CN117557951A - Power grid abnormal event monitoring method, device, computer equipment and storage medium - Google Patents
Power grid abnormal event monitoring method, device, computer equipment and storage medium Download PDFInfo
- Publication number
- CN117557951A CN117557951A CN202311363362.2A CN202311363362A CN117557951A CN 117557951 A CN117557951 A CN 117557951A CN 202311363362 A CN202311363362 A CN 202311363362A CN 117557951 A CN117557951 A CN 117557951A
- Authority
- CN
- China
- Prior art keywords
- recognition result
- matching value
- abnormal
- image recognition
- power grid
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 170
- 238000000034 method Methods 0.000 title claims abstract description 114
- 238000012544 monitoring process Methods 0.000 title claims abstract description 73
- 230000008569 process Effects 0.000 claims abstract description 68
- 238000012545 processing Methods 0.000 claims abstract description 36
- 238000004590 computer program Methods 0.000 claims description 43
- 238000012806 monitoring device Methods 0.000 claims description 9
- 238000004891 communication Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 8
- 238000012423 maintenance Methods 0.000 description 6
- 230000008859 change Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 229910021389 graphene Inorganic materials 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/44—Event detection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The application relates to a power grid abnormal event monitoring method, a device, computer equipment and a storage medium. The method comprises the following steps: receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request; recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data; and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process. By the method, the monitoring force of the abnormal event handling process can be increased, and the monitoring efficiency is greatly improved.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a method and apparatus for monitoring an abnormal event of a power grid, a computer device, and a storage medium.
Background
Along with the intelligent and digital transformation of the power grid regulation, the quantity of distribution feeder lines and equipment of the power grid is continuously increased, so that abnormal events of the power grid are also increased, and in order to ensure that the abnormal events of the power grid can be repaired sequentially, the processing process of the abnormal events of the power grid is often required to be monitored.
At present, the monitoring of the abnormal event of the power grid is usually performed manually through written records or sound recordings. However, with the increase of the traffic volume, and the coordination application of a plurality of service systems is involved in the monitoring process of the abnormal event of the power grid, the monitoring mode of the abnormal event of the power grid has the problems of small monitoring force and low efficiency.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a power grid abnormal event monitoring method, apparatus, computer device, and storage medium that can improve the abnormal event monitoring efficiency.
In a first aspect, the present application provides a method for monitoring an abnormal event of a power grid. The method comprises the following steps:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process.
In one embodiment, the method further comprises:
acquiring a target matching value between an image recognition result and an abnormal event handling standard;
and if the target matching value is smaller than the matching value threshold value, updating the abnormal event handling standard according to the image recognition result.
In one embodiment, the image recognition result includes a procedure recognition result, the abnormal event handling criteria includes a procedure handling criteria, and obtaining a target match value between the image recognition result and the abnormal event handling criteria includes:
consistency comparison is carried out on the operation step identification result and the operation step treatment standard to obtain a first matching value;
and obtaining a target matching value according to the first matching value.
In one embodiment, the image recognition result further includes an equipment wear recognition result, the abnormal event handling criteria further includes an equipment wear handling criteria, and the obtaining the target matching value according to the first matching value includes:
consistency comparison is carried out on the equipment wearing recognition result and the equipment wearing treatment standard to obtain a second matching value;
and carrying out statistical processing on the first matching value and the second matching value to obtain a target matching value.
In one embodiment, the method further comprises:
determining a first influence parameter of the operation step recognition result on the image recognition result according to the first matching value;
determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value;
and if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold value, outputting accident warning information.
In one embodiment, after collecting the abnormal data according to the grid data monitoring request, the method further includes:
searching a historical image identification result corresponding to a historical treatment process corresponding to the abnormal data according to the abnormal data;
and outputting a historical image recognition result.
In a second aspect, the application further provides a power grid abnormal event monitoring device. The device comprises:
the data acquisition module is used for receiving the power grid data monitoring request and acquiring abnormal data according to the power grid data monitoring request;
the video recording module is used for recording the event handling process of the abnormal event corresponding to the abnormal data to obtain recorded video data;
the video identification module is used for carrying out image identification processing on each frame of image in the recorded video data to obtain a target image identification result which is used for representing an event handling process.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process.
In a fourth aspect, the present application also provides a computer-readable storage medium. A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process.
In a fifth aspect, the present application also provides a computer program product. Computer program product comprising a computer program which, when executed by a processor, realizes the steps of:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process.
The power grid abnormal event monitoring method, the power grid abnormal event monitoring device, the computer equipment and the storage medium. Receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request; recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data; and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process. Therefore, the processing process of the abnormal event can be recorded, and the event handling process of the abnormal event is recorded through the target image recognition result of the recorded video data, so that the operation backtracking of the fault handling process can be realized more clearly and intuitively, the monitoring force of the processing process of the abnormal event is increased, and the monitoring efficiency is greatly increased because the recording is not needed.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.
FIG. 1 is an application environment diagram of a method for monitoring grid anomalies in one embodiment;
FIG. 2 is a flow chart of a method for monitoring an abnormal event of a power grid in one embodiment;
FIG. 3 is a flow diagram of updating exception handling criteria in one embodiment;
FIG. 4 is a flowchart of a method for monitoring an abnormal event of a power grid according to another embodiment;
FIG. 5 is a block diagram of a grid anomaly monitoring device in one embodiment;
FIG. 6 is a block diagram of a grid anomaly monitoring device in another embodiment;
FIG. 7 is a block diagram of a grid anomaly monitoring device in yet another embodiment;
FIG. 8 is a block diagram of a grid anomaly monitoring device in yet another embodiment;
fig. 9 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The power grid abnormal event monitoring method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in FIG. 1. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing data required for the relevant processing. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements the grid anomaly monitoring method according to any of the embodiments described below.
In one embodiment, as shown in fig. 2, a method for monitoring abnormal events of a power grid is provided, and the method is applied to the computer equipment in fig. 1 for illustration, and includes the following steps:
s201, receiving a power grid data monitoring request, and collecting abnormal data according to the power grid data monitoring request.
The abnormal data can comprise at least one of abnormal signal data of power grid equipment, abnormal signal data of a power grid line, emergency data related to the power grid and the like; the power grid data monitoring request is a request which is uploaded by a user and used for monitoring power grid data, and the power grid data monitoring request carries an abnormal data name.
Specifically, when a power grid data monitoring request uploaded by a user is received, an abnormal data name to be monitored is analyzed from the power grid data monitoring request, and abnormal data corresponding to the abnormal data name is searched and acquired according to the abnormal data name.
Optionally, after the abnormal data is collected, a historical image recognition result corresponding to a historical treatment process corresponding to the abnormal data can be searched according to the abnormal data; and outputting a historical image recognition result.
The historical image recognition result is a recognition result of recorded video data of an abnormal event corresponding to the same type of abnormal data in a historical period.
Specifically, a historical image recognition result related to the abnormal data name is searched in a storage system of the computer equipment according to the abnormal data name, and the historical image recognition result is output, so that when an operation and maintenance person handles an abnormal event corresponding to the abnormal data, the historical image recognition result is used as a reference, and the treatment efficiency is improved.
S202, recording event handling processes of abnormal events corresponding to the abnormal data to obtain recorded video data.
Specifically, recording the event handling process of the abnormal event corresponding to the abnormal data may include recording an omnibearing and full-flow process of the event handling process; for example, when the equipment fails, recording an operation process and a recording process for processing the equipment failure, wherein the operation process may include at least one of a failure checking process, a failure cause analysis process, a failure positioning process, a failure resolving process, and an equipment resetting process for the equipment, the recording process includes at least one of a maintenance record, a failure cause record, a step record for resolving the failure, and an information record for an operator for processing the failure for the equipment, and recording the whole processing process is completed, so as to obtain recorded video data.
S203, performing image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result.
Wherein the target image recognition result is used to characterize the event handling process.
Specifically, the recorded video data may be input into a video image recognition model, and the output result of the model is the target image recognition result.
Optionally, the recorded video data may be further divided into a plurality of video images according to a preset frame number requirement, the video images are input into a video image recognition model, and an output result of the model is a target image recognition result.
In the above embodiment, a power grid data monitoring request is received, and abnormal data is collected according to the power grid data monitoring request; recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data; and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process. Therefore, the processing process of the abnormal event can be recorded, and the event handling process of the abnormal event is recorded through the target image recognition result of the recorded video data, so that the operation backtracking of the fault handling process can be realized more clearly and intuitively, the monitoring force of the processing process of the abnormal event is increased, and the monitoring efficiency is greatly increased because the recording is not needed.
The above embodiment teaches how to enhance the monitoring of the time treatment process of the abnormal event, and in order to make the scheme more complete, as shown in fig. 3, how to update the abnormal event treatment criteria, the specific method includes:
s301, acquiring a target matching value between an image recognition result and an abnormal event handling standard.
The abnormal event handling standard is a standard when an operation and maintenance person handles the abnormal event; the image recognition result is the process of handling the abnormal event by the operation and maintenance personnel.
Specifically, according to the name of the abnormal event, searching and acquiring an abnormal event handling standard of the abnormal event from a storage system of the computer equipment, and comparing the consistency of the image recognition result and the abnormal event handling standard to obtain a target matching value between the image recognition result and the abnormal event handling standard.
Optionally, the image recognition result may include an operation step recognition result, and the abnormal event handling criterion may include an operation step handling criterion, so that the operation step recognition result and the operation step handling criterion may be compared first to obtain the target matching value according to the first matching value.
Specifically, the first matching value may be directly used as the target matching value, or may be used as the target matching value after the first matching value is statistically processed.
Optionally, the image recognition result may further include an equipment wearing recognition result, and the abnormal event handling criterion may further include an equipment wearing handling criterion, so that the method of obtaining the target matching value may further be that the equipment wearing recognition result is compared with the equipment wearing handling criterion to obtain a second matching value; and carrying out statistical processing on the first matching value and the second matching value to obtain a target matching value.
Specifically, according to weights preset by the first matching value and the second matching value, carrying out weighted summation on the first matching value and the second matching value, and taking a weighted summation result as a target matching value; the average of the first matching value and the second matching value may also be taken as the target matching value.
S302, if the target matching value is smaller than the matching value threshold, updating the abnormal event handling standard according to the image recognition result.
Specifically, the target matching value is compared with a preset matching value threshold, if the target matching value is smaller than the matching value threshold, the event handling process of the abnormal event is proved to be inconsistent with the abnormal event handling standard, the image recognition result and the abnormal event handling standard are required to be evaluated at the moment, for example, the image recognition result and the abnormal event handling standard are input into an evaluation model to obtain an image recognition result score and an abnormal event handling standard score, if the image recognition result score is higher than the abnormal event handling standard score, the abnormal event handling standard is described to be outdated, and at the moment, the abnormal event handling standard is required to be updated based on the image recognition result.
Optionally, a first influencing parameter of the image recognition result by the operation step recognition result can be determined according to the first matching value; determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value; and if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold value, outputting accident warning information.
Specifically, a difference value between the first matching value and the matching value threshold may be used as a first influencing parameter of the image recognition result by the operation step recognition result; and taking the difference value between the second matching value and the matching value threshold value as a second influence parameter of the equipment wearing recognition result on the image recognition result, comparing the sum of the first influence parameter and the second influence parameter with the influence parameter threshold value, if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold value, proving that the operation steps of the operation and maintenance personnel and the equipment wearing have larger differences with the abnormal event treatment standard, namely, the risk of abnormal treatment exists, and outputting accident warning information to remind the operation and maintenance personnel that the accident possibly occurs.
In the above embodiment, the abnormal event handling standard can be updated according to the target matching value between the image recognition result and the abnormal event handling standard, so that the handling process of the abnormal event can be standardized more regularly.
In the above embodiment, the history image recognition result is used as a reference for the handling of the abnormal event, so that the handling efficiency and accuracy of the abnormal event are increased.
In order to more fully demonstrate the present solution, this embodiment provides an alternative way of monitoring an abnormal event of a power grid, as shown in fig. 4:
s401, receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request.
S402, searching a historical image recognition result corresponding to a historical treatment process corresponding to the abnormal data according to the abnormal data.
S403, outputting a historical image recognition result.
S404, recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data.
S405, performing image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result.
Wherein the target image recognition result is used to characterize the event handling process.
S406, consistency comparison is carried out on the operation step identification result and the operation step treatment standard, and a first matching value is obtained.
S407, comparing the consistency of the equipment wearing recognition result with the equipment wearing treatment standard to obtain a second matching value.
S408, carrying out statistical processing on the first matching value and the second matching value to obtain a target matching value.
S409, determining a first influence parameter of the operation step recognition result on the image recognition result according to the first matching value.
S410, determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value.
S411, if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold, outputting accident alarm information.
The specific process of S401 to S411 may refer to the description of the foregoing method embodiment, and its implementation principle and technical effect are similar, and are not repeated herein.
It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a power grid abnormal event monitoring device for realizing the power grid abnormal event monitoring method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the device for monitoring abnormal events of the power grid provided below may be referred to the limitation of the method for monitoring abnormal events of the power grid hereinabove, and will not be described herein.
In one embodiment, as shown in fig. 5, there is provided a power grid abnormal event monitoring apparatus 5, including: a data acquisition module 50, a video recording module 51 and a video identification module 52, wherein:
the data acquisition module 50 is used for receiving a power grid data monitoring request and acquiring abnormal data according to the power grid data monitoring request;
the video recording module 51 is configured to record an event handling process of an abnormal event corresponding to the abnormal data, so as to obtain recorded video data;
the video recognition module 52 is configured to perform image recognition processing on each frame of image in the recorded video data, so as to obtain a target image recognition result, where the target image recognition result is used to characterize the event handling process.
In another embodiment, as shown in fig. 6, the power grid abnormal event monitoring apparatus 5 in fig. 5 further includes:
a value acquisition module 53 for acquiring a target matching value between the image recognition result and the abnormal event handling standard.
The standard updating module 54 is configured to update the abnormal event handling standard according to the image recognition result if the target matching value is smaller than the matching value threshold.
In another embodiment, the image recognition result includes an operation step recognition result, the abnormal event handling criteria includes an operation step handling criteria, as shown in fig. 7, and the numerical value obtaining module 53 in fig. 6 includes:
the numerical comparison unit 530 is configured to compare the operation step identification result with the operation step treatment standard to obtain a first matching value.
The value obtaining unit 531 is configured to obtain a target matching value according to the first matching value.
In another embodiment, the image recognition result further includes an equipment wearing recognition result, the abnormal event handling criterion further includes an equipment wearing handling criterion, and the numerical value obtaining unit 531 in fig. 7 is specifically configured to:
consistency comparison is carried out on the equipment wearing recognition result and the equipment wearing treatment standard to obtain a second matching value; and carrying out statistical processing on the first matching value and the second matching value to obtain a target matching value.
In another embodiment, the value obtaining module 53 in fig. 6 is further specifically configured to:
determining a first influence parameter of the operation step recognition result on the image recognition result according to the first matching value; determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value; and if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold value, outputting accident warning information.
In another embodiment, as shown in fig. 8, the data acquisition module 50 in fig. 5 includes:
the result searching unit 500 is configured to search, according to the abnormal data, a historical image recognition result corresponding to a historical treatment process corresponding to the abnormal data.
A result output unit 501 for outputting a history image recognition result.
The modules in the power grid abnormal event monitoring device can be all or partially realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one exemplary embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 9. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing power grid anomaly data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a method for monitoring an abnormal event of a power grid.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program when executed by a processor implements a method for monitoring an abnormal event of a power grid. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 9 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application applies, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring a target matching value between an image recognition result and an abnormal event handling standard; and if the target matching value is smaller than the matching value threshold value, updating the abnormal event handling standard according to the image recognition result.
In one embodiment, the processor when executing the computer program further performs the steps of:
consistency comparison is carried out on the operation step identification result and the operation step treatment standard to obtain a first matching value; and obtaining a target matching value according to the first matching value.
In one embodiment, the processor when executing the computer program further performs the steps of:
consistency comparison is carried out on the equipment wearing recognition result and the equipment wearing treatment standard to obtain a second matching value; and carrying out statistical processing on the first matching value and the second matching value to obtain a target matching value.
In one embodiment, the processor when executing the computer program further performs the steps of:
determining a first influence parameter of the operation step recognition result on the image recognition result according to the first matching value; determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value; and if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold value, outputting accident warning information.
In one embodiment, the processor when executing the computer program further performs the steps of:
searching a historical image identification result corresponding to a historical treatment process corresponding to the abnormal data according to the abnormal data; and outputting a historical image recognition result.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a target matching value between an image recognition result and an abnormal event handling standard; and if the target matching value is smaller than the matching value threshold value, updating the abnormal event handling standard according to the image recognition result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
consistency comparison is carried out on the operation step identification result and the operation step treatment standard to obtain a first matching value; and obtaining a target matching value according to the first matching value.
In one embodiment, the computer program when executed by the processor further performs the steps of:
consistency comparison is carried out on the equipment wearing recognition result and the equipment wearing treatment standard to obtain a second matching value; and carrying out statistical processing on the first matching value and the second matching value to obtain a target matching value.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a first influence parameter of the operation step recognition result on the image recognition result according to the first matching value; determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value; and if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold value, outputting accident warning information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
searching a historical image identification result corresponding to a historical treatment process corresponding to the abnormal data according to the abnormal data; and outputting a historical image recognition result.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording event handling processes of the abnormal events corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing an event handling process.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a target matching value between an image recognition result and an abnormal event handling standard; and if the target matching value is smaller than the matching value threshold value, updating the abnormal event handling standard according to the image recognition result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
consistency comparison is carried out on the operation step identification result and the operation step treatment standard to obtain a first matching value; and obtaining a target matching value according to the first matching value.
In one embodiment, the computer program when executed by the processor further performs the steps of:
consistency comparison is carried out on the equipment wearing recognition result and the equipment wearing treatment standard to obtain a second matching value; and carrying out statistical processing on the first matching value and the second matching value to obtain a target matching value.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a first influence parameter of the operation step recognition result on the image recognition result according to the first matching value; determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value; and if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold value, outputting accident warning information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
searching a historical image identification result corresponding to a historical treatment process corresponding to the abnormal data according to the abnormal data; and outputting a historical image recognition result.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples represent only a few embodiments of the present application, which are described in more detail and are not thereby to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A method for monitoring an abnormal event of a power grid, the method comprising:
receiving a power grid data monitoring request, and acquiring abnormal data according to the power grid data monitoring request;
recording an event handling process of an abnormal event corresponding to the abnormal data to obtain recorded video data;
and carrying out image recognition processing on each frame of image in the recorded video data to obtain a target image recognition result, wherein the target image recognition result is used for representing the event handling process.
2. The method according to claim 1, wherein the method further comprises:
acquiring a target matching value between the image recognition result and an abnormal event handling standard;
and if the target matching value is smaller than a matching value threshold value, updating the abnormal event handling standard according to the image recognition result.
3. The method of claim 2, wherein the image recognition result comprises a procedure recognition result, the abnormal event handling criteria comprises a procedure handling criteria, the obtaining a target match value between the image recognition result and the abnormal event handling criteria comprises:
consistency comparison is carried out on the operation step identification result and the operation step treatment standard to obtain a first matching value;
and acquiring the target matching value according to the first matching value.
4. The method of claim 2, wherein the image recognition result further comprises an equipment wear recognition result, the abnormal event handling criteria further comprises an equipment wear handling criteria, the obtaining the target matching value from a first matching value comprises:
consistency comparison is carried out on the equipment wearing recognition result and the equipment wearing treatment standard to obtain a second matching value;
and carrying out statistical processing on the first matching value and the second matching value to obtain the target matching value.
5. The method according to any one of claims 3-4, further comprising:
determining a first influence parameter of the operation step identification result on the image identification result according to the first matching value;
determining a second influence parameter of the equipment wearing recognition result on the image recognition result according to the second matching value;
and if the sum of the first influence parameter and the second influence parameter is larger than the influence parameter threshold, outputting accident warning information.
6. The method of claim 1, wherein after the collecting of the abnormal data according to the grid data monitoring request, the method further comprises:
searching a historical image recognition result corresponding to a historical treatment process corresponding to the abnormal data according to the abnormal data;
and outputting the historical image recognition result.
7. A power grid anomaly monitoring device, the device comprising:
the data acquisition module is used for receiving a power grid data monitoring request and acquiring abnormal data according to the power grid data monitoring request;
the video recording module is used for recording the event handling process of the abnormal event corresponding to the abnormal data to obtain recorded video data;
the video identification module is used for carrying out image identification processing on each frame of image in the recorded video data to obtain a target image identification result, and the target image identification result is used for representing the event handling process.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311363362.2A CN117557951A (en) | 2023-10-19 | 2023-10-19 | Power grid abnormal event monitoring method, device, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311363362.2A CN117557951A (en) | 2023-10-19 | 2023-10-19 | Power grid abnormal event monitoring method, device, computer equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117557951A true CN117557951A (en) | 2024-02-13 |
Family
ID=89811848
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311363362.2A Pending CN117557951A (en) | 2023-10-19 | 2023-10-19 | Power grid abnormal event monitoring method, device, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117557951A (en) |
-
2023
- 2023-10-19 CN CN202311363362.2A patent/CN117557951A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20160063387A1 (en) | Monitoring and detecting environmental events with user devices | |
| CN113823396A (en) | Medical equipment management method and device, computer equipment and storage medium | |
| CN114446019A (en) | Alarm information processing method, device, equipment, storage medium and product | |
| CN117557951A (en) | Power grid abnormal event monitoring method, device, computer equipment and storage medium | |
| CN115438812A (en) | Life-saving management method and device for power transmission equipment, computer equipment and storage medium | |
| CN114118469A (en) | Internet of things equipment diagnosis method and device, computer equipment and storage medium | |
| CN115630527B (en) | Exception model detection method, device, computer equipment and storage medium | |
| CN116577586A (en) | Power equipment fault monitoring method, device, computer equipment and storage medium | |
| CN117097599B (en) | Network service detection method, device, computer equipment and storage medium | |
| CN116881092A (en) | Method, device, equipment and storage medium for predicting alarm data | |
| CN116129351A (en) | Personnel monitoring alarm method, device, computer equipment and storage medium | |
| CN116757677A (en) | Linkage processing method and device for abnormal power grid equipment and computer equipment | |
| CN117893006A (en) | Power grid risk assessment method, device, equipment, medium and program product | |
| CN118155383A (en) | Early warning processing method, early warning processing device, computer equipment and storage medium | |
| CN116594835A (en) | Application health monitoring method and device, storage medium and computer equipment | |
| CN118245585A (en) | Intrinsic safety problem display method, device, equipment, storage medium and product | |
| CN118260110A (en) | Fault exercise method, device, computer equipment, storage medium and program product | |
| CN116248754A (en) | Information pushing method, device, computer equipment and storage medium | |
| CN117194191A (en) | Log monitoring alarm method, device, computer equipment and storage medium | |
| CN115834353A (en) | Fault self-healing method, device, equipment, storage medium and computer program product | |
| CN117724930A (en) | Data monitoring method, device, computer equipment and storage medium | |
| CN117590149A (en) | Fault solution generation method, device and equipment based on big data technology | |
| CN117149589A (en) | Resource management method, device, equipment, storage medium and product of business system | |
| CN118297399A (en) | Intrinsic safety problem analysis method, device, apparatus, storage medium and product | |
| CN117056307A (en) | Database management method, apparatus, device, storage medium, and program product |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |