CN112994250A - Heavy overload event monitoring method and device, electronic equipment and storage medium - Google Patents
Heavy overload event monitoring method and device, electronic equipment and storage medium Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F40/00—Handling natural language data
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/40—Display of information, e.g. of data or controls
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Abstract
The invention discloses a heavy overload event monitoring method, a heavy overload event monitoring device, electronic equipment and a storage medium, wherein the method comprises the following steps: the method comprises the steps of periodically obtaining heavy overload event data of a visual system, dividing the heavy overload event data according to preset keyword labels to obtain divided heavy overload event data, traversing the divided heavy overload event data, recombining the divided heavy overload event data according to equipment names and equipment information in an equipment table to obtain a target heavy overload event data set, obtaining detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set, and monitoring the heavy overload event by periodically detecting the heavy overload information and the heavy overload equipment in the detailed event structure data. According to the invention, the heavy overload events are detected by systematic classification of the heavy overload events, so that the safe and stable operation level of the power grid is improved.
Description
Technical Field
The present invention relates to the field of heavy overload monitoring technologies, and in particular, to a method and an apparatus for monitoring a heavy overload event, an electronic device, and a storage medium.
Background
With the rapid development of economy and the rapid increase of power demand, the power grid is continuously enlarged, the heavy overload problem is highlighted, and various faults are frequently developed. If the overload is not monitored and analyzed, the line can be in overload operation for a long time, the conductor heats seriously, the insulation layer is damaged and reduced, finally, a fault is developed, the power supply influence is caused to a power supply user, and the economy of a power supply company is influenced.
Since monitoring of heavy overloads is of great importance for long-term safe operation of the power grid, every power supply company also pays much attention. At present, some systems collect and analyze electrical equipment data, when equipment parameters exceed set values, a load prediction alarm event is generated and concurrent information is sent to remind relevant technicians, and the technicians then adopt experience to predict and regulate according to the static data. For the existing static heavy overload event data, a better method is needed to analyze the data, the swept range is more refined and analyzed, and the management is more refined and corresponding adjustment measures are taken.
Therefore, in order to safely and stably operate a power grid, a heavy overload event monitoring method needs to be constructed to solve the technical problem that the heavy overload event cannot be detected through a system at present.
Disclosure of Invention
The invention provides a heavy overload event monitoring method and device, electronic equipment and a storage medium, which solve the technical problem that the heavy overload event cannot be detected through a system at present.
In a first aspect, the present invention provides a method for monitoring a heavy overload event, including:
periodically acquiring heavy overload event data of a visual system; the heavy overload event data is data of events generated by equipment operating at higher overload multiples and overload time;
dividing the heavy overload event data according to a preset keyword label to obtain divided heavy overload event data;
traversing the divided heavy overload event data, and recombining the divided heavy overload event data according to the device name and the device information in the device table to obtain a target heavy overload event data set;
obtaining detail event structure data according to the divided heavy overload event data and the target heavy overload event data set;
and monitoring the heavy overload event by periodically detecting heavy overload information and heavy overload equipment in the detailed event structure data.
Optionally, the preset keyword tag comprises a preset site tag and a preset main transformer content tag; dividing the heavy overload event data according to a preset keyword label to obtain divided heavy overload event data, wherein the divided heavy overload event data comprises the following steps:
according to preset different site tags, carrying out initial division on the heavy overload event data to obtain the heavy overload event data after the initial division;
and carrying out secondary division on the initially divided heavy overload event data according to preset different main transformer content labels to obtain the divided heavy overload event data.
Optionally, obtaining detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set, where the obtaining includes:
according to the name and overload time of the heavy overload event, carrying out layered display on the heavy overload equipment information in the target heavy overload event data set to obtain detailed data of the heavy overload event displayed in a layered manner;
and classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the heavy overload events displayed in a layered mode to obtain detailed event structure data.
Optionally, classifying the divided heavy overload event data, the target heavy overload event data set, and the detailed data of the hierarchically displayed heavy overload event to obtain detailed event structure data, including:
establishing a three-level hierarchical structure;
and classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload events into the three-level hierarchical structure according to the time and the type of the heavy overload events to obtain detailed event structure data.
In a second aspect, the present invention provides a heavy overload event monitoring apparatus, including:
the acquisition module is used for periodically acquiring the heavy overload event data of the visual system; the heavy overload event data is data of events generated by equipment operating at higher overload multiples and overload time;
the dividing module is used for dividing the heavy overload event data according to a preset keyword label to obtain divided heavy overload event data;
the recombination module is used for traversing the divided heavy overload event data and recombining the divided heavy overload event data according to the equipment name and the equipment information in the equipment table to obtain a target heavy overload event data set;
the structure module is used for obtaining detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set;
and the detection module is used for monitoring the heavy overload event by periodically detecting heavy overload information and heavy overload equipment in the detail event structure data.
Optionally, the preset keyword tag comprises a preset site tag and a preset main transformer content tag; the dividing module includes:
the initial division submodule is used for initially dividing the heavy overload event data according to preset different site tags to obtain the initially divided heavy overload event data;
and the secondary division submodule is used for carrying out secondary division on the initially divided heavy overload event data according to preset different main transformer content labels to obtain the divided heavy overload event data.
Optionally, the structural module comprises:
the hierarchical submodule is used for hierarchically displaying the heavy overload equipment information in the target heavy overload event data set according to the name and the overload time of the heavy overload event to obtain detailed data of the hierarchically displayed heavy overload event;
and the classification submodule is used for classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the heavy overload events displayed in a layered mode to obtain detailed event structure data.
Optionally, the classification sub-module includes:
the building unit is used for building a three-level hierarchical structure;
and the classifying unit is used for classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload event into the three-level hierarchical structure according to the time and the type of the heavy overload event to obtain detailed event structure data.
In a third aspect, the present invention provides an electronic device comprising a processor, a memory, and a program or instructions stored on the memory and executable on the processor, which when executed by the processor, implement the steps of the method according to the first aspect.
In a fourth aspect, the present invention provides a readable storage medium on which is stored a program or instructions which, when executed by a processor, performs the steps of the method according to the first aspect.
According to the technical scheme, the invention has the following advantages: the invention provides a heavy overload event monitoring method, which comprises the steps of periodically acquiring heavy overload event data of a visual system, dividing the heavy overload event data according to preset keyword labels to obtain divided heavy overload event data, traversing the divided heavy overload event data, recombining the divided heavy overload event data according to an equipment name and equipment information in an equipment table to obtain a target heavy overload event data set, acquiring detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set, periodically detecting the heavy overload information and the heavy overload equipment in the detailed event structure data to monitor the heavy overload events, classifying the heavy overload events by a system to detect the heavy overload events, and solving the technical problem that the heavy overload events can not be detected by the system at present, the safe and stable operation level of the power grid is improved, and support is provided for power grid load.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a flowchart illustrating a first embodiment of a method for monitoring a heavy overload event according to the present invention;
fig. 2 is a flowchart illustrating a second embodiment of a method for monitoring a heavy overload event according to the present invention;
fig. 3 is a block diagram of an embodiment of a heavy overload event monitoring device according to the present invention.
Detailed Description
The embodiment of the invention provides a heavy overload event monitoring method, a heavy overload event monitoring device, electronic equipment and a storage medium, which are used for solving the technical problem that the heavy overload event cannot be detected through a system at present.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating a first method for monitoring a heavy overload event according to a first embodiment of the present invention, including:
step S101, heavy overload event data of a visualization system are periodically acquired; the heavy overload event data is data of events generated by equipment operating at higher overload multiples and overload time;
step S102, dividing the heavy overload event data according to a preset keyword label to obtain divided heavy overload event data;
step S103, traversing the divided heavy overload event data, and recombining the divided heavy overload event data according to the device name and the device information in the device table to obtain a target heavy overload event data set;
step S104, obtaining detail event structure data according to the divided heavy overload event data and the target heavy overload event data set;
step S105, monitoring the heavy overload event by periodically detecting heavy overload information and heavy overload devices in the detail event structure data.
The method for monitoring the heavy overload event provided by the embodiment of the invention comprises the steps of periodically acquiring heavy overload event data of a visual system, dividing the heavy overload event data according to preset keyword labels to obtain divided heavy overload event data, traversing the divided heavy overload event data, recombining the divided heavy overload event data according to an equipment name and equipment information in an equipment table to obtain a target heavy overload event data set, acquiring detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set, periodically detecting heavy overload information and heavy overload equipment in the detailed event structure data to monitor the heavy overload event, and classifying the heavy overload event by the system to detect the heavy overload event, the technical problem that the existing system cannot detect the heavy overload event is solved, the safe and stable operation level of the power grid is improved, and support is provided for special power grid load.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for monitoring a heavy overload event according to a second embodiment of the present invention, including:
step S201, periodically acquiring heavy overload event data of a visualization system;
it should be noted that the heavy overload event data is data of events generated by devices operating at higher overload multiples and overload times.
The visualization system is a system which collects a large amount of heterogeneous system data, integrates and utilizes big data analysis capability and computer vision technology, combines multiple analysis means such as correlation analysis, spatial analysis and multidimensional analysis, excavates a corresponding data service algorithm model, and finally displays an analysis result through a visualization interface.
In the embodiment of the invention, a worker synchronously visualizes main network overload event data of the system through a data acquisition system; and by utilizing a data acquisition middleware, newly establishing a main network overload event source table and a new system target table of the conversion configuration visualization system, and periodically executing conversion, wherein the execution period is one minute.
Step S202, according to preset different site labels, carrying out initial division on the heavy overload event data to obtain the heavy overload event data after the initial division;
it should be noted that the preset keyword tag includes a preset site tag and a preset main change content tag.
In the embodiment of the invention, the heavy overload event data is initially divided according to the preset different site tags to obtain the initially divided heavy overload event data.
In the specific implementation, according to the site a, the site B and the site C involved in the heavy overload event, the heavy overload event data is initially divided into the site a heavy overload event data, the site B heavy overload event data and the site C heavy overload event data.
Step S203, secondary division is carried out on the initially divided heavy overload event data according to different preset main transformer content labels to obtain divided heavy overload event data;
in the embodiment of the invention, the initially divided heavy overload event data is divided for the second time according to the preset different main transformer content labels to obtain the divided heavy overload event data.
In the specific implementation, according to a D main transformer and an E main transformer related to a heavy overload event, the station A heavy overload event data, the station B heavy overload event data and the station C heavy overload event data which are subjected to the initial division are subjected to secondary division, and the divided station A heavy overload event data, the station A E main transformer heavy overload event data, the station B D main transformer heavy overload event data, the station B E main transformer heavy overload event data, the station C D main transformer heavy overload event data and the station C E main transformer heavy overload event data are combined to obtain the divided heavy overload event data.
Step S204, traversing the divided heavy overload event data, and recombining the divided heavy overload event data according to the device name and the device information in the device table to obtain a target heavy overload event data set;
it should be noted that, traversing refers to making one visit to each node in the tree (or graph) in turn along a certain search route. The operation performed by the access node depends on the specific application problem, and the specific access operation may be to check the value of the node, update the value of the node, and the like. Different traversal methods have different access node orders. Traversal is one of the most important operations in the binary tree, and is the basis for performing other operations in the binary tree.
In the embodiment of the invention, the divided heavy overload event data is traversed, then a new piece of data is reconstructed by related equipment and stored in a main network heavy overload list according to the equipment name and the equipment information in the equipment list, and the originally synchronized heavy overload event data is cleaned and reconstructed by the fields and stored in the main network heavy overload event list.
In the specific implementation, according to the device name and the device information in the device table, the heavy overload event data of the site D main transformer a, the heavy overload event data of the site E main transformer a, the heavy overload event data of the site D main transformer B, the heavy overload event data of the site E main transformer B, the heavy overload event data of the site D main transformer C and the heavy overload event data of the site E main transformer C are recombined and divided into heavy overload event data about F devices, heavy overload event data about G devices, and the like, and heavy overload event data about the devices are obtained as a target heavy overload event data set.
Step S205, according to the name and overload time of the heavy overload event, hierarchically displaying the heavy overload equipment information in the target heavy overload event data set to obtain detailed data of the hierarchically displayed heavy overload event;
in the embodiment of the present invention, the heavy overload device information in the target heavy overload event data set needs to be displayed hierarchically according to the name and the overload time of the heavy overload event, so as to classify the detailed data of the heavy overload event performed later.
In a specific implementation, the heavy overload event data about the equipment is displayed in a layered mode according to overload time, and the heavy overload event data about the F equipment in X year Y month Z1, X year Y month Z2, X year Y month Z1, X year Y month Z2 and the like are displayed to obtain detailed data of the heavy overload event displayed in a layered mode.
Step S206, classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the heavy overload events displayed in a layered mode to obtain detailed event structure data;
in an optional embodiment, classifying the divided heavy overload event data, the target heavy overload event data set, and the detailed data of the hierarchically displayed heavy overload event to obtain detailed event structure data includes:
establishing a three-level hierarchical structure;
classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload event into the three-level hierarchical structure according to the time and the type of the heavy overload event to obtain detailed event structure data;
in the embodiment of the invention, the classified heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload event are classified to obtain detailed event structure data.
In a specific implementation, a three-level hierarchical structure is created, and the divided heavy overload event data, the target heavy overload event data set and the detailed data of the heavy overload events displayed in a hierarchical manner are classified;
when the heavy overload event type belongs to the site type, adding detailed data of the heavy overload event to a first level;
when the heavy overload event type does not belong to the site type, judging whether the heavy overload event type belongs to a main transformer type;
if yes, adding detailed data of the heavy overload event to a second level;
if not, adding the detailed data of the heavy overload event to a third level;
detail event structure data is obtained.
The method specifically comprises the following steps: and adding the site A heavy overload event data, the site B heavy overload event data and the site C heavy overload event data to the first stage.
And adding the heavy overload event data of the site D main transformer A, the heavy overload event data of the site E main transformer A, the heavy overload event data of the site D main transformer B, the heavy overload event data of the site E main transformer B, the heavy overload event data of the site D main transformer C and the heavy overload event data of the site E main transformer C to the second stage.
Heavy overload event data on F devices, displayed as X year Y month Z1 day, X year Y month Z2 day, X year Y month Z1 day, and X year Y month Z2 day are added to the third level.
And classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload event to obtain detailed event structure data.
Step S207, monitoring the heavy overload event by periodically detecting heavy overload information and heavy overload equipment in the detail event structure data;
in the embodiment of the present invention, the heavy overload event is monitored by periodically detecting heavy overload information and heavy overload devices in the detail event structure data.
In a specific implementation, the detection of the heavy overload information and the heavy overload devices in the detailed event structure data may be performed periodically, and the execution period is one minute, and the monitoring of the heavy overload events is implemented by periodically detecting the heavy overload information and the heavy overload devices in the detailed event structure data.
The method for monitoring the heavy overload event provided by the embodiment of the invention comprises the steps of periodically acquiring heavy overload event data of a visual system, dividing the heavy overload event data according to preset keyword labels to obtain divided heavy overload event data, traversing the divided heavy overload event data, recombining the divided heavy overload event data according to an equipment name and equipment information in an equipment table to obtain a target heavy overload event data set, acquiring detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set, periodically detecting heavy overload information and heavy overload equipment in the detailed event structure data to monitor the heavy overload event, and classifying the heavy overload event by the system to detect the heavy overload event, the technical problem that the existing system cannot detect the heavy overload event is solved, the safe and stable operation level of the power grid is improved, and support is provided for special power grid load.
Referring to fig. 3, fig. 3 is a block diagram of a monitoring device for heavy overload events according to an embodiment of the present invention, including:
an obtaining module 101, configured to periodically obtain overload event data of a visualization system; the heavy overload event data is data of events generated by equipment operating at higher overload multiples and overload time;
the dividing module 102 is configured to divide the heavy overload event data according to a preset keyword tag to obtain divided heavy overload event data;
the restructuring module 103 is configured to traverse the divided heavy overload event data, and restructure the divided heavy overload event data according to the device name and the device information in the device table to obtain a target heavy overload event data set;
a structure module 104, configured to obtain detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set;
a detecting module 105, configured to monitor the heavy overload event by periodically detecting heavy overload information and heavy overload devices in the detail event structure data.
In an optional embodiment, the preset keyword tags include preset site tags and preset main transformer content tags; the dividing module 102 includes:
the initial division submodule is used for initially dividing the heavy overload event data according to preset different site tags to obtain the initially divided heavy overload event data;
and the secondary division submodule is used for carrying out secondary division on the initially divided heavy overload event data according to preset different main transformer content labels to obtain the divided heavy overload event data.
In an alternative embodiment, the fabric module 104 includes:
the hierarchical submodule is used for hierarchically displaying the heavy overload equipment information in the target heavy overload event data set according to the name and the overload time of the heavy overload event to obtain detailed data of the hierarchically displayed heavy overload event;
and the classification submodule is used for classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the heavy overload events displayed in a layered mode to obtain detailed event structure data.
In an alternative embodiment, the classification sub-module comprises:
the building unit is used for building a three-level hierarchical structure;
and the classifying unit is used for classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload event into the three-level hierarchical structure according to the time and the type of the heavy overload event to obtain detailed event structure data.
An embodiment of the present invention further provides an electronic device, which includes a memory and a processor, where the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for monitoring a heavy overload event according to any of the above embodiments.
The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by the processor, implements the method for monitoring a heavy overload event according to any of the above embodiments.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present application, it should be understood that the method, apparatus, electronic device and storage medium disclosed in the present application may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a readable storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned readable storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for monitoring heavy overload events, comprising:
periodically acquiring heavy overload event data of a visual system; the heavy overload event data is data of events generated by equipment operating at higher overload multiples and overload time;
dividing the heavy overload event data according to a preset keyword label to obtain divided heavy overload event data;
traversing the divided heavy overload event data, and recombining the divided heavy overload event data according to the device name and the device information in the device table to obtain a target heavy overload event data set;
obtaining detail event structure data according to the divided heavy overload event data and the target heavy overload event data set;
and monitoring the heavy overload event by periodically detecting heavy overload information and heavy overload equipment in the detailed event structure data.
2. The method for monitoring the heavy overload event according to claim 1, wherein the preset keyword tags comprise preset site tags and preset main transformer content tags; dividing the heavy overload event data according to a preset keyword label to obtain divided heavy overload event data, wherein the divided heavy overload event data comprises the following steps:
according to preset different site tags, carrying out initial division on the heavy overload event data to obtain the heavy overload event data after the initial division;
and carrying out secondary division on the initially divided heavy overload event data according to preset different main transformer content labels to obtain the divided heavy overload event data.
3. The method for monitoring heavy overload events according to claim 1 or 2, wherein obtaining detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set includes:
according to the name and overload time of the heavy overload event, carrying out layered display on the heavy overload equipment information in the target heavy overload event data set to obtain detailed data of the heavy overload event displayed in a layered manner;
and classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the heavy overload events displayed in a layered mode to obtain detailed event structure data.
4. The method for monitoring heavy overload events according to claim 3, wherein classifying the divided heavy overload event data, the target heavy overload event data set, and the detailed data of the hierarchically displayed heavy overload events to obtain detailed event structure data includes:
establishing a three-level hierarchical structure;
and classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload events into the three-level hierarchical structure according to the time and the type of the heavy overload events to obtain detailed event structure data.
5. A device for monitoring heavy overload events, comprising:
the acquisition module is used for periodically acquiring the heavy overload event data of the visual system; the heavy overload event data is data of events generated by equipment operating at higher overload multiples and overload time;
the dividing module is used for dividing the heavy overload event data according to a preset keyword label to obtain divided heavy overload event data;
the recombination module is used for traversing the divided heavy overload event data and recombining the divided heavy overload event data according to the equipment name and the equipment information in the equipment table to obtain a target heavy overload event data set;
the structure module is used for obtaining detailed event structure data according to the divided heavy overload event data and the target heavy overload event data set;
and the detection module is used for monitoring the heavy overload event by periodically detecting heavy overload information and heavy overload equipment in the detail event structure data.
6. The device for monitoring the heavy overload event according to claim 5, wherein the preset keyword tags comprise preset site tags and preset main transformer content tags; the dividing module includes:
the initial division submodule is used for initially dividing the heavy overload event data according to preset different site tags to obtain the initially divided heavy overload event data;
and the secondary division submodule is used for carrying out secondary division on the initially divided heavy overload event data according to preset different main transformer content labels to obtain the divided heavy overload event data.
7. Monitoring device of a heavy overload event according to claim 5 or 6, characterized in that the structural module comprises:
the hierarchical submodule is used for hierarchically displaying the heavy overload equipment information in the target heavy overload event data set according to the name and the overload time of the heavy overload event to obtain detailed data of the hierarchically displayed heavy overload event;
and the classification submodule is used for classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the heavy overload events displayed in a layered mode to obtain detailed event structure data.
8. The apparatus for monitoring heavy overload events according to claim 7, wherein the classification submodule comprises:
the building unit is used for building a three-level hierarchical structure;
and the classifying unit is used for classifying the divided heavy overload event data, the target heavy overload event data set and the detailed data of the hierarchically displayed heavy overload event into the three-level hierarchical structure according to the time and the type of the heavy overload event to obtain detailed event structure data.
9. An electronic device comprising a processor and a memory, the memory storing computer readable instructions that, when executed by the processor, perform the method of any of claims 1-4.
10. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the method according to any of claims 1-4.
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