, the virtual inspection nodes for data acquisition can be determined, so that the acquired inspection data can be bound with the corresponding virtual inspection nodes subsequently, and the inspection data corresponding to each virtual inspection node can be acquired rapidly.
And S3, calling a combined control analysis strategy to control the combined control equipment, and acquiring data based on the acquisition gesture group corresponding to the trigger inspection node to obtain inspection data corresponding to the trigger inspection node.
After determining the trigger routing inspection node, the scheme can control routing inspection equipment to collect routing inspection data at the trigger routing inspection node and bind the collected routing inspection data with the corresponding trigger routing inspection node. When the inspection data are acquired, the scheme can correspondingly acquire the inspection nodes according to the combined control equipment and the acquisition gesture group corresponding to the triggered inspection nodes.
The specific implementation manner of step S3 based on the above embodiment may be:
S31, controlling the inspection equipment to perform image acquisition once according to the acquisition gesture group corresponding to the triggering inspection node, and obtaining a first image.
In practical applications, the combined control device may be a lighting device. It can be understood that when the image is collected, because the collected places are different, the light rays during the collection are different, the images collected at some collecting positions can be normal, and the collected images at some collecting positions can have poor image effect due to the too dark light rays, so that the scheme can firstly collect the image according to the collecting gesture group when controlling the combined control equipment, and then correspondingly control the combined control equipment after analyzing the collected first image.
The collection gesture group can comprise a plurality of preset shooting gestures preset by a worker, and it can be understood that because collected places are different, data to be collected may be different, if the data are collected according to the unified preset shooting gestures, the collection of the inspection data of some collected places may be insufficient, and therefore the worker can configure the collection gesture group corresponding to each virtual inspection node in advance, and accordingly the inspection data at the corresponding virtual inspection node can be collected more comprehensively through the collection gesture group.
S32, invoking a joint control analysis strategy to perform joint control analysis on the first image to obtain joint control analysis data, controlling the joint control equipment according to the joint control analysis data, and performing secondary image acquisition based on the acquisition gesture group to obtain a second image.
In some embodiments, the joint control analysis strategy is called to perform joint control analysis on the first image to obtain joint control analysis data, the joint control equipment is controlled according to the joint control analysis data, and secondary image acquisition is performed based on the acquisition gesture group to obtain a second image:
S321, obtaining an image brightness value of the first image, and obtaining joint control analysis data according to a comparison result of the image brightness value and a preset image brightness value.
In practical application, the image brightness value of the first image may be obtained by using an image brightness calculation method in the prior art, for example, an opencv may be used to obtain the image brightness value of the first image, which is not described herein in detail. The preset image brightness value can be set correspondingly by a worker according to actual requirements.
S322, determining the first image with the image brightness value smaller than the preset image brightness value as a deleted image according to the joint control analysis data.
It can be understood that if the image brightness value is smaller than the preset image brightness value, it indicates that the light of the inspection device during data acquisition may be too dark, and the image data acquired under such conditions may not be very good, so that the corresponding first image may be used as a deleted image, and the deleted image is deleted later, and image data acquisition is performed again, so that the image definition of the inspection data may be improved.
S323, starting the combined control equipment, acquiring a preset gesture corresponding to the deleted image, controlling the inspection equipment to acquire a secondary image based on the preset gesture, acquiring a second image corresponding to the corresponding preset gesture, deleting the deleted image, and acquiring a gesture group comprising a plurality of preset gestures.
When the secondary image acquisition is carried out, the combined control equipment can be started, the secondary image acquisition is carried out according to the preset gesture corresponding to the deleted image, then the deleted image is deleted, and the acquired second image is used as a final acquired image corresponding to the corresponding preset gesture.
In some embodiments, after the combined control device is turned on, the illuminance of the combined control device can be correspondingly adjusted according to the image brightness value of the first image, so that the lighting effect of the combined control device can be optimized, and the definition of the acquired second image can be improved.
And S33, acquiring a summary template corresponding to the trigger inspection node to summarize the first image and/or the second image, so as to obtain summary data corresponding to the trigger inspection node.
It can be understood that the trigger inspection node may correspond to more than one image data, so after the first image and/or the second image are obtained, the first image and/or the second image may be summarized to obtain summarized data corresponding to the trigger inspection node.
Specifically, the summary data may be obtained by:
s331, calling a summary template corresponding to the trigger inspection node, wherein the summary template comprises a plurality of filling areas, and the filling areas correspond to the preset gestures one by one.
In practical application, a worker can preset a corresponding summarizing template for a corresponding virtual inspection node according to the collection gesture group, so that image data collected by each preset gesture can be summarized through the summarizing template.
S332, acquiring a first image or a second image corresponding to each preset gesture, and filling the first image or the second image into the corresponding filling area to obtain summarized data corresponding to the trigger inspection node.
In some embodiments, when the first image or the second image is filled into the respective filling area, the center point of the respective first image or the second image may be positioned by the center point of the filling area, and the respective first image or the second image is filled into the respective filling area.
S34, performing abnormal object feedback processing on the summarized data to obtain feedback data, and obtaining corresponding inspection data corresponding to the trigger inspection node according to the summarized data and the feedback data.
In practical application, the equipment of patrolling and examining is when patrolling and examining, probably can shoot the unusual thing, and under this condition, the regional internal probably problematic of corresponding patrolling and examining, consequently in order to remind the staff in time to make the targeted processing to corresponding area of patrolling and examining, this scheme still can carry out feedback processing to summarized data, obtain feedback data, obtain the corresponding data of patrolling and examining that triggers the node and correspond through feedback data and summarized data for the staff can be through the data of patrolling and examining to the regional condition of patrolling and examining of corresponding patrolling and examining.
In some embodiments, step S34 may be implemented through steps S341 to S343, which is specifically as follows:
s341, a preset anomaly is called to perform feedback analysis on the first image and/or the second image corresponding to the summarized data, and the first image or the second image with the preset anomaly is obtained to be used as a feedback image.
In practical application, the preset anomaly may be an anomaly preset by a worker, for example, the preset anomaly may be a person, it is understood that devices in some areas of the transformer substation may be in a high-voltage state, and if the worker walks at will, it may be dangerous, so the worker may set the preset anomaly as a person when setting the preset anomaly. In addition, in other cases, the preset abnormal object may be set as another object according to the actual requirement.
It will be appreciated that if a preset anomaly exists in the first image or the second image, it is indicated that the corresponding inspection area may be abnormal, and thus the corresponding first image or the second image may be used as a feedback image, through which the corresponding inspection area is fed back.
S342, determining the preset gesture corresponding to the feedback image as a feedback gesture, and controlling the inspection equipment to acquire data based on the preset duration and the feedback gesture to obtain feedback data corresponding to the corresponding trigger inspection node.
Specifically, in order to perform abnormal feedback on the corresponding inspection area, data acquisition can be performed according to the feedback gesture and the preset duration corresponding to the feedback image, and the acquired video data are used as feedback data, so that abnormal conditions in the corresponding inspection area can be fed back through the feedback data.
S343, obtaining inspection data according to the summarized data and the feedback data, and binding the inspection data with the corresponding trigger inspection node.
Through the mode, the inspection data of each virtual inspection node can be quickly acquired through the inspection twin space, so that the efficiency of inspection data inspection can be improved, the inspection condition of each inspection area can be fed back through the inspection data, and a worker can timely conduct targeted processing through the inspection data.
S4, receiving a triggering and carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to the carding strategy to obtain carding data to the management end.
In order to intuitively display the acquired plurality of inspection data, the inspection data can be further carded according to the carding strategy, and the carded carding data are sent to the management end, so that the management end can intuitively check the inspection data.
The specific implementation manner of step S4 based on the above embodiment may be:
S41, responding to the triggering carding request, and calling a preset patrol chart, wherein the preset patrol chart comprises a plurality of initial twin spaces corresponding to preset patrol targets.
The preset inspection map comprises a plurality of preset inspection targets which need to be inspected in the transformer substation, and each preset inspection target can correspond to a target area which needs to be inspected. It will be appreciated that since the preset inspection targets are different, the initial twin space corresponding to each preset inspection target is also different. For example, a distribution equipment area in a substation may correspond to one preset patrol target, a main area may correspond to another preset patrol target, and the areas to be patrol may be different, so that the corresponding initial twin spaces may also be different.
S42, a first preset pixel value is called to highlight an initial twin space corresponding to the inspection target in the preset inspection image, and an inspection indication image is obtained.
It can be understood that, in order to enable a user to know a patrol target specifically corresponding to the patrol data, an initial twin space corresponding to the patrol target in the preset patrol image can be highlighted by a first preset pixel value.
S43, obtaining a preset track map corresponding to the virtual inspection track, wherein the preset track map comprises display tracks corresponding to the virtual inspection track, and the display tracks comprise display nodes corresponding to the virtual inspection nodes.
It can be understood that, since the virtual inspection track corresponding to the initial twin space may have a plurality of virtual inspection nodes, in order to enable a user to know which virtual inspection node the inspection data specifically corresponds to, a preset track diagram corresponding to the virtual inspection track may be obtained, and the virtual inspection nodes corresponding to each inspection data are indicated by the preset track diagram.
S44, sequentially obtaining display nodes corresponding to the virtual inspection nodes in the preset track map as check nodes, and calling a second preset pixel value to perform protruding display on the check nodes to obtain node indication maps corresponding to the virtual inspection nodes.
For example, if a certain virtual inspection node corresponds to a first display node in the preset track map, the first display node may be highlighted according to the second preset pixel value, so as to obtain a node indication map corresponding to the virtual inspection node.
S45, the initial display shaft is called, and the initial display shaft is updated according to the inspection indication map, the node indication map and the inspection data to obtain carding data, and the carding data are generated to the management end.
In some embodiments, step S45 may be implemented by steps S451 to S453:
S451, inserting each node indication graph into the forefront of the inspection data corresponding to the corresponding virtual inspection node, and obtaining the filling data corresponding to each virtual inspection node.
It can be understood that the node indication map is inserted into the forefront of the patrol data corresponding to the corresponding virtual patrol node, so as to prompt the user of the specific virtual patrol node corresponding to the corresponding patrol data through the node indication map.
S452, filling a slot position corresponding to each virtual inspection node and a space filling slot position corresponding to the initial twin space are constructed on the initial display shaft.
In some embodiments, when node filling slots corresponding to each virtual inspection node are constructed, each virtual inspection node may be arranged according to an acquisition order to obtain a node sequence, then node filling slots corresponding to each virtual inspection node are constructed according to the node sequence, and space filling slots are constructed before all the nodes are filled with slots.
It should be noted that if one virtual inspection node has multiple poses corresponding to multiple images, at this time, the virtual inspection node needs to correspondingly construct multiple node filling slots, so that the images corresponding to the virtual inspection node can be filled into the corresponding node filling slots.
S453, filling each filling data into a node filling slot corresponding to the corresponding virtual inspection node, filling the inspection indication map into the space filling slot, and obtaining carding data to the management end.
By the mode, the inspection data corresponding to the inspection target can be carded, and the carded data can be intuitively displayed for a user.
Referring to fig. 2, a schematic structural diagram of a joint control analysis system based on an AI intelligent auxiliary control system device according to an embodiment of the present invention includes:
The configuration module is used for acquiring an initial twin space corresponding to the patrol target, updating the initial twin space based on patrol configuration information of a management end to obtain a patrol twin space, wherein the patrol configuration information comprises a virtual patrol track and a virtual patrol node positioned on the virtual patrol track;
The trigger module is used for receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node;
The acquisition module is used for calling a joint control analysis strategy to control the joint control equipment, and acquiring data based on an acquisition gesture group corresponding to the trigger inspection node to obtain inspection data corresponding to the trigger inspection node;
and the carding module is used for receiving a triggering carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to the carding strategy to obtain carding data to be generated to the management end.
The apparatus of the embodiment shown in fig. 2 may be correspondingly used to perform the steps in the embodiment of the method shown in fig. 1, and the implementation principle and technical effects are similar, and are not repeated here.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (7)
1. A joint control analysis method based on AI intelligent auxiliary control system equipment is characterized by comprising the following steps:
Acquiring an initial twin space corresponding to an inspection target, and updating the initial twin space based on inspection configuration information of a management end to obtain an inspection twin space, wherein the inspection configuration information comprises a virtual inspection track and a virtual inspection node positioned on the virtual inspection track;
Receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node;
the combined control analysis strategy is called to control the combined control equipment, and data acquisition is carried out based on the acquisition gesture group corresponding to the trigger inspection node, so that inspection data corresponding to the trigger inspection node is obtained;
receiving a triggering and carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to a carding strategy to obtain carding data to be generated to the management end;
The combined control analysis strategy is called to control the combined control equipment, and data acquisition is carried out based on the acquisition gesture group corresponding to the trigger inspection node to obtain inspection data corresponding to the trigger inspection node, and the method comprises the following steps:
Controlling the inspection equipment to acquire images for one time according to the acquisition gesture group corresponding to the triggering inspection node to obtain a first image;
The joint control analysis strategy is called to perform joint control analysis on the first image to obtain joint control analysis data, the joint control equipment is controlled according to the joint control analysis data, and secondary image acquisition is performed based on the acquisition gesture group to obtain a second image;
acquiring a summarizing template corresponding to the trigger inspection node to summarize the first image and/or the second image, so as to obtain summarizing data corresponding to the trigger inspection node;
Performing abnormal object feedback processing on the summarized data to obtain feedback data, and obtaining corresponding inspection data of the trigger inspection node according to the summarized data and the feedback data;
The method for acquiring the combined control analysis strategy to perform combined control analysis on the first image to obtain combined control analysis data, controlling the combined control equipment according to the combined control analysis data, and performing secondary image acquisition based on the acquisition gesture group to obtain a second image, comprises the following steps:
Acquiring an image brightness value of the first image, and acquiring joint control analysis data according to a comparison result of the image brightness value and a preset image brightness value;
Determining a first image with the image brightness value smaller than the preset image brightness value as a deleted image according to the joint control analysis data;
Starting the combined control equipment, acquiring a preset gesture corresponding to the deleted image, controlling the inspection equipment to acquire a secondary image based on the preset gesture, acquiring a second image corresponding to the corresponding preset gesture, deleting the deleted image, and acquiring a gesture group comprising a plurality of preset gestures;
Receiving a triggering and carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to a carding strategy to obtain carding data to be generated to the management end, wherein the method comprises the following steps:
Responding to the triggering carding request, and calling a preset patrol diagram, wherein the preset patrol diagram comprises a plurality of initial twin spaces corresponding to preset patrol targets;
calling a first preset pixel value to highlight an initial twin space corresponding to the patrol target in the preset patrol diagram, so as to obtain a patrol indication diagram;
acquiring a preset track map corresponding to the virtual inspection track, wherein the preset track map comprises display tracks corresponding to the virtual inspection track, and the display tracks comprise display nodes corresponding to the virtual inspection nodes;
Sequentially acquiring display nodes corresponding to the virtual inspection nodes in the preset track map as check nodes, and calling a second preset pixel value to perform protruding display on the check nodes to obtain node indication maps corresponding to the virtual inspection nodes;
And calling an initial display shaft, and updating the initial display shaft according to the inspection indication diagram, the node indication diagram and the inspection data to obtain carding data to the management end.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The method comprises the steps of obtaining an initial twin space corresponding to an inspection target, updating the initial twin space based on inspection configuration information of a management end to obtain an inspection twin space, wherein the inspection configuration information comprises a virtual inspection track and a virtual inspection node positioned on the virtual inspection track, and the method comprises the following steps:
analyzing the routing inspection configuration information to obtain a virtual routing inspection track corresponding to the actual routing inspection track, wherein virtual routing inspection nodes corresponding to the actual routing inspection nodes are arranged on the virtual routing inspection track;
acquiring actual numbers corresponding to the actual routing inspection nodes, numbering virtual routing inspection nodes corresponding to the actual routing inspection nodes according to the actual numbers, and acquiring virtual numbers corresponding to the virtual routing inspection nodes;
and updating the initial twin space according to the virtual tour-inspection track and the virtual tour-inspection node to obtain a tour-inspection twin space.
3. The method of claim 2, wherein the step of determining the position of the substrate comprises,
Receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node, wherein the joint control equipment comprises:
Receiving track trigger information of the patrol equipment on the corresponding actual patrol nodes on the actual patrol track;
Obtaining a virtual number corresponding to the actual number of the actual routing inspection node in the routing inspection twin space as a target number;
And determining the virtual inspection node corresponding to the target number as a trigger inspection node, and acquiring the joint control equipment corresponding to the trigger inspection node.
4. The method of claim 1, wherein the step of determining the position of the substrate comprises,
Acquiring a summary template corresponding to the trigger inspection node to summarize the first image and/or the second image to obtain summary data corresponding to the trigger inspection node, including:
a summary template corresponding to the trigger inspection node is called, wherein the summary template comprises a plurality of filling areas, and the filling areas are in one-to-one correspondence with the preset gestures;
and acquiring a first image or a second image corresponding to each preset gesture, and filling the first image or the second image into the corresponding filling area to obtain summarized data corresponding to the trigger inspection node.
5. The method of claim 1, wherein the step of determining the position of the substrate comprises,
Performing abnormal object feedback processing on the summarized data to obtain feedback data, and obtaining corresponding inspection data corresponding to the trigger inspection node according to the summarized data and the feedback data, wherein the method comprises the following steps:
A preset abnormal object is called to carry out feedback analysis on the first image and/or the second image corresponding to the summarized data, and the first image or the second image with the preset abnormal object is obtained to be used as a feedback image;
Determining a preset gesture corresponding to the feedback image as a feedback gesture, and controlling the inspection equipment to acquire data based on a preset duration and the feedback gesture to obtain feedback data corresponding to the corresponding trigger inspection node;
And obtaining inspection data according to the summarized data and the feedback data, and binding the inspection data with the corresponding trigger inspection node.
6. The method of claim 5, wherein the step of determining the position of the probe is performed,
The initial display shaft is called, and updated according to the inspection indication graph, the node indication graph and the inspection data to obtain carding data, and the carding data are sent to the management end, and the method comprises the following steps:
Inserting each node indication graph into the forefront of the inspection data corresponding to the corresponding virtual inspection node to obtain filling data corresponding to each virtual inspection node;
Constructing node filling slots corresponding to the virtual inspection nodes and space filling slots corresponding to the initial twin space on the initial display shaft;
filling each filling data into a node filling slot corresponding to the corresponding virtual inspection node, filling the inspection indication map into the space filling slot, and obtaining carding data to the management end.
7. A joint control analysis system based on AI intelligent auxiliary control system equipment is characterized by comprising:
The configuration module is used for acquiring an initial twin space corresponding to the patrol target, updating the initial twin space based on patrol configuration information of a management end to obtain a patrol twin space, wherein the patrol configuration information comprises a virtual patrol track and a virtual patrol node positioned on the virtual patrol track;
The trigger module is used for receiving track trigger information of the inspection equipment, taking a corresponding virtual inspection node as a trigger inspection node according to the track trigger information, and acquiring the joint control equipment corresponding to the trigger inspection node;
The acquisition module is used for calling a joint control analysis strategy to control the joint control equipment, and acquiring data based on an acquisition gesture group corresponding to the trigger inspection node to obtain inspection data corresponding to the trigger inspection node;
The carding module is used for receiving a triggering carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to the carding strategy to obtain carding data which are generated to the management end;
The combined control analysis strategy is called to control the combined control equipment, and data acquisition is carried out based on the acquisition gesture group corresponding to the trigger inspection node to obtain inspection data corresponding to the trigger inspection node, and the method comprises the following steps:
Controlling the inspection equipment to acquire images for one time according to the acquisition gesture group corresponding to the triggering inspection node to obtain a first image;
The joint control analysis strategy is called to perform joint control analysis on the first image to obtain joint control analysis data, the joint control equipment is controlled according to the joint control analysis data, and secondary image acquisition is performed based on the acquisition gesture group to obtain a second image;
acquiring a summarizing template corresponding to the trigger inspection node to summarize the first image and/or the second image, so as to obtain summarizing data corresponding to the trigger inspection node;
Performing abnormal object feedback processing on the summarized data to obtain feedback data, and obtaining corresponding inspection data of the trigger inspection node according to the summarized data and the feedback data;
The method for acquiring the combined control analysis strategy to perform combined control analysis on the first image to obtain combined control analysis data, controlling the combined control equipment according to the combined control analysis data, and performing secondary image acquisition based on the acquisition gesture group to obtain a second image, comprises the following steps:
Acquiring an image brightness value of the first image, and acquiring joint control analysis data according to a comparison result of the image brightness value and a preset image brightness value;
Determining a first image with the image brightness value smaller than the preset image brightness value as a deleted image according to the joint control analysis data;
Starting the combined control equipment, acquiring a preset gesture corresponding to the deleted image, controlling the inspection equipment to acquire a secondary image based on the preset gesture, acquiring a second image corresponding to the corresponding preset gesture, deleting the deleted image, and acquiring a gesture group comprising a plurality of preset gestures;
Receiving a triggering and carding request of the management end to the virtual inspection track, and carding the inspection data of the virtual inspection track according to a carding strategy to obtain carding data to be generated to the management end, wherein the method comprises the following steps:
Responding to the triggering carding request, and calling a preset patrol diagram, wherein the preset patrol diagram comprises a plurality of initial twin spaces corresponding to preset patrol targets;
calling a first preset pixel value to highlight an initial twin space corresponding to the patrol target in the preset patrol diagram, so as to obtain a patrol indication diagram;
acquiring a preset track map corresponding to the virtual inspection track, wherein the preset track map comprises display tracks corresponding to the virtual inspection track, and the display tracks comprise display nodes corresponding to the virtual inspection nodes;
Sequentially acquiring display nodes corresponding to the virtual inspection nodes in the preset track map as check nodes, and calling a second preset pixel value to perform protruding display on the check nodes to obtain node indication maps corresponding to the virtual inspection nodes;
And calling an initial display shaft, and updating the initial display shaft according to the inspection indication diagram, the node indication diagram and the inspection data to obtain carding data to the management end.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109298785A (en) * | 2018-09-06 | 2019-02-01 | 天津联图科技有限公司 | A kind of man-machine joint control system and method for monitoring device |
| CN112381963A (en) * | 2020-11-12 | 2021-02-19 | 广东电网有限责任公司 | Intelligent power Internet of things inspection method and system based on digital twin technology |
| CN114022798A (en) * | 2021-10-29 | 2022-02-08 | 国网河南省电力公司洛阳供电公司 | Transformer substation inspection robot obstacle avoidance method based on digital twinning technology |
| CN114268167A (en) * | 2021-11-18 | 2022-04-01 | 国网新疆电力有限公司信息通信公司 | Transformer substation system based on digital twinning technology |
| WO2022133330A1 (en) * | 2020-12-18 | 2022-06-23 | Strong Force Vcn Portfolio 2019, Llc | Robot fleet management and additive manufacturing for value chain networks |
| CN115209379A (en) * | 2022-08-15 | 2022-10-18 | 江苏方天电力技术有限公司 | Power grid cloud edge cooperative inspection system and method based on 5G intelligent networked unmanned aerial vehicle |
| CN115374508A (en) * | 2022-08-09 | 2022-11-22 | 福建中锐网络股份有限公司 | Large and medium-sized reservoir safety inspection system based on virtual reality technology |
| CN115496398A (en) * | 2022-10-12 | 2022-12-20 | 国网四川省电力公司电力科学研究院 | Electric power operation safety control method and system |
| CN116191662A (en) * | 2022-12-14 | 2023-05-30 | 国网江苏省电力有限公司电力科学研究院 | Substation operation and maintenance method based on digital twinning |
| CN116667531A (en) * | 2023-05-19 | 2023-08-29 | 国网江苏省电力有限公司泰州供电分公司 | Acousto-optic-electric collaborative inspection method and device based on digital twin transformer substation |
| WO2023160012A1 (en) * | 2022-02-25 | 2023-08-31 | 南京信息工程大学 | Unmanned aerial vehicle assisted edge computing method for random inspection of power grid line |
| CN117172749A (en) * | 2023-09-06 | 2023-12-05 | 佳都科技集团股份有限公司 | Rail transit inspection maintenance worker management method, device, equipment and storage medium |
| CN117291583A (en) * | 2023-11-27 | 2023-12-26 | 贵州联广科技股份有限公司 | Internet of things data management method and system |
| CN117314956A (en) * | 2023-10-10 | 2023-12-29 | 江苏征途技术股份有限公司 | Interactive pedestrian track prediction method based on graphic neural network |
| CN117424886A (en) * | 2023-09-22 | 2024-01-19 | 青岛巨川水处理有限公司 | Intelligent water service management and control platform and management and control method |
| CN117455231A (en) * | 2023-10-24 | 2024-01-26 | 四川中烟工业有限责任公司 | Monitoring and early warning method and system based on risk assessment model |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220274703A1 (en) * | 2021-02-28 | 2022-09-01 | Michele Di Cosola | Autonomous Inspection System within a Smart Self-Healing Node Centric Blockchain Network for Safety and Quality Management |
-
2024
- 2024-02-22 CN CN202410196465.2A patent/CN117765451B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109298785A (en) * | 2018-09-06 | 2019-02-01 | 天津联图科技有限公司 | A kind of man-machine joint control system and method for monitoring device |
| CN112381963A (en) * | 2020-11-12 | 2021-02-19 | 广东电网有限责任公司 | Intelligent power Internet of things inspection method and system based on digital twin technology |
| WO2022133330A1 (en) * | 2020-12-18 | 2022-06-23 | Strong Force Vcn Portfolio 2019, Llc | Robot fleet management and additive manufacturing for value chain networks |
| CN114022798A (en) * | 2021-10-29 | 2022-02-08 | 国网河南省电力公司洛阳供电公司 | Transformer substation inspection robot obstacle avoidance method based on digital twinning technology |
| CN114268167A (en) * | 2021-11-18 | 2022-04-01 | 国网新疆电力有限公司信息通信公司 | Transformer substation system based on digital twinning technology |
| WO2023160012A1 (en) * | 2022-02-25 | 2023-08-31 | 南京信息工程大学 | Unmanned aerial vehicle assisted edge computing method for random inspection of power grid line |
| CN115374508A (en) * | 2022-08-09 | 2022-11-22 | 福建中锐网络股份有限公司 | Large and medium-sized reservoir safety inspection system based on virtual reality technology |
| CN115209379A (en) * | 2022-08-15 | 2022-10-18 | 江苏方天电力技术有限公司 | Power grid cloud edge cooperative inspection system and method based on 5G intelligent networked unmanned aerial vehicle |
| CN115496398A (en) * | 2022-10-12 | 2022-12-20 | 国网四川省电力公司电力科学研究院 | Electric power operation safety control method and system |
| CN116191662A (en) * | 2022-12-14 | 2023-05-30 | 国网江苏省电力有限公司电力科学研究院 | Substation operation and maintenance method based on digital twinning |
| CN116667531A (en) * | 2023-05-19 | 2023-08-29 | 国网江苏省电力有限公司泰州供电分公司 | Acousto-optic-electric collaborative inspection method and device based on digital twin transformer substation |
| CN117172749A (en) * | 2023-09-06 | 2023-12-05 | 佳都科技集团股份有限公司 | Rail transit inspection maintenance worker management method, device, equipment and storage medium |
| CN117424886A (en) * | 2023-09-22 | 2024-01-19 | 青岛巨川水处理有限公司 | Intelligent water service management and control platform and management and control method |
| CN117314956A (en) * | 2023-10-10 | 2023-12-29 | 江苏征途技术股份有限公司 | Interactive pedestrian track prediction method based on graphic neural network |
| CN117455231A (en) * | 2023-10-24 | 2024-01-26 | 四川中烟工业有限责任公司 | Monitoring and early warning method and system based on risk assessment model |
| CN117291583A (en) * | 2023-11-27 | 2023-12-26 | 贵州联广科技股份有限公司 | Internet of things data management method and system |
Non-Patent Citations (3)
| Title |
|---|
| Design and research of substation inspection mode based on digital twins;Zipeng Zhang等;《2023 2nd International Conference on Big Data, Information and Computer Network (BDICN)》;20230428;53-57 * |
| 基于物联网技术的配电站房智慧监控系统的设计与实现;谢李丹等;《内江科技》;20230331;第44卷(第03期);13-14+58 * |
| 数字孪生变电站框架设计与关键技术研究;张冀等;《万方数据》;20231228;15-30 * |
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