Cleaning method and system of zipper type photovoltaic cleaning robot

Abstract

The invention discloses a cleaning method and system of a zipper type photovoltaic cleaning robot, and the method comprises the steps: real-time fault diagnosis and early warning, intelligent logic judgment and decision making, diversified fault processing mechanisms, working mode selection and communication and data interaction, detection of parameters such as pulse and current through a sensor, and fault judgment in combination with preset logic. Corresponding processing is executed according to different fault types, multiple working modes are supported, the system adapts to extreme weather, and remote interaction is achieved through RS485 and Lora. The system comprises a detection unit, a control unit and the like, the detection unit collects parameters, the control unit integrates an SLAM algorithm to execute logic judgment, the execution unit achieves cleaning action, and the communication unit guarantees data transmission. According to the method, the fault diagnosis real-time performance and the equipment fault tolerance and environment adaptability are improved, manual intervention is reduced, the operation and maintenance cost is reduced, it is ensured that the robot is in a safe and operable state all the time, and the use safety of the cleaning robot is improved.

Description

Technical Field

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

[0002] In the field of photovoltaic power generation, with the continuous expansion of the scale of photovoltaic power stations, the cleaning and maintenance of photovoltaic panels have become an important issue. Dust and dirt on the surface of photovoltaic panels will seriously affect their power generation efficiency. Therefore, it is necessary to regularly clean the photovoltaic panels. However, traditional cleaning methods often rely on manual operation, which is not only inefficient but also has potential safety hazards. To improve the 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, single fault handling mechanisms, poor adaptability to extreme weather, and insufficient path planning and obstacle avoidance capabilities.

[0003] The applications of common photovoltaic cleaning robots are becoming increasingly widespread. However, in the prior art, the fault diagnosis and handling capabilities of cleaning robots are limited, usually relying on manual inspections, which are inefficient and costly. Moreover, the fault diagnosis of most photovoltaic cleaning robots mainly relies on manual inspections after the fact and analyzing log data, lacking real-time performance and accuracy. At the same time, when cleaning robots encounter faults, manual intervention is often required, reducing the autonomy and efficiency of cleaning operations. Additionally, existing photovoltaic cleaning robots in the prior art also have poor adaptability to extreme weather and often cannot automatically adjust the cleaning strategy according to weather conditions, resulting in the safety and efficiency of cleaning operations being affected and unable to meet the working requirements of photovoltaic cleaning robot applications. For this reason, a cleaning method and system for a zip-type photovoltaic cleaning robot are proposed. Summary of the Invention

[0004] The present invention provides the following technical solution: A cleaning method for a zip-type photovoltaic cleaning robot, comprising the following steps: S1 Real-time Fault Diagnosis and Early Warning: First, install a zip made of high-strength and wear-resistant materials and a cleaning brush head at the output end of the cleaning robot. Subsequently, use sensors to detect the pulse signal and current value of the cleaning robot in real time, and combine preset logical judgment conditions to conduct real-time diagnosis on the operating state of the cleaning robot and identify the type of fault. S2 Intelligent Logical Judgment and Decision-making: Power-on Self-checking Logic: When the robot starts, automatically detect whether the return path of the motor is blocked. By comparing the pulse being 0, current overload, and the real-time cleaning duration in both reverse and forward directions, ensure that the robot is in a safe and operable state. At the same time, during the cleaning process, continuously monitor the pulse, current, and cleaning duration, and dynamically adjust the cleaning strategy. Shutdown self-check logic: Detect the main loop voltage of the robot. When the detected main loop voltage drops, it is determined that the system is about to shut down, and then the reverse and forward real-time cleaning durations are stored in the EEPROM. S3 Diverse fault handling mechanism: For different fault types, corresponding handling mechanisms are edited. That is, during abnormal standby, start timed cleaning and manual command cleaning, and when the device fails and stops, lock the device and trigger a remote alarm. When the out-of-warehouse fails, automatically attempt to re-out-of-warehouse and switch to an alternative path. S4 Working mode selection: Through the manual mode, automatic mode, aging mode, and customized mode set inside the cleaning robot, select the corresponding working mode according to the actual scenario and requirements. And for different extreme weather conditions, add corresponding processing steps. At the same time, use the lidar and camera set inside the robot to perceive the cleaning environment in real time, and combine with the SLAM algorithm to achieve intelligent path planning and obstacle avoidance. S5 Communication and data interaction: Through the RS485 and Lora configured in the cleaning robot for serial communication, realize remote monitoring, configuration, and data interaction with the upper computer, other devices, or the cloud platform.

[0005] The present invention provides a cleaning system for a zip-type photovoltaic cleaning robot, adopting the above-mentioned cleaning method for a zip-type photovoltaic cleaning robot, including: 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 through 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 lidar, a camera, and a voltage sensor; The control unit is used to execute the cleaning method, including performing fault logic judgment based on the pulse and current data of the detection unit, controlling the motor action of the execution unit and adjusting the cleaning strategy, and interacting data with external devices through the communication unit. The control unit is bidirectionally electrically connected to the detection unit, the execution unit, the communication unit, and the storage unit. The SLAM algorithm is set inside the control unit; The execution unit is used to receive the rotation speed and steering control signals. The execution unit includes a drive motor, a cleaning brush head, and a zip mechanism. The cleaning brush head is fixedly connected to the output shaft of the drive motor through a coupling. The traction end of the zip mechanism cooperates with the wire rope reel of the drive motor; The communication unit includes an RS485 communication module and a Lora wireless module. An EEPROM storage chip is set inside the storage unit. The storage unit is used to save the reverse and forward real-time cleaning durations, fault codes, and device configuration parameters; The power supply unit includes a main power supply module and a backup power supply module. The output terminal of the main power supply module is connected to the power supply ports 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 driving mechanism, and a waterproof sealing component.

[0006] Preferably, the basis for determining the fault type in step S1 and step S2 is as follows: During timed cleaning or manual command cleaning, if the cleaning fails to cross the ridge and returns to the starting point of this time, it is regarded as abnormal standby. During timed cleaning or manual command cleaning, if it reaches the end point normally, it is regarded as normal standby. During power-on self-check, if it returns to the starting point normally, it is regarded as normal standby. During timed cleaning or manual command cleaning, if the cleaning fails to cross the ridge twice in a row, it is regarded as a fault shutdown and the device is locked. During power-on self-check, if the cleaning fails to cross the ridge on the way back to the starting point, it is regarded as a fault shutdown and the device is locked. If the cleaning fails to cross the ridge and the real-time cleaning duration is less than the ridge avoidance time, it is regarded as a failure to exit the bin. If the proximity switch cycle is unstable and fluctuates frequently within the cycle, it is due to the mismatch between the motor speed and the wire rope, which is regarded as abnormal power. If the real-time cleaning time is greater than the set cleaning time, it is regarded as a failure to exit the bin. If the pulse is 0, the current is overloaded, and the reverse real-time cleaning duration is less than the forward real-time cleaning duration, and if the pulse is 0, the current is overloaded, and the real-time cleaning duration is less than the set cleaning duration, it is regarded as the device being stuck. If the pulse is 0, the current is overloaded, and the real-time cleaning duration is equal to the set cleaning duration, it is regarded as reaching the end point. If the real-time cleaning duration is greater than the set cleaning duration and the number of pulses is less than the set threshold, it is regarded as abnormal transmission, 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 regarded as abnormal transmission, that is, the wire rope is disconnected.

[0007] Preferably, the corresponding processing steps added for different extreme weather conditions in step S4 are as follows: In extremely cold weather, add a device preheating program, adjust the viscosity of the motor lubricating oil, and improve the battery heat preservation performance. In high-temperature weather, start the device cooling system, reduce the motor operating power, and optimize the cleaning path to avoid direct sunlight areas. In rainy and cloudy days, improve the sensor detection accuracy, adjust the cleaning frequency, and increase anti-slip measures. In sandstorm weather, enable the device dust cover, strengthen the motor seal, and adjust the cleaning strategy to short-cycle and high-frequency cleaning.

[0008] Preferably, the serial communication in step S5 includes RS485-1, RS485-2, RS485-3, RS485-4, and a Lora serial port. The connection method of the serial communication is as follows: RS485-1 is used as a debugging serial port, which is directly connected to the PC and also connected through USR-DR164. The UI obtains logs in ASCII format; RS485-2 is used as a service configuration serial port. The control board runs as a Modbus RTU slave. The PC is connected through a serial port and USR-DR164, and the UI performs parameter configuration and display through the Modbus protocol; RS485-3 is connected to the motor driver. The control board runs as a Modbus master and communicates with the motor driver; RS485-4 is used as a spare serial port for reserved docking with other devices; The Lora serial port is used to communicate with the gateway through Modbus RTU. The communication channel is Lora, and the data content is the same as that of RS485-2.

[0009] Preferably, the collaborative perception mechanism between the lidar and the 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. The camera synchronously captures images to verify the nature of the 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.

[0010] Preferably, the lidar is connected to the control unit through a USB interface. The lidar is used to emit laser beams with wavelengths of 650-800 nm 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 through an HDMI interface. The environmental data collected by the lidar and the camera are transmitted to the inside of the SLAM algorithm module of the control unit.

[0011] Preferably, 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 in the FPGA coprocessor of the main controller and performs real-time analysis on pulse and current data through preset logical conditions. The key input port of the mode switching module is connected to the device operation panel.

[0012] Preferably, a MAX485 chip is provided inside the RS485 communication module of the communication unit. The data transmission line for RS485 communication uses a twisted shielded cable. An SX1278 chip is provided inside the Lora wireless module.

[0013] Preferably, the heating module of the environment adaptation unit is composed of PTC thermistors. The PTC thermistors are pasted on the motor stator winding and the inner wall of the battery compartment. The PTC thermistors are connected to the PWM port of the control unit through MOS transistors. The dust cover driving mechanism is connected to the sliding guide rail of the brush head dust cover through a micro stepping motor and in combination with a synchronous belt.

[0014] In summary, compared with the prior art, the present invention provides a cleaning method and system for a zip-type photovoltaic cleaning robot, having the following beneficial effects: 1. Through the real-time fault diagnosis and warning process, the present invention can improve the maintenance efficiency and service life of the cleaning robot. By means of sensors, key parameters such as pulse signals and current values are monitored in real time, and combined with preset logical judgment conditions, the system can quickly identify various fault types such as jamming, abnormal standby, and fault shutdown, enabling faults to be detected and processed in a timely manner in the initial state, thus effectively avoiding the expansion of faults, reducing downtime, improving the continuity and stability of the cleaning operation. At the same time, through the intelligent logical judgment and decision-making process, the cleaning robot can adapt to a more complex cleaning environment. That is, in the power-on self-check stage, the system ensures that the robot is always in a safe and operable state by detecting whether the motor return path is jammed and making a comprehensive judgment based on pulses, current, and cleaning duration, improving the use safety of the cleaning robot; 2. Through the diversified fault handling process, the present invention enhances the fault tolerance and self-recovery ability of the cleaning robot, and corresponding processing mechanisms are designed for different fault types. For example, when in abnormal standby, start timed cleaning or manual command cleaning; when in fault shutdown, lock the device and trigger a remote alarm; when the out-of-warehouse fails, automatically attempt to re-enter the warehouse or switch to an alternative path. These mechanisms enable the cleaning robot to quickly respond when encountering faults, reduce manual intervention, and improve the autonomy and efficiency of the cleaning operation; 3. By adding corresponding processing steps for different extreme weather conditions, the present invention can significantly improve the adaptability and stability of the cleaning robot in complex environments, enabling the robot to automatically adjust the cleaning strategy when encountering bad weather to ensure the safety and efficiency of the cleaning operation. At the same time, the lidar and camera installed inside the robot can sense 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 to accurately measure the distance and shape of the surrounding environment, construct a three-dimensional map of the cleaning area, and combined 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 to avoid repeated cleaning and missed areas. At the same time, during the cleaning process, if an obstacle or unexpected situation is encountered, the SLAM algorithm can quickly adjust the path, thereby reducing manual intervention and lowering the operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is the flowchart of the method of the present invention.

[0016] Figure 2 is the system architecture diagram of the present invention.

[0017] Figure 3 is the shutdown detection logic diagram of the present invention.

[0018] Figure 4 is the power-on self-check logic diagram of the present invention.

[0019] Figure 5 is the normal operation logic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0021] Please refer to Figure 1 , the present invention provides a technical solution, a cleaning method for a zip-type photovoltaic cleaning robot, including the following steps: S1 Real-time fault diagnosis and warning: First, install a zip and a cleaning brush head made of high-strength and wear-resistant materials at the output end of the cleaning robot. Subsequently, the pulse signal and current value of the cleaning robot are detected in real time through sensors, and combined with preset logical judgment conditions, the running state of the cleaning robot is diagnosed in real time to identify the type of fault; Please refer to Figure 3 , Figure 4 and Figure 5 , S2 intelligent logic judgment and decision-making: Power-on self-check logic: When the robot starts, it automatically detects whether the motor return path is blocked. By comparing the pulse being 0, current overload, and the real-time cleaning duration in both reverse and forward directions, it ensures that the robot is in a safe and operable state. Meanwhile, during the cleaning process, it continuously monitors the pulse, current, and cleaning duration to dynamically adjust the cleaning strategy; Power-off self-check logic: It detects the main loop voltage of the robot. When it detects that the main loop voltage drops, it determines that the system is about to shut down, and then stores the real-time cleaning duration in both reverse and forward directions into the EEPROM; The basis for determining the fault type is: During timed cleaning or manual command cleaning, if it fails to cross a threshold and returns to the starting point of this time, it is regarded as abnormal standby; During timed cleaning or manual command cleaning, if it reaches the end point normally, it is regarded as normal standby; During power-on self-check, if it returns to the starting point normally, it is regarded as normal standby; During timed cleaning or manual command cleaning, if it fails to cross a threshold twice in a row, it is regarded as a fault shutdown and the device is locked; During power-on self-check, if it fails to cross a threshold on the way back to the starting point, it is regarded as a fault shutdown and the device is locked; If it fails to cross a threshold and the real-time cleaning duration is less than the threshold avoidance time, it is regarded as a failure to exit the bin; If the proximity switch cycle is unstable and fluctuates frequently within the cycle, it is due to the mismatch between the motor speed and the wire rope, and it is regarded as abnormal power; If the real-time cleaning time is greater than the set cleaning time, it is regarded as a failure to exit the bin; If the pulse is 0, the current is overloaded, and the reverse real-time cleaning duration is less than the forward real-time cleaning duration, and if the pulse is 0, the current is overloaded, and the real-time cleaning duration is less than the set cleaning duration, it is regarded as equipment blockage; If the pulse is 0, the current is overloaded, and the real-time cleaning duration is equal to the set cleaning duration, it is regarded as reaching the end point; If the real-time cleaning duration is greater than the set cleaning duration and the number of pulses is less than the set threshold, it is regarded as abnormal transmission, 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 regarded as abnormal transmission, that is, the wire rope is disconnected; S3 diversified fault handling mechanism: For different fault types, corresponding handling mechanisms are edited, that is, when in abnormal standby, timed cleaning and manual command cleaning are started, while when in fault shutdown, the device is locked and a remote alarm is triggered. When there is a failure to exit the bin, it automatically attempts to re-exit the bin and switches to the backup path; S4 working mode selection: By setting manual mode, automatic mode, aging mode, and customized mode inside the cleaning robot, select the corresponding working mode according to the actual scenario and requirements. Additionally, add corresponding processing steps for different extreme weather conditions. At the same time, use the lidar and camera set inside the robot to perceive the cleaning environment in real time, and combine with the SLAM algorithm to achieve intelligent path planning and obstacle avoidance. 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, identify the edges of photovoltaic panels, obstacles, and height differences. The camera synchronously captures images to verify the nature of the obstacles. When combined with the SLAM algorithm, the environmental map is updated every 5 seconds, and a safety buffer distance of 20 - 40 centimeters is reserved during path planning; And the corresponding processing steps added for different extreme weather conditions are as follows: In extremely cold climates, add a device preheating program, adjust the viscosity of the motor lubricating oil, and improve the battery heat preservation performance; In high-temperature climates, start the device cooling system, reduce the operating power of the motor, and optimize the cleaning path to avoid direct sunlight areas; In rainy and cloudy days, improve the detection accuracy of sensors, adjust the cleaning frequency, and increase anti-slip measures; In sandstorm weather, enable the device dust cover, strengthen the motor seal, and adjust the cleaning strategy to short-cycle and high-frequency cleaning; S5 Communication and Data Interaction: Through the RS485 and Lora configured in the cleaning robot for serial communication, realize remote monitoring, configuration, and data interaction with the upper computer, other devices, or cloud platforms. The serial communication includes RS485-1, RS485-2, RS485-3, RS485-4, and the Lora serial port. The connection method of the serial communication is as follows: RS485-1 is used as the debugging serial port, directly connected to the PC and through the USR-DR164, and the UI obtains the log in ASCII form; RS485-2 is used as the service configuration serial port, the control board runs the Modbus RTU slave station, the PC is connected through the serial port and the USR-DR164, and the UI configures and displays parameters through the Modbus protocol; RS485-3 is connected to the motor driver, the control board runs the Modbus master station, and communicates with the motor driver; RS485-4 is used as a spare serial port, reserved for docking other devices; The Lora serial port is used to communicate with the gateway through Modbus RTU, the communication channel is Lora, and the data content is the same as that of RS485-2.

[0022] Please refer to Figure 2, the present invention provides a cleaning system for a zip - type photovoltaic cleaning robot, which adopts the above - mentioned cleaning method for a zip - type photovoltaic cleaning robot, and includes: A detection unit, a control unit, an execution unit, a communication unit, a storage unit, a power supply unit and an environment adaptation unit. The detection unit is electrically connected to the control unit through a data bus. The detection unit is used to collect the operation parameters of the cleaning robot in real time. The detection unit includes a current sensor, a pulse sensor, a lidar, a camera and a voltage sensor. The lidar is connected to the control unit through a USB interface. The lidar is used to emit a laser beam with a wavelength of 650 - 800 nm 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 through an HDMI interface. The environmental data collected by the lidar and the camera are transmitted to the inside of the SLAM algorithm module of the control unit. The lidar is stably connected to the control unit through a USB interface. This interface design not only ensures the high - speed data transmission but also the reliability of the connection. The lidar internally integrates a high - precision laser emitter, which can emit laser beams with wavelengths in the range of 650 - 800 nm. These laser beams scan the cleaning area at a certain frequency. When they encounter the photovoltaic panel array or other obstacles, the laser beams will be reflected. The receiver of the lidar will capture these reflected signals and generate a three - dimensional point cloud map of the cleaning area through the built - in algorithm processing. This map details the position, shape of the photovoltaic panels and the distribution of surrounding obstacles, providing important spatial information for subsequent path planning. At the same time, the camera is connected to the image processor of the control unit through an 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 at the front end or the 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 photovoltaic panels, the textures of obstacles, etc., providing important visual information for the SLAM algorithm; The environmental data collected by the lidar and camera need to be transmitted to the inside of the SLAM algorithm module of the control unit for processing. The data transmission process is as follows: First, the lidar and camera respectively convert the collected three-dimensional point cloud map and image information into digital signals. These digital signals are transmitted to the control unit through USB and HDMI interfaces. Inside the control unit, the data will undergo preliminary preprocessing, such as denoising and filtering, to improve the data quality. Then, the preprocessed data will be transmitted to the SLAM algorithm module. The SLAM algorithm module is the core part of the control unit. It is responsible for fusing the data of the lidar and camera, constructing an environmental map of the cleaning area, and determining the position of the robot in the map. During the data transmission process, in order to ensure the synchronization and consistency of the data, the control unit will use methods such as timestamps or synchronization signals to synchronize the data of the lidar and camera. In this way, when the SLAM algorithm module processes the data, it can ensure that the three-dimensional point cloud map and image information are temporally matched, thereby improving the accuracy of the environmental map and the positioning accuracy of the robot. As the cleaning robot moves, the lidar and camera will continuously collect new environmental data and repeat the above 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 according to the position of the robot and the requirements of the cleaning task. At the same time, during the cleaning process, if an obstacle or unexpected situation is encountered, the SLAM algorithm module can quickly adjust the path to ensure that the robot can complete the cleaning task safely and efficiently; The control unit is used to execute the cleaning method, including performing fault logic judgment based on the pulse and current data of the detection unit, controlling the motor action of the execution unit and adjusting the cleaning strategy, and interacting with external devices through the communication unit. The control unit is bidirectionally electrically connected to the detection unit, the execution unit, the communication unit, and the storage unit. An SLAM algorithm is set inside the control unit. 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 in the FPGA coprocessor of the main controller and performs real-time analysis on the pulse and current data through preset logical conditions. The key input port of the mode switching module is connected to the device operation panel; The execution unit is used to receive the rotation speed and steering control signals. The execution unit includes a drive motor, a cleaning brush head, and a zip-lock mechanism. The cleaning brush head is fixedly connected to the output shaft of the drive motor through a coupling. The traction end of the zip-lock mechanism cooperates with the wire rope reel of the drive motor; The communication unit includes an RS485 communication module and a Lora wireless module. An EEPROM storage chip is provided inside the storage unit, which is used to save the forward and reverse real-time cleaning duration, fault codes, and device configuration parameters. A MAX485 chip is provided inside the RS485 communication module of the communication unit. The data transmission line of the RS485 communication uses a twisted shielded cable. An SX1278 chip is provided inside the Lora wireless module; 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 ports 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 driving mechanism, and a waterproof sealing component. The heating module of the environmental adaptation unit is composed of PTC thermistors, which are pasted on the motor stator winding and the inner wall of the battery compartment. The PTC thermistors are connected to the PWM port of the control unit through MOS tubes. The dust cover driving mechanism is connected to the sliding guide rail of the brush head dust cover through a micro stepping motor and a synchronous belt.

[0023] Through the real-time fault diagnosis and early warning process, this solution can improve the maintenance efficiency and service life of the cleaning robot. With the help of sensors to monitor key parameters such as pulse signals and current values in real time, and combined with preset logical judgment conditions, the system can quickly identify various fault types such as jamming, abnormal standby, and fault shutdown, enabling faults to be detected and processed in a timely manner in the initial state, effectively avoiding the expansion of faults, reducing downtime, improving the continuity and stability of the cleaning operation. At the same time, through the intelligent logical judgment and decision-making process, the cleaning robot can adapt to more complex cleaning environments. That is, in the power-on self-check stage, the system ensures that the robot is always in a safe and operable state by detecting whether the motor return path is jammed and making a comprehensive judgment based on pulses, current, and cleaning duration, improving the use safety of the cleaning robot.

[0024] Through the diversified fault handling process, this solution enhances the fault tolerance and self-recovery capabilities of the cleaning robot. Corresponding handling mechanisms are designed for different fault types. For example, when in abnormal standby, start timed cleaning or manual command cleaning; when in fault shutdown, lock the device and trigger a remote alarm; when the out-of-warehouse fails, automatically attempt to re-enter the warehouse or switch to an alternative path. These mechanisms enable the cleaning robot to respond quickly when encountering faults, reduce manual intervention, and improve the autonomy and efficiency of the cleaning operation.

[0025] By adding corresponding processing steps for different extreme weather conditions, this solution can significantly improve the adaptability and stability of the cleaning robot in complex environments, enabling the robot to automatically adjust the cleaning strategy when encountering bad weather to ensure the safety and efficiency of the cleaning operation. At the same time, the lidar and camera installed inside the robot can continuously perceive the cleaning environment, providing accurate environmental information for intelligent path planning and obstacle avoidance. The lidar can emit laser beams and receive reflected signals to accurately measure the distance and shape of the surrounding environment, constructing a three-dimensional map of the cleaning area. And combined with the SLAM algorithm, it can construct the environmental map of the cleaning area in real time according to 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 missed areas. At the same time, during the cleaning process, if an obstacle or unexpected situation is encountered, the SLAM algorithm can quickly adjust the path, thereby reducing manual intervention and lowering the operation and maintenance costs.

[0026] It should be noted that in this article, relational terms such as first and second are only used 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 "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0027] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A cleaning method for a zip-type photovoltaic cleaning robot, characterized in that, It includes the following steps: S1 Real-time fault diagnosis and early warning: First, install a zipper and a cleaning brush head made of high-strength and wear-resistant materials at the output end of the cleaning robot. Then, use sensors to detect the pulse signal and current value of the cleaning robot in real time, and combine the preset logical judgment conditions to conduct real-time diagnosis on the operating state of the cleaning robot and identify the fault type; S2 Intelligent logical judgment and decision-making: Power-on self-check logic: When the robot starts, automatically detect whether the motor return path is blocked. By comparing the pulse being 0, current overload, and the real-time cleaning duration in both reverse and forward directions, ensure that the robot is in a safe and operable state. At the same time, during the cleaning process, continuously monitor the pulse, current, and cleaning duration, and dynamically adjust the cleaning strategy; Power-off self-check logic: Detect the main loop voltage of the robot. When it is detected that the main loop voltage drops, it is judged that the system is about to shut down. Then, store the real-time cleaning duration in both reverse and forward directions into the EEPROM; S3 Diversified fault handling mechanisms: For different fault types, edit corresponding handling mechanisms, that is, start timed cleaning and manual command cleaning during abnormal standby, lock the device and trigger remote alarm during fault shutdown, and automatically try to re-enter the bin and switch to the standby path when the bin exit fails; S4 Working mode selection: Through the manual mode, automatic mode, aging mode, and customized mode set inside the cleaning robot, select the corresponding working mode according to the actual scenario and requirements, and add corresponding processing steps for different extreme weather conditions. At the same time, use the lidar and camera set inside the robot to sense the cleaning environment in real time, and combine with the SLAM algorithm to achieve intelligent path planning and obstacle avoidance; S5 Communication and data interaction: Conduct serial communication through the RS485 and Lora configured in the cleaning robot to achieve remote monitoring, configuration, and data interaction with the upper computer, other devices, and the cloud platform.

2. The cleaning method of a zip-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 timed cleaning and manual command cleaning, if it fails to cross a ridge and returns to the starting point of this time, it is regarded as abnormal standby; During timed cleaning and manual command cleaning, if it reaches the end point normally, it is regarded as normal standby; During power-on self-check, if it returns to the starting point normally, it is regarded as normal standby; During timed cleaning and manual command cleaning, if it fails to cross a ridge twice in a row, it is regarded as a fault shutdown and the device is locked; During power-on self-check, if it fails to cross a ridge on the way back to the starting point, it is regarded as a fault shutdown and the device is locked; If it fails to cross a ridge and the real-time cleaning duration is less than the ridge avoidance time, it is regarded as a bin exit failure; If the proximity switch cycle is unstable and fluctuates frequently within the cycle, it is due to the mismatch between the motor speed and the wire rope, which is regarded as power abnormality; If the real-time cleaning time is greater than the set cleaning time, it is regarded as a bin exit failure; If the pulse is 0 and the current is overloaded and the reverse real-time cleaning duration is less than the forward real-time cleaning duration, and if the pulse is 0 and the current is overloaded and the real-time cleaning duration is less than the set cleaning duration, it is regarded as device blockage; If the pulse is 0 and the current is overloaded and the real-time cleaning duration is equal to the set cleaning duration, it is regarded as reaching the end point; If the real-time cleaning duration is greater than the set cleaning duration and the number of pulses is less than the set threshold, it is regarded as transmission abnormality, that is, the wire rope is loose; When the real-time cleaning time is greater than the set cleaning time and the pulse is 0, it is regarded as abnormal transmission, that is, the steel wire rope is disconnected.

3. The cleaning method of a zip-type photovoltaic cleaning robot according to claim 1, wherein: The corresponding processing steps added for different extreme weather conditions in step S4 are as follows: In extremely cold climates, add an equipment preheating program, adjust the viscosity of the motor lubricating oil, and improve the battery heat preservation performance; In high-temperature climates, start the equipment cooling system, reduce the motor operating power, and optimize the cleaning path to avoid direct sunlight areas; In rainy and cloudy days, improve the sensor detection accuracy, adjust the cleaning frequency, and increase anti-slip measures; In sandstorm weather, enable the equipment dust cover, strengthen the motor seal, and adjust the cleaning strategy to short-cycle and high-frequency cleaning.

4. A cleaning method for a zip-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. The connection method of the serial communication is as follows: RS485-1 is used as the debugging serial port, which is directly connected to the PC and through USR-DR164. The UI obtains the log in ASCII format; RS485-2 is used as the service configuration serial port. The control board runs the Modbus RTU slave station. The PC is connected to the serial port and USR-DR164, and the UI configures and displays parameters through the Modbus protocol; RS485-3 is connected to the motor driver. The control board runs the Modbus master station and communicates with the motor driver; RS485-4 is used as a spare serial port to reserve for docking other devices; The Lora serial port is used to communicate with the gateway through Modbus RTU. The communication channel is Lora, and the data content is the same as that of RS485-2.

5. A cleaning method for a zip-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. The camera synchronously collects images to verify the nature of the 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 cleaning system for a zip-type photovoltaic cleaning robot, which adopts the cleaning method of a zip-type photovoltaic cleaning robot according to any one of claims 1-5, characterized in that, It includes: 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 through 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 lidar, a camera, and a voltage sensor; The control unit is used to execute the cleaning method described in claim 1, including 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 interacting data with external devices through the communication unit. The control unit is bidirectionally electrically connected to the detection unit, the execution unit, the communication unit, and the storage unit. The SLAM algorithm is set inside the control unit; The execution unit is used to receive the rotation speed and steering control signals. The execution unit includes a drive motor, a cleaning brush head, and a zip-lock mechanism. The cleaning brush head is fixedly connected to the output shaft of the drive motor through a coupling. The traction end of the zip-lock mechanism cooperates with the steel wire rope reel of the drive motor; The communication unit includes an RS485 communication module and a Lora wireless module. An EEPROM storage chip is provided inside the storage unit, and the storage unit is used to save the forward and reverse real-time cleaning duration, fault codes, and device configuration parameters. The power supply unit includes a main power supply module and a backup power supply module. The output terminal of the main power supply module is connected to the power supply ports 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, and the environmental adaptation unit includes a heating module, a dust cover driving mechanism, and a waterproof sealing component.

7. The cleaning system of a zip-type photovoltaic cleaning robot according to claim 6, characterized in that: The lidar is connected to the control unit through a USB interface. The lidar is used to emit a laser beam of 650 - 800nm 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 through an HDMI interface. The environmental data collected by the lidar and the camera is transmitted to the SLAM algorithm module inside the control unit.

8. The cleaning system of a zip-type photovoltaic cleaning robot 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 terminal of the detection unit. The fault diagnosis module is integrated in the FPGA coprocessor of the main controller and performs real-time analysis on pulse and current data through preset logical conditions. The key input port of the mode switching module is connected to the device operation panel.

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

10. The cleaning system of a zip-type photovoltaic cleaning robot according to claim 6, characterized in that: The heating module of the environmental adaptation unit is composed of PTC thermistors. The PTC thermistors are pasted on the motor stator winding and the inner wall of the battery compartment. The PTC thermistors are connected to the PWM port of the control unit through MOS tubes. The dust cover driving mechanism is connected to the sliding guide of the brush head dust cover through a micro stepping motor and a synchronous belt.

Images