Improved photovoltaic cleaning device

Abstract

The invention relates to the technical field of photovoltaic cleaning monitoring, in particular to an improved photovoltaic cleaning device which comprises an automatic navigation system used for positioning a cleaning start point and a cleaning end point on a photovoltaic panel; the at least one cleaning unit is used for removing dust and dirt on the photovoltaic panel; the intelligent sensing system is used for monitoring the cleaning state and preventing the photovoltaic panel from being damaged, the automation level of cleaning operation is improved, and manual intervention and cost are reduced; precise identification and positioning of dirt distribution of the photovoltaic panel are achieved, the cleaning path is optimized, and the cleaning efficiency is improved. A cleaning strategy is automatically adjusted according to real-time feedback, so that the photovoltaic panel is prevented from being damaged while the cleaning quality is ensured; and the remote control function allows an operator to flexibly arrange a cleaning task according to the actual pollution condition of the photovoltaic panel, so that the convenience and flexibility of use are enhanced.

Description

Technical Field

[0001] The invention relates to the technical field of photovoltaic cleaning monitoring, in particular to an improved photovoltaic cleaning device. Background Art

[0002] In the field of photovoltaic energy, keeping photovoltaic panels clean is crucial to maximizing the efficiency of light energy conversion. However, photovoltaic cleaning devices in the prior art mostly use manual cleaning or simple mechanical wiping, which have problems such as low efficiency, high cost, incomplete cleaning or damage to photovoltaic panels. In addition, automated cleaning equipment often lacks precise navigation and intelligent monitoring functions, making it difficult to adapt to different environments and photovoltaic panel conditions, and unable to achieve efficient and customized cleaning operations. Summary of the invention

[0003] In view of the above problems or problems existing in the prior art, the present invention is proposed.

[0004] It is therefore an object of the present invention to provide an improved photovoltaic cleaning device.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: including, an automated navigation system for locating the starting point and end point of cleaning on the photovoltaic panel; at least one cleaning unit for removing dust and dirt on the photovoltaic panel; and an intelligent sensing system for monitoring the cleaning status and avoiding damage to the photovoltaic panel.

[0006] As a preferred solution of the improved photovoltaic cleaning device of the present invention, the cleaning unit includes a replaceable cleaning brush or cleaning cloth.

[0007] As a preferred solution of the improved photovoltaic cleaning device of the present invention, the automated navigation system includes a sensor and a motion control unit for achieving precise positioning and path planning.

[0008] As a preferred solution of the improved photovoltaic cleaning device of the present invention, the intelligent sensing system includes at least one image sensor and a corresponding image processing algorithm for identifying the distribution of dirt on the photovoltaic panel.

[0009] As a preferred solution of the improved photovoltaic cleaning device of the present invention, it includes an intelligent control system for automatically adjusting the cleaning strategy according to the dirt distribution and cleaning status.

[0010] As a preferred solution of the improved photovoltaic cleaning device of the present invention, the intelligent control system is capable of remotely receiving cleaning instructions and automatically starting the cleaning program according to the actual degree of contamination of the photovoltaic panel.

[0011] As a preferred solution of the improved photovoltaic cleaning device of the present invention, wherein: the intelligent image processing algorithm includes inputting an image of a photovoltaic panel including a cleaning state;

[0012] Using a convolutional neural network to extract features from an input image, wherein the convolutional neural network includes a plurality of convolutional layers and pooling layers for extracting image features layer by layer;

[0013] Based on the convolutional neural network, a region proposal network (RPN) is used to generate candidate cleanliness regions. RPN searches for potential photovoltaic panel regions at different scales through a sliding window.

[0014] Apply fully connected layers to the candidate regions generated by RPN for cleanliness classification and bounding box regression.

[0015] As a preferred solution of the improved photovoltaic cleaning device of the present invention, the bounding box regression adopts the following formula:

[0016] [x,y,w,h]=[x p ,y p ,w p ,h p ]+[dx,dy][dw,dh]

[0017] Among them, [x, y, w, h] refers to the predicted box after transformation, [x p ,y p ,w p ,h p ] refers to the initial proposed cleanliness candidate region, [dx,dy] refers to the offset of the center point of the bounding box, and [dw,dh] refers to the scaling factor of the width and height of the bounding box.

[0018] As a preferred solution of the improved photovoltaic cleaning device of the present invention, it includes the following steps: starting the automatic navigation system to locate the cleaning starting point; activating the cleaning unit to start removing dirt on the photovoltaic panel; using the intelligent sensing system to monitor the cleaning effect; according to the feedback from the intelligent sensing system, the intelligent control system adjusts the cleaning strategy; after cleaning is completed, it automatically returns to the starting point or the designated position.

[0019] As a preferred solution of the improved photovoltaic cleaning device of the present invention, there is a computer-readable storage medium having computer program instructions stored thereon, and the computer-executable instructions implement the steps of the above method when executed by a processor.

[0020] The improved photovoltaic cleaning device of the present invention has the following beneficial effects: it improves the automation level of cleaning operations, reduces manual intervention and costs; it realizes accurate identification and positioning of dirt distribution on photovoltaic panels, optimizes the cleaning path, and improves cleaning efficiency; it automatically adjusts the cleaning strategy based on real-time feedback to ensure cleaning quality while avoiding damage to the photovoltaic panels; the remote control function allows the operator to flexibly arrange cleaning tasks according to the actual contamination situation of the photovoltaic panels, thereby enhancing the convenience and flexibility of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0022] Figure 1 Figure 1 is a diagram of a computer device based on an improved photovoltaic cleaning device. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0026] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides an improved photovoltaic cleaning device, which includes an automated navigation system for locating the cleaning starting point and end point on the photovoltaic panel; at least one cleaning unit for removing dust and dirt on the photovoltaic panel; and an intelligent sensing system for monitoring the cleaning status and avoiding damage to the photovoltaic panel.

[0027] Specifically, the cleaning unit includes a replaceable cleaning brush or a cleaning cloth.

[0028] Furthermore, the automated navigation system includes sensors and motion control units for achieving precise positioning and path planning.

[0029] Wherein, the intelligent sensing system includes at least one image sensor and a corresponding image processing algorithm for identifying the distribution of dirt on the photovoltaic panel.

[0030] Preferably, an intelligent control system is included for automatically adjusting the cleaning strategy according to dirt distribution and cleaning status.

[0031] It should be noted that the intelligent control system is capable of remotely receiving cleaning instructions and automatically starting a cleaning procedure according to the actual degree of contamination of the photovoltaic panels.

[0032] When used, the intelligent image processing algorithm includes, as input, an image of a photovoltaic panel including a clean state;

[0033] Using a convolutional neural network to extract features from an input image, wherein the convolutional neural network includes a plurality of convolutional layers and pooling layers for extracting image features layer by layer;

[0034] Based on the convolutional neural network, a region proposal network (RPN) is used to generate candidate cleanliness regions. RPN searches for potential photovoltaic panel regions at different scales through a sliding window.

[0035] A fully connected layer is applied to the candidate regions generated by RPN to perform cleanliness classification and bounding box regression. Preferably, the bounding box regression adopts the following formula,

[0036] [x,y,w,h]=[x p ,y p ,w p ,h p ]+[dx,dy][dw,dh]

[0037] Among them, [x, y, w, h] refers to the predicted box after transformation, [x p ,y p ,w p ,h p ] refers to the initial proposed cleanliness candidate region, [dx,dy] refers to the offset of the center point of the bounding box, and [dw,dh] refers to the scaling factor of the width and height of the bounding box.

[0038] Furthermore, the following steps are included: starting the automated navigation system to locate the cleaning starting point; activating the cleaning unit to start removing dirt from the photovoltaic panel; using the intelligent sensing system to monitor the cleaning effect; based on the feedback from the intelligent sensing system, the intelligent control system adjusts the cleaning strategy; after cleaning is completed, automatically returning to the starting point or the designated location.

[0039] In summary, the present invention accurately locates the cleaning starting point and end point on the photovoltaic panel through its automated navigation system, and realizes efficient cleaning path planning. The device is equipped with at least one cleaning unit, which can replace the cleaning brush or cleaning cloth as needed to adapt to different degrees and types of dirt. The intelligent sensing system is equipped with a high-resolution image sensor to capture the surface state of the photovoltaic panel in real time, and through advanced image processing algorithms such as convolutional neural networks and region proposal networks, identify and locate the dirt area, so as to accurately adjust the cleaning strategy. The intelligent control system can not only automatically adjust the operation of the cleaning unit according to real-time feedback, but also support remote command reception, allowing the operator to flexibly arrange cleaning tasks according to the actual pollution of the photovoltaic panel. During the cleaning process, the intelligent control system ensures that the cleaning effect is optimal while avoiding damage to the photovoltaic panel. After the cleaning is completed, the device automatically returns to the starting point or the designated position and waits for the next task. In addition, the cleaning unit design of the device takes into account the convenience of maintenance and replacement, ensuring the continuity of the cleaning effect and the long-term stable operation of the equipment. Through the photovoltaic cleaning device of the present invention, the automation and intelligence of the photovoltaic panel cleaning work are realized, the cleaning efficiency and quality are significantly improved, and the labor cost and time are reduced, providing an efficient, economical and reliable solution for the operation and maintenance management of photovoltaic power stations.

[0040] The bounding box regression formula also includes,

[0041] x=x p +dx;

[0042] y=y p +dy;

[0043] w=w p *e dw ;

[0044] h=h p *e dh ;;

[0045] Here, e is the base of natural logarithms and is used to express the exponential form of the scaling factor.

[0046] It should be noted that the non-maximum suppression algorithm has the following steps: Step 1, for each category, sort the detection boxes according to their confidence scores. Step 2, select the detection box with the highest confidence as the reference box. Step 3, calculate the intersection over union (IoU) of other detection boxes and the reference box. Step 4, if the IoU between the detection box and the reference box is higher than a preset threshold, suppress the detection box (i.e., remove it from the candidate list); Step 5, continue to select the next detection box with the highest confidence that has not been suppressed as the new reference box, and repeat steps 3 and 4 until all detection boxes have been considered.

[0047] When used, the calculation formula of the IoU is,

[0048]

[0049] Among them, AOI refers to Area of ​​Intersection, which is the area of ​​the overlapping area of ​​two bounding boxes, and AOU refers to Area of ​​Union, which is the area of ​​the union of two bounding boxes, which is equal to the sum of their respective areas minus the area of ​​the overlapping area.

[0050] In particular, the IoU is calculated as follows,

[0051] If there are two bounding boxes A and B, their coordinates are (x A ,y A , w A ,h A ) and (x B ,y B , w B ,h B ), where w and h represent the width and height of the bounding box, respectively.

[0052] First calculate the coordinates of the intersection area of ​​the two bounding boxes:

[0053] Upper left corner coordinate, x min =max(x A , x B );

[0054] Coordinate of the lower right corner, y min =min(y A +h A ,y B +h B );

[0055] Width intersect =max(0,y min -x min );

[0056] Height intersect =max(0, x min -y min );

[0057] Then calculate the intersection area, AOI = w intersec *h intersect ;

[0058] Then calculate the area of ​​each of the two bounding boxes,

[0059] S A =w A *h A ;

[0060] S B =w B *h B ;

[0061] Then calculate the area of ​​the union region, AOU = S A +S B -AOI;

[0062] Finally, calculate IoU.

[0063] Furthermore, in practical applications, if w intersect or intersect If it is a negative number, that is, the two bounding boxes do not overlap, the IoU will be zero, indicating that the two bounding boxes have no or only a small overlap.

[0064] This embodiment also provides a computer device suitable for the situation when the improved photovoltaic cleaning device is used, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement all or part of the steps of the method described in the embodiment of the present invention as proposed in the above embodiment.

[0065] This embodiment also provides a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method in any optional implementation of the above embodiment is executed. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0066] Importantly, it should be noted that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are only exemplary. Although only a few embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible (e.g., the size, scale, structure, shape and proportion of various elements, and parameter values ​​(e.g., temperature, pressure, etc.), installation arrangement, use of materials, color, directional changes, etc.) without substantially departing from the novel teachings and advantages of the subject matter described in the application. For example, the element shown as integrally formed can be composed of multiple parts or elements, the position of the element can be inverted or otherwise changed, and the nature or number or position of the discrete element can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present invention. The order or sequence of any process or method steps can be changed or reordered according to alternative embodiments. In the claims, any "device plus function" clause is intended to cover the structure of performing the function described herein, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments. Therefore, the invention is not limited to a specific embodiment, but extends to numerous modifications still falling within the scope of the appended claims.

[0067] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0068] It will be appreciated that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but will be a routine task of design, fabrication, and production for those of ordinary skill having the benefit of this disclosure without undue experimentation.

[0069] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An improved photovoltaic cleaning device, characterized in that: Included are, an automated navigation system for locating the starting and ending points of cleaning on the photovoltaic panels; At least one cleaning unit for removing dust and dirt from the photovoltaic panels; and an intelligent sensing system for monitoring the cleaning status and avoiding damage to the photovoltaic panels.

2. The improved photovoltaic cleaning device according to claim 1, characterized in that: The cleaning unit includes a replaceable cleaning brush or a cleaning cloth.

3. The improved photovoltaic cleaning device according to claim 1 or 2, characterized in that: The automated navigation system includes sensors and a motion control unit for achieving precise positioning and path planning.

4. The improved photovoltaic cleaning device as claimed in claim 3, characterized in that: The intelligent sensing system includes at least one image sensor and a corresponding image processing algorithm for identifying the distribution of dirt on the photovoltaic panel.

5. The improved photovoltaic cleaning device as claimed in claim 4, characterized in that: Includes an intelligent control system to automatically adjust the cleaning strategy based on dirt distribution and cleaning status.

6. The improved photovoltaic cleaning device according to claim 4 or 5, characterized in that: The intelligent control system can remotely receive cleaning instructions and automatically start a cleaning program according to the actual degree of contamination of the photovoltaic panels.

7. The improved photovoltaic cleaning device according to claim 6, characterized in that: The intelligent image processing algorithm includes, inputting an image of a photovoltaic panel including a clean state; Using a convolutional neural network to extract features from an input image, wherein the convolutional neural network includes a plurality of convolutional layers and pooling layers for extracting image features layer by layer; Based on the convolutional neural network, a region proposal network (RPN) is used to generate candidate cleanliness regions. RPN searches for potential photovoltaic panel regions at different scales through a sliding window. Apply fully connected layers to the candidate regions generated by RPN for cleanliness classification and bounding box regression.

8. The improved photovoltaic cleaning device according to claim 7, characterized in that: The bounding box regression adopts the following formula, [x,y,w,h]=[x p ,y p ,w p ,h p ]+[dx,dy][dw,dh] Among them, [x, y, w, h] refers to the predicted box after transformation, [x p ,y p ,w p ,h p ] refers to the initial proposed cleanliness candidate region, [dx,dy] refers to the offset of the center point of the bounding box, and [dw,dh] refers to the scaling factor of the width and height of the bounding box.

9. A cleaning method using the device according to any one of claims 1 to 8, characterized in that: The method comprises the following steps: starting the automatic navigation system and locating the cleaning starting point; Activate the cleaning unit to start removing dirt from the photovoltaic panels; use the intelligent sensing system to monitor the cleaning effect; based on the feedback from the intelligent sensing system, the intelligent control system adjusts the cleaning strategy; After cleaning is completed, it automatically returns to the starting point or designated location.

10. A computer-readable storage medium having computer program instructions stored thereon, wherein the computer-executable instructions implement the steps of the method of claim 8 when executed by a processor.

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