CN114926395A - Photovoltaic panel infrared image string drop detection method and system - Google Patents
Photovoltaic panel infrared image string drop detection method and system Download PDFInfo
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Abstract
The invention discloses a photovoltaic panel infrared image string drop detection method and a system, wherein the method comprises the following steps: s1, collecting an infrared image of the photovoltaic module; s2, segmenting each small photovoltaic module in the infrared image by using an image segmentation technology; s3, calculating the pixel gray average value of all pixels in the G channel of each divided small photovoltaic module area, and representing the whole gray value distribution condition of the small photovoltaic module area by the gray average value; s4, setting a pixel gray threshold of the G channel, and judging whether the small photovoltaic module is a string drop module or not according to the comparison between the gray average value calculated in the step S3 and the gray threshold; s5, combining the edges of the string dropping components to obtain a string dropping area; s6, carrying out test verification on the string falling area; and S7, outputting and displaying the string identification result. The invention can avoid energy waste and dangerous accidents caused by string dropping. The algorithm is simple and practical, and time waste and fund consumption caused by manual detection are reduced.
Description
Technical Field
The invention relates to the field of photovoltaic power generation, in particular to a photovoltaic panel infrared image string drop detection method and system.
Background
As a clean energy source, photovoltaic power generation is becoming more and more unique in the power field. In recent years, more and more solar photovoltaic modules are used in photovoltaic power stations. Due to the fact that the solar cell panel works outdoors for a long time and is influenced by natural disasters such as environment in a power station, strong wind, hail and the like, the solar cell panel inevitably breaks down, and even the whole string falls. How to automatically detect the string drop of the solar cell panel component is particularly critical to the improvement of the power generation efficiency and the guarantee of the safety of a power station.
The heating characteristics of the solar panel are clearly visible in the thermal imaging image, so that the faults of the components on the photovoltaic panel are easier to detect by using the thermal imaging image. When a component string falls on the photovoltaic panel, the temperature of the component in the string falling area is higher. Based on this, the string-missing component can be distinguished from the normal component. Due to the particularity of the string drop fault, the string drop fault is difficult to detect by using methods such as deep learning and the like. At present, manual detection methods are mostly adopted for detecting the string-dropping faults, and are time-consuming and labor-consuming.
Disclosure of Invention
In order to solve the existing problems, the invention provides a photovoltaic panel infrared image string drop detection method and a system, and the specific scheme is as follows:
a photovoltaic panel infrared image string drop detection method comprises the following steps:
s1, collecting an infrared image of the photovoltaic module;
s2, segmenting each small photovoltaic module in the infrared image acquired in the step S1 by utilizing an image segmentation technology;
s3, calculating the pixel gray level mean value of all pixels of each small photovoltaic module area segmented in the step S2 in a G channel, and representing the whole gray level value distribution condition of the small photovoltaic module area by the gray level mean value;
s4, setting a pixel gray threshold of a G channel, and judging whether the small photovoltaic module is a string drop module or not according to the comparison between the gray average value calculated in the step S3 and the gray threshold;
s5, combining the edges of the string dropping component to obtain a string dropping area;
s6, carrying out test verification on the string falling area;
and S7, outputting and displaying the string identification result.
Preferably, in step S1, an infrared camera is mounted on the drone to capture an infrared image.
Preferably, in the step S3, the G channel pixel gray value mean of the small photovoltaic module i
Comprises the following steps:
one of the small photovoltaic modules is marked as i, and the pixel area in the image where the small photovoltaic module is positioned is omega i The G channel image of the infrared image is I, and (x, y) is a certain pixel coordinate of the image I, | omega i L is the pixel region omega i The number of pixels in the pixel.
Preferably, in step S4, the G-channel pixel grayscale threshold is set to 200, when the grayscale mean value is greater than 200, it is determined that the small photovoltaic module is a string drop module, and if the grayscale mean value is less than 200, it is determined that the small photovoltaic module is a non-string drop module.
Preferably, the step of obtaining the run-out region in step S5 includes:
s51, utilizing a findContours function in OpenCV to identify and frame the edges of the small divided photovoltaic modules,
s52, according to the string dropping component identified in the step S4, excluding the edge of the non-string dropping component and reserving the edge of the string dropping component;
and S53, removing the overlapped part of the edge frames of the string dropping component, and only reserving the outer frame of the string dropping component area, namely framing the string dropping area by a large rectangular frame.
Preferably, the test verifying step of step S6 includes:
s61, if the number of the small photovoltaic modules divided in the infrared image meets the string drop judgment condition is less than or equal to 3, judging that the image is a non-string drop fault image;
s62, checking and judging whether the serial numbers of the string dropping components are continuous or not to analyze whether the areas of the string dropping components in the image are continuous or not, and judging the image to be a non-string dropping fault image if the small components of the string dropping components are scattered in the infrared image;
s63, if the whole gray value of the infrared image of the photovoltaic panel is large, all small photovoltaic modules in the image are easily judged to be string dropping due to reflection, at the moment, the average value of the gray levels of G channels of the string dropping modules and the average value of the gray levels of G channels of the non-string dropping modules are respectively calculated, the difference value between the average value of the gray levels of the G channels of the string dropping modules and the average value of the gray levels of the G channels of the non-string dropping modules is calculated, and if the difference value is smaller than 20 pixels, the image is judged to be a non-string dropping fault image.
The invention also discloses a computer readable storage medium, wherein a computer program is stored on the medium, and after the computer program is operated, the photovoltaic panel infrared image string drop detection method is executed.
The invention also discloses a computer system which comprises a processor and a storage medium, wherein the storage medium is stored with a computer program, and the processor reads and runs the computer program from the storage medium to execute the photovoltaic panel infrared image string drop detection method.
Preferably, the system of the photovoltaic panel infrared image string drop detection method comprises a data acquisition module, a data transmission module, a data storage module, a data processing module and a data display module which are electrically connected in sequence;
the data acquisition module is an infrared camera carrying an unmanned aerial vehicle and is used for acquiring infrared images of the photovoltaic module;
the data transmission module is used for transmitting the infrared image data acquired by the infrared camera to the data storage module;
the data storage module is used for storing infrared image data acquired by the infrared camera;
the data processing module is used for analyzing, processing and verifying the infrared image data in the data memory module and then uploading the infrared image data to the data display module;
and the data display module is used for displaying the string identification result.
The invention has the beneficial effects that:
according to the invention, the string-dropping fault detection is carried out on the infrared image of the photovoltaic panel by means of image processing, so that energy waste and dangerous accidents caused by string dropping can be avoided. Compared with recognition methods such as deep learning, the algorithm has the characteristics of simplicity, instantaneity, practicability and the like, so that time waste and fund consumption caused by manual detection are reduced. The algorithm has the greatest characteristic that the algorithm is carried out according to the priori knowledge of the gray value difference of the G channel between the string dropping area and the non-string dropping area, so that the algorithm has great simplicity, the implementation process is simple, the identification effect is good, and the algorithm has the greatest advantages of feasibility and practicability.
Drawings
In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the embodiments or technical solutions of the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
For infrared images of photovoltaic panels, they are generally analyzed from the point of view of their grayscale images as well as the RGB three-channel images. For an image of an R channel of an infrared image, if gray values of all component areas are large, the string dropping component and the non-string dropping component are difficult to distinguish; for a B-channel image of an infrared image, gray values of all component areas are small, the gray value of a string-dropping component tends to zero, and although the string-dropping component has a larger gray value than a non-string-dropping component, the string-dropping component and the non-string-dropping component are still difficult to distinguish; therefore, the R-channel image and the B-channel image of the infrared image are excluded as reference images for identifying the string fault.
In the photovoltaic panel infrared image, the pixel gray values of the string-dropping component and the non-string-dropping component in the G channel image have great difference. Therefore, the string falling assembly in the infrared image can be separated out, and the purpose of detecting the string falling fault of the photovoltaic panel is achieved.
The intuitive and essential difference between the string dropping component and the non-string dropping component in the infrared image of the photovoltaic panel is the difference in temperature, but the numerical difference caused by the temperature difference is too small, so that the difference in temperature is utilized to set a threshold value to identify the string dropping component area in the infrared image, which is not practical. The difference in temperature between the dropped component and the non-dropped component in the infrared image is reflected in the difference in gray value in the image, and the gray value is very different, so that it is appropriate and practical to set a threshold value to identify a dropped component and a region with a string fault using the great difference in gray value between the dropped region and the non-dropped region.
Referring to fig. 1, a photovoltaic panel infrared image string drop detection method includes the following steps:
s1, collecting an infrared image of the photovoltaic module by using an unmanned aerial vehicle carrying an infrared camera;
s2, segmenting the image by using an image segmentation technology and an image processing or deep learning method, and segmenting each small photovoltaic module in the infrared image acquired in the step S1;
s3, calculating the pixel gray average value of all pixels of each small photovoltaic module area segmented in the step S2 in a G channel, and representing the whole gray value distribution condition of the small photovoltaic module area by the gray average value;
small lightMean value of grey values of G-channel pixels of voltage component i
Comprises the following steps:
one of the small photovoltaic modules is marked as i, and the pixel area in the image where the small photovoltaic module is positioned is omega i The G channel image of the infrared image is I, and (x, y) is a certain pixel coordinate, | omega of the image I i L is the pixel region omega i The number of pixels in the pixel.
S4, setting a pixel gray threshold of the G channel, and judging whether the small photovoltaic module is a string drop module or not according to the comparison between the gray average value calculated in the step S3 and the gray threshold; and setting the gray level threshold value of the G channel pixel to be 200, judging the small photovoltaic module to be a string dropping module when the gray level mean value is more than 200, and judging the small photovoltaic module to be a non-string dropping module if the gray level mean value is less than 200.
The gray threshold is set by counting the mean value of the gray values of the G channels of all the divided small assemblies. The average gray scale value of the G channel of the string-dropping component is about 220-240, and the average gray scale value of the G channel of the non-string-dropping component is about 140-150, which is much lower than 200, so the difference between the two is about 60-80. To include some deviation, the gray-level value of 200 is used as a boundary, the G-channel gray-level value with the mean value of 200 is regarded as a dropped device, and the G-channel gray-level value with the mean value of less than 200 is regarded as a non-dropped device.
S5, combining the edges of the string dropping component to obtain a string dropping area;
the step of obtaining the string dropping area comprises the following steps:
s51, utilizing a findContours function in OpenCV to identify and frame the edges of the small segmented photovoltaic modules,
s52, according to the string dropping component identified in the step S4, eliminating the edge of the string dropping component and keeping the edge of the string dropping component;
and S53, removing the overlapped part of the edge frames of the string-dropping assembly, and only reserving the outer frame of the string-dropping assembly area, namely framing the string-dropping area by a large rectangular frame.
S6, carrying out test verification on the string falling area; wherein, the test verification step comprises:
s61, if the number of the small photovoltaic modules divided in the infrared image meets the string drop judgment condition is less than or equal to 3, judging that the image is a non-string drop fault image;
s62, checking and judging whether the serial numbers of the string dropping components are continuous or not to analyze whether the areas of the string dropping components in the image are continuous or not, and judging the image to be a non-string dropping fault image if the small components of the string dropping components are scattered in the infrared image;
s63, if the whole gray value of the infrared image of the photovoltaic panel is large, all small photovoltaic modules in the image are easily judged to be string dropping due to reflection, at the moment, the average value of the gray levels of G channels of the string dropping modules and the average value of the gray levels of G channels of the non-string dropping modules are respectively calculated, the difference value between the average value of the gray levels of the G channels of the string dropping modules and the average value of the gray levels of the G channels of the non-string dropping modules is calculated, and if the difference value is smaller than 20 pixels, the image is judged to be a non-string dropping fault image.
And S7, outputting and displaying the string identification result.
A system of a photovoltaic panel infrared image string drop detection method comprises a data acquisition module, a data transmission module, a data storage module, a data processing module and a data display module which are electrically connected in sequence.
The data acquisition module is an infrared camera carrying an unmanned aerial vehicle and is used for acquiring infrared images of the photovoltaic module.
The data transmission module is used for transmitting the infrared image data acquired by the infrared camera to the data storage module.
The data storage module is used for storing infrared image data acquired by the infrared camera.
The data processing module is used for analyzing and processing the infrared image data in the data memory module, verifying the infrared image data and uploading the infrared image data to the data display module.
And the data display module is used for displaying the string identification result.
The invention also discloses a computer readable storage medium, wherein a computer program is stored on the medium, and after the computer program runs, the photovoltaic panel infrared image string drop detection method is executed.
The invention also discloses a computer system which comprises a processor and a storage medium, wherein the storage medium is stored with a computer program, and the processor reads the computer program from the storage medium and runs the computer program to execute the photovoltaic panel infrared image string-dropping detection method.
According to the invention, the string-dropping fault detection is carried out on the infrared image of the photovoltaic panel by means of image processing, so that energy waste and dangerous accidents caused by string dropping can be avoided. Compared with recognition methods such as deep learning, the algorithm has the characteristics of simplicity, instantaneity, practicability and the like, so that time waste and fund consumption caused by manual detection are reduced. The algorithm has the greatest characteristic that the algorithm is carried out according to the priori knowledge of the gray value difference of the G channel between the string dropping area and the non-string dropping area, so that the algorithm has great simplicity, the implementation process is simple, the identification effect is good, and the algorithm has the greatest advantages of feasibility and practicability.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A photovoltaic panel infrared image string drop detection method is characterized by comprising the following steps:
s1, collecting an infrared image of the photovoltaic module;
s2, segmenting each small photovoltaic module in the infrared image obtained in the step S1 by utilizing an image segmentation technology;
s3, calculating the pixel gray average value of all pixels of each small photovoltaic module area segmented in the step S2 in a G channel, and representing the whole gray value distribution condition of the small photovoltaic module area by the gray average value;
s4, setting a pixel gray threshold of a G channel, and judging whether the small photovoltaic module is a string drop module or not according to the comparison between the gray average value calculated in the step S3 and the gray threshold;
s5, combining the edges of the string dropping component to obtain a string dropping area;
s6, carrying out test verification on the string falling area;
and S7, outputting and displaying the string identification result.
2. The method of claim 1, wherein: and in the step S1, an unmanned aerial vehicle is used for carrying an infrared camera to acquire infrared images.
3. The method according to claim 1, wherein the step S3 is implemented by using the mean value of gray-scale values of G-channel pixels of small photovoltaic modules i
Comprises the following steps:
one of the small photovoltaic modules is marked as i, and the pixel area in the image where the small photovoltaic module is positioned is omega i The G channel image of the infrared image is I, and (x, y) is a certain pixel coordinate of the image I, | omega i L is the pixel region omega i The number of pixels in the pixel.
4. The method of claim 1, wherein: in step S4, the gray level threshold of the G channel pixel is set to 200, and when the gray level mean value is greater than 200, the small photovoltaic module is determined to be a string drop module, and if the gray level mean value is less than 200, the small photovoltaic module is determined to be a non-string drop module.
5. The method of claim 1, wherein: the step of obtaining the run-out region in the step S5 includes:
s51, utilizing a findContours function in OpenCV to identify and frame the edges of the small divided photovoltaic modules,
s52, according to the string dropping component identified in the step S4, eliminating the edge of the non-string dropping component and reserving the edge of the string dropping component;
and S53, removing the overlapped part of the edge frames of the string dropping component, and only reserving the outer frame of the string dropping component area, namely framing the string dropping area by a large rectangular frame.
6. The method of claim 1, wherein the step of testing and verifying of step S6 comprises:
s61, if the number of the small photovoltaic modules divided in the infrared image meets the string drop judgment condition is less than or equal to 3, judging that the image is a non-string drop fault image;
s62, checking and judging whether the serial numbers of the string dropping components are continuous or not to analyze whether the areas of the string dropping components in the image are continuous or not, and judging the image to be a non-string dropping fault image if the small components of the string dropping components are scattered in the infrared image;
s63, if the whole gray value of the infrared image of the photovoltaic panel is large, all small photovoltaic modules in the image are easily judged to be string dropping due to reflection, at the moment, the average value of the gray levels of G channels of the string dropping modules and the average value of the gray levels of G channels of the non-string dropping modules are respectively calculated, the difference value between the average value of the gray levels of the G channels of the string dropping modules and the average value of the gray levels of the G channels of the non-string dropping modules is calculated, and if the difference value is smaller than 20 pixels, the image is judged to be a non-string dropping fault image.
7. A computer-readable storage medium, characterized in that: the medium has a computer program stored thereon, and the computer program is executed to perform the photovoltaic panel infrared image string drop detection method according to any one of claims 1 to 6.
8. A computer system, characterized by: the photovoltaic panel infrared image string-dropping detection method comprises a processor and a storage medium, wherein a computer program is stored on the storage medium, and the processor reads the computer program from the storage medium and runs the computer program to execute the photovoltaic panel infrared image string-dropping detection method according to any one of claims 1 to 6.
9. The system for the photovoltaic panel infrared image string drop detection method of any one of claims 1 to 6, characterized in that: the system comprises a data acquisition module, a data transmission module, a data storage module, a data processing module and a data display module which are electrically connected in sequence;
the data acquisition module is an infrared camera carrying an unmanned aerial vehicle and is used for acquiring infrared images of the photovoltaic module;
the data transmission module is used for transmitting the infrared image data acquired by the infrared camera to the data storage module;
the data storage module is used for storing infrared image data acquired by the infrared camera;
the data processing module is used for analyzing, processing and verifying the infrared image data in the data memory module and then uploading the infrared image data to the data display module;
and the data display module is used for displaying the string-dropping identification result.
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