KR102133224B1 - An automatic diagnosis system of solar array that is using a CAD design drawing that overlapped pictures taken by a thermal imaging camera of a drone - Google Patents

Abstract

The present invention is to automatically diagnose whether a solar array is abnormal by using thermal imaging video information generated by a drone and a computer aided design (CAD) design drawing of a solar power generation complex in order to allow a few of managers to quickly and effectively manage and maintain the large-scale solar power generation complex. The drone flying at a certain altitude uses a high-resolution thermal imaging camera to overlap the thermal imaging video information for photographing the large-scale solar power generation complex by a block unit to the CAD design drawing of the solar power generation complex so as to generate video information for diagnosing the solar array, thereby automatically diagnosing whether the solar array is abnormal by using an AI diagnosis algorithm.

Description

An automatic diagnosis system of solar array that is using a CAD design drawing that overlapped pictures taken by a thermal imaging camera of a drone}

The present invention relates to a photovoltaic array automatic diagnosis system utilizing CAD design drawings for photovoltaic array installation, and more specifically, a drone is created to manage and maintain a large-scale photovoltaic power generation complex quickly and efficiently with a small number of managers. It is an invention that automatically diagnoses the abnormality of a solar array by using a thermal image image information and a CAD design drawing of a photovoltaic complex.

That is, according to the present invention, a drone flying at a constant altitude overlaps a thermal design image image information obtained by photographing a large-scale photovoltaic complex in block units using a high-resolution thermal imaging camera on a CAD design drawing of the photovoltaic complex to diagnose a solar array. It is an invention that generates image information and diagnoses the abnormality of the solar array using AI diagnostic algorithm.

In modern society, as technology develops day by day, our lives are becoming more convenient and enriched, and in proportion to this, the amount of electricity we use is increasing.

In particular, the power produced in Korea is obtained through thermal power generation, hydro power generation, nuclear power generation, and new and renewable energy. Electricity in the country depends on thermal power generation and nuclear power.

However, countries around the world have implemented an environmental regulation system such as the declaration of eco-friendly policies such as greenhouse gas reduction, and the energy supply system that relies on existing fossil fuels and nuclear energy due to oil shocks and oil prices in the past and accidents at Fukushima nuclear power plant in Japan. The need for new and renewable energy is being emphasized to escape from this, and interest in power generation using renewable energy including solar power is also increasing.

In particular, photovoltaic power generation has been actively conducted recently, with energy supplied from the sun close to infinity without any significant consumption of fuel, and a large-scale photovoltaic power generation complex has been created and operated for solar power generation efficiency.

At this time, a large number of managers are required to efficiently manage and maintain a large-scale photovoltaic complex, and because of the excessive labor cost problem, it is necessary to manage the large-scale photovoltaic complex efficiently through as few managers as possible. It is growing.

Therefore, the present invention is to propose a technology for quickly and efficiently managing and maintaining a large-scale photovoltaic complex with a small number of people by utilizing a drone.

The following are prior arts related to this.

1. Korea Patent Registration No. 10-1832454 Solar cell heat generation method using drone-based thermal infrared sensor 2. Republic of Korea Patent Publication No. 10-2018-0138354 Solar module diagnostic system using unmanned aerial vehicle 3. Republic of Korea Patent Publication No. 10-2019-0036589 Server to detect whether the solar array is defective

The present invention is to solve the above problems,

The present invention aims to automatically diagnose a solar array using a drone in order to quickly and efficiently manage and maintain a large-scale photovoltaic complex with a small number of managers.

Specifically, in the present invention, a drone flying at a certain height overlaps a thermal design image image information obtained by photographing a large-scale photovoltaic complex in block units using a high-resolution thermal imaging camera on a CAD design drawing of the photovoltaic complex to create a photovoltaic array. The purpose of the present invention is to generate diagnostic image information and diagnose an abnormality in the solar array using an AI diagnostic algorithm.

In order to achieve the above object, the solar array automatic diagnosis system utilizing the CAD design drawings for solar array installation of the present invention,

A drone 100 that flies at a predetermined altitude to photograph solar arrays installed on the ground to obtain a plurality of unit thermal image images, and generates thermal image image information composed of the obtained unit thermal image images;

Diagnostic image information generating means 200 for overlapping the thermal image image information generated by the drone 100 on a photovoltaic array CAD design drawing to generate image information for diagnosis of the photovoltaic array;

And comprising an abnormality diagnosis means (300) for diagnosing the abnormality of the solar array using the image information for diagnosis of the photovoltaic array generated by the diagnosis image information generation means (200) and an AI diagnosis algorithm. Automated diagnostic system for photovoltaic arrays using CAD design drawings for photovoltaic array installation.

Since the present invention automatically diagnoses the photovoltaic array using the thermal image image information generated by the drone and the CAD design drawing of the photovoltaic complex, it is possible to maintain a large-scale photovoltaic complex with a small number of managers. Provides

In addition, the present invention is to use a high-resolution thermal imaging camera for a drone flying at a certain height to overlap a thermal imaging image image information of a large-scale photovoltaic complex in block units to a CAD design drawing of the photovoltaic complex to diagnose a solar array. By generating image information, it diagnoses the abnormality of the photovoltaic array and allows the administrator to take action according to the diagnosis result, so it has the effect of providing high management visibility using the CAD design drawings already made when designing a large-scale photovoltaic complex.

1 is a conceptual diagram of the present invention
Figure 2 is a block diagram of the present invention
3 is a state diagram of a drone of the present invention photographing a solar array
4 is a functional block diagram of the present invention
5 is an exemplary diagram of CAD design drawing information for solar array installation of the present invention
6 is a diagram illustrating an example of image information for diagnosing a solar array in which a thermal image image is overlapped with a CAD design drawing for installing the solar array of the present invention.
7 is an enlarged view of part A of FIG. 6;
8 is an enlarged view of a portion B of FIG. 7
9 is an example of a solar array failure type

Embodiments of the present invention will be described in detail with reference to FIGS. 1 to 9 attached.

Referring to Figure 1, the present invention is a large-scale photovoltaic complex 20 to quickly and efficiently manage and maintain a large number of photovoltaic complex 20, the thermal imaging image information generated by the drone 100 and the photovoltaic complex As an invention that automatically diagnoses the abnormality of a solar array (also called a solar panel) using a CAD design drawing, a drone flying at a certain altitude uses a high-resolution thermal imaging camera to unite a large-scale photovoltaic complex by a certain area unit. The present invention relates to a method of diagnosing an abnormality of a solar array using AI diagnostic algorithm by generating image information for diagnosing a solar array by overlapping thermal image image information photographed with a CAD design drawing of a photovoltaic power generation complex.

Therefore, the solar array automatic diagnosis system 10 according to the present invention includes a drone 100, a diagnostic image information generating means 200, and an abnormality diagnosis means 300, as shown in FIG. 2.

Specifically, the solar array automatic diagnosis system using the CAD design drawings for solar array installation of the present invention,

A drone 100 that flies at a predetermined altitude to photograph solar arrays installed on the ground to obtain a plurality of unit thermal image images, and generates thermal image image information composed of the obtained unit thermal image images;

Diagnostic image information generating means 200 for overlapping the thermal image image information generated by the drone 100 on a photovoltaic array CAD design drawing to generate image information for diagnosis of the photovoltaic array;

It characterized in that it comprises a diagnostic information 300 for diagnosing the abnormality of the photovoltaic array by using the image information for diagnosis and the AI diagnostic algorithm generated by the diagnostic image information generating means 200.

Referring to Figure 1, the solar array automatic diagnosis system 10 of the present invention is an invention that enables to quickly and efficiently manage and maintain a large-scale photovoltaic complex 20 of several kilometres with a small number of managers. .

That is, since the large-scale photovoltaic complex 20 is too large and wide for the administrator to visually inspect and repair the solar arrays 21 of the large-scale photovoltaic complex 20, as shown in FIG. 3, in the present invention, the administrator Instead, the solar array is diagnosed by photographing the solar arrays 21 of the photovoltaic complex 20 using the drone 100.

The drone 100 acquires a plurality of unit thermal image images by photographing the solar arrays 21 of the large-scale photovoltaic complex 20 installed on the ground while flying at a constant altitude, and the acquired unit thermal image images It is a kind of unmanned aerial vehicle that generates image information of a thermal image composed of.

The thermal image image information generated by the drone 100 is provided to the diagnostic image information generating means 200, which is transmitted to the diagnostic image information generating means 200 in real time whenever a unit thermal image image is photographed. Alternatively, after storing all of the thermal image image information consisting of unit thermal image images on a storage medium installed in the drone, the manager on the ground recovers the storage medium on which the thermal image image information is stored from the drone and generates image information ( 200).

The drone 100 includes a thermal imaging camera 110, a GPS module 120, a flight control module 130, and an image information generation module 140, as shown in FIG.

3 and 4, the thermal imaging camera 110 is installed downwardly on one side of the drone 100, and the solar arrays 21 of the large-scale photovoltaic complex 20 installed on the ground are divided into regions. The unit thermal image images are acquired by photographing, and identification information is matched for each acquired image and provided to the image information generation module 140.

Here, the unit thermal image image is a kind of photographic information obtained by photographing the photovoltaic arrays 21 of the photovoltaic power generation unit 20 by a certain area while the drone 100 is flying.

Accordingly, as shown in FIG. 3, a target solar array 22 is positioned at the center of a certain region including a plurality (for example, 20 to 30) of solar arrays 21, and the drone 100 is applicable. The target flight moves to the global positioning system (GPS) position of the target solar array 22 to photograph a certain area.

The photovoltaic arrays 21 of the photovoltaic complex 20 are divided into A regions, B regions, C regions...N regions, etc., which are blocked for each region, as shown in FIG. The solar array GPS 22 is located.

For example, in FIG. 3, a certain region is the A region, the target solar array 21 is located in the center of the A region, and the GPS location information of the target solar array 21 in the center of the A region is shown. In the case of 36.366823 and 127.382819, the drone 100 is a target flight moving to a location where the GPS location information is 36.366823 and 127.382819, and photographs a unit thermal image image of the A region.

Subsequently, by moving and shooting to the position of the target photovoltaic array 22 in the center of the other area, the sequence of unit thermal image images of the photovoltaic arrays 21 of the photovoltaic power generation unit 20 taken for each area is ordered. It is to acquire as it is.

At this time, the thermal imaging camera 110 is applied to a high-resolution thermal imaging camera, to diagnose abnormalities of the solar arrays 21 using the heat distribution information included in the image captured by the high-resolution thermal imaging camera 110. .

Referring to FIG. 1, the GPS module 120 generates reference GPS location information of a corresponding unit thermal image image whenever the high-resolution thermal imager 110 acquires unit thermal image images, and generates the generated reference The identification information is matched for each GPS location information and provided to the image information generation module 140.

The generated reference GPS location information is characterized in that it is the location information of the target solar array 22 in the center of the unit thermal image image taken by the high-resolution thermal imaging camera 110 at present.

The flight control module 130 is a component that controls the target flight of the drone 100 so that the high-resolution thermal imaging camera 110 can shoot unit thermal image images for each region.

The flight control module 130 stores target flight information including GPS location information of target solar modules 22 at the center of each shooting area, and the flight control module 130 uses the pre-stored target flight information. The target flight is controlled so that the photovoltaic arrays 21 of the photovoltaic power generation complex 20 can be sequentially photographed for each specific region.

For example, in order to photograph the area A shown in FIG. 3, control is made to fly to the GPS position of the target solar array 22 in the center of the area A included in the flight information, and when shooting of the area A ends, B Control to fly to the GPS position of the target solar array 22 in the center of the B area included in the flight information to photograph the area, and target in the center of the C area included in the flight information to photograph the C area Through the process of controlling to fly to the GPS position of the photovoltaic array 22, the drone flight is controlled so that all the photovoltaic arrays 21 of the photovoltaic complex 20 can be photographed.

Referring to FIG. 4, the image information generation module 140 matches the reference GPS location information generated and provided by the GPS module 120 for each unit thermal image image acquired by the high-resolution thermal imaging camera 110. ) To generate and store the thermal image image information.

At this time, the image information generation module 140, when matching the unit thermal image image and the corresponding reference GPS location information, performs matching using identification information matched to the unit thermal image image and the corresponding reference GPS location information. .

The thermal image image information generated by the image information generating module 140 is a collection of unit thermal image images in which reference GPS location information is matched. The diagnostic image information generating means 200 generates image information for diagnosing solar arrays. Used as basic information.

Referring to FIGS. 1 and 2, the diagnostic image information generating means 200 displays thermal image image information generated by photographing the solar arrays 21 of the photovoltaic complex 20 while the drone 100 is flying. A configuration that overlaps on a CAD (computer aided design) design drawing for photovoltaic array installation to generate image information for diagnosing photovoltaic arrays. Design drawing DB 210, individual location information matching unit 220, and diagnostic image information generation It comprises a portion 230.

4 and 5, the design drawing DB 210 stores the CAD design drawings for the photovoltaic array installation where each photovoltaic array is shown and GPS installation location information is matched for each of the illustrated photovoltaic arrays. have.

Here, the CAD design drawing information for installation of the photovoltaic array stored in the design drawing DB 210 is CAD design drawing information used when installing the photovoltaic complex 20 installed on a large scale on the ground, generally a large-scale photovoltaic complex ( 20) When designing and constructing, it is created and managed. In the present invention, a CAD design drawing for installation of a photovoltaic array that has already been stored and managed is used for diagnosing a photovoltaic array abnormality.

The CAD design drawings for the photovoltaic array installation is characterized in that it includes drawing information on the arrangement structure of the photovoltaic arrays, information on a GPS installation location of the photovoltaic arrays, and array connection information of the photovoltaic arrays. 5, a CAD design drawing for installing a solar array is illustrated.

The individual location information matching unit 220 is configured to match the individual GPS location information for each of the solar array images in the unit thermal image image in which the reference GPS location information is matched, and provide it to the diagnostic image information generation unit 230, It comprises a relationship information generation module 221, individual location information generation module 222.

The relationship information generation module 221 generates positional relationship information for solar array images constituting the unit thermal image image.

Specifically, reference GPS location information (target solar array 22 GPS location information) is matched for each unit thermal image image, and the relationship information generation module 221 is a target at the center of the unit thermal image image It is to generate location relationship information of each photovoltaic array image based on the reference GPS location information, which is the GPS location information of the photovoltaic array 22.

For example, the target photovoltaic array 22 is located at the center of the unit thermal image image photographed in the region E of FIG. 3, and other photovoltaic arrays 21 and 23 are located around it. The positional relationship information for the image of any solar array 23 in the vicinity is any one sunlight using the target solar array 22 in the center of the unit thermal image image photographing the E region as a reference point (0.0). The coordinates (-2,+3) of the array 23 become the positional relationship information of any one solar array 23.

The individual location information generating module 222 configures a unit thermal image image using reference GPS location information, size information of the solar array, and location relationship information of the solar arrays generated by the relationship information generating module 221. This configuration generates individual GPS location information for each photovoltaic array image and matches the generated individual GPS location information to the corresponding photovoltaic array image.

The size information of the solar array is information that is known in advance, and may be, for example, (2×3)m.

For example, the reference GPS position information is 36.366823, 127.382819 (the GPS position information of the target solar array 22), and the target solar array 22 is a reference point (0.0) of any one of the solar array 23 If the positional relationship information is (-2,+3), and the size of the solar array is (2×3)m, a GPS array at a position 4m to the left and 9m to the top from 36.366823, 127.382819 is located in a solar array (23 ) Is matched with individual GPS location information. At this time, the individual GPS position information of the target solar array 22 becomes reference GPS position information.

The reason that the individual location information matching unit 220 matches the individual GPS location information for each of the solar array images in the unit thermal image image is that the diagnostic image information generating unit 230 uses the solar array images for the photovoltaic array installation CAD This is to make it easy to overlap the design drawings.

The diagnostic image information generating unit 230 extracts a CAD design drawing for photovoltaic array installation from the design drawing DB 210, and overlaps the photovoltaic array images matching individual GPS location information on the extracted CAD design drawing for photovoltaic As a configuration for generating image information for diagnosis of an array, it includes a design drawing extraction module 231, an image separation module 232, and an image information generation module 233.

The design drawing extraction module 231 extracts CAD design drawing information for photovoltaic array installation from the design drawing DB 210, wherein the CAD design drawing information for photovoltaic array installation is drawing information for the arrangement structure of each photovoltaic array, It basically includes information on the GPS installation location of each solar array and array connection information of each solar array. 5 illustrates a CAD design drawing for installing the extracted solar array.

The image separation module 232 is configured to separate solar array images matching individual GPS location information from corresponding unit thermal image images.

The image information generation module 233 overlaps the separated solar array images with each of the solar arrays shown on the extracted CAD design drawing, but installs the same GPS as the individual GPS location information matched to the separated solar array image. This is a configuration that generates diagnostic image information by overlapping and overlapping the separated solar array image on the solar array shown on the CAD design drawing with location information. The generated solar array diagnostic image information is provided to the abnormality diagnosis means 300.

FIG. 6 illustrates an image for diagnosing a photovoltaic array in which separated photovoltaic array images overlap with corresponding photovoltaic arrays illustrated on a CAD design drawing, and FIG. 7 shows a specific portion of the photovoltaic array diagnostic image shown in FIG. 6. An enlarged image is illustrated, and FIG. 8 illustrates an enlarged image of a specific portion of the solar array diagnostic image illustrated in FIG. 7.

The abnormality diagnosis means 300 is configured to diagnose whether the solar array is abnormal using the image information for diagnosis of the photovoltaic array generated by the diagnosis image information generation means 200 and the AI diagnosis algorithm, the learning unit 310, It comprises a failure diagnosis unit 320, a failure information display unit 330.

Referring to FIG. 4, the learning unit 310 acquires learning solar array images photographed by a thermal imaging camera from the outside, and based on the heat distribution information of the acquired learning solar array images, learns the solar array images for learning. This is a configuration that generates learning models for solar array failure types by learning based on machine learning.

The learning unit 310 acquires, for example, various learning solar array images including various types of failures illustrated in B of FIG. 9 from the outside, and learns the acquired learning solar array images based on machine learning. It is to generate various learning models for solar array failure types. The technology for learning based on machine learning is the same as the prior art, so a detailed description will be omitted.

The failure diagnosis unit 320 uses the learning model generated by the learning unit 310 and the AI diagnosis algorithm to generate the photovoltaic array images in the image information for diagnosis of the photovoltaic array generated by the image information generating means 200 for diagnosis. This is a configuration that diagnoses an error and generates fault information for each solar array.

Specifically, a photovoltaic array image to be diagnosed is selected from the image information for diagnosing the photovoltaic array, heat distribution information of the selected photovoltaic array image is detected, and the heat distribution information is the same or similar to the detected heat distribution information. Determine whether there is a failure type using the learning model generated by the learning unit 310, and if there is a failure type having the same or similar heat distribution information, determine that the selected photovoltaic array is a failure and display the failure information for each photovoltaic array. To create.

In general, a solar array is an aggregate composed of a plurality of solar modules electrically connected as illustrated in FIG. 9A, and a solar module means an aggregate composed of a plurality of solar cells electrically connected.

A plurality of photovoltaic modules are electrically connected by a string connection to form a solar array, and a plurality of photovoltaic cells are electrically connected by a bypass diode to form a photovoltaic module.

At this time, when a damage occurs in one of the photovoltaic cells constituting the photovoltaic cell or a shadow is generated due to external contamination, localized deterioration in which heat is collected in the corresponding photovoltaic cell that is damaged or has a shadow occurs Bypass diodes are configured for each photovoltaic cell so that a hot spot occurs and normal electricity production of other normal photovoltaic cells is not disturbed by a local hot spot.

In addition, if there is a problem with the bypass diode, deterioration occurs in the entire photovoltaic module, and if there is a problem in string connection, deterioration occurs in the entire photovoltaic array.

In addition, a potential induced degradation (PID) phenomenon may occur due to the potential difference between the photovoltaic cells and the photovoltaic array frame. In this case, a large number of local hot spots are irregularly generated in the entire photovoltaic array. Occurs.

The failure diagnosis unit 320 uses a learning model generated by the learning unit 310 and an AI diagnosis algorithm to generate a photovoltaic array image using image information for diagnosis of the photovoltaic array generated by the image information generation means 200 for diagnosis. It is to diagnose the star failure automatically.

For example, if a selected solar array image to be diagnosed is the same as the first picture in FIG. 9B, the best solar array state without any damaged cells is judged as normal, and the selected diagnosis If the target photovoltaic array image is an image in which a local hot spot occurs as shown in Figure 2 in FIG. 9B, it is determined that any one photovoltaic cell is damaged or shaded by external contamination (FIG. 9) The image corresponding to the second picture of the B picture is a learning model that is generated by the damage or external contamination of the photovoltaic cell is generated by the learning unit 310), the selected target solar array image If the image of the solar array has some streak deterioration (hot spot) as shown in Figure 3 B of Figure 9, it is determined that the bypass diode of the solar module constituting the solar array is damaged (Fig. 9) In the image corresponding to the third picture of the B picture of Fig. 4, the learning model that the bypass diode is damaged is generated by the learning unit 310), and the selected solar array image to be diagnosed is the fourth of the B picture of Fig. 9 As shown in the figure, if a hot spot occurs in the entire photovoltaic array, it is determined that there is a problem with the string connection of the photovoltaic array (the image corresponding to picture 4 in Figure B in Figure 9 is photovoltaic) A learning model called an image in which the string connection of the array has a problem is generated by the learning unit 310), and the selected solar array image to be diagnosed is a plurality of solar arrays as shown in FIG. If an irregular hot spot occurs, it is determined that a PID (Potential Induced Degradation) phenomenon has occurred in the photovoltaic array. The learning model called the generated image is generated by the learning unit 310).

The failure diagnosis unit 320 generates failure information for each photovoltaic array image of the photovoltaic array images in the image information for diagnosis of the photovoltaic array through the above-described failure determination process.

In particular, the failure information for each solar array generated for each solar array image to be diagnosed includes GPS installation location information and failure type information of the corresponding solar array, and the failure types include cell damage or contamination, bypass diode damage, and string. It includes at least the connection error and PID error.

The failure information display unit 330 is configured to display failure information on the monitoring device.

Specifically, the failure information display unit 330 uses the failure information for each photovoltaic array generated by the failure diagnosis unit 320 to cause a failure in the monitoring device on which a management screen displaying string arrays and photovoltaic arrays is displayed. Visually displays the position of the light array and the type of failure of the photovoltaic array, but in case the type of failure is more than the string connection, the part of the string connection that has an abnormality on the string connection diagram displayed on the management screen is different from the normal string connection part. It is characterized by being displayed.

By displaying the failure information as described above, the administrator can intuitively know the photovoltaic array having an abnormality and the failure type of the photovoltaic array, and in particular, when the failure type is a string connection or more, the string connection portion of the error is visually easy It is possible to quickly and accurately cope with failures.

In the above, the technical idea of the present invention has been described with reference to the accompanying drawings, but this is illustrative of preferred embodiments of the present invention and does not limit the present invention. In addition, it is obvious that anyone who has ordinary knowledge in this technical field can make various modifications and imitation without departing from the scope of the technical idea of the present invention.

10: system
20: Solar Power Complex
30: satellite
100: drone
200: diagnostic image information generating means
300: abnormal diagnosis means

Claims (8)

In the solar array automatic diagnosis system utilizing the CAD design drawings for the installation of the solar array,
In order to photograph the photovoltaic arrays installed on the ground, a plurality of unit thermal image images are acquired while target flying at a predetermined altitude according to preset target flight information, and thermal image image image information composed of the acquired unit thermal image images The drone 100 to generate;
Diagnostic image information generating means 200 for overlapping the thermal image image information generated by the drone 100 on a photovoltaic array CAD design drawing to generate image information for diagnosis of the photovoltaic array;
And an abnormality diagnosis means (300) for diagnosing an abnormality of the solar array using the image information for diagnosis of the photovoltaic array generated by the diagnosis image information generation means (200) and an AI diagnosis algorithm,

The target flight information is flight information that allows the drone 100 to fly to the positions of the target solar arrays, and the unit thermal image image acquired by the drone 100 is an image image including a plurality of solar arrays, A reference GPS location information is matched for each unit thermal image image, and the reference GPS location information is location information of a target solar array in the center of the unit thermal image image,

The diagnostic image information generating means 200,
Design diagram DB 210 for storing CAD design drawings for photovoltaic array installation where each photovoltaic array is shown and GPS installation location information is matched for each of the illustrated photovoltaic arrays,
Individual location information matching unit 220 for matching individual GPS location information for each of the solar array images in the unit thermal image image where the reference GPS location information is matched,
A diagnostic image that extracts a CAD design drawing for installing a solar array from the design drawing DB 210 and overlaps solar array images matching individual GPS location information on the extracted CAD design drawing to generate image information for diagnosing a solar array. It includes an information generating unit 230,

The individual location information matching unit 220,
A relation information generating module 221 for generating positional relationship information for the solar array images constituting the unit thermal image image,
Individual for each of the solar array images constituting the unit thermal image image using the reference GPS location information, the size information of the solar array, and the positional relation information of each solar array generated by the relation information generation module 221 It includes an individual location information generating module 222 for generating GPS location information and matching the generated individual GPS location information to a corresponding photovoltaic array image,
The positional relationship information is a photovoltaic array automatic diagnosis system using a CAD design drawing for photovoltaic array installation, characterized in that it is the positional relationship of the photovoltaic array images based on the photovoltaic array in the center of the unit thermal image image.
The method according to claim 1,
The drone 100,
A high-resolution thermal imaging camera 110 provided by the image information generation module 140 by acquiring unit thermal image images by photographing photovoltaic arrays installed on the ground for a certain area and matching identification information with each acquired image ,
Whenever the high-resolution thermal imaging camera 110 acquires unit thermal image images, it generates reference GPS location information of the corresponding unit thermal image image and matches identification information for each generated reference GPS location information to generate image information module GPS module 120 provided by (140),
Flight control module 130 for controlling the flight of the drone 100 according to the target flight information so that the high-resolution thermal imaging camera 110 can shoot unit thermal image images for each region,
An image information generating module 140 for generating and storing thermal image image information by matching reference GPS location information for each unit thermal image image acquired by the high-resolution thermal image camera 110 and acquired;
The reference GPS location information generated by the GPS module 120 is for the installation of a solar array, characterized in that it is location information of a target solar array in the center of the unit thermal image image taken by the high-resolution thermal imaging camera 110. Automated diagnostic system for solar arrays using CAD design drawings.
delete delete The method according to claim 1,
The diagnostic image information generation unit 230,
A design drawing extraction module 231 for extracting CAD design drawing information for solar array installation from the design drawing DB 210;
An image separation module 232 for separating solar array images matching individual GPS location information from corresponding unit thermal image images;
Separated solar array images are overlapped with each of the solar arrays shown on the extracted CAD design drawing, but shown on the CAD design drawing with the same GPS installation location information as the individual GPS location information matched to the separated solar array image. Includes an image information generation module 233 for overlapping the separated photovoltaic array image to the photovoltaic array to generate diagnostic image information,
The CAD design drawing information for installation of the solar array includes drawing information about the arrangement structure of each solar array, information on a GPS installation location of each solar array, and array connection information of each solar array. Automated diagnostic system for solar arrays using CAD design drawings for optical array installation.
The method according to claim 1,
The abnormality diagnosis means 300,
Learning that acquires learning solar array images from the outside and learns the learning solar array images based on machine learning based on the heat distribution information of the acquired learning solar array images to generate a learning model for the solar array failure type. Wealth 310,
By using the learning model generated by the learning unit 310 and the AI diagnosis algorithm, the photovoltaic array by diagnosing an abnormality of each photovoltaic array image in the image information for photovoltaic array diagnosis generated by the image information generating means 200 for diagnosis A failure diagnosis unit 320 for generating each failure information,
A failure information display unit 330 for displaying the failure information on the monitoring device,
Photovoltaic array automatic diagnosis system using CAD design drawings for photovoltaic array installation, characterized in that the photovoltaic array images for learning acquired by the learning unit 310 are images of a photovoltaic array in which a failure occurs. .
The method according to claim 6,
The failure diagnosis unit 320,
Through the AI diagnostic algorithm, a photovoltaic array image to be diagnosed is selected from the image information for diagnosing the photovoltaic array, the heat distribution information of the selected photovoltaic array image is detected, and a fault having heat distribution information equal to or similar to the detected heat distribution information Determine whether there is a type by using the learning model generated by the learning unit 310, and if there is a failure type having the same or similar heat distribution information, determine that the selected photovoltaic array is a failure and generate failure information for each photovoltaic array. Ha,
The failure information for each photovoltaic array includes GPS installation location information and a failure type information of the photovoltaic array,
The failure type includes at least cell damage or contamination, bypass diode damage, string connection abnormality, PID abnormality, PV array automatic diagnosis system using a CAD design drawing for solar array installation.
The method according to claim 6,
The failure information display unit 330,
Using the failure information for each solar array generated by the failure diagnosis unit 320, the position of the solar array where the failure occurs in the monitoring device displaying the management screen displaying the solar arrays and the string connection diagram and the type of failure of the corresponding solar array Visually,
If the failure type is more than the string connection, the solar array automatic diagnosis system using the CAD design drawings for solar array installation, characterized in that the string connection portion of the abnormality is displayed on the string connection diagram displayed on the management screen.

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