CN216994838U - Photovoltaic module defect automatic identification device - Google Patents
Photovoltaic module defect automatic identification device Download PDFInfo
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- CN216994838U CN216994838U CN202220771712.3U CN202220771712U CN216994838U CN 216994838 U CN216994838 U CN 216994838U CN 202220771712 U CN202220771712 U CN 202220771712U CN 216994838 U CN216994838 U CN 216994838U
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Abstract
The utility model relates to the technical field of photovoltaic module defect identification, in particular to an automatic photovoltaic module defect identification device, which comprises an unmanned aerial vehicle and an edge calculation device, wherein the unmanned aerial vehicle comprises a mounting plate, a holder assembly is arranged at the bottom end of the mounting plate, the holder assembly comprises a rotating plate which is rotatably connected to the mounting plate, a push lug is fixedly arranged on one side of the circumferential outer wall of the rotating plate, a mounting block is fixed on one side of the bottom outer wall of the mounting plate, an electric telescopic rod II is connected between the mounting block and the push lug through a hinge, and a movable end plate is connected on one side of the bottom outer wall of the rotating plate through a hinge; when the unmanned aerial vehicle patrols and examines, double-light information of the component is acquired through a double-light image sensor carried on the unmanned aerial vehicle; the arranged holder component is utilized, the holder angle is adjusted according to the shooting angle parameter corresponding to each route point, the double-light image sensor is enabled to be perpendicular to the photovoltaic component for shooting, and therefore the shooting effect of the photovoltaic component is guaranteed.
Description
Technical Field
The utility model relates to the technical field of photovoltaic module defect identification, in particular to an automatic photovoltaic module defect identification device.
Background
The photovoltaic module is a core part in a solar power generation system and is also the most important part in the solar power generation system. The solar energy is converted into electric energy, or the electric energy is sent to a storage battery for storage, or a load is pushed to work.
However, when the photovoltaic module is actually put into use, the problems such as vegetation shielding, fixed facility shielding, surface stains, surface damage, internal defects and edge dust deposition are prone to occur, and the power generation effect of the photovoltaic module is affected; at present, the faults are mainly checked by maintenance personnel, the efficiency is low, and the fault elimination effect is poor, so that an automatic photovoltaic module defect identification device is urgently needed.
SUMMERY OF THE UTILITY MODEL
The utility model aims to provide a photovoltaic module defect automatic identification device to solve the problems in the background technology.
The technical scheme of the utility model is as follows: photovoltaic module defect automatic identification equipment, including unmanned aerial vehicle and edge calculation device, unmanned aerial vehicle includes the mounting panel, and the bottom of mounting panel is provided with cloud platform subassembly, cloud platform subassembly is including rotating the commentaries on classics board of connecting on the mounting panel, and changes circumference outer wall one side fixed mounting of board and push away the ear, bottom outer wall one side of mounting panel is fixed with the installation piece, and has electric telescopic handle two through hinged joint between installation piece and the push away the ear, there is movable end plate bottom outer wall one side of commentaries on classics board through hinged joint, and the tip fixed mounting of activity end plate has two optical image sensor, there is electric telescopic handle one through hinged joint between activity end plate and the commentaries on classics board, edge calculation device includes image segmentation processing module and fault identification calculation module.
Preferably, a controller is fixedly mounted on one side of the outer wall of the bottom of the mounting plate, and one side of the controller is electrically connected with a signal receiver and a signal transmitter respectively.
Preferably, the edge computing device is connected with the unmanned aerial vehicle through a wireless technology.
Preferably, the dual light image sensor is composed of a dual light camera.
Preferably, the top outer wall of the mounting plate is fixedly provided with the unmanned aerial vehicle shell, and the top outer wall of the mounting plate is fixedly provided with four extension arms.
Preferably, the end parts of the four extension arms are fixedly provided with motors, and the output shafts of the motors are fixedly connected with paddles.
Preferably, the two ends of the outer wall of the bottom of the mounting plate are fixedly provided with the supports.
Preferably, two the equal fixed mounting of one side outer wall of support has the small-size electric putter of level setting, and the equal fixed mounting of two small-size electric putter's extension rod tip has the protection casing, and the notch with the movable end board adaptation is all seted up on the top of two protection casings.
The utility model provides a photovoltaic module defect automatic identification device through improvement, and compared with the prior art, the photovoltaic module defect automatic identification device has the following improvements and advantages:
(1) when the unmanned aerial vehicle patrols and examines, double-light information of the component is acquired through a double-light image sensor carried on the unmanned aerial vehicle; the arranged holder component is utilized, the holder angle is adjusted according to the shooting angle parameter corresponding to each route point, so that the double-light image sensor is kept perpendicular to the photovoltaic component for shooting, and the shooting effect on the photovoltaic component is ensured; the specific operation method is that the second electric telescopic rod is used for pushing and pulling the push lug through the extension and retraction of the extension rod of the second electric telescopic rod, so that the rotary plate and the double-light image sensor are subjected to rotation adjustment; the elevation angles of the movable end plate and the double-light image sensor can be adjusted by utilizing the first electric telescopic rod, so that the double-light image sensor can be kept vertical to the photovoltaic module;
(2) the intelligent AI diagnosis and identification system firstly obtains the heating or abnormal position on the photovoltaic module through infrared light information; since the information on the infrared light information is limited and the cause of the failure cannot be well determined, the system is supplemented with visible light information. According to the fault position on the infrared picture and a conversion matrix obtained in advance, the system obtains the position of the fault on visible light; the system predefines the category which may cause the hot spot, and after the visible light pictures are classified, the specific reason causing the hot spot can be estimated.
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The utility model is further explained below with reference to the figures and examples:
FIG. 1 is a schematic overall perspective view of the present invention;
FIG. 2 is a perspective view of the mounting plate of the present invention;
FIG. 3 is an enlarged schematic view of the structure of FIG. 2 at A in accordance with the present invention;
FIG. 4 is a schematic structural diagram of a second embodiment of the present invention;
fig. 5 is a schematic flow diagram of the present invention.
Description of the reference numerals:
1. mounting a plate; 2. a support; 3. an extension arm; 4. a motor; 5. an unmanned aerial vehicle housing; 6. a paddle; 7. a dual-light image sensor; 8. a movable end plate; 9. a first electric telescopic rod; 10. an edge calculation device; 11. an image segmentation processing module; 12. a fault identification calculation module; 13. rotating the plate; 14. pushing the lug; 15. a second electric telescopic rod; 16. a controller; 17. a signal receiver; 18. a signal transmitter; 19. a protective cover; 20. a small electric push rod.
Detailed Description
The present invention is described in detail below, and technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
The utility model provides a photovoltaic module defect automatic identification device by improvement, and the technical scheme of the utility model is as follows:
the first embodiment is as follows:
as shown in fig. 1, fig. 2, fig. 3 and fig. 5 are shown, photovoltaic module defect automatic identification device, including unmanned aerial vehicle and edge calculating device 10, unmanned aerial vehicle includes mounting panel 1, and the bottom of mounting panel 1 is provided with cloud platform subassembly, cloud platform subassembly is including rotating the commentaries on classics board 13 of connecting on mounting panel 1, and the circumference outer wall one side fixed mounting who changes board 13 has push away ear 14, bottom outer wall one side of mounting panel 1 is fixed with the installation piece, and there is electric telescopic handle two 15 through hinged joint between installation piece and the push away ear 14, there is movable end plate 8 bottom outer wall one side of commentaries on classics board 13 through hinged joint, and the tip fixed mounting of movable end plate 8 has two light image sensor 7, there is electric telescopic handle one 9 through hinged joint between movable end plate 8 and the commentaries on classics board 13, edge calculating device 10 includes image segmentation processing module 11 and fault identification calculating module 12.
By means of the structure, when the unmanned aerial vehicle patrols and examines, double-light information of the components is obtained through the double-light image sensor 7 carried on the unmanned aerial vehicle; the intelligent AI diagnosis and identification system obtains the heating or abnormal position on the photovoltaic module through infrared light information; since the information on the infrared light information is limited and the cause of the failure cannot be well determined, the system is supplemented with visible light information. And according to the fault position on the infrared picture and a conversion matrix obtained in advance, the system obtains the position of the fault on the visible light.
Further, a controller 16 is fixedly installed on one side of the outer wall of the bottom of the mounting plate 1, and one side of the controller 16 is electrically connected with a signal receiver 17 and a signal emitter 18 respectively.
Further, the edge computing device 10 is connected to the drone via wireless technology.
Further, the dual light image sensor 7 is composed of a dual light camera.
By means of the structure, the angle of the cradle head is adjusted according to the shooting angle parameters corresponding to each route point by using the set cradle head component, so that the double-light image sensor 7 is kept perpendicular to the photovoltaic component for shooting; the specific operation method is that the second electric telescopic rod 15 is used for pushing and pulling the push lug 14 through the extension and retraction of the extension rod of the second electric telescopic rod, so that the rotating plate 13 and the dual-light image sensor 7 are subjected to rotation adjustment processing; by means of the arranged electric telescopic rod I9, the elevation angles of the movable end plate 8 and the double-light image sensor 7 can be adjusted, and therefore the double-light image sensor 7 can be kept perpendicular to the photovoltaic module.
Further, the top outer wall of the mounting plate 1 is fixedly provided with an unmanned aerial vehicle shell 5, and the top outer wall of the mounting plate 1 is fixedly provided with four extension arms 3.
Further, the end parts of the four extension arms 3 are fixedly provided with motors 4, and output shafts of the motors 4 are fixedly connected with paddles 6.
Further, the two ends of the outer wall of the bottom of the mounting plate 1 are fixedly provided with a support 2.
It should be noted that: the unmanned aerial vehicle and the edge computing device 10 are both connected with an external system.
The working principle is as follows: when the unmanned aerial vehicle patrols and examines, the double-light information of the component is obtained through a double-light image sensor 7 carried on the unmanned aerial vehicle; adjusting the angle of the cradle head according to shooting angle parameters corresponding to all route points by using the set cradle head component, so that the double-light image sensor 7 keeps vertical to the photovoltaic component for shooting; the specific operation method is that the second electric telescopic rod 15 is used for pushing and pulling the push lug 14 through the extension and retraction of the extension rod, so that the rotating plate 13 and the dual-light image sensor 7 are subjected to rotation adjustment processing; the elevation angles of the movable end plate 8 and the double-light image sensor 7 can be adjusted by using the first electric telescopic rod 9, so that the double-light image sensor 7 can be kept vertical to the photovoltaic module; the intelligent AI diagnosis and identification system obtains the heating or abnormal position on the photovoltaic module through infrared light information; since the information on the infrared light information is limited and the cause of the failure cannot be well determined, the system is supplemented with visible light information. According to the fault position on the infrared picture and a conversion matrix obtained in advance, the system obtains the position of the fault on visible light; the system predefines the category which may cause the hot spot, and after the visible light pictures are classified, the specific reason causing the hot spot can be estimated;
specifically, the faults that can be identified by the infrared light picture include: hot spots, diode failure, string shorts, open string and component missing. The system reclassifies hot spot faults by utilizing visible light pictures, and the fault types are as follows: vegetation shelter, fixed facility shelter, surface smudge, surface damage, internal defects, and edge dust. And classifying the diode faults, wherein the fault types are as follows: vegetation shielding, fixed facility shielding, surface damage and diode failure;
after the system obtains the position of the fault on the picture and the fault category through an AI algorithm, the geographical position information of the fault component also needs to be known. The current systems support geographical location estimation of faulty components by video or pictures. When video data are collected, GPS information and time stamps of the unmanned aerial vehicle during flying need to be additionally provided, and the system utilizes an offline monocular vision synchronous positioning and Mapping (SLAM) algorithm to quickly estimate the camera attitude of each frame in the video and construct a point cloud. By combining the GPS information of the unmanned aerial vehicle, the system can estimate the latitude, longitude and altitude of each point in the point cloud. When collecting picture data, each picture needs to have a certain overlapping degree. Latitude and longitude information and timestamps are typically already stored in the picture files. The system utilizes a motion recovery from motion (SFM) algorithm to estimate the camera pose of each picture and construct a dense point cloud. The latitude and longitude and the elevation of each point on the point cloud can be estimated by utilizing the latitude and longitude information on the picture. The points on the point cloud have corresponding positions on the picture, and if the fault frame has the points corresponding to the point cloud, the longitude and latitude of the fault can be known.
Example two:
as shown in fig. 4, photovoltaic module defect automatic identification equipment, this embodiment compares in embodiment one, and the equal fixed mounting of one side outer wall of two supports 2 has the small-size electric putter 20 of level setting, and the equal fixed mounting of the extension rod tip of two small-size electric putter 20 has protection casing 19, and the notch with activity end plate 8 looks adaptation is all seted up on the top of two protection casings 19, and the protection casing 19 of being convenient for is through activity end plate 8 and then fold.
Borrow by above-mentioned structure, after the completion was discerned the trouble of photovoltaic module, the extension rod of electric telescopic handle 9 can be taken back out to pack up the two light image sensor 7 of 8 tip of movable end plate, at this moment, personnel can take place signal instruction to unmanned aerial vehicle, controller 16 utilizes signal receiver 17 to receive corresponding signal after, the extension rod of steerable two small-size electric putter 20 stretches out, and make two protection casings 19 fold mutually, play good guard action to two light image sensor 7.
Claims (8)
1. Photovoltaic module defect automatic identification equipment, including unmanned aerial vehicle and edge calculating device (10), unmanned aerial vehicle includes mounting panel (1), and the bottom of mounting panel (1) is provided with cloud platform subassembly, its characterized in that: cloud platform subassembly is including rotating commentaries on classics board (13) of connecting on mounting panel (1), and the circumference outer wall one side fixed mounting who changes board (13) pushes away ear (14), bottom outer wall one side of mounting panel (1) is fixed with the installation piece, and installs the piece and push away and have electric telescopic handle two (15) through hinged joint between ear (14), there is movable end plate (8) bottom outer wall one side of commentaries on classics board (13) through hinged joint, and the tip fixed mounting of activity end plate (8) has two light image sensor (7), there is one (9) of electric telescopic handle through hinged joint between activity end plate (8) and the commentaries on classics board (13), processing module (11) and fault identification calculation module (12) are cut apart including the image to edge calculation device (10).
2. The automatic photovoltaic module defect identification device according to claim 1, characterized in that: the bottom outer wall one side fixed mounting of mounting panel (1) has controller (16), and one side electric connection of controller (16) has signal receiver (17) and signal transmitter (18) respectively.
3. The automatic photovoltaic module defect identification device according to claim 2, characterized in that: the edge computing device (10) is connected with the unmanned aerial vehicle by wireless technology.
4. The photovoltaic module defect automatic identification device according to claim 1, characterized in that: the double-light image sensor (7) is composed of double-light cameras.
5. The photovoltaic module defect automatic identification device according to claim 1, characterized in that: the top outer wall fixed mounting of mounting panel (1) has unmanned aerial vehicle casing (5), and mounting panel (1) top outer wall fixed mounting has four extension arms (3).
6. The device for automatically identifying defects of photovoltaic modules according to claim 5, wherein: four the equal fixed mounting in tip of extension arm (3) has motor (4), and the output shaft fixedly connected with paddle (6) of motor (4).
7. The photovoltaic module defect automatic identification device according to claim 1, characterized in that: and the two ends of the outer wall of the bottom of the mounting plate (1) are fixedly provided with a bracket (2).
8. The device for automatically identifying defects of photovoltaic modules according to claim 7, wherein: two the equal fixed mounting of one side outer wall of support (2) has small-size electric putter (20) that the level set up, and the equal fixed mounting of extension rod tip of two small-size electric putter (20) has protection casing (19), and the notch with activity end plate (8) looks adaptation is all seted up on the top of two protection casings (19).
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202220771712.3U CN216994838U (en) | 2022-04-02 | 2022-04-02 | Photovoltaic module defect automatic identification device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202220771712.3U CN216994838U (en) | 2022-04-02 | 2022-04-02 | Photovoltaic module defect automatic identification device |
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| CN216994838U true CN216994838U (en) | 2022-07-19 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116667775A (en) * | 2023-07-14 | 2023-08-29 | 北京国领智能科技有限公司 | Unmanned aerial vehicle-based photovoltaic electric field automatic cleaning method and system |
| CN116707445A (en) * | 2023-08-04 | 2023-09-05 | 华能新能源股份有限公司山西分公司 | Photovoltaic module fault positioning method and system |
-
2022
- 2022-04-02 CN CN202220771712.3U patent/CN216994838U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116667775A (en) * | 2023-07-14 | 2023-08-29 | 北京国领智能科技有限公司 | Unmanned aerial vehicle-based photovoltaic electric field automatic cleaning method and system |
| CN116707445A (en) * | 2023-08-04 | 2023-09-05 | 华能新能源股份有限公司山西分公司 | Photovoltaic module fault positioning method and system |
| CN116707445B (en) * | 2023-08-04 | 2023-11-03 | 华能新能源股份有限公司山西分公司 | Photovoltaic module fault positioning method and system |
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