Photovoltaic bird repelling system and method applied to sea, storage medium and electronic equipment

Abstract

The invention provides a photovoltaic bird repelling system applied to the sea, a photovoltaic 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 bird repelling system comprises a plurality of laser bird repelling units and a plurality of sound wave bird repelling units, and the sound wave bird repelling units are distributed at different positions in an offshore photovoltaic site; the sound wave bird repelling unit comprises a camera used for collecting a first scene image; the sounding array comprises a plurality of sounders; the first data processor is used for acquiring a first scene image collected by the camera, identifying the first scene image, performing depth estimation by using the first scene image under the condition that a bird object is identified so as to determine the distance of the bird object relative to the sound wave bird repelling unit, and performing depth estimation by using the first scene image under the condition that the distance is smaller than or equal to a first distance threshold value; and controlling the sounding array to emit sound waves. 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 bird-repelling system applied to offshore photovoltaics, a bird-repelling 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 bird-repelling system applied to offshore photovoltaics is provided, comprising a plurality of laser bird-repelling units and a plurality of sonic bird-repelling units, wherein each laser bird-repelling unit is distributed at different positions on the periphery of 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 unit, and each sonic bird-repelling unit is distributed at different positions inside and at the boundary of the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the sonic bird-repelling unit; wherein the sonic bird-repelling unit comprises: a camera for collecting a first scene image; a sound array comprising a plurality of sound emitters; a first data processor for acquiring the first scene image collected by the camera, identifying the first scene image, and when a bird object is identified, performing depth estimation using the first scene image to determine the distance of the bird object relative to the sonic bird-repelling unit, and when the distance is less than or equal to a first distance threshold, controlling the sound array to emit sound waves.

[0006] Optionally, the laser bird-repellent unit includes: a rotating table, used to rotate in response to a rotation instruction; a laser, mounted on the rotating table; a laser driving unit, used to drive the laser to work; a second data processor, used to acquire a second scene image, identify the second scene image, and when a bird object is identified, use the second scene image to perform depth estimation to determine the distance of the bird object relative to the laser bird-repellent unit, and when the distance is less than or equal to a second 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; wherein the second distance threshold is greater than the first distance threshold.

[0007] Optionally, the second data processor is also used to send a start instruction to a target sonic bird repellent unit corresponding to the laser bird repellent unit when it is determined that the distance of the bird object relative to the laser bird repellent unit is between a first distance threshold and a second distance threshold; the first data processor of the target sonic bird repellent unit controls the camera to start in response to the start instruction to capture a first scene image.

[0008] Optionally, when the sonic bird repelling unit emits sonic waves to repel the target bird object, the first data processor of the sonic bird repelling unit sends an operation stop instruction to the target laser bird repelling unit corresponding to the sonic bird repelling unit; the second data processor of the target laser bird repelling unit controls the laser emission operation targeting the target bird object to stop in response to the operation stop instruction.

[0009] Optionally, the process of the second data processor using the second scene image to perform depth estimation includes: the second data processor determines the size of the second scene image, and if the size of the second scene image is larger than a first preset size, downsamples the second scene image to obtain a first intermediate image, inputs the second 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 second scene image.

[0010] 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.

[0011] Optionally, if the size of the second scene image is between the first preset size and the second preset size, the second data processor inputs the second scene image into the first neural network, and determines the obtained first depth image as the depth estimation result of the second scene image; if the size of the second scene image is smaller than the second preset size, the second data processor upsamples the second 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; inputs the second intermediate image into the first neural network to obtain a third depth image; and downsamples the third depth image to obtain the depth estimation result of the second scene image.

[0012] According to a second aspect of the present disclosure, a bird-repelling method applied to offshore photovoltaics is provided. The bird-repelling method is applied to a bird-repelling system for offshore photovoltaics. The bird-repelling system includes a plurality of laser bird-repelling units and a plurality of sound wave bird-repelling units. Each laser bird-repelling unit 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 unit. Each sound wave bird-repelling unit is distributed at different positions inside and at the boundary of the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the sound wave bird-repelling unit. The sound wave bird-repelling unit includes a camera and a sound array. The camera is used to collect a first scene image. The sound array includes a plurality of sound emitters. The bird-repelling method includes: obtaining a first scene image collected by the camera and identifying the first scene image; when a bird object is identified, using the first scene image to perform depth estimation to determine the distance of the bird object relative to the sound wave bird-repelling unit; when the distance is less than or equal to a first distance threshold, controlling the sound array to emit sound waves.

[0013] According to a third aspect of the present disclosure, a bird-repelling device applied to offshore photovoltaics is provided. The bird-repelling device is applied to a bird-repelling system of offshore photovoltaics. The bird-repelling system includes a plurality of laser bird-repelling units and a plurality of sound wave bird-repelling units. Each laser bird-repelling unit 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 unit. Each sound wave bird-repelling unit is distributed at different positions inside and at the boundary of the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the sound wave bird-repelling unit. The sound wave bird-repelling unit includes a camera and a sound array. The camera is used to collect a first scene image. The sound array includes a plurality of sound emitters. The bird-repelling device includes: an image recognition module, which is used to obtain a first scene image collected by the camera and recognize the first scene image; a distance determination module, which is used to perform depth estimation using the first scene image when a bird object is identified to determine the distance of the bird object relative to the sound wave bird-repelling unit; and a bird-repelling start module, which is used to control the sound array to emit sound waves when the distance is less than or equal to a first distance threshold.

[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 above-mentioned 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 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, for special scenarios such as offshore photovoltaics, a bird repellent system including a laser bird repellent unit and an acoustic bird repellent unit is deployed, and an automatic 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 components; 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 controls the sound array to emit bird repellent sound waves when the distance is less than a threshold. This linkage analysis and processing method at least realizes the intelligent control of acoustic bird repellent; on the other hand, the solution of the present disclosure adopts a combination of laser bird repellent and acoustic bird repellent, making full use of the characteristics of each method. Their combined use can significantly improve the offshore photovoltaic bird repellent effect.

[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 bird repelling system applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown.

[0020] Figure 2 A schematic diagram showing the configuration of the laser bird-repelling unit and the sonic bird-repelling unit of an embodiment of the present disclosure.

[0021] Figure 3 A block diagram of a sonic bird-repelling unit according to an exemplary embodiment of the present disclosure is schematically shown.

[0022] Figure 4 A block diagram of a laser bird-repelling unit according to an exemplary embodiment of the present disclosure is schematically shown.

[0023] Figure 5 The flowchart of the depth estimation process of the embodiment of the present disclosure is schematically shown.

[0024] Figure 6 A flow chart of a bird-repelling method applied to offshore photovoltaics according to an embodiment of the present disclosure is schematically shown.

[0025] Figure 7A block diagram of a bird-repelling device applied to offshore photovoltaics according to an embodiment of the present disclosure is schematically shown.

[0026] Figure 8 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 1 The block diagram of a bird repellent system applied to offshore photovoltaics according to an exemplary embodiment of the present disclosure is schematically shown. Figure 1 The bird-repelling system 1 applied to offshore photovoltaics according to the embodiment of the present disclosure may include an acoustic bird-repelling unit 11 and a laser bird-repelling unit 12. In view of the fact that the offshore photovoltaic area is usually large, the number of the acoustic bird-repelling unit 11 and the laser bird-repelling unit 12 used in the present disclosure is usually multiple.

[0031] Specifically, the position and number of each acoustic wave bird-repelling unit 11 can be determined according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the acoustic wave bird-repelling unit 11 (i.e., the effective bird-repelling range). Considering the bird-repelling ability of the acoustic wave bird-repelling unit 11, the acoustic wave bird-repelling unit 11 can be distributed at different positions inside and at the boundary of the offshore photovoltaic site.

[0032] The position and number of each laser bird-repellent unit 12 can be determined according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the laser in the laser bird-repellent unit 12 (i.e., the effective bird-repellent range). Considering the bird-repelling ability of the laser bird-repellent unit 12 and the impact of the laser on the photovoltaic components, the laser bird-repellent unit 12 can be distributed at different locations outside the offshore photovoltaic site.

[0033] It should be noted that the sonic bird-repelling unit 11 of the disclosed embodiment can be configured at one end of a support pile, and the other end of the support pile can be fixed to the seabed by a pile-sinking process. The laser bird-repelling unit 12 of the disclosed embodiment can also be configured at one end of a support pile, and the other end of the support pile can be fixed to the seabed by a pile-sinking process. Usually, the support pile corresponding to the sonic bird-repelling unit 11 and the support pile corresponding to the laser bird-repelling unit 12 are not the same support pile.

[0034] refer to Figure 1 The sonic bird-repelling unit 11 can also be connected to the laser bird-repelling unit 12 in a wired or wireless manner to achieve the transmission of control instructions, thereby realizing various joint bird-repelling strategies.

[0035] Figure 2 The schematic diagram shows the configuration of the laser bird-repelling unit and the sonic bird-repelling unit of the embodiment of the present disclosure. Figure 2 ,This exemplary offshore photovoltaic scenario, through the above analysis method, can be configured with 2 laser bird-repelling units and 19 sonic bird-repelling units.

[0036] Among them, the sonic bird-repelling unit 11 can be configured in the river channel of the offshore photovoltaic area and the boundary of the offshore photovoltaic area. Compared with the sonic bird-repelling unit 11, the laser bird-repelling unit 12 can be configured on the periphery of the offshore photovoltaic site. While giving full play to the laser bird-repelling effect, it avoids the influence of the laser on the photovoltaic components as much as possible.

[0037] refer to Figure 3 The sonic bird-repelling unit 11 of the embodiment of the present disclosure may include a camera 131 , a sound array 132 , and a first data processor 133 .

[0038] The camera 131 may be used to capture a first scene image.

[0039] The sound array 132 may include a plurality of sound emitters, and the sound pressure of the sound array 132 is required to reach 100 decibels to 130 decibels at 1 meter. The present disclosure does not limit the number of sound emitters, for example, 20, 48, etc.

[0040] The first data processor 133 can be used to obtain a first scene image captured by the camera 131, identify the first scene image, and when a bird object is identified, use the first scene image to perform depth estimation to determine the distance of the bird object relative to the acoustic bird-repelling unit, and when the distance is less than or equal to a first distance threshold, control the sound array 132 to emit sound waves.

[0041] refer to Figure 4 The laser bird-repelling unit 12 of the embodiment of the present disclosure may include a rotating platform 141 , a laser 142 , a laser driving unit 143 and a second data processor 144 .

[0042] The rotating platform 141 can rotate in response to a rotation instruction.

[0043] The laser 142 can be mounted on a rotating platform. Specifically, a 520nm green laser can be used. In combination with the rotation of the rotating platform 141, the continuous rotation angles achieved by the laser 142 of the present disclosure include horizontal rotation of 0° to 360° and vertical rotation of -85° to 20°.

[0044] The laser driving unit 143 can be used to drive the laser 142 to work.

[0045] The second data processor 144 is used to perform data analysis and processing operations to achieve control of the bird-repelling operation of the laser bird-repelling unit 12. Specifically, the second data processor 144 can obtain a second scene image, identify the second scene image, and use the second 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 unit 12. When the distance is less than or equal to the second distance threshold, a rotation instruction is sent to the rotating table 141 to control the laser emitting end of the laser 142 to rotate to match the direction of the bird object, and control the laser driving unit 143 to drive the laser 142 to work. The second distance threshold is greater than the above-mentioned first distance threshold.

[0046] In addition, both the sonic bird-repelling unit 11 and the laser bird-repelling unit 12 may also include a power storage unit, a power management unit and a housing. The power storage unit is used to store the electrical energy required for the operation of the unit, and the source of the electrical energy may include an offshore photovoltaic power generation system, or a power supply configured separately for the unit. The power management unit is used to control the power supply mode. The housing has a structure that covers other modules of the unit. In order to meet the requirements of offshore photovoltaic exposure, waterproofing, and corrosion resistance, the selection of the housing material needs to at least consider these factors. For example, the housing can be constructed of aluminum alloy, and the present disclosure does not limit this.

[0047] According to some embodiments of the present disclosure, the second data processor 144 may also be used to send a start instruction to a target sound wave bird repelling unit corresponding to the laser bird repelling unit 12 when it is determined that the distance of the bird object relative to the laser bird repelling unit 12 is between the first distance threshold and the second distance threshold. The first data processor of the target sound wave bird repelling unit may control the camera to start in response to the start instruction to capture the first scene image.

[0048] According to some embodiments of the present disclosure, when the sonic bird-repelling unit 11 emits sonic waves to drive away the target bird object, the first data processor of the sonic bird-repelling unit 11 sends an operation stop instruction to the target laser bird-repelling unit corresponding to the sonic bird-repelling unit 11. The second data processor of the target laser bird-repelling unit controls the laser emission operation for the target bird object to stop in response to the operation stop instruction. Thus, the influence that the laser may cause to the photovoltaic module is avoided, and the influence includes, for example, a decrease in photoelectric efficiency, damage to the photovoltaic module, etc.

[0049] The data processing process of the second data processor 144 is described below.

[0050] First, a second scene image may be acquired and the second scene image may be recognized.

[0051] According to some embodiments of the present disclosure, the laser bird-repelling unit 12 may further include a camera, and the second scene image acquired by the second data processor 144 is an image captured by the camera.

[0052] According to other embodiments of the present disclosure, in an offshore photovoltaic scenario, the laser bird-repelling unit 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-repelling unit 12 may be determined as a surveillance camera corresponding thereto, and the present disclosure does not limit the specific value of the predetermined distance.

[0053] In this case, the second scene image may be an image captured by the above-mentioned surveillance camera.

[0054] Identifying the second scene image includes determining whether the second 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. In addition, the recognition algorithm of the first data processor 133 can be the same as the recognition algorithm of the second data processor 144.

[0055] In the case where it is identified that the second scene image does not contain a bird object, the second scene image may be discarded.

[0056] In the case where it is identified that the second scene image contains a bird object, the second scene image may be used to perform depth estimation to determine the distance of the bird object relative to the laser bird repelling unit 12 .

[0057] Specifically, in the embodiment where the second scene image comes from the above-mentioned surveillance camera, on the one hand, the second 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, given that the installation positions of the laser bird repellent unit 12 and the surveillance camera are fixed, the distance of the laser bird repellent unit 12 relative to the surveillance camera can be obtained. Thus, the distance of the bird object relative to the laser bird repellent unit 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 unit 12 relative to the surveillance camera.

[0058] When the determined distance is less than or equal to the second distance threshold, the second data processor 144 may send a rotation instruction to the rotating platform 141 to control the laser emitting end of the laser 142 to rotate to match the direction of the bird object, that is, to aim the laser emitting end at the bird object. Next, the second data processor 144 may control the laser driving unit 143 to drive the laser 142 to work and emit laser light. The present disclosure does not limit the specific value of the second distance threshold.

[0059] If it is determined that the distance is greater than the second 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 second distance threshold.

[0060] The depth estimation process can be implemented by 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 second scene image. Especially for the scene where the surveillance camera and the laser bird repellent unit 12 are independently configured, it is difficult to achieve a complete match in this regard. In this case, the depth estimation problem will be inaccurate. In order to at least improve the accuracy of depth estimation, the present disclosure also provides a depth estimation solution.

[0061] First, the second data processor 144 determines the size of the second scene image. If the size of the second scene image is larger than the first preset size, the second scene image is downsampled to obtain a first intermediate image. The second scene image is input into the 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 second 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.

[0062] 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.

[0063] If the size of the second scene image is between the first preset size and the second preset size, the second data processor 144 may input the second scene image into the first neural network and determine the obtained first depth image as the depth estimation result of the second scene image.

[0064] If the size of the second scene image is smaller than the second preset size, the second data processor 144 may upsample the second 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 second scene image.

[0065] refer to Figure 5 The above depth estimation process is illustrated by way of example.

[0066] In step S502, a second scene image may be acquired.

[0067] In step S504, the size of the second scene image may be determined.

[0068] In step S506, the relationship between the size of the second 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.

[0069] If the size of the second scene image is larger than the preset size, step S508 is executed; if the size of the second scene image is equal to the preset size, step S512 is executed. If the size of the second scene image is smaller than the preset size, step S514 is executed.

[0070] In step S508, the second scene image may be input into the first neural network to obtain a first depth image; and the second scene image may be downsampled and then input into the first neural network to obtain a second depth image.

[0071] In step S510, 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 second scene image.

[0072] In step S512, the second scene image may be input into the first neural network to obtain a depth image corresponding to the second scene image.

[0073] In step S514, the second 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 second scene image.

[0074] 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.

[0075] It should be noted that the depth estimation scheme executed by the first data processor 133 in the acoustic bird-repelling unit 11 may also be executed in the same manner as that of the second data processor 144 , which will not be described in detail in this disclosure.

[0076] Furthermore, the disclosed embodiment also provides a bird-repelling method applied to offshore photovoltaics. The bird-repelling method is applied to a bird-repelling system for offshore photovoltaics. The bird-repelling system includes multiple laser bird-repelling units and multiple sonic bird-repelling units. Each laser bird-repelling unit is distributed at different positions on the periphery of 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 unit. Each sonic bird-repelling unit is distributed at different positions inside and at the boundary of the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the sonic bird-repelling unit. The sonic bird-repelling unit includes a camera and a sound array. The camera is used to collect a first scene image. The sound array includes multiple sound generators.

[0077] Figure 6 The flowchart of the bird-repelling method applied to offshore photovoltaics according to an embodiment of the present disclosure is schematically shown. Figure 6 The bird-repelling method of the embodiment of the present disclosure may include:

[0078] S62. Obtain a first scene image captured by a camera, and identify the first scene image.

[0079] S64. When a bird object is identified, depth estimation is performed using the first scene image to determine a distance of the bird object relative to the acoustic bird driving unit.

[0080] S66. When the distance is less than or equal to the first distance threshold, control the sound array to emit sound waves.

[0081] According to an exemplary embodiment of the present disclosure, a laser bird-repelling unit includes: a rotating table, which is used to rotate in response to a rotation instruction; a laser, which is installed on the rotating table; a laser driving unit, which is used to drive the laser to work; a second data processor, which is used to acquire a second scene image, identify the second scene image, and when a bird object is identified, use the second scene image to perform depth estimation to determine the distance of the bird object relative to the laser bird-repelling unit, and when the distance is less than or equal to a second 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; wherein the second distance threshold is greater than the first distance threshold.

[0082] According to an exemplary embodiment of the present disclosure, the second data processor is also used to send a start instruction to the target sonic bird repellent unit corresponding to the laser bird repellent unit when it is determined that the distance of the bird object relative to the laser bird repellent unit is between the first distance threshold and the second distance threshold; the first data processor of the target sonic bird repellent unit controls the camera to start in response to the start instruction to capture the first scene image.

[0083] According to an exemplary embodiment of the present disclosure, when a sonic bird repellent unit emits sonic waves to repel a target bird object, a first data processor of the sonic bird repellent unit sends an operation stop instruction to a target laser bird repellent unit corresponding to the sonic bird repellent unit; a second data processor of the target laser bird repellent unit controls the laser emission operation for the target bird object to stop in response to the operation stop instruction.

[0084] According to an exemplary embodiment of the present disclosure, a process in which a second data processor uses a second scene image to perform depth estimation includes: the second data processor determines the size of the second scene image, and if the size of the second scene image is larger than a first preset size, downsamples the second scene image to obtain a first intermediate image, inputs the second 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 second scene image.

[0085] 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.

[0086] According to an exemplary embodiment of the present disclosure, if the size of the second scene image is between the first preset size and the second preset size, the second data processor inputs the second scene image into the first neural network, and determines the obtained first depth image as the depth estimation result of the second scene image; if the size of the second scene image is smaller than the second preset size, the second data processor upsamples the second 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 the depth estimation result of the second scene image.

[0087] Since the various steps of the 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.

[0088] 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.

[0089] Furthermore, the disclosed embodiment also provides a bird-repelling device applied to offshore photovoltaics. The bird-repelling device is applied to a bird-repelling system for offshore photovoltaics. The bird-repelling system includes multiple laser bird-repelling units and multiple sonic bird-repelling units. Each laser bird-repelling unit is distributed at different positions on the periphery of 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 unit. Each sonic bird-repelling unit is distributed at different positions inside and at the boundary of the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the sonic bird-repelling unit. The sonic bird-repelling unit includes a camera and a sound array. The camera is used to collect a first scene image. The sound array includes multiple sound generators.

[0090] Figure 7 The block diagram of the bird repellent device applied to offshore photovoltaics according to the embodiment of the present disclosure is schematically shown. Figure 7 The bird-repelling device 7 applied to offshore photovoltaics according to the embodiment of the present disclosure may include an image recognition module 71 , a distance determination module 73 and a bird-repelling starting module 75 .

[0091] Specifically, the image recognition module 71 can be used to obtain a first scene image captured by a camera and identify the first scene image; the distance determination module 73 can be used to perform depth estimation using the first scene image when a bird object is identified to determine the distance of the bird object relative to the acoustic bird-repelling unit; the bird-repelling start module 75 can be used to control the sound array to emit sound waves when the distance is less than or equal to a first distance threshold.

[0092] Since the functional modules of the bird-repelling device applied to offshore photovoltaics in the embodiment of the present disclosure are the same as those in the above-mentioned system embodiment, they will not be described in detail here.

[0093] 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.

[0094] 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.

[0095] The program product may use 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 of the above. 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 of the above.

[0096] 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.

[0097] 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.

[0098] 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 cases involving 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., through the Internet using an Internet service provider).

[0099] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0100] 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".

[0101] Refer to the following Figure 8 The electronic device 800 according to this embodiment of the present disclosure is described. Figure 8 The electronic device 800 shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure. The first data processor and / or the second data processor may be configured in the form of the electronic device 800.

[0102] like Figure 8 As shown, the electronic device 800 is in the form of a general computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one storage unit 820, a bus 830 connecting different system components (including the storage unit 820 and the processing unit 810), and a display unit 840.

[0103] The storage unit stores a program code, which can be executed by the processing unit 810, so that the processing unit 810 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 810 can execute various steps of the bird-repelling method applied to offshore photovoltaics in an embodiment of the present disclosure.

[0104] The storage unit 820 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 8201 and / or a cache memory unit 8202 , and may further include a read-only memory unit (ROM) 8203 .

[0105] The storage unit 820 may also include a program / utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 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.

[0106] Bus 830 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.

[0107] The electronic device 800 may also communicate with one or more external devices 900 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 800, and / or any device that enables the electronic device 800 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed through an input / output (I / O) interface 850. Furthermore, the electronic device 800 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 860. Figure 8 As shown, the network adapter 860 communicates with other modules of the electronic device 800 via the bus 830. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0108] 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, including several 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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 bird-repelling system for offshore photovoltaics, characterized in that: It includes a plurality of laser bird-repelling units and a plurality of sonic bird-repelling units. Each of the laser bird-repelling units 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 unit. Each of the sonic bird-repelling units is distributed at different positions inside and on the boundary of the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the sonic bird-repelling unit. The sonic bird-repelling unit includes: A camera, used for collecting a first scene image; A sound array, comprising a plurality of sound generators; The first data processor is used to obtain the first scene image captured by the camera, identify the first scene image, and when a bird object is identified, use the first scene image to perform depth estimation to determine the distance of the bird object relative to the acoustic bird-repelling unit, and when the distance is less than or equal to a first distance threshold, control the sound array to emit sound waves.

2. The bird repelling system according to claim 1, characterized in that: The laser bird repellent unit 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; a second data processor, configured to acquire a second scene image, identify the second scene image, and when a bird object is identified, perform depth estimation using the second scene image to determine a distance of the bird object relative to the laser bird-repelling unit, and when the distance is less than or equal to a second distance threshold, send a rotation instruction 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; The second distance threshold is greater than the first distance threshold.

3. The bird repelling system according to claim 2, characterized in that: The second data processor is further configured to send a start instruction to a target acoustic wave bird repelling unit corresponding to the laser bird repelling unit when it is determined that the distance of the bird object relative to the laser bird repelling unit is between the first distance threshold and the second distance threshold; The first data processor of the target acoustic wave bird-repelling unit controls the camera to start in response to the start-up instruction to collect the first scene image.

4. The bird repelling system according to claim 2, characterized in that: In the case where the sonic wave bird-repelling unit emits sonic waves to drive away the target bird object, the first data processor of the sonic wave bird-repelling unit sends an operation stop instruction to the target laser bird-repelling unit corresponding to the sonic wave bird-repelling unit; The second data processor of the target laser bird repelling unit controls the laser emission operation for the target bird object to stop in response to the operation stop instruction.

5. The bird repelling system according to claim 2, characterized in that: The process of the second data processor performing depth estimation using the second scene image includes: The second data processor determines the size of the second scene image, and if the size of the second scene image is larger than a first preset size, downsamples the second scene image to obtain a first intermediate image, inputs the second 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 second scene image.

6. The bird repelling system according to claim 5, 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.

7. The bird repelling system according to claim 6, characterized in that: If the size of the second scene image is between the first preset size and the second preset size, the second data processor inputs the second scene image into the first neural network, and determines the obtained first depth image as the depth estimation result of the second scene image; If the size of the second scene image is smaller than the second preset size, the second data processor upsamples the second 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 second scene image.

8. A bird-repelling method applied to offshore photovoltaics, characterized in that: The bird-repelling method is applied to a bird-repelling system for offshore photovoltaics, wherein the bird-repelling system comprises a plurality of laser bird-repelling units and a plurality of sonic bird-repelling units, wherein each of the laser bird-repelling units 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 unit, and each of the sonic bird-repelling units is distributed at different positions inside and on the boundary of the offshore photovoltaic site according to the shape and area of ​​the offshore photovoltaic area and the effective working range of the sound array in the sonic bird-repelling unit; the sonic bird-repelling unit comprises a camera and a sound array, wherein the camera is used to collect a first scene image, and the sound array comprises a plurality of sound generators; wherein the bird-repelling method comprises: Acquire the first scene image captured by the camera, and identify the first 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 acoustic bird repelling unit; When the distance is less than or equal to a first distance threshold, the sound array is controlled to emit sound waves.

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 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 bird-repelling method for offshore photovoltaics as described in claim 8 by executing the executable instructions.

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