CN214177452U - Power plant monitoring system - Google Patents
Power plant monitoring system Download PDFInfo
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- CN214177452U CN214177452U CN202120260331.4U CN202120260331U CN214177452U CN 214177452 U CN214177452 U CN 214177452U CN 202120260331 U CN202120260331 U CN 202120260331U CN 214177452 U CN214177452 U CN 214177452U
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
The application relates to a power plant monitoring system. The power plant monitoring system comprises: the system comprises an industrial television system and a monitoring terminal, wherein the industrial television system comprises a plurality of image acquisition devices arranged in each production area of a power plant; the monitoring terminal is used for displaying image signals of each production area, and the power plant monitoring system further comprises an AI server and a cloud platform server. Based on the original industrial television system and the monitoring terminal in the power plant, the AI server for image recognition is additionally arranged, image recognition is carried out on image signals collected by an image collecting device of the industrial television system, recognition results of fault states of all production areas of the power plant are obtained, and the recognition results are sent to the monitoring terminal through the application cloud server. The system has low construction cost and high cost performance. In addition, the AI server can carry out AI intelligent recognition on the image signal, thereby realizing the rapid and accurate recognition of the abnormal condition of the equipment in the production area and reducing the occurrence of misjudgment and missed judgment.
Description
Technical Field
The utility model relates to a power plant's production facility safety monitoring field, more specifically relates to a power plant monitoring system.
Background
In recent years, the demand of China on energy and power is greatly increased, attention is paid to power supply and power grid construction, a power plant is taken as an important power production enterprise in China, and safe production is an important means for ensuring long-term operation of a power grid and healthy development of the power enterprise. In the production process of a power plant, the field environment has the characteristics of large volume of power equipment, more electrical equipment, more high-temperature and high-voltage equipment, inflammability, explosiveness, more toxic substances and the like, and the abnormal conditions often occur, such as power equipment failure, pipeline damage, part falling, oil leakage, water leakage, gas leakage and the like, so that stable operation of various equipment in the production area of the power plant is ensured or fault diagnosis can be timely discovered, and the equipment needs to be effectively monitored.
The traditional video monitoring system has the problems of low fault judgment accuracy and easy generation of misjudgment and missed judgment.
SUMMERY OF THE UTILITY MODEL
In view of the above, it is necessary to provide a power plant monitoring system for solving the above technical problems.
The embodiment of the utility model provides a power plant monitoring system, including industrial television system and monitor terminal, the industrial television system includes a plurality of image acquisition devices, and the image acquisition device sets up in each production area of power plant for gather each production area's image signal; the monitor terminal is connected with the industrial television system through the local area network in the plant and is used for displaying the image signals of each production area, and the power plant monitor system is characterized by further comprising: an AI server and a cloud platform server; the AI server is connected with each image acquisition device through an in-plant local area network and is used for carrying out AI image identification on the image signals through an AI image signal identification algorithm model; the cloud platform server comprises a control cloud server and an application cloud server, the control cloud server is connected with the AI server through an in-plant local area network and is used for sending the AI image signal recognition algorithm model to the AI server; the application cloud server is connected with the AI server through the in-plant local area network and is used for acquiring and storing the identification result of the AI server on the image signal; the application cloud server is further connected with the monitoring terminal through a public network and used for sending the identification result to the monitoring terminal.
In one embodiment, the image acquisition device comprises a plurality of image acquisition units, and the power plant monitoring system further comprises a convergence switch arranged in each production area of the power plant; each image acquisition unit is connected to the convergence switch and is accessed to the local area network in the factory through the convergence switch.
In one embodiment, the application cloud platform server is further configured to connect to a production service system of the power plant, and obtain a device state log stored by the production service system.
In one embodiment, the power plant monitoring system further comprises an application server for data forwarding, wherein the application cloud platform server is connected with the AI server through the application server and is used for receiving the identification result forwarded by the application server; the application cloud platform server is also connected with the production service system through the application server and is used for receiving the equipment state log forwarded by the application server.
In one embodiment, the AI server and the application server are deployed in a machine room of the power plant.
In one embodiment, the monitoring terminals comprise an in-plant monitoring terminal and an out-plant monitoring terminal; the in-plant monitoring terminal is connected with the industrial television system through an in-plant local area network and is used for displaying image signals of all production areas; the in-plant monitoring terminal is also connected with the application cloud server through a public network and used for receiving the identification result; and the off-plant monitoring terminal is connected with the application cloud server through the public network and is used for receiving the identification result.
In one embodiment, the monitoring terminal comprises a computer device and a mobile terminal.
In one embodiment, the AI server is a cluster of servers.
In one embodiment, the image acquisition unit comprises a high definition camera.
In one embodiment, aggregation switches include hundreds of megabits switches and gigabit switches.
The embodiment of the utility model provides an add the AI server that is used for image recognition based on original industry television system and monitor terminal in the power plant, carry out image recognition to the image signal that the image acquisition device of industry television system gathered, obtain the identification result of the fault state of each production area territory of relevant power plant to send monitor terminal with the identification result through using cloud ware. The power plant monitoring system is built by combining the original industrial television system, the system construction cost is reduced, and the power plant monitoring system has the advantage of higher cost performance. In addition, the AI server can carry out AI intelligent recognition on the image signal, thereby realizing the rapid and accurate recognition of the abnormal condition of the equipment in the production area and reducing the occurrence of misjudgment and missed judgment.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments or the conventional technologies of the present application, the drawings used in the descriptions of the embodiments or the conventional technologies will be briefly introduced below, it is obvious that the drawings in the following descriptions are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a power plant monitoring system according to one embodiment;
FIG. 2 is a schematic diagram of the connection of an image acquisition unit to an in-plant LAN according to one embodiment;
FIG. 3 is a schematic diagram of a power plant monitoring system according to another embodiment;
FIG. 4 is a diagram of the primary data paths of the plant monitoring system in one embodiment.
Detailed Description
To facilitate an understanding of the present application, the present application will now be described more fully with reference to the accompanying drawings. Embodiments of the present application are set forth in the accompanying drawings. This application may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
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 application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
It will be understood that when an element is referred to as being "connected" to another element, it can be directly connected to the other element or be connected to the other element through intervening elements. Further, "connection" in the following embodiments is understood to mean "electrical connection", "communication connection", or the like, if there is a transfer of electrical signals or data between the connected objects.
As used herein, the singular forms "a", "an" and "the" may include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises/comprising," "includes" or "including," etc., specify the presence of stated features, integers, steps, operations, components, parts, or combinations thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, components, parts, or combinations thereof. Also, as used in this specification, the term "and/or" includes any and all combinations of the associated listed items.
As described in the background art, the conventional video monitoring system in the prior art has a problem of easily generating erroneous judgment and missed judgment, and the applicant researches and discovers that the problem occurs because the conventional video monitoring system judges a monitoring picture by manpower and generates a large amount of image information in a video monitoring process, so that a large amount of manpower is consumed and erroneous judgment and missed judgment are easily generated due to fatigue, and therefore, it is necessary to design a monitoring system for intelligently sensing the abnormal state of production equipment to monitor the safety of a production process of a power plant, reduce manpower and material resources, improve the fault early warning capability and fault judgment efficiency, and shorten the fault processing time.
For the above reasons, please refer to fig. 1, an embodiment of the present invention provides a power plant monitoring system 10, which includes an industrial television system 100, a monitoring terminal 300, an AI server 500, and a cloud platform server 700. The industrial television system 100 includes a plurality of image capturing devices 110, and the image capturing devices 110 are disposed in each production area of the power plant, such as a main transformer room, a bus duct, a main building, a GIS room, a boiler area, and the like of the power plant, and are configured to capture image signals of each production area. Industrial television system 100 is currently widely used in power plants, and workers do not need to observe production in a production area, thereby avoiding harm to the workers due to severe production environments such as toxic, harmful, and high temperature. In addition, the image signal acquired by the image acquisition device 110 directly transmits the image signal, which occupies a large network bandwidth and a large memory, so the industrial television system 100 can also be used for streaming media processing and forwarding of the image signal. Specifically, the video may be compressed by providing a video processing server or the like in the industrial television system 100 and then transmitted based on a video transmission protocol, such as an RTP transmission protocol. Common video compression standards include H.265, H.264, or MPEG-4. Further, the industrial television system 100 may further be provided with a storage server for storing the acquired image signals, so that the staff member can call the image signals at the historical time when necessary.
The monitoring terminal 300 is connected to the industrial television system 100 through an intra-plant lan, and is configured to receive image signals of each production area. Referring to fig. 4, the industrial tv system 100 collects and transmits image signals of each production area of the power plant to the monitoring terminal 300, so that the power plant staff can obtain the image signals of the production areas distributed at each location from the monitoring terminal 300 to know the operation status of each production area. It is understood that the in-plant local area network may interconnect various devices within the power plant through network connectors, network cables, etc., so that the devices within the power plant may perform data interaction, resource sharing, etc.
The AI (artificial intelligence) server 500 is connected to each image acquisition device 110 through an intra-plant lan, and is configured to perform AI image recognition on the image signal through an AI image signal recognition algorithm model. The AI server 500 is a server having a processing module, which is formed by combining a CPU with processors such as a GPU (graphics processing unit) and a TPU (temporal processing unit), as a core computing unit. The AI server 500 has a great performance advantage in performing AI image recognition compared to a conventional server. Meanwhile, AI image recognition is developed rapidly at present, and a mature convolutional neural network model is adopted as an AI image signal recognition algorithm model to perform AI image recognition on image signals of each production area of the power plant so as to obtain the operation condition of each production area. In particular, convolutional layers in a convolutional neural network model may perform feature extraction on the image signal. And compressing the image signal subjected to the feature extraction processing through a pooling layer in the convolutional neural network model, reducing parameters to be analyzed and improving the operation speed. And finally, the full-connection layer can comprehensively analyze the results obtained by the Pohua layer to obtain the predicted values of all the recognition results, and then the maximum predicted value is selected as the recognition result to be output.
Cloud platform server 700 includes a control cloud server 710 and an application cloud server 730. The control cloud server 710 is connected to the AI server 500 through an in-plant lan, and is configured to send the AI image signal recognition algorithm model to the AI server 500. The cloud server 710 is controlled to distribute the recognition algorithm model for the AI server 500, so that development and upgrading of the system are facilitated, and expansibility of the system is improved. Further, to improve system security, the control cloud server 710 may also be configured to perform key authentication on the AI server 500. The control cloud server 710 distributes the algorithm model to the AI server 500 only after the key authentication of the AI server 500 passes. In addition, the control cloud server 710 is also configured to acquire an operation state of the AI server 500. Referring to fig. 4, data interaction between the control cloud server 710 and the application cloud server 730 is performed in a wireless communication manner. When the AI server 500 breaks down, the control cloud server 710 can quickly learn and send a corresponding AI server 500 fault signal to the application cloud server 730, the monitoring terminal 300 can receive the AI server 500 fault signal through the application cloud server 730, and a power plant worker can timely maintain the AI server 500 according to the fault signal.
The application cloud server 730 is connected to the AI server 500 through the intra-plant local area network, and is configured to acquire and store an identification result of the AI server 500 on the image signal. The identification result includes the type, location, and the like of the failure of the failed device in each production area, and the type, severity, and the like of the abnormal situation of the production area. Uploading the recognition result to the application cloud server 730 can save memory for the AI server 500 and reduce the load of the AI server 500. Further, the application cloud server 730 may be further connected to the industrial television system 100, and is configured to receive and store the image signal acquired by the industrial television system 100. It can be understood that the application cloud server 730 can be flexibly and flexibly configured according to the requirements of the power plant on performance, memory and the like. The image signals are stored in the application cloud server 730, and compared with a special storage server, the subsequent upgrading is more convenient, and the cost is lower. In addition, the monitoring terminal 300 may be connected to the application cloud server 730 through a public network to obtain the identification result. The monitoring terminal 300 can obtain the identification result through simple operation, and the cost of system maintenance is reduced.
The embodiment of the utility model provides an add AI server 500 that is used for image recognition based on original industry television system 100 and monitor terminal 300 in the power plant, carry out image recognition to the image signal that image acquisition device 110 of industry television system 100 gathered, obtain the identification result of the fault state of each production area territory of relevant power plant to send monitor terminal 300 with the identification result through using cloud server 730. The power plant monitoring system is built by combining the original industrial television system 100, so that the system construction cost is reduced, and the power plant monitoring system has a higher cost performance advantage. In addition, the AI server 500 can perform AI intelligent recognition on the image signal, so as to realize rapid and accurate recognition of abnormal conditions of equipment in the production area and reduce the occurrence of misjudgment and missed judgment.
In one embodiment, referring to fig. 2, the image capturing device 110 includes a plurality of image capturing units 111, and the power plant monitoring system 10 further includes a convergence switch 200 disposed in each production area of the power plant; each image capturing unit 111 is connected to the aggregation switch 200, and accesses the intra-plant lan through the aggregation switch 200. The aggregation switch 200 receives data of all the image capturing units 111 disposed in each production area, and the aggregation switch 200 uniformly exports the data and transmits the data to the industrial television system 100 and the AI server 500 through the in-plant local area network. Further, the image capturing apparatus 110 may further include an acquisition auxiliary device, which is connected to the image capturing unit 111, such as a controllable pan/tilt head, for adjusting an angle of the image capturing unit 111. When the monitoring range of the image acquisition unit 111 is insufficient, the angle of the image acquisition unit 111 is adjusted through the controllable holder to cover different positions of the production area, so that large-range scanning monitoring is realized. In addition, the controllable cloud deck is connected with the monitoring terminal 300, and the monitoring terminal 300 is used for sending a control command for adjusting the angle of the image acquisition unit 111 to the controllable cloud deck, so that power plant workers can conveniently monitor different positions of a production area.
In one embodiment, the image acquisition unit 111 comprises a high definition camera. The high-definition camera is adopted to obtain a clearer image signal, so that the AI server 500 can perform AI image recognition, and the precision of a recognition result is improved. Further, the high-definition camera may be a high-definition industrial camera, such as a full-format CCD industrial camera. The high-definition industrial camera can obtain image signals with high definition and resolution, can adapt to complex environments in a power plant, and can stably work for a long time.
In one embodiment, aggregation switch 200 includes a hundred megabyte switch and a gigabit switch. When the number of image capturing units 111 provided in each production area exceeds 100, a gigabit switch is preferably used to prevent data loss due to insufficient bandwidth.
In an embodiment, referring to fig. 3, the application cloud platform server 700 is further configured to connect to the production service system 400 of the power plant, and obtain the device status log stored by the production service system 400. It is understood that the production service system 400 is a system used by a power plant to manage and adjust the operation status of a production facility, and the production service system 400 includes a status acquisition device connected to the production facility, and the status acquisition device can acquire real-time actions, status information, and the like of the facility. The production service system 400 further includes a log server, and the log server is configured to obtain real-time actions, status information, and the like of the devices, and generate and store device status logs of each device based on the real-time actions, status information, and the like. After the application cloud platform server 700 obtains the device status log from the production service system 400, the monitoring terminal 300 is connected to the application cloud platform server 700 through the public network, and the condition of any one device can be directly obtained from the application cloud platform server 700. In addition, when the AI server 500 identifies that a certain device is abnormal, the application cloud platform server 700 may further perform analysis by combining the status log and the identification result of the device, so as to further confirm whether the device is abnormal, thereby improving the system monitoring accuracy.
In one embodiment, please continue to refer to fig. 3, the power plant monitoring system 10 further includes an application server 600 for data forwarding, the application cloud platform server 700 is connected to the AI server 500 through the application server 600 for receiving the identification result forwarded by the application server 600, and the application cloud platform server 700 is further connected to the production service system 400 through the application server 600 for receiving the device status log forwarded by the application server 600. Referring to fig. 4, the application server 600 receives and forwards data of each access system or server to the application cloud server 730, thereby saving network bandwidth and reducing network and server bottlenecks.
In one embodiment, the AI server 500 and the application server 600 are deployed in a machine room of a power plant.
In one embodiment, the AI server 500 is a server cluster. In some application scenarios with a high requirement on the AI image recognition speed, a server cluster formed by a plurality of AI servers 500 can be used to perform AI image recognition together, so as to improve the computing capability and accelerate the AI image recognition speed.
In one embodiment, the monitoring terminals 300 include an in-plant monitoring terminal 300 and an out-of-plant monitoring terminal 300. The in-plant monitoring terminal 300 is connected to the industrial television system 100 through an in-plant lan, and is configured to receive real-time image signals of each production area. The off-plant monitoring terminal 300 and the in-plant monitoring terminal 300 are connected to the application cloud server 730 through a public network, respectively, and are configured to receive the AI image recognition result obtained by the AI server 500. The in-plant monitoring terminal 300 is disposed in a power plant, and the out-plant monitoring terminal 300 is disposed in a power grid company. Referring to fig. 4, both the in-plant monitoring terminal 300 and the off-plant monitoring terminal 300 may be connected to the application cloud platform server 700 through a public network to perform data interaction with the application cloud platform server 700. Based on this, the in-plant monitoring terminal 300 and the off-plant monitoring terminal 300 may also obtain data such as status logs of the devices through the application cloud platform server 700, so that the work such as service analysis and service management may be performed on the power plant remotely. The in-plant monitoring terminal 300 can also directly receive real-time image signals of each production area to directly observe the conditions in the power plant. This distinguishes the authority of the monitoring terminals 300 inside and outside the power plant to acquire the power plant data, so as to improve the system security.
In one embodiment, the monitoring terminal 300 includes a computer device as well as a mobile terminal.
In the description herein, references to the description of "some embodiments," "other embodiments," "desired embodiments," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, a schematic description of the above terminology may not necessarily refer to the same embodiment or example.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the utility model. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A power plant monitoring system comprises an industrial television system and a monitoring terminal, wherein the industrial television system comprises a plurality of image acquisition devices, and the image acquisition devices are arranged in production areas of a power plant and are used for acquiring image signals of the production areas; the monitor terminal is connected with the industrial television system through a local area network in a plant and is used for displaying the image signals of the production areas, and the power plant monitor system is characterized by further comprising: an AI server and a cloud platform server;
the AI server is connected with each image acquisition device through the in-plant local area network and is used for carrying out AI image identification on the image signals through an AI image signal identification algorithm model;
the cloud platform server comprises a control cloud server and an application cloud server, and the control cloud server is connected with the AI server through the in-plant local area network and is used for sending the AI image signal recognition algorithm model to the AI server; the application cloud server is connected with the AI server through the in-plant local area network and is used for acquiring and storing the identification result of the AI server on the image signal; the application cloud server is further connected with the monitoring terminal through a public network and used for sending the identification result to the monitoring terminal.
2. A power plant monitoring system according to claim 1, wherein the image capturing device comprises a plurality of image capturing units, the power plant monitoring system further comprising a convergence switch disposed in each production area of the power plant;
and each image acquisition unit is connected to the convergence switch and is accessed to the in-plant local area network through the convergence switch.
3. The power plant monitoring system of claim 1, wherein the application cloud platform server is further configured to connect to a production service system of a power plant and obtain a device status log stored by the production service system.
4. A power plant monitoring system according to claim 3, further comprising an application server for data forwarding, the application cloud platform server being connected to the AI server via the application server for receiving the identification result forwarded by the application server; the application cloud platform server is also connected with the production service system through the application server and is used for receiving the equipment state log forwarded by the application server.
5. The power plant monitoring system of claim 4, wherein the AI server and the application server are deployed within a machine room of the power plant.
6. A power plant monitoring system according to claim 1, wherein the monitoring terminals include an in-plant monitoring terminal and an out-of-plant monitoring terminal;
the in-plant monitoring terminal is connected with the industrial television system through an in-plant local area network and is used for receiving the image signals of the production areas; the in-plant monitoring terminal is also connected with the application cloud server through a public network and used for receiving the identification result;
and the off-site monitoring terminal is connected with the application cloud server through a public network and is used for receiving the identification result.
7. A power plant monitoring system according to claim 1, characterized in that the monitoring terminal comprises a computer device or a mobile terminal.
8. The power plant monitoring system of claim 1, wherein the AI server is a server cluster.
9. The power plant monitoring system of claim 2, wherein the image acquisition unit comprises a high definition camera.
10. The power plant monitoring system of claim 2, wherein the aggregation switch comprises a hundred megabyte switch or a gigabit switch.
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| CN202120260331.4U CN214177452U (en) | 2021-01-29 | 2021-01-29 | Power plant monitoring system |
| PCT/CN2021/079288 WO2022160414A1 (en) | 2021-01-29 | 2021-03-05 | System for monitoring power plant |
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| CN202120260331.4U CN214177452U (en) | 2021-01-29 | 2021-01-29 | Power plant monitoring system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114758296A (en) * | 2022-04-19 | 2022-07-15 | 国网湖北省电力有限公司黄石供电公司 | Power grid equipment remote monitoring method and system based on VR technology |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US8315719B2 (en) * | 2009-12-30 | 2012-11-20 | Eduardo Pedrosa Santos | Decentralized system and architecture for remote real time monitoring of power transformers, reactors, circuit breakers, instrument transformers, disconnect switches and similar high voltage equipment for power plants and electric power substations |
| CN211293956U (en) * | 2019-11-14 | 2020-08-18 | 北京国电通网络技术有限公司 | AI-based identification and alarm system for abnormal agent on construction site |
| CN211406109U (en) * | 2020-04-08 | 2020-09-01 | 深圳江行联加智能科技有限公司 | Portable video mobile monitoring system with AI recognition function |
| CN112188164A (en) * | 2020-09-29 | 2021-01-05 | 爱动超越人工智能科技（北京）有限责任公司 | AI vision-based violation real-time monitoring system and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114758296A (en) * | 2022-04-19 | 2022-07-15 | 国网湖北省电力有限公司黄石供电公司 | Power grid equipment remote monitoring method and system based on VR technology |
| CN114758296B (en) * | 2022-04-19 | 2023-02-24 | 国网湖北省电力有限公司黄石供电公司 | Power grid equipment remote monitoring method and system based on VR technology |
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