CN111092491A - Transformer substation supervision method and device and computer readable storage medium - Google Patents
Transformer substation supervision method and device and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a transformer substation supervision method and device and a computer readable storage medium. The supervision method is used for supervising the condition of a transformer substation maintenance operation site, and comprises the following steps: acquiring information to be matched of an operation site; judging whether the information to be matched is matched with a protection system trained by a deep learning algorithm; if yes, starting a protection system; if not, alarming. According to the transformer substation supervision method and the supervision device, the invalid intrusion target is filtered after the protection system is trained through the deep learning algorithm, the face recognition accuracy of the protection system is improved, and the misjudgment rate is reduced. Further, the protection system comprises a primary protection and a secondary protection; deep learning algorithm training is carried out on the primary protection; the secondary protection is provided with out-of-range alarm reminding.
Description
Technical Field
The invention relates to the technical field of intelligent monitoring of power systems, in particular to a transformer substation supervision method and device and a computer readable storage medium.
Background
The power grid system is a main artery of national energy transmission; the construction of the ultrahigh-voltage and extra-high-voltage national power grid and the realization of the optimal configuration of energy resources is taken as an important target and task of power grid construction, and has important significance for ensuring the safe and stable operation of a power supply and the power grid.
With the continuous construction and development of ultrahigh voltage and extra-high voltage networks, the number of transformer substations is increased rapidly, and higher requirements are provided for the overhaul work of the transformer substations. How to achieve the effects of safe operation, controllable cost and efficient management, the modern society provides guidance of 'actively constructing a smart energy system' and 'accelerating the construction of a smart power grid'.
In the prior art, video images or infrared electronic fences are generally used for real-time monitoring in ultrahigh voltage and extra-high voltage intelligent management and control. However, by adopting the mode, on one hand, the transformer substation operation site cannot be monitored, and on the other hand, the safety level is low and the alarm error rate is high.
Disclosure of Invention
In view of the above, it is necessary to provide an intelligent supervision method, apparatus and computer readable storage medium for extra-high voltage and ultra-high voltage substations to solve the above problems.
The invention provides a transformer substation supervision method, which is used for supervising the condition of a transformer substation maintenance operation field, and comprises the following steps:
acquiring information to be matched of an operation site;
judging whether the information to be matched is matched with a protection system trained by a deep learning algorithm;
if yes, starting a protection system;
if not, alarming.
Preferably, the protection system being trained by the deep learning algorithm comprises:
acquiring training sample data, wherein the training sample data comprises image information of workers and image information of moving objects;
and training the protection system by using the image information through a deep learning algorithm.
Preferably, the step of judging whether the information to be matched is matched with the protection system trained by the deep learning algorithm further comprises:
and displaying the overhaul site information of the operation site, wherein the overhaul site information comprises an overhaul control picture, alarm information, a construction schematic diagram or a control schematic diagram.
Preferably, the protection system comprises a primary protection system and a secondary protection system;
the first-level protection system carries out deep learning algorithm training;
the secondary protection system is provided with out-of-range alarm reminding.
The invention also provides a transformer substation supervision device, which is used for supervising the condition of the transformer substation maintenance operation site, and comprises:
an information acquisition unit configured to acquire real-time information of a work site;
a processor configured to implement instructions;
a storage unit adapted to store a plurality of instructions, the instructions adapted to be loaded and executed by the processor:
acquiring information to be matched of an operation site;
judging whether the information to be matched is matched with a protection system trained by a deep learning algorithm;
if yes, starting a protection system;
if not, alarming; and
a communication unit configured to establish a communication connection between the information acquisition unit and the processor.
Preferably, the instructions are further adapted to be loaded and executed by the processor:
acquiring training sample data, wherein the training sample data comprises image information of workers and image information of moving objects;
and training the protection system by using the image information through a deep learning algorithm.
Preferably, the supervision apparatus further comprises a display unit;
the instructions are further adapted to be loaded and executed by the processor:
and displaying the overhaul site information of the operation site, wherein the overhaul site information comprises information to be matched, an overhaul control picture, alarm information, a construction schematic diagram and a control schematic diagram.
Preferably, the protection system comprises a primary protection and a secondary protection;
deep learning algorithm training is carried out on the primary protection;
the secondary protection is provided with out-of-range alarm reminding.
Preferably, the instructions are further adapted to be loaded and executed by the processor:
and establishing a plurality of overhaul projects, distributing control resources for each overhaul project, and uploading a construction area diagram and a control schematic diagram.
The invention also provides a computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method.
Compared with the prior art, the transformer substation supervision method and the transformer substation supervision device provided by the invention have the following beneficial effects:
according to the transformer substation supervision method and the supervision device, the invalid intrusion target is filtered after the protection system is trained through the deep learning algorithm, the face recognition accuracy of the protection system is improved, and the misjudgment rate is reduced.
Further, the protection system comprises a primary protection and a secondary protection; deep learning algorithm training is carried out on the primary protection; the secondary protection is provided with out-of-range alarm reminding. Specifically, if the information to be matched is matched with a protection system trained by a deep learning algorithm, the primary protection system is started, and when a worker or a maintenance vehicle enters an operation field for maintenance, the secondary protection system is provided with an out-of-range alarm prompt to prompt the worker or the maintenance vehicle to enter a dangerous area due to a fault. Specifically, for the workers who enter the field, an electronic fence is established, and the workers can be ensured to stay in a safe area for operation by the aid of scientific and technological means and the function of automatic alarm for preventing border crossing.
Drawings
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a block schematic diagram of a substation supervision apparatus according to an embodiment of the present invention;
fig. 2 is a block schematic diagram of a substation supervision system of the substation supervision apparatus according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of a substation supervision method according to an embodiment of the present invention.
In the figure: 100. the transformer substation monitoring device comprises a transformer substation monitoring device body 110, an information acquisition unit 120, a storage unit 130, a processor 140, a display unit 150, a communication unit 200, a transformer substation monitoring system 210, a data acquisition module 220, a training module 230, a judgment module 240 and a control module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments 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.
It will be understood that when an element or component is referred to as being "connected" to another element or component, it can be directly connected to the other element or component or intervening elements or components may also be present. When an element or component is referred to as being "disposed on" another element or component, it can be directly on the other element or component or intervening elements or components may also be present.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a schematic block diagram of a substation supervision device 100 according to the present invention, where the substation supervision device 100 is used for supervising conditions of a substation maintenance operation site, and is particularly used for intelligently managing and controlling an extra-high voltage or ultra-high voltage operation site. The invention provides a substation supervision device 100, and the supervision device 100 comprises an information acquisition unit 110, a storage unit 120, a processor 130, a display unit 140 and a communication unit 150.
The information acquisition unit 110 is configured to acquire the job site to be matched. The information to be matched comprises identification information of personnel to enter the operation field and identification information of moving objects. Specifically, the identification information of the person to enter the operation site includes identification information such as face image information and identity ID of the person; the identification information of the moving object includes basic information of the moving object such as the maintenance car and the auxiliary tool, for example, the identification ID of the maintenance car and the auxiliary tool.
Further, the information acquiring unit 110 of the present invention may, but is not limited to, use a face recognition camera, where the face recognition camera may perform video monitoring in real time, and may dynamically acquire real-time information of a job site through the video monitoring.
The storage unit 120 is capable of storing associated data and a plurality of instructions. The storage unit 120 stores therein original data of workers and moving objects, such as face image information of the workers, identification IDs of the maintenance vehicle and the auxiliary tool, and the like. The storage unit 120 also prestores the border crossing condition of the workers on the overhaul job site and the data of unmatched personnel or moving objects entering the overhaul job site, records the big data of the construction process, generates an analysis report form through data mining, and provides data support for the optimization improvement and working decision of subsequent site construction.
The storage unit 120 may be a hard disk, a usb disk, a random access memory, etc.
In at least one embodiment, the storage unit 120 may be an internal storage system, such as a flash memory, a random access memory RAM, a readable memory ROM, and the like.
In at least one embodiment, the storage unit 120 includes two or more storage devices, for example, where one storage device is a memory and another storage device is a drive. Furthermore, the storage device may also be wholly or partially independent of the supervising apparatus 100.
The processor 130 may be a central processing unit, a digital signal processor, or a single chip microcomputer. The processor 130 is used for processing related data and sending a plurality of instructions, and the instructions are suitable for being loaded and executed by the processor 130.
The processor 130 is also configured to perform a comprehensive analysis in real time according to data such as personnel crossing situations and unauthenticated personnel entering situations generated in the construction job site, and generate a report for the project manager to view.
The display unit 140 is configured to display the above information to be matched. Specifically, the display unit 140 includes, but is not limited to, using a mobile phone, a PAD, a notebook computer, or a tablet computer. Further, the display unit 140 is also configured to display overhaul site information of the work site, the overhaul site information including information to be matched, an overhaul deployment and control screen, alarm information, a construction diagram or a deployment and control diagram.
The communication unit 150 is configured to establish communication connections between the information acquisition unit 110 and the processor 130, and between the processor 130 and the display unit 140. The communication unit 150 is based on a standard IP network, is convenient to network, can realize dynamic centralized monitoring only in places where the Internet can be accessed, provides the most effective monitoring means for multi-site centralized intelligent monitoring with wide monitoring node distribution and large quantity based on a TCP/IP network communication protocol, and provides possibility for unified management of network operation and maintenance by using a monitoring system based on the IP network.
Referring to fig. 2, fig. 2 is a block diagram of a substation supervision system 200 according to an embodiment of the present invention. The substation supervision system 200 is applied to the substation supervision device 100. The substation supervision system 200 includes a data collection module 210, a training module 220, a judgment module 230, and a control module 240.
The data acquisition module 210 is configured to acquire training sample data including image information of a worker and image information of a moving object. Training sample data acquired by the data acquisition module 210 is mainly used for deep learning and information matching of a subsequent protection system.
The training module 220 is configured to train the protection system through a deep learning algorithm using the image information. The protection system is obtained by training the computer vision system through the deep learning algorithm, and after the protection system is trained through the deep learning algorithm, the face recognition accuracy of the protection system is improved, and the misjudgment rate is reduced.
The determining module 230 is configured to determine whether the information to be matched matches the protection system trained by the deep learning algorithm. The control module 240 is configured to control the activation or alarming of the protection system.
Specifically, if the information to be matched is matched with the protection system trained by the deep learning algorithm, the control module 240 controls the protection system to be started, and the worker or the moving object enters the operation site. If the information to be matched is not matched with the protection system trained by the deep learning algorithm, the control module 240 controls the protection system to send an alarm prompt, which indicates that unqualified workers or maintenance vehicles may enter the operation site.
Further, in a preferred embodiment, the protection system includes a primary protection and a secondary protection; deep learning algorithm training is carried out on the primary protection; the secondary protection is provided with out-of-range alarm reminding. Specifically, if the information to be matched is matched with a protection system trained by a deep learning algorithm, the primary protection system is started, and when a worker or a moving object (a maintenance vehicle or a maintenance tool) enters an operation field for maintenance, the secondary protection system is provided with an out-of-range alarm prompt to prompt the worker or the maintenance vehicle to enter a dangerous area due to a fault. Specifically, for the workers who enter the field, an electronic fence is established, and the workers can be ensured to stay in a safe area for operation by the aid of scientific and technological means and the function of automatic alarm for preventing border crossing.
In some preferred embodiments, the control module 240 is further configured to control the establishment of a plurality of service profiles, the staff have preset a plurality of service projects in advance, allocate the deployment and control resources for each service project and upload the construction area map and the deployment and control schematic map
In other preferred embodiments, to achieve flexibility of deployment of the substation supervision device 100, a mobile power supply device, specifically, an external power supply and a photovoltaic panel, needs to be configured for the information acquisition unit 110, so as to ensure that the substation supervision device 100 can normally operate for 24 hours in the absence of power (where the absence of power refers to that the photovoltaic panel cannot normally operate in some weather or environment). And configuring the most appropriate external power supply for the hardware resource through the calculation of the energy of the storage battery and the power of the hardware equipment. The mobile power supply unit may be configured with a mobile power supply capability of 720W/H.
Referring to fig. 3, the present invention further provides a transformer substation supervision method, and fig. 3 is a flow diagram of the transformer substation supervision method, which specifically includes the following steps:
and S301, collecting information to be matched of the operation site.
Specifically, the information acquisition unit 110 is configured to acquire information to be matched of a work site. The information to be matched comprises identification information of personnel to enter the operation field and identification information of moving objects. Specifically, the identification information of the person to enter the operation site includes identification information such as face image information and identity ID of the person; the identification information of the moving object includes moving objects such as a maintenance vehicle and an auxiliary tool.
Step S302, judging whether the information to be matched is matched with the protection system trained by the deep learning algorithm.
Specifically, the determining module 230 is configured to determine whether the information to be matched matches with the protection system trained by the deep learning algorithm.
If yes, go to step S303 to start the protection system. If the information to be matched is matched with the protection system trained by the deep learning algorithm, the control module 240 controls the protection system to be started, and a worker or a maintenance vehicle enters the operation field.
If not, executing step S304 to alarm. If the information to be matched is not matched with the protection system trained by the deep learning algorithm, the control module 240 controls the protection system to send an alarm prompt, which indicates that unqualified workers or maintenance vehicles may enter the operation site.
The following steps are also included before step S301:
step S3011, training sample data is collected.
Specifically, the data acquisition module 210 is configured to acquire training sample data including image information of a worker and image information of a moving object. Training sample data acquired by the data acquisition module 210 is mainly used for deep learning and information matching of a subsequent protection system.
And step S3012, training the protection system by using the image information through a deep learning algorithm.
Specifically, the training module 220 is configured to train the protection system through a deep learning algorithm using the image information. The protection system is obtained by training the computer vision system, and after the protection system is trained by the deep learning algorithm, invalid intrusion targets are filtered, so that the face recognition accuracy of the protection system is improved, and the misjudgment rate is reduced.
In a preferred embodiment, the protection system includes a primary protection and a secondary protection; deep learning algorithm training is carried out on the primary protection; the secondary protection is provided with out-of-range alarm reminding. Specifically, if the information to be matched is matched with a protection system trained by a deep learning algorithm, the primary protection system is started, and when a worker or a maintenance vehicle enters an operation field for maintenance, the secondary protection system is provided with out-of-range alarm reminding to remind the worker or a moving object of entering a dangerous area due to a fault. Specifically, for the workers who enter the field, an electronic fence is established, and the workers can be ensured to stay in a safe area for operation by the aid of scientific and technological means and the function of automatic alarm for preventing border crossing.
Step S305 is further included after step S302, and service site information of the work site is displayed.
Specifically, the display unit 140 is configured to display overhaul site information of the work site, the overhaul site information including information to be matched, an overhaul deployment screen, alarm information, a construction diagram, or a deployment diagram.
The present invention also provides a computer readable storage medium, which stores a computer program that, when executed by the processor 130, may implement the steps of the above-described method embodiments, such as the steps S301 to S305 shown in fig. 3.
According to the transformer substation supervision method and the supervision device 100, after the protection system is trained through the deep learning algorithm, the invalid intrusion target is filtered, the face recognition accuracy of the protection system is improved, and the misjudgment rate is reduced.
Further, the protection system comprises a primary protection and a secondary protection; deep learning algorithm training is carried out on the primary protection; the secondary protection is provided with out-of-range alarm reminding. Specifically, if the information to be matched is matched with a protection system trained by a deep learning algorithm, the primary protection system is started, and when a worker or a maintenance vehicle enters an operation field for maintenance, the secondary protection system is provided with an out-of-range alarm prompt to prompt the worker or the maintenance vehicle to enter a dangerous area due to a fault. Specifically, for the workers who enter the field, an electronic fence is established, and the workers can be ensured to stay in a safe area for operation by the aid of scientific and technological means and the function of automatic alarm for preventing border crossing.
It will be understood by those skilled in the art that all or part of the processes of the above embodiments may be implemented by hardware that is instructed to be performed by a computer program, and the program may be stored in a computer-readable storage medium, and when executed, may include processes of the embodiments of the methods described above.
In addition, functional units in the embodiments of the present invention may be integrated into the same processor, or each unit may exist alone physically, or two or more units are integrated into the same unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes a plurality of instructions for enabling an electronic device (which may be a handheld electronic device, such as a smart phone, a laptop computer, a Personal Digital Assistant (PDA), an intelligent wearable device, or a desktop electronic device, such as a desktop computer, an intelligent television, or the like) or a Processor (Processor) to perform some steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), an optical disk, or other various media storing program codes.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Several units or systems recited in the system claims may also be implemented by one and the same unit or system in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A transformer substation supervision method is used for supervising the condition of a transformer substation maintenance operation site, and is characterized in that: the supervision method comprises the following steps:
acquiring information to be matched of an operation site;
judging whether the information to be matched is matched with a protection system trained by a deep learning algorithm;
if yes, starting the protection system;
if not, alarming.
2. The substation supervision method according to claim 1, characterized in that: the protection system is trained by a deep learning algorithm and comprises the following steps:
acquiring training sample data, wherein the training sample data comprises image information of workers and image information of moving objects;
and training the protection system by using the image information through a deep learning algorithm.
3. The substation supervision method according to claim 2, characterized in that: after judging whether the information to be matched is matched with the protection system trained by the deep learning algorithm, the method further comprises the following steps:
and displaying the overhaul site information of the operation site, wherein the overhaul site information comprises an overhaul control picture, alarm information, a construction schematic diagram or a control schematic diagram.
4. The substation supervision method according to claim 1, characterized in that:
the protection system comprises a primary protection system and a secondary protection system;
the primary protection system performs the deep learning algorithm training;
and the secondary protection system is provided with out-of-range alarm reminding.
5. The utility model provides a transformer substation supervision device for supervise the transformer substation overhauls the operation site conditions, its characterized in that: the supervision device comprises:
an information acquisition unit configured to acquire real-time information of a work site;
a processor configured to implement instructions;
a storage unit adapted to store a plurality of instructions, the instructions adapted to be loaded and executed by the processor:
acquiring information to be matched of an operation site;
judging whether the information to be matched is matched with a protection system trained by a deep learning algorithm;
if yes, starting the protection system;
if not, alarming; and
a communication unit configured to establish a communication connection between the information acquisition unit and the processor.
6. The substation supervision device of claim 5, wherein: the instructions are further adapted to be loaded and executed by the processor:
acquiring training sample data, wherein the training sample data comprises image information of workers and image information of moving objects;
and training the protection system by using the image information through a deep learning algorithm.
7. The substation supervision device of claim 6, wherein: the supervision device further comprises a display unit;
the instructions are further adapted to be loaded and executed by the processor:
and displaying the overhaul site information of the operation site, wherein the overhaul site information comprises information to be matched, an overhaul control picture, alarm information, a construction schematic diagram and a control schematic diagram.
8. The substation supervision device of claim 6, wherein: the protection system comprises a primary protection and a secondary protection;
the first-level protection carries out deep learning algorithm training;
and the secondary protection is provided with out-of-range alarm reminding.
9. The substation supervision device of claim 6, wherein:
the instructions are further adapted to be loaded and executed by the processor:
and establishing a plurality of overhaul projects, distributing control resources for each overhaul project, and uploading a construction area diagram and a control schematic diagram.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
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| CN111640282A (en) * | 2020-05-29 | 2020-09-08 | 北京潞电电气设备有限公司 | Method, system and device for monitoring safety distance of personnel in power distribution room |
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| KR100791781B1 (en) * | 2007-06-14 | 2008-01-04 | 김미현 | Remote control system for Electronic watt hour meter |
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