CN114022972A - Intelligent image acquisition system and method for unmanned aerial vehicle - Google Patents
Intelligent image acquisition system and method for unmanned aerial vehicle Download PDFInfo
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- CN114022972A CN114022972A CN202111647259.1A CN202111647259A CN114022972A CN 114022972 A CN114022972 A CN 114022972A CN 202111647259 A CN202111647259 A CN 202111647259A CN 114022972 A CN114022972 A CN 114022972A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/20—Checking timed patrols, e.g. of watchman
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/003—Flight plan management
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/003—Flight plan management
- G08G5/0039—Modification of a flight plan
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0047—Navigation or guidance aids for a single aircraft
- G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0073—Surveillance aids
- G08G5/0082—Surveillance aids for monitoring traffic from a ground station
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0095—Aspects of air-traffic control not provided for in the other subgroups of this main group
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/06—Traffic control systems for aircraft, e.g. air-traffic control [ATC] for control when on the ground
- G08G5/065—Navigation or guidance aids, e.g. for taxiing or rolling
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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 discloses an intelligent image acquisition system and method for an unmanned aerial vehicle, wherein the system comprises a management information large area, an internet large area and the internet; the management information area comprises unmanned aerial vehicle application, a technical middle station, a data middle station and a service middle station, wherein the data middle station comprises an unstructured platform; the Internet large area comprises unmanned aerial vehicle application, a technical middle platform and an unstructured platform; the management information large area and the internet large area realize information penetration through a logic type information network safety isolation device, and the internet large area and the internet realize information penetration through a firewall. The invention solves the technical problems of repeated task dispatching, data line down-flow, insufficient safety control and low defect identification efficiency in the prior art.
Description
Technical Field
The invention belongs to the technical field of image acquisition, and particularly relates to an intelligent image acquisition system and method for an unmanned aerial vehicle.
Background
The current unmanned aerial vehicle application technology is mature day by day, unmanned aerial vehicle autonomous flight under various application scenes has been realized, flight process state real time monitoring, big data analysis technique, cloud computing technique, artificial intelligence and machine learning technique have had qualitative leap, can ensure that all kinds of graphic images and structured data that unmanned aerial vehicle obtained etc. can carry out deep intelligent analysis according to the needs of application scene, and under this prerequisite, unmanned aerial vehicle intelligence patrols and examines the technique and show wide application prospect in transmission line patrols and examines.
As shown in fig. 1, the current unmanned aerial vehicle inspection process includes the following steps:
1. applying in a space domain: applying for a flight airspace of the unmanned aerial vehicle to an air traffic control department in a offline mode;
2. planning: recording an inspection annual plan, a monthly plan and a weekly plan in an unmanned aerial vehicle inspection control platform;
3. and (3) task formulation: an unmanned aerial vehicle inspection task is formulated by combining an inspection plan;
4. task dispatching: importing the task/track file into a flight terminal in a offline mode;
5. and (3) inspection operation: performing inspection operation, safety monitoring and flight terminal archiving offline;
6. safety monitoring: information such as the position of the unmanned aerial vehicle cannot be acquired online, and safety control of field operation is lacked;
7. data returning: uploading the inspection data to the unmanned aerial vehicle autonomous inspection application in an offline mode;
8. and (3) data analysis: generating defects and storing the defects in an unmanned aerial vehicle system after the inspection task picture is subjected to intelligent analysis and artificial secondary rechecking;
9. defect circulation: and manually introducing the generated defects into the PMS to trigger a subsequent flow.
But unmanned aerial vehicle patrols and examines still to have the task at present and repeat the dispatch, the data line circulation down, the safety control is not enough, defect identification efficiency is not high scheduling problem, mainly includes: the position and state information of the unmanned aerial vehicle cannot be acquired in real time, the comprehensive control capability of an applicable area is deficient, the risk of mistakenly entering an unsuitable area exists, and the safety control capability of field operation is deficient; the unmanned aerial vehicle autonomous inspection collected images cannot be automatically identified and are transmitted back to the enterprise intranet in real time, and are not effectively fused with the existing enterprise intranet platform; defect data generated by inspection cannot be communicated and transferred to a PMS (permanent magnet synchronous motor) system, so that defects cannot be maintained at the same source; the internal and external networks lack a safe, convenient and stable interaction channel, data such as routing inspection tasks, flight path files, video images and the like do not realize on-line data communication, and the manual participation degree is too high.
Disclosure of Invention
In order to solve the technical problems of repeated task dispatching, data line down-flow, insufficient safety control and low defect identification efficiency in the prior art, the invention provides an intelligent image acquisition system and method for an unmanned aerial vehicle, and the technical scheme is as follows:
an unmanned aerial vehicle intelligent image acquisition system comprises a management information large area, an internet large area and the internet; the management information area comprises unmanned aerial vehicle application, a technical middle station, a data middle station and a service middle station, wherein the data middle station comprises an unstructured platform; the Internet large area comprises unmanned aerial vehicle application, a technical middle platform and an unstructured platform; the management information large area and the internet large area realize information penetration through a logic type information network safety isolation device, and the internet large area and the internet realize information penetration through a firewall.
Furthermore, the technical middle station for managing the information large area comprises a main side artificial intelligence platform and a provincial and municipal side artificial intelligence platform; the total side artificial intelligence platform comprises a sample library, a model library and a training platform; the provincial and municipal artificial intelligence platform comprises a sample library and a model library; the technical middle platform of the Internet large area comprises an artificial intelligence operation platform; the method comprises the steps that a headquarter side artificial intelligence platform obtains sample information from a provincial and municipal side artificial intelligence platform, the sample information is trained by the headquarter side artificial intelligence platform to obtain a model algorithm, the provincial and municipal side artificial intelligence platform obtains the model algorithm, a technical central station of an internet large area calls the model algorithm, and a patrol picture obtained by unmanned aerial vehicles in patrol obtains defect information through the model algorithm.
Furthermore, the unmanned aerial vehicle realizes the positioning and deviation correction of the unmanned aerial vehicle through the RTK service.
Further, still include outside unmanned aerial vehicle, outside unmanned aerial vehicle patrols and examines the operation through the unified authentication in internet big district after.
The invention also provides an intelligent image acquisition method of the unmanned aerial vehicle, the unmanned aerial vehicle application of the management information area issues the structural data related to the unmanned aerial vehicle inspection task to the internet area through the service central station of the management information area, the internet area receives and caches the structural data related to the unmanned aerial vehicle inspection task and issues the structural data to the unmanned aerial vehicle inspection terminal of the internet, and the unmanned aerial vehicle inspection terminal carries out autonomous inspection operation and uploads the inspection pictures to the unstructured platform of the internet area for long-term storage.
Furthermore, the provincial and municipal artificial intelligence platform of the technical middlebox of the management information district automatically pulls sample information from the unmanned aerial vehicle application of the management information district through a sample collection interface, collects and uploads the sample information to a sample library of the headquarter artificial intelligence platform for use by a training platform of the headquarter artificial intelligence platform.
And storing the model algorithm which is subjected to the training verification and reaches the standard in the training platform of the headquarter-side artificial intelligence platform into a model library of the headquarter-side artificial intelligence platform, and issuing the model algorithm in the model library to the model library of the provincial and municipal-side artificial intelligence platform for the technical central office of the large area of the Internet to call.
The unmanned aerial vehicle application of the internet large area uploads the inspection picture to the technical intermediate station of the internet large area, algorithm model identification is carried out on an artificial intelligence operation platform of the technical intermediate station through a called model algorithm, and an identification result is returned to the unmanned aerial vehicle application of the internet large area.
And the unmanned aerial vehicle application in the large Internet area transmits the defect picture with the defect identification result back to the unmanned aerial vehicle application in the large management information area, and transmits the defect information back to the service platform in the large management information area.
Furthermore, generating airworthiness area data on the management information large area side according to the copied airspace files and by combining GIS data, power grid resource data and non-airworthiness area ledger information, and storing the airworthiness area data in the management information large area.
And on the internet large area side, the real-time position monitoring of the unmanned aerial vehicle is realized by calling the flight coordinate information returned during the field operation of the unmanned aerial vehicle and combining the airworthiness area data.
And calling the video data of the field operation of the unmanned aerial vehicle and the task execution state data to realize the safety control of the field operation of the unmanned aerial vehicle.
Further, unified authentication is carried out to outsourcing flight crew and outside unmanned aerial vehicle to give interim operation authority, carry out operation safety management and control and supplementary early warning to internet large tracts of land with outside unmanned aerial vehicle's flight state data and flight position information real-time feedback.
Furthermore, image data generated by inspection of the external unmanned aerial vehicle is only temporarily stored at the machine end, and after the image data is transmitted back to the Internet large area, the inspection data temporarily stored on the external unmanned aerial vehicle is immediately eliminated.
The invention has the beneficial effects that: the invention is based on technologies such as artificial intelligence, image recognition and the like, and takes service digitization, management standardization and operation intellectualization as directions, thereby realizing online circulation of the whole process of services such as flight airspace management, routing inspection plan making, operation safety monitoring, data interaction processing, auxiliary maintenance decision and the like, improving the capabilities of defect recognition analysis, data safety protection and whole operation process control, reducing the operation pressure of basic level staff, and comprehensively supporting the construction of digital teams and groups.
Drawings
Fig. 1 is a current flow chart of unmanned aerial vehicle inspection work.
Fig. 2 is an architecture diagram of an intelligent image acquisition system of an unmanned aerial vehicle according to the invention.
Fig. 3 is an application architecture diagram of an intelligent image acquisition system for an unmanned aerial vehicle according to the present invention.
Fig. 4 is a unmanned aerial vehicle autonomous inspection data flow chart of the unmanned aerial vehicle intelligent image acquisition system of the invention.
Fig. 5 is a sample and defect data flow diagram of the intelligent image acquisition system for unmanned aerial vehicles according to the present invention.
Fig. 6 is a flow chart of security management and control data of the intelligent image acquisition system of the unmanned aerial vehicle.
Fig. 7 is a outsourcing management data flow chart of the intelligent image acquisition system of the unmanned aerial vehicle.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. 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.
As shown in FIG. 2, an unmanned aerial vehicle intelligent image acquisition system comprises a management information large area, an internet large area and the internet. The management information area comprises unmanned aerial vehicle application, a technical middle station, a data middle station and a service middle station, wherein the data middle station comprises an unstructured platform; the Internet large area comprises unmanned aerial vehicle application, a technical middle platform and an unstructured platform; the management information large area and the internet large area realize information penetration through a logic type information network safety isolation device, and the internet large area and the internet realize information penetration through a firewall.
The unmanned aerial vehicle application of the management information large area comprises an operation plan management module, an operation task management module, a navigable area management and control module, an airline management module, a statistical analysis module and a basic configuration module.
The technical middle platform for managing the information large area comprises a power grid GIS platform, an artificial intelligence platform and a unified authority platform. The power grid GIS platform generates a navigable area file by combining the power grid resource center of the power grid GIS platform in service and the ledger and graphic information provided by the power grid topology center, and integrating the wholesale airspace information and the non-navigable area information, so as to define the safe operation range; the artificial intelligence platform provides an image recognition algorithm analysis service, carries out intelligent defect recognition on the unmanned aerial vehicle inspection image data, and meanwhile can realize a sample collection function and carry out unified management on sample information; the unified authority platform provides convenient, quick, safe and reliable account management, authentication management, authority management and safety audit management for business application and micro-service.
The data center of the management information large area comprises an analysis layer, a sharing layer and a source pasting layer. The method comprises the steps of storing massive unmanned aerial vehicle inspection pictures by adopting an unstructured platform and a fragmentation distributed storage technology, carrying out cross-data-domain comprehensive calculation analysis based on full-service data and a unified model, and supporting unmanned aerial vehicle data analysis statistics and value mining application through various data services.
The service center of the management information area comprises a power grid resource center, an operation management center and a power grid topology center. Through a power grid resource center and an operation management center, based on a unified data model, sharing services such as power grid resource query, patrol plan maintenance and patrol task maintenance are called, information penetration between a management information large area and an internet large area is realized through an information network safety isolation device (logic type), and services such as power transmission equipment ledger information acquisition, patrol plan assignment, patrol task distribution and defect data reporting are supported.
The unmanned aerial vehicle application of the internet large area comprises a airworthiness area management module, a task management module, a defect management and control module, a flight monitoring module and a temporary storage database. The data stored in the temporary storage database comprises flight states, alarm information, flight tracks and the like.
The technical middle platform of the Internet large area comprises a unified video platform, a power grid GIS platform, an artificial intelligence platform, a unified authority platform and an extranet mobile portal. The unified video platform accesses real-time video data of the unmanned aerial vehicle into the unified video platform to realize visual monitoring of field operation; the power grid GIS platform generates a navigable area file by combining the power grid resource center of the platform in the service and the ledger and graphic information provided by the power grid topology center through the service of the power grid GIS platform and integrating the wholesale airspace information and the non-navigable area information, so as to define the safe operation range; the artificial intelligence platform provides an image recognition algorithm analysis service, and carries out intelligent defect recognition on the unmanned aerial vehicle inspection image data; the function of collecting samples is realized, and the sample information is managed in a unified way; the unified authority platform provides convenient, quick, safe and reliable account management, authentication management, authority management and safety audit management for business application and micro-service; the external network mobile portal builds the native android micro-application of the unmanned aerial vehicle based on the APP, and supports the unmanned aerial vehicle to patrol the service by utilizing the APP data transmission link. The unstructured platform stores massive unmanned aerial vehicle inspection pictures through a fragmentation distributed storage technology.
In an embodiment, the unmanned aerial vehicle inspection terminal and the unmanned aerial vehicle are in communication connection with the internet large area through the internet 4G/5G.
In an embodiment, the intelligent image acquisition system for the unmanned aerial vehicle, provided by the invention, is based on an external network mobile portal APP, fuses native SDKs such as a Dajiang unmanned aerial vehicle and the like, establishes a transmission channel between an unmanned aerial vehicle inspection terminal and the unmanned aerial vehicle, realizes real-time transmission of signals such as positioning and deviation correction of the unmanned aerial vehicle, and performs flight control on the unmanned aerial vehicle. The unmanned aerial vehicle data security transmission link is communicated by utilizing a transmission channel of an external network mobile portal, namely internet-internet large area-management information large area, service functions such as unmanned aerial vehicle operation information retrieval, inspection data storage and the like are supported by a service center sharing service of the management information large area and by combining a public service provided by the service center and a technical center, so that the services such as unmanned aerial vehicle monitoring, inspection task receiving, inspection data return and the like are realized, and the technical problems that the internal and external networks lack a safe, convenient and stable interaction channel, the online data communication of the inspection task, the flight path file, the video image and the like is not realized, and the manual participation degree is too high in the prior art are solved.
Specifically, the unmanned aerial vehicle field operation personnel carries out unmanned aerial vehicle flight control through the remote controller, unmanned aerial vehicle passes through RTK service and acquires unmanned aerial vehicle location, signals such as rectify, and give internet unmanned aerial vehicle inspection terminal in real time transmission, unmanned aerial vehicle inspection terminal passes through "internet-internet large area-management information large area" transmission channel, with signal through information network safety isolating device (logical type) real-time transmission to management information large area, realize unmanned aerial vehicle control, patrol and examine the task and receive, patrol and examine data passback.
In order to realize the aims of real-time, digital, visual, intelligent and fine information acquisition of the unmanned aerial vehicle, the intelligent processing and data through closed-loop management of the unmanned aerial vehicle inspection service are realized by fusing the public services of the external network mobile portal, the service center, the data center, the technical center and other support platforms.
Specifically, as shown in fig. 3, the management information area includes a headquarters level unmanned aerial vehicle application and a provincial level unmanned aerial vehicle application. The headquarter-level unmanned aerial vehicle application comprises unmanned aerial vehicle service monitoring and comprehensive statistical analysis, and the provincial-level unmanned aerial vehicle application comprises operation plan management, operation task management, airworthiness area management and control, airline management, statistical analysis and basic management. In the application of the provincial unmanned aerial vehicle, operation plan management comprises plan making, plan approval, plan changing and plan finishing, the operation task management comprises an operation inspection task, an operation inspection work order, operation task issuing and historical track checking, the airworthiness area management and control comprises airworthiness area management and airworthiness area warning, the airline management comprises airline recording, airline updating, airline deleting and airline checking, statistical analysis comprises inspection airline warehousing rate, unmanned aerial vehicle configuration rate and operation coverage rate, and basic management comprises dictionary configuration and service auditing configuration.
Correspondingly, the Internet large area comprises airworthiness area management and control, defect management, task management and flight monitoring. The airworthiness region management and control comprises warning information acquisition, warning information synchronization, operation path receiving and operation path synchronization, defect management comprises defect identification and defect uploading, task management comprises task work order acquisition, airworthiness region information acquisition, airline file acquisition and task result management, and flight monitoring comprises safety monitoring and state monitoring.
On the unmanned aerial vehicle patrols and examines the terminal, receive including the task airline, unmanned aerial vehicle independently patrols and examines, unmanned aerial vehicle flight control, patrol and examine data passback.
In an embodiment, unmanned aerial vehicle patrols and examines data transversal distribution in management information big district and internet big district, and at management information big district side, general technology class, equipment ledger class, basic data class, patrol and examine task class, safety control class data storage platform in the business, and defect picture, sample picture are saved respectively in unstructured platform and artificial intelligence platform. At the large area side of the Internet, safety control data such as alarm information, flight state data, flight tracks and the like are temporarily stored (namely, the data are sold instantly), so that the real-time calling of autonomous inspection operation is facilitated, the safety control of field operation is realized, and data such as operation result type inspection pictures, videos and the like are stored in an unstructured platform according to periodic requirements.
Specifically, patrol and examine data flow and turn to the direction about unmanned aerial vehicle, can divide into following several types:
1. flight path data: acquiring a track file from an unmanned aerial vehicle application in a management information large area, issuing the track file to the unmanned aerial vehicle application in the internet large area through an information network safety isolation device (logic type), extracting track data, and issuing the track data to the unmanned aerial vehicle app in the internet through a firewall;
2. and (3) patrol planning: calling a service center maintenance inspection plan from the unmanned aerial vehicle application of the management information large area, and issuing the service center maintenance inspection plan to the service center of the management information large area;
3. and (3) patrol task: the method comprises the steps that a service middle station maintenance inspection task is called from an unmanned aerial vehicle application of a management information large area and is issued to the service middle station of the management information large area, the service middle station of the management information large area issues the task to the unmanned aerial vehicle application of an internet large area through an information network safety isolation device (logic type), track data are extracted, and then the track data are issued to an unmanned aerial vehicle app of the internet through a firewall;
4. and (5) inspecting the work order: the method comprises the steps that a service middle station maintenance inspection work order is called from an unmanned aerial vehicle application of a management information large area and is issued to the service middle station of the management information large area, a task is issued to the unmanned aerial vehicle application of the internet large area by the service middle station of the management information large area through an information network safety isolation device (logic type), work order data are obtained, and then the inspection work order is issued to an unmanned aerial vehicle app of the internet through a firewall;
5. flight monitoring: the unmanned aerial vehicle app of the internet transmits the flight monitoring data back to the unmanned aerial vehicle application of the internet large area through the firewall and transmits the flight monitoring data back to the business center station of the management information large area through the information network safety isolation device (logic type).
6. Patrol return (picture video): the unmanned aerial vehicle app of internet passes back picture data, video data to the unmanned aerial vehicle application and the unified video platform in the internet large area through preventing the hot wall respectively, and wherein, the data of passing back for unmanned aerial vehicle application passes back in proper order through unstructured speech platform, information network safety isolating device (logical type) again and gives unmanned aerial vehicle application, unstructured platform, the artificial intelligence platform in the management information large area.
7. Defect information: the unmanned aerial vehicle application in the internet large area returns the defect information to the service central station in the management information large area through the information network security isolation device (logic type).
In order to realize the online circulation of the autonomous inspection task and the unified track file, the GIS technology and the middle platform service are used as supports, the operation flows of unmanned aerial vehicle track planning, autonomous operation, data return and automatic filing are established, and the autonomous inspection operation capability of the unmanned aerial vehicle is improved. As shown in fig. 4, unmanned aerial vehicle is independently patrolled and examined and is included:
1. and deploying track planning service in the management information area, formulating an autonomous inspection task, and issuing structured data such as related track files, task information and the like to the internet area.
2. And receiving and caching the structural data related to the inspection task issued by the management information large area in the internet large area so as to be called by related service application.
3. And receiving the inspection task file containing the planning track information at the inspection terminal, and carrying out autonomous inspection operation. And automatically naming and filing the inspection pictures according to the additional information of the autonomous air route, and uploading the inspection pictures to an internet large-area unstructured database on line for long-term storage.
For sample and defect data circulation, in one embodiment, the unmanned aerial vehicle inspection image data is subjected to defect identification and verification through an artificial intelligence platform, defect information is automatically circulated to a defect management module of a management information large area, and the automation of defect data circulation is promoted; and meanwhile, uploading the image classification sample set data to an artificial intelligence platform, and performing iterative upgrade on the algorithm model.
As shown in fig. 5, the technical middle station of the management information large area includes a main-side artificial intelligence platform and a provincial-city-side artificial intelligence platform; the total side artificial intelligence platform comprises a sample library, a model library and a training platform; the provincial and municipal artificial intelligence platform comprises a sample library and a model library; the technical middle platform of the Internet large area comprises an artificial intelligence operation platform; the method comprises the steps that a headquarter side artificial intelligence platform obtains sample information from a provincial and municipal side artificial intelligence platform, the sample information is trained by the headquarter side artificial intelligence platform to obtain a model algorithm, the provincial and municipal side artificial intelligence platform obtains the model algorithm, a technical central station of an internet large area calls the model algorithm, and a patrol picture obtained by unmanned aerial vehicles in patrol obtains defect information through the model algorithm. The method specifically comprises the following steps:
sample uploading: and deploying an artificial intelligence platform sample library and a model library at the province and city side, automatically pulling sample information from the unmanned aerial vehicle application through a sample collection interface, uploading the collected sample information to the sample library at the general side, and performing processes such as labeling and publishing for model training.
Issuing a model: and issuing the model algorithm which is subjected to the training verification and reaches the standard in the headquarter side model library to an province-city side artificial intelligence platform model library, deploying the model algorithm to a province-city level model service platform or a model server, applying and calling the model algorithm by an unmanned aerial vehicle, and supporting the unmanned aerial vehicle to intelligently identify images.
For safety control, as shown in fig. 6, digitally analyzing the batched airspace information, and combining the checked non-airworthiness region ledger, the checked GIS data and the checked power grid resource data to generate an unmanned aerial vehicle operation airworthiness region; based on the internet large area, the information such as the real-time position of the unmanned aerial vehicle, the task execution state and the like is obtained in real time, the field operation condition of the unmanned aerial vehicle is monitored in real time, the functions of automatic warning and flight limitation such as over-area and over-limit are realized, and the safety management and control of the field operation are enhanced.
Wherein, the management information large area side: and generating airworthiness region data according to the batched airspace files by combining GIS data, power grid resource data, the searched non-airworthiness region ledger and other information, and storing the airworthiness region data in a management information area.
The large-area side of the Internet: through the flight coordinate information of transferring the postback during unmanned aerial vehicle field operation, combine the airworthiness district data, realize unmanned aerial vehicle real-time position control, can transfer unmanned aerial vehicle field operation video data and task execution state data simultaneously, realize unmanned aerial vehicle field operation's full flow safety management and control.
The internet side: the unmanned aerial vehicle transmits back the position data in real time, and the real-time transmission of the image information and the task execution state information is realized through the mobile terminal.
In an embodiment, the unmanned aerial vehicle further comprises outsourcing management, and the external unmanned aerial vehicle performs routing inspection operation after uniform authentication of the internet large area. As shown in fig. 7, the outsourcing flight crew and the external drone are collectively authenticated, and a provisional work authority is given. In the outsourcing operation process, the flight state data and the flight position information are transmitted back to the Internet large area in real time to carry out operation safety control and auxiliary early warning, and the risk that the unmanned aerial vehicle enters the non-suitable-for-flight area by mistake is reduced. The patrol inspection image data generated by outsourcing operation is transmitted back to the large area side of the internet for centralized storage, so that the patrol inspection data is prevented from being stored at the external unmanned aerial vehicle end. And the image data that outside unmanned aerial vehicle patrolled and examined the production only do the processing of keeping in at the machine end, treat that image data passes back to internet large area after, eliminate in time patrolling and examining the data of saving on outside unmanned aerial vehicle, accomplish to pass promptly and sell (data are kept in temporary), avoid data to reveal.
The invention also provides an intelligent image acquisition method of the unmanned aerial vehicle, the unmanned aerial vehicle application of the management information area issues the structural data related to the unmanned aerial vehicle inspection task to the internet area through the service central station of the management information area, the internet area receives and caches the structural data related to the unmanned aerial vehicle inspection task and issues the structural data to the unmanned aerial vehicle inspection terminal of the internet, and the unmanned aerial vehicle inspection terminal carries out autonomous inspection operation and uploads the inspection pictures to the unstructured platform of the internet area for long-term storage.
In one embodiment, the provincial and municipal artificial intelligence platform of the technical central office of the management information district automatically pulls sample information from the unmanned aerial vehicle application of the management information district through a sample collection interface, collects and uploads the sample information to a sample library of the headquarter artificial intelligence platform for use by a training platform of the headquarter artificial intelligence platform;
storing a model algorithm which is subjected to training verification and reaches the standard in a training platform of the headquarter-side artificial intelligence platform into a model library of the headquarter-side artificial intelligence platform, and issuing the model algorithm in the model library to the model library of the provincial and municipal-side artificial intelligence platform for being called by a technical central office of an internet large area;
uploading the inspection picture to a technical middle station of the internet large area by the unmanned aerial vehicle application of the internet large area, carrying out algorithm model identification on an artificial intelligence operation platform of the technical middle station through a called model algorithm, and returning an identification result to the unmanned aerial vehicle application of the internet large area;
and the unmanned aerial vehicle application in the large Internet area transmits the defect picture with the defect identification result back to the unmanned aerial vehicle application in the large management information area, and transmits the defect information back to the service platform in the large management information area.
In one embodiment, at the management information large area side, generating airworthiness area data by combining GIS data, power grid resource data and non-airworthiness area ledger information according to the copied airspace files, and storing the airworthiness area data in the management information large area;
on the internet large area side, real-time position monitoring of the unmanned aerial vehicle is realized by calling flight coordinate information returned during field operation of the unmanned aerial vehicle and combining airworthiness area data;
and calling the video data of the field operation of the unmanned aerial vehicle and the task execution state data to realize the safety control of the field operation of the unmanned aerial vehicle.
In one embodiment, outsourcing flight personnel and external unmanned aerial vehicles are subjected to unified authentication, temporary operation permission is given, and flight state data and flight position information of the external unmanned aerial vehicles are transmitted back to an internet large area in real time to perform operation safety control and auxiliary early warning.
In one embodiment, the image data generated by the inspection of the external unmanned aerial vehicle is only temporarily stored at the machine end, and after the image data is transmitted back to the internet large area, the inspection data temporarily stored on the external unmanned aerial vehicle is immediately eliminated.
The invention is based on technologies such as artificial intelligence, image recognition and the like, and takes service digitization, management standardization and operation intellectualization as directions, thereby realizing online circulation of the whole process of services such as flight airspace management, routing inspection plan making, operation safety monitoring, data interaction processing, auxiliary maintenance decision and the like, improving the capabilities of defect recognition analysis, data safety protection and whole operation process control, reducing the operation pressure of basic level staff, and comprehensively supporting the construction of digital teams and groups.
Service digitization: the management information area and the internet area are communicated, offline manual intervention links are reduced, online circulation of tasks such as task distribution, data return, image recognition and defect registration is achieved, and the autonomous inspection application level of the unmanned aerial vehicle is improved.
Management standardization: and a field operation safety control system is established, field operation behaviors are normalized internally, outsourcing operation management is perfected externally, the over-regional operation condition is basically avoided, and the comprehensive control capability of the aeronautical area is enhanced.
Operation intellectualization: the number and the types of defect samples are enriched, automatic sample collection and model issuing as required are realized, the intelligent image identification and large-scale application level is improved, and the primary operation burden is reduced.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, and various changes may be made apparent to those skilled in the art as long as they are within the spirit and scope of the present invention as defined and defined by the appended claims, and all matters of the invention which utilize the inventive concepts are protected.
Claims (9)
1. The utility model provides an unmanned aerial vehicle intelligence image acquisition system which characterized in that: the system comprises a management information area, an internet area and the internet; the management information large area comprises an unmanned aerial vehicle application, a technical middle station, a data middle station and a service middle station, wherein the data middle station comprises an unstructured platform; the Internet large area comprises unmanned aerial vehicle application, a technical middle station and an unstructured platform; the management information large area and the internet large area realize information penetration through a logic type information network safety isolation device, and the internet large area and the internet realize information penetration through a firewall.
2. The intelligent unmanned aerial vehicle image acquisition system of claim 1, wherein: the technical middle station of the management information large area comprises a main side artificial intelligence platform and a provincial and municipal side artificial intelligence platform; the total side artificial intelligence platform comprises a sample library, a model library and a training platform; the provincial and urban side artificial intelligence platform comprises a sample library and a model library; the technical middle platform of the Internet large area comprises an artificial intelligence operation platform; the system comprises a main-side artificial intelligence platform, a province-city-side artificial intelligence platform, an Internet large area, a central station and an unmanned aerial vehicle, wherein the main-side artificial intelligence platform obtains sample information from the province-city-side artificial intelligence platform, the sample information is trained by the main-side artificial intelligence platform to obtain a model algorithm, the province-city-side artificial intelligence platform obtains the model algorithm, the technical central station of the Internet large area calls the model algorithm, and a patrol picture obtained by patrol of the unmanned aerial vehicle obtains defect information through the model algorithm.
3. The intelligent image acquisition system of unmanned aerial vehicle of claim 1 or 2, wherein: the unmanned aerial vehicle realizes positioning and deviation correction of the unmanned aerial vehicle through RTK service.
4. The intelligent unmanned aerial vehicle image acquisition system of claim 3, wherein: still include outside unmanned aerial vehicle, outside unmanned aerial vehicle passes through the operation of patrolling and examining is carried out after the unified authentication in internet big district.
5. An unmanned aerial vehicle intelligent image acquisition method of the unmanned aerial vehicle intelligent image acquisition system according to claim 1, characterized in that: the unmanned aerial vehicle application in management information big district sends the unmanned aerial vehicle to patrol and examine the relevant structured data of task to internet big district through the business center platform in management information big district, internet big district receives and caches unmanned aerial vehicle patrols and examines the relevant structured data of task to send to the unmanned aerial vehicle of internet and patrol and examine the terminal, unmanned aerial vehicle patrols and examines the terminal and carries out the operation of independently patrolling and examining, and will patrol and examine the picture and upload to the unstructured platform in internet big district carries out long-term storage.
6. The intelligent image acquisition method for unmanned aerial vehicles according to claim 5, wherein: the provincial and municipal artificial intelligence platform of the technical central office of the management information large area automatically pulls sample information from the unmanned aerial vehicle application of the management information large area through a sample collection interface, collects and uploads the sample information to a sample library of a main artificial intelligence platform for use by a training platform of the main artificial intelligence platform;
storing the model algorithm which is subjected to the training verification and reaches the standard in the training platform of the headquarter-side artificial intelligence platform into a model library of the headquarter-side artificial intelligence platform, and issuing the model algorithm in the model library to the model library of the province-city-side artificial intelligence platform for the technical central office of the large area of the internet to call;
the unmanned aerial vehicle application of the large Internet area uploads the inspection picture to a technical intermediate station of the large Internet area, algorithm model identification is carried out on an artificial intelligent operation platform of the technical intermediate station through a called model algorithm, and an identification result is returned to the unmanned aerial vehicle application of the large Internet area;
and the unmanned aerial vehicle application in the Internet large area transmits the defect picture with the identification result of the defect back to the unmanned aerial vehicle application in the management information large area, and transmits the defect information back to the service platform in the management information large area.
7. An intelligent unmanned aerial vehicle image acquisition method as claimed in claim 5 or 6, wherein: generating airworthiness region data on the management information large region side according to the batched airspace files by combining GIS data, power grid resource data and non-airworthiness region ledger information, and storing the airworthiness region data in the management information large region;
on the internet large area side, real-time position monitoring of the unmanned aerial vehicle is achieved by calling flight coordinate information returned during field operation of the unmanned aerial vehicle and combining airworthiness area data;
and calling the video data of the field operation of the unmanned aerial vehicle and the task execution state data to realize the safety control of the field operation of the unmanned aerial vehicle.
8. The intelligent image acquisition method for unmanned aerial vehicles according to claim 7, wherein: and performing unified authentication on outsourcing flight personnel and an external unmanned aerial vehicle, giving temporary operation permission, and transmitting the flight state data and the flight position information of the external unmanned aerial vehicle back to the internet large area in real time to perform operation safety control and auxiliary early warning.
9. The intelligent image acquisition method for unmanned aerial vehicles according to claim 8, wherein: the image data generated by the inspection of the external unmanned aerial vehicle is only temporarily stored at the machine end, and after the image data is transmitted back to the Internet large area, the inspection data temporarily stored on the external unmanned aerial vehicle is immediately eliminated.
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