String type EL automatic detection system and method

Abstract

The invention discloses a string type EL automatic detection system and method. The system comprises an automatic drawing device, an unmanned aerial vehicle with an EL detection camera, an external intelligent low-voltage power supply, an external intelligent high-voltage constant-current power supply, a monitoring device and a handheld intelligent terminal. The automatic drawing device comprises a microcontroller, a motor driving plate and a mechanical arm. The motor driving plate is connected with an X-axis motor, a Y-axis motor, a first Z-axis motor and a second Z-axis motor which are used for controlling the position and action of the mechanical arm. In the detection process, fuse loops and solar cell string loops are automatically in one-to-one correspondence, and an unmanned aerial vehicle EL detection camera automatically moves to the position above the corresponding string to take a picture. The system is suitable for an EL detection application occasion of internal defect quality of a matrix assembly of a photovoltaic power station, enables field maintenance personnel to avoid tedious operation, high-risk environment operation and repeated low-value labor, greatly improves the working efficiency, effectively reduces the operation and maintenance cost, and enables EL detection to be safer.

Description

Technical Field

[0001] The invention relates to an intelligent control system based on EL automatic detection of a busbar monitoring group string, and belongs to the field of photovoltaic equipment fault detection. Background Art

[0002] In recent years, the global photovoltaic industry has developed well. With the continuous advancement of photovoltaic technology and the continuous decline in costs, more and more countries and regions have begun to vigorously develop the photovoltaic industry. This has led to increasingly fierce competition in the international market. However, this has also brought more development opportunities and challenges to the photovoltaic industry.

[0003] With the increasing number of photovoltaic power stations, in order to improve the power generation efficiency of the photovoltaic power stations that have been built, the need to strengthen the diagnosis of photovoltaic components is becoming increasingly urgent. EL detection of components in the operating power stations has become a demand of more and more owners. The current problems with the EL detection method of the power station with the combiner box + centralized inverter solution are: first, low efficiency, second, difficult operation, third, poor safety, and fourth, low accuracy of test data.

[0004] The conventional solution in the prior art is to add corresponding functions to the equipment, such as adding wireless communication modules and energy storage low-voltage power supplies, intelligent switch fuses in the combiner box, and adding wireless communication modules and high-power energy storage constant current sources at the inverter end. However, since the detection frequency is not high, adding corresponding functions to the equipment will increase the equipment procurement cost and the equipment operation failure rate.

[0005] Therefore, achieving efficiency, safety, data accuracy and automation of the testing process while strictly controlling increased costs is an issue that the industry urgently needs to address. Summary of the invention

[0006] The purpose of the present invention is to overcome the shortcomings of the existing string EL detection technology and provide a string EL automatic detection system and method. Before the detection, an automatic pulling device is installed in the junction box. The automatic pulling device, an external intelligent power supply, a drone carrying an EL detection camera, a mobile phone APP, and a junction box monitoring device constitute a junction box string EL automatic detection system, which solves the problems of high labor cost, low efficiency, difficult operation, and poor safety in EL detection of solar cells in photovoltaic power stations.

[0007] According to the technical solution provided by the present invention, the group string type EL automatic detection system includes: an automatic pulling device, a drone carrying an EL detection camera, an external intelligent low-voltage power supply, an external intelligent high-voltage constant current power supply, a monitoring device and a handheld intelligent terminal;

[0008] The automatic pulling device is installed above the fuse in the junction box and is used to close or pull up the fuse cabin; the external intelligent low-voltage power supply is used to power the automatic pulling device and the monitoring device; the external intelligent high-voltage constant-current power supply is connected to the PV bus to output stable voltage and current; the monitoring device is used to detect the bus voltage, the on-off status of the string circuit and the current value, and when receiving a query command, it promptly replies to the detection data; the handheld intelligent terminal is used to set parameters including the junction box model, the number of strings, the fuse model, the number of strings detected at a single time, and the detection current, as well as to control the entire system; after receiving the command, the drone carrying the EL detection camera flies to the specified position coordinates to take pictures of the solar cells and send back the pictures; the automatic pulling device, the external intelligent low-voltage power supply, the external intelligent high-voltage constant-current power supply, the monitoring device, and the handheld intelligent terminal are all equipped with wireless communication modules, which can perform automatic wireless networking.

[0009] Specifically, the automatic pulling device includes a microcontroller, a motor drive board, and a robotic arm. The motor drive board is connected to an X-axis motor, a Y-axis motor, a first Z-axis motor, and a second Z-axis motor for controlling the position and movement of the robotic arm. The microcontroller is connected to the motor drive board, a touch screen, a wireless communication module, and a wired network interface. The wired network interface is used to connect to a background computer and to connect to the monitoring device.

[0010] Specifically, the X-axis motor uses a DC servo motor, which is used to adjust the X-direction position of the robot arm, and adjust the movement speed and step as needed; the Y-axis motor uses a stepper motor, which is used to fine-tune the Y-direction position of the robot arm, and fine-tune the center position coordinates of the robot arm as needed.

[0011] The first Z-axis motor uses a DC servo motor, which is used to control the pulling and closing action of the fuse cabin in the Z direction of the robot arm; the second Z-axis motor uses a stepper motor, which is used for the rapid release and clamping action of the chuck on the robot arm in the Z direction.

[0012] The present invention also provides a string-type EL automatic detection method, which is applied to the above-mentioned string-type EL automatic detection system.

[0013] The method includes: firstly disconnecting the photovoltaic switch in the junction box, installing the automatic pulling device above the fuse, and supplying power to the automatic pulling device and the monitoring device with an external intelligent low-voltage power supply. After the automatic pulling device, the external intelligent low-voltage power supply, the monitoring device, and the handheld intelligent terminal are automatically wirelessly networked, the handheld intelligent terminal sends a query device address instruction through a wireless communication module to automatically adapt the junction box address, and setting parameters including the junction box model, the number of strings, the fuse model, the number of strings detected at a single time, and the detection current on the touch screen of the handheld intelligent terminal or the automatic pulling device. The automatic pulling device self-learns parameters including the position coordinates of each string, the pulling and closing action force, and the speed of the motor, and stores the corresponding values. After all string loop operations are completed, the application software records all values ​​and analyzes them to automatically match the detected parameter values. After the self-learning is completed, the control robot arm automatically pulls up the fuse cabins of all fuses, and then the system automatically connects to the external intelligent high-voltage constant-current power supply in the power-off state and connects to the wireless network of the system.

[0014] After the handheld smart terminal shows that the network is successfully connected, it sends take-off and position coordinate instructions to the drone. After receiving feedback that the drone has arrived at the designated photo-taking location, the system automatically performs EL detection after pressing a one-button operation instruction on the touch screen of the handheld smart terminal or the automatic pulling device.

[0015] The process of automated EL testing includes:

[0016] The microcontroller sends a command to the motor drive board to control the mechanical arm to close the fuse cockpit of the first string, and then sends a command to the external intelligent high-voltage constant-current power supply to turn on the power supply. After the power is turned on, the external intelligent high-voltage constant-current power supply provides a constant voltage and current to the bus. The microcontroller sends a query command to the monitoring device to confirm whether the bus voltage is the specified voltage and whether the first channel current is the specified current. After confirmation, the microcontroller sends a photo command to the drone, and the EL detection camera takes a photo. After receiving the photo end command, the microcontroller sends a power-off command to the external intelligent high-voltage constant-current power supply, and the mechanical arm pulls up the fuse cockpit. The microcontroller sends a query command to the monitoring device. After confirming that the current value of the first channel is zero, the above steps are repeated to detect the second string, and so on until all strings are detected. The microcontroller sends a power-off command to the external intelligent high-voltage constant-current power supply to cut off the power supply, automatically close all fuse cockpits and restore them to their original state, and the application software saves the test data; finally, the external intelligent low-voltage power supply is manually disconnected and the automatic pulling device is removed.

[0017] After the inspection is completed, the photo data taken by the EL inspection camera will not only be saved locally, but will also be synchronously updated to the automatic pulling device and the handheld smart terminal. The automatic pulling device is then connected to the background computer, and the analysis and processing software on the handheld smart terminal or computer will perform defect analysis on the photo information and output the inspection results.

[0018] Compared with the prior art, the present invention has the following advantages:

[0019] The present invention is used to automatically detect the EL of each solar cell in a photovoltaic power station. During the detection process, the fuse circuit and the solar cell string circuit can be automatically matched one by one, and the drone EL detection camera automatically moves to the corresponding string position to take pictures. After the EL detection camera takes infrared pictures of the solar cells, the data information of the photos is transmitted to the smart phone APP software or the background computer through Bluetooth or other wireless communication methods. The software performs defect analysis on the solar cells in the photos and outputs a detection result report.

[0020] The system is suitable for EL internal defect quality detection applications of array components in photovoltaic power stations, allowing on-site maintenance personnel to say goodbye to tedious operations, high-risk environment operations and repetitive low-value labor, greatly improving work efficiency, effectively reducing operation and maintenance costs, and making EL detection safer. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the use state of the present invention installed in a combiner box.

[0022] Figure 2 It is a circuit block diagram of the automatic pulling device. DETAILED DESCRIPTION

[0023] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0024] The present invention generally includes an automatic pulling device, a drone carrying an EL detection camera, an external intelligent low-voltage power supply, an external intelligent high-voltage constant-current power supply, a monitoring device and a handheld intelligent terminal (such as a smart phone or a tablet).

[0025] like Figure 1As shown, the automatic pull-out device 3 is installed above the fuses FU1~FUn in the combiner box 1, and is used to close or pull up the fuse fuse cabin; the external intelligent low-voltage power supply 5 is used to power the automatic pull-out device 3 and the monitoring device 4; the external intelligent high-voltage constant current power supply 6 is connected to the PV (photovoltaic) busbar, and is used to output stable voltage and current; the monitoring device 4 is used to detect the busbar voltage, the on-off state of the string circuit and the current value, and to respond to the detection data immediately when receiving the query command; the handheld intelligent terminal 7 is used to set parameters including the combiner box model, the number of strings, the fuse model, the number of strings detected at a single time, and the detection current, as well as the overall control of the system. The busbar in the combiner box 1 is connected to the power grid through the photovoltaic switch 2.

[0026] In the embodiment, the mechanical arm on the automatic pulling device 3 is controlled by four motors, thereby cutting off or closing the fuse circuit in the fuse. When the fuse circuit is closed, the external intelligent high-voltage constant current power supply 6 provides 1500V voltage and 5A current to power a solar cell. At this time, the solar cell will emit light due to the current passing through the surface. The EL detection camera on the drone takes infrared photos of the group of solar cells, and then transmits the data information of the photos back. The software analyzes the defects of the solar cells in the photos and outputs the detection result report. Through this system, it is possible to flexibly, quickly, efficiently, safely and at low cost perform defect detection and analysis on solar cells, thereby improving the operation and maintenance efficiency and safety of photovoltaic power stations.

[0027] like Figure 2 As shown, the automatic pulling device includes: a microcontroller, a motor drive board, and a robotic arm. The motor drive board is connected to an X-axis motor, a Y-axis motor, a first Z-axis motor, and a second Z-axis motor for controlling the position and movement of the robotic arm. The microcontroller is connected to the motor drive board, a touch screen, a wireless communication module, and a wired network interface. The wired network interface (such as a TCP network port) is used to connect to a background computer and to connect to the monitoring device.

[0028] The following is a detailed introduction to the basic composition and functional features of the system.

[0029] 1. Motor drive board: installed inside the automatic pulling device, used to control the precise position of the three directions of X, Y, and Z axes and the movement of the pulling robot arm.

[0030] 2. Microcontroller unit (such as single-chip microcomputer): used to detect whether there is a key signal input, drive the touch screen display, communicate and transmit data with external Bluetooth or wireless LORA devices and external TCP network port devices in real time, send response control instructions to the motor driver board according to external action instructions, and adjust the position and action control of the robotic arm.

[0031] 3. Touch screen: used to display and set system parameters in real time, such as the number and width of fuses in the combiner box, the starting coordinates of the robot arm, the supply voltage and current at both ends of the fuse, the X, Y, and Z axis coordinates of the robot arm, the speed of the four motors, the protection current, the combiner box device address, etc. The touch screen is set above the automatic pulling device to provide a friendly human-machine operation interface for the system.

[0032] 4. Bluetooth communication: used to form a network with handheld smart terminals, combiner box monitoring devices, smart power systems, drones and other equipment, and to send and receive data and control instructions in the network in real time. The automatic pulling device, external smart low-voltage power supply, external smart high-voltage constant-current power supply, monitoring device, and handheld smart terminal are all equipped with Bluetooth communication modules, which can automatically form a Bluetooth network.

[0033] 5. Other wireless communications: The system supports two wireless communication methods, one is the short-range Bluetooth communication method of about 100 meters, and the second is the long-range wireless LORA communication method of about 3 kilometers. Select according to the specific situation of the peripheral connection device.

[0034] 6. Wired communication: In addition to wireless communication, the system also supports 2-way RS485 and 1-way TCP network port communication. RS485 is used to communicate with the motor drive board and the monitoring device, and the TCP network port is used to connect to the PC backend system to configure the control system parameters, analyze the photo data, and output the test report.

[0035] 7. Monitoring device: During the system detection process, it is used to detect the bus voltage, the on / off status of the string circuit and the current value. When receiving the query command, it will reply the corresponding status value in time.

[0036] 8. External intelligent low-voltage power supply: used to stably output 24V, 5A power, and power the microcontroller, motor driver board, and 4 motors at the same time.

[0037] 9.X-axis motor: A DC servo motor is used to adjust the X-axis position of the robot arm. The speed and step of movement can be adjusted as needed.

[0038] Y-axis motor: A stepper motor is used to fine-tune the Y-axis position of the robotic arm. The center position coordinates of the robotic arm can be fine-tuned as needed.

[0039] First Z-axis motor: A DC servo motor is used to control the pulling and closing action of the fuse cabin in the Z direction of the robot arm.

[0040] Second Z-axis motor: A stepper motor is used for the rapid release and clamping of the chuck on the robot arm in the Z direction.

[0041] Adapting the above system, the present invention also provides a method for automatic detection of string EL: first disconnect the photovoltaic switch in the junction box, install the automatic pulling device above the fuse and fix it, and the external intelligent low-voltage power supply supplies power to the automatic pulling device and the monitoring device. After the automatic pulling device, the external intelligent low-voltage power supply, the monitoring device, and the handheld intelligent terminal are automatically wirelessly networked (taking Bluetooth as an example), the handheld intelligent terminal sends a query device address instruction through the Bluetooth communication module to automatically adapt the junction box address, and the junction box model, the number of strings, the fuse model, the number of strings detected at a single time, the detection current and other parameters are set on the touch screen of the handheld intelligent terminal or the automatic pulling device. The automatic pulling device operates and learns the position coordinates of each string, the pulling and closing action force, the motor speed and other parameters and stores the corresponding values. After all string loop operations are completed, the system records all values ​​and analyzes them, and automatically matches the detected parameter values. After the self-learning is completed, the mechanical arm automatically pulls up the fuse cabins of all fuses, and at this time, the external intelligent high-voltage constant current power supply (power-off state) is connected, and connected to the system Bluetooth network.

[0042] After the mobile phone APP prompts that the network is successfully connected, send the drone take-off and position coordinate instructions. After receiving the feedback of reaching the designated position, press the "one-key operation" command on the touch screen of the handheld smart terminal or the automatic pulling device, and the system automatically performs EL detection. After the detection is completed, the photo data taken by the infrared thermal imaging EL detection camera carried by the drone will not only be saved locally, but will also be synchronously updated to the automatic pulling device and the handheld smart terminal. Through the TCP network port of the automatic pulling device, the backend analysis and processing software on the PC is connected, and the application software on the handheld smart terminal or computer compares and analyzes the photo information to quickly find out the bad situation of the solar cell.

[0043] After the "one-button operation" instruction, the microcontroller of the automatic pulling device sends an instruction to the motor drive board to control the mechanical arm to close the fuse cockpit of the first fuse, and then sends an instruction to the external intelligent high-voltage constant current power supply (1500V, 5A). After the power is turned on, a query instruction is sent to the monitoring device to confirm whether the bus voltage is 1500V and whether the current of the first channel is 5A. After confirmation, a photo-taking instruction is sent to the drone to take pictures. After the microcontroller receives the end of the photo-taking instruction, it sends a power-off instruction to the external intelligent high-voltage constant current power supply. The mechanical arm pulls up the fuse cockpit. After sending a query instruction to the monitoring device and confirming that the current value of the first channel is zero, the above steps are repeated to perform the second string detection until all strings are detected. The microcontroller sends a power-off instruction to the external intelligent high-voltage constant current power supply to cut off the power supply, and controls the mechanical arm to close all fuse cockpits and restore them to their original state. The software system saves the test data. Finally, the external low-voltage power supply is manually disconnected and the automatic pulling device is removed. At this time, the EL function detection of all strings of a combiner box is completed.

[0044] The automatic pulling device of the present invention has a self-learning function: after the automatic pulling device is installed in the junction box, before the EL detection is performed, it is necessary to perform position learning and memory of the entire structural system, motor action force learning and memory, mechanical arm stroke learning and memory, and store parameters such as the number of fuses. The application software comprehensively analyzes various data to obtain various parameters of the fully automatic working mode.

[0045] This system is a reusable equipment system. Once powered on again, the system will adapt to the current combiner box monitoring device address device and automatically learn the current box fuse model, robot arm X, Y, Z coordinate position, motor speed and other information. No manual intervention is required during the automatic detection process.

[0046] After the system is powered on for the first time, it automatically sends a query to the combiner box device address information. After receiving the device address information, it automatically updates the address of the combiner box device to be tested to the latest address value.

[0047] The system working modes are divided into separation mode and automatic mode, which are set through the touch screen or the working mode selection button in the mobile phone APP. In the automatic mode, after the system performs the self-learning function, one-key operation can be selected to perform fully automatic detection. If the data of a group string circuit is found to be abnormal after the test, the circuit can be retested separately.

[0048] During the detection process, if the system encounters abnormalities such as the fuse on-off state being inconsistent with the detection requirements, the bus voltage value being incorrect, the string current value being incorrect, etc., a fault warning prompt will be given in time on the touch screen and mobile phone APP software.

[0049] In summary, compared with the traditional EL detection scheme, the present invention has the following significant advantages:

[0050] High safety: Traditional EL detection solutions basically rely on after-sales maintenance personnel to manually operate the high-voltage power supply and fuse cabin at the inverter and combiner box ends. This control system implements fully automatic testing after power-on. After power-on, there is basically no need for manual live operation during the test process. Only a small amount of intervention is required on the touch screen or mobile phone APP. The entire test process is very safe and reliable, away from the danger of high-voltage live operation.

[0051] High efficiency: Compared with traditional testing methods, this detection system does not require multiple people to coordinate operations during the test, nor does it require too much waiting and confirmation time. Only two maintenance personnel are required at most. All tests are automatically confirmed by the system, and the waiting confirmation time is in milliseconds, which is very efficient.

[0052] Easy to operate: The present invention integrates the microcontroller into the automatic pulling device, and uses a snap-on installation method, so it can be quickly installed in the combiner box. Other peripheral devices are also integrated devices, and there is no need for excessive wiring and debugging and installation. It automatically forms a network after power-on, and maintenance personnel only need to perform a small amount of simple settings and operations on the touch screen and mobile phone APP.

[0053] Accuracy: In traditional manual detection methods, due to negligence in coordination and confirmation work, there will be many errors in the detected photo information and electrical parameters. However, this system has adaptive and self-learning functions. No manual confirmation is required during the detection process, which will not cause the problem of mismatch between the string number and the corresponding photo information of the solar cell, and the problem of inaccurate voltage and current values ​​of the string and solar cell. The detection accuracy can reach 100%.

Claims

1. The string type EL automatic detection system is characterized by: It includes an automatic pulling device, a drone carrying an EL detection camera, an external intelligent low-voltage power supply, an external intelligent high-voltage constant-current power supply, a monitoring device, and a handheld intelligent terminal; The automatic pulling device is installed above the fuse in the junction box and is used to close or pull up the fuse cabin; the external intelligent low-voltage power supply is used to power the automatic pulling device and the monitoring device; the external intelligent high-voltage constant-current power supply is connected to the PV bus to output stable voltage and current; the monitoring device is used to detect the bus voltage, the on-off status of the string circuit and the current value, and when receiving a query command, it promptly replies to the detection data; the handheld intelligent terminal is used to set parameters including the junction box model, the number of strings, the fuse model, the number of strings detected at a single time, and the detection current, as well as to control the entire system; after receiving the command, the drone carrying the EL detection camera flies to the specified position coordinates to take pictures of the solar cells and send back the pictures; the automatic pulling device, the external intelligent low-voltage power supply, the external intelligent high-voltage constant-current power supply, the monitoring device, and the handheld intelligent terminal are all equipped with wireless communication modules, which can perform automatic wireless networking.

2. The string EL automatic detection system as claimed in claim 1, characterized in that: The automatic pulling device includes a microcontroller, a motor drive board, and a robotic arm. The motor drive board is connected to an X-axis motor, a Y-axis motor, a first Z-axis motor, and a second Z-axis motor for controlling the position and movement of the robotic arm. The microcontroller is connected to the motor drive board, a touch screen, a wireless communication module, and a wired network interface. The wired network interface is used to connect to a background computer and to connect to the monitoring device.

3. The string EL automatic detection system as claimed in claim 2, characterized in that: The X-axis motor uses a DC servo motor, which is used to adjust the X-direction position of the robot arm, and adjust the movement speed and step as needed; the Y-axis motor uses a stepper motor, which is used to fine-tune the Y-direction position of the robot arm, and fine-tune the center position coordinates of the robot arm as needed.

4. The string EL automatic detection system as claimed in claim 2, characterized in that: The first Z-axis motor uses a DC servo motor, which is used to control the pulling and closing action of the fuse cabin in the Z direction of the robot arm; the second Z-axis motor uses a stepper motor, which is used to quickly release and clamp the chuck on the robot arm in the Z direction.

5. A method for automatic detection of string EL, characterized in that: Applied to the string EL automatic detection system, the system includes: an automatic pulling device, a drone carrying an EL detection camera, an external intelligent low-voltage power supply, an external intelligent high-voltage constant-current power supply, a monitoring device and a handheld intelligent terminal; the automatic pulling device includes a microcontroller, a motor drive board, and a robotic arm; The method includes: firstly disconnecting the photovoltaic switch in the junction box, installing the automatic pulling device above the fuse, and supplying power to the automatic pulling device and the monitoring device with an external intelligent low-voltage power supply. After the automatic pulling device, the external intelligent low-voltage power supply, the monitoring device, and the handheld intelligent terminal are automatically wirelessly networked, the handheld intelligent terminal sends a query device address instruction through a wireless communication module to automatically adapt the junction box address, and setting parameters including the junction box model, the number of strings, the fuse model, the number of strings detected at a single time, and the detection current on the touch screen of the handheld intelligent terminal or the automatic pulling device. The automatic pulling device self-learns parameters including the position coordinates of each string, the pulling and closing action force, and the speed of the motor, and stores the corresponding values. After all string loop operations are completed, the application software records all values ​​and analyzes them to automatically match the detected parameter values. After the self-learning is completed, the control robot arm automatically pulls up the fuse cabins of all fuses, and then the system automatically connects to the external intelligent high-voltage constant-current power supply in the power-off state and connects to the wireless network of the system. After the handheld smart terminal shows that the network is successfully connected, it sends take-off and position coordinate instructions to the drone. After receiving feedback that the drone has arrived at the designated photo-taking location, the system automatically performs EL detection after pressing a one-button operation instruction on the touch screen of the handheld smart terminal or the automatic pulling device.

6. The automatic detection method for string EL as claimed in claim 5, characterized in that: The process of automated EL testing includes: The microcontroller sends a command to the motor drive board to control the mechanical arm to close the fuse cockpit of the first string, and then sends a command to the external intelligent high-voltage constant-current power supply to turn on the power supply. After the power is turned on, the external intelligent high-voltage constant-current power supply provides a constant voltage and current to the bus. The microcontroller sends a query command to the monitoring device to confirm whether the bus voltage is the specified voltage and whether the first channel current is the specified current. After confirmation, the microcontroller sends a photo command to the drone, and the EL detection camera takes a photo. After receiving the photo end command, the microcontroller sends a power-off command to the external intelligent high-voltage constant-current power supply, and the mechanical arm pulls up the fuse cockpit. The microcontroller sends a query command to the monitoring device. After confirming that the current value of the first channel is zero, the above steps are repeated to detect the second string, and so on until all strings are detected. The microcontroller sends a power-off command to the external intelligent high-voltage constant-current power supply to cut off the power supply, automatically close all fuse cockpits and restore them to their original state, and the application software saves the test data; finally, the external intelligent low-voltage power supply is manually disconnected and the automatic pulling device is removed.

7. The automatic detection method for string EL as claimed in claim 6, characterized in that: After the inspection is completed, the photo data taken by the EL inspection camera will not only be saved locally, but will also be synchronously updated to the automatic pulling device and the handheld smart terminal. The automatic pulling device is then connected to the background computer, and the analysis and processing software on the handheld smart terminal or computer will perform defect analysis on the photo information and output the inspection results.

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