CN117353658A - IV&CV fusion diagnostic system - Google Patents

Abstract

The invention discloses an IV&CV fusion diagnosis system, which includes: a fusion diagnosis server, an IV diagnosis server and a drone. The fusion diagnosis server is communicated with the IV diagnosis server and the drone respectively, and is used to execute after responding to a diagnosis task request. Diagnostic tasks include: triggering the IV diagnostic server to perform IV diagnostic analysis on the current data and voltage data of the photovoltaic components in the target photovoltaic power station, and receiving the IV diagnostic analysis results sent by the IV diagnostic server; controlling the flight of the drone to perform IV diagnostic analysis on the photovoltaic components in the target photovoltaic power station. Collect images of photovoltaic modules to obtain photovoltaic module images, and identify the photovoltaic module images to obtain CV diagnostic analysis results; match and fuse the IV diagnostic analysis results and CV diagnostic analysis results to obtain the final diagnostic analysis results. The IV&CV fusion diagnosis system of the embodiment of the present invention can improve the fault diagnosis rate of photovoltaic components by fusion diagnosis of IV and CV.

Description

IV&CV fusion diagnostic system

Technical field

The invention relates to the field of data processing technology, and in particular to an IV&CV fusion diagnosis system.

Background technique

With the development of the photovoltaic industry, the inspection program for photovoltaic modules has moved from manual inspection to the era of inspection and diagnosis using a variety of equipment. Such as IV diagnostic instruments, drones, etc. The emergence of such equipment has improved the time-consuming and labor-intensive pain points of manual inspections in the photovoltaic inspection industry, improved the efficiency of photovoltaic inspections and reduced labor costs to a certain extent. At present, manual inspection, traditional manual drone inspection and IV diagnosis still have the following shortcomings: 1. Manual inspection of a photovoltaic station of a certain scale requires several days to inspect all components, and it is necessary to judge whether the components are faulty based on experience , the equipment failure detection rate is low, which greatly affects the efficiency of the power station. 2. The IV diagnosis results can only locate the strings. When operation and maintenance personnel eliminate defects, they need to manually screen them one by one and analyze and determine the specific faulty components, which makes it impossible to accurately locate faulty components. 3. Traditional drone inspections can improve the pain points of manual inspections, but they will be affected by factors such as the number of pilots and the different technical levels of the pilots. As a result, traditional drone inspections cannot form a standardized, normalized and programmed system. Assignment form.

Contents of the invention

The present invention aims to solve one of the technical problems in the related art, at least to a certain extent. To this end, the purpose of the present invention is to propose an IV&CV fusion diagnosis system to improve the fault diagnosis rate of photovoltaic modules.

In order to achieve the above object, an embodiment of the present invention proposes an IV&CV fusion diagnosis system. The system includes: a fusion diagnosis server, an IV diagnosis server and a drone. The fusion diagnosis server is connected to the IV diagnosis server and the UAV respectively. The UAV communication connection is used to perform the diagnostic task after responding to the diagnostic task request, including: triggering the IV diagnostic server to perform IV diagnostic analysis on the current data and voltage data of the photovoltaic components in the target photovoltaic power station, and receiving the IV IV diagnostic analysis results sent by the diagnostic server; control the flight of the drone, collect images of photovoltaic components in the target photovoltaic power station, obtain photovoltaic component images, and identify the photovoltaic component images to obtain CV diagnosis Analysis results: Match and fuse the IV diagnostic analysis results and the CV diagnostic analysis results to obtain the final diagnostic analysis results.

In addition, the IV&CV fusion diagnosis system according to the embodiment of the present invention may also have the following additional technical features:

According to an embodiment of the present invention, the fusion diagnosis server is further configured to: determine a target area according to the IV diagnosis analysis result, wherein the target area is the area where the candidate faulty photovoltaic component is located; control the drone to fly to At the target area, images of the photovoltaic components in the target area are collected; and images of the photovoltaic components in the target area are identified to determine the final diagnostic analysis results from the candidate faulty photovoltaic components.

According to an embodiment of the present invention, the system further includes: a collection server, a forward isolation device and a reverse isolation device. The collection server communicates with the fusion diagnosis through the forward isolation device and the reverse isolation device. Server communication connection, configured to: receive the diagnosis task request sent by the fusion diagnosis server through the reverse isolation device; trigger the IV diagnosis server to perform inspection of the photovoltaic components in the target photovoltaic power station according to the diagnosis task request. The current data and voltage data are subjected to IV diagnosis analysis; the IV diagnosis analysis results sent by the IV diagnosis server are transmitted to the fusion diagnosis server through the forward isolation device.

According to an embodiment of the present invention, the fusion diagnosis server includes: a picture memory, a relational database, a message queue and a data processing module; the picture memory is used to store the photovoltaic module image; the relational database, A storage path for storing the IV diagnostic analysis results and the CV diagnostic analysis results, as well as the photovoltaic module image fed back by the picture memory; the message queue, used to receive the diagnostic task request and the CV Diagnostic analysis results; the data processing module is used to use a pre-trained AI model to identify the photovoltaic component image after monitoring the message queue to receive the diagnostic task request, and obtain the CV diagnostic analysis As a result, the CV diagnostic analysis result is transmitted to the relational database storage through the message queue, and the IV diagnostic analysis result and the CV diagnostic analysis result are matched and fused to obtain the final diagnostic analysis result.

According to an embodiment of the present invention, the photovoltaic component image includes a visible light image and an infrared image. When the data processing module uses a pre-trained AI model to identify the photovoltaic component image, it is specifically used to: according to the The actual size of the infrared image is calculated based on the infrared camera parameters corresponding to the infrared image, and is recorded as the first actual size. The actual size of the visible light image is calculated based on the visible light camera parameters corresponding to the visible light image, and is recorded as the second actual size. ; Obtain the position information of the UAV, and determine the position of the center point of the infrared image in the visible light image based on the position information, the first actual size, and the second actual size, record is the first position; according to the first position and the position of the faulty photovoltaic component in the infrared image, the position of the faulty photovoltaic component in the visible light image is obtained, which is recorded as the second position; according to the UAV The yaw angle establishes an image field of view coordinate system; in the image field of view coordinate system, according to the second position and the viewing angle of the visible light camera, the viewing angle of the faulty photovoltaic component relative to the drone is obtained, and the entire process is completed. Describe the location of faulty photovoltaic modules.

According to an embodiment of the present invention, the system further includes: a client, the client is communicatively connected to the fusion diagnosis server, and is used to send the diagnosis task request to the fusion diagnosis server and receive the fusion diagnosis request. A fault diagnosis report transmitted by the diagnosis server, wherein the fault diagnosis report is generated by the fusion diagnosis server based on the final faulty photovoltaic module.

According to an embodiment of the present invention, before executing the diagnostic task, the fusion diagnosis server is also used to: obtain weather information of the environment where the target photovoltaic power station is located; determine whether the weather information satisfies the preset diagnosis task conditions; if If satisfied, perform diagnostic tasks.

According to an embodiment of the present invention, the fusion diagnosis server is also configured to perform one of the following actions when the weather information does not meet the preset diagnosis task conditions: perform task waiting and stay within the preset time. When the weather information meets the preset diagnosis task conditions, the diagnosis task is performed; the historical IV diagnosis analysis results and the historical photovoltaic module images collected by the drone are used to perform fault fusion diagnosis.

According to an embodiment of the present invention, the preset diagnostic task conditions include: wind speed less than 10m/s and irradiance greater than 600W/m2.

According to an embodiment of the present invention, the IV diagnosis server communicates with the collection server through an intranet firewall.

The IV&CV fusion diagnosis system of the embodiment of the present invention can improve the fault diagnosis rate of photovoltaic modules through IV and CV fusion diagnosis of photovoltaic modules, and can accurately identify and mark the location of faults. At the same time, it can reduce labor costs and improve operation and maintenance efficiency.

Description of drawings

Figure 1 is a schematic structural diagram of an IV&CV fusion diagnosis system according to an embodiment of the present invention;

Figure 2 is a schematic work flow diagram of a fusion diagnosis server according to an embodiment of the present invention;

Figure 3 is a schematic structural diagram of an IV&CV fusion diagnosis system according to another embodiment of the present invention;

Figure 4 is a schematic structural diagram of a converged diagnosis server according to an embodiment of the present invention;

Figure 5 is a schematic flow chart of the data processing module using a pre-trained AI model to identify photovoltaic module images according to an embodiment of the present invention;

Figure 6 is an example diagram of an infrared image coordinate system and a visible light image coordinate system according to an embodiment of the present invention;

Figure 7 is an example diagram of an image field of view coordinate system according to an embodiment of the present invention;

Figure 8 is an example diagram illustrating the corresponding viewing angles of the fault location and the x and y of the drone according to an embodiment of the present invention;

Figure 9 is a schematic diagram of the specific work flow of the IV&CV fusion diagnosis system according to an embodiment of the present invention.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present invention and are not to be construed as limiting the present invention.

The IV&CV fusion diagnostic system according to the embodiment of the present invention will be described below with reference to the accompanying drawings.

Figure 1 is a schematic structural diagram of an IV&CV fusion diagnosis system according to an embodiment of the present invention.

As shown in Figure 1, the IV&CV fusion diagnosis system includes: a fusion diagnosis server 10, an IV diagnosis server 20 and a drone 30. The fusion diagnosis server 10 is communicatively connected to the IV diagnosis server 20 and the drone 30 respectively for responding to the diagnosis. After the task request, the diagnostic task is performed, including: triggering the IV diagnostic server 20 to perform IV diagnostic analysis on the current data and voltage data of the photovoltaic components in the target photovoltaic power station, and receiving the IV diagnostic analysis results sent by the IV diagnostic server 20; controlling the drone 30 flights, collect images of photovoltaic modules in the target photovoltaic power station, obtain photovoltaic module images, and identify the photovoltaic module images to obtain CV diagnostic analysis results; match and fuse the IV diagnostic analysis results and CV diagnostic analysis results to obtain Final diagnostic analysis results.

It should be noted that IV diagnosis is to detect and diagnose faulty components in photovoltaic modules by analyzing the current-voltage (I-V) curve of photovoltaic modules. Specifically, the IV scan command can be sent to the inverter through the data collector, and the inverter completes the complete IV curve data collection of the photovoltaic string. Based on the analysis of typical IV characteristic parameters of photovoltaic strings, different defect information of photovoltaic strings is identified, and based on the defect information, it is judged whether there are abnormalities in the photovoltaic strings. CV diagnosis uses algorithms to identify images collected by the drone 30 to determine the type of fault in the photovoltaic module.

The IV&CV fusion diagnosis system of the embodiment of the present invention can improve the fault diagnosis rate of photovoltaic modules through IV and CV fusion diagnosis of photovoltaic modules, and can accurately identify and mark the location of faults. At the same time, it can reduce labor costs and improve operation and maintenance efficiency.

In some embodiments of the present invention, as shown in Figure 2, the fusion diagnosis server 10 is also used to:

S11. Determine the target area based on the IV diagnostic analysis results, where the target area is the area where the candidate faulty photovoltaic module is located.

S12, control the drone 30 to fly to the target area to collect images of the photovoltaic modules in the target area.

S13, identify the photovoltaic module images in the target area to determine the final diagnostic analysis results from the candidate faulty photovoltaic modules.

As an example, it can be divided into extreme speed mode and fine mode according to actual diagnostic needs. In the extreme speed mode, the IV curve of the photovoltaic power station is first comprehensively tested through IV diagnosis to identify performance problems of the panels in the entire photovoltaic module, and CV diagnosis is performed on the discovered faulty strings. This can not only reduce the flight route of the UAV 30, but also make full use of the advantages of fast IV and precise CV. In the fine mode, IV and CV are used simultaneously for comprehensive detection, and a comprehensive and detailed "physical examination" of the inside and outside of the photovoltaic module can be achieved, which can achieve a more comprehensive and accurate diagnosis.

In this embodiment, the IV&CV fusion diagnosis system can formulate targeted inspection tasks to achieve precise location of problem components within the faulty string, thereby reducing unnecessary inspections by the UAV 30 and saving the power of the UAV 30 consumption.

In some embodiments of the present invention, as shown in Figure 3, the IV&CV fusion diagnosis system also includes: a collection server 40, a forward isolation device 50 and a reverse isolation device 60. The collection server 40 is communicatively connected to the fusion diagnosis server 10 through the forward isolation device 50 and the reverse isolation device 60, and is used for:

S21: Receive the diagnosis task request sent by the fusion diagnosis server 10 through the reverse isolation device 60.

S22, trigger the IV diagnosis server 20 to perform IV diagnosis analysis on the current data and voltage data of the photovoltaic components in the target photovoltaic power station according to the diagnosis task request.

S23 , transmit the IV diagnosis analysis results sent by the IV diagnosis server 20 to the fusion diagnosis server 10 through the forward isolation device 50 .

Specifically, the IV diagnosis server 20 communicates with the collection server 40 through the intranet firewall 70 .

As an example, both the collection server 40 and the fusion diagnosis server 10 can be communicatively connected to other devices through the switch 80 .

It should be noted that in some embodiments, the IV&CV fusion diagnosis system can be divided into a production control area and a management information area, where the production control area can include a control area (safety I area) and a non-control area (safety II area). area), the management information area may include Security III area.

In this embodiment, personnel and equipment can be protected from voltage surges through the use of forward isolation 50 . When the equipment needs to be repaired or inspected, the forward isolating device 50 is used to cut off the circuit and guide the voltage to the ground through the grounding device, which can ensure the safety of the staff. The stability and reliability of the power module can be improved by using the reverse isolation device 60 .

In some embodiments of the present invention, as shown in Figure 4 , the fusion diagnosis server 10 includes: a picture memory 101, a relational database 102, a message queue 103 and a data processing module 104.

The picture memory 101 is used to store photovoltaic module images.

As an example, after the drone 30 completes the image collection of the photovoltaic modules in the target photovoltaic power station, the captured photovoltaic module images are uploaded to the picture memory 101 through the "air to ground, ground to cloud" transmission process.

The relational database 102 is used to store the IV diagnostic analysis results and CV diagnostic analysis results, as well as the storage path of the photovoltaic module image fed back by the picture memory 101 .

The message queue 103 is used to receive diagnostic task requests and CV diagnostic analysis results.

As an example, message queue 103 may be a RabbitMQ message queue.

The data processing module 104 is configured to use the pre-trained AI model to identify the photovoltaic module image after listening to the message queue 103 to receive the diagnostic task request, obtain the CV diagnostic analysis results, and transmit the CV diagnostic analysis results through the message queue 103 stored in the relational database 102, and the IV diagnostic analysis results and the CV diagnostic analysis results are matched and fused to obtain the final diagnostic analysis result.

As an example, the data processing module 104 may also transmit the final diagnostic analysis results to the relational database 102 for storage.

In this embodiment, the reliability and data processing efficiency of the IV&CV fusion diagnosis system can be improved through the picture memory 101, the relational database 102, the message queue 103 and the data processing module 104.

In some embodiments of the present invention, the photovoltaic module image includes a visible light image and an infrared image. As shown in Figure 5, the data processing module 104 is specifically used to identify the photovoltaic module image using a pre-trained AI model:

S31. Calculate the actual size of the infrared image according to the infrared camera parameters corresponding to the infrared image, and record it as the first actual size. Calculate the actual size of the visible light image according to the visible light camera parameters corresponding to the visible light image, and record it as the second actual size.

S32, obtain the position information of the UAV 30, and determine the position of the center point of the infrared image in the visible light image based on the position information, the first actual size, and the second actual size, and record it as the first position.

S33. According to the first position and the position of the faulty photovoltaic module in the infrared image, the position of the faulty photovoltaic module in the visible light image is obtained, which is recorded as the second position.

As an example, as shown in Figure 6, an infrared image coordinate system O1X1Y1 and a visible light image coordinate system O2X2Y2 can be established. The registration of the infrared image in the visible light image is obtained through the position information, the first actual size, and the second actual size.

S34: Establish an image field of view coordinate system according to the yaw angle of the UAV 30.

As an example, as shown in Figure 7, the image field of view coordinate system is established with the UAV 30 as the coordinate origin.

S35. In the image field of view coordinate system, according to the second position and the angle of view of the visible light camera, the angle of view of the faulty photovoltaic module relative to the drone 30 is obtained, and the positioning of the faulty photovoltaic module is completed.

As an example, as shown in FIG. 8 , the fault location and the corresponding x and y angles of the drone 30 are obtained according to the second position and the visual angle of the visible light camera, thereby completing the positioning of the faulty photovoltaic module.

In this embodiment, the data processing module 104 is able to accurately identify and mark the location of the defect in the failed photovoltaic module.

In some embodiments of the present invention, the IV&CV fusion diagnosis system also includes: a client, which is communicatively connected to the fusion diagnosis server 10 and is used to send diagnostic task requests to the fusion diagnosis server 10 and receive faults transmitted by the fusion diagnosis server 10 Diagnosis report, wherein the fault diagnosis report is generated by the converged diagnosis server 10 based on the final faulty photovoltaic module.

As an example, the client can deliver a diagnostic plan through an HTTP request.

In some embodiments of the present invention, before performing the diagnostic task, the fusion diagnosis server 10 is also used to:

S41: Obtain weather information of the environment where the target photovoltaic power station is located.

S42: Determine whether the weather information meets the preset diagnosis task conditions.

S43, if satisfied, execute the diagnostic task.

Specifically, the fusion diagnosis server 10 is also configured to perform one of the following actions when the weather information does not meet the preset diagnosis task conditions: perform task waiting, and wait until the weather information meets the preset diagnosis task conditions within the preset time. Perform diagnostic tasks; use historical IV diagnostic analysis results and historical photovoltaic module images collected by the drone 30 to perform fault fusion diagnosis.

More specifically, the preset diagnostic task conditions include: wind speed less than 10m/s and irradiance greater than 600W/m2.

In this embodiment, according to the weather information, it is selected whether to perform the diagnostic task, and when the preset diagnostic task conditions are not met, the historical IV diagnostic analysis results and the historical photovoltaic component images collected by the drone 30 can be used to perform fault fusion diagnosis. It can meet various diagnostic scenarios and facilitate timely and accurate acquisition of diagnostic results.

As an example, as shown in Figure 9, the specific work flow of the present invention is illustrated:

A1, the client issues a plan request to the fusion diagnosis server 10.

A2, the converged diagnosis server 10 transmits the diagnosis task request through the reverse isolation device 60 .

A3: The collection server 40 sends a diagnostic task request to the IV diagnostic server 20.

A4, the IV diagnostic server 20 performs IV diagnostic analysis on the current data and voltage data of the photovoltaic modules in the target photovoltaic power station according to the diagnostic task request, and responds to the IV diagnostic analysis results to the collection server 40 .

A5, the collection server 40 transmits the IV diagnosis analysis results to the fusion diagnosis server 10 through the forward isolation device 50.

A6, the fusion diagnosis server 10 issues the flight task to the drone 30 through MQTT.

A7, the UAV 30 collects images of the photovoltaic modules in the target photovoltaic power station, obtains visible light images and infrared images of the photovoltaic modules, and uploads them to the picture memory 101.

A8, the image memory 101 generates a storage path for photovoltaic component images.

A9. The fusion diagnosis server 10 stores the storage path of the photovoltaic module image into the relational database 102.

A10, the relational database 102 feeds back the storage response.

A11, the fusion diagnosis server 10 puts the diagnosis task request into the message queue 103.

A12, the message queue 103 pushes the corresponding request to the data processing module 104.

A13, after listening to the diagnostic task request, the data processing module 104 uses the pre-trained AI model to identify the photovoltaic component image, obtain the CV diagnostic analysis results, and match and fuse the IV diagnostic analysis results and the CV diagnostic analysis results to obtain Final diagnostic analysis results.

A14, the data processing module 104 transmits the final diagnostic analysis result to the message queue 103.

A15, message queue 103 pushes the final diagnostic analysis result.

A16, the fusion diagnosis server 10 transmits the final diagnosis analysis results to the relational database 102 for storage.

A17, the relational database 102 feeds back the storage response.

A18: The client receives the fault diagnosis report transmitted by the converged diagnosis server 10.

It will be understood that the logic and/or steps represented in the flowchart diagrams or otherwise described herein, for example, may be considered a sequenced list of executable instructions for implementing the logical functions, and may be embodied in any computer-readable in a medium for use by, or in connection with, an instruction execution system, device, or device (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device, or device and execute the instructions) system, device or equipment. For the purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer readable media include the following: electrical connections with one or more wires (electronic device), portable computer disk cartridges (magnetic device), random access memory (RAM), Read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium may even be paper or other suitable medium on which the program may be printed, as the paper or other medium may be optically scanned, for example, and subsequently edited, interpreted, or otherwise suitable as necessary. process to obtain the program electronically and then store it in computer memory.

Meanwhile, various parts of the present invention can be implemented in hardware, software, firmware or their combination. In the above embodiments, various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if it is implemented in hardware, as in another embodiment, it can be implemented by any one or a combination of the following technologies known in the art: a logic gate circuit with a logic gate circuit for implementing a logic function on a data signal. Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.

In the description of this specification, reference to the terms "one embodiment," "some embodiments," "an example," "specific examples," or "some examples" or the like means that specific features are described in connection with the embodiment or example. , structures, materials or features are included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

In addition, the terms “first” and “second” are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of indicated technical features. Therefore, features defined as "first" and "second" may explicitly or implicitly include at least one of these features. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise expressly and specifically limited.

Although the embodiments of the present invention have been shown and described above, it can be understood that the above-mentioned embodiments are illustrative and should not be construed as limitations of the present invention. Those of ordinary skill in the art can make modifications to the above-mentioned embodiments within the scope of the present invention. The embodiments are subject to changes, modifications, substitutions and variations.

Claims (10)

1. An IV & CV fusion diagnostic system, the system comprising: the system comprises a fusion diagnosis server, an IV diagnosis server and an unmanned aerial vehicle, wherein the fusion diagnosis server is respectively in communication connection with the IV diagnosis server and the unmanned aerial vehicle and is used for responding to a diagnosis task request and then executing the diagnosis task, and the system comprises:

triggering the IV diagnosis server to perform IV diagnosis analysis on current data and voltage data of a photovoltaic module in a target photovoltaic power station, and receiving an IV diagnosis analysis result sent by the IV diagnosis server;

controlling the unmanned aerial vehicle to fly, acquiring an image of a photovoltaic module in the target photovoltaic power station, obtaining a photovoltaic module image, and identifying the photovoltaic module image to obtain a CV diagnosis analysis result;

and carrying out matching fusion on the IV diagnosis analysis result and the CV diagnosis analysis result to obtain a final diagnosis analysis result.

2. The IV & CV fusion diagnostic system of claim 1, wherein the fusion diagnostic server is further configured to:

determining a target area according to the IV diagnosis analysis result, wherein the target area is an area where the candidate fault photovoltaic module is located;

controlling the unmanned aerial vehicle to fly to the target area so as to acquire images of the photovoltaic modules in the target area;

and identifying the photovoltaic module image in the target area to determine a final diagnosis analysis result from the candidate fault photovoltaic module.

3. The IV & CV fusion diagnostic system of claim 1, further comprising: the collection server is in communication connection with the fusion diagnosis server through the forward isolation device and the reverse isolation device and is used for:

receiving the diagnosis task request sent by the fusion diagnosis server through the reverse isolation device;

triggering the IV diagnosis server to perform IV diagnosis analysis on current data and voltage data of a photovoltaic module in the target photovoltaic power station according to the diagnosis task request;

and transmitting the IV diagnosis analysis result sent by the IV diagnosis server to the fusion diagnosis server through the forward isolation device.

4. The IV & CV fusion diagnostic system of claim 1, wherein the fusion diagnostic server comprises: the system comprises a picture memory, a relational database, a message queue and a data processing module;

the picture memory is used for storing the photovoltaic module image;

the relational database is used for storing the IV diagnosis analysis result, the CV diagnosis analysis result and the storage path of the photovoltaic module image fed back by the picture memory;

the message queue is used for receiving the diagnosis task request and the CV diagnosis analysis result;

and the data processing module is used for identifying the photovoltaic module image by utilizing a pre-trained AI model after the message queue is monitored to receive the diagnosis task request, obtaining the CV diagnosis analysis result, transmitting the CV diagnosis analysis result to the relational database for storage through the message queue, and carrying out matching fusion on the IV diagnosis analysis result and the CV diagnosis analysis result to obtain a final diagnosis analysis result.

5. The IV & CV fusion diagnostic system of claim 4, wherein the photovoltaic module image comprises a visible light image and an infrared image, the data processing module is specifically configured to, when identifying the photovoltaic module image using a pre-trained AI model:

calculating the actual size of the infrared image according to the infrared camera parameters corresponding to the infrared image, marking the actual size as a first actual size, and calculating the actual size of the visible light image according to the visible light camera parameters corresponding to the visible light image, marking the actual size as a second actual size;

acquiring position information of the unmanned aerial vehicle, and determining the position of the central point of the infrared image in the visible light image according to the position information, the first actual size and the second actual size, and marking the position as a first position;

obtaining the position of the fault photovoltaic module in the visible light image according to the first position and the position of the fault photovoltaic module in the infrared image, and marking the position as a second position;

establishing an image view coordinate system according to the yaw angle of the unmanned aerial vehicle;

and in the image view coordinate system, according to the second position and the visual angle of the visible light camera, obtaining the visual angle of the fault photovoltaic module relative to the unmanned aerial vehicle, and completing the positioning of the fault photovoltaic module.

6. The IV & CV fusion diagnostic system of claim 1, further comprising: the client is in communication connection with the fusion diagnosis server and is used for sending the diagnosis task request to the fusion diagnosis server and receiving a fault diagnosis report transmitted by the fusion diagnosis server, wherein the fault diagnosis report is generated by the fusion diagnosis server according to the final fault photovoltaic module.

7. The IV & CV fusion diagnostic system of claim 1, wherein the fusion diagnostic server is further configured to, prior to performing diagnostic tasks:

acquiring weather information of the environment where the target photovoltaic power station is located;

judging whether the weather information meets a preset diagnosis task condition or not;

if so, performing the diagnostic task.

8. The IV & CV fusion diagnostic system of claim 7, wherein the fusion diagnostic server is further configured to perform one of the following actions when the weather information does not satisfy the preset diagnostic task condition:

task waiting is carried out, and a diagnosis task is executed when the weather information meets the preset diagnosis task condition within preset time;

and performing fault fusion diagnosis by using the historical IV diagnosis analysis result and the historical photovoltaic module image acquired by the unmanned aerial vehicle.

9. The IV & CV fusion diagnostic system of claim 8, wherein the preset diagnostic task conditions include: wind speeds less than 10m/s and irradiance greater than 600W/m2.

10. The IV & CV fusion diagnostic system of claim 3, wherein the IV diagnostic server communicates with the collection server through an intranet firewall.