A cleaning method and system for a zipper-type photovoltaic cleaning robot

Abstract

The present invention discloses a cleaning method and system for a zipper-type photovoltaic cleaning robot. The method includes real-time fault diagnosis and early warning, intelligent logical judgment and decision-making, diversified fault handling mechanisms, working mode selection, and communication and data interaction. Sensors are used to detect parameters such as pulses and currents, and faults are judged in combination with preset logic. Corresponding processing is performed for different fault types. The system supports multiple working modes and adapts to extreme weather conditions. RS485 and Lora are used to achieve remote interaction. The system includes detection and control units. The detection unit collects parameters, the control unit integrates a SLAM algorithm to perform logical judgment, the execution unit implements cleaning actions, and the communication unit ensures data transmission. This invention improves the real-time nature of fault diagnosis, the fault tolerance of the equipment, and the environmental adaptability, reduces manual intervention, reduces operation and maintenance costs, and ensures that the robot is always in a safe and operational state, thereby improving the safety of the cleaning robot.

Description

Technical Field

[0001] The present invention relates to the application field of photovoltaic cleaning robots, and in particular to a cleaning method and system of a zipper-type photovoltaic cleaning robot. Background Art

[0002] In the field of photovoltaic power generation, as the scale of photovoltaic power plants continues to expand, the cleaning and maintenance of photovoltaic panels has become a major issue. Dust and dirt on the surface of photovoltaic panels can seriously affect their power generation efficiency, making regular cleaning of photovoltaic panels necessary. However, traditional cleaning methods often rely on manual labor, which is not only inefficient but also poses safety risks. To improve cleaning efficiency and safety, photovoltaic cleaning robots have emerged. However, existing photovoltaic cleaning robots still have some problems in practical applications, such as insufficient fault diagnosis and early warning capabilities, a simple fault handling mechanism, poor adaptability to extreme weather conditions, and insufficient path planning and obstacle avoidance capabilities.

[0003] Common photovoltaic cleaning robots are increasingly widely used, but existing technologies have limited fault diagnosis and troubleshooting capabilities for cleaning robots, often relying on manual inspections, which is inefficient and costly. Furthermore, most photovoltaic cleaning robot fault diagnosis is primarily performed through post-fault manual inspections and analysis of log data, lacking real-time and precision. Furthermore, when the cleaning robot encounters a fault, manual intervention is often required, reducing the autonomy and efficiency of the cleaning operation. Furthermore, existing photovoltaic cleaning robots are also poorly adaptable to extreme weather conditions and are often unable to automatically adjust their cleaning strategies based on weather conditions, compromising the safety and efficiency of cleaning operations and failing to meet the operational requirements of photovoltaic cleaning robots. Therefore, a cleaning method and system for a zipper-type photovoltaic cleaning robot are proposed. Summary of the Invention

[0004] The present invention provides the following technical solution: a cleaning method of a zipper-type photovoltaic cleaning robot, comprising the following steps:

[0005] S1 real-time fault diagnosis and early warning:

[0006] First, a zipper and cleaning brush made of high-strength, wear-resistant materials are installed at the output end of the cleaning robot. Then, the sensor detects the pulse signal and current value of the cleaning robot in real time. Combined with the preset logical judgment conditions, the operating status of the cleaning robot is diagnosed in real time to identify the fault type.

[0007] S2 intelligent logic judgment and decision-making:

[0008] Power-on self-test logic: When the robot starts, it automatically detects whether the motor return path is blocked. By comparing pulse zero, current overload, and reverse and forward real-time cleaning time, it ensures that the robot is in a safe and operational state. During the cleaning process, it continuously monitors pulses, current, and cleaning time to dynamically adjust the cleaning strategy.

[0009] Shutdown self-check logic: The robot's main circulation voltage is detected. When the main circulation voltage drops, the system is judged to be shut down. Then the reverse and forward real-time cleaning time is stored in the EEPROM.

[0010] S3 has diverse fault handling mechanisms:

[0011] For different fault types, corresponding handling mechanisms are edited. For example, scheduled cleaning and manual cleaning are initiated when the device is in standby mode due to an abnormality; when the device is shut down due to a fault, the device is locked and a remote alarm is triggered; and when the device fails to exit the warehouse, it automatically attempts to exit the warehouse again and switches to an alternative path.

[0012] S4 working mode selection:

[0013] Through the manual mode, automatic mode, aging mode and customized mode set inside the cleaning robot, the corresponding working mode is selected according to the actual scenario and needs, and corresponding processing steps are added for different extreme weather conditions. At the same time, the lidar and camera set inside the robot are used to perceive the cleaning environment in real time, and combined with the SLAM algorithm, intelligent path planning and obstacle avoidance are achieved;

[0014] S5 communication and data interaction:

[0015] Serial communication is carried out through RS485 and Lora configured on the cleaning robot to achieve remote monitoring, configuration and data interaction with the host computer, other devices or cloud platforms.

[0016] The present invention provides a zipper-type photovoltaic cleaning robot cleaning system, which adopts the above-mentioned zipper-type photovoltaic cleaning robot cleaning method, comprising:

[0017] A detection unit, a control unit, an execution unit, a communication unit, a storage unit, a power supply unit, and an environmental adaptation unit. The detection unit is electrically connected to the control unit via a data bus. The detection unit is used to collect operating parameters of the cleaning robot in real time. The detection unit includes a current sensor, a pulse sensor, a laser radar, a camera, and a voltage sensor.

[0018] A control unit, configured to execute the cleaning method, including performing fault logic judgment based on pulse and current data from the detection unit, controlling the motor movement and cleaning strategy adjustment of the execution unit, and exchanging data with an external device via a communication unit. The control unit is bidirectionally electrically connected to the detection unit, the execution unit, the communication unit, and the storage unit. A SLAM algorithm is internally provided in the control unit;

[0019] An actuator unit, configured to receive speed and steering control signals, comprising a drive motor, a cleaning brush head, and a zipper mechanism, wherein the cleaning brush head is fixedly connected to an output shaft of the drive motor via a coupling, and a traction end of the zipper mechanism engages with a wire rope reel of the drive motor;

[0020] The communication unit includes an RS485 communication module and a Lora wireless module. An EEPROM memory chip is provided inside the storage unit. The storage unit is used to store the real-time forward and reverse cleaning time, fault codes and equipment configuration parameters;

[0021] The power supply unit includes a main power supply module and a backup power supply module. The output end of the main power supply module is connected to the power supply port of the control unit, the detection unit and the execution unit. The backup power supply module is connected in parallel with the main power supply module through a diode. The environmental adaptation unit is connected to the GPIO port of the control unit. The environmental adaptation unit includes a heating module, a dust cover drive mechanism and a waterproof sealing component.

[0022] Preferably, the fault type determination basis in step S1 and step S2 is:

[0023] During scheduled cleaning or manual cleaning, if the system fails to clear the barrier, it will return to the starting point and be considered as abnormal standby.

[0024] When cleaning by scheduled or manual command, if the end point is reached normally, it is regarded as normal standby;

[0025] During the power-on self-test, if the machine returns to the starting point normally, it is considered as normal standby;

[0026] During scheduled cleaning or manual cleaning, if the system fails to clear the ridge twice, it will be considered as a fault shutdown and the equipment will be locked.

[0027] During the power-on self-test, if the machine fails to cross the bump on the way back to the starting point, it will be considered a fault shutdown and the device will be locked;

[0028] If the clearing fails and the real-time cleaning time is less than the clearing retreat time, it is considered as a warehouse exit failure.

[0029] The proximity switch cycle is unstable and fluctuates frequently within the cycle. This is due to a mismatch between the motor speed and the wire rope, which is considered a power abnormality.

[0030] If the real-time cleaning time is greater than the set cleaning time, it is considered as a warehouse exit failure;

[0031] If the pulse is 0, the current is overloaded, and the reverse real-time cleaning time is less than the forward real-time cleaning time, or if the pulse is 0, the current is overloaded, and the real-time cleaning time is less than the set cleaning time, it is considered that the device is stuck;

[0032] When the pulse is 0, the current is overloaded, and the real-time cleaning time is equal to the set cleaning time, it is considered to have reached the end point;

[0033] If the real-time cleaning time is longer than the set cleaning time and the number of pulses is less than the set threshold, it is considered a transmission abnormality, that is, the wire rope is loose;

[0034] If the real-time cleaning time is greater than the set cleaning time and the pulse is 0, it is considered as a transmission abnormality, that is, the wire rope is disconnected.

[0035] Preferably, the corresponding processing steps added in step S4 for different extreme weather conditions are:

[0036] In extremely cold climates, add equipment preheating procedures, adjust motor lubricant viscosity, and improve battery insulation performance;

[0037] In hot weather, activate the equipment's cooling system, reduce motor power, and optimize the cleaning path to avoid areas exposed to direct sunlight.

[0038] On rainy days, improve sensor detection accuracy, adjust cleaning frequency, and add anti-slip measures;

[0039] During sandstorms, activate the equipment dust cover, strengthen the motor seal, and adjust the cleaning strategy to short-cycle, high-frequency cleaning.

[0040] Preferably, the serial communication in step S5 includes RS485-1, RS485-2, RS485-3, RS485-4 and Lora serial ports, and the connection mode of the serial communication is:

[0041] RS485-1 is used as the debugging serial port. The PC is connected directly or through USR-DR164. The UI obtains logs in ASCII format.

[0042] RS485-2 is used as the service configuration serial port, the control board runs the Modbus RTU slave, the PC is connected to the USR-DR164 through the serial port, and the UI uses the Modbus protocol for parameter configuration and display;

[0043] RS485-3 connects to the motor driver, and the control board runs the Modbus master station to communicate with the motor driver;

[0044] RS485-4 is used as a backup serial port, reserved for connecting to other devices;

[0045] The Lora serial port is used to communicate with the gateway via Modbus RTU. The communication channel is Lora and the data content is consistent with RS485-2.

[0046] Preferably, the collaborative perception mechanism of the lidar and camera in step S4 is: the lidar scans in real time to generate a three-dimensional environmental point cloud map, identifies the edges of photovoltaic panels, obstacles and height differences, and the camera synchronously collects images to verify the nature of obstacles. At the same time, when combined with the SLAM algorithm, the environmental map is updated every 5 seconds, and a safety buffer distance of 20-40 cm is reserved during path planning.

[0047] Preferably, the laser radar is connected to the control unit via a USB interface, and the laser radar is used to emit a 650-800nm ​​laser beam to scan and generate a three-dimensional point cloud map of the photovoltaic panel array. The camera is connected to the image processor of the control unit via an HDMI interface, and the environmental data collected by the laser radar and the camera is transmitted to the SLAM algorithm module of the control unit.

[0048] Preferably, the control unit includes a main controller, a fault diagnosis module and a mode switching module. The main controller adopts an ARM Cortex-M4 chip. The ADC interface of the main controller is connected to the sensor signal output end of the detection unit. The fault diagnosis module is integrated into the FPGA coprocessor of the main controller and performs real-time analysis of pulse and current data through preset logical conditions. The key input port of the mode switching module is connected to the equipment operation panel.

[0049] Preferably, a MAX485 chip is provided inside the RS485 communication module of the communication unit, a data transmission line of the RS485 communication adopts a twisted shielded pair line, and a SX1278 chip is provided inside the Lora wireless module.

[0050] Preferably, the heating module of the environmental adaptation unit is composed of a PTC thermistor, which is adhered to the motor stator winding and the inner wall of the battery compartment. The PTC thermistor is connected to the PWM port of the control unit through a MOS tube, and the dust cover drive mechanism is connected to the sliding guide rail of the brush head dust cover through a micro stepping motor combined with a synchronous belt.

[0051] In summary, compared with the prior art, the present invention provides a cleaning method and system for a zipper-type photovoltaic cleaning robot, which has the following beneficial effects:

[0052] 1. The present invention can improve the maintenance efficiency and service life of the cleaning robot through real-time fault diagnosis and early warning processes. By using sensors to monitor key parameters such as pulse signals and current values ​​in real time, and combining them with preset logical judgment conditions, the system can quickly identify various fault types such as jamming, abnormal standby, and fault shutdown, so that faults can be discovered and handled in a timely manner in the initial state, thereby effectively avoiding the expansion of faults, reducing downtime, and improving the continuity and stability of cleaning operations. At the same time, through intelligent logical judgment and decision-making processes, the cleaning robot can adapt to more complex cleaning environments. That is, during the power-on self-test stage, the system detects whether the motor return path is blocked, and combines pulses, current, and cleaning time to make a comprehensive judgment to ensure that the robot is always in a safe and operational state, thereby improving the safety of the cleaning robot.

[0053] 2. The present invention enhances the fault tolerance and autonomous recovery capabilities of the cleaning robot through diversified fault handling processes, and designs corresponding handling mechanisms for different fault types. For example, it can start scheduled cleaning or manually command cleaning when in abnormal standby mode, lock the device and trigger a remote alarm when it stops due to a fault, and automatically try to re-exit or switch to an alternative path when the exit fails. These mechanisms enable the cleaning robot to respond quickly when encountering a fault, reduce manual intervention, and improve the autonomy and efficiency of cleaning operations.

[0054] 3. The present invention can significantly improve the adaptability and stability of the cleaning robot in complex environments by adding corresponding processing steps for different extreme weather conditions. This allows the robot to automatically adjust its cleaning strategy when encountering severe weather, ensuring the safety and efficiency of the cleaning operation. At the same time, the laser radar and camera installed inside the robot perceive the cleaning environment in real time, providing accurate environmental information for intelligent path planning and obstacle avoidance. The laser radar can emit a laser beam and receive reflected signals, thereby accurately measuring the distance and shape of the surrounding environment and constructing a three-dimensional map of the cleaning area. In combination with the SLAM algorithm, it can construct an environmental map of the cleaning area in real time based on the data collected by the laser radar and camera. Based on the environmental map and the robot's position information, the SLAM algorithm can plan the optimal cleaning path to avoid repeated cleaning and missed areas. At the same time, during the cleaning process, if obstacles or emergencies are encountered, the SLAM algorithm can quickly adjust the path, thereby reducing manual intervention and lowering operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a flow chart of the method of the present invention.

[0056] Figure 2 It is a system architecture diagram of the present invention.

[0057] Figure 3 This is the shutdown detection logic diagram of the present invention.

[0058] Figure 4 This is the power-on self-test logic diagram of the present invention.

[0059] Figure 5 It is a normal operation logic diagram of the present invention. DETAILED DESCRIPTION

[0060] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0061] See also Figure 1 The present invention provides a technical solution, a cleaning method of a zipper-type photovoltaic cleaning robot, comprising the following steps:

[0062] S1 real-time fault diagnosis and early warning:

[0063] First, a zipper and cleaning brush made of high-strength, wear-resistant materials are installed at the output end of the cleaning robot. Then, the sensor detects the pulse signal and current value of the cleaning robot in real time. Combined with the preset logical judgment conditions, the operating status of the cleaning robot is diagnosed in real time to identify the fault type.

[0064] See also Figure 3 、 Figure 4 and Figure 5 , S2 intelligent logic judgment and decision-making:

[0065] Power-on self-test logic: When the robot starts, it automatically detects whether the motor return path is blocked. By comparing pulse zero, current overload, and reverse and forward real-time cleaning time, it ensures that the robot is in a safe and operational state. During the cleaning process, it continuously monitors pulses, current, and cleaning time to dynamically adjust the cleaning strategy.

[0066] Shutdown self-check logic: The robot's main circulation voltage is detected. When the main circulation voltage drops, the system is judged to be shut down. Then the reverse and forward real-time cleaning time is stored in the EEPROM.

[0067] The fault type is determined based on:

[0068] During scheduled cleaning or manual cleaning, if the system fails to clear the barrier, it will return to the starting point and be considered as abnormal standby.

[0069] When cleaning by scheduled or manual command, if the end point is reached normally, it is regarded as normal standby;

[0070] During the power-on self-test, if the machine returns to the starting point normally, it is considered as normal standby;

[0071] During scheduled cleaning or manual cleaning, if the system fails to clear the ridge twice, it will be considered as a fault shutdown and the equipment will be locked.

[0072] During the power-on self-test, if the machine fails to cross the bump on the way back to the starting point, it will be considered a fault shutdown and the device will be locked;

[0073] If the clearing fails and the real-time cleaning time is less than the clearing retreat time, it is considered as a warehouse exit failure.

[0074] The proximity switch cycle is unstable and fluctuates frequently within the cycle. This is due to a mismatch between the motor speed and the wire rope, which is considered a power abnormality.

[0075] If the real-time cleaning time is greater than the set cleaning time, it is considered as a warehouse exit failure;

[0076] If the pulse is 0, the current is overloaded, and the reverse real-time cleaning time is less than the forward real-time cleaning time, or if the pulse is 0, the current is overloaded, and the real-time cleaning time is less than the set cleaning time, it is considered that the device is stuck;

[0077] When the pulse is 0, the current is overloaded, and the real-time cleaning time is equal to the set cleaning time, it is considered to have reached the end point;

[0078] If the real-time cleaning time is longer than the set cleaning time and the number of pulses is less than the set threshold, it is considered a transmission abnormality, that is, the wire rope is loose;

[0079] If the real-time cleaning time is greater than the set cleaning time and the pulse is 0, it is considered as a transmission abnormality, that is, the wire rope is disconnected;

[0080] S3 has diverse fault handling mechanisms:

[0081] For different fault types, corresponding handling mechanisms are edited. For example, scheduled cleaning and manual cleaning are initiated when the device is in standby mode due to an abnormality; when the device is shut down due to a fault, the device is locked and a remote alarm is triggered; and when the device fails to exit the warehouse, it automatically attempts to exit the warehouse again and switches to an alternative path.

[0082] S4 working mode selection:

[0083] Through the manual mode, automatic mode, aging mode and customized mode set inside the cleaning robot, the corresponding working mode is selected according to the actual scenario and needs, and corresponding processing steps are added for different extreme weather conditions. At the same time, the lidar and camera set inside the robot are used to perceive the cleaning environment in real time, and combined with the SLAM algorithm, intelligent path planning and obstacle avoidance are realized. The collaborative perception mechanism of the lidar and camera is as follows: the lidar scans in real time to generate a three-dimensional environmental point cloud map, identifies the edges of photovoltaic panels, obstacles and height differences, and the camera synchronously collects images to verify the nature of obstacles. At the same time, when combined with the SLAM algorithm, the environmental map is updated every 5 seconds, and a safety buffer distance of 20-40 cm is reserved during path planning;

[0084] The corresponding processing steps for different extreme weather conditions are as follows:

[0085] In extremely cold climates, add equipment preheating procedures, adjust motor lubricant viscosity, and improve battery insulation performance;

[0086] In hot weather, activate the equipment's cooling system, reduce motor power, and optimize the cleaning path to avoid areas exposed to direct sunlight.

[0087] On rainy days, improve sensor detection accuracy, adjust cleaning frequency, and add anti-slip measures;

[0088] During sandstorms, use equipment dust covers, strengthen motor seals, and adjust cleaning strategies to short-cycle, high-frequency cleaning.

[0089] S5 communication and data interaction:

[0090] Serial communication is performed through the RS485 and Lora ports configured on the cleaning robot to achieve remote monitoring, configuration, and data interaction with the host computer, other devices, or cloud platforms. Serial communication includes RS485-1, RS485-2, RS485-3, RS485-4, and Lora serial ports. The connection method of the serial communication is as follows:

[0091] RS485-1 is used as the debugging serial port. The PC is connected directly or through USR-DR164. The UI obtains logs in ASCII format.

[0092] RS485-2 is used as the service configuration serial port, the control board runs the Modbus RTU slave, the PC is connected to the USR-DR164 through the serial port, and the UI uses the Modbus protocol for parameter configuration and display;

[0093] RS485-3 connects to the motor driver, and the control board runs the Modbus master station to communicate with the motor driver;

[0094] RS485-4 is used as a backup serial port, reserved for connecting to other devices;

[0095] The Lora serial port is used to communicate with the gateway via Modbus RTU. The communication channel is Lora and the data content is consistent with RS485-2.

[0096] See also Figure 2 The present invention provides a zipper-type photovoltaic cleaning robot cleaning system, which adopts the above-mentioned zipper-type photovoltaic cleaning robot cleaning method, including:

[0097] The detection unit, control unit, execution unit, communication unit, storage unit, power supply unit, and environmental adaptation unit are electrically connected to the control unit via a data bus. The detection unit is used to collect the operating parameters of the cleaning robot in real time. The detection unit includes a current sensor, a pulse sensor, a laser radar (LiDAR), a camera, and a voltage sensor. The LiDAR is connected to the control unit via a USB interface. The LiDAR emits a 650-800nm ​​laser beam to scan and generate a three-dimensional point cloud image of the photovoltaic array. The camera is connected to the control unit's image processor via an HDMI interface. Environmental data collected by the LiDAR and camera is transmitted to the control unit's SLAM algorithm module. The LiDAR maintains a stable connection to the control unit via the USB interface. This interface design ensures both high-speed data transmission and connection reliability. The LiDAR integrates a high-precision laser transmitter capable of emitting laser beams with a wavelength range of 650-800nm. These laser beams scan the cleaning area at a constant frequency. When encountering the photovoltaic array or other obstacles, the laser beams are reflected. The LiDAR receiver captures these reflected signals and processes them using a built-in algorithm to generate a three-dimensional point cloud image of the cleaning area. This picture details the position, shape and distribution of surrounding obstacles of the photovoltaic panels, providing important spatial information for subsequent path planning. At the same time, the camera is connected to the image processor of the control unit via the HDMI interface. The HDMI interface supports the transmission of high-definition video signals, ensuring that the image information collected by the camera can be transmitted to the control unit in a high-quality and low-latency manner. The camera is usually installed on the front or top of the cleaning robot and can capture images of the cleaning area in all directions. These image information contains rich environmental details, such as the edges of the photovoltaic panels, the texture of the obstacles, etc., which provides important visual information for the SLAM algorithm;

[0098] Environmental data collected by the LiDAR and camera needs to be transmitted to the SLAM algorithm module of the control unit for processing. The data transmission process is as follows: First, the LiDAR and camera convert the collected 3D point cloud and image information into digital signals. These digital signals are transmitted to the control unit via USB and HDMI interfaces. Within the control unit, the data undergoes preliminary preprocessing, such as denoising and filtering, to improve data quality. Next, the preprocessed data is transmitted to the SLAM algorithm module. The SLAM algorithm module is the core component of the control unit. It is responsible for fusing the LiDAR and camera data to construct an environmental map of the cleaning area and determine the robot's position within this map. During the data transmission process, to ensure data synchronization and consistency, the control unit synchronizes the LiDAR and camera data using methods such as timestamps or synchronization signals. This ensures that the 3D point cloud and image information are temporally aligned when processing the data, thereby improving the accuracy of the environmental map and the robot's positioning precision. As the cleaning robot moves, the LiDAR and camera continuously collect new environmental data, repeating the aforementioned data transmission and processing process. In this way, the SLAM algorithm module can update the environmental map in real time and dynamically plan the optimal cleaning path based on the robot's position and the requirements of the cleaning task. At the same time, if obstacles or emergencies are encountered during the cleaning process, the SLAM algorithm module can quickly adjust the path to ensure that the robot can complete the cleaning task safely and efficiently.

[0099] A control unit for executing a cleaning method, including performing fault logic judgment based on pulse and current data from the detection unit, controlling motor motion and cleaning strategy adjustment of the execution unit, and exchanging data with an external device via a communication unit. The control unit is bidirectionally electrically connected to the detection unit, the execution unit, the communication unit, and the storage unit. The control unit is internally provided with a SLAM algorithm and includes a main controller, a fault diagnosis module, and a mode switching module. The main controller uses an ARM Cortex-M4 chip. The ADC interface of the main controller is connected to the sensor signal output end of the detection unit. The fault diagnosis module is integrated into the FPGA coprocessor of the main controller and performs real-time analysis of the pulse and current data based on preset logical conditions. The key input port of the mode switching module is connected to the device operation panel.

[0100] An actuator unit, configured to receive speed and steering control signals, comprising a drive motor, a cleaning brush head, and a zipper mechanism, wherein the cleaning brush head is fixedly connected to an output shaft of the drive motor via a coupling, and a traction end of the zipper mechanism engages with a wire rope reel of the drive motor;

[0101] The communication unit includes an RS485 communication module and a Lora wireless module. An EEPROM memory chip is provided inside the storage unit. The storage unit is used to store the real-time forward and reverse cleaning time, fault codes, and device configuration parameters. The RS485 communication module of the communication unit is internally provided with a MAX485 chip. The data transmission line of the RS485 communication adopts a twisted shielded pair cable. The Lora wireless module is internally provided with an SX1278 chip.

[0102] The power supply unit includes a main power supply module and a backup power supply module. The output end of the main power supply module is connected to the power supply port of the control unit, the detection unit and the execution unit. The backup power supply module is connected in parallel with the main power supply module through a diode. The environmental adaptation unit is connected to the GPIO port of the control unit. The environmental adaptation unit includes a heating module, a dust cover drive mechanism and a waterproof sealing assembly. The heating module of the environmental adaptation unit is composed of a PTC thermistor, which is adhered to the motor stator winding and the inner wall of the battery compartment. The PTC thermistor is connected to the PWM port of the control unit through a MOS tube. The dust cover drive mechanism is connected to the sliding guide rail of the brush head dust cover through a micro stepping motor and a synchronous belt.

[0103] This solution can improve the maintenance efficiency and service life of the cleaning robot through real-time fault diagnosis and early warning processes. By using sensors to monitor key parameters such as pulse signals and current values ​​in real time, and combining with preset logical judgment conditions, the system can quickly identify various fault types such as jamming, abnormal standby, and fault shutdown, so that faults can be discovered and handled in time in the initial state, thereby effectively avoiding the expansion of faults, reducing downtime, and improving the continuity and stability of cleaning operations. At the same time, through intelligent logical judgment and decision-making processes, the cleaning robot can adapt to more complex cleaning environments. That is, during the power-on self-test stage, the system detects whether the motor return path is blocked, and combines the comprehensive judgment of pulses, current and cleaning time to ensure that the robot is always in a safe and operational state, thereby improving the safety of the cleaning robot.

[0104] This solution enhances the cleaning robot's fault tolerance and self-recovery capabilities through diversified fault handling processes, and designs corresponding handling mechanisms for different fault types, such as starting scheduled cleaning or manually commanding cleaning when in abnormal standby mode, locking the device and triggering a remote alarm when it stops due to a fault, and automatically attempting to re-exit or switch to an alternative path when an exit fails. These mechanisms enable the cleaning robot to respond quickly when encountering a fault, reduce manual intervention, and improve the autonomy and efficiency of cleaning operations.

[0105] By adding corresponding processing steps for different extreme weather conditions, this solution can significantly improve the adaptability and stability of cleaning robots in complex environments. This allows the robot to automatically adjust its cleaning strategy when encountering inclement weather, ensuring the safety and efficiency of cleaning operations. At the same time, the lidar and camera installed inside the robot perceive the cleaning environment in real time, providing accurate environmental information for intelligent path planning and obstacle avoidance. The lidar can emit laser beams and receive reflected signals, thereby accurately measuring the distance and shape of the surrounding environment and constructing a three-dimensional map of the cleaning area. In combination with the SLAM algorithm, it can construct an environmental map of the cleaning area in real time based on the data collected by the lidar and camera. Based on the environmental map and the robot's position information, the SLAM algorithm can plan the optimal cleaning path, avoiding repeated cleaning and missing areas. At the same time, if obstacles or emergencies are encountered during the cleaning process, the SLAM algorithm can quickly adjust the path, thereby reducing manual intervention and lowering operation and maintenance costs.

[0106] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0107] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A cleaning method for a zipper-type photovoltaic cleaning robot, characterized in that: The following steps are involved: S1 real-time fault diagnosis and early warning: First, a zipper and cleaning brush made of high-strength, wear-resistant materials are installed at the output end of the cleaning robot. Then, the sensor detects the pulse signal and current value of the cleaning robot in real time. Combined with the preset logical judgment conditions, the operating status of the cleaning robot is diagnosed in real time to identify the fault type. S2 intelligent logic judgment and decision-making: Power-on self-test logic: When the robot starts, it automatically detects whether the motor return path is blocked. By comparing pulse zero, current overload, and reverse and forward real-time cleaning time, it ensures that the robot is in a safe and operational state. During the cleaning process, it continuously monitors pulses, current, and cleaning time to dynamically adjust the cleaning strategy. Shutdown self-check logic: The robot's main circulation voltage is detected. When the main circulation voltage drops, the system is judged to be shut down. Then the reverse and forward real-time cleaning time is stored in the EEPROM. S3 has diverse fault handling mechanisms: For different fault types, corresponding handling mechanisms are edited. For example, scheduled cleaning and manual cleaning are initiated when the device is in standby mode due to an abnormality; when the device is shut down due to a fault, the device is locked and a remote alarm is triggered; and when the device fails to exit the warehouse, it automatically attempts to exit the warehouse again and switches to an alternative path. S4 working mode selection: Through the manual mode, automatic mode, aging mode and customized mode set inside the cleaning robot, the corresponding working mode is selected according to the actual scenario and needs, and corresponding processing steps are added for different extreme weather conditions. At the same time, the lidar and camera set inside the robot are used to perceive the cleaning environment in real time, and combined with the SLAM algorithm, intelligent path planning and obstacle avoidance are achieved; S5 communication and data interaction: Serial communication is carried out through RS485 and Lora configured on the cleaning robot to achieve remote monitoring, configuration and data interaction with the host computer, other devices and cloud platforms.

2. A cleaning method for a zipper-type photovoltaic cleaning robot according to claim 1, characterized in that: The basis for determining the fault type in step S1 and step S2 is: During scheduled cleaning or manual cleaning, if the system fails to clear the barrier, it will return to the starting point and be considered as abnormal standby. When cleaning by scheduled or manual command, if the end point is reached normally, it is regarded as normal standby; During the power-on self-test, if the machine returns to the starting point normally, it is considered as normal standby; During scheduled cleaning or manual cleaning, if the system fails to clear the ridge twice, it will be considered as a fault shutdown and the equipment will be locked. During the power-on self-test, if the machine fails to cross the bump on the way back to the starting point, it will be considered a fault shutdown and the device will be locked; If the clearing fails and the real-time cleaning time is less than the clearing retreat time, it is considered as a warehouse exit failure. The proximity switch cycle is unstable and fluctuates frequently within the cycle. This is due to a mismatch between the motor speed and the wire rope, which is considered a power abnormality. If the real-time cleaning time is greater than the set cleaning time, it is considered as a warehouse exit failure; If the pulse is 0, the current is overloaded, and the reverse real-time cleaning time is less than the forward real-time cleaning time, or if the pulse is 0, the current is overloaded, and the real-time cleaning time is less than the set cleaning time, it is considered that the device is stuck; When the pulse is 0, the current is overloaded, and the real-time cleaning time is equal to the set cleaning time, it is considered to have reached the end point; If the real-time cleaning time is longer than the set cleaning time and the number of pulses is less than the set threshold, it is considered a transmission abnormality, that is, the wire rope is loose; If the real-time cleaning time is greater than the set cleaning time and the pulse is 0, it is considered as a transmission abnormality, that is, the wire rope is disconnected.

3. The cleaning method of a zipper-type photovoltaic cleaning robot according to claim 1, characterized in that: The additional processing steps for different extreme weather conditions in step S4 are: In extremely cold climates, add equipment preheating procedures, adjust motor lubricant viscosity, and improve battery insulation performance; In hot weather, activate the equipment's cooling system, reduce motor power, and optimize the cleaning path to avoid areas exposed to direct sunlight. On rainy days, improve sensor detection accuracy, adjust cleaning frequency, and add anti-slip measures; During sandstorms, activate the equipment dust cover, strengthen the motor seal, and adjust the cleaning strategy to short-cycle, high-frequency cleaning.

4. The cleaning method of a zipper-type photovoltaic cleaning robot according to claim 1, characterized in that: The serial communication in step S5 includes RS485-1, RS485-2, RS485-3, RS485-4 and Lora serial ports, and the connection mode of the serial communication is: RS485-1 is used as the debugging serial port. The PC is connected directly or through USR-DR164. The UI obtains logs in ASCII format. RS485-2 is used as the service configuration serial port, the control board runs the Modbus RTU slave, the PC is connected to the USR-DR164 through the serial port, and the UI uses the Modbus protocol for parameter configuration and display; RS485-3 connects to the motor driver, and the control board runs the Modbus master station to communicate with the motor driver; RS485-4 is used as a backup serial port, reserved for connecting to other devices; The Lora serial port is used to communicate with the gateway via Modbus RTU. The communication channel is Lora and the data content is consistent with RS485-2.

5. The cleaning method of a zipper-type photovoltaic cleaning robot according to claim 1, characterized in that: The collaborative perception mechanism of the lidar and camera in step S4 is as follows: the lidar scans in real time to generate a three-dimensional environmental point cloud map, identifies the edges of photovoltaic panels, obstacles and height differences, and the camera synchronously collects images to verify the nature of obstacles. At the same time, when combined with the SLAM algorithm, the environmental map is updated every 5 seconds, and a safety buffer distance of 20-40 cm is reserved during path planning.

6. A zipper-type photovoltaic cleaning robot cleaning system, using a zipper-type photovoltaic cleaning robot cleaning method according to any one of claims 1 to 5, characterized in that: include: A detection unit, a control unit, an execution unit, a communication unit, a storage unit, a power supply unit, and an environmental adaptation unit. The detection unit is electrically connected to the control unit via a data bus. The detection unit is used to collect operating parameters of the cleaning robot in real time. The detection unit includes a current sensor, a pulse sensor, a laser radar, a camera, and a voltage sensor. A control unit for executing the cleaning method according to claim 1, comprising performing fault logic judgment based on the pulse and current data of the detection unit, controlling the motor action and cleaning strategy adjustment of the execution unit, and exchanging data with an external device through a communication unit, the control unit being bidirectionally electrically connected to the detection unit, the execution unit, the communication unit, and the storage unit, and a SLAM algorithm being internally provided in the control unit; An actuator unit, configured to receive speed and steering control signals, comprising a drive motor, a cleaning brush head, and a zipper mechanism, wherein the cleaning brush head is fixedly connected to an output shaft of the drive motor via a coupling, and a traction end of the zipper mechanism engages with a wire rope reel of the drive motor; The communication unit includes an RS485 communication module and a Lora wireless module. An EEPROM memory chip is provided inside the storage unit. The storage unit is used to store the real-time forward and reverse cleaning time, fault codes and equipment configuration parameters; The power supply unit includes a main power supply module and a backup power supply module. The output end of the main power supply module is connected to the power supply port of the control unit, the detection unit and the execution unit. The backup power supply module is connected in parallel with the main power supply module through a diode. The environmental adaptation unit is connected to the GPIO port of the control unit. The environmental adaptation unit includes a heating module, a dust cover drive mechanism and a waterproof sealing component.

7. The zipper-type photovoltaic cleaning robot cleaning system according to claim 6, characterized in that: The laser radar is connected to the control unit via a USB interface. The laser radar is used to emit a 650-800nm ​​laser beam to scan and generate a three-dimensional point cloud map of the photovoltaic panel array. The camera is connected to the image processor of the control unit via an HDMI interface. The environmental data collected by the laser radar and the camera are transmitted to the SLAM algorithm module of the control unit.

8. The zipper-type photovoltaic cleaning robot cleaning system according to claim 6, characterized in that: The control unit includes a main controller, a fault diagnosis module and a mode switching module. The main controller uses an ARM Cortex-M4 chip. The ADC interface of the main controller is connected to the sensor signal output end of the detection unit. The fault diagnosis module is integrated into the FPGA coprocessor of the main controller and performs real-time analysis of pulse and current data through preset logical conditions. The key input port of the mode switching module is connected to the equipment operation panel.

9. The zipper-type photovoltaic cleaning robot cleaning system according to claim 6, characterized in that: The RS485 communication module of the communication unit is internally provided with a MAX485 chip, the data transmission line of the RS485 communication adopts a twisted shielded pair line, and the Lora wireless module is internally provided with a SX1278 chip.

10. The zipper-type photovoltaic cleaning robot cleaning system according to claim 6, characterized in that: The heating module of the environmental adaptation unit is composed of a PTC thermistor, which is adhered to the motor stator winding and the inner wall of the battery compartment. The PTC thermistor is connected to the PWM port of the control unit through a MOS tube. The dust cover drive mechanism is connected to the sliding guide rail of the brush head dust cover through a micro stepping motor and a synchronous belt.

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