Defect processing method and device for photovoltaic panel, electronic equipment and storage medium

Abstract

The invention discloses a defect processing method and device for a photovoltaic panel, electronic equipment and a storage medium. The method comprises the following steps: identifying the defect types of the photovoltaic panel in a photovoltaic panel image, the defect number corresponding to each defect type and the area occupied by each defect type; calculating a damage coefficient value corresponding to the photovoltaic panel, and when the damage coefficient value is greater than a damage coefficient threshold value, taking the photovoltaic panel as a photovoltaic panel to be maintained; calculating an external operation index value corresponding to the to-be-maintained photovoltaic panel according to the external environment parameters of the to-be-maintained photovoltaic panel, calculating an internal operation index value corresponding to the to-be-maintained photovoltaic panel according to the internal element parameters, and determining a damage reason of the to-be-maintained photovoltaic panel; and matching a treatment scheme corresponding to the damage reason according to the damage reason, and then performing defect treatment on the photovoltaic panel to be maintained according to the treatment scheme. According to the invention, the operation effect of the photovoltaic panel can be guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of defect recognition, and particularly to a method, device, electronic device and storage medium for defect processing of a photovoltaic panel. Background Art

[0002] With the increasing global emphasis on energy sustainability and environmental protection, solar energy, as a clean and renewable energy source, has witnessed rapid development in its development and utilization, and the photovoltaic industry has risen rapidly. Among them, the photovoltaic panel, as the core component of solar power generation, its performance and reliability directly affect the efficiency and stability of the photovoltaic power generation system. And the defects of the photovoltaic panel directly affect the performance and reliability of the photovoltaic panel. Therefore, it is necessary to inspect and identify the defects of the photovoltaic panel, and after identifying the defects of each photovoltaic panel, analyze whether each photovoltaic panel is damaged, analyze the cause of the damage, and perform maintenance processing on each damaged photovoltaic panel according to the cause of the damage.

[0003] The prior art can realize the defect recognition of the photovoltaic panel, select a suitable UAV model, plan the inspection path of the UAV according to the UAV model, and realize the recognition of the defects of the photovoltaic panel based on the UAV inspection by calculating the value of the latitude disaster coefficient. In the defect recognition step of the photovoltaic panel, the texture features and color features of the photovoltaic panel are defined, and the defect manifestation behavior recognition of the photovoltaic panel is completed according to the kernel function construction principle. However, the above prior art lacks the analysis of whether each photovoltaic panel is damaged and the analysis of the maintenance strategy for each damaged photovoltaic panel, and cannot determine whether each photovoltaic panel needs to be repaired, and cannot guarantee the operation effect of each photovoltaic panel in the future. Summary of the Invention

[0004] The present invention provides a method, device, electronic device and storage medium for defect processing of a photovoltaic panel to solve the technical problem that the prior art lacks the analysis of whether each photovoltaic panel is damaged and the analysis of the maintenance strategy for each damaged photovoltaic panel, and cannot determine whether each photovoltaic panel needs to be repaired, and cannot guarantee the operation effect of each photovoltaic panel in the future.

[0005] To solve the above technical problem, an embodiment of the present invention provides a method for defect processing of a photovoltaic panel, including:

[0006] Obtain an image of the photovoltaic panel;

[0007] Perform defect recognition on the image to identify the defect type of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type;

[0008] Based on the defect types of the photovoltaic panel, the number of defects corresponding to each defect type, and the area occupied by each defect type, a damage coefficient value corresponding to the photovoltaic panel is calculated, and the damage coefficient value is compared with a preset damage coefficient threshold. When the damage coefficient value is greater than the damage coefficient threshold, it is determined that the photovoltaic panel needs to be repaired, and the photovoltaic panel is used as a photovoltaic panel to be repaired;

[0009] Obtain the external environment parameters and internal component parameters of the photovoltaic panel to be repaired;

[0010] Based on the external environment parameters, an external operation index value corresponding to the photovoltaic panel to be repaired is calculated. Based on the internal component parameters, an internal operation index value corresponding to the photovoltaic panel to be repaired is calculated, and the external operation index value and the internal operation index value are respectively compared with a preset operation index threshold, and then the damage cause of the photovoltaic panel to be repaired is determined according to the comparison result;

[0011] According to the damage cause, a treatment plan corresponding to the damage cause is matched, and then the defect treatment of the photovoltaic panel to be repaired is carried out according to the treatment plan.

[0012] As a preferred solution, the obtaining of the image of the photovoltaic panel includes:

[0013] Obtain the historical defect types of the photovoltaic panel, the number of defects corresponding to each historical defect type, and the area occupied by each historical defect type;

[0014] Based on the historical defect types of the photovoltaic panel, the number of defects corresponding to each historical defect type, and the area occupied by each historical defect type, a historical inspection index value of the photovoltaic panel is calculated, and the historical inspection index value is compared with a preset inspection index threshold. When the historical inspection index value is greater than the inspection index threshold, the photovoltaic panel is used as a key inspection photovoltaic panel, otherwise the photovoltaic panel is used as an ordinary inspection photovoltaic panel;

[0015] When the photovoltaic panel is an ordinary inspection photovoltaic panel, control the drone to collect the image of the photovoltaic panel according to the preset highest image acquisition height and the preset S-shaped curve acquisition route;

[0016] When the photovoltaic panel is a key inspection photovoltaic panel, control the drone to collect the image of the photovoltaic panel according to the preset lowest image acquisition height and the preset cross-shaped curve acquisition route;

[0017] Among them, the historical inspection index value is calculated by the following formula:

[0018]

[0019] Among them, A ab is the inspection weight coefficient of the b-th defect type in the a-th photovoltaic panel; B ab is the weight coefficient of the number of defects of the b-th defect type in the a-th photovoltaic panel; C ab is the number of defects of the b-th defect type in the a-th photovoltaic panel; D ab is the weight coefficient of the area occupied by the b-th defect type in the a-th photovoltaic panel; E ab is the area occupied by the b-th defect type in the a-th photovoltaic panel; φ a is the inspection index of the a-th photovoltaic panel; a is the number of each photovoltaic panel, a = 1, 2, 3,..., c, and c is the total number of photovoltaic panels; b is the number of each defect type, b = 1, 2, 3,... d, and d is the total number of defect types. a, b, c, and d are all positive integers; E a is the area of the a-th photovoltaic panel; I 1 、I 2 and I 3 are respectively the weight coefficient of the inspection index of the defect type, the weight coefficient of the inspection index of the number of defects, and the weight coefficient of the inspection index of the area occupied by the defect.

[0020] As a preferred solution, the defect recognition of the image, and obtaining the defect type of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type, includes:

[0021] Input the image into a preset defect type recognition model, so that the defect type recognition model recognizes the defects existing in the photovoltaic panel in the image and the defect types corresponding to each defect and outputs them;

[0022] According to the defects existing in the photovoltaic panel in the image and the defect types corresponding to each defect, count the number of defects corresponding to each defect type;

[0023] Perform pixel statistics on the photovoltaic panel area of each defect type to obtain the area occupied by each defect type in the image;

[0024] Among them, the defect type recognition model is trained by inputting the historical image of the photovoltaic panel and outputting the defects existing in the photovoltaic panel in the historical image and the defect types corresponding to each defect to a preset convolutional neural network model.

[0025] As a preferred solution, the reasons for the damage include: poor external environment or internal damage of the photovoltaic panel;

[0026] According to the reasons for the damage, match the corresponding treatment solutions, including:

[0027] When the cause of the damage is poor external environment, obtain the external parameters, implementation duration, and implementation cost of each preset environmental governance plan;

[0028] According to the external parameters, implementation duration, and implementation cost of each environmental governance plan, calculate the priority coefficient value corresponding to each environmental governance plan, and then use the environmental governance plan with the highest priority coefficient value as the treatment plan for the photovoltaic panel to be repaired;

[0029] When the cause of the damage is internal damage of the photovoltaic panel, obtain the repair parameters, repair cost, and repair technical indicators in each preset internal repair plan;

[0030] According to the repair parameters, repair cost, and repair technical indicators in each internal repair plan, calculate the priority coefficient value corresponding to each internal repair plan, and then use the internal repair plan with the highest priority coefficient value as the treatment plan for the photovoltaic panel to be repaired;

[0031] Among them, the priority coefficient value corresponding to each environmental governance plan is calculated by the following formula:

[0032]

[0033] Among them, T u and S u are the implementation duration and cost of the u-th environmental governance plan respectively; T' and S' are the preset implementation duration threshold and preset governance cost respectively; V 1 and V 2 are the weight coefficients of the implementation duration and governance cost respectively; N u is the priority coefficient of the u-th environmental governance plan; u is the number of each environmental governance plan, u = 1, 2, 3,..., y, y represents the total number of environmental governance plans, and both u and y are positive integers;

[0034] The priority coefficient value corresponding to each internal repair plan is calculated by the following formula:

[0035]

[0036] Among them, X z and Y z are the cost and repair technical indicators of the z-th internal repair plan respectively; X' and Y' are the preset repair cost and preset repair technical indicators respectively; w 1 and w 2 are the weight coefficients of the repair cost and repair technology respectively; W z is the priority coefficient of the z-th internal repair plan; z is the number of each internal repair plan, is the total number of internal maintenance plans, z and are both positive integers.

[0037] As an optimal solution, the damage coefficient value corresponding to the photovoltaic panel is calculated by the following formula:

[0038]

[0039] where C ab is the number of defects of the b-th defect type in the a-th photovoltaic panel; C′ b is the preset threshold value of the number of defects of the b-th defect type; E ab is the area occupied by the b-th defect type in the a-th photovoltaic panel; E′ b is the preset threshold value of the area occupied by the b-th defect type; is the damage coefficient of the a-th photovoltaic panel; J 1 and J 2 are the weight coefficients of the number of defects and the area of defects respectively; a is the number of each photovoltaic panel, a = 1, 2, 3,..., c, c is the total number of photovoltaic panels; b is the number of each defect type, b = 1, 2, 3,... d, d is the total number of defect types, and a, c, b, and d are all positive integers.

[0040] As an optimal solution, the external operation index value corresponding to the photovoltaic panel to be repaired is calculated by the following formula:

[0041]

[0042] where ζ x is the external operation index value of the x-th photovoltaic panel to be repaired; R xp is the value of the p-th main external parameter of the x-th photovoltaic panel to be repaired; R′ p is the optimal value of the p-th main external parameter; L p is the weight coefficient of the p-th main external parameter; q is an adjustment coefficient, and q is a positive number; x is the number of each repair panel, x = 1, 2, 3,..., j, j is the total number of photovoltaic panels to be repaired; p is the number of each main external parameter, p = 1, 2, 3,..., r, r is the total number of main external parameters, and x, j, p, and r are all positive integers.

[0043] As an optimal solution, the internal operation index value corresponding to the photovoltaic panel to be repaired is calculated by the following formula:

[0044]

[0045] where M x is the internal operation index value of the x-th photovoltaic panel to be repaired; Gε is the value of the ε-th main internal parameter; G ε ′ is the optimal value of the ε-th main internal parameter; G ε1 and G ε2 are respectively the maximum value of the standard numerical range of the ε-th main internal parameter and the minimum value of the standard numerical range of the ε-th main internal parameter; σ ε is the weight coefficient of the ε-th main internal parameter; ε is the number of each main internal parameter, ε = 1, 2, 3,..., s, s is the total number of main internal parameters, and both ε and s are positive integers.

[0046] Based on the above embodiments, another embodiment of the present invention provides a defect processing device for a photovoltaic panel, including: an image acquisition module, a defect recognition module, a damage coefficient calculation module, a photovoltaic panel parameter acquisition module, a damage cause analysis module, and a repair processing module;

[0047] The image acquisition module is used to acquire an image of the photovoltaic panel;

[0048] The defect recognition module is used to perform defect recognition on the image, and recognize the defect types of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type;

[0049] The damage coefficient calculation module is used to calculate the damage coefficient value corresponding to the photovoltaic panel according to the defect types of the photovoltaic panel, the number of defects corresponding to each defect type, and the area occupied by each defect type, and compare the damage coefficient value with a preset damage coefficient threshold. When the damage coefficient value is greater than the damage coefficient threshold, it is determined that the photovoltaic panel needs to be repaired, and the photovoltaic panel is used as a photovoltaic panel to be repaired;

[0050] The photovoltaic panel parameter acquisition module is used to acquire the external environment parameters and internal component parameters of the photovoltaic panel to be repaired;

[0051] The damage cause analysis module is used to calculate the external operation index value corresponding to the photovoltaic panel to be repaired according to the external environment parameters, calculate the internal operation index value corresponding to the photovoltaic panel to be repaired according to the internal component parameters, and compare the external operation index value and the internal operation index value with a preset operation index threshold respectively, and then determine the damage cause of the photovoltaic panel to be repaired according to the comparison result;

[0052] The repair processing module is used to match a processing scheme corresponding to the damage cause according to the damage cause, and then perform defect processing on the photovoltaic panel to be repaired according to the processing scheme.

[0053] Based on the above embodiments, another embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the defect processing method of the photovoltaic panel described in the above embodiments of the present invention is implemented.

[0054] Based on the above embodiments, another embodiment of the present invention provides a storage medium, which includes a stored computer program. When the computer program runs, the device where the storage medium is located is controlled to execute the defect processing method of the photovoltaic panel described in the above embodiments of the present invention.

[0055] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0056] The present invention provides a method for processing defects of a photovoltaic panel, which performs defect identification on an image of the photovoltaic panel, and identifies the defect types of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type; calculates a damage coefficient value corresponding to the photovoltaic panel according to the defect types of the photovoltaic panel, the number of defects corresponding to each defect type, and the area occupied by each defect type, and compares the damage coefficient value with a preset damage coefficient threshold. When the damage coefficient value is greater than the damage coefficient threshold, it is determined that the photovoltaic panel needs to be repaired, and the photovoltaic panel is used as a photovoltaic panel to be repaired; obtains the external environmental parameters and internal component parameters of the photovoltaic panel to be repaired; calculates an external operation index value corresponding to the photovoltaic panel to be repaired according to the external environmental parameters, calculates an internal operation index value corresponding to the photovoltaic panel to be repaired according to the internal component parameters, and compares the external operation index value and the internal operation index value with a preset operation index threshold respectively, and then determines the damage cause of the photovoltaic panel to be repaired according to the comparison result; matches a processing scheme corresponding to the damage cause, and then performs defect processing on the photovoltaic panel to be repaired according to the processing scheme.

[0057] After the present invention performs defect identification on the photovoltaic panel, it also determines whether each photovoltaic panel needs to be repaired according to the number of defects in each defect type and the area occupied by each defect type in the photovoltaic panel, obtains the external environmental parameters and internal component parameters of the photovoltaic panel to be repaired, analyzes the damage cause of the photovoltaic panel to be repaired, matches the corresponding processing scheme, and ensures the operation effect of the photovoltaic panel. Description of the Drawings

[0058] Figure 1 is a schematic flowchart of a method for processing defects of a photovoltaic panel provided by an embodiment of the present invention;

[0059] Figure 2 It is a schematic structural diagram of a defect processing device for a photovoltaic panel provided by an embodiment of the present invention. Detailed implementation manners

[0060] To make the objectives, technical solutions, and advantages of the present application clearer, the technical solutions in the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are some but not all of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts fall within the scope of protection of the present application.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion.

[0062] In the description of the embodiments of the present application, technical terms such as "first" and "second" are only used to distinguish different objects and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity, specific order, or primary-secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "a plurality" is two or more, unless otherwise specifically defined.

[0063] Referring to "embodiments" herein means that specific features, structures, or characteristics described in connection with the embodiments may be included in at least one embodiment of the present application. The phrase does not necessarily refer to the same embodiment everywhere in the specification, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0064] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0065] In the description of the embodiments of the present application, the term "a plurality" refers to two or more (including two). Similarly, "multiple groups" refers to two or more groups (including two groups), and "multiple pieces" refers to two or more pieces (including two pieces).

[0066] In the description of the embodiments of the present application, unless otherwise clearly defined and limited, technical terms such as "installation", "connection", "connection", "fixation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can also be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific situations.

[0067] Embodiment 1

[0068] Please refer to Figure 1 , which is a schematic flowchart of a method for processing defects of a photovoltaic panel provided by an embodiment of the present invention, including the following specific steps:

[0069] S1. Obtain an image of the photovoltaic panel;

[0070] Preferably, the obtaining of the image of the photovoltaic panel includes: obtaining the historical defect types of the photovoltaic panel, the number of defects corresponding to each historical defect type, and the area occupied by each historical defect type; calculating the historical inspection index value of the photovoltaic panel according to the historical defect types of the photovoltaic panel, the number of defects corresponding to each historical defect type, and the area occupied by each historical defect type, and comparing the historical inspection index value with a preset inspection index threshold. When the historical inspection index value is greater than the inspection index threshold, the photovoltaic panel is used as a key inspection photovoltaic panel, otherwise the photovoltaic panel is used as an ordinary inspection photovoltaic panel; when the photovoltaic panel is an ordinary inspection photovoltaic panel, control the drone to collect the image of the photovoltaic panel according to the preset highest image acquisition height and the preset S-shaped curve acquisition route; when the photovoltaic panel is a key inspection photovoltaic panel, control the drone to collect the image of the photovoltaic panel according to the preset lowest image acquisition height and the preset cross-shaped curve acquisition route.

[0071] Among them, the historical inspection index value is calculated by the following formula:

[0072]

[0073] Among them, A ab is the inspection weight coefficient of the bth defect type in the ath photovoltaic panel; B ab is the weight coefficient of the number of defects of the bth defect type in the ath photovoltaic panel; C ab is the number of defects of the bth defect type in the ath photovoltaic panel; D ab is the weight coefficient of the area occupied by the bth defect type in the ath photovoltaic panel; E abis the area occupied by the b-th defect type in the a-th photovoltaic panel; φ a is the inspection index of the a-th photovoltaic panel; a is the number of each photovoltaic panel, a = 1, 2, 3,..., c, where c is the total number of photovoltaic panels; b is the number of each defect type, b = 1, 2, 3,...d, where d is the total number of defect types, and a, b, c, and d are all positive integers; E a is the area of the a-th photovoltaic panel; I 1 、I 2 and I 3 are the weight coefficients of the defect type inspection index, the defect quantity inspection index, and the area occupied by the defect inspection index respectively.

[0074] Specifically, in the prior art for the photovoltaic panel defect identification step, an appropriate UAV model is selected, the inspection path of the UAV is planned according to the UAV model, and the extraction of the defect quantity of the photovoltaic panel based on UAV inspection is realized by calculating the value of the dimensionality disaster coefficient. In the defect identification step of the photovoltaic panel, the texture features and color features of the photovoltaic panel are defined, and the defect manifestation behavior identification of the photovoltaic panel is completed according to the kernel function construction principle.

[0075] The prior art has at least the following technical problems:

[0076] (1) In the prior art, the inspection route of the UAV is planned according to the UAV model, without considering the defect types and defect quantities existing in each photovoltaic panel, and it is impossible to ensure the clarity of the defect images in the collected images of each photovoltaic panel and the accuracy of subsequent defect type identification;

[0077] (2) The prior art constructs the photovoltaic panel defect identification kernel function according to the texture features and color features of each photovoltaic panel image, and identifies the defects of each photovoltaic panel according to the defect identification kernel function of each photovoltaic panel. This process is computationally cumbersome and cannot accurately identify the defect types of each defect, the number of defects in each defect type, and the area occupied by each defect type;

[0078] (3) After identifying the defects of each photovoltaic panel, it is necessary to analyze whether each photovoltaic panel is damaged, analyze the cause of the damage, and repair each damaged photovoltaic panel according to the cause of the damage. However, the prior art lacks the analysis of whether each photovoltaic panel is damaged and the repair of each damaged photovoltaic panel, and it is impossible to determine whether each photovoltaic panel needs to be repaired, and it is impossible to ensure the operation effect of each photovoltaic panel in the future.

[0079] In view of the problems existing in the prior art, the present invention provides a method for processing defects of photovoltaic panels, which specifically includes the following steps:

[0080] Step 1: Collect images of photovoltaic panels:

[0081] A camera is mounted on the drone, and the number of defects that have existed in each photovoltaic panel is obtained from the database. According to the number of defects that have existed in each photovoltaic panel, the inspection route of the drone is planned, and the drone collects images of each photovoltaic panel according to the planned inspection route.

[0082] In a specific embodiment, the process of planning the inspection route of the drone is as follows: Obtain the types of defects that have existed in each photovoltaic panel, the number of defects in each type of defect, the area occupied by each type of defect, and the area of each photovoltaic panel from the database, and analyze the historical inspection indicators of each photovoltaic panel. Compare the historical inspection indicators of each photovoltaic panel with the preset inspection index threshold. If the historical inspection indicator of a certain photovoltaic panel is lower than the preset inspection index threshold, then this photovoltaic panel is an ordinary inspection photovoltaic panel; if the historical inspection indicator of a certain photovoltaic panel is higher than the preset inspection index threshold, then this photovoltaic panel is a key inspection photovoltaic panel. In this way, each ordinary inspection photovoltaic panel and each key inspection photovoltaic panel are obtained.

[0083] It should be noted that the preset inspection index threshold is set in advance according to the types of defects that have existed in each photovoltaic panel with a low historical damage degree and the number of defects in each type of defect.

[0084] Within each ordinary inspection photovoltaic panel, each ordinary panel is divided into each sub-region according to the preset maximum area threshold. When collecting images of each ordinary inspection panel, the drone is at the preset maximum acquisition height threshold and uses an S-shaped curve to collect images of each sub-region in each ordinary photovoltaic panel, and integrates the images of each sub-region to obtain images of each ordinary photovoltaic panel.

[0085] In each key inspection photovoltaic panel, each key inspection panel is divided into each sub-region according to the preset minimum area threshold. When collecting images of each key inspection panel, the drone is at the preset minimum acquisition height threshold and uses a "rice" - shaped curve to collect images of each sub-region in each key inspection panel, and integrates the images of each sub-region to obtain images of each key photovoltaic panel.

[0086] It should be noted that the preset maximum area is set according to the types of defects that have existed in each ordinary inspection photovoltaic panel and the number of defects, the preset minimum area is set according to the types of defects that have existed in each key inspection photovoltaic panel and the number of defects, and the preset maximum acquisition height and the preset minimum acquisition height are set according to the parameters of the camera on the drone.

[0087] The specific process of calculating the historical inspection indicators of each photovoltaic panel is as follows:

[0088]

[0089] Where A abThe inspection weight coefficient representing the b-th defect type in the a-th photovoltaic panel, B ab The weight coefficient representing the number of defects in the b-th defect type in the a-th photovoltaic panel, C ab The number of defects in the b-th defect type in the a-th photovoltaic panel, D ab The weight coefficient representing the area occupied by the b-th defect type in the a-th photovoltaic panel, E ab The area occupied by the b-th defect type in the a-th photovoltaic panel, φ a The inspection index of the a-th photovoltaic panel. Here, a represents the number of each photovoltaic panel, a = 1, 2, 3,..., c, where c represents the total number of photovoltaic panels; b represents the number of each defect type, b = 1, 2, 3,... d, where d represents the total number of defect types. a, b, c, and d are all positive integers, E a The area of the a-th photovoltaic panel, I 1 、I 2 、I 3 respectively represent the weight coefficient of the inspection index of the defect type, the weight coefficient of the inspection index of the number of defects, and the weight coefficient of the inspection index of the area occupied by the defect.

[0090] It should be noted that the inspection weight coefficients of each defect type are set according to the difficulty of image recognition of each defect type. The higher the difficulty of recognition, the higher the set inspection weight coefficient, and the sum of the inspection weight coefficients of each defect type is 1.

[0091] It should also be noted that the weight coefficients of the number of defects in each defect type are set according to the number of defects in each defect type. The higher the number of defects, the higher the set weight coefficient, and the sum of the weight coefficients of the number of defects in each defect type is 1.

[0092] It should also be noted that the weight coefficients of the area occupied by each defect type are set according to the size of the area occupied by each defect type. The larger the occupied area, the higher the set weight coefficient, and the sum of the weight coefficients of the area occupied by each defect type is 1.

[0093] It should also be noted that according to the sizes of the inspection index of the defect type, the inspection index of the number of defects, and the inspection index of the area occupied by the defect, the weight coefficient of the inspection index of the defect type, the weight coefficient of the inspection index of the number of defects, and the weight coefficient of the inspection index of the area occupied by the defect are set, and 1 +I 2 +I 3 = 1.

[0094] S2. Perform defect recognition on the said image to identify the defect types of the photovoltaic panels in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type;

[0095] Preferably, for defect recognition of the image to obtain the defect types of the photovoltaic panels in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type, it includes: inputting the image into a preset defect type recognition model to enable the defect type recognition model to recognize the defects existing in the photovoltaic panels in the image and the defect types corresponding to each defect and output them; according to the defects existing in the photovoltaic panels in the image and the defect types corresponding to each defect, statistically obtaining the number of defects corresponding to each defect type; performing pixel statistics on the photovoltaic panel areas of each defect type to obtain the area occupied by each defect type in the image; wherein, the defect type recognition model is trained by using historical images of photovoltaic panels as input and the defects existing in the photovoltaic panels in the historical images and the defect types corresponding to each defect as output on a preset convolutional neural network model.

[0096] Step 2. Identify defects:

[0097] Through deep learning technology, perform defect recognition on the image to obtain the defect types of the photovoltaic panels in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type.

[0098] It should be noted that before transmitting each photovoltaic panel image to the convolutional neural network, a large number of photovoltaic panel defect images are transmitted into the convolutional neural network to train the classification model of the convolutional neural network. The defect types of each defect in each photovoltaic panel image are identified through the trained classification model. For the number of defects, the number of defects of each defect type in each photovoltaic panel image can be obtained by counting the identified defect targets. By performing pixel statistics on the areas of each defect type and combining information such as the scale of the image, the area occupied by each defect type in each photovoltaic panel image is calculated through conversion.

[0099] S3. Calculate the damage coefficient value corresponding to the photovoltaic panel according to the defect types of the photovoltaic panel, the number of defects corresponding to each defect type, and the area occupied by each defect type, and compare the damage coefficient value with a preset damage coefficient threshold. When the damage coefficient value is greater than the damage coefficient threshold, it is determined that the photovoltaic panel needs to be repaired, and the photovoltaic panel is used as a photovoltaic panel to be repaired;

[0100] Preferably, the damage coefficient value corresponding to the photovoltaic panel is calculated by the following formula:

[0101]

[0102] where C ab is the number of defects of the bth defect type in the ath photovoltaic panel; C' bis the threshold of the number of defects of the preset b-th defect type; E ab is the area occupied by the b-th defect type in the a-th photovoltaic panel; E′ b is the threshold of the area occupied by the preset b-th defect type; is the damage coefficient of the a-th photovoltaic panel; J 1 and J 2 are respectively the weight coefficient of the number of defects and the weight coefficient of the defect area; a is the number of each photovoltaic panel, a = 1, 2, 3,..., c, c is the total number of photovoltaic panels; b is the number of each defect type, b = 1, 2, 3,... d, d is the total number of defect types, and a, c, b, and d are all positive integers.

[0103] Step 3: Obtain each photovoltaic panel to be repaired:

[0104] According to the number of defects in each defect type and the area occupied by each defect type in each photovoltaic panel, determine whether each photovoltaic panel needs to be repaired, and obtain each photovoltaic panel to be repaired;

[0105] In a specific embodiment, the process of determining whether each photovoltaic panel needs to be repaired and obtaining each photovoltaic panel to be repaired is as follows: Obtain the number of defects in each defect type and the area occupied by each defect type in each photovoltaic panel, and calculate the damage coefficient of each photovoltaic panel. Compare the damage coefficient of each photovoltaic panel with the preset damage coefficient threshold. If the damage coefficient of a certain photovoltaic panel is lower than the preset damage coefficient threshold, it means that the photovoltaic panel does not need to be repaired. If the damage coefficient of a certain photovoltaic panel is higher than the preset damage coefficient threshold, it means that the photovoltaic panel needs to be repaired. Use this method to determine whether each photovoltaic panel needs to be repaired, and call each photovoltaic panel that needs to be repaired each photovoltaic panel to be repaired.

[0106] It should be noted that the preset damage coefficient threshold is set according to the number of defects in each defect type and the area occupied by each defect type of each photovoltaic panel that has not been repaired historically.

[0107] The specific process of calculating the damage coefficient of each photovoltaic panel is as follows:

[0108]

[0109] In the formula C ab represents the number of defects in the b-th defect type in the a-th photovoltaic panel, C′ b represents the threshold of the number of defects in the preset b-th defect type, E ab represents the area occupied by the b-th defect type in the a-th photovoltaic panel, E′ b represents the threshold of the area occupied by the preset b-th defect type, represents the damage coefficient of the a-th photovoltaic panel, J1 and J 2 respectively represent the weight coefficient of the number of defects and the weight coefficient of the area of defects. a represents the number of each photovoltaic panel, a = 1, 2, 3,..., c, where c represents the total number of photovoltaic panels, b represents the number of each defect type, b = 1, 2, 3,... d, where d represents the total number of defect types. a, c, b, and d are all positive integers.

[0110] It should be noted that the number of defects and the area occupied by each defect type in each photovoltaic panel that has not been repaired historically are obtained, and the average value of the number of defects in each defect type and the average value of the area occupied by each defect type are calculated, and they are used as the threshold value of the number of defects in each preset defect type and the threshold value of the area occupied by each preset defect type.

[0111] It should also be noted that through experiments, when the numerical value of the number of defects is the same as the numerical value of the area of defects, the influence coefficient of the number of defects on the damage of the photovoltaic panel and the influence coefficient of the area of defects on the damage of the photovoltaic panel are determined. According to the magnitudes of the influence coefficient of the number of defects on the damage of the photovoltaic panel and the influence coefficient of the area of defects on the damage of the photovoltaic panel, the weight coefficient of the number of defects and the weight coefficient of the area of defects are set. The greater the influence coefficient, the greater the set weight coefficient, and the sum of the weight coefficient of the number of defects and the weight coefficient of the area of defects is 1.

[0112] S4. Obtain the external environmental parameters and internal component parameters of the photovoltaic panel to be repaired;

[0113] S5. According to the external environmental parameters, calculate the corresponding external operation index value of the photovoltaic panel to be repaired. According to the internal component parameters, calculate the corresponding internal operation index value of the photovoltaic panel to be repaired, and compare the external operation index value and the internal operation index value with a preset operation index threshold respectively, and then determine the damage cause of the photovoltaic panel to be repaired according to the comparison result;

[0114] Preferably, the corresponding external operation index value of the photovoltaic panel to be repaired is calculated by the following formula:

[0115]

[0116] where ζ x is the external operation index value of the xth photovoltaic panel to be repaired; R xp is the value of the pth main external parameter of the xth photovoltaic panel to be repaired; R′ p is the optimal value of the pth main external parameter; L pis the weight coefficient of the p-th main external parameter; q is the adjustment coefficient, and q is a positive number; x is the number of each maintenance panel, x = 1, 2, 3,..., j, where j is the total number of photovoltaic panels to be maintained; p is the number of each main external parameter, p = 1, 2, 3,..., r, where r is the total number of main external parameters, and x, j, p, and r are all positive integers.

[0117] Preferably, the internal operation index value corresponding to the photovoltaic panel to be maintained is calculated by the following formula:

[0118]

[0119] where M x is the internal operation index value of the x-th photovoltaic panel to be maintained; G ε is the value of the ε-th main internal parameter; G′ ε is the optimal value of the ε-th main internal parameter; G ε1 and G ε2 are respectively the maximum value of the standard numerical range of the ε-th main internal parameter and the minimum value of the standard numerical range of the ε-th main internal parameter; σ ε is the weight coefficient of the ε-th main internal parameter; ε is the number of each main internal parameter, ε = 1, 2, 3,..., s, where s is the total number of main internal parameters, and ε and s are both positive integers.

[0120] Step Four: Analyze the cause of damage:

[0121] Obtain the number of defects, each external parameter, and each internal parameter corresponding to each historical detection of each photovoltaic panel to be maintained, analyze the main parameters that cause the change in the number of defects in each defect type, obtain the main parameters of each photovoltaic panel to be maintained, and determine the cause of damage to each photovoltaic panel to be maintained.

[0122] It should be noted that the main parameters include the main external parameters and the main internal parameters; the external parameters include rainfall, tree distribution, and garbage quantity, etc., and the internal parameters include voltage, current, resistance, and temperature, etc.

[0123] In a specific embodiment, the process of analyzing the cause of damage to each photovoltaic panel to be maintained is as follows:

[0124] S11. Obtain the number of defects, each external environmental parameter, and each internal component parameter corresponding to each historical detection of each photovoltaic panel to be maintained from the database, and analyze the correlation coefficients between each defect type and each external parameter and each internal component parameter.

[0125] S12. Compare the correlation coefficients of each defect type with each external parameter and each internal component parameter with a preset correlation coefficient threshold. If the correlation coefficient of a certain defect type with a certain external parameter or internal parameter is lower than the preset correlation coefficient threshold, it means that the change in the number of defects of this defect type has a low correlation with the change in the value of this external parameter or internal parameter. If the correlation coefficient of a certain defect type with a certain external parameter or internal parameter is higher than the preset correlation coefficient threshold, it means that the change in the number of defects of this defect type has a high correlation with the change in the value of this external parameter or internal parameter, and this external parameter or internal parameter is called the main external parameter or main internal parameter. Obtain each main external parameter and each main internal parameter by this method.

[0126] It should be noted that through experiments, it is determined that under the condition that the change amounts of each external parameter or each internal parameter value are the same, the change amounts of the number of defects in each defect type are obtained, and a preset correlation coefficient threshold is set according to the change amounts of the number of defects in each defect type.

[0127] S13. Use a drone to collect panoramic images of each maintenance panel. Through deep learning technology, obtain each main external parameter in the panoramic images of each maintenance panel, and use sensors to collect each main internal component parameter of each maintenance photovoltaic panel. It should be noted that the sensors include resistance sensors, voltage sensors, current sensors, temperature sensors, etc.

[0128] S14. According to each main external parameter and each main internal component parameter of each maintenance photovoltaic panel, calculate the external operation index and internal operation index of each photovoltaic panel, and compare them with a preset operation index threshold. If the external operation index of a certain maintenance photovoltaic panel is lower than the preset operation index threshold, it means that the cause of damage to this photovoltaic panel to be repaired is poor external environment. If the internal operation index of a certain maintenance photovoltaic panel is lower than the preset operation index threshold, it means that the cause of damage to this photovoltaic panel to be repaired is internal damage of the photovoltaic panel.

[0129] It should be noted that obtain each main external parameter and each main internal parameter of each photovoltaic panel that has not been repaired historically, calculate the operation index threshold according to the obtained data, and use it as the preset operation index threshold.

[0130] In the above, the specific process of analyzing the correlation coefficients of each defect type with each external environment parameter and each internal component parameter is as follows:

[0131] S21. Calculate the change in the number of defects at adjacent historical detection times for each photovoltaic panel to be repaired, and compare it with a preset change threshold. If the change in the number of defects at a certain adjacent historical acquisition time for a certain photovoltaic panel to be repaired is lower than the preset change threshold, it means that the degree of damage to the photovoltaic panel to be repaired is low during the interval duration between the adjacent historical acquisition times. If the change in the number of defects at a certain adjacent historical acquisition time for a certain photovoltaic panel to be repaired is higher than the preset change threshold, it means that the degree of damage to the photovoltaic panel to be repaired is high during the interval duration between the adjacent historical acquisition times, and the interval duration between the adjacent historical acquisition times is called the damage time period. Obtain the damage time periods of each photovoltaic panel to be repaired in this way.

[0132] It should be noted that the preset change threshold is set by experimentally determining the degree of influence of changes in the number of different defects on the performance of the photovoltaic panel.

[0133] S22. Obtain the types of defects affected by each photovoltaic panel to be repaired during each damage time period, the change in the number of defects of each type of defect affected by each photovoltaic panel to be repaired during each damage time period, the change in the numerical values of each external parameter and the change in the numerical values of each internal parameter of each photovoltaic panel to be repaired during each damage time segment. According to the analysis formula: Obtain the average influence index β of the g-th external parameter of the x-th photovoltaic panel to be repaired on the f-th type of affected defect xfg and the average influence index χ of the i-th internal parameter of the x-th photovoltaic panel to be repaired on the f-th type of affected defect xfi , where F xgt represents the change in the numerical value of the g-th external parameter of the x-th photovoltaic panel to be repaired during the t-th damage time period, H xit represents the change in the numerical value of the i-th internal parameter of the x-th photovoltaic panel to be repaired during the t-th damage time period, G xft represents the change in the number of defects of the f-th type of affected defect of the x-th photovoltaic panel to be repaired during the t-th damage time period. x represents the number of each photovoltaic panel to be repaired, x = 1, 2, 3,..., j, where j represents the total number of photovoltaic panels to be repaired, f represents the number of each affected defect parameter, f = 1, 2, 3,..., k, where k represents the total number of affected defect types, g represents the number of each external parameter, g = 1, 2, 3,..., l, where l represents the total number of external parameters, t represents the number of each damage time segment, t = 1, 2, 3,..., m, where m represents the total number of damage time segments, i represents the number of each internal parameter, i = 1, 2, 3,..., n, where i represents the total number of internal parameters. x, j, f, k, g, l, t, m, i, and n are all positive integers.

[0134] S23. According to the analysis formula: Obtain the average value of the change in the number of defects of the f - th affected defect type in the x - th photovoltaic panel to be repaired According to the analysis formula: Obtain the correlation coefficient γ between the f - th affected defect type of the x - th photovoltaic panel to be repaired and the g - th external parameter xfg , according to the analysis formula: Obtain the correlation coefficient τ between the f - th affected defect type of the x - th photovoltaic panel to be repaired and the i - th internal parameter efi .

[0135] S24. According to the analysis formula: Obtain the correlation coefficient γ′ between the f - th defect type and the g - th external parameter fg and the correlation coefficient τ′ between the f - th defect type and the i - th internal parameter fg .

[0136] Among the above, the specific process of obtaining the affected defect types of each photovoltaic panel to be repaired in each damage time period is as follows:

[0137] Obtain the change in the number of defects of each defect type of each photovoltaic panel to be repaired in each damage time period, and compare the change in the number of defects of each defect type with the preset threshold of the change in the number of defects of each defect type. If the change in the number of defects of a certain defect type of a certain photovoltaic panel to be repaired in a certain damage time period is lower than the preset threshold of the change in the number of defects of this defect type, it means that the degree of influence of this defect type of this photovoltaic panel to be repaired in this damage time period is low. If the change in the number of defects of a certain defect type in a certain photovoltaic panel to be repaired in a certain damage time period is higher than the preset threshold of the change in the number of defects of this defect type, it means that the degree of influence of this defect type of this photovoltaic panel to be repaired in this damage time period is high, and this defect type is called the affected defect type. In this way, obtain the affected defect types of each photovoltaic panel to be repaired in each damage time period.

[0138] It should be noted that obtain the change in the number of defects of each defect type on each un - repaired photovoltaic panel in the same time period, and calculate the average value of the change in the number of defects of each defect type, and use it as the preset threshold of the change in the number of defects of each defect type.

[0139] Among the above, the specific process of calculating the external operation index and internal operation index of each photovoltaic panel to be repaired is as follows: According to the analysis formula: Obtain the external operation index ζ of the x - th photovoltaic panel to be repaired x , where R xp represents the value of the p - th main external parameter of the x - th photovoltaic panel to be repaired, and R′ prepresents the optimal value of the p-th main external parameter, L p represents the weight coefficient of the p-th main external parameter, q represents the adjustment coefficient, q is a positive number, x represents the number of each photovoltaic panel to be repaired, x = 1, 2, 3,..., j, j represents the total number of photovoltaic panels to be repaired, p represents the number of each main external parameter, p = 1, 2, 3,..., r, r represents the total number of main external parameters, and x, j, p, and r are all positive integers.

[0140] It should be noted that the weight coefficients of each main external parameter are set according to the influence degree of each main external parameter on the performance of the photovoltaic panel. The higher the influence degree, the higher the set weight coefficient, and the sum of the weight coefficients of each main external parameter is 1.

[0141] It should also be noted that the values of each main external parameter of each normally operating photovoltaic panel are obtained, and the average value of the values of each main external parameter is calculated and used as the optimal value of each external parameter.

[0142] According to the analysis formula: the internal operation index M of the x-th photovoltaic panel to be repaired is obtained x , where G ε represents the value of the ε-th main internal parameter, G ε ' represents the optimal value of the ε-th main internal parameter, G ε1 , G ε2 respectively represent the maximum value of the standard value range of the ε-th main internal parameter and the minimum value of the standard value range of the ε-th main internal parameter, and σ ε represents the weight coefficient of the ε-th main internal parameter, ε represents the number of each main internal parameter, ε = 1, 2, 3,..., s, s represents the total number of main internal parameters, and ε and s are both positive integers.

[0143] It should be noted that the weight coefficients of each main internal parameter are set according to the influence degree of each main internal parameter on the performance of the photovoltaic panel. The higher the influence degree, the higher the set weight coefficient, and the sum of the weight coefficients of each main internal parameter is 1. The optimal values of each main internal parameter are obtained from each photovoltaic panel manufacturer.

[0144] S6. According to the damage cause, match the corresponding treatment plan, and then perform defect treatment on the photovoltaic panel to be repaired according to the treatment plan.

[0145] Preferably, the reasons for damage include: poor external environment or internal damage of the photovoltaic panel; according to the reasons for damage, a treatment plan corresponding to the reasons for damage is matched, including: when the reason for damage is a poor external environment, obtaining the external parameters, implementation duration, and implementation cost governed by each preset environmental treatment plan; according to the external parameters, implementation duration, and implementation cost governed by each environmental treatment plan, calculating the priority coefficient value corresponding to each environmental treatment plan, and then taking the environmental treatment plan with the highest priority coefficient value as the treatment plan for the photovoltaic panel to be repaired; when the reason for damage is internal damage of the photovoltaic panel, obtaining the repair parameters, repair cost, and repair technical indicators in each preset internal repair plan; according to the repair parameters, repair cost, and repair technical indicators in each internal repair plan, calculating the priority coefficient value corresponding to each internal repair plan, and then taking the internal repair plan with the highest priority coefficient value as the treatment plan for the photovoltaic panel to be repaired;

[0146] Among them, the priority coefficient value corresponding to each environmental treatment plan is calculated by the following formula:

[0147]

[0148] Among them, T u and S u are respectively the implementation duration and the cost of the u-th environmental treatment plan; T' and S' are respectively the preset implementation duration threshold and the preset governance cost; V 1 and V 2 are respectively the weight coefficient of the implementation duration and the weight coefficient of the governance cost; N u is the priority coefficient of the u-th environmental treatment plan; u is the number of each environmental treatment plan, u = 1, 2, 3,..., y, y represents the total number of environmental treatment plans, and both u and y are positive integers;

[0149] The priority coefficient value corresponding to each internal repair plan is calculated by the following formula:

[0150]

[0151] Among them, X z and Y z are respectively the cost of the z-th internal repair plan and the repair technical index in the z-th internal repair plan; X' and Y' are respectively the preset repair cost and the preset repair technical index; w 1 and w 2 are respectively the weight coefficient of the repair cost and the weight coefficient of the repair technology; W z is the priority coefficient of the z-th internal repair plan; z is the number of each internal repair plan, is the total number of internal repair plans, z and All are positive integers.

[0152] Step Five: Repair the photovoltaic panel:

[0153] Select the optimal repair plan for repair according to the damage reasons of each photovoltaic panel to be repaired.

[0154] In a specific embodiment, the process of selecting the optimal repair plan for repair is as follows:

[0155] If the damage reason of a certain photovoltaic panel to be repaired is poor external environment:

[0156] S31. Obtain the main external parameters to be treated, the implementation duration and cost of each environmental treatment plan, and analyze the priority coefficient of each environmental treatment plan:

[0157]

[0158] In the formula, T u , S u respectively represent the implementation duration of the u-th environmental treatment plan and the cost of the u-th environmental treatment plan, T' and S' respectively represent the preset implementation duration threshold and the preset treatment cost, V 1 , V 2 respectively represent the weight coefficient of the implementation duration and the weight coefficient of the treatment cost, N u represents the priority coefficient of the u-th environmental treatment plan, u represents the number of each environmental treatment plan, u = 1, 2, 3,..., y, y represents the total number of environmental treatment plans, and both u and y are positive integers.

[0159] It should be noted that the preset treatment cost and the preset implementation duration are set according to the existing repair funds and the repair time required by the team members.

[0160] S32. Select the environmental treatment plan with the highest priority coefficient as the repair plan for this repair panel.

[0161] If the damage reason of a certain photovoltaic panel to be repaired is internal damage of the photovoltaic panel:

[0162] S41. Select the parameters to be repaired, the repair cost and the repair technical indicators of each internal repair plan, and analyze the priority coefficient of each internal repair plan:

[0163]

[0164] In the formula, X z , Y z respectively represent the cost of the z-th internal repair plan and the repair technical indicators in the z-th internal repair plan, X' and Y' respectively represent the preset repair cost and the preset repair technical indicators, w1 , w 2 respectively represent the weight coefficient of the maintenance cost and the weight coefficient of the maintenance technology. z represents the number of each internal maintenance plan, and W z represents the priority coefficient of the z-th internal maintenance plan. represents the total number of internal maintenance plans. Both z and are positive integers.

[0165] It should be noted that when formulating each internal maintenance plan, the maintenance technology in each internal maintenance plan is evaluated, and according to the evaluation results, the maintenance technology indicators of each internal maintenance plan are set.

[0166] It should also be noted that a preset maintenance cost is set according to the existing maintenance funds.

[0167] It should also be noted that according to the maintenance skills mastered by each group member, the comprehensive maintenance technology indicators of the maintenance team are analyzed and used as the preset maintenance indicators.

[0168] S42. Select the internal maintenance plan with the highest priority coefficient as the maintenance plan for the panel to be repaired;

[0169] Through the steps of S31 - S42 above, the optimal maintenance plan for each photovoltaic panel to be repaired is obtained, that is, the treatment plan for the photovoltaic panel to be repaired. Then, the photovoltaic panel to be repaired is defect - treated according to the treatment plan.

[0170] Thus, it can be seen that the present invention provides a method for defect - treating a photovoltaic panel. Through the present invention, the following beneficial effects can be achieved:

[0171] (1) First, according to the data of each defect type that each photovoltaic panel has historically had, the drone inspection route is planned. Then, deep - learning technology is used to obtain the data of each defect type existing in the images of each photovoltaic panel, and each photovoltaic panel to be repaired is obtained. After that, the number of defects and the numerical values of each parameter corresponding to each historical detection of each photovoltaic panel to be repaired in each defect type are obtained. The main parameters that cause the change in the number of defects in each defect type are analyzed, and the damage reasons of each repaired photovoltaic panel are analyzed. Finally, the optimal maintenance plan is selected for repair, which increases the judgment on whether each photovoltaic panel is damaged, ensures the clarity of each defect image and the future operation effect of each photovoltaic panel, and also ensures the accuracy of defect type recognition, the number of defects in each defect type and the occupied area.

[0172] (2) According to the historical defect types of each photovoltaic panel, the number of defects in each defect type, the area occupied by each defect type, and the area of each photovoltaic panel, each photovoltaic panel is divided into each ordinary inspection photovoltaic panel and each key inspection area photovoltaic panel. In each ordinary inspection photovoltaic panel, an S-shaped curve is used to collect images of each sub-region in each ordinary photovoltaic panel, and in each key inspection photovoltaic panel, a "cross" shaped curve is used to collect images of each sub-region in each key inspection panel, ensuring the clarity of each defect image and the accuracy of defect type identification. Moreover, through deep learning technology, the defect types of each defect, the number of defects in each defect type, and the area occupied by each defect type are accurately identified, reducing the calculation process of defect identification.

[0173] (3) According to the number of defects in each defect type and the area occupied by each defect type in each photovoltaic panel, it is determined whether each photovoltaic panel needs to be repaired, and the main parameters of each repaired photovoltaic panel are obtained. The reasons for the damage of each repaired photovoltaic panel are analyzed, and the optimal repair plan is selected to ensure the future operation effect of each photovoltaic panel.

[0174] Embodiment 2

[0175] Please refer to Figure 2 , which is a schematic structural diagram of a defect processing device for a photovoltaic panel provided by an embodiment of the present invention. The device includes: an image acquisition module, a defect identification module, a damage coefficient calculation module, a photovoltaic panel parameter acquisition module, a damage cause analysis module, and a repair processing module;

[0176] The image acquisition module is used to acquire images of photovoltaic panels;

[0177] The defect identification module is used to identify defects in the image, and identify the defect types of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type;

[0178] The damage coefficient calculation module is used to calculate the corresponding damage coefficient value of the photovoltaic panel according to the defect type of the photovoltaic panel, the number of defects corresponding to each defect type, and the area occupied by each defect type, and compare the damage coefficient value with a preset damage coefficient threshold. When the damage coefficient value is greater than the damage coefficient threshold, it is determined that the photovoltaic panel needs to be repaired, and the photovoltaic panel is used as a to-be-repaired photovoltaic panel;

[0179] The photovoltaic panel parameter acquisition module is used to acquire the external environment parameters and internal component parameters of the to-be-repaired photovoltaic panel;

[0180] The damage cause analysis module is configured to calculate the external operation index value corresponding to the photovoltaic panel to be repaired according to the external environment parameters, calculate the internal operation index value corresponding to the photovoltaic panel to be repaired according to the internal component parameters, compare the external operation index value and the internal operation index value with a preset operation index threshold respectively, and then determine the damage cause of the photovoltaic panel to be repaired according to the comparison result;

[0181] The repair processing module is configured to match a processing solution corresponding to the damage cause according to the damage cause, and then perform defect processing on the photovoltaic panel to be repaired according to the processing solution.

[0182] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the attached drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that they have a communication connection, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0183] Those skilled in the art can clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the foregoing method embodiment, and will not be elaborated here.

[0184] Embodiment III

[0185] Correspondingly, an embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the method for defect processing of the photovoltaic panel described in the foregoing invention embodiments.

[0186] The electronic device may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The device may include, but is not limited to, a processor and a memory.

[0187] The so-called processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the device and connects various parts of the entire device through various interfaces and lines.

[0188] Embodiment 4

[0189] Correspondingly, an embodiment of the present invention provides a storage medium, the storage medium includes a stored computer program, wherein, when the computer program runs, it controls the device where the storage medium is located to execute the photovoltaic panel defect processing method described in the above-mentioned embodiment of the invention.

[0190] The memory can be used to store the computer program. The processor realizes various functions of the device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices.

[0191] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0192] The above is the preferred embodiment of the present invention. It should be pointed out that for those of ordinary skill in the art of the present technology, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope of the present invention.

Claims

1. A method for handling defects of a photovoltaic panel, characterized in that: include: Acquire images of photovoltaic panels; Performing defect recognition on the image to obtain defect types of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type; According to the defect type of the photovoltaic panel, the number of defects corresponding to each defect type, and the area occupied by each defect type, a damage coefficient value corresponding to the photovoltaic panel is calculated, and the damage coefficient value is compared with a preset damage coefficient threshold value. When the damage coefficient value is greater than the damage coefficient threshold value, it is determined that the photovoltaic panel needs to be repaired, and the photovoltaic panel is used as a photovoltaic panel to be repaired; Acquiring external environmental parameters and internal component parameters of the photovoltaic panel to be repaired; According to the external environmental parameters, an external operating index value corresponding to the photovoltaic panel to be repaired is calculated, and according to the internal component parameters, an internal operating index value corresponding to the photovoltaic panel to be repaired is calculated, and the external operating index value and the internal operating index value are respectively compared with a preset operating index threshold value, and then the damage cause of the photovoltaic panel to be repaired is determined according to the comparison result; According to the damage cause, a treatment plan corresponding to the damage cause is matched, and then defects of the photovoltaic panel to be repaired are treated according to the treatment plan.

2. The photovoltaic panel defect treatment method according to claim 1, characterized in that: The step of acquiring an image of a photovoltaic panel comprises: Obtain the historical defect types of photovoltaic panels, the number of defects corresponding to each historical defect type, and the area occupied by each historical defect type; According to the historical defect types of the photovoltaic panel, the number of defects corresponding to each historical defect type, and the area occupied by each historical defect type, a historical inspection index value of the photovoltaic panel is calculated, and the historical inspection index value is compared with a preset inspection index threshold value. When the historical inspection index value is greater than the inspection index threshold value, the photovoltaic panel is regarded as a key inspection photovoltaic panel, otherwise, the photovoltaic panel is regarded as a common inspection photovoltaic panel; When the photovoltaic panel is a common inspection photovoltaic panel, the drone is controlled to collect images of the photovoltaic panel according to a preset maximum image collection height and a preset S-curve collection line; When the photovoltaic panel is a key inspection photovoltaic panel, the drone is controlled to collect images of the photovoltaic panel according to a preset minimum image collection height and a preset cross-shaped curve collection line; The historical inspection index value is calculated by the following formula: Among them, A ab B is the inspection weight coefficient of the bth defect type in the ath photovoltaic panel; ab is the weight coefficient of the number of defects of the bth defect type in the ath photovoltaic panel; C ab is the number of defects of the bth defect type in the ath photovoltaic panel; D ab is the weight coefficient of the area occupied by the bth defect type in the ath photovoltaic panel; E ab is the area occupied by the bth defect type in the ath photovoltaic panel; φ a is the inspection index of the a-th photovoltaic panel; a is the number of each photovoltaic panel, a=1,2,3,...,c, c is the total number of photovoltaic panels; b is the number of each defect type, b=1,2,3,...d, d is the total number of defect types, a, b, c and d are all positive integers; E a is the area of ​​the ath photovoltaic panel; I1, I2 and I3 are the weight coefficients of the defect type inspection index, the weight coefficient of the defect quantity inspection index and the weight coefficient of the defect area inspection index respectively.

3. The photovoltaic panel defect treatment method according to claim 1, characterized in that: The performing defect recognition on the image to obtain the defect type of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type includes: Inputting the image into a preset defect type recognition model, so that the defect type recognition model recognizes and outputs defects existing in the photovoltaic panel in the image and defect types corresponding to each defect; According to the defects existing in the photovoltaic panel in the image and the defect types corresponding to the defects, the number of defects corresponding to the defect types is obtained by counting; Perform pixel statistics on the photovoltaic panel area of ​​each defect type to obtain the area occupied by each defect type in the image; The defect type recognition model is obtained by training a preset convolutional neural network model with historical images of photovoltaic panels as input, defects of photovoltaic panels in the historical images, and defect types corresponding to each defect as output.

4. The photovoltaic panel defect treatment method according to claim 1, characterized in that: The damage causes include: poor external environment or internal damage to the photovoltaic panel; According to the damage cause, matching a processing solution corresponding to the damage cause includes: When the damage is caused by a poor external environment, the external parameters, implementation time and implementation cost of each preset environmental management plan are obtained; Calculate the priority coefficient value corresponding to each of the environmental governance schemes according to the external parameters governed by each of the environmental governance schemes, the implementation time and the implementation cost, and then use the environmental governance scheme with the highest priority coefficient value as the treatment scheme for the photovoltaic panel to be repaired; When the damage is caused by internal damage to the photovoltaic panel, the maintenance parameters, maintenance costs and maintenance technical indicators in each preset internal maintenance plan are obtained; Calculate the priority coefficient value corresponding to each of the internal maintenance plans according to the maintenance parameters, maintenance costs and maintenance technical indicators in each of the internal maintenance plans, and then use the internal maintenance plan with the highest priority coefficient value as the processing plan for the photovoltaic panel to be repaired; The priority coefficient values ​​corresponding to the environmental governance schemes are calculated by the following formula: Among them, T u and S u are the implementation time and cost of the u-th environmental governance plan respectively; T′ and S′ are the preset implementation time threshold and the preset governance cost respectively; V1 and V2 are the weight coefficients of the implementation time and the governance cost respectively; N u is the priority coefficient of the u-th environmental governance plan; u is the number of each environmental governance plan, u = 1, 2, 3, ..., y, y represents the total number of environmental governance plans, and u and y are both positive integers; The priority coefficient value corresponding to each internal maintenance plan is calculated by the following formula: Among them, X z and Y z are the cost of the z-th internal maintenance plan and the maintenance technical index in the z-th internal maintenance plan respectively; X′ and Y′ are the preset maintenance cost and the preset maintenance technical index respectively; w1 and w2 are the weight coefficient of the maintenance cost and the weight coefficient of the maintenance technology respectively; W z is the priority coefficient of the zth internal maintenance plan; z is the number of each internal maintenance plan, is the total number of internal maintenance options, z and All are positive integers.

5. The photovoltaic panel defect treatment method according to claim 1, characterized in that: The damage coefficient value corresponding to the photovoltaic panel is calculated by the following formula: Among them, C ab is the number of defects of the bth defect type in the ath photovoltaic panel; C b ′ is the preset defect quantity threshold of the bth defect type; E ab is the area occupied by the bth defect type in the ath photovoltaic panel; E b ′ is the preset area threshold occupied by the b-th defect type; is the damage coefficient of the a-th photovoltaic panel; J1 and J2 are the weight coefficient of the defect number and the weight coefficient of the defect area respectively; a is the number of each photovoltaic panel, a=1,2,3,...,c, c is the total number of photovoltaic panels; b is the number of each defect type, b=1,2,3,...d, d is the total number of defect types, and a, c, b and d are all positive integers.

6. The photovoltaic panel defect treatment method according to claim 1, characterized in that: The external operating index value corresponding to the photovoltaic panel to be repaired is calculated by the following formula: Among them, x is the external operating index value of the xth photovoltaic panel to be repaired; R xp is the value of the pth main external parameter of the xth photovoltaic panel to be repaired; R′ p is the optimal value of the pth main external parameter; L p is the weight coefficient of the pth main external parameter; q is the adjustment coefficient, q is a positive number; x is the number of each maintenance panel, x = 1, 2, 3, ..., j, j is the total number of photovoltaic panels to be repaired; p is the number of each main external parameter, p = 1, 2, 3, ..., r, r is the total number of main external parameters, x, j, p and r are all positive integers.

7. The photovoltaic panel defect treatment method according to claim 1, characterized in that: The internal operating index value corresponding to the photovoltaic panel to be repaired is calculated by the following formula: Among them, M x is the internal operating index value of the xth photovoltaic panel to be repaired; G ε is the value of the εth main internal parameter; G ε ′ is the optimal value of the εth main internal parameter; G ε1 and G ε2 are the maximum value of the standard numerical range of the εth main internal parameter and the minimum value of the standard numerical range of the εth main internal parameter respectively; σ ε is the weight coefficient of the εth main internal parameter; ε is the number of each main internal parameter, ε=1,2,3,...,s, s is the total number of main internal parameters, and ε and s are both positive integers.

8. A photovoltaic panel defect treatment device, characterized in that: include: Image acquisition module, defect recognition module, damage coefficient calculation module, photovoltaic panel parameter acquisition module, damage cause analysis module and maintenance processing module; The image acquisition module is used to acquire an image of the photovoltaic panel; The defect recognition module is used to perform defect recognition on the image, and identify the defect type of the photovoltaic panel in the image, the number of defects corresponding to each defect type, and the area occupied by each defect type; The damage coefficient calculation module is used to calculate the damage coefficient value corresponding to the photovoltaic panel according to the defect type of the photovoltaic panel, the number of defects corresponding to each defect type, and the area occupied by each defect type, and compare the damage coefficient value with a preset damage coefficient threshold value. When the damage coefficient value is greater than the damage coefficient threshold value, it is determined that the photovoltaic panel needs to be repaired, and the photovoltaic panel is used as a photovoltaic panel to be repaired; The photovoltaic panel parameter acquisition module is used to acquire the external environment parameters and internal component parameters of the photovoltaic panel to be repaired; The damage cause analysis module is used to calculate the external operating index value corresponding to the photovoltaic panel to be repaired according to the external environmental parameters, calculate the internal operating index value corresponding to the photovoltaic panel to be repaired according to the internal component parameters, and compare the external operating index value and the internal operating index value with a preset operating index threshold value respectively, and then determine the damage cause of the photovoltaic panel to be repaired according to the comparison result; The repair processing module is used to match a processing scheme corresponding to the damage cause according to the damage cause, and then perform defect processing on the photovoltaic panel to be repaired according to the processing scheme.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the defect handling method for the photovoltaic panel as claimed in any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is executed, the device where the storage medium is located is controlled to execute the photovoltaic panel defect processing method according to any one of claims 1 to 7.

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