CN111668925A - Transformer inspection tour inspection device based on intelligent vision - Google Patents
Transformer inspection tour inspection device based on intelligent vision Download PDFInfo
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- CN111668925A CN111668925A CN201910163792.7A CN201910163792A CN111668925A CN 111668925 A CN111668925 A CN 111668925A CN 201910163792 A CN201910163792 A CN 201910163792A CN 111668925 A CN111668925 A CN 111668925A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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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 invention provides a transformer inspection tour inspection device based on intelligent vision, which comprises: the video acquisition module is used for acquiring video information of the transformer patrol in real time; the video processing module is electrically connected with the video acquisition module and used for processing and analyzing the video stream to obtain an abnormal image, a transformer equipment state evaluation conclusion and a fault early warning and generate a result message; and the wireless communication module is electrically connected with the video processing module and is used for uploading the abnormal image and the message data to a transformer cloud monitoring platform or the Internet of things. The transformer inspection tour inspection device improves the operation and maintenance efficiency of the transformer, reduces the operation and maintenance cost, actually improves the quality of a power grid, and realizes the intelligent operation and maintenance of the power grid.
Description
Technical Field
The invention relates to the technical field of transformers, in particular to a transformer inspection tour inspection device based on intelligent vision.
Background
In recent years, national economy of China is continuously developed at a high speed, electric power is used as the basis of development of various industries, and the length of a power transmission line and the number of transformer substations are rapidly increased.
At present, the daily inspection work of the power transformer is mainly completed manually, and the inspection standard is the power standard DL/T572 'Power Transformer operation guide rules' and DL/T573 'Power Transformer overhaul guide rules' and some enterprise standards set by each power department. The inspection work of the power equipment consumes a large amount of manpower and material resources, and the condition of missed inspection and misjudgment easily occurs in manual inspection, so that the inspection quality and efficiency are influenced.
In order to solve the problems, a series of online monitoring devices are developed at home and abroad aiming at the condition maintenance of the transformer, and the devices are based on automation and industrial control technologies, and have large detection errors and high false alarm rate. In addition, in actual use, due to the fact that the influence of site working conditions, weather, environment and the like is large, the reliability of products is not good, false alarm and false alarm are generated sometimes, manual inspection cannot be completely replaced, the detection dependence can be achieved, the auxiliary means can be used, and the significance for reducing the workload of operation and maintenance is not large.
In view of the above technical problems in the prior art, there is a need in the art for an effective monitoring device or apparatus for monitoring and detecting the state information of a transformer, the real-time shape, appearance, local shape, and whether deformation occurs in real time.
Disclosure of Invention
The present invention has been made to solve, at least in part, the technical problems occurring in the prior art.
The technical scheme adopted for solving the technical problem of the invention is as follows:
the invention provides a transformer inspection tour inspection device based on intelligent vision, which comprises:
the video acquisition module is used for acquiring video information of the transformer patrol in real time;
the video processing module is electrically connected with the video acquisition module and used for processing and analyzing the video stream to obtain an abnormal image, a transformer equipment state evaluation conclusion and a fault early warning and generate a result message;
and the wireless communication module is electrically connected with the video processing module and is used for uploading the abnormal image and the message data to a transformer cloud monitoring platform or the Internet of things.
Optionally, the video acquisition module is specifically configured to acquire online monitoring data and instrument panel data in the transformer operation inspection process, and data of internal and external forms of the equipment in real time.
Optionally, the video processing module includes:
the characteristic extraction and analysis module is used for carrying out deep mining and information processing on each frame of image in the video stream, extracting key information, obtaining abnormal images, transformer equipment state evaluation conclusion and fault early warning, and generating result messages;
and the information compression coding module is used for coding and compressing the abnormal image.
Optionally, an AI deep learning algorithm model is embedded in the feature extraction and analysis module, and the algorithm model is used for analyzing and predicting the abnormal fault state of the transformer according to the key information, and providing abnormal fault early warning analysis and troubleshooting suggestions of the transformer so as to obtain a transformer equipment state evaluation conclusion and a fault early warning, and generate a result message.
Optionally, an AI deep learning algorithm model is embedded in the feature extraction and analysis module, and the algorithm model is used for performing reinforcement learning on the potential transformer fault hazard and the transformer abnormal features according to the key information so as to extract an abnormal image in real time.
Optionally, the video processing module further includes: and the storage module is used for storing the abnormal image and the message data.
Optionally, the wireless communication module adopts an NB-IOT wireless communication module.
Optionally, the NB-IOT wireless communication module is based on a 5G communication network protocol and a 5G communication internet of things software platform.
Optionally, the patrol inspection apparatus further includes: and the power supply module is respectively and electrically connected with the video acquisition module, the video processing module and the wireless communication module.
Optionally, the power supply module comprises: the solar energy power supply component, the common power supply component and the switching module are electrically connected with the solar energy power supply component and the common power supply component; the switching module is used for automatically switching the solar power supply mode and the common power supply mode according to a preset switching logic.
Has the advantages that:
the transformer patrol inspection device based on intelligent vision disclosed by the invention solves the data transmission problem existing in the digital construction process, solves the problem of video image fault collection, is efficiently applied in the aspects of transformer fault model analysis and transformer intelligent manufacturing decision, greatly reduces the operation and maintenance cost and the manufacturing cost, and particularly greatly reduces the safety risk of manual operation and maintenance.
Drawings
Fig. 1 is a block diagram of a transformer inspection tour inspection device based on intelligent vision according to an embodiment of the present invention;
fig. 2 is a flowchart of the transformer patrol inspection apparatus based on intelligent vision according to the embodiment of the present invention.
In the figure: 100-a video acquisition module; 200-a video processing module; 201-feature extraction analysis module; 202-information compression coding module; 203-a storage module; 300-a wireless communication module; 400-a power supply module; 401-solar powered components; 402-a common power supply component; 403-switching module.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention is further described in detail below with reference to the accompanying drawings and examples.
The embodiment of the invention provides a transformer inspection tour inspection device based on intelligent vision.
As shown in fig. 1, the transformer inspection tour-inspection apparatus includes:
the video acquisition module 100 is used for acquiring video information of transformer patrol inspection in real time, and is a video acquisition terminal compatible with the standard protocol standard in the industry;
the video processing module 200 is electrically connected with the video acquisition module 100, and is configured to process and analyze a video stream to obtain an abnormal image, a transformer equipment state evaluation conclusion, and a fault early warning, and generate a result message, where the result message includes the transformer equipment state evaluation conclusion, an abnormal information event, and early warning information;
and the wireless communication module 300 is electrically connected with the video processing module 200 and is used for uploading the abnormal image and the message data to a transformer cloud monitoring platform or the internet of things.
The transformer cloud monitoring platform stores factory data of the transformer, and mining analysis is performed on the operation data and the field data by using a big data mining analysis technology, so that accuracy of equipment state evaluation is guaranteed.
In this embodiment, transformer tour inspection device has improved transformer fortune dimension efficiency, has reduced fortune dimension cost, and what be real has improved the electric wire netting quality, has realized the intelligent fortune dimension of electric wire netting.
The video acquisition module 100 is specifically configured to acquire online monitoring data, instrument panel data, and device internal and external shape data during transformer operation inspection in real time, so as to collect inspection related information such as real-time monitoring information, instrument pointer information, internal and external shape information during transformer online operation.
The video processing module 200 includes:
the characteristic extraction and analysis module 201 is used for performing deep mining and information processing on each frame of image in the video stream, extracting key information, obtaining abnormal images, transformer equipment state evaluation conclusion and fault early warning, and generating result messages;
and the information compression and encoding module 202 is used for performing encoding and compression processing on the abnormal image.
An AI (Artificial Intelligence) deep learning algorithm model is embedded in the feature extraction and analysis module 201, and the algorithm model is used for analyzing and predicting the abnormal fault state of the transformer according to the key information, providing the abnormal fault early warning analysis and troubleshooting suggestions of the transformer, so as to obtain the state evaluation conclusion and the fault early warning of the transformer equipment, and generating a result message.
The algorithm model is also used for performing reinforcement learning on the potential transformer fault hazards and the transformer abnormal features according to the key information so as to extract abnormal images (namely abnormal frames) in real time without delay processing.
As can be seen, the video processing module 200 adopts an ARM architecture, carries a simplified LINUX system, and embeds an AI deep learning algorithm model to implement high-concurrency low-power consumption real-time image processing, and therefore, the video processing module may also be referred to as an embedded hardware platform and an AI algorithm integrated video processing module.
The video processing module 200 further includes: and the storage module 203 is used for storing the abnormal image and the message data.
As can be seen, the video processing module 200 performs analysis, extraction, encoding and decoding, storage, and the like on the images in the video stream acquired by the video acquisition module 100 in real time. Wherein, an Artificial Intelligence (AI) deep learning algorithm model is adopted to analyze a state evaluation conclusion and a fault early warning of the transformer equipment, a result message is generated,
the wireless communication module 300 is an NB-IOT wireless communication module, and the wireless communication module 300 is further configured to upload the abnormal image and the message data to the next layer NB-IOT network, so as to train a stronger analysis prediction model.
The NB-IOT refers to a Narrow-Band Internet of Things (Narrow-Internet of Things) technology, and has become an important branch of the Internet of everything. The NB-IOT uses a License frequency band, can adopt three deployment modes such as in-band, guard band or independent carrier, and coexists with the existing network.
In this embodiment, the wireless communication module 300 introduces an NB (Narrow Band) technology, breaks through a non-real-time bottleneck of wireless communication, realizes information intercommunication between transformers, and realizes intercommunication between a transformer and a big data center of the internet of things.
The NB-IOT wireless communication module is based on a 5G communication network protocol and a 5G communication Internet of things software platform, can realize long-distance all-weather communication, and can receive and transmit video information and algorithm model calculation results in real time. And patrolling personnel with specific authority can check the video information of the transformer patrol in real time by using any handheld terminal which can be networked and supports 5G through the IP and NB-IOT equipment numbers.
In the embodiment, after the video acquisition module collects the inspection related information such as real-time monitoring information, instrument pointer information, internal and external form information and the like in the transformer operation inspection, the video processing module processes and analyzes video streams containing the information, obtains a transformer equipment state evaluation conclusion and fault early warning by using a big data AI algorithm, and realizes end-to-end intercommunication and end-to-end intercommunication by using a real-time NB-IOT (narrow-band Internet of things) technology, thereby laying a solid foundation for a user to timely maintain network equipment, timely inspect potential hazards of the transformer, improve operation and maintenance efficiency, reduce operation and maintenance cost and improve equipment maintenance quality.
As shown in fig. 1, the transformer patrol inspection apparatus further includes: and a power supply module 400 electrically connected to the video capture module 100, the video processing module 200 and the wireless communication module 300, respectively.
The power supply module 400 includes: a solar power supply part 401 (i.e., a solar cell module), a general power supply part 402, and a switching module 403 electrically connected to both. The switching module 406 is configured to automatically switch between the solar power supply mode and the normal power supply mode according to a switching logic preset therein, so that the power supply module 400 has the solar power supply mode and the normal power supply mode, and can automatically switch between the solar power supply mode and the normal power supply mode, thereby solving the problem of power supply in the field environment. Moreover, the solar power supply can completely meet the energy consumption of the video acquisition module, the video processing module and the NB-IOT wireless communication module, and is energy-saving and environment-friendly.
The working process of the transformer patrol inspection device is briefly described below with reference to fig. 2.
As shown in fig. 2, the work flow of the transformer patrol inspection apparatus includes the following steps S101 to S110.
S101, equipment initialization;
s102, collecting a transformer patrol video;
s103, carrying out AI algorithm calculation and analysis to obtain a state evaluation conclusion and fault early warning of the transformer equipment;
s104, judging whether an abnormal scene exists or not, if so, executing the step S105, and if not, returning to the step S102;
s105, performing compression coding on the abnormal image;
s106, realizing end-to-end transceiving intercommunication by using a narrow-band Internet of things technology;
s107, enhancing a model;
s108, routing inspection abnormal positioning and fault prediction are carried out;
s109, finishing the inspection;
and S110, ending video tracking.
In summary, the transformer inspection tour inspection device based on the intelligent vision provided by the invention is an online monitoring device based on real-time video, wherein a video acquisition module collects online monitoring data, instrument panel data, device internal and external shape data and the like in transformer operation tour inspection, a video processing module analyzes and predicts the abnormal fault state of a transformer through a big data artificial intelligence algorithm technology, an operation and maintenance worker is helped to master the actual condition of the transformer by using a real-time internet of things technology and a video processing technology, an AI algorithm is used for providing early warning analysis and troubleshooting suggestions of the abnormal fault of the transformer, the safe and reliable operation of the transformer is guaranteed, meanwhile, the mutual communication and interconnection between transformer devices are realized through the internet of things + technology, the operation and maintenance workload is reduced, and the tour inspection efficiency is improved. The invention also carries out multi-directional and interrelated multi-parameter comprehensive analysis on a large amount of working condition information of the operation of the transformer, thereby effectively improving the accuracy of the on-line monitoring of the transformer and improving the intelligent level of products.
Therefore, the transformer patrol inspection device is innovative in that: an AI algorithm is carried at a video signal acquisition end to realize tour inspection fault prediction analysis, the real-time communication and remote transmission of interconnection and intercommunication among transformers are realized by adopting an NB-IOT (narrowband Internet of things) technology, and the concepts of green energy, energy conservation and environmental protection are realized by adopting a solar cell technology.
It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.
Claims (10)
1. The utility model provides a transformer inspection tour inspection device based on intelligence vision, its characterized in that includes:
the video acquisition module is used for acquiring video information of the transformer patrol in real time;
the video processing module is electrically connected with the video acquisition module and used for processing and analyzing the video stream to obtain an abnormal image, a transformer equipment state evaluation conclusion and a fault early warning and generate a result message;
and the wireless communication module is electrically connected with the video processing module and is used for uploading the abnormal image and the message data to a transformer cloud monitoring platform or the Internet of things.
2. The transformer patrol inspection device according to claim 1, wherein the video collection module is specifically configured to collect online monitoring data, instrument panel data, and device internal and external shape data during transformer operation patrol inspection in real time.
3. The transformer patrol inspection device according to claim 1, wherein the video processing module comprises:
the characteristic extraction and analysis module is used for carrying out deep mining and information processing on each frame of image in the video stream, extracting key information, obtaining abnormal images, transformer equipment state evaluation conclusion and fault early warning, and generating result messages;
and the information compression coding module is used for coding and compressing the abnormal image.
4. The transformer patrol inspection device according to claim 3, wherein an AI deep learning algorithm model is embedded in the feature extraction and analysis module, and the algorithm model is used for analyzing and predicting the abnormal fault state of the transformer according to the key information, and providing early warning analysis and troubleshooting suggestions of the abnormal fault of the transformer so as to obtain a transformer equipment state assessment conclusion and early warning of the fault and generate a result message.
5. The transformer patrol inspection device according to claim 3, wherein an AI deep learning algorithm model is embedded in the feature extraction and analysis module, and the algorithm model is used for performing reinforcement learning on potential transformer fault hazards and transformer abnormal features according to the key information so as to extract abnormal images in real time.
6. The transformer patrol inspection device according to claim 3, wherein the video processing module further comprises: and the storage module is used for storing the abnormal image and the message data.
7. The transformer patrol inspection device according to claim 1, wherein the wireless communication module is an NB-IOT wireless communication module.
8. The transformer patrol inspection device according to claim 7, wherein the NB-IOT wireless communication module is based on a 5G communication network protocol and a 5G communication internet of things software platform.
9. The transformer patrol inspection device according to claim 1, further comprising: and the power supply module is respectively and electrically connected with the video acquisition module, the video processing module and the wireless communication module.
10. The transformer patrol inspection device according to claim 9, wherein the power supply module comprises: the solar energy power supply component, the common power supply component and the switching module are electrically connected with the solar energy power supply component and the common power supply component; the switching module is used for automatically switching the solar power supply mode and the common power supply mode according to a preset switching logic.
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| CN201910163792.7A CN111668925A (en) | 2019-03-05 | 2019-03-05 | Transformer inspection tour inspection device based on intelligent vision |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112683911A (en) * | 2020-11-17 | 2021-04-20 | 国网山东省电力公司济南供电公司 | Cable tunnel intelligence unmanned aerial vehicle inspection check out test set with high stability |
| CN114089664A (en) * | 2021-11-18 | 2022-02-25 | 贵州电网有限责任公司 | Oil-immersed transformer state monitoring system based on internet of things technology |
| CN114582037A (en) * | 2022-02-28 | 2022-06-03 | 成都商汤科技有限公司 | Inspection method and device, electronic equipment and computer readable storage medium |
| WO2023116225A1 (en) * | 2021-12-21 | 2023-06-29 | 华为技术有限公司 | Network inspection method, network device and network management device |
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