CN116168464A - Unmanned aerial vehicle inspection data identification and management method and system based on distributed storage - Google Patents
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Abstract
The invention discloses a method and a system for identifying and managing unmanned aerial vehicle inspection data based on distributed storage, wherein S1, the inspection data of an unmanned aerial vehicle is obtained and is initially processed; s2, performing fault identification on the primarily processed inspection data, marking a fault part, and uploading the marked inspection data to an inspection system for data sharing; s3, dumping and archiving the patrol data with the fault identification completed; s4, utilizing the embedded data set to carry out archival image database construction on the patrol data to be archived in a mode of extending the Raster Type, and storing the archival image database in a distributed storage database; the method and the system are used for carrying out standardized identification on standardized transmission line photos collected by the unmanned aerial vehicle, providing an image data storage module of a distributed storage technology, developing an image automatic archiving management system, automatically identifying and leading-in history hidden danger records, storing corresponding data in a real-time classified manner, organically integrating with a transmission inspection management system, and greatly improving the operation and inspection work efficiency.
Description
Technical field:
the invention relates to the field of data management, in particular to a method and a system for identifying and managing unmanned aerial vehicle inspection data based on distributed storage.
The background technology is as follows:
the development of society drives the urbanization process to accelerate, and the electricity demand and scale are also rising year by year. In order to adapt to the increasing power consumption requirement and the stability of power supply, the power transmission line needs to be inspected regularly.
In the process of inspection of the transmission line through the unmanned aerial vehicle, more than 30 images and videos are generated in each inspection of each base tower, hundreds of similar images and images named by digital numbers are classified and filed by groups after each inspection, and the filing efficiency is low and errors are easy to occur. According to the current workload, a large amount of data is generated each year, and the data is gradually and rapidly increased along with the increase of the number of rounds. And generating massive image and video data, wherein the image and video data currently lack systematic, normalized and standardized filing management means, and the image data files geometrically grow and lack effective identification, arrangement and filing means, so that a large amount of data becomes invalid data, and the data storage is scattered, so that the management and maintenance are not facilitated, and the efficient query and application are difficult.
Therefore, a set of system is urgently needed to store unmanned aerial vehicle images and videos in a standardized and automatic mode, high-efficiency inquiry and statistics of mass data are achieved, a data base is provided for future intelligent analysis and big data processing, and scientific operation and maintenance and high-efficiency overhaul are scientifically conducted.
The invention comprises the following steps:
in order to solve the technical problems, the invention provides the unmanned aerial vehicle inspection data identification and management method based on the distributed storage, and the unmanned aerial vehicle images and videos can be automatically archived and stored through an image automatic identification technology and a distributed storage technology, and the distributed storage is beneficial to management and maintenance and convenient for subsequent efficient inquiry and application.
In order to solve the technical problems, the invention provides a technical scheme that: a unmanned aerial vehicle inspection data identification and management method based on distributed storage comprises the following steps:
step one, acquiring inspection data of an unmanned aerial vehicle on a power transmission line in real time, and performing primary processing on the acquired inspection data;
step two, performing fault identification on the primarily processed inspection data, marking fault parts of the inspection data with faults, and uploading the marked inspection data to an inspection system for data sharing;
step three, initiating a data archiving request, and carrying out dump archiving operation on the patrol data after fault identification;
and fourthly, utilizing the embedded data set to carry out archival image database construction on the patrol data ready for archival in a mode of extending the Raster Type, and storing the archival image database in a distributed storage database.
Further, in the first step, the inspection data includes: the SAR image of the inspection target in the power transmission line and the basic information of the power transmission line are contained.
Further, in the first step, the preliminary processing of the acquired inspection data includes: the SAR image is monitored and identified through the SAR automatic target identification system, noise of the SAR image is removed, an interested region is obtained, target classification identification is carried out on the interested region, and type marking is carried out according to the target type.
Further, in the second step, the fault identification process for the inspection data is as follows: and performing fault identification through an AI automatic identification technology.
Further, before fault identification, AI deep learning is performed through a training database, wherein the training database is formed after manual fault labeling is performed on a pre-collected picture.
In the fourth step, the process of archiving the images and creating the library is as follows:
1) Transforming the primarily processed inspection data into a zip compressed file;
2) Expanding a corresponding grid Type Raster Type according to the Type of the archival image;
3) Registering a Raster type dll to realize the support of the mosaic data set on the archival image;
4) And building a database by using the mosaic data set.
In the fourth step, the distributed storage database adopts an extensible distributed network storage system structure, a plurality of storage servers are utilized to share the storage load, the storage information is positioned by using the position server, the data of each node is duplicated and backed up in multiple copies, meanwhile, one main copy capable of providing read/write service is selected from the multiple copies, the other copies are used as standby copies, the standby copies do not serve outside, and only read-only service is provided inside.
In order to solve the technical problems, the invention provides another technical scheme as follows: the unmanned aerial vehicle inspection data identification and management system based on the distributed storage based on the method is characterized in that: the system comprises a data acquisition module, an archiving management module, a storage module and a control module, wherein the real-time control module is communicated with the acquisition module, the archiving management module and the storage module, and the system comprises the following components:
and a data acquisition module: receiving inspection data for inspecting the transmission line sent by the unmanned aerial vehicle in real time, and sending the acquired inspection data to the control module;
and the control module is used for: preprocessing the inspection data sent by the data acquisition module, carrying out fault identification on the preprocessed inspection data, initiating a data archiving request after the fault identification, carrying out dump archiving on the inspection data with the fault identification, marking a fault part on the inspection data with the fault, and uploading the marked inspection data to an inspection system for data sharing;
an archiving management module: the method comprises the steps that a data set is inlaid in a mode of Raster Type expansion, so that the inspection data sent by a control module are archived and an image database is built;
and a storage module: and storing the archived inspection data by adopting an extensible distributed network storage system structure.
In order to solve the technical problems, the invention provides another technical scheme as follows: unmanned aerial vehicle inspection data identification and management device based on distributed storage, characterized by comprising:
a memory for storing a computer program;
and the processor is used for reading and executing the computer program stored in the memory, and when the computer program is executed, the processor executes the unmanned aerial vehicle inspection data identification and management method based on distributed storage.
The beneficial effects of the invention are as follows:
1. the standardized transmission line photo that this application gathered to unmanned aerial vehicle carries out standardized discernment, proposes distributed storage technology's image data storage module, develops image automation and files management system, and automatic discernment imports the historical hidden danger record, realizes the standardization to corresponding data of real-time storage can with the transmission of electricity inspection management system's organic integration, promotes fortune and examines work efficiency by a wide margin.
2. Through carrying out big data AI discernment to the data that collect in advance, annotate from the hidden danger storehouse of taking through earlier stage and carry out AI degree of depth study, after the preliminary treatment is carried out to the inspection image that unmanned aerial vehicle obtained to later stage, through AI analysis automated processing, mark the hidden danger and upload to distributed storage ware and store to with inspection system shared data, realize inspection system looks over hidden danger information in real time, realize the automation, standardization.
3. According to the method, the embedded data set is utilized to realize archiving image database construction in a mode of expanding the Raster Type, and the image management efficiency and the automation degree are improved in the mode.
The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments, as illustrated in the accompanying drawings.
Description of the drawings:
in order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only five of the inventions, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the method of the present application.
Fig. 2 is a block diagram of SAR automatic target identification.
FIG. 3 is a schematic diagram of dump archiving.
Fig. 4 is a block diagram of a system in the present application.
FIG. 5 is a block diagram of the device of the present application
The specific embodiment is as follows:
embodiments of the present invention will be described in detail below with reference to the accompanying drawings. While the invention is susceptible of embodiment in the drawings, it is to be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided to provide a more thorough and complete understanding of the invention. It should be understood that the drawings and embodiments of the invention are for illustration purposes only and are not intended to limit the scope of the present invention.
It should be understood that the steps recited in the method embodiments of the present invention may be performed in a different order. Furthermore, method embodiments may include additional steps omitting the execution of the illustrated steps. The scope of the invention is not limited in this respect.
The names of messages or information interacted between the devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of such messages or information.
Examples
As shown in fig. 1-3, the invention provides a method for identifying and managing unmanned aerial vehicle inspection data based on distributed storage, which comprises the following steps:
step S1, acquiring inspection data of the unmanned aerial vehicle on the power transmission line in real time, and performing primary processing on the acquired inspection data.
And S2, performing fault identification on the primarily processed inspection data, marking fault parts of the inspection data with faults, and uploading the marked inspection data to an inspection system for data sharing.
And S3, initiating a data archiving request, and carrying out dump archiving operation on the patrol data with the fault identification completed.
And S4, utilizing the embedded data set to carry out archival image database construction on the patrol data ready for archival in a mode of extending the Raster Type, and storing the archival image database in a distributed storage database.
In the step S1, the inspection data includes: the SAR image of the inspection target in the power transmission line and the basic information of the power transmission line are contained.
The basic information of the power transmission line comprises the information such as the name of the line, the position of a target when a target image is acquired, and the like; the transmission line is composed of a line pole tower, a wire, an insulator, a line fitting, a stay wire, a pole tower foundation, a grounding device and the like. The devices on these power lines are identified as targets.
In the step S1, the process of performing the preliminary processing on the acquired inspection data is as follows: the SAR image is monitored and identified through the SAR automatic target identification system, noise of the SAR image is removed, an interested region is obtained, target classification identification is carried out on the interested region, and type marking is carried out according to the target type.
The function of automatic target recognition (Automatic Target Recognition, abbreviated as ATR) through SAR is to explain and analyze the acquired SAR image, and to induce and re-dig a great amount of SAR information, thereby obtaining a region of interest (Regions of Interest, abbreviated as ROI) and classifying and recognizing the ROI. SAR ATR includes three stages of detection (Prescreener), discrimination (Discrimination), and Classification (Classification).
The noise in the SAR image greatly reduces the quality of the image, blurs the characteristic information of the region of interest, and influences the subsequent application of target detection, classification, recognition and the like. These noises are inevitably present due to factors such as system, environment, and human beings. Therefore, how to remove noise while maintaining or enhancing image region features is a key in SAR image ROI extraction.
The SAR image target feature extraction is an important component part of the SAR ATR in the identification stage, and whether the extracted features have better resolution and identification capability is a key for influencing the whole target identification.
In the step S2, the process of performing fault identification on the inspection data is as follows: and performing fault identification through an AI automatic identification technology.
Further, before fault identification, AI deep learning is performed through a training database, wherein the training database is formed after manual fault labeling is performed on a pre-collected picture.
In the step S3, a data archiving request is initiated, which requires that all blockchain data in front of the snapshot point be dumped and archived. The node dumps the block data to be dumped, corresponding transaction receipt and other data, and updates the local generation state content into the snapshot state obtained by previous backup.
By adopting a segmented storage mode, any certain segment of data can be archived, and the consistency of the data states of all nodes can be ensured. The data on the chain is ensured to be stable in a certain quantity, and the cost is greatly reduced and the system performance is increased while the disk space is effectively released.
In the step S4, the process of creating the archive image library includes:
1) Transforming the primarily processed inspection data into a zip compressed file;
2) Expanding a corresponding grid Type Raster Type according to the Type of the archival image;
3) Registering a Raster type dll to realize the support of the mosaic data set on the archival image;
4) And building a database by using the mosaic data set.
And selecting a Raster Type corresponding to the archival image in the image adding process. The mosaic dataset does not provide a library-building scheme for archival images, and for this data type can be stored in a conventional manner by Arc SDE. But can utilize the embedded dataset to realize archival image database construction through the mode of expanding the Raster Type, this mode improves image management efficiency and degree of automation.
In the step S4, the distributed storage database adopts an extensible distributed network storage system structure, uses a plurality of storage servers to share the storage load, uses a location server to locate the storage information, performs multi-copy backup on the data of each node, simultaneously selects one main copy capable of providing read/write service from a plurality of copies, and the other copies are used as standby copies, and the standby copies do not serve outside and only provide read-only service inside.
If a traditional network storage system is adopted, a centralized storage server is adopted to store all data, and the storage server becomes a bottleneck of system performance, is also a focus of reliability and safety, and cannot meet the requirements of large-scale storage application. The distributed network storage system adopts an expandable system structure, utilizes a plurality of storage servers to share the storage load, utilizes the position servers to position the storage information, improves the reliability, availability and access efficiency of the system, is easy to expand, and can ensure the system performance most importantly.
To ensure high reliability and availability of a distributed storage system, multiple copies of the data for each node need to be duplicated for backup:
the Primary copy (Primary) is typically only one and can provide read/write services;
there may be multiple Backup copies (Backup) without providing read-only services to the external service.
If the primary copy fails, one of the backup copies needs to be elected to become the new primary copy, which becomes an "election".
The election of the new primary copy may be performed through a master node lease protocol, a distributed lock, an election protocol such as the Paxos protocol, etc.
As shown in fig. 4, in order to solve the above technical problem, another technical solution provided by the present invention is: the unmanned aerial vehicle inspection data identification and management system based on the distributed storage based on the method is characterized in that: the system comprises a data acquisition module 41, an archiving management module 43, a storage module 44 and a control module 42, wherein the control module 42 is communicated with the data acquisition module 41, the archiving management module 43 and the storage module 44, and the system comprises the following components:
data acquisition module 41: receiving inspection data for inspecting the transmission line sent by the unmanned aerial vehicle in real time, and sending the acquired inspection data to the control module;
control module 42: preprocessing the inspection data sent by the data acquisition module, carrying out fault identification on the preprocessed inspection data, initiating a data archiving request after the fault identification, carrying out dump archiving on the inspection data with the fault identification, marking a fault part on the inspection data with the fault, and uploading the marked inspection data to an inspection system for data sharing;
archive management module 43: the method comprises the steps that a data set is inlaid in a mode of Raster Type expansion, so that the inspection data sent by a control module are archived and an image database is built;
storage module 44: and storing the archived inspection data by adopting an extensible distributed network storage system structure.
The above disclosed method steps are implemented by using the disclosed system.
As shown in fig. 5, in order to solve the above technical problem, another technical solution provided by the present invention is: unmanned aerial vehicle inspection data identification and management device based on distributed storage, characterized by comprising:
a memory 51 for storing a computer program;
and a processor 52 for reading and executing the computer program stored in the memory, wherein the processor performs the unmanned aerial vehicle inspection data identification and management method based on distributed storage.
The processor 52 is configured to control itself and the memory to implement the unmanned aerial vehicle inspection data identification and management method based on distributed storage. The processor 52 may also be referred to as a CPU (Central Processing Unit ). The processor 52 may be an integrated circuit chip having signal processing capabilities. Processor 52 may also be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a Field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The general purpose processor 52 may be a microprocessor or the processor 52 may be any conventional processor or the like. In addition, the processor 52 may be commonly implemented by an integrated circuit chip.
The foregoing description of various embodiments is intended to highlight differences between the various embodiments, which may be the same or similar to each other and is not repeated herein for the sake of brevity.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (9)
1. A unmanned aerial vehicle inspection data identification and management method based on distributed storage comprises the following steps:
step one, acquiring inspection data of an unmanned aerial vehicle on a power transmission line in real time, and performing primary processing on the acquired inspection data;
step two, performing fault identification on the primarily processed inspection data, marking fault parts of the inspection data with faults, and uploading the marked inspection data to an inspection system for data sharing;
step three, initiating a data archiving request, and carrying out dump archiving operation on the patrol data after fault identification;
and fourthly, utilizing the embedded data set to carry out archival image database construction on the patrol data ready for archival in a mode of extending the Raster Type, and storing the archival image database in a distributed storage database.
2. The unmanned aerial vehicle inspection data identification and management method based on distributed storage according to claim 1, wherein the method is characterized by comprising the following steps: in the first step, the inspection data includes: the SAR image of the inspection target in the power transmission line and the basic information of the power transmission line are contained.
3. The unmanned aerial vehicle inspection data identification and management method based on distributed storage according to claim 1, wherein the method is characterized by comprising the following steps: in the first step, the process of performing preliminary processing on the acquired inspection data is as follows: the SAR image is monitored and identified through the SAR automatic target identification system, noise of the SAR image is removed, an interested region is obtained, target classification identification is carried out on the interested region, and type marking is carried out according to the target type.
4. The unmanned aerial vehicle inspection data identification and management method based on distributed storage according to claim 1, wherein the method is characterized by comprising the following steps: in the second step, the fault identification process for the inspection data is as follows: and performing fault identification through an AI automatic identification technology.
5. The unmanned aerial vehicle inspection data identification and management method based on distributed storage according to claim 4, wherein the method is characterized by comprising the following steps: before fault identification, AI deep learning is performed through a training database, wherein the training database is formed by manually marking the pre-collected pictures.
6. The unmanned aerial vehicle inspection data identification and management method based on distributed storage according to claim 1, wherein the method is characterized by comprising the following steps: in the fourth step, the process of creating the archive image library is as follows:
1) Transforming the primarily processed inspection data into a zip compressed file;
2) Expanding a corresponding grid Type Raster Type according to the Type of the archival image;
3) Registering a Raster type dll to realize the support of the mosaic data set on the archival image;
4) And building a database by using the mosaic data set.
7. The unmanned aerial vehicle inspection data identification and management method based on distributed storage according to claim 1, wherein the method is characterized by comprising the following steps: in the fourth step, the distributed storage database adopts an extensible distributed network storage system structure, a plurality of storage servers are utilized to share storage load, a position server is utilized to position storage information, multi-copy copying and backup are carried out on data of each node, meanwhile, a main copy capable of providing read/write service is selected from a plurality of copies, the rest copies are used as standby copies, the standby copies do not serve outside, and only read-only service is provided inside.
8. A unmanned aerial vehicle inspection data identification and management system based on distributed storage based on the method of any one of claims 1-7, characterized in that: the system comprises a data acquisition module, an archiving management module, a storage module and a control module, wherein the real-time control module is communicated with the acquisition module, the archiving management module and the storage module, and the system comprises the following components:
and a data acquisition module: receiving inspection data for inspecting the transmission line sent by the unmanned aerial vehicle in real time, and sending the acquired inspection data to the control module;
and the control module is used for: preprocessing the inspection data sent by the data acquisition module, carrying out fault identification on the preprocessed inspection data, initiating a data archiving request after the fault identification, carrying out dump archiving on the inspection data with the fault identification, marking a fault part on the inspection data with the fault, and uploading the marked inspection data to an inspection system for data sharing;
an archiving management module: the method comprises the steps that a data set is inlaid in a mode of Raster Type expansion, so that the inspection data sent by a control module are archived and an image database is built;
and a storage module: and storing the archived inspection data by adopting an extensible distributed network storage system structure.
9. Unmanned aerial vehicle inspection data identification and management device based on distributed storage, characterized by comprising:
a memory for storing a computer program;
a processor for reading and executing the computer program stored in the memory, which processor, when executed, performs the unmanned aerial vehicle inspection data identification and management method based on distributed storage as claimed in any one of claims 1 to 7.
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| CN117389293A (en) * | 2023-10-31 | 2024-01-12 | 广州天海翔航空科技有限公司 | Flight control management method and system for inspection unmanned aerial vehicle |
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