Power grid equipment risk state early warning method and device, electronic equipment and storage medium

Abstract

The invention discloses a power grid equipment risk state early warning method and device, electronic equipment and a storage medium. The power grid equipment risk state early warning method comprises the steps of obtaining equipment information and environment information of power grid equipment in a monitoring range; according to the equipment information and the environment information, constructing a three-dimensional virtual model comprising an equipment type, an equipment number, a power grid equipment location section and a section number; early warning information in the monitoring range is acquired in real time, the early warning information comprises meteorological disaster early warning information and an early warning section, and target detection equipment is determined and a patrol path is generated in combination with the early warning information and the three-dimensional virtual model; sending the patrol path to the detection object to collect device data of the target detection device; and determining risk early warning information of the target detection equipment according to the equipment data. Through the steps, the risk items in the monitoring range can be detected and evaluated in time, risk early warning can be carried out on the power grid equipment with risks, faults and damage accidents of the power grid equipment can be reduced, and the stability of a power system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of risk status early warning for power grid equipment, and in particular to a method, device, electronic device and storage medium for early warning of risk status for power grid equipment. Background Art

[0002] With the rapid economic development and the growing demand for electricity in society, the scale of the power system is becoming increasingly large. The coverage of the power grid continues to expand, the transmission lines are getting longer and longer, the number of substations is increasing, and a large number of power generation equipment, transmission equipment, and distribution equipment are interconnected to form a complex giant network. This large-scale power system makes the spread and impact of power safety risks wider, and once a failure occurs, it may trigger a chain reaction.

[0003] Traditional early warning systems are struggling to cope with the needs of safety risk monitoring and early warning of such a large-scale power system. Traditional early warning systems often rely on manpower, which requires people to collect risk indicator data, integrate and calculate safety status scores, form early warning results based on the scores, and then conduct problem analysis and rectification around the early warning results. The implementation of this safety status evaluation and early warning work mechanism has improved the management and handling efficiency of safety risks to a certain extent, but in the process of implementation, the timeliness of the final early warning cannot be guaranteed by manually obtaining data and then integrating and calculating it, and it can often only achieve the effect of post-rectification. Summary of the invention

[0004] The present invention provides a method for early warning of risk status of power grid equipment to solve the problem that the timeliness of early warning of risk status of power grid equipment cannot be guaranteed.

[0005] In a first aspect, the present invention provides a method for early warning of risk status of power grid equipment, comprising:

[0006] Obtain equipment information and environmental information of power grid equipment within the monitoring range;

[0007] Constructing a three-dimensional virtual model according to the equipment information and the environmental information, wherein the three-dimensional virtual model includes equipment type and equipment number of the power grid equipment, and the location and location number of the power grid equipment;

[0008] Acquire warning information within the monitoring range in real time, the warning information including meteorological disaster warning information and warning areas;

[0009] Determining a target detection device in combination with the warning information and the three-dimensional virtual model and generating a patrol path for detecting the target detection device;

[0010] Sending the patrol path to the detection object to collect device data of the target detection device;

[0011] The risk warning information of the target detection device is determined according to the device data.

[0012] In a second aspect, the present invention provides a risk status early warning device for power grid equipment, comprising:

[0013] An information acquisition module is used to obtain device information and environmental information of power grid devices within the monitoring range;

[0014] A model building module, used to build a three-dimensional virtual model according to the equipment information and the environmental information, wherein the three-dimensional virtual model includes the equipment type and equipment number of the power grid equipment, the location of the power grid equipment and the location number;

[0015] A warning information acquisition module is used to obtain the warning information within the monitoring range in real time, wherein the warning information includes meteorological disaster warning information and warning areas;

[0016] A detection information determination module, used to determine a target detection device in combination with the warning information and the three-dimensional virtual model and to generate a patrol path for detecting the target detection device;

[0017] A device data collection module, used for sending the patrol path to the detection object to collect device data of the target detection device;

[0018] The risk warning information determination module is used to determine the risk warning information of the target detection device according to the device data.

[0019] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0020] at least one processor; and

[0021] a memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the power grid equipment risk status early warning method described in the first aspect of the present invention.

[0023] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a processor to implement the power grid equipment risk status warning method described in the first aspect of the present invention when executed.

[0024] The method for early warning of the risk status of power grid equipment provided by the embodiment of the present invention obtains the equipment information and environmental information of the power grid equipment within the monitoring range; constructs a three-dimensional virtual model based on the equipment information and environmental information, the three-dimensional virtual model includes the equipment type and equipment number of the power grid equipment, the location of the power grid equipment and the location number; obtains early warning information within the monitoring range in real time, the early warning information includes meteorological disaster early warning information and early warning areas, combines the early warning information and the three-dimensional virtual model to determine the target detection equipment and generate a patrol path for detecting the target detection equipment; sends the patrol path to the detection object to collect the equipment data of the target detection equipment; determines the risk early warning information of the target detection equipment based on the equipment data. Through the above steps, the risk items within the monitoring range can be detected and evaluated in a timely manner, and risk early warnings can be issued for risky power grid equipment, which can reduce the occurrence of failures and damage accidents of power grid equipment and improve the stability of the power system.

[0025] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 This is a flow chart of a method for early warning of risk status of power grid equipment provided by Embodiment 1 of the present invention;

[0028] Figure 2 It is a structural schematic diagram of a risk status early warning device for power grid equipment provided by Embodiment 2 of the present invention;

[0029] Figure 3 It is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] Embodiment 1

[0032] Figure 1 This is a flowchart of a method for early warning of a risk status of a power grid device provided in the first embodiment of the present invention. This embodiment is applicable to situations where early warning of a risk status of a power grid device is required. The method can be executed by an early warning device for risk status of a power grid device. The early warning device for risk status of a power grid device can be implemented in the form of hardware and / or software. The early warning device for risk status of a power grid device can be configured in an electronic device. Figure 1 As shown, the grid equipment risk status early warning method includes:

[0033] S101. Obtain equipment information and environmental information of power grid equipment within a monitoring range.

[0034] Equipment information may include the name, type, model, and location of the power grid equipment. Equipment information can usually be obtained from the management system of the power grid equipment. Environmental information may include key entities such as buildings, vegetation, and roads around the power grid equipment. Environmental information can be obtained by taking photos or videos of the detection range by drones, and then determining the environmental information through photos or videos.

[0035] S102: construct a three-dimensional virtual model according to the equipment information and the environment information, wherein the three-dimensional virtual model includes the equipment type and equipment number of the power grid equipment, and the location and location number of the power grid equipment.

[0036] The three-dimensional model is a polygonal representation of an object, and is usually designed with the aid of modeling software in a computer or other video equipment. The displayed object may be a power grid device and key entities around the power grid device. After the entity modeling is completed, the power grid devices and road sections in the model are numbered. Specifically, the numbering may be performed according to the device model of the power grid device, the name of the road section or the road number, or the numbering may be performed regularly, and the present invention is not limited to this.

[0037] S103. Acquire warning information within the monitoring range in real time, the warning information including meteorological disaster warning information and warning areas.

[0038] Meteorological disaster warning information includes meteorological data and disaster warning data. Meteorological data includes temperature, precipitation, air pressure, wind speed, etc. Disaster warning data includes rainstorm, typhoon, fire, earthquake, etc. Warning area refers to the area targeted by the warning information.

[0039] S104, determining a target detection device in combination with the warning information and the three-dimensional virtual model and generating a patrol path for detecting the target detection device.

[0040] Specifically, it includes: determining the equipment type of the power grid equipment to be inspected according to the meteorological disaster warning information to obtain the target equipment type; using the power grid equipment in the three-dimensional virtual model, which is located in the warning area and has the target equipment type as the target detection equipment; and generating a patrol path for detecting the target detection equipment according to the three-dimensional virtual model and the target detection equipment.

[0041] The risks of each type of power grid equipment in different meteorological disaster environments are different. For example, when encountering severe weather such as strong winds and ice, the transmission line may experience abnormal conditions such as excessive sag. When encountering hot and dry weather, there may also be fire warnings, and the distribution station may experience abnormal conditions of high-temperature operation. Distribution stations near mountains and forests also have fire risks. Therefore, the equipment type of the power grid equipment to be inspected can be determined based on the meteorological disaster warning information, the target equipment type can be obtained, and then a patrol path can be generated for the power grid equipment of the target equipment type in the warning area.

[0042] Specifically, generating a patrol path for detecting the target detection device based on the three-dimensional virtual model and the target detection device includes: marking the road section where the target detection device is located to obtain multiple marking points; and performing path planning for the marking points based on the shortest path principle to obtain a patrol path for detecting the target detection device.

[0043] There may be multiple target detection devices, which may be located in different areas. Therefore, when multiple target detection devices are to be inspected, a patrol path may be generated based on the positional relationship between the target detection devices. Specifically, the patrol path may be obtained based on the shortest path principle.

[0044] Of course, when there are target detection devices with large intervals, patrol paths can also be generated for target detection devices with intervals within a certain range, so that multiple patrol paths may be obtained, thereby avoiding wasting travel time between target detection devices with large intervals.

[0045] S105: Send the patrol path to the detection object to collect device data of the target detection device.

[0046] The detection object can be a drone or a robot, which is equipped with sensors, including cameras, temperature sensors, humidity sensors, etc. When the drone or robot receives the patrol path, it generates corresponding control instructions to control the movement of the drone or robot and collect data.

[0047] The detection object may be a detection personnel. Before sending the patrol path to the detection object, the method further includes: obtaining first personnel information of the detection personnel; and determining the detection object with detection authority from the detection personnel based on the device information of the target detection device and the first personnel information.

[0048] Different inspectors may be responsible for supervising power grid equipment in different areas and of different equipment types, that is, they have different inspection permissions for different power grid equipment. Therefore, the first personnel information of different inspectors is associated with different equipment information.

[0049] S106. Determine risk warning information of the target detection device according to the device data.

[0050] After obtaining the equipment data, the equipment data can be analyzed and risk warning information of the target detection equipment can be determined. Specifically, determining the risk warning information of the target detection equipment based on the equipment data includes: determining the detection parameter type based on the equipment information of the target detection equipment; analyzing the parameters of the detection parameter type from the equipment data; judging whether the parameters of the detection parameter type exceed a preset parameter threshold; if so, generating risk warning information, and issuing the risk warning information of the target detection equipment to the maintenance object.

[0051] Exemplarily, when the power grid equipment is a transmission line and the equipment data is image information, the equipment data can be analyzed to obtain the sag data of the transmission line, and determine whether the sag data exceeds a preset sag parameter threshold. If so, relevant risk warning information is generated based on the sag data. The risk warning information should also include the equipment type, the location of the equipment, and the risk type.

[0052] In an optional embodiment, the maintenance object includes maintenance personnel. Before issuing the risk warning information of the target detection device to the maintenance object, it also includes: obtaining second personnel information of the maintenance personnel; based on the device information of the target detection device and the second personnel information, determining the maintenance object with maintenance authority from the maintenance personnel.

[0053] Both the first personnel information and the second personnel information may include the staff member's personal ID card, academic certificate, degree certificate, professional title certificate, professional qualification certificate, award certificate, work log and work authority, work performance rating, etc.

[0054] In an optional embodiment, the method for early warning of risk status of power grid equipment further includes: generating an operation plan according to the risk early warning information and risk level, the operation plan including operation risks and operation processes, and providing timely warnings and solutions for risks that may occur during the operation. The work plan can also be displayed to demonstrate the expected progress of the work, possible risks, and equipment changes after using the solution to the staff, as well as subsequent equipment changes and risk changes.

[0055] In an optional embodiment, it also includes: determining the risk level of the risk warning information, obtaining risk processing data from the generation of the risk warning information to the lifting of the risk warning; optimizing the detection parameter type and parameter threshold associated with the power grid equipment according to the risk level and risk processing data.

[0056] Risk processing data includes, such settings may include the time when the risk occurs and ends, the cause of the risk, equipment operation data, risk resolution measures, the time to implement the resolution measures, and personnel behavior data, environmental data, and required equipment information. According to the risk level and based on the risk processing data, the detection parameter types and parameter thresholds associated with the power grid equipment are optimized. For example, when the risk level is high, the parameter thresholds can be adjusted appropriately so that preventive measures can be taken in the early stages of the risk to avoid the expansion of the hazard. The correlation between the detection parameter type and the cause of the risk can also be analyzed to determine whether it is necessary to increase or decrease the detection parameter type associated with a certain power grid equipment; this can help improve the credibility of risk warnings, reduce risk processing time, and improve the effectiveness of risk resolution measures.

[0057] Specifically, risk processing data can be used by staff to input external data and transmit the data to the designated module of the system as specified by the staff. Security risks can also be graded according to the degree of urgency and the degree of harm. Machine learning algorithms are used to optimize the system's identification and early warning of security risk status in continuous data input.

[0058] The method for early warning of the risk status of power grid equipment provided by the embodiment of the present invention obtains the equipment information and environmental information of the power grid equipment within the monitoring range; constructs a three-dimensional virtual model based on the equipment information and environmental information, the three-dimensional virtual model includes the equipment type and equipment number of the power grid equipment, the location of the power grid equipment and the location number; obtains early warning information within the monitoring range in real time, the early warning information includes meteorological disaster early warning information and early warning areas, combines the early warning information and the three-dimensional virtual model to determine the target detection equipment and generate a patrol path for detecting the target detection equipment; sends the patrol path to the detection object to collect the equipment data of the target detection equipment; determines the risk early warning information of the target detection equipment based on the equipment data. Through the above steps, the risk items within the monitoring range can be detected and evaluated in a timely manner, and risk early warnings can be issued for risky power grid equipment, which can reduce the occurrence of failures and damage accidents of power grid equipment and improve the stability of the power system.

[0059] Optionally, when maintenance personnel perform maintenance on target detection equipment, they usually need to use tools, including protective equipment, detection tools, maintenance tools, etc. The risk status early warning method for power grid equipment also includes: recording the tool number and the tool production date, usage time, usage status, and location information. If the tool has a service life requirement, a replacement instruction is sent to the responsible person at least one month before the expiration of the period to prevent maintenance personnel from using tools that have exceeded their service life, thereby ensuring maintenance efficiency and the safety of maintenance personnel.

[0060] Embodiment 2

[0061] Figure 2 This is a schematic diagram of the structure of a power grid equipment risk status early warning device provided in the second embodiment of the present invention. Figure 2 As shown, the power grid equipment risk status early warning device includes:

[0062] The information acquisition module 21 is used to acquire device information and environmental information of power grid devices within the monitoring range;

[0063] A model building module 22, configured to build a three-dimensional virtual model according to the device information and the environmental information, wherein the three-dimensional virtual model includes the device type and device number of the power grid device, the location of the power grid device and the location number;

[0064] The warning information acquisition module 23 is used to obtain the warning information within the monitoring range in real time, and the warning information includes meteorological disaster warning information and warning areas;

[0065] A detection information determination module 24, used to determine a target detection device in combination with the warning information and the three-dimensional virtual model and to generate a patrol path for detecting the target detection device;

[0066] The device data collection module 25 is used to send the patrol path to the detection object to collect the device data of the target detection device;

[0067] The risk warning information determination module 26 is used to determine the risk warning information of the target detection device according to the device data.

[0068] Optionally, the detection information determination module 24 includes:

[0069] A target device type determination submodule is used to determine the device type of the power grid device to be inspected according to the meteorological disaster warning information to obtain the target device type;

[0070] A target detection device determination submodule, configured to use a power grid device in the three-dimensional virtual model, located in the warning area and having a device type of the target device as a target detection device;

[0071] A patrol path generation submodule is used to generate a patrol path for detecting the target detection device according to the three-dimensional virtual model and the target detection device.

[0072] Optionally, the patrol path generation submodule includes:

[0073] A marking point acquisition unit, used for marking the road section where the target detection device is located to obtain a plurality of marking points;

[0074] A patrol path generation unit is used to plan the path of the marking points based on the shortest path principle to obtain a patrol path for detecting the target detection device.

[0075] Optionally, the detection object includes a detection person, and the power grid equipment risk status early warning device further includes:

[0076] A first personnel information acquisition module, used for acquiring first personnel information of a detection person before sending the patrol path to the detection object;

[0077] The detection object determination module is used to determine the detection object with detection authority from the detection personnel based on the device information of the target detection device and the first personnel information.

[0078] Optionally, the risk warning information determination module 26 includes:

[0079] A detection parameter type determination submodule, used to determine the detection parameter type according to the device information of the target detection device;

[0080] A parameter analysis submodule, used for analyzing the device data to obtain the parameters of the detection parameter type;

[0081] A parameter judgment submodule is used to judge whether the parameter of the detection parameter type exceeds a preset parameter threshold; if so, the content of the risk warning information generation submodule is executed;

[0082] The risk warning information generation submodule is used to generate risk warning information and send the risk warning information of the target detection equipment to the maintenance object.

[0083] Optionally, the maintenance object includes a maintenance person, and the risk warning information determination module 26 further includes:

[0084] A second personnel information acquisition submodule, used for acquiring second personnel information of the maintenance personnel before issuing risk warning information of the target detection equipment to the maintenance object;

[0085] The maintenance object determination submodule is used to determine the maintenance object with maintenance authority from among the maintenance personnel based on the device information of the target detection device and the second personnel information.

[0086] Optionally, the power grid equipment risk status early warning device also includes:

[0087] A risk level determination module, used to determine the risk level of the risk warning information;

[0088] Obtain risk processing data from the generation of risk warning information to the lifting of risk warning information;

[0089] The optimization module is used to optimize the detection parameter type and parameter threshold associated with the power grid equipment according to the risk level and the risk processing data.

[0090] The power grid equipment risk status early warning device provided in the embodiment of the present invention can execute the power grid equipment risk status early warning method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0091] Embodiment 3

[0092] Figure 3 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0093] like Figure 3 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0094] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0095] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 41 executes the various methods and processes described above, such as a risk status early warning method for power grid equipment.

[0096] In some embodiments, the grid equipment risk status early warning method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the grid equipment risk status early warning method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the grid equipment risk status early warning method in any other appropriate manner (e.g., by means of firmware).

[0097] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0098] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0099] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0100] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0101] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0102] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0103] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0104] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for early warning of risk status of power grid equipment, characterized in that: include: Obtain equipment information and environmental information of power grid equipment within the monitoring range; Constructing a three-dimensional virtual model according to the equipment information and the environmental information, wherein the three-dimensional virtual model includes equipment type and equipment number of the power grid equipment, and the location and location number of the power grid equipment; Acquire warning information within the monitoring range in real time, the warning information including meteorological disaster warning information and warning areas; Determining a target detection device in combination with the warning information and the three-dimensional virtual model and generating a patrol path for detecting the target detection device; Sending the patrol path to the detection object to collect device data of the target detection device; The risk warning information of the target detection device is determined according to the device data.

2. The method for early warning of risk status of power grid equipment according to claim 1, characterized in that: The determining of the target detection device and the patrol path of the target detection device by combining the warning information, the device information and the three-dimensional virtual model includes: Determine the equipment type of the power grid equipment to be inspected according to the meteorological disaster warning information, and obtain the target equipment type; The power grid equipment in the three-dimensional virtual model, located in the warning area and having the equipment type of the target equipment type, is used as the target detection equipment; A patrol path for detecting the target detection device is generated according to the three-dimensional virtual model and the target detection device.

3. The method for early warning of risk status of power grid equipment according to claim 2, characterized in that: The step of generating a patrol path for detecting the target detection device according to the three-dimensional virtual model and the target detection device comprises: Marking the road section where the target detection device is located to obtain multiple marking points; The path planning is performed on the marking points based on the shortest path principle to obtain a patrol path for detecting the target detection device.

4. The method for early warning of risk status of power grid equipment according to claim 1, characterized in that: The detection object includes a detection person, and before sending the patrol path to the detection object, the method further includes: Obtain the first person information of the testing personnel; Based on the device information of the target detection device and the first personnel information, a detection object with detection authority is determined from the detection personnel.

5. The method for early warning of risk status of power grid equipment according to any one of claims 1 to 4, characterized in that: The step of determining the risk warning information of the target detection device according to the device data includes: Determining a detection parameter type according to device information of the target detection device; Analyzing and obtaining parameters of the detection parameter type from the device data; Determining whether a parameter of the detection parameter type exceeds a preset parameter threshold; If so, risk warning information is generated and the risk warning information of the target detection equipment is sent to the maintenance object.

6. The method for early warning of risk status of power grid equipment according to claim 5, characterized in that: The maintenance object includes a maintenance personnel, and before the risk warning information of the target detection device is issued to the maintenance object, the method further includes: Obtain the second person information of the maintenance personnel; Based on the device information of the target detection device and the second personnel information, a maintenance object having maintenance authority is determined from among the maintenance personnel.

7. The method for early warning of risk status of power grid equipment according to any one of claims 1 to 4, characterized in that: Also includes: Determining the risk level of the risk warning information; Obtain risk processing data from the generation of risk warning information to the lifting of risk warning information; The detection parameter types and parameter thresholds associated with the power grid equipment are optimized according to the risk level and the risk processing data.

8. A risk status early warning device for power grid equipment, characterized in that: include: An information acquisition module is used to obtain device information and environmental information of power grid devices within the monitoring range; A model building module, used to build a three-dimensional virtual model according to the equipment information and the environmental information, wherein the three-dimensional virtual model includes the equipment type and equipment number of the power grid equipment, the location of the power grid equipment and the location number; A warning information acquisition module is used to obtain the warning information within the monitoring range in real time, wherein the warning information includes meteorological disaster warning information and warning areas; A detection information determination module, used to determine a target detection device in combination with the warning information and the three-dimensional virtual model and to generate a patrol path for detecting the target detection device; A device data collection module, used for sending the patrol path to the detection object to collect device data of the target detection device; The risk warning information determination module is used to determine the risk warning information of the target detection device according to the device data.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the power grid equipment risk status early warning method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power grid equipment risk status early warning method according to any one of claims 1 to 7 when executed.

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