Marine photovoltaic laser bird repelling system and method, medium and electronic equipment

Abstract

The invention provides a photovoltaic laser bird repelling system applied to the sea, a photovoltaic laser bird repelling method applied to the sea, a computer readable storage medium and electronic equipment, and relates to the technical field of bird repelling. The laser bird repelling system comprises a plurality of supporting piles and laser bird repelling equipment arranged at one end of each supporting pile. The laser is mounted on the rotating table; a laser driving unit; the data processing unit is used for acquiring a scene image, identifying the scene image, performing depth estimation by using the scene image under the condition that a bird object is identified so as to determine the distance of the bird object relative to the laser bird repelling equipment, and performing depth estimation by using the scene image under the condition that the distance is smaller than or equal to a distance threshold value; a rotation instruction is sent to the rotating table to control the laser transmitting end of the laser to rotate to be matched with the direction of the bird object, and the laser driving unit is controlled to drive the laser to work. According to the invention, automatic bird repelling control in an offshore photovoltaic scene can be realized.

Description

Background Art

[0002] The photovoltaic modules of offshore photovoltaics are installed in the outdoor environment at sea. Birds are prone to stay and build nests on the photovoltaic modules. Their excrement will also contaminate the photovoltaic modules, causing the normal operation of the photovoltaic modules to be affected. In severe cases, the photovoltaic modules may be damaged.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0004] The purpose of the present disclosure is to provide a laser bird repellent system applied to offshore photovoltaics, a laser bird repellent method applied to offshore photovoltaics, a computer-readable storage medium and an electronic device, thereby overcoming the adverse effects of bird activities on offshore photovoltaics at least to a certain extent.

[0005] According to a first aspect of the present disclosure, a laser bird-repelling system applied to offshore photovoltaics is provided, comprising a plurality of support piles and a laser bird-repelling device arranged at one end of each support pile, wherein each support pile is distributed at different positions outside the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repelling device, and the other end of the support pile is fixed to the seabed by a pile sinking process; wherein the laser bird-repelling device comprises: a rotating table for rotating in response to a rotation instruction; a laser mounted on the rotating table; a laser driving unit for driving the laser to work; a data processing unit for acquiring a scene image, identifying the scene image, and when a bird object is identified, using the scene image to perform depth estimation to determine the distance of the bird object relative to the laser bird-repelling device, and when the distance is less than or equal to a distance threshold, sending a rotation instruction to the rotating table to control the laser emitting end of the laser to rotate to match the direction of the bird object, and controlling the laser driving unit to drive the laser to work.

[0006] Optionally, at an offshore photovoltaic site, the laser bird-repellent device corresponds to one or more surveillance cameras, and each surveillance camera is configured on a photovoltaic bracket; wherein the data processing unit acquires the scene image, including: the data processing unit acquires the scene image captured by the surveillance camera.

[0007] Optionally, the process of the data processing unit using the scene image to perform depth estimation to determine the distance of the bird object relative to the laser bird repellent device includes: the data processing unit uses the scene image to perform depth estimation to determine the distance of the bird object relative to the surveillance camera, obtains the distance of the laser bird repellent device relative to the surveillance camera, and determines the distance of the bird object relative to the laser bird repellent device based on the distance of the bird object relative to the surveillance camera and the distance of the laser bird repellent device relative to the surveillance camera.

[0008] Optionally, the process of the data processing unit using the scene image to perform depth estimation includes: the data processing unit determines the size of the scene image, and if the size of the scene image is larger than a first preset size, downsamples the scene image to obtain a first intermediate image, inputs the scene image into a trained first neural network to obtain a first depth image, and inputs the first intermediate image into the first neural network to obtain a second depth image; the first neural network is trained by training samples whose size is less than or equal to the first preset size; the first depth image and the second depth image are input into the second neural network to perform depth image fusion to obtain a depth estimation result of the scene image.

[0009] Optionally, the size of the training sample of the first neural network is between a first preset size and a second preset size, the first preset size is larger than the second preset size, and the size of the first intermediate image is an intermediate value between the first preset size and the second preset size.

[0010] Optionally, if the size of the scene image is between the first preset size and the second preset size, the data processing unit inputs the scene image into the first neural network, and determines the obtained first depth image as the depth estimation result of the scene image.

[0011] Optionally, if the size of the scene image is smaller than a second preset size, the data processing unit upsamples the scene image to obtain a second intermediate image; wherein the size of the second intermediate image is between the first preset size and the second preset size; the second intermediate image is input into the first neural network to obtain a third depth image; and the third depth image is downsampled to obtain a depth estimation result of the scene image.

[0012] According to a second aspect of the present disclosure, a laser bird-repelling method applied to offshore photovoltaics is provided. The laser bird-repelling method is applied to a laser bird-repelling system for offshore photovoltaics. The laser bird-repelling system includes a plurality of support piles and a laser bird-repelling device arranged at one end of each support pile. Each support pile is distributed at different positions outside the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repelling device. The other end of the support pile is fixed to the seabed by a pile sinking process. The laser bird-repelling device includes a rotating table, a laser, and a laser driving unit. The rotating table is used to rotate in response to a rotation instruction. The laser is installed on the rotating table. The laser driving unit is used to drive the laser to work. The laser bird-repelling method includes: acquiring a scene image and identifying the scene image. When a bird object is identified, using the scene image to perform depth estimation to determine the distance of the bird object relative to the laser bird-repelling device. When the distance is less than or equal to a distance threshold, sending a rotation instruction to the rotating table to control the laser emitting end of the laser to rotate to match the direction of the bird object, and controlling the laser driving unit to drive the laser to work.

[0013] According to a third aspect of the present disclosure, a laser bird-repelling device applied to offshore photovoltaics is provided. The laser bird-repelling device is applied to a laser bird-repelling system of offshore photovoltaics. The laser bird-repelling system includes a plurality of supporting piles and a laser bird-repelling device arranged at one end of each supporting pile. Each supporting pile is distributed at different positions outside the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repelling device. The other end of the supporting pile is fixed to the seabed by a pile sinking process. The laser bird-repelling device includes a rotating table, a laser, and a laser driving unit. The rotating table is used to rotate in response to a rotation instruction. The laser is installed on the rotating table. The laser driving unit is used to drive the laser to work. The laser bird-repelling device includes: an image recognition module, which is used to acquire a scene image and identify the scene image; a distance determination module, which is used to use the scene image to perform depth estimation when a bird object is identified to determine the distance of the bird object relative to the laser bird-repelling device; and a bird-repelling start module, which is used to send a rotation instruction to the rotating table to control the laser emitting end of the laser to rotate to match the direction of the bird object when the distance is less than or equal to the distance threshold, and control the laser driving unit to drive the laser to work.

[0014] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the laser bird-repelling method applied to offshore photovoltaics is implemented.

[0015] According to a fifth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; the processor is configured to implement the above-mentioned laser bird-repelling method applied to offshore photovoltaics by executing the executable instructions.

[0016] In the technical solutions provided in some embodiments of the present disclosure, on the one hand, a laser bird-repellent system is deployed for special scenarios such as offshore photovoltaics, and an automatic laser bird-repellent strategy is implemented in combination with image recognition. The entire bird-repellent process is completed automatically without human control, ensuring the timeliness of bird-repellent, protecting the offshore photovoltaic site from interference from bird activities, and ensuring the normal operation of photovoltaic modules; on the other hand, the solution of the present disclosure uses images for depth estimation, and determines the distance of the bird in combination with the estimated depth, and drives the laser to work when the distance is less than a threshold. This linkage analysis and processing method at least realizes the intelligent control of the laser, avoids waste of resources and the impact of continuous laser emission on photovoltaic modules.

[0017] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0019] Figure 1 A block diagram of a laser bird-repellent system applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown.

[0020] Figure 2 The flowchart of the depth estimation process according to the embodiment of the present disclosure is schematically shown.

[0021] Figure 3 A flow chart of a laser bird-repelling method applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown.

[0022] Figure 4 A block diagram of a laser bird-repellent device applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown.

[0023] Figure 5 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0024] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the example embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0025] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0026] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the steps. For example, some steps may be decomposed, while some steps may be combined or partially combined, so the actual execution order may change according to the actual situation. In addition, all the terms "first", "second", "third", etc. below are only for the purpose of distinction and should not be used as limitations of the present disclosure.

[0027] Figure 1 The block diagram of the laser bird repellent system applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown. Figure 1 The laser bird-repelling system 1 of the embodiment of the present disclosure may include a support pile 11 and a laser bird-repelling device 12 .

[0028] It should be understood that the laser bird-repellent device 12 can be configured at one end of the support pile 11, and the other end of the support pile 11 can be fixed to the seabed by a pile-sinking process. In the offshore photovoltaic scenario, the number of laser bird-repellent devices 12 and support piles 11 is usually multiple. Specifically, the position and number of support piles 11 can be determined based on the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repellent device 12 (i.e., the effective bird-repelling range). In the exemplary embodiment of the present disclosure, multiple support piles 11 can be distributed at different locations outside the offshore photovoltaic site, rather than inside the offshore photovoltaic site, thereby minimizing the impact of the laser on the photovoltaic components.

[0029] like Figure 1 As shown, the laser bird-repelling device 12 of the embodiment of the present disclosure may include a rotating platform 121 , a laser 122 , a laser driving unit 123 and a data processing unit 124 .

[0030] The rotating platform 121 can rotate in response to a rotation instruction.

[0031] The laser 122 can be mounted on a rotating platform. Specifically, a 520nm green laser can be used. In combination with the rotation of the rotating platform 121, the continuous rotation angles achieved by the laser 122 of the present disclosure include horizontal rotation of 0° to 360° and vertical rotation of -85° to 20°.

[0032] The laser driving unit 123 can be used to drive the laser 122 to work.

[0033] The data processing unit 124 is used to perform data analysis and processing operations to achieve control of the bird-repelling operation of the laser bird-repelling device 12 .

[0034] In addition, the laser bird-repellent device 12 may also include a power storage unit, a power management unit and a shell. The power storage unit is used to store the electric energy required for the operation of the laser bird-repellent device 12. The source of the electric energy may include an offshore photovoltaic power generation system, or a power supply separately configured for the laser bird-repellent device 12. The power management unit is used to control the power supply mode of the laser bird-repellent device 12. The shell has a structure that covers other unit modules of the laser bird-repellent device 12. In order to meet the requirements of offshore photovoltaic exposure, waterproofing, and corrosion resistance, the selection of the shell material needs to at least consider these factors. For example, the shell can be constructed of aluminum alloy, and the present disclosure does not limit this.

[0035] The data processing process of the data processing unit 124 is described below.

[0036] First, a scene image may be acquired and the scene image may be recognized.

[0037] According to some embodiments of the present disclosure, the laser bird repellent device 12 may further include a camera, and the scene image acquired by the data processing unit 124 is an image captured by the camera.

[0038] According to other embodiments of the present disclosure, in an offshore photovoltaic scenario, the laser bird-repellent device 12 may correspond to one or more surveillance cameras, each surveillance camera being configured on a photovoltaic bracket, and specifically, each surveillance camera being distributed on the same or different photovoltaic brackets. It is understandable that the surveillance camera is a camera pre-installed for monitoring the on-site environment in an offshore photovoltaic scenario. In addition, a surveillance camera within a predetermined distance from the laser bird-repellent device 12 may be determined as a surveillance camera corresponding thereto, and the present disclosure does not limit the specific value of the predetermined distance.

[0039] In this case, the scene image may be an image captured by the above-mentioned surveillance camera.

[0040] Identifying the scene image includes determining whether the scene image contains a bird image. This process can be implemented using a classification model based on a convolutional neural network or by template comparison, which is not limited in the present disclosure.

[0041] In the case where it is identified that the scene image does not contain a bird object, the scene image may be discarded.

[0042] When it is identified that the scene image contains a bird object, the scene image may be used to perform depth estimation to determine the distance of the bird object relative to the laser bird repellent device 12 .

[0043] Specifically, in the embodiment where the scene image comes from the above-mentioned surveillance camera, on the one hand, the scene image can be used for depth estimation to determine the distance of the bird object relative to the surveillance camera. On the other hand, since the installation positions of the laser bird repellent device 12 and the surveillance camera are fixed, the distance of the laser bird repellent device 12 relative to the surveillance camera can be obtained. Therefore, the distance of the bird object relative to the laser bird repellent device 12 can be determined based on the distance of the bird object relative to the surveillance camera and the distance of the laser bird repellent device 12 relative to the surveillance camera.

[0044] When the determined distance is less than or equal to the distance threshold, the data processing unit 124 may send a rotation instruction to the rotating platform 121 to control the laser emitting end of the laser 122 to rotate to match the direction of the bird object, that is, to aim the laser emitting end at the bird object. Next, the data processing unit 124 may control the laser driving unit 123 to drive the laser 122 to work so as to emit laser light. The present disclosure does not limit the specific value of the distance threshold.

[0045] If it is determined that the distance is greater than the distance threshold, the camera is controlled to track the bird object until the bird object exceeds a predetermined range or the distance is less than or equal to the distance threshold.

[0046] The depth estimation process can be implemented by using a neural network. However, there may be a problem that the image size during neural network training is inconsistent with the image size of the current scene image. Especially for the scene where the surveillance camera and the laser bird repellent device 12 are independently configured, it is difficult to achieve a complete match in this regard. In this case, the problem of inaccurate depth estimation will result. In order to at least improve the accuracy of depth estimation, the present disclosure also provides a depth estimation solution.

[0047] First, the data processing unit 124 determines the size of the scene image. If the size of the scene image is larger than a first preset size, the scene image is downsampled to obtain a first intermediate image. The scene image is input into a trained first neural network to obtain a first depth image. And the first intermediate image is input into the first neural network to obtain a second depth image. Among them, the first neural network is trained by training samples whose size is less than or equal to the first preset size. Next, the first depth image and the second depth image can be input into the second neural network to perform depth image fusion to obtain a depth estimation result of the scene image. Among them, both the first neural network and the second neural network can be structures based on convolutional neural networks, and the present disclosure does not limit the specific model structures and training processes of the two.

[0048] According to some embodiments of the present disclosure, the size of the training sample of the first neural network is between a first preset size and a second preset size, and the first preset size is larger than the second preset size, for example, the first preset size is 512×512, and the second preset size is 256×256. The size of the first intermediate image is the intermediate value between the first preset size and the second preset size.

[0049] If the size of the scene image is between the first preset size and the second preset size, the data processing unit 124 may input the scene image into the first neural network, and determine the obtained first depth image as the depth estimation result of the scene image.

[0050] If the size of the scene image is smaller than the second preset size, the data processing unit 124 may upsample the scene image to obtain a second intermediate image; wherein the size of the second intermediate image is between the first preset size and the second preset size. Next, the second intermediate image may be input into the first neural network to obtain a third depth image. Then, the third depth image may be downsampled to obtain a depth estimation result of the scene image.

[0051] refer to Figure 2 The above depth estimation process is illustrated by way of example.

[0052] In step S202, a scene image may be acquired.

[0053] In step S204, the size of the scene image may be determined.

[0054] In step S206, the relationship between the size of the scene image and the preset size can be determined. The preset size can be understood as the first preset size, or a size range consisting of the first preset size and the second preset size. When the preset size is understood as a size range consisting of the first preset size and the second preset size, less than the preset size means less than the second preset size, greater than the preset size means greater than the first preset size, and equal to the preset size means between the first preset size and the second preset size.

[0055] If the size of the scene image is larger than the preset size, step S208 is executed; if the size of the scene image is equal to the preset size, step S212 is executed. If the size of the scene image is smaller than the preset size, step S214 is executed.

[0056] In step S208, the scene image may be input into the first neural network to obtain a first depth image; and the scene image may be downsampled and then input into the first neural network to obtain a second depth image.

[0057] In step S210, the first depth image and the second depth image may be input into a second neural network to obtain a depth image corresponding to the scene image.

[0058] In step S212, the scene image may be input into the first neural network to obtain a depth image corresponding to the scene image.

[0059] In step S214, the scene image may be upsampled and then input into the first neural network, and the result output by the model may be downsampled to obtain a depth image corresponding to the scene image.

[0060] In addition to the above-mentioned depth estimation method, the present disclosure may also adopt other ranging schemes combined with deep learning, and the present disclosure does not limit this.

[0061] Furthermore, the disclosed embodiments also provide a laser bird-repelling method applied to offshore photovoltaics. The laser bird-repelling method is applied to a laser bird-repelling system for offshore photovoltaics. The laser bird-repelling system includes a plurality of supporting piles and a laser bird-repelling device arranged at one end of each supporting pile. Each supporting pile is distributed at different positions around the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repelling device. The other end of the supporting pile is fixed to the seabed by a pile sinking process. The laser bird-repelling device may include a rotating table, a laser, and a laser driving unit. The rotating table is used to rotate in response to a rotation instruction. The laser is installed on the rotating table. The laser driving unit is used to drive the laser to work.

[0062] Figure 3 The flowchart of the laser bird-repelling method applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown. Figure 3 The laser bird-repelling method may include the following steps: S32. Acquire a scene image, and identify the scene image.

[0063] S34. When a bird object is identified, depth estimation is performed using the scene image to determine the distance of the bird object relative to the laser bird repellent device.

[0064] S36. When the distance is less than or equal to the distance threshold, a rotation instruction is sent to the rotating stage to control the laser emitting end of the laser to rotate to match the direction of the bird object, and control the laser driving unit to drive the laser to work.

[0065] According to an exemplary embodiment of the present disclosure, at an offshore photovoltaic site, the laser bird-repellent device corresponds to one or more monitoring cameras, and each monitoring camera is configured on a photovoltaic bracket; wherein acquiring a scene image includes: acquiring a scene image captured by a monitoring camera.

[0066] According to an exemplary embodiment of the present disclosure, the process of using scene images to perform depth estimation to determine the distance of a bird object relative to a laser bird repellent device includes: using scene images to perform depth estimation to determine the distance of the bird object relative to a surveillance camera, obtaining the distance of the laser bird repellent device relative to the surveillance camera, and determining the distance of the bird object relative to the laser bird repellent device based on the distance of the bird object relative to the surveillance camera and the distance of the laser bird repellent device relative to the surveillance camera.

[0067] According to an exemplary embodiment of the present disclosure, a process of performing depth estimation using a scene image includes: determining the size of the scene image, and if the size of the scene image is larger than a first preset size, downsampling the scene image to obtain a first intermediate image, inputting the scene image into a trained first neural network to obtain a first depth image, and inputting the first intermediate image into the first neural network to obtain a second depth image; the first neural network is trained by training samples whose size is less than or equal to the first preset size; and inputting the first depth image and the second depth image into the second neural network to perform depth image fusion to obtain a depth estimation result of the scene image.

[0068] According to an exemplary embodiment of the present disclosure, the size of the training sample of the first neural network is between a first preset size and a second preset size, the first preset size is larger than the second preset size, and the size of the first intermediate image is an intermediate value between the first preset size and the second preset size.

[0069] According to an exemplary embodiment of the present disclosure, if the size of the scene image is between the first preset size and the second preset size, the scene image is input into the first neural network, and the obtained first depth image is determined as the depth estimation result of the scene image.

[0070] According to an exemplary embodiment of the present disclosure, if the size of a scene image is smaller than a second preset size, the scene image is upsampled to obtain a second intermediate image; wherein the size of the second intermediate image is between the first preset size and the second preset size; the second intermediate image is input into the first neural network to obtain a third depth image; and the third depth image is downsampled to obtain a depth estimation result of the scene image.

[0071] Since the various steps of the laser bird-repelling method applied to offshore photovoltaics in the embodiment of the present disclosure are the same as those in the above-mentioned system implementation, they will not be repeated here.

[0072] It should be noted that although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0073] Furthermore, this example embodiment also provides a laser bird-repelling device for offshore photovoltaics. The laser bird-repelling device is applied to a laser bird-repelling system for offshore photovoltaics. The laser bird-repelling system includes a plurality of support piles and a laser bird-repelling device configured at one end of each support pile. Each support pile is distributed at different positions outside the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repelling device. The other end of the support pile is fixed to the seabed by a pile sinking process. The laser bird-repelling device includes a rotating table, a laser, and a laser driving unit. The rotating table is used to rotate in response to a rotation instruction. The laser is installed on the rotating table. The laser driving unit is used to drive the laser to work.

[0074] Figure 4 The block diagram of a laser bird-repellent device applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown. Figure 4 According to an exemplary embodiment of the present disclosure, a laser bird-repelling device 4 applied to offshore photovoltaics may include an image recognition module 41 , a distance determination module 43 and a bird-repelling starting module 45 .

[0075] Specifically, the image recognition module 41 can be used to acquire a scene image and identify the scene image; the distance determination module 43 can be used to perform depth estimation using the scene image when a bird object is identified, so as to determine the distance of the bird object relative to the laser bird repellent device; the bird repellent start module 45 can be used to send a rotation instruction to the rotating table to control the laser emitting end of the laser to rotate to match the direction of the bird object when the distance is less than or equal to the distance threshold, and control the laser driving unit to drive the laser to work.

[0076] Since the functional modules of the laser bird-repellent device applied to offshore photovoltaics in the embodiment of the present disclosure are the same as those in the above-mentioned system implementation, they will not be described in detail here.

[0077] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary implementations of the present disclosure described in the above "Exemplary Method" section of the present specification.

[0078] The program product for implementing the above method according to the embodiment of the present disclosure can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0079] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical disk, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0080] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0081] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0082] Program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0083] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0084] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0085] Refer to the following Figure 5 The electronic device 500 according to this embodiment of the present disclosure is described. Figure 5 The electronic device 500 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure. The data processing unit of the present disclosure can be configured in the form of the electronic device 500.

[0086] like Figure 5 As shown, the electronic device 500 is in the form of a general computing device. The components of the electronic device 500 may include but are not limited to: at least one processing unit 510, at least one storage unit 520, a bus 530 connecting different system components (including the storage unit 520 and the processing unit 510), and a display unit 540.

[0087] The storage unit stores a program code, which can be executed by the processing unit 510, so that the processing unit 510 executes the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of this specification. For example, the processing unit 510 can execute various steps of the laser bird repelling method applied to offshore photovoltaics in an embodiment of the present disclosure.

[0088] The storage unit 520 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 5201 and / or a cache storage unit 5202 , and may further include a read-only storage unit (ROM) 5203 .

[0089] The storage unit 520 may also include a program / utility 5204 having a set (at least one) of program modules 5205, such program modules 5205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0090] Bus 530 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0091] The electronic device 500 may also communicate with one or more external devices 600 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 500, and / or communicate with any device that enables the electronic device 500 to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface 550. In addition, the electronic device 500 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 560. As shown, the network adapter 560 communicates with other modules of the electronic device 500 through a bus 530. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0092] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0093] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0094] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0095] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing what is disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and embodiments are to be considered merely as exemplary, and the true scope and spirit of the present disclosure are indicated by the claims.

[0096] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A laser bird-repellent system for offshore photovoltaics, characterized in that: The invention comprises a plurality of supporting piles and a laser bird-repelling device arranged at one end of each supporting pile, wherein each supporting pile is distributed at different positions outside the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repelling device, and the other end of the supporting pile is fixed to the seabed by a pile sinking process; wherein the laser bird-repelling device comprises: A rotating platform, used for rotating in response to a rotation instruction; A laser is mounted on the rotating table; A laser driving unit, used to drive the laser to work; The data processing unit is used to acquire a scene image, identify the scene image, and when a bird object is identified, use the scene image to perform depth estimation to determine the distance of the bird object relative to the laser bird repellent device, and when the distance is less than or equal to a distance threshold, send a rotation instruction to the rotating table to control the laser emitting end of the laser to rotate to match the direction of the bird object, and control the laser driving unit to drive the laser to work.

2. The laser bird-repelling system according to claim 1, characterized in that: At the offshore photovoltaic site, the laser bird-repellent device corresponds to one or more monitoring cameras, and each monitoring camera is configured on a photovoltaic bracket; wherein the data processing unit obtains the scene image, including: the data processing unit obtains the scene image collected by the monitoring camera.

3. The laser bird-repellent system according to claim 2, characterized in that: The process of the data processing unit using the scene image to perform depth estimation to determine the distance of the bird object relative to the laser bird repellent device includes: The data processing unit uses the scene image to perform depth estimation to determine the distance of the bird object relative to the surveillance camera, obtains the distance of the laser bird repellent device relative to the surveillance camera, and determines the distance of the bird object relative to the laser bird repellent device based on the distance of the bird object relative to the surveillance camera and the distance of the laser bird repellent device relative to the surveillance camera.

4. The laser bird-repelling system according to any one of claims 1 to 3, characterized in that: The process of the data processing unit performing depth estimation using the scene image includes: The data processing unit determines the size of the scene image, and if the size of the scene image is larger than a first preset size, downsamples the scene image to obtain a first intermediate image, inputs the scene image into a trained first neural network to obtain a first depth image, and inputs the first intermediate image into the first neural network to obtain a second depth image; the first neural network is trained by training samples whose size is less than or equal to the first preset size; the first depth image and the second depth image are input into a second neural network to perform depth image fusion to obtain a depth estimation result of the scene image.

5. The laser bird-repellent system according to claim 4, characterized in that: The size of the training sample of the first neural network is between the first preset size and the second preset size, the first preset size is larger than the second preset size, and the size of the first intermediate image is an intermediate value between the first preset size and the second preset size.

6. The laser bird-repellent system according to claim 5, characterized in that: If the size of the scene image is between the first preset size and the second preset size, the data processing unit inputs the scene image into the first neural network, and determines the obtained first depth image as a depth estimation result of the scene image.

7. The laser bird-repellent system according to claim 5, characterized in that: If the size of the scene image is smaller than the second preset size, the data processing unit upsamples the scene image to obtain a second intermediate image; wherein the size of the second intermediate image is between the first preset size and the second preset size; the second intermediate image is input into the first neural network to obtain a third depth image; and the third depth image is downsampled to obtain a depth estimation result of the scene image.

8. A laser bird-repelling method applied to offshore photovoltaics, characterized in that: The laser bird-repelling method is applied to a laser bird-repelling system for offshore photovoltaics. The laser bird-repelling system comprises a plurality of support piles and a laser bird-repelling device disposed at one end of each of the support piles. Each of the support piles is distributed at different positions outside the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repelling device. The other end of the support pile is fixed to the seabed by a pile sinking process. The laser bird-repelling device comprises a rotating platform, a laser, and a laser driving unit. The rotating platform is used to rotate in response to a rotation instruction. The laser is mounted on the rotating table; The laser driving unit is used to drive the laser to work; wherein the laser bird-repelling method comprises: Acquire a scene image, and identify the scene image; When a bird object is identified, depth estimation is performed using the scene image to determine the distance of the bird object relative to the laser bird repellent device; When the distance is less than or equal to the distance threshold, a rotation instruction is sent to the rotating platform to control the laser emitting end of the laser to rotate to match the direction of the bird object, and control the laser driving unit to drive the laser to work.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the laser bird-repelling method applied to offshore photovoltaics as described in claim 8 is implemented.

10. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to implement the laser bird-repelling method for offshore photovoltaics as described in claim 8 by executing the executable instructions.

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