CN117523389A - Unmanned aerial vehicle cruises disease discernment and 3D location management system - Google Patents
Unmanned aerial vehicle cruises disease discernment and 3D location management system Download PDFInfo
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Abstract
The invention relates to the technical field of unmanned aerial vehicle cruising, in particular to an unmanned aerial vehicle cruising disease identification and 3D positioning management system, which comprises a cruising end and a management end connected with the cruising end through a network; the cruising end comprises a first transmission unit and an acquisition module connected with the first transmission unit; the acquisition module comprises a first positioning unit and an image acquisition unit; the first positioning unit consists of horizontal positioning and vertical positioning; the acquisition module transmits acquired data to the management end through a first transmission unit; the management end comprises a second transmission unit and a management module connected with the second transmission unit; according to the invention, the damage position of the bridge is projected to the surface of the bridge model to form the record, so that the damage position of the bridge is quickly and intuitively found in the subsequent maintenance process of the bridge by maintenance personnel, the time for searching the damage position of the bridge is greatly reduced, and the bridge maintenance efficiency of the maintenance personnel is improved.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle cruising, in particular to an unmanned aerial vehicle cruising disease identification and 3D positioning management system.
Background
The unmanned aerial vehicle cruising device can be suitable for farmland crop monitoring, forest disease monitoring, building inspection, infrastructure safety monitoring, environment monitoring and wind farm/solar farm inspection; the unmanned aerial vehicle is provided with a high-resolution camera and an image processing algorithm, so that the comprehensive and efficient cruising can be carried out on the bridge and road surfaces in the infrastructure, and various diseases such as cracks, bulges, falling blocks, rust and the like can be detected and identified in real time; and timely discovering structural defects, problems and risks, and providing corresponding management and maintenance plans.
The bridge in the infrastructure utilizes unmanned aerial vehicle to cruise and is common disease recognition mode, and unmanned aerial vehicle cruises's time increases and prolongs according to bridge's size and disease degree, and unmanned aerial vehicle cruises's the position of disease of taking notes the bridge that the camera that the unmanned aerial vehicle was taken with oneself carried, and the transmission is carried back to the management end and is recorded, and to some bridges that drop into operation comparatively far away, disease condition and disease's position are more, and unmanned aerial vehicle cruises the image that the transmission was comparatively numerous, so in follow-up maintenance personnel to maintain or repair the bridge, the position of disease that the feedback will be a time consuming loaded down with trivial details process when seeking unmanned aerial vehicle cruises.
In view of the above, the present invention provides an unmanned aerial vehicle cruise disease recognition and 3D positioning management system, which solves the above technical problems.
Disclosure of Invention
In order to make up for the defects of the prior art, the invention provides the unmanned aerial vehicle cruise disease identification and 3D positioning management system, and the disease position of the bridge is projected to the surface of the bridge model to form a record, so that the disease position of the bridge is quickly and intuitively found in the subsequent maintenance process of the bridge by maintenance personnel, the time for searching the bridge disease position is greatly reduced, and the bridge maintenance efficiency of the maintenance personnel is improved.
The invention relates to an unmanned aerial vehicle cruise disease identification and 3D positioning management system, which comprises a cruise end and a management end connected with the cruise end through a network; the cruising end comprises a first transmission unit and an acquisition module connected with the first transmission unit; the acquisition module comprises a first positioning unit and an image acquisition unit; the first positioning unit consists of horizontal positioning and vertical positioning; the first positioning unit takes a positioning element as a carrier, such as a GPS; the image acquisition unit takes image acquisition equipment as a carrier, such as a camera; the acquisition module transmits acquired data to the management end through a first transmission unit;
the management end comprises a second transmission unit and a management module connected with the second transmission unit; the management module comprises a model processing unit and an analysis unit; the model processing unit is used for generating, modifying and exporting a model; the model processing unit can mark the model according to the analysis result of the analysis unit; the cruising end takes an unmanned plane as a carrier, and the management end takes a server as a carrier; the model processing unit is used for importing a bridge three-dimensional model from a system of a bridge design or construction department according to a bridge name, the first positioning unit is used for acquiring the horizontal position and the vertical position, namely the space position, of the unmanned aerial vehicle in real time, the first positioning unit is used for transmitting the space position of the unmanned aerial vehicle to the first transmission unit through the acquisition module, transmitting the space position of the unmanned aerial vehicle to the second transmission unit through the first transmission unit, transmitting the space position of the unmanned aerial vehicle to the model processing unit in the management module through the second transmission unit in real time, and capturing the position of the bridge by the model processing unit according to a navigation system such as a GPS (global positioning system) and the like, so that the relative position between the bridge and the unmanned aerial vehicle is obtained; and a maintainer can quickly and intuitively obtain the disease position of the actual bridge according to the red system position in the corresponding bridge model in the model processing unit.
Preferably, the management module further comprises a comparison unit; the contrast unit can extract building contours in the image data of the image acquisition unit to form image data characteristics; the comparison unit can also extract the outline of model data perceived by the cruising object model at the same position and angle in the model processing unit to form cruising object model characteristics; the comparison unit compares the image data characteristics with cruising object model characteristics; the model processing unit selectively projects the image data to the cruising object model according to the comparison result of the comparison unit; the cruiser is the bridge.
Preferably, the management module further comprises a feedback unit; the comparison unit and the analysis unit feed back the comparison result and the analysis result to the feedback unit in real time; the feedback unit can generate adjustment measures according to feedback content and transmit the adjustment measures back to the acquisition module by using the second transmission unit and the first transmission unit.
Preferably, the analysis unit can collect statistics on the disease positions of the cruising object, and the feedback unit can match corresponding image acquisition time according to the number of the disease positions of the cruising object.
Preferably, the management module comprises a cruise unit; the cruising unit can record the position and the angle of the first unmanned aerial vehicle in the shooting state to generate an original position; the position of the unmanned aerial vehicle recorded by the cruising unit is the position of the relative bridge; the cruising unit transmits the original position to a cruising end through a second transmission unit; and the cruising end cruises the unmanned aerial vehicle according to the original position.
Preferably, the cruising unit records the position and the angle of the unmanned aerial vehicle in the shooting state again to generate a cruising position; the comparison unit compares the cruising position with the original position; the feedback unit can timely feed back to the cruising end according to the comparison result of the comparison unit.
Preferably, the model processing unit completes image data projection of the model; the analysis unit can carry out overall simulation analysis of cruising objects according to all disease images.
Preferably, the model processing unit is capable of adjusting image data parameters on the model; the analysis unit can pour out a deduction result according to the image data parameters regulated by the model processing unit.
The beneficial effects of the invention are as follows:
1. according to the invention, the damage position of the bridge is projected to the surface of the bridge model to form the record, so that the damage position of the bridge is quickly and intuitively found in the subsequent maintenance process of the bridge by maintenance personnel, the time for searching the damage position of the bridge is greatly reduced, and the bridge maintenance efficiency of the maintenance personnel is improved.
2. According to the invention, after the feedback unit obtains feedback, the feedback unit can send out a re-shooting instruction, and generates a focal length adjustment instruction of the unmanned aerial vehicle camera according to the enlarged or reduced position of the image data, and after the feedback unit transmits the instruction to the cruising end through the second transmission unit, no one can re-shoot the image data according to the instruction, and adjust according to the focal length adjustment instruction, so that the accuracy of bridge disease identification is ensured.
3. In the process of image acquisition of the unmanned aerial vehicle, the cruise unit captures the position data and shooting angle at the moment of image acquisition by the image acquisition unit, namely the cruise position, and the image data shot for the second time and the original image data are the same position and angle under the condition that the cruise position corresponds to the original position, so that the analysis of the analysis unit is facilitated, the analysis unit can judge the degree change condition of the bridge diseases according to the image data at the same position and angle, and the stability of the bridge is ensured.
Drawings
The invention will be further described with reference to the drawings and embodiments.
Fig. 1 is a block flow diagram of a system in accordance with the present invention.
Detailed Description
The invention is further described in connection with the following detailed description in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
As shown in FIG. 1, the unmanned aerial vehicle cruise disease recognition and 3D positioning management system comprises a cruise end and a management end connected with the cruise end through a network; the cruising end comprises a first transmission unit and an acquisition module connected with the first transmission unit; the acquisition module comprises a first positioning unit and an image acquisition unit; the first positioning unit consists of horizontal positioning and vertical positioning; the first positioning unit takes a positioning element as a carrier, such as a GPS; the image acquisition unit takes image acquisition equipment as a carrier, such as a camera; the acquisition module transmits acquired data to the management end through a first transmission unit;
the management end comprises a second transmission unit and a management module connected with the second transmission unit; the management module comprises a model processing unit and an analysis unit; the model processing unit is used for generating, modifying and exporting a model; the model processing unit can mark the model according to the analysis result of the analysis unit; the cruising end takes an unmanned plane as a carrier, and the management end takes a server as a carrier;
when the system is used, the bridge in the infrastructure is cruising by using the unmanned aerial vehicle as a common disease identification mode, the cruising time of the unmanned aerial vehicle is prolonged according to the body type of the bridge and the increase of the disease degree, the unmanned aerial vehicle can record the disease position of the bridge by using a camera carried by the unmanned aerial vehicle and send the disease position back to a management end for recording, and for some long-running bridges, the disease condition and the disease position are more, the image sent back by cruising of the unmanned aerial vehicle is more, so that the searching for the disease position fed back by cruising of the unmanned aerial vehicle is a time-consuming and tedious process for subsequent maintenance personnel to maintain or repair the bridge;
therefore, the invention starts the first positioning unit in the acquisition module of the cruising end before the unmanned aerial vehicle cruises, obtains the bridge name currently required to cruise according to the position of the first positioning unit and matching with the electronic map, then the model processing unit leads in the three-dimensional model of the bridge from the system of the bridge design or construction department according to the bridge name, the first positioning unit can acquire the horizontal position and the vertical position, namely the space position, of the unmanned aerial vehicle in real time, the first positioning unit can transmit the space position of the unmanned aerial vehicle to the first transmission unit through the acquisition module, the first transmission unit transmits the space position to the second transmission unit, the second transmission unit transmits the space position to the model processing unit in the management module in real time, the position of the bridge is captured by the model processing unit according to the navigation system such as GPS, so the relative position between the bridge and the unmanned aerial vehicle is obtained, the model processing unit can update the space position of the unmanned aerial vehicle in the bridge model in real time, the image acquisition unit can shoot each structure of the bridge along with the movement of the unmanned aerial vehicle, the image acquisition unit can acquire image data of each structure of the bridge under different angles, meanwhile, the orientation of a camera in the unmanned aerial vehicle can be acquired, then the image acquisition unit can transmit the acquired image data and the position data of the lens orientation data communicated with the first positioning unit to the first transmission unit, the first transmission unit can transmit the data acquired by the acquisition module to the management module through the second transmission unit in real time, the model processing unit can update the space position of the unmanned aerial vehicle model in the bridge model in real time, meanwhile, the model processing unit can update the camera orientation of the unmanned aerial vehicle camera captured by the image acquisition unit in the bridge model, the analysis unit can analyze the image data acquired by the image acquisition unit, and the disease identification is carried out by analyzing the disease characteristics such as cracks, bulges, falling blocks, rust and the like in the image data, the analysis unit can also analyze the data of the infrared thermal image shot by the unmanned aerial vehicle, identify potential hidden diseases such as water leakage, concrete defects and the like, the analysis unit can identify the image data into a disease image and a non-disease image, the model processing unit can project the disease image and the non-disease image onto the bridge model according to the analysis result of the analysis unit, the disease image is marked into a red system, the non-disease image is marked into a green system, the deeper the red system is more seriously represented, the green system is deeper, the bridge is more firm and reliable, and the position of the disease image and the non-disease image projected onto the bridge model is more accurate, and the model processing unit needs to be combined with the camera orientation of the bridge in the process of marking the image data; thus completing the process of identifying and positioning the diseases on the bridge; a maintainer can quickly and intuitively obtain the disease position of the actual bridge according to the red system position in the corresponding bridge model in the model processing unit;
according to the invention, the damage position of the bridge is projected to the surface of the bridge model to form the record, so that the damage position of the bridge is quickly and intuitively found in the subsequent maintenance process of the bridge by maintenance personnel, the time for searching the damage position of the bridge is greatly reduced, and the bridge maintenance efficiency of the maintenance personnel is improved.
As an embodiment of the present invention, the management module further includes a comparison unit; the contrast unit can extract building contours in the image data of the image acquisition unit to form image data characteristics; the comparison unit can also extract the outline of model data perceived by the cruising object model at the same position and angle in the model processing unit to form cruising object model characteristics; the comparison unit compares the image data characteristics with cruising object model characteristics; the model processing unit selectively projects the image data to the cruising object model according to the comparison result of the comparison unit; the cruiser is a bridge;
during the use, in order to make image data projection more accurate in the position on the bridge model, before image data projection is in the corresponding position on the bridge model, the contrast unit can draw the building contour in the image data and form image data feature, for example image data expresses and just the below pier quantity that exposes is four in the position of a bridge support, the contrast unit can also draw the bridge model contour and form bridge model feature, the bridge model in the model processing unit, unmanned aerial vehicle model corresponds the simulation with the angle of actual unmanned aerial vehicle's position and camera, the bridge model under unmanned aerial vehicle model's camera carries out the building contour and draws, thereby form bridge model feature, for example, the bridge model feature also is the position of a bridge support and the below pier quantity that exposes is four, the two can coincide under the same proportion, so represent same position and angle, the result that the contrast unit contrasts the bridge is correct, if the two can not coincide under the same proportion coincidence building contour line, represent not in same position and angle, the result that contrast unit contrasts is wrong, under the contrast result, the condition, the processing unit can be with the image model position can be more accurate to the position on the bridge model is guaranteed to follow-up, more accurate position can be found to the image data on the bridge, and more accurate maintenance model.
As an embodiment of the present invention, the management module further includes a feedback unit; the comparison unit and the analysis unit feed back the comparison result and the analysis result to the feedback unit in real time; the feedback unit can generate an adjusting measure according to the feedback content and transmit the adjusting measure back to the acquisition module by using the second transmission unit and the first transmission unit;
when the unmanned aerial vehicle is used, the comparison unit is partially overlapped with the result of the comparison of the image data characteristics and the model data characteristics, for example, the right half part of the image data characteristics and the left half part of the model data characteristics can be overlapped, after the comparison unit transmits the comparison result to the feedback unit, the feedback unit can generate adjustment measures, namely, the camera of the unmanned aerial vehicle deflects towards the right side, so that the aim of overlapping the image data characteristics and the model data characteristics building outline is fulfilled, and the feedback unit can transmit the adjustment measures to the image acquisition unit in the acquisition module through the first transmission unit and the first transmission unit, so that the unmanned aerial vehicle makes corresponding changes; in the process of analyzing the image data, if the image is too fuzzy or the image data needs to be amplified or reduced, the feedback unit sends out a re-shooting instruction after feedback is obtained, and generates a focal length adjustment instruction of the unmanned aerial vehicle camera according to the amplified or reduced position of the image data, and after the instruction is transmitted to the cruising end through the second transmission unit, the feedback unit can re-shoot the image data according to the instruction, adjust according to the focal length adjustment instruction, so that the accuracy of bridge disease identification is ensured.
As an implementation mode of the invention, the analysis unit can collect and count the type disease positions of the cruising object, and the feedback unit can match corresponding image acquisition time according to the number of the type disease positions of the cruising object;
when the device is used, the analysis unit can count the disease positions of the bridge according to the positions of the bridge, such as piers, supports and the like, so that statistics data of the disease numbers of all the positions of the bridge are obtained, the disease statistics results of all the positions of the bridge are sequenced from high to low, the higher the counted data of the disease positions of the bridge is, the more the disease positions of the bridge are, the feedback unit can generate corresponding image acquisition time after obtaining the data analyzed by the analysis unit, namely, the more the disease positions of the bridge are, the longer the image acquisition time generated by the feedback unit is, the feedback unit can feed back adjustment measures to the unmanned aerial vehicle, and the unmanned aerial vehicle can prolong the image acquisition time at some high-incidence bridge disease positions.
As an embodiment of the present invention, the management module includes a cruise unit; the cruising unit can record the position and the angle of the first unmanned aerial vehicle in the shooting state to generate an original position; the position of the unmanned aerial vehicle recorded by the cruising unit is the position of the relative bridge; the cruising unit transmits the original position to a cruising end through a second transmission unit; and the cruising end cruises the unmanned aerial vehicle according to the original position.
As an implementation mode of the invention, the cruising unit records the position and the angle of the unmanned aerial vehicle in the re-shooting state to generate a cruising position; the comparison unit compares the cruising position with the original position; the feedback unit timely feeds back to the cruising end according to the comparison result of the comparison unit;
when the system is used, in the process of identifying the first cruising disease of the unmanned aerial vehicle, the cruising unit records the photographed position data and photographed angle data of the unmanned aerial vehicle and generates an original position, in order to facilitate the follow-up analysis of the disease position and the control of the disease degree of the bridge, the image acquisition unit is preferably used for photographing the disease position of the bridge at the same position and under the same angle, so that the comparison analysis is convenient, in order to ensure the real-time of the process, in the process of secondarily collecting the image of the unmanned aerial vehicle, the cruising unit captures the instantaneous position data and photographed angle, namely the cruising position, under the condition that the cruising position corresponds to the original position, the image data representing the secondary photographing is the same position and angle as the original image data, so that the analysis of the analysis unit is convenient, the analysis unit can judge the degree change condition of the bridge disease degree according to the image data at the same position and under the same angle, and the stability of the bridge is ensured.
As one embodiment of the present invention, the model processing unit performs image data projection of the model; the analysis unit can carry out overall simulation analysis of cruising objects according to all disease images.
As an embodiment of the present invention, the model processing unit is capable of adjusting image data parameters on a model; the analysis unit can pour out a deduction result according to the image data parameters regulated by the model processing unit;
when the method is used, after projection on the model is completed through image data, the damage position of the bridge model is increased compared with the original intact bridge model, so that the analysis unit can analyze the whole bridge under the condition that the bridge damage position is available, so as to obtain the whole bridge analysis result, after the analysis result is analyzed by related departments, timely maintenance is carried out, or measures for limiting the weight of vehicles are taken, more importantly, after the current bridge damage analysis is completed, the model processing unit can adjust image data parameters, accurately adjust the parameters of the damage image, so that the damage position of the bridge model is further enlarged, for example, the rust parameter is increased, the cracking value of a rubber pad is increased, the water leakage amount is increased, so that the analysis unit can analyze the bridge model according to the adjusted damage data, obtain the deduced bridge damage development condition, and take reference for the maintenance of the related departments, and also take precaution for the safety of the bridge; the bridge disease development conditions deduced by the analysis unit are convinced by taking historical disease data of other bridges as references; and through analysis of the analysis unit, early warning is made for monitoring the cruising diseases of the bridge.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (8)
1. Unmanned aerial vehicle cruises disease discernment and 3D location management system, its characterized in that: the system comprises a cruising end and a management end connected with the cruising end through a network; the cruising end comprises a first transmission unit and an acquisition module connected with the first transmission unit; the acquisition module comprises a first positioning unit and an image acquisition unit; the first positioning unit consists of horizontal positioning and vertical positioning; the acquisition module transmits acquired data to the management end through a first transmission unit;
the management end comprises a second transmission unit and a management module connected with the second transmission unit; the management module comprises a model processing unit and an analysis unit; the model processing unit is used for generating, modifying and exporting a model; the model processing unit can mark the model according to the analysis result of the analysis unit.
2. The unmanned aerial vehicle cruise disease recognition and 3D positioning management system according to claim 1, wherein: the management module further comprises a comparison unit; the contrast unit can extract building contours in the image data of the image acquisition unit to form image data characteristics; the comparison unit can also extract the outline of model data perceived by the cruising object model at the same position and angle in the model processing unit to form cruising object model characteristics; the comparison unit compares the image data characteristics with cruising object model characteristics; and the model processing unit selectively projects the image data to the cruising object model according to the comparison result of the comparison unit.
3. The unmanned aerial vehicle cruise disease recognition and 3D positioning management system according to claim 2, wherein: the management module further comprises a feedback unit; the comparison unit and the analysis unit feed back the comparison result and the analysis result to the feedback unit in real time; the feedback unit can generate adjustment measures according to feedback content and transmit the adjustment measures back to the acquisition module by using the second transmission unit and the first transmission unit.
4. The unmanned aerial vehicle cruise disease recognition and 3D positioning management system according to claim 3, wherein: the analysis unit can collect and count the type disease positions of the cruising object, and the feedback unit can be matched with corresponding image acquisition time according to the number of the type disease positions of the cruising object.
5. The unmanned aerial vehicle cruise disease recognition and 3D positioning management system according to claim 3, wherein: the management module comprises a cruising unit; the cruising unit can record the position and the angle of the first unmanned aerial vehicle in the shooting state to generate an original position; the cruising unit transmits the original position to a cruising end through a second transmission unit; and the cruising end cruises the unmanned aerial vehicle according to the original position.
6. The unmanned aerial vehicle cruise disease recognition and 3D positioning management system according to claim 5, wherein: the cruising unit records the position and the angle of the unmanned aerial vehicle in the shooting state again to generate a cruising position; the comparison unit compares the cruising position with the original position; the feedback unit can timely feed back to the cruising end according to the comparison result of the comparison unit.
7. The unmanned aerial vehicle cruise disease identification and 3D positioning management system of claim 6, wherein: the model processing unit finishes image data projection of the model; the analysis unit can carry out overall simulation analysis of cruising objects according to all disease images.
8. The unmanned aerial vehicle cruise disease identification and 3D positioning management system of claim 7, wherein: the model processing unit can adjust image data parameters on the model; the analysis unit can pour out a deduction result according to the image data parameters regulated by the model processing unit.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103247056A (en) * | 2013-05-29 | 2013-08-14 | 中国人民解放军第三军医大学第一附属医院 | Three-dimensional model to two-dimensional image space registering method of human body bone joint system |
CN109444171A (en) * | 2018-09-18 | 2019-03-08 | 山东理工大学 | Integrated Bridges Detection based on unmanned plane |
CN111999298A (en) * | 2020-06-30 | 2020-11-27 | 南京林业大学 | Unmanned aerial vehicle bridge system of patrolling and examining fast based on 5G technique |
US20210349476A1 (en) * | 2018-09-20 | 2021-11-11 | China Construction Science & Technology Group Co., Ltd. | Method and apparatus for controlling cruise of unmanned air vehicle based on prefabricated construction platform |
CN115700753A (en) * | 2022-10-25 | 2023-02-07 | 华能阳江风力发电有限公司 | Unmanned aerial vehicle patrols and examines image defect identification system based on mobile terminal technique |
CN116631087A (en) * | 2023-07-20 | 2023-08-22 | 厦门闽投科技服务有限公司 | Unmanned aerial vehicle-based electric power inspection system |
-
2023
- 2023-11-07 CN CN202311470511.5A patent/CN117523389A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103247056A (en) * | 2013-05-29 | 2013-08-14 | 中国人民解放军第三军医大学第一附属医院 | Three-dimensional model to two-dimensional image space registering method of human body bone joint system |
CN109444171A (en) * | 2018-09-18 | 2019-03-08 | 山东理工大学 | Integrated Bridges Detection based on unmanned plane |
US20210349476A1 (en) * | 2018-09-20 | 2021-11-11 | China Construction Science & Technology Group Co., Ltd. | Method and apparatus for controlling cruise of unmanned air vehicle based on prefabricated construction platform |
CN111999298A (en) * | 2020-06-30 | 2020-11-27 | 南京林业大学 | Unmanned aerial vehicle bridge system of patrolling and examining fast based on 5G technique |
CN115700753A (en) * | 2022-10-25 | 2023-02-07 | 华能阳江风力发电有限公司 | Unmanned aerial vehicle patrols and examines image defect identification system based on mobile terminal technique |
CN116631087A (en) * | 2023-07-20 | 2023-08-22 | 厦门闽投科技服务有限公司 | Unmanned aerial vehicle-based electric power inspection system |
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