CN115512289A - AR (augmented reality) -glasses-based power operation safety monitoring method and system - Google Patents
AR (augmented reality) -glasses-based power operation safety monitoring method and system Download PDFInfo
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Abstract
The invention discloses an AR (augmented reality) glasses-based power operation safety monitoring method and system, and belongs to the technical field of power safety. The invention relates to an AR (augmented reality) glasses-based electric power operation safety monitoring method, which comprises the steps of coding and decoding video information of an electric power operation field acquired by AR glasses by constructing a video preprocessing model, an edge calculation model and an early warning model, and slicing the coded and decoded video information into monitoring pictures; then, carrying out picture preprocessing on the monitoring picture to generate a target picture; then, carrying out comparison analysis on the target picture to obtain a comparison result; and generating alarm information according to the comparison result, and realizing the safety monitoring of the power operation. The invention takes the data collected by the AR glasses as links, embodies the reasonable structure of the light site collecting end and the heavy edge computing server, and can effectively promote the safety management and maintenance of the operation construction site, so that the safety of the construction site is changed from post-processing to pre-management and control.
Description
Technical Field
The invention relates to an AR glasses-based power operation safety monitoring method and system, and belongs to the technical field of power safety.
Background
Chinese patent (CN 112396718A) discloses an on-site construction safety and quality supervision research system based on AR technology. The inspection personnel set inspection tasks at the background management end and then wear the glasses acquisition terminal to inspect on site, the glasses acquisition terminal automatically identifies the equipment state, and the identification result is displayed in the field of view of the display module through the projection module; and comparing the recognition state with the prefabricated data of the background management end, automatically judging whether the inspection result is normal or not, and displaying the result on the display module through the projection module. Therefore, for traditional multi-person inspection, inspection of a plurality of devices can be achieved only by one person. If the inspection personnel encounters the problem or question which can not be solved independently, the inspection personnel can remotely guide the experts remotely connected with the service end to help solve the difficult problem in the inspection so as to smoothly complete the inspection work; the inspection efficiency can be greatly improved without carrying various operation instruction books and operation manuals.
However, the scheme does not disclose how to process the acquired data and how to judge the abnormal conditions, so that the electric power operation safety monitoring scheme based on the AR technology cannot be realized, and the popularization and the use are not facilitated.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a method for encoding and decoding the video information of the electric power operation field collected by AR glasses by constructing a video preprocessing model, an edge calculation model and an early warning model, and slicing the encoded and decoded video information into monitoring pictures; then, carrying out picture pretreatment on the monitoring picture to generate a target picture; then, carrying out comparison analysis on the target picture to obtain a comparison result; according to the comparison result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific, reasonable and feasible, and the AR glasses-based electric power operation safety monitoring method is convenient to popularize and use.
The invention aims to provide a method for analyzing and processing monitoring images of a power operation site collected by AR glasses by constructing an edge calculation model and an early warning model to obtain an analysis result; according to the analysis result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific, reasonable, feasible and convenient to popularize and use.
The invention aims to provide a method for comparing and analyzing the video information of the electric power operation field collected by the AR glasses by arranging the AR glasses, the network communication module and the AI edge calculation box to obtain a comparison result; according to the comparison result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific and reasonable, and the AR glasses-based electric power operation safety monitoring system is practical and feasible and convenient to popularize and use.
The invention aims at providing the AR glasses-based electric power operation safety monitoring method and the AR glasses-based electric power operation safety monitoring system which take the data acquired by the AR glasses as links, can embody the reasonable structures of a light site acquisition end and a heavy edge calculation server end, and can effectively promote the safety management and maintenance of an operation construction site, so that the safety of the construction site is changed from post-treatment to pre-management and control, and the regular maintenance of equipment is changed to the state maintenance of the equipment.
In order to achieve one of the above objects, a first technical solution of the present invention is:
an AR glasses-based power operation safety monitoring method,
the method comprises the following steps:
the method comprises the steps of firstly, acquiring video information of an electric power operation site acquired through AR glasses;
secondly, coding and decoding the video information in the first step through a pre-constructed video preprocessing model, and slicing the coded and decoded video information into monitoring pictures;
thirdly, carrying out picture preprocessing on the monitoring picture in the second step to generate a target picture;
fourthly, carrying out comparison analysis on the target picture in the third step by utilizing a pre-constructed edge calculation model to obtain a comparison result;
fifthly, generating alarm information according to the comparison result in the fourth step by using a pre-constructed early warning model;
and sixthly, sending the alarm information in the fifth step to the AR glasses to realize the safety monitoring of the power operation.
Through continuous exploration and test, encoding and decoding video information of an electric power operation field collected by AR glasses by constructing a video preprocessing model, an edge calculation model and an early warning model, and slicing the encoded and decoded video information into monitoring pictures; then, carrying out picture preprocessing on the monitoring picture to generate a target picture; then, carrying out comparison analysis on the target picture to obtain a comparison result; according to the comparison result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific and reasonable, and the method is practical and feasible and convenient to popularize and use.
Furthermore, the method takes the data acquired by the AR glasses as links, embodies the reasonable structures of the light site acquisition end and the heavy edge calculation server end, and can effectively promote the safety management and maintenance of the operation construction site, so that the safety of the construction site is changed from post-processing to pre-management and control, and the regular maintenance of the equipment is changed to the state maintenance of the equipment.
As a preferable technical measure:
in the first step, the video information comprises a wearing image or/and a head image or/and a face image.
As a preferable technical measure:
in the second step, the picture preprocessing comprises image enhancement, image sharpening and image edge extraction.
As a preferable technical measure:
and in the third step, the edge calculation model is constructed by using a gray correlation analysis unit, and the monitoring image is compared with the field violation mathematical model to realize monitoring and analysis of the video information uploaded by the AR glasses.
As a preferable technical measure:
the grey correlation analysis unit comprises the following contents:
step 1: quantizing the monitoring image into a plurality of two-dimensional data, and drawing a plurality of curves according to the two-dimensional data;
and 2, step: comparing the curves in the step 1 with sequence curves in the electric power operation violation information to obtain the similarity of the geometric shapes of the curves and the sequence curves, and drawing the sequence curves;
and 3, step 3: converting the curves and the sequence curves in the step 2 into a parent sequence and a plurality of sub-sequences;
and 4, step 4: preprocessing the mother sequence and the plurality of sub sequences in the step 3 to obtain a standardized mother sequence and a plurality of sub sequences;
and 5: calculating the association degree of each element in the normalized subsequence with the corresponding element in the parent sequence in the step 4;
step 6: and calculating the association degree of the subsequence with the parent sequence according to the association degree of the elements in the step 5.
As a preferable technical measure:
the mother sequence is a data sequence reflecting electric power operation violation information;
the subsequences are data sequences of the monitoring image and comprise two-dimensional data I, two-dimensional data II and two-dimensional data III.
As a preferable technical measure:
the preprocessing method is to divide each element by the mean value of the corresponding sequence, and the calculation formula is as follows:
wherein x is ij Are elements in a parent sequence or a subsequence.
As a preferable technical measure:
the expression for the subsequence is:
x 1 ＝{x 1 (1),x 1 (2),...,x 1 (n)}；
x 2 ＝{x 2 (1),x 2 (2),...,x 2 (n)}；
x 3 ＝{x 3 (1),x 3 (2),...,x 3 (n)}；
the expression of the parent sequence is:
x 0 ＝{x 0 (1),x 0 (2),...,x 0 (n)}；
the calculation formula of the association degree of each element in the subsequence with the corresponding element in the parent sequence is as follows:
wherein a is the minimum difference between the parent sequence and the subsequence;
b is the maximum difference between the parent sequence and the subsequence;
the calculation formula of the minimum difference between the parent sequence and the subsequence is as follows:
the calculation formula of the maximum difference between the parent sequence and the subsequence is as follows:
the calculation formula of the correlation degree of the subsequence and the parent sequence is as follows:
in order to achieve one of the above objects, a second technical solution of the present invention is:
an AR glasses-based power operation safety monitoring method,
the method comprises the following steps:
acquiring a monitoring image of the power operation site acquired through AR glasses;
analyzing and processing the monitoring image through a pre-constructed edge calculation model to obtain an analysis result;
processing the analysis result by utilizing a pre-constructed early warning model to obtain corresponding warning information;
and sending the alarm information to the AR glasses so that the AR glasses can make corresponding logic actions according to the alarm information to realize safety monitoring of the power operation.
According to the method, through continuous exploration and test, monitoring images of a power operation field collected by AR glasses are analyzed and processed by constructing an edge calculation model and an early warning model, so that an analysis result is obtained; and according to the analysis result, alarm information is generated, the safety monitoring of the power operation is realized, and the scheme is scientific, reasonable, feasible and convenient to popularize and use.
Furthermore, the method takes the data acquired by the AR glasses as links, embodies the reasonable structures of the light site acquisition end and the heavy edge calculation server end, and can effectively promote the safety management and maintenance of the operation construction site, so that the safety of the construction site is changed from post-processing to pre-management and control, and the regular maintenance of the equipment is changed to the state maintenance of the equipment.
In order to achieve one of the above objects, a third technical solution of the present invention is:
an AR glasses-based electric power operation safety monitoring system,
the AR glasses-based electric power operation safety monitoring method is adopted;
the system comprises AR glasses, a network communication module and an AI edge calculation box;
the AR glasses send the related monitoring data to the AI edge computing box through the network communication module;
the AI edge calculation box comprises a video preprocessing module, a picture preprocessing module, an edge calculation module, a field violation math module and an early warning module;
the AI edge calculation box transmits the alarm information to the AR glasses through the network communication module;
and displaying alarm information on the AR glasses.
According to the invention, through continuous exploration and test, the AR glasses, the network communication module and the AI edge calculation box are arranged, and the video information of the power operation field collected by the AR glasses is compared and analyzed to obtain a comparison result; according to the comparison result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific and reasonable, and the method is feasible and convenient to popularize and use.
Furthermore, the data acquired by the AR glasses are taken as links, the reasonable structures of the light site acquisition end and the heavy edge calculation server end are embodied, the safety management and maintenance of the operation construction site can be effectively promoted, the post-processing of the construction site safety is changed into the pre-management and control, and the regular maintenance of the equipment is changed to the state maintenance of the equipment.
Compared with the prior art, the invention has the following beneficial effects:
through continuous exploration and test, encoding and decoding video information of an electric power operation field collected by AR glasses by constructing a video preprocessing model, an edge calculation model and an early warning model, and slicing the encoded and decoded video information into monitoring pictures; then, carrying out picture pretreatment on the monitoring picture to generate a target picture; then, carrying out comparison analysis on the target picture to obtain a comparison result; according to the comparison result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific and reasonable, and the method is practical and feasible and convenient to popularize and use.
Further, the monitoring image of the power operation site collected by the AR glasses is analyzed and processed by constructing an edge calculation model and an early warning model, so that an analysis result is obtained; according to the analysis result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific and reasonable, and the method is feasible and convenient to popularize and use.
Furthermore, the AR glasses, the network communication module and the AI edge calculation box are arranged, and the video information of the power operation site collected by the AR glasses is compared and analyzed to obtain a comparison result; according to the comparison result, alarm information is generated, safety monitoring of electric power operation is achieved, the scheme is scientific and reasonable, and the method is feasible and convenient to popularize and use.
Furthermore, the data acquired by the AR glasses are taken as links, the reasonable structures of the light site acquisition end and the heavy edge calculation server end are embodied, the safety management and maintenance of the operation construction site can be effectively promoted, the post-processing of the construction site safety is changed into the pre-management and control, and the regular maintenance of the equipment is changed to the state maintenance of the equipment.
Drawings
FIG. 1 is a schematic diagram of an AR glasses-based power operation safety monitoring system according to the present invention;
FIG. 2 is a flowchart of a method for monitoring safety of power operation based on AR glasses according to the present invention;
fig. 3 is a flowchart of an AR glasses-based power operation safety monitoring method according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
On the contrary, the invention is intended to cover alternatives, modifications, equivalents and alternatives which may be included within the spirit and scope of the invention as defined by the appended claims. Furthermore, in the following detailed description of the present invention, certain specific details are set forth in order to provide a better understanding of the present invention. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "or/and" includes any and all combinations of one or more of the associated listed items.
The invention relates to a power operation safety monitoring method based on AR glasses, which comprises the following specific embodiments:
an AR glasses-based power operation safety monitoring method,
the method comprises the following steps:
the method comprises the steps of firstly, acquiring video information of an electric power operation site acquired through AR glasses;
secondly, coding and decoding the video information in the first step through a pre-constructed video preprocessing model, and slicing the coded and decoded video information into monitoring pictures;
thirdly, carrying out picture preprocessing on the monitoring picture in the second step to generate a target picture;
fourthly, performing contrast analysis on the target picture in the third step by using a pre-constructed edge calculation model to obtain a contrast result;
fifthly, generating alarm information according to the comparison result in the fourth step by using a pre-constructed early warning model;
and sixthly, sending the alarm information in the fifth step to the AR glasses to realize the safety monitoring of the power operation.
The invention relates to a power operation safety monitoring method based on AR glasses, which comprises the following specific embodiments:
an AR glasses-based power operation safety monitoring method,
the method comprises the following steps:
the method comprises the steps of firstly, collecting monitoring images of a power operation site through AR glasses;
secondly, analyzing and processing the monitoring image in the first step through a pre-constructed edge calculation model to obtain an analysis result;
thirdly, processing the analysis result in the second step by using a pre-constructed early warning model to obtain corresponding warning information;
fourthly, sending the alarm information in the third step to AR glasses;
and fifthly, the AR glasses make corresponding logic actions according to the alarm information in the fourth step, and safety monitoring of the power operation is achieved.
The invention relates to a first specific embodiment of an AR glasses-based power operation safety monitoring system, which comprises the following steps:
an AR glasses-based electric power operation safety monitoring system,
the AR glasses-based electric power operation safety monitoring method is adopted;
the system comprises AR glasses, a network communication module and an AI edge calculation box;
the AR glasses send the related monitoring data to the AI edge calculation box through the network communication module;
the AI edge calculation box comprises a video preprocessing module, a picture preprocessing module, an edge calculation module, a field violation math module and an early warning module;
the AI edge calculation box transmits the alarm information to the AR glasses through the network communication module;
and displaying alarm information on the AR glasses.
The invention relates to a second specific embodiment of an AR glasses-based electric power operation safety monitoring system, which comprises the following steps:
a safety monitoring system for electric power operation based on AR glasses comprises the AR glasses, a network communication module and an AI edge calculation box.
In this example, the AR glasses data send the relevant monitoring data to the AI edge computing box through the network communication module formed by the transmission medium. The AI edge calculation box consists of an AR monitoring terminal AI processing system and an early warning module, the edge calculation result is pushed by the alarm information processing module, the site early warning is displayed and processed, and the monitoring result or the acousto-optic early warning signal is transmitted by the communication layer. The system architecture is shown in fig. 1.
In this example, the AR glasses: a monitor, an earphone, a microphone, and a camera are provided. The camera realizes on-site video information acquisition, the monitor realizes display of alarm information and related video information, the earphone realizes alarm and voice information broadcast, and the microphone and the earphone cooperate to realize a talkback function.
In the embodiment, the AR glasses report information and the electric power engineering safety standard are combined in the AI edge computing box, a field violation mathematical model is established through algorithm learning and the existing AI model by video information collected by the AR glasses camera, and violation or early warning information can be pushed to the AR glasses monitor and the voice talkback monitoring function module earphone.
In this example, the AI edge calculation box: the system is provided with a video preprocessing module, a picture preprocessing module, an edge calculating module, a field violation math module and an early warning module.
The video preprocessing module encodes and decodes video information acquired by the camera of the AR glasses, slices the encoded and decoded video information into pictures and sends the pictures to the picture preprocessing module and the AI computing unit, the picture preprocessing module and the AI computing unit perform image enhancement, sharpening and edge extraction on the sliced pictures to generate target pictures and send the target pictures to the edge computing module, the edge computing module compares the target pictures with a field violation mathematical model by using an artificial intelligent neural network to realize AI analysis on the video information uploaded by the AR glasses, and AI analysis results are pushed to the AR glasses through the early warning module. And after receiving the abnormal information, the control unit of the AR glasses analyzes the abnormal information, and displays an analysis result on a glasses screen to prompt that abnormal conditions exist.
The image acquisition, image processing, AI analysis, process can be seen in fig. 2.
One embodiment of the edge calculation module of the present invention:
aiming at the characteristics of multiple operation scenes, multiple operation unit control key points, multiple control key point classifications and the like of an electric power operation field, the edge calculation module compares a target picture with a field violation mathematical model by using a grey correlation analysis method of an evaluation model, and AI analysis of video information uploaded by AR glasses is realized.
The specific analysis process of the grey correlation analysis method of the evaluation class model is as follows:
the first step is as follows: quantizing the target picture data into two-dimensional data, and drawing a curve;
the second step: comparing the similarity of the geometric shapes of the curve drawn in the first step and the sequence curve of the field violation mathematical model to draw a sequence curve;
the third step: determining the sequence of analysis.
The sequences are divided into two categories: one category is called a parent sequence, namely a data sequence reflecting the overall behavior characteristics or development of the system, and can be understood as a dependent variable in regression analysis, wherein the dependent variable is a list of field violation mathematical model sequence curves. The other kind of data sequence, called sub-sequence, that is, the data sequence composed of factors affecting the system development, can be understood as the independent variable in the regression analysis, and here, the target picture data is quantized into two-dimensional data 1, 2, 3, etc. respectively.
The fourth step: the data is preprocessed.
The purpose of preprocessing is to remove dimension influence, narrow the data range and facilitate calculation. There are various methods for data normalization, and the normalization method used here is the average value of each element divided by the corresponding index, that is:
the fifth step: and calculating the association degree of each element in the processed subsequence and the corresponding element in the parent sequence.
The parent sequence is:
x 0 ＝{x 0 (1),x 0 (2),...,x 0 (n)}
the subsequence is:
x 1 ＝{x 1 (1),x 1 (2),...,x 1 (n)}
x 2 ＝{x 2 (1),x 2 (2),...,x 2 (n)}
x 3 ＝{x 3 (1),x 3 (2),...,x 3 (n)}
calculating the minimum difference of the parent-child sequences:
calculating the maximum difference of the parent-child sequences:
the degree of association of each element in the subsequence with a corresponding element in the parent sequence can be calculated.
In grey correlation analysis, define:
where is the resolution factor, which is generally between 0,1, often 0.5.
And a sixth step: the respective sequences, i.e. the degree of association of the index with the system as a whole, are calculated.
Defining:
it is used to express the relevance of some index and the overall development of the system. The relevance between each element in the index and the element corresponding to the parent sequence is obtained, and the relevance between the index and the system as a whole can be regarded by averaging the relevance.
The grey correlation analysis method of the evaluation model mainly has two functions, namely system analysis and judgment of importance of factors influencing system development. And the second is used for comprehensively evaluating the problem and giving the rank of the research object or the scheme. In the system development process, if the two factor variation trends have consistency, namely the synchronous variation degree is higher, the correlation degree of the two factors is higher; otherwise, it is lower.
Regression analysis, variance analysis, principal component analysis and the like are often used in mathematical statistics to probe the problem, but the methods have the common defects that a large amount of data is required, and the result is not significant if the data amount is small; sometimes it is also required that the sample be subjected to a particular distribution or that the quantitative results be inconsistent with the qualitative analysis.
Grey correlation analysis can then better cope with these problems. The gray correlation analysis has no requirement on the sample size and the irregularity of the samples (the sample size cannot be too small), and the quantitative result basically conforms to the qualitative analysis. The basic idea of grey correlation analysis is to determine whether the sequence curves are closely related according to their geometric similarity. The closer the curve is, the greater the degree of correlation between the corresponding sequences, and vice versa. The more similar the geometrical similarity of the curves formed by two or more sequences, the more closely related the changes, i.e. the high degree of correlation. The method is used for researching the relevance from the angle of pure data, and if the two indexes are extremely similar in curve shape, the grey relevance analysis can consider that the relevance degree of the two indexes is high. Grey correlation analysis gives a ranking of the degree of correlation of the various factors with the system population. The higher the degree of association, the greater the influence of the corresponding factors on the system development.
One specific embodiment of the application of the invention:
the AR glasses are worn by safety supervision personnel on an electric power operation construction site, real-time video monitoring data of the environment are sent to the AI edge calculation box through the data transmission module, the AI edge calculation box is used for AI analysis, and AI analysis results are pushed to the AR glasses through the early warning module to form closed-loop monitoring.
After the AR glasses device in this embodiment is turned on, the AR glasses actively report heartbeat information to the AI edge computing box, after the AI edge computing box acquires the heartbeat information of the AR glasses, the state of the AR glasses device sending the heartbeat information is set to the on-line state of the device, the AI edge computing box then sends a query monitoring data information command to the AR glasses sending the heartbeat information at regular time, the AR glasses then collect video data and report the collected video data information to the AI edge computing box in real time, after the AI edge computing box performs AI data analysis and comparison through the reported video data, the corresponding logic result is sent to the AR glasses, the AR glasses perform corresponding logic actions according to the corresponding logic results, and the AR glasses monitoring flow based on edge computing is shown in fig. 3.
In this example, the contents of the field violation mathematical model can be added by opening the learning mode of the AR glasses through the AI edge computing box.
The invention realizes the data transmission module as a transmission link, and embodies the reasonable structure of a light field acquisition end and a heavy edge calculation server. The safety management and maintenance of the operation construction site are promoted from the aspects of personnel, property, machines and tools, laws, technologies, environment and the like, the safety of the construction site is changed from post treatment to pre-management and control, and the regular maintenance of the equipment is changed to the state maintenance of the equipment.
An embodiment of an apparatus to which the method of the invention is applied:
a computer apparatus, comprising:
one or more processors;
storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement a method of AR glasses-based power operation safety monitoring described above.
An embodiment of a computer medium to which the method of the invention is applied is:
a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements an AR glasses-based power operation safety monitoring method as described above.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as methods, systems, computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A power operation safety monitoring method based on AR glasses is characterized in that,
the method comprises the following steps:
the method comprises the steps of firstly, acquiring video information of an electric power operation site acquired through AR glasses;
secondly, coding and decoding the video information in the first step through a pre-constructed video preprocessing model, and slicing the coded and decoded video information into monitoring pictures;
thirdly, carrying out picture preprocessing on the monitoring picture in the second step to generate a target picture;
fourthly, performing contrast analysis on the target picture in the third step by using a pre-constructed edge calculation model to obtain a contrast result;
fifthly, generating alarm information according to the comparison result in the fourth step by using a pre-constructed early warning model;
and sixthly, sending the alarm information in the fifth step to the AR glasses to realize the safety monitoring of the electric power operation.
2. The AR glasses-based power operation safety monitoring method according to claim 1,
in the first step, the video information comprises a wearing image or/and a head image or/and a face image.
3. The AR glasses-based power operation safety monitoring method according to claim 1,
in the second step, the picture preprocessing comprises image enhancement, image sharpening and image edge extraction.
4. The AR glasses-based power operation safety monitoring method according to claim 1,
in the third step, the edge calculation model is constructed by using a gray correlation analysis unit, and monitoring and analysis of the video information uploaded by the AR glasses are realized by comparing the monitored image with a field violation mathematical model.
5. The AR glasses-based power operation safety monitoring method according to claim 4,
grey correlation analysis unit, including the following:
step 1: quantizing the monitoring image into a plurality of two-dimensional data, and drawing a plurality of curves according to the two-dimensional data;
and 2, step: comparing the curves in the step 1 with sequence curves in the electric power operation violation information to obtain the similarity of the geometric shapes of the curves and the sequence curves, and drawing the sequence curves;
and step 3: converting the curves and the sequence curves in the step 2 into a parent sequence and a plurality of sub-sequences;
and 4, step 4: preprocessing the mother sequence and the plurality of sub sequences in the step 3 to obtain a standardized mother sequence and a plurality of sub sequences;
and 5: calculating the association degree of each element in the normalized subsequence and the corresponding element in the parent sequence in the step 4;
step 6: and calculating the association degree of the subsequence with the parent sequence according to the association degree of the elements in the step 5.
6. The AR glasses-based power operation safety monitoring method according to claim 5,
the mother sequence is a data sequence reflecting electric power operation violation information;
the subsequences are data sequences of the monitored images and comprise two-dimensional data I, two-dimensional data II and two-dimensional data III.
7. The AR glasses-based power operation safety monitoring method according to claim 5,
the preprocessing method is to divide each element by the mean value of the corresponding sequence, and the calculation formula is as follows:
wherein x is ij Are elements in a parent sequence or a subsequence.
8. The AR glasses-based power operation safety monitoring method according to claim 5,
the expression for the subsequence is:
x 1 ＝{x 1 (1),x 1 (2),...,x 1 (n)}；
x 2 ＝{x 2 (1),x 2 (2),...,x 2 (n)}；
x 3 ＝{x 3 (1),x 3 (2),...,x 3 (n)}；
the expression of the parent sequence is:
x 0 ＝{x 0 (1),x 0 (2),...,x 0 (n)}；
the calculation formula of the association degree of each element in the subsequence with the corresponding element in the parent sequence is as follows:
wherein a is the minimum difference between the parent sequence and the subsequence;
b is the maximum difference between the parent sequence and the subsequence;
the calculation formula of the minimum difference between the parent sequence and the subsequence is as follows:
the calculation formula of the maximum difference between the parent sequence and the subsequence is as follows:
the calculation formula of the association degree of the subsequence and the parent sequence is as follows:
9. a power operation safety monitoring method based on AR glasses is characterized in that,
the method comprises the following steps:
acquiring a monitoring image of the power operation site acquired through AR glasses;
analyzing and processing the monitoring image through a pre-constructed edge calculation model to obtain an analysis result;
processing the analysis result by utilizing a pre-constructed early warning model to obtain corresponding warning information;
and sending the alarm information to the AR glasses so that the AR glasses can make corresponding logic actions according to the alarm information to realize safety monitoring of the power operation.
10. An AR glasses-based electric power operation safety monitoring system is characterized in that,
adopting an AR glasses-based power operation safety monitoring method as claimed in any one of claims 1-9;
the system comprises AR glasses, a network communication module and an AI edge calculation box;
the AR glasses send the related monitoring data to the AI edge computing box through the network communication module;
the AI edge calculation box comprises a video preprocessing module, a picture preprocessing module, an edge calculation module, a field violation math module and an early warning module;
the AI edge calculation box transmits the alarm information to the AR glasses through the network communication module;
and displaying alarm information on the AR glasses.
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