A photovoltaic cleaning robot adaptive adhesion and obstacle crossing control method for complex working conditions

Abstract

The application discloses a photovoltaic cleaning robot adaptive adhesion and obstacle crossing control method for complex working conditions, and relates to the technical field of photovoltaic cleaning robot control, which comprises the following steps: collecting photovoltaic cleaning robot negative pressure cavity pressure, attitude angle, running acceleration, obstacle geometric parameters and control system cable component state data; constructing mechanical stress sequence, thermal stress sequence and electric load sequence of each cable section according to robot action time sequence, and correcting multi-stress field life model based on conductor resistance change, so as to calculate cable cumulative damage and cable residual life; determining obstacle crossing control parameters according to adhesion safety margin, obstacle geometric parameters and cable residual life; controlling the robot to perform obstacle approach, load transfer, obstacle crossing and contact recovery, and updating cable life state to correct obstacle crossing control parameters of the next obstacle crossing period. The application takes into account the robot obstacle crossing safety and long-term reliability of the cable component.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic cleaning robot control technology, and in particular to an adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions. Background Technology

[0002] As photovoltaic (PV) power generation systems continue to expand into mountainous, hilly, desert, and large-scale distributed building surfaces, the installation slope, array gap, frame height, and surface contamination of PV modules exhibit significant differences. PV cleaning robots, during operation, not only need to perform adsorption, walking, and surface cleaning, but also frequently need to execute turning, wheel lifting, frame crossing, and posture recovery maneuvers. Existing PV cleaning robots typically adjust adsorption force and walking parameters based on negative pressure chamber pressure, posture information, obstacle size, or preset motion trajectories. Related research mainly focuses on path coverage, stain recognition, obstacle detection, and obstacle avoidance control. However, under complex conditions such as continuous obstacle crossing, slope turning, and load fluctuations, the robot control system cable assembly repeatedly endures bending, torsion, and axial tension during the movement process. Simultaneously, it is also affected by conductor temperature rise, current changes, and contact resistance fluctuations, easily leading to cumulative fatigue damage in the bending and connection sections of the cable. If obstacle-crossing control relies solely on the robot's current attachment state and obstacle geometry, without considering the remaining lifespan of the control system's cable assemblies as a motion constraint, the robot may still employ large lifting amplitudes, obstacle-crossing speeds, or turning angles even when the attachment safety margin meets requirements. This can lead to the continuous accumulation of cable damage, increasing the risk of conductor breakage, connection failure, and control signal interruption. Therefore, how to dynamically assess the multi-stress field damage of the cable assemblies while ensuring the robot's attachment stability and obstacle-crossing capability, and how to feed the assessment results back to the subsequent obstacle-crossing control process, has become a problem that needs to be solved in the control technology of photovoltaic cleaning robots under complex working conditions.

[0003] CN117629185B discloses a method for planning the operating path of a photovoltaic cleaning robot under complex working conditions, belonging to the field of path planning technology. This invention introduces a boundary-finding strategy and a bottom-exploration strategy. The boundary-finding strategy expands the exploration range of the photovoltaic cleaning robot during operation, while the bottom-exploration strategy ensures that after entering a new area and completing the cleaning task of the entire area, the photovoltaic cleaning robot can effectively return to the previous area to continue cleaning the unfinished parts, thereby improving the efficiency and adaptability of the photovoltaic cleaning robot and enabling it to better cope with the challenges of complex environments. This technology mainly focuses on planning the area exploration, cleaning coverage, and operating path continuity of the photovoltaic cleaning robot. Its control is based on the robot's positional relationship in the photovoltaic array and the area cleaning status. It does not perform segmented analysis of the bending, torsional, and axial tensile loads generated by adsorption, turning, wheel lifting, crossing, and resetting actions on the control system cable assembly, nor does it construct a multi-stress field life model of the cable assembly in conjunction with conductor temperature, current, and conductor resistance changes. Therefore, this technology has difficulty adjusting the robot's obstacle-crossing actions based on the cumulative damage and remaining lifespan of the cable. When frequently traveling back and forth, turning continuously, and crossing component edges multiple times, there may still be a problem where the running path is reasonable but the fatigue damage of the cable components is accelerated.

[0004] CN120588224A This invention relates to the field of automation control technology and discloses a control method, system, and robot for a photovoltaic panel cleaning robot, including the following steps: S1, real-time acquisition of photovoltaic panel surface image data through a multimodal vision sensor module mounted on the cleaning robot, generating a cleaning level and matching a corresponding cleaning strategy; S2, real-time monitoring of the robot's surrounding environment using a multi-sensor fusion module, adjusting the robot's movement trajectory or triggering emergency braking for intelligent obstacle avoidance; S3, real-time updating of the environmental map based on an adaptive path planning algorithm combining A* algorithm and reinforcement learning to achieve full coverage cleaning and avoid repetition or omissions. By combining a multimodal vision sensor module with a deep learning algorithm, accurate identification of stains and obstacles is achieved, generating a dynamic cleaning strategy. Through Q-learning training, cleaning time is shortened and repetitive operations are avoided, thereby improving cleaning efficiency and coverage. This technology can adjust cleaning strategies and movement trajectories based on stain levels, environmental maps, and obstacle recognition results. However, its multi-sensor fusion primarily serves environmental perception, obstacle avoidance, and coverage path updates. It fails to jointly convert negative pressure chamber pressure, attitude angle, and running acceleration into attachment safety margins, nor does it divide the control system cable assembly into fixed segments, movable bending segments, and connecting segments, or analyze the mechanical stress, thermal stress, and electrical load of different cable segments according to the robot's action sequence. Consequently, this technology lacks constraints on the remaining lifespan of the cables when determining obstacle-crossing speed, the lifting sequence of the walking unit, and the turning angle, making it difficult to balance the robot's immediate obstacle avoidance safety with the long-term reliability of the control system cable assembly.

[0005] In summary, existing path planning and motion control technologies for photovoltaic cleaning robots suffer from the problem of separation between attachment status, obstacle geometry, and the lifespan of the control system's cable assemblies. This makes it difficult to dynamically adjust subsequent control parameters based on changes in mechanical stress, thermal stress, and electrical load generated by obstacle-crossing actions. This invention provides an adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions, thereby solving the problems of neglecting cumulative damage to cable assemblies and the potential for obstacle-crossing actions to accelerate cable fatigue failure under complex conditions. Summary of the Invention

[0006] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract and title of the invention. Such simplifications or omissions shall not be used to limit the scope of the present invention.

[0007] Given that existing photovoltaic cleaning robot control technologies suffer from the separation of attachment status, obstacle geometry, and the lifespan of control system cable assemblies, making it difficult to balance robot obstacle-crossing safety with the long-term reliability of cable assemblies, this invention is proposed.

[0008] Therefore, the problem to be solved by this invention is how to adaptively determine the robot's attachment adjustment and obstacle crossing control parameters under complex slope, continuous turning and frequent obstacle crossing conditions, taking into account the robot's attachment safety margin, obstacle geometry parameters and the remaining life of the control system cable assembly.

[0009] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides an adaptive attachment and obstacle-crossing control method for a photovoltaic cleaning robot under complex working conditions, comprising: The negative pressure chamber pressure, attitude angle, running acceleration, obstacle geometry parameters, bending radius, torsion angle, axial tension, conductor temperature, current and conductor resistance of the control system cable assembly are obtained. The control system cable assembly is divided into fixed section, movable bending section and connection section to form cable assembly status data. Align the cable assembly status data according to the action sequence of adsorption, turning, lifting wheel, crossing and resetting, construct the mechanical stress sequence, thermal stress sequence and electrical load sequence of each cable segment, and correct the multi-stress field life model according to the change of conductor resistance to calculate the cumulative damage and remaining life of the cable. The attachment safety margin is calculated based on the negative pressure chamber pressure, attitude angle and running acceleration. The obstacle geometric parameters, cable remaining life and attachment safety margin are used together as constraints to determine the negative pressure chamber pressure adjustment sequence, walking unit lifting sequence, obstacle crossing speed and turning angle, thus forming obstacle crossing control parameters. The photovoltaic cleaning robot is controlled to sequentially execute obstacle approach, load transfer, obstacle crossing and contact recovery according to the obstacle crossing control parameters. The cumulative cable damage and remaining cable life are updated based on the newly added cable component status data during the execution, and the obstacle crossing control parameters for the next obstacle crossing cycle are corrected.

[0010] Compared with existing technologies, the beneficial effects of this invention are as follows: By collecting the operating status parameters of the photovoltaic cleaning robot and the multi-dimensional status parameters of the control system cable assembly, and by managing the cable assembly in segments, this invention achieves synchronous perception of the robot's operating status and the cable's stress state. This provides an accurate data foundation for subsequent life assessment and obstacle crossing control, improving the comprehensiveness of status perception under complex working conditions. By constructing a sequence of cable mechanical stress, thermal stress, and electrical load, and combining this with dynamic correction of the multi-stress field life model based on conductor resistance changes, this invention achieves accurate assessment of the cable's cumulative damage and remaining life. This allows life prediction to truly reflect the cable's service status, providing a basis for control strategy optimization and preventative maintenance, and improving the overall performance of the cable. Operational reliability: By using attachment safety margin, obstacle geometry parameters, and cable remaining life as joint constraints, obstacle crossing control parameters are generated, achieving coordinated optimization of attachment capability, obstacle crossing performance, and cable life. This enables the robot to adaptively adjust its obstacle crossing strategy for different obstacles and working conditions, reducing cable stress damage while ensuring attachment stability and improving the obstacle crossing success rate under complex working conditions. By continuously updating the cumulative cable damage and remaining life based on the real-time status during obstacle crossing execution and correcting the control parameters for the next obstacle crossing cycle, closed-loop optimization of the obstacle crossing control strategy is achieved. This allows the control parameters to be dynamically adjusted according to the equipment status, further improving the robot's safety, stability, and environmental adaptability during long-term continuous operation. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart of an adaptive attachment and obstacle-crossing control method for a photovoltaic cleaning robot designed for complex working conditions. Detailed Implementation

[0012] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0013] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the scope of protection of this invention.

[0014] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0015] As mentioned in the background section, existing technologies typically focus on path planning, obstacle recognition, and trajectory adjustment for photovoltaic cleaning robots. They fail to analyze the mechanical stress, thermal stress, and electrical load on the cable assemblies according to the action sequence of adsorption, turning, wheel lifting, crossing, and resetting. Furthermore, they do not correct the multi-stress field life model of the cable assemblies based on conductor resistance changes. This can lead to accelerated fatigue damage to the cable assemblies during continuous obstacle crossing due to unreasonable control parameter settings. To address these issues, this invention provides an adaptive attachment and obstacle crossing control method for photovoltaic cleaning robots operating in complex conditions.

[0016] Reference Figure 1 , Figure 1 This is a flowchart illustrating an adaptive attachment and obstacle-crossing control method for a photovoltaic cleaning robot under complex working conditions, according to an embodiment of the present invention. Figure 1 As shown, an adaptive attachment and obstacle-crossing control method for a photovoltaic cleaning robot under complex working conditions includes: S1: Obtain the negative pressure chamber pressure, attitude angle, running acceleration, obstacle geometry parameters, bending radius, torsion angle, axial tension, conductor temperature, current and conductor resistance of the control system cable assembly of the photovoltaic cleaning robot, divide the control system cable assembly into fixed section, movable bending section and connection section, and form cable assembly status data.

[0017] S1.1: Deploy the status acquisition components and establish the positional correspondence between the photovoltaic cleaning robot and the control system cable assembly.

[0018] S1.1: Establish the positional correspondence between the robot body, the walking unit, and the control system cable assembly.

[0019] Specifically, based on the robot's body structure, the location of the negative pressure chamber, the location of the walking unit, and the laying path of the control system cable assembly, a robot body coordinate system is established, and the starting point position, ending point position, fixed clamping position, movable joint position, and electrical connection position of the control system cable assembly are recorded.

[0020] Preferably, the robot's forward direction is taken as the longitudinal direction of the robot's body coordinate system, the direction perpendicular to the robot's forward direction and parallel to the surface of the photovoltaic module is taken as the transverse direction of the robot's body coordinate system, and the direction perpendicular to the surface of the photovoltaic module is taken as the normal direction of the robot's body coordinate system.

[0021] Furthermore, multiple cable position nodes are set along the laying path of the control system cable assembly, and node identifiers are configured for each cable position node in the order from the cable start position to the cable end position; the spatial coordinates of each cable position node in the robot body coordinate system and the correspondence between each cable position node and the negative pressure chamber, walking unit, fixed clamping position, movable joint position and electrical connection position are recorded respectively to obtain cable laying position data.

[0022] It should be noted that the cable laying location data serves as the basis for subsequent division into fixed sections, flexible bending sections, and connecting sections, and for determining the cable segments to which the bending radius, torsion angle, and axial tensile force belong.

[0023] S1.2: Divide the control system cable assembly into fixed sections, movable bending sections, and connecting sections according to the cable constraint state.

[0024] In this embodiment, the control system cable assembly is segmented along the laying direction of the control system cable assembly according to the fixed clamping position, the movable joint position, and the electrical connection position.

[0025] Cable segments located between adjacent fixed clamping positions and whose spatial displacement during robot walking, turning, and obstacle crossing is less than a preset displacement threshold are classified as fixed segments; cable segments located between fixed clamping positions and movable joint positions, or between adjacent movable joint positions, and which bend or twist as the walking unit is lifted, the robot turns, or the relative position of the negative pressure chamber changes, are classified as movable bending segments; and cable segments containing electrical connection positions and located within a preset length range on both sides of the electrical connection positions are classified as connecting segments.

[0026] The preset displacement threshold is determined based on the allowable movement of the fixing fixture corresponding to the fixed clamping position and the cable position measurement error. Specifically, the allowable movement of the fixing fixture and three times the cable position measurement error can be used as the preset displacement threshold to eliminate the influence of the cable position measurement error on the fixed segment division result.

[0027] The adjacent preset length range is determined based on the length of the stress relief structure at the tail of the connector corresponding to the electrical connection position and the minimum allowable bending radius of the control system cable assembly; the larger value between the length of the stress relief structure at the tail and the minimum allowable bending radius is taken along both sides of the electrical connection position to form the adjacent preset length range.

[0028] When the same cable section meets the criteria for both active bending section and connection section, the portion including the electrical connection location and the adjacent preset length range is classified as the connection section, and the portion outside the adjacent preset length range is classified as the active bending section.

[0029] Configure cable segment identifiers for fixed sections, flexible bending sections, and connecting sections respectively, and associate each cable segment identifier with the corresponding node identifier, the start position of the cable segment, and the end position of the cable segment.

[0030] For example, when the allowable movement of the fixing clamp is 1 mm and the cable position measurement error is 0.2 mm, the preset displacement threshold can be set to 1.6 mm; when the length of the tail stress relief structure is 30 mm and the minimum allowable bending radius is 40 mm, 40 mm can be selected on both sides of the electrical connection position as the adjacent preset length range. The above values ​​are adjusted according to the specifications and installation structure of the control system cable assembly.

[0031] S1.3: Collect the negative pressure chamber pressure, attitude angle, and running acceleration of the photovoltaic cleaning robot.

[0032] In this embodiment of the application, during the operation of the photovoltaic cleaning robot, the negative pressure chamber pressure, attitude angle and running acceleration are collected according to a preset sampling period, and a sampling timestamp is added to each collection result.

[0033] The internal pressure of each negative pressure chamber and the external environmental pressure at the robot's location are collected separately. The difference between the external environmental pressure and the internal pressure of the negative pressure chamber is taken as the negative pressure chamber pressure of the corresponding negative pressure chamber. The negative pressure chamber pressure is represented by a positive value. When the internal pressure of the negative pressure chamber decreases, the negative pressure chamber pressure increases.

[0034] The system collects the pitch, roll, and yaw angles of the photovoltaic cleaning robot relative to the surface of the photovoltaic module, and converts these angles into attitude angles. It also collects the acceleration components of the photovoltaic cleaning robot along the longitudinal, lateral, and normal directions of the robot's body coordinate system, and converts these acceleration components into running acceleration.

[0035] For a photovoltaic cleaning robot with multiple negative pressure chambers, according to the installation position of each negative pressure chamber in the robot's coordinate system, a negative pressure chamber position mark is configured for the pressure of each negative pressure chamber, so that the pressure of each negative pressure chamber corresponds to the negative pressure chamber at the front, rear, left, or right of the robot.

[0036] It should be noted that the attitude angle and running acceleration use the same time reference as the negative pressure chamber pressure, and the corresponding sampling timestamp is recorded in each acquisition result.

[0037] S1.4: Obtain the geometric parameters of obstacles in the forward direction of the photovoltaic cleaning robot.

[0038] During the process of the photovoltaic cleaning robot approaching an obstacle, the distance acquisition unit arranged at the front of the robot collects the distance information between the obstacle surface and the photovoltaic cleaning robot, and determines the obstacle geometric parameters based on the distance information corresponding to multiple acquisition directions. The obstacle geometric parameters include obstacle height, obstacle width, obstacle approach distance and obstacle edge direction.

[0039] The obstacle height is determined based on the normal height difference between the top, bottom, or bottom surface of the obstacle and the surface of the gap relative to the current photovoltaic module surface; where the obstacle height corresponding to an obstacle protruding from the current photovoltaic module surface is taken as a positive value, and the obstacle height corresponding to a depression or gap below the current photovoltaic module surface is taken as a negative value.

[0040] The obstacle width is determined by the coverage length of the gap between the obstacle or component along the robot's forward direction; the obstacle approach distance is determined by the longitudinal distance between the robot's front end and the edge of the obstacle closest to the robot; and the obstacle edge direction is determined by the angle between the extension direction of the obstacle edge and the lateral direction of the robot's body coordinate system.

[0041] For photovoltaic module frames, module gaps, and protruding connectors, the corresponding obstacle height, obstacle width, obstacle approach distance, and obstacle edge direction are recorded respectively, and the obstacle geometric parameters are correlated with the negative pressure chamber pressure, attitude angle, and running acceleration at the same acquisition time.

[0042] S1.5: Collect the bending radius, torsion angle and axial tension of each cable segment.

[0043] Based on the cable segment identifier, the bending radius, torsion angle and axial tension of the fixed segment, the movable bending segment and the connecting segment are collected respectively, and the collected results are written into the corresponding cable segment identifier.

[0044] At least three measurement positions are set along the centerline of each cable segment. The spatial coordinates of each measurement position in the robot body coordinate system are collected. The local curvature of the corresponding cable segment is determined based on the change in spatial coordinates of adjacent measurement positions, and the reciprocal of the local curvature is determined as the bending radius of the corresponding measurement position.

[0045] The torsion angle is determined based on the relative rotation angle of the starting and ending sections of each cable segment around the cable centerline; the axial tensile force borne by the corresponding cable segment along the cable centerline is collected by a tensile force acquisition unit set at the end of each cable segment or at a fixed clamping position.

[0046] For the active bending section, record the minimum bending radius, maximum absolute torsion angle, and maximum axial tensile force at the same sampling timestamp; for the fixed section, record the minimum bending radius, maximum absolute torsion angle, and maximum axial tensile force in the area adjacent to the fixed clamping position; for the connection section, record the minimum bending radius, maximum absolute torsion angle, and maximum axial tensile force on both sides of the electrical connection position respectively.

[0047] The minimum bending radius is used as the segmented record value of the bending radius, the maximum absolute torsion angle is used as the segmented record value of the torsion angle, and the maximum axial tensile force is used as the segmented record value of the axial tensile force to characterize the mechanical load state of each cable segment at the same sampling time.

[0048] S1.6: Collect conductor temperature, current and conductor resistance of each cable segment.

[0049] In this embodiment of the application, the conductor temperatures of the fixed section, the movable bending section and the connecting section are collected according to the cable segment identification, and the current flowing through the corresponding cable segment and the voltage drop at both ends of the corresponding cable segment are collected simultaneously.

[0050] Voltage acquisition nodes are set at both ends of the corresponding cable segment. The voltage drop is collected using a four-terminal measurement method. The conductor resistance is determined based on the ratio of voltage drop to current, so as to reduce the influence of lead resistance and connection contact resistance on conductor resistance.

[0051] When the current is greater than or equal to the preset lower current limit, the conductor resistance is calculated based on the voltage drop and current at the current sampling time; when the current is lower than the preset lower current limit, the conductor temperature and current at the current sampling time are retained, and the conductor resistance at the current sampling time is marked as pending supplementation.

[0052] For conductor resistance in a state to be supplemented, after the walking unit, negative pressure chamber adjustment unit, or other execution unit connected to the corresponding cable segment enters the action gap, the corresponding cable segment is switched to the resistance detection branch, a preset detection current is applied to the corresponding cable segment, the detection voltage drop corresponding to the preset detection current is collected, and the supplementary conductor resistance is calculated based on the detection voltage drop and the preset detection current. The supplementary conductor resistance is written into the sampling record corresponding to the state to be supplemented, and a supplementary measurement mark is added.

[0053] If no additional conductor resistance is obtained within an obstacle crossing cycle, the state of pending replenishment is retained, and the corresponding sampling record is not used to correct the conductor resistance change in the subsequent multi-stress field life model, so as to avoid using invalid resistance values ​​in the calculation of cable cumulative damage.

[0054] It should be noted that the preset current lower limit is determined based on the effective resolution of the voltage acquisition unit, the reference conductor resistance of the corresponding cable segment, and the preset signal-to-noise ratio. Specifically, the expected voltage drop generated by the preset current lower limit flowing through the reference conductor resistance is not less than three times the effective resolution of the voltage acquisition unit. The preset detection current is greater than or equal to the preset current lower limit and less than the allowable continuous current of the corresponding cable segment. The application duration of the preset detection current is determined based on the time required for the voltage acquisition unit to complete stable sampling.

[0055] For the connection section, record the conductor temperature and conductor resistance on both sides of the electrical connection position; for the movable bending section, record the conductor temperature corresponding to the position of the minimum bending radius; for the fixed section, record the conductor temperature in the area adjacent to the fixed clamping position.

[0056] Conductor temperature, current, and conductor resistance use the same time reference as bending radius, torsion angle, and axial tensile force, so that the mechanical and electrothermal parameters of each cable segment correspond to the sampling timestamp.

[0057] S1.7: Generate cable assembly status data according to the sampling timestamp and cable segment identifier.

[0058] In this embodiment, the negative pressure chamber pressure, attitude angle, running acceleration, and obstacle geometry parameters at the same sampling time are used as robot running status fields; the bending radius, torsion angle, axial tension, conductor temperature, current, and conductor resistance corresponding to the fixed segment, the movable bending segment, and the connecting segment are used as cable segmentation status fields.

[0059] The robot's running status field and cable segment status field are arranged according to the sampling timestamp. The cable segment status fields of the same cable segment at different sampling times are then collected according to the cable segment identifier to form cable assembly status data. The cable assembly status data includes at least the sampling timestamp, cable segment identifier, cable segment type, bending radius, torsion angle, axial tension, conductor temperature, current, conductor resistance, conductor resistance measurement status, negative pressure chamber pressure, attitude angle, running acceleration, and obstacle geometry parameters.

[0060] For robot running status fields and cable segmentation status fields with inconsistent sampling times, time matching is performed based on their respective sampling timestamps. When the time difference between two sampling times is less than or equal to a preset synchronization time threshold, the robot running status field and cable segmentation status field with the closest time are arranged into the same sampling record. When the time difference exceeds the preset synchronization time threshold, an asynchronous flag is added to the corresponding sampling record, and the corresponding sampling record is not used to construct the multi-stress state at the same time.

[0061] It should be noted that the preset synchronization time threshold is determined based on the maximum sampling period of each acquisition channel and the duration of the shortest action phase among adsorption, turning, wheel lifting, crossing, and reset. The preset synchronization time threshold is no greater than the maximum sampling period and less than one-tenth of the duration of the shortest action phase.

[0062] The cable assembly status data represents the mechanical and electrothermal states of different cable segments according to the cable segment identifiers, and is associated with the attachment state, motion state and obstacle space state of the photovoltaic cleaning robot according to the sampling timestamp. This data serves as the basis for constructing mechanical stress sequence, thermal stress sequence and electrical load sequence according to the action sequence of adsorption, turning, lifting wheels, crossing and resetting.

[0063] S2: Align the cable assembly status data according to the action sequence of adsorption, turning, lifting wheel, crossing and resetting, construct the mechanical stress sequence, thermal stress sequence and electrical load sequence of each cable segment, and correct the multi-stress field life model according to the change of conductor resistance to calculate the cumulative damage and remaining life of the cable.

[0064] S2.1: Divide the obstacle-crossing action cycle and its action stages according to the action records of the photovoltaic cleaning robot.

[0065] In this embodiment of the application, the control commands output by the photovoltaic cleaning robot controller to the negative pressure chamber and the walking unit during the obstacle approach process are read, and the action feedback information corresponding to each control command is read. The command output timestamp of each control command and the feedback timestamp of each action feedback information are recorded to form a robot action record.

[0066] The moment when the photovoltaic cleaning robot begins to adjust the pressure of the negative pressure chamber is taken as the start moment of an obstacle-crossing action cycle. The moment when the photovoltaic cleaning robot crosses the obstacle away from the edge of the robot and the pressure of the negative pressure chamber, attitude angle and running acceleration return to the stable range before obstacle crossing is taken as the end moment of the obstacle-crossing action cycle. An action cycle identifier is configured for the robot action record between the start moment and the end moment.

[0067] According to the sequence of control instructions in the robot's motion record, the obstacle crossing action cycle is divided into the adsorption stage, turning stage, wheel lifting stage, crossing stage, and reset stage, and each action stage is assigned an action stage identifier.

[0068] The time interval from when the photovoltaic cleaning robot starts adjusting the negative pressure chamber pressure to when the negative pressure chamber pressure reaches the corresponding target pressure is divided into the adsorption stage; the time interval from when the photovoltaic cleaning robot starts changing its direction of travel to when the turning angle reaches the corresponding target angle is divided into the turning stage; the time interval from when the walking unit starts to rise to when the walking unit reaches the corresponding rising position is divided into the wheel lifting stage; the time interval from when the walking unit starts to cross the obstacle edge on the side of the obstacle close to the robot to when the walking unit crosses the obstacle edge on the side of the obstacle away from the robot is divided into the crossing stage; and the time interval from when the walking unit starts to fall back to when the photovoltaic cleaning robot resumes a stable walking state is divided into the reset stage.

[0069] When the control commands of adjacent action phases overlap in time, the timestamp of the command output of the corresponding control command in the later action phase will be used as the dividing time between adjacent action phases, and the corresponding action phase identifier will be configured according to the dividing time.

[0070] S2.2: Align cable assembly status data according to action cycle identifier and action phase identifier.

[0071] In this embodiment of the application, the robot running status field and cable segment status field located in the same obstacle crossing action cycle are extracted from the cable component status data according to the sampling timestamp, and the corresponding action cycle identifier and action stage identifier are configured for each cable component status data according to the start time and end time of each action stage.

[0072] The bending radius, torsion angle, axial tension, conductor temperature, current and conductor resistance corresponding to the same cable segment identifier are arranged in time according to a unified time step; wherein the unified time step is determined according to the maximum sampling period of each acquisition channel in step S1.

[0073] For sampling records with asynchronous identifiers, the corresponding robot running status field and cable segmentation status field are not configured as multi-stress states at the same time. For sampling records where the conductor resistance measurement status is a valid measurement state or a supplementary measurement state, the corresponding conductor resistance is retained. For sampling records where the conductor resistance measurement status is a supplementary state, the corresponding bending radius, torsion angle, axial tension, conductor temperature, and current are retained, and the corresponding conductor resistance is not used for model correction for the time being.

[0074] When the time interval between adjacent valid sampling records is less than or equal to two unified time steps, the missing position is interpolated based on the adjacent valid sampling records; when the time interval between adjacent valid sampling records is greater than two unified time steps, the corresponding time interval is marked as a data missing interval, and the damage increment of the corresponding cable segment is not calculated using the data missing interval.

[0075] According to the cable segment identifier, the cable assembly status data of the fixed segment, the movable bending segment and the connecting segment are collected in the adsorption stage, turning stage, lifting wheel stage, crossing stage and reset stage to form the cable segment timing data corresponding to each cable segment.

[0076] S2.3: Construct the mechanical stress sequence for each cable segment based on the bending radius, torsion angle, and axial tensile force.

[0077] In this embodiment of the application, the equivalent bearing diameter, equivalent bearing cross-sectional area, equivalent elastic modulus, equivalent shear modulus, and effective length of cable segments corresponding to the specifications of the control system cable assembly are obtained, and the equivalent bearing diameter, equivalent bearing cross-sectional area, equivalent elastic modulus, equivalent shear modulus, and effective length of cable segments are associated with the fixed segment, the movable bending segment, and the connecting segment, respectively, according to the cable segment identifier.

[0078] The bending stress of the corresponding cable segment is determined based on the bending radius, equivalent bearing diameter, and equivalent elastic modulus under the same sampling timestamp. The bending stress is directly proportional to the product of the equivalent elastic modulus and the equivalent bearing diameter, and inversely proportional to the bending radius. The torsional shear stress of the corresponding cable segment is determined based on the torsion angle, the effective length of the cable segment, the equivalent bearing diameter, and the equivalent shear modulus. The torsional shear stress is directly proportional to the product of the equivalent shear modulus, the equivalent bearing diameter, and the torsion angle, and inversely proportional to the effective length of the cable segment. The axial stress of the corresponding cable segment is determined based on the axial tensile force and the equivalent bearing cross-sectional area. The axial stress is the ratio of the axial tensile force to the equivalent bearing cross-sectional area.

[0079] The combined normal stresses when bending stress and axial stress are superimposed in the same direction and in opposite directions are calculated respectively. The combined normal stresses with larger absolute values ​​are selected and the torsional shear stresses are processed to obtain the mechanical equivalent stresses at the corresponding sampling timestamps.

[0080] The mechanical equivalent stresses corresponding to the same cable segment identifier are arranged according to the sampling timestamp, and the mechanical equivalent stresses in the adsorption stage, turning stage, lifting wheel stage, crossing stage and reset stage are collected according to the action stage identifier to form the mechanical stress sequence of each cable segment.

[0081] The equivalent bearing diameter, equivalent bearing cross-sectional area, equivalent elastic modulus, and equivalent shear modulus are determined based on the load-deformation relationship measured in tensile, bending, and torsion tests of control system cable assemblies of the same specifications. This is to reduce the calculation deviation caused by directly treating multi-strand conductors, insulation layers, shielding layers, and sheaths as solid round rods.

[0082] S2.4: Construct the thermal stress sequence and electrical load sequence for each cable segment based on conductor temperature, current and conductor resistance.

[0083] In this embodiment, the reference conductor temperature, coefficient of linear expansion, and thermal constraint coefficient corresponding to the fixed segment, the movable bending segment, and the connecting segment are obtained respectively. The reference conductor temperature is the conductor temperature of each cable segment when the photovoltaic cleaning robot is in a stable operating state before performing the first obstacle-crossing action cycle. The coefficient of linear expansion is determined according to the corresponding conductor material. The thermal constraint coefficient is determined according to the end constraint state and the degree of restriction of free thermal elongation of the corresponding cable segment.

[0084] The thermal stress of the corresponding cable segment is determined based on the temperature difference between the conductor temperature and the reference conductor temperature at the same sampling timestamp, the coefficient of linear expansion, the thermal constraint coefficient, and the equivalent elastic modulus, while retaining the direction of the thermal stress corresponding to the heating and cooling processes.

[0085] The thermal stresses corresponding to the same cable segment identifier are arranged according to the sampling timestamp, and the thermal stresses in each action stage are collected according to the action stage identifier to form the thermal stress sequence of each cable segment.

[0086] The Joule loss of the corresponding cable segment is determined based on the current and conductor resistance under the same sampling timestamp, and the Joule loss per unit length is determined based on the Joule loss and the effective length of the cable segment. The current and Joule loss per unit length are arranged according to the sampling timestamp, and the current and Joule loss per unit length in each action stage are collected according to the action stage identifier to form the electrical load sequence of each cable segment.

[0087] When the conductor resistance measurement status is in the supplementary state, the Joule loss per unit length under the corresponding sampling timestamp is not calculated temporarily; when the corresponding supplementary conductor resistance is obtained in step S1, the Joule loss per unit length is calculated based on the supplementary conductor resistance and the current under the corresponding sampling timestamp, and the supplementary calculation result is written into the electrical load sequence of the corresponding cable segment.

[0088] S2.5: The multi-stress field life model is constructed based on accelerated life test data of control system cable assemblies.

[0089] In this embodiment of the application, cable life samples with the same conductor structure, insulation structure, shielding structure, sheath structure and electrical connection structure as the fixed section, the movable bending section and the connecting section are selected respectively, and the cable life samples are installed according to the constraint state of the corresponding cable segments.

[0090] Multiple mechanical stress levels, multiple conductor temperature levels, and multiple electrical load levels were set for the cable life test samples. Among them, the mechanical stress level was formed by different combinations of bending radius, torsion angle, and axial tensile force; the conductor temperature level was formed by different average conductor temperature and temperature cycling range; and the electrical load level was formed by different current and Joule loss per unit length.

[0091] The cable life specimens were subjected to bending, torsion, axial tension, temperature cycling, and current carrying in sequence according to the preset multi-stress combination. The mechanical stress cycle number, conductor temperature change, Joule loss per unit length, and conductor resistance change of each cable life specimen under different multi-stress combinations were recorded.

[0092] When a cable life sample experiences any of the following conditions: conductor continuity interruption, insulation performance below the preset insulation limit, or the relative change in conductor resistance after temperature correction reaches the preset resistance failure threshold, the corresponding cable life sample is recorded as having reached a failure state, and the number of failure cycles at the time of reaching the failure state is recorded.

[0093] Based on the mechanical equivalent stress amplitude, thermal stress amplitude, average conductor temperature, Joule loss per unit length, and failure cycle number corresponding to each cable life sample, a multi-factor regression method was used to establish the correspondence between the stress level and the allowable cycle number for the fixed section, the flexible bending section, and the connection section, forming a multi-stress field life model.

[0094] In the multi-stress field life model, mechanical stress parameters, thermal stress parameters, electrical load parameters, and interaction parameters between mechanical stress and thermal stress, mechanical stress and electrical load, and thermal stress and electrical load are set respectively. Each interaction parameter is tested based on cable life samples that were not involved in the determination of model parameters. When any interaction parameter fails to reduce the prediction deviation of the allowable number of cycles, the corresponding interaction parameter is set to zero.

[0095] It should be noted that the fixed section, the movable bending section, and the connecting section each adopt a corresponding multi-stress field life model to reflect the differences in the impact of mechanical stress, thermal stress, and electrical load on cable life under different cable constraint states.

[0096] S2.6: Calculate the cumulative damage of the multi-stress field life model based on the mechanical stress sequence, thermal stress sequence, and electrical load sequence.

[0097] Peak and valley values ​​of mechanical stress sequence for each cable segment are extracted, and the rain flow cycle counting method is used to identify mechanical stress cycles within the obstacle crossing action cycle, so as to obtain the mechanical equivalent stress amplitude, mechanical equivalent average stress and actual number of cycles corresponding to each mechanical stress cycle.

[0098] Based on the start and end times of each mechanical stress cycle, the maximum and minimum thermal stress values ​​are extracted from the thermal stress sequence corresponding to the same cable segment identifier, and the thermal stress amplitude of the corresponding mechanical stress cycle is determined based on the maximum and minimum thermal stress values.

[0099] Based on the start and end times of each mechanical stress cycle, the current and Joule loss per unit length are extracted from the electrical load sequence corresponding to the same cable segment identifier, and the average conductor temperature and equivalent Joule loss per unit length within the corresponding time interval are calculated.

[0100] Input the mechanical equivalent stress amplitude, thermal stress amplitude, average conductor temperature, and equivalent Joule loss per unit length corresponding to each mechanical stress cycle into the multi-stress field life model of the corresponding cable segment type to obtain the allowable number of cycles under the corresponding multi-stress conditions.

[0101] The Miner linear cumulative damage method is adopted to calculate the ratio of the actual number of cycles of each mechanical stress cycle to the corresponding allowable number of cycles. The ratios of the same cable segment in the current obstacle crossing action cycle are accumulated to obtain the periodic model damage amount of the corresponding cable segment.

[0102] The cumulative damage of the corresponding cable segment is obtained by adding the damage amount of the periodic model to the cumulative damage amount of the historical model of the corresponding cable segment before the current obstacle crossing cycle.

[0103] Record the damage amount of the stage model corresponding to the adsorption stage, turning stage, wheel lifting stage, crossing stage and reset stage according to the action stage identifier, so as to determine the contribution of different action stages to the cumulative damage amount.

[0104] S2.7: Based on the change in conductor resistance, correct the cumulative damage of the multi-stress field life model to obtain the cumulative damage of cable segments.

[0105] The reference conductor resistance of each cable segment under initial healthy conditions is obtained, and the corresponding reference conductor resistance temperature is recorded. Based on the temperature coefficient of resistance of the corresponding conductor material, the conductor resistance at each sampling timestamp is converted to the reference conductor resistance temperature to obtain the temperature-corrected conductor resistance.

[0106] Based on the temperature-corrected conductor resistance and the reference conductor resistance corresponding to the same cable segment identifier, the relative change in conductor resistance is determined, and the relative change in conductor resistance is arranged according to the obstacle crossing action cycle to obtain the conductor resistance change sequence of the corresponding cable segment.

[0107] Based on the conductor resistance changes and failure cycle counts recorded in the accelerated life test, a resistance damage correspondence is established between the relative change in conductor resistance and the degree of cable damage. The resistance characterization damage is then determined from the resistance damage correspondence based on the current relative change in conductor resistance.

[0108] When the resistance-indicated damage amount is greater than the cumulative damage amount, the cumulative damage amount of the corresponding cable segment is increased based on the difference between the resistance-indicated damage amount and the cumulative damage amount; when the resistance-indicated damage amount is less than or equal to the cumulative damage amount, the cumulative damage amount of the corresponding cable segment is retained, and the cumulative damage amount of the corresponding cable segment is obtained.

[0109] For sampling records where the conductor resistance measurement status is pending, the relative change in conductor resistance is not determined using the corresponding sampling record. When the supplementary conductor resistance is subsequently obtained, the temperature-corrected conductor resistance and the relative change in conductor resistance of the corresponding sampling record are re-determined, and the resistance characterization damage and cumulative damage of the corresponding cable segment are updated.

[0110] By using changes in conductor resistance to perform unidirectional incremental correction of cumulative damage, the resistance increase corresponding to conductor microcracks, reduction in effective conductor cross-sectional area, and changes in contact state at electrical connection points is reflected in the cumulative damage of cable segments, and historical damage that has already occurred is avoided due to a short-term decrease in conductor resistance.

[0111] S2.8: Calculate the cumulative damage and remaining life of the cable by calculating the cumulative damage of each cable segment.

[0112] The maximum value among the cumulative damage amounts of the cable segments corresponding to each fixed segment, each movable bending segment, and each connecting segment is determined as the cumulative damage amount of the control system cable assembly, and the cable segment identifier corresponding to the cumulative damage amount is recorded.

[0113] Calculate the periodic damage increment of each cable segment in the most recent obstacle crossing action cycles. The periodic damage increment is the periodic model damage amount corresponding to the current obstacle crossing action cycle. Determine the average periodic damage increment of the corresponding cable segment based on the periodic model damage amount in the most recent obstacle crossing action cycles.

[0114] Based on the remaining damage space between the preset damage failure threshold of the corresponding cable segment and the cumulative damage of the cable segment, as well as the average periodic damage increment of the corresponding cable segment, the remaining obstacle-crossing action cycle number of the corresponding cable segment is calculated.

[0115] When the cumulative damage to a cable segment reaches or exceeds the corresponding preset damage failure threshold, the remaining obstacle crossing action cycle number for the corresponding cable segment is recorded as zero; when the average periodic damage increment is zero, the remaining obstacle crossing action cycle number corresponding to the previous obstacle crossing action cycle is used.

[0116] The minimum value among the remaining obstacle-crossing action cycles corresponding to each fixed segment, each movable bending segment, and each connecting segment is determined as the remaining cable life of the control system cable assembly, and the cable segment identifier and action stage identifier corresponding to the remaining cable life are recorded.

[0117] The cumulative damage to the cable, the remaining life of the cable, the cable segmentation markers corresponding to the remaining life of the cable, and the corresponding action stage markers serve as the data basis for subsequently determining the pressure adjustment sequence of the negative pressure chamber, the lifting sequence of the walking unit, the obstacle crossing speed, and the turning angle by using obstacle geometry parameters, the remaining life of the cable, and the attachment safety margin together as constraints.

[0118] S3: Calculate the attachment safety margin based on the negative pressure chamber pressure, attitude angle, and running acceleration. Use the obstacle geometry parameters, cable remaining life, and attachment safety margin together as constraints to determine the negative pressure chamber pressure adjustment sequence, walking unit lifting sequence, obstacle crossing speed, and turning angle, thus forming obstacle crossing control parameters.

[0119] S3: Calculate the adhesion safety margin based on the negative pressure chamber pressure, attitude angle, and running acceleration. Using obstacle geometry parameters, cable remaining life, and adhesion safety margin as constraints, determine the negative pressure chamber pressure adjustment sequence, walking unit lifting sequence, obstacle-crossing speed, and turning angle to form obstacle-crossing control parameters. This includes the following steps: S3.1: Calculate the attachment safety margin at the start of the current obstacle crossing action cycle based on the negative pressure chamber pressure, attitude angle, and running acceleration.

[0120] In this embodiment of the application, the negative pressure chamber pressure, attitude angle and running acceleration in the cable assembly status data corresponding to the start time of the current obstacle crossing action cycle are read; according to the position identifier of each negative pressure chamber, the front negative pressure chamber pressure, rear negative pressure chamber pressure, left negative pressure chamber pressure and right negative pressure chamber pressure of the photovoltaic cleaning robot are obtained respectively, and the negative pressure chamber pressure in each direction is recorded as front adsorption force, rear adsorption force, left adsorption force and right adsorption force respectively.

[0121] Based on the pitch and roll angles in the attitude angles, the tilt direction and degree of the photovoltaic cleaning robot relative to the surface of the photovoltaic module at the current moment are determined. The components of gravity along the longitudinal and lateral directions of the robot's body coordinate system are calculated according to the pitch and roll angles, and the component of gravity along the longitudinal direction is recorded as the longitudinal disturbance component, and the component of gravity along the lateral direction is recorded as the lateral disturbance component.

[0122] Based on the acceleration components along the longitudinal, lateral, and normal directions of the robot's body coordinate system, the inertial force at the start of the current obstacle-crossing action cycle is determined. Specifically, the product of the acceleration component along the longitudinal direction and the mass of the photovoltaic cleaning robot is recorded as the longitudinal inertial force, the product of the acceleration component along the lateral direction and the mass of the photovoltaic cleaning robot is recorded as the lateral inertial force, and the product of the acceleration component along the normal direction and the mass of the photovoltaic cleaning robot is recorded as the normal inertial force.

[0123] Based on the negative pressure chamber pressure in each direction and the longitudinal disturbance component, lateral disturbance component, longitudinal inertial force, lateral inertial force, and normal inertial force, the adhesion safety margin in each direction is calculated as follows: For the front adhesion safety margin, the front adhesion force is subtracted from the distribution of the resultant force of the longitudinal disturbance component and the longitudinal inertial force in the longitudinal direction at the front of the photovoltaic cleaning robot, and then divided by the front adhesion force to obtain the front adhesion safety margin; for the rear adhesion safety margin, the rear adhesion force is subtracted from the distribution of the resultant force of the longitudinal disturbance component and the longitudinal inertial force in the longitudinal direction at the front of the photovoltaic cleaning robot. The rear attachment safety margin is obtained by dividing the amount of material distributed at the rear of the cleaning robot by the rear adsorption force. For the left attachment safety margin, the left adsorption force is subtracted from the amount of material distributed on the left side of the photovoltaic cleaning robot by the resultant force of the lateral disturbance component and the lateral inertial force in the lateral direction, and then divided by the left adsorption force. For the right attachment safety margin, the right adsorption force is subtracted from the amount of material distributed on the right side of the photovoltaic cleaning robot by the resultant force of the lateral disturbance component and the lateral inertial force in the lateral direction, and then divided by the right adsorption force.

[0124] The minimum value among the front attachment safety margin, rear attachment safety margin, left attachment safety margin, and right attachment safety margin is determined as the attachment safety margin at the start of the current obstacle crossing cycle.

[0125] S3.2: Determine the obstacle crossing mode category of the current obstacle crossing action cycle through obstacle geometry parameters, and generate initial obstacle crossing control parameters based on the obstacle crossing mode category.

[0126] In this embodiment of the application, the obstacle crossing mode category of the current obstacle crossing action cycle is determined based on the obstacle height, obstacle width and obstacle edge direction in the obstacle geometry parameters. The obstacle crossing mode category includes low obstacle crossing mode, medium height obstacle crossing mode and high obstacle crossing mode, as well as single-sided obstacle crossing mode and double-sided obstacle crossing mode.

[0127] The obstacle crossing modes are as follows: low obstacle crossing mode corresponds to obstacle height less than a first preset height threshold; medium obstacle crossing mode corresponds to obstacle height greater than or equal to the first preset height threshold and less than a second preset height threshold; and tall obstacle crossing mode corresponds to obstacle height greater than or equal to the second preset height threshold. The single-sided obstacle crossing mode corresponds to obstacle width less than the lateral width of the photovoltaic cleaning robot; and the double-sided obstacle crossing mode corresponds to obstacle width greater than or equal to the lateral width of the photovoltaic cleaning robot.

[0128] It should be noted that the first and second preset height thresholds are determined based on statistical values ​​of the height distribution of common obstacles on the surface of photovoltaic modules. Specifically, the first preset height threshold is 1.2 times the smaller of the photovoltaic module frame height and the cable clip height, and the second preset height threshold is 1.5 times the larger of the photovoltaic module frame height and the cable clip height. When the photovoltaic module frame height is 30 mm and the cable clip height is 45 mm, the first preset height threshold is 36 mm and the second preset height threshold is 67.5 mm. When the obstacle height is less than 36 mm, it is classified as a low obstacle crossing mode; when the obstacle height is greater than or equal to 36 mm and less than 67.5 mm, it is classified as a medium-height obstacle crossing mode; and when the obstacle height is greater than or equal to 67.5 mm, it is classified as a high obstacle crossing mode.

[0129] Based on the obstacle-crossing mode category, the system reads the corresponding initial negative pressure chamber pressure adjustment sequence, initial walking unit lifting sequence, initial obstacle-crossing speed, and initial steering angle from the preset obstacle-crossing parameter library as the initial obstacle-crossing control parameters. The preset obstacle-crossing parameter library stores default obstacle-crossing control parameters corresponding to different obstacle-crossing mode categories.

[0130] S3.3: Apply first-level constraints to the initial obstacle crossing control parameters to obtain the first-level obstacle crossing control parameters.

[0131] In this embodiment, the remaining cable lifespan at the start of the current obstacle crossing action cycle, the cable segment identifier corresponding to the remaining cable lifespan, and the action stage identifier corresponding to the remaining cable lifespan are obtained from step S2. Based on the cable segment identifier corresponding to the remaining cable lifespan, the type of the weakest cable segment in the control system cable assembly is determined. The type of the weakest cable segment is any one of a fixed segment, a movable bending segment, or a connecting segment.

[0132] When the weakest cable segment is a movable bending segment, the remaining cable life is determined to be mainly limited by bending and torsional fatigue damage; when the weakest cable segment is a connecting segment, the remaining cable life is determined to be mainly limited by bending and torsion combination and stress damage at the connector tail; when the weakest cable segment is a fixed segment, the remaining cable life is determined to be mainly limited by axial tension and thermal stress damage.

[0133] Based on the action stage identifier corresponding to the remaining life of the cable, determine the target action stage that contributes the most to the remaining life of the cable. The target action stage is any one of the following stages: adsorption stage, turning stage, wheel lifting stage, crossing stage, and reset stage.

[0134] Based on the weakest cable segment type and the target action stage, a first-level constraint is applied to the initial obstacle-crossing control parameters, specifically including: When the weakest cable segment type is an active bending segment and the target action stage is the wheel lifting stage, the remaining cable life is used as the upper limit constraint to reduce the lifting speed corresponding to the initial walking unit lifting sequence in the initial obstacle crossing control parameters, and to set a priority lifting mark for the walking unit that produces the smallest bending radius in the initial walking unit lifting sequence, so as to reduce the peak bending stress borne by the active bending segment in the wheel lifting stage. When the weakest cable segment is an active bending segment and the target action phase is a turning phase, the remaining cable life is used as the upper limit constraint to reduce the angular velocity corresponding to the initial turning angle in the initial obstacle crossing control parameters. A turning limit mark is set for the walking unit that generates the maximum torsion angle in the turning phase in the initial walking unit lifting sequence, so as to reduce the peak torsional shear stress borne by the active bending segment in the turning phase. When the weakest cable segment is a connecting segment and the target action phase is the crossing phase, the remaining cable life is used as the upper limit constraint to reduce the initial obstacle crossing speed in the initial obstacle crossing control parameters and extend the lifting action duration corresponding to the initial walking unit lifting sequence in the initial obstacle crossing control parameters, so as to reduce the bending and torsional combined stress borne by the connecting segment in the crossing phase. When the weakest cable segment is a fixed segment and the target action phase is the adsorption phase or the reset phase, the remaining cable life is used as the upper limit constraint to reduce the rate of change of negative pressure in the negative pressure chamber corresponding to the initial negative pressure chamber pressure adjustment sequence in the initial obstacle crossing control parameters, so as to reduce the axial tensile force fluctuation of the fixed segment in the adsorption phase and the reset phase. After the first level of constraint processing, the first level of obstacle crossing control parameters are obtained.

[0135] S3.4: Apply second-level constraints to the first-level obstacle crossing control parameters using the attached safety margin to obtain the second-level obstacle crossing control parameters.

[0136] In this embodiment, the attachment safety margin at the start of the current obstacle crossing action cycle is obtained from S3.1, and a preset safety margin lower limit value is obtained. The attachment safety margin is then compared with the preset safety margin lower limit value.

[0137] When the adhesion safety margin is greater than or equal to the preset lower limit of the safety margin, the current photovoltaic cleaning robot is determined to be in a high adhesion safety state. The first-level obstacle crossing control parameters remain unchanged and are used as the second-level obstacle crossing control parameters. When the adhesion safety margin is less than the preset lower limit of the safety margin, the current photovoltaic cleaning robot is determined to be in a low adhesion safety state. It is necessary to prioritize ensuring adhesion stability and apply a second-level constraint to the first-level obstacle crossing control parameters. The second-level constraint has a higher priority than the first-level constraint.

[0138] It should be noted that the preset safety margin lower limit is determined based on the minimum adhesion allowance required for the photovoltaic cleaning robot to operate stably on the surface of tilted photovoltaic modules. Specifically, the preset safety margin lower limit is a value between 0.25 and 0.35; preferably, when the tilt angle of the photovoltaic module surface is less than 15°, the preset safety margin lower limit is 0.25; when the tilt angle of the photovoltaic module surface is greater than or equal to 15° and less than 30°, the preset safety margin lower limit is 0.30; and when the tilt angle of the photovoltaic module surface is greater than or equal to 30°, the preset safety margin lower limit is 0.35. When the adhesion safety margin is less than the preset safety margin lower limit, the photovoltaic cleaning robot is determined to be in a low adhesion safety state.

[0139] The second level of constraints specifically includes: reducing the obstacle crossing speed in the first level obstacle crossing control parameters, and recording the reduced obstacle crossing speed as the obstacle crossing speed derating value; increasing the target value of the negative pressure chamber pressure in each negative pressure chamber in the negative pressure chamber pressure adjustment sequence in the first level obstacle crossing control parameters, and recording the increased target value of the negative pressure chamber pressure as the negative pressure chamber pressure compensation value; and extending the time interval between the lifting action of the walking unit that produces the minimum bending radius and the lifting action of other walking units in the lifting sequence of the walking unit in the first level obstacle crossing control parameters, so as to reduce the center of gravity transfer speed of the photovoltaic cleaning robot during the wheel lifting stage.

[0140] After the second level of constraint processing, the second level of obstacle crossing control parameters are obtained.

[0141] S3.5: Based on the obstacle height, obstacle width, obstacle approach distance and obstacle edge direction in the obstacle geometry parameters, apply the third-level constraint to the second-level obstacle crossing control parameters to obtain the obstacle crossing control parameters.

[0142] In this embodiment, the approach time required for the photovoltaic cleaning robot to reach the edge of the obstacle closest to the robot is calculated based on the obstacle approach distance and the obstacle crossing speed derating value or the obstacle crossing speed in the first-level obstacle crossing control parameters. When the approach time is less than a preset lower limit, a pre-pressurization command is added to the negative pressure chamber pressure adjustment sequence in the second-level obstacle crossing control parameters. The pre-pressurization command initiates the negative pressure establishment action corresponding to the negative pressure chamber pressure compensation value before the photovoltaic cleaning robot reaches the edge of the obstacle closest to the robot.

[0143] The heading angle correction for the photovoltaic cleaning robot when crossing obstacles is determined based on the angle between the obstacle edge direction and the lateral direction of the robot's body coordinate system. When the angle is not zero, the heading angle correction is superimposed on the turning angle in the second-level obstacle crossing control parameters to ensure that the forward direction of the photovoltaic cleaning robot is perpendicular to the edge extension direction of the obstacle during the crossing process, thereby reducing the risk of lateral slippage during the crossing process.

[0144] Based on the difference between the obstacle width and the lateral width of the photovoltaic cleaning robot, a grouping and lifting strategy for the walking units during the crossing process is determined. When the obstacle width is less than the lateral width of the photovoltaic cleaning robot, the walking units that overlap with the obstacle are assigned to the first lifting group, and the walking units that do not overlap with the obstacle are assigned to the second lifting group. Different lifting speeds are configured for the first and second lifting groups, with the lifting speed of the first lifting group being greater than that of the second lifting group, in order to shorten the overall crossing time.

[0145] The pressure adjustment sequence of the negative pressure chamber after the third-level constraint treatment, the lifting sequence of the walking unit, the obstacle crossing speed, and the turning angle are used as obstacle crossing control parameters.

[0146] S3.6: Determine the execution priority of obstacle crossing control parameters based on the comparison between the attachment safety margin and the preset safety margin lower limit.

[0147] In this embodiment of the application, each control parameter in the obstacle crossing control parameters is divided into a high-priority control parameter group and a low-priority control parameter group according to its correlation with attachment stability and cable life.

[0148] Control parameters associated with the target value of the negative pressure chamber pressure in the negative pressure chamber pressure adjustment sequence and the lifting speed in the walking unit lifting sequence are classified into the high-priority control parameter group; control parameters associated with the steering angle and obstacle crossing speed are classified into the low-priority control parameter group.

[0149] When the attachment safety margin is less than the preset safety margin lower limit and the remaining cable life is less than the preset life warning value, the execution order of the high priority control parameter group is set to precede the execution order of the low priority control parameter group, and the control parameters corresponding to the target action stage are executed first in the low priority control parameter group.

[0150] When the attachment safety margin is greater than or equal to the preset safety margin lower limit and the remaining cable life is less than the preset life warning value, the execution order of the control parameters corresponding to the target action stage in the low priority control parameter group is set to precede the non-essential control parameters in the high priority control parameter group.

[0151] When the attachment safety margin is greater than or equal to the preset lower safety margin value and the remaining cable life is greater than or equal to the preset life warning value, the control parameters are executed in the order of the obstacle crossing control parameters without adjusting the execution priority.

[0152] It should be noted that the preset lifespan warning value is determined by multiplying the expected lifespan of the control system cable assembly under normal operating conditions by the safety factor, and is pre-stored in the controller of the photovoltaic cleaning robot.

[0153] S3.7: Output the obstacle crossing control parameters and their execution priority to the actuator of the photovoltaic cleaning robot.

[0154] In this embodiment of the application, the negative pressure chamber pressure adjustment sequence, walking unit lifting sequence, obstacle crossing speed and turning angle obtained after the first-level constraint, second-level constraint and third-level constraint processing are used to form obstacle crossing control parameters, and the obstacle crossing control parameters are associated with the execution priority determined in S3.6 and stored.

[0155] According to the execution priority, the obstacle crossing control parameters are arranged into a sequence of control instructions to be executed in chronological order, and the sequence of control instructions is output to the negative pressure chamber, walking unit and steering mechanism of the photovoltaic cleaning robot.

[0156] The control command sequence includes the command output timestamp, control parameter value, and execution sequence number for each control command. The negative pressure chamber adjusts the suction force of each negative pressure chamber according to the pressure adjustment sequence and pressure compensation value. The traveling unit performs lifting and lowering actions according to the lifting sequence and speed. The steering mechanism adjusts the direction of travel based on the steering angle and heading angle correction.

[0157] The obstacle crossing control parameters, execution priority, and control command sequence are used as data inputs in step S4 to control the robot to perform obstacle approach, load transfer, obstacle crossing, and contact recovery in sequence according to the obstacle crossing control parameters. The robot also updates the cumulative cable damage and remaining cable life based on the newly added cable component status data during execution and corrects the obstacle crossing control parameters for the next obstacle crossing cycle.

[0158] S4: Control the photovoltaic cleaning robot to sequentially execute obstacle approach, load transfer, obstacle crossing and contact recovery according to the obstacle crossing control parameters, and update the cumulative cable damage and remaining cable life based on the newly added cable component status data during the execution, and correct the obstacle crossing control parameters for the next obstacle crossing cycle.

[0159] S4.1: Read obstacle crossing control parameters and execution priority, and establish the control execution record for the current obstacle crossing action cycle.

[0160] In this embodiment of the application, the obstacle crossing control parameters, execution priority, and control command sequence output in step S3 are read from the controller of the photovoltaic cleaning robot. The obstacle crossing control parameters include the negative pressure chamber pressure adjustment sequence, the walking unit lifting sequence, the obstacle crossing speed, and the turning angle. The control command sequence includes the command output timestamp, control parameter value, and execution sequence number of each control command.

[0161] Read the obstacle geometry parameters, attachment safety margin, cumulative cable damage, cable remaining life, cable segment identifiers corresponding to the current obstacle crossing action cycle, and corresponding action stage identifiers, and record the reading results as the cycle reference data for the current obstacle crossing action cycle.

[0162] The control command sequence is arranged according to execution priority. The control commands executed during the obstacle approach phase, the control commands corresponding to the turning angle, and the approach walking commands corresponding to the obstacle crossing speed in the negative pressure chamber pressure adjustment sequence are divided into the obstacle approach command group. The control commands used to change the pressure distribution of each negative pressure chamber in the negative pressure chamber pressure adjustment sequence and the initial lifting commands in the walking unit lifting sequence are divided into the load transfer command group. The crossing lifting commands, the crossing walking commands corresponding to the obstacle crossing speed, and the heading maintenance commands corresponding to the turning angle in the walking unit lifting sequence are divided into the obstacle crossing command group. The walking unit descent commands and the pressure recovery commands of each negative pressure chamber are divided into the contact recovery command group.

[0163] Configure execution phase identifiers for the obstacle approach command group, load transfer command group, obstacle crossing command group, and contact recovery command group, and establish control execution records according to the command output timestamps in the control command sequence. The control execution record includes at least the execution phase identifier, control parameter value, execution sequence number, command output timestamp, and corresponding action feedback information.

[0164] S4.2: Control the photovoltaic cleaning robot to perform obstacle approach according to the obstacle approach instruction group, and collect the status data of newly added cable components during the obstacle approach.

[0165] The photovoltaic cleaning robot's direction of travel is adjusted according to the turning angle in the obstacle approach command group, and it moves towards the edge of the obstacle on the side closest to the robot at the obstacle crossing speed; when the obstacle approach command group includes a pre-pressurization command, the pressure of the corresponding negative pressure chamber is adjusted according to the negative pressure chamber pressure adjustment sequence, so that the pressure of the corresponding negative pressure chamber reaches the target pressure value corresponding to the negative pressure chamber pressure compensation value.

[0166] The remaining distance between the front end of the photovoltaic cleaning robot and the edge of the obstacle closest to the robot is continuously calculated based on the obstacle approach distance. The load transfer trigger distance is determined by multiplying the maximum adjustment time required to reach the target pressure value corresponding to the negative pressure chamber (based on the negative pressure chamber pressure compensation value) by the current obstacle-crossing speed. When the obstacle approach distance decreases to the load transfer trigger distance, the increase in the photovoltaic cleaning robot's walking speed stops, and the robot enters the load transfer phase according to the load transfer command group.

[0167] During obstacle approach, the negative pressure chamber pressure, attitude angle, running acceleration, obstacle geometric parameters, bending radius, torsion angle, axial tension, conductor temperature, current and conductor resistance of each cable segment are continuously collected according to the sampling method in step S1. Sampling timestamps and corresponding cable segment identifiers are added to each collection result to form new cable assembly status data during obstacle approach.

[0168] The time interval for adjusting the negative pressure chamber pressure during obstacle approach is configured as the adsorption phase, and the time interval for changing the steering angle is configured as the steering phase; when the adsorption phase and the steering phase overlap, the corresponding action phase identifier is retained according to the instruction output timestamp of each control command.

[0169] S4.3: Adjust the pressure of each negative pressure chamber and the position of each walking unit according to the load transfer command group to transfer the load of the photovoltaic cleaning robot to the support side that has not entered the obstacle area.

[0170] According to the pressure adjustment sequence of the negative pressure chamber, first adjust the negative pressure chamber that does not overlap with the obstacle, and then adjust the negative pressure chamber that overlaps with the obstacle, so that the main attachment load of the photovoltaic cleaning robot is transferred to the side of the negative pressure chamber that has not entered the obstacle area.

[0171] According to the lifting sequence of the walking units, lifting commands are output to the corresponding walking units in sequence. For walking units divided into the first lifting group, lifting is performed according to the lifting speed corresponding to the first lifting group; for walking units divided into the second lifting group, lifting is performed according to the lifting speed corresponding to the second lifting group, while maintaining the action time interval between the first and second lifting groups.

[0172] During the lifting process of each walking unit, the front attachment safety margin, rear attachment safety margin, left attachment safety margin and right attachment safety margin are updated according to the calculation method in step S3.1 based on the real-time collected negative pressure chamber pressure, attitude angle and running acceleration, and the minimum value among them is updated as the real-time attachment safety margin.

[0173] When the real-time attachment safety margin is greater than or equal to the preset safety margin lower limit, and the corresponding walking unit reaches the lifting position specified in the walking unit lifting sequence, the current load transfer state is recorded as a stable load transfer state, and the obstacle crossing stage is entered.

[0174] When the real-time attachment safety margin is less than the preset lower limit of the safety margin, the lifting command of the walking unit that has not yet been executed is suspended, the pressure of the negative pressure chamber that has reached the target pressure value is maintained, and the lifted walking unit is lowered back to the position corresponding to the most recent stable load transfer state; then, the pressure of the negative pressure chamber on the side that has not entered the obstacle area is increased according to the negative pressure chamber pressure adjustment sequence, and the real-time attachment safety margin is recalculated.

[0175] When the real-time attachment safety margin recovers to a value greater than or equal to the preset lower safety margin, the load transfer command group continues to be executed from the stable load transfer state; when the real-time attachment safety margin fails to recover to the preset lower safety margin within the preset attachment recovery time, the current obstacle crossing action cycle is stopped and the current obstacle crossing action cycle is configured as an attachment margin insufficient cycle.

[0176] It should be noted that the preset adhesion recovery time is determined based on the shortest time interval between adjacent pressure adjustment actions in the negative pressure chamber pressure adjustment sequence, and the preset adhesion recovery time is no more than half of the duration of the adsorption stage; preferably, the preset adhesion recovery time is a value between 1 second and 3 seconds, and the specific value is determined based on the negative pressure chamber volume and vacuum pump flow rate of the photovoltaic cleaning robot.

[0177] During load transfer, the status data of newly added cable components are continuously collected, and the time interval between the start of lifting of each walking unit and reaching the corresponding lifting position is configured as the wheel lifting phase.

[0178] S4.4: Control the corresponding walking unit to cross the obstacle according to the obstacle crossing instruction group, and simultaneously determine the attachment status and cable mechanical status.

[0179] Under stable load transfer conditions, the photovoltaic cleaning robot is driven forward according to the obstacle-crossing speed, and the forward direction of the photovoltaic cleaning robot is maintained according to the turning angle and heading angle correction. The lifting position of the corresponding walking unit is maintained according to the lifting sequence of the walking unit, so that the walking unit crosses the edge of the obstacle close to the robot and the edge of the obstacle away from the robot in sequence.

[0180] Based on the obstacle approach distance, obstacle width, obstacle crossing speed, and displacement feedback of each walking unit, the positional relationship of each walking unit relative to the obstacle's edge closer to the robot and the obstacle's edge farther from the robot is determined. When a walking unit in the first lifting group crosses the obstacle's edge farther from the robot, the negative pressure chamber pressure of the corresponding negative pressure chamber in the first lifting group is maintained, and subsequent walking units are driven into the obstacle area according to the lifting sequence of the walking units.

[0181] During obstacle crossing, the real-time attachment safety margin is continuously updated, and the bending radius, torsion angle, axial tension, and conductor temperature corresponding to each cable segment are read. Any of the following conditions is determined as obstacle crossing abort: the real-time attachment safety margin is less than the preset safety margin lower limit, the bending radius is less than the minimum allowable bending radius of the corresponding cable segment, the axial tension is greater than the allowable axial tension of the corresponding cable segment, and the conductor temperature is higher than the allowable conductor temperature of the corresponding cable segment.

[0182] It should be noted that the minimum allowable bending radius is determined based on the specifications of the control system cable assembly, the allowable axial tensile force is determined based on the ratio of the axial tensile strength of the control system cable assembly to the preset safety factor, and the allowable conductor temperature is determined based on the temperature resistance rating of the insulation material of the control system cable assembly, and these values ​​are pre-stored in the controller of the photovoltaic cleaning robot.

[0183] If no obstacle crossing termination condition is encountered, continue executing the obstacle crossing command group; if an obstacle crossing termination condition is encountered, stop increasing the forward displacement of the photovoltaic cleaning robot, maintain the negative pressure chamber pressure on the side that has not entered the obstacle area, and lower the corresponding walking unit in the reverse order of the lifting sequence of the walking unit, so that the photovoltaic cleaning robot returns to the most recent stable load transfer state.

[0184] When the obstacle crossing abort condition disappears after returning to the stable load transfer state, the current obstacle crossing speed is reduced, and the obstacle crossing command group is re-executed at the reduced obstacle crossing speed; when the obstacle crossing abort condition does not disappear, the current obstacle crossing action cycle is stopped, and the reason for obstacle crossing abort is recorded according to the cable segment identifier and parameter type corresponding to the obstacle crossing abort condition.

[0185] After the stable load transfer state, the time interval between when each walking unit begins to cross the obstacle and approaches the edge of the robot and when each walking unit crosses the obstacle and moves away from the edge of the robot is configured as the crossing phase, and the newly added cable component status data during the crossing phase is continuously collected.

[0186] S4.5: Control each walking unit to restore contact according to the contact restoration command group, and adjust the pressure of each negative pressure chamber to the pressure range corresponding to the stable walking state.

[0187] Once each walking unit has passed the obstacle and moved away from the edge of the robot, the contact recovery instruction group sequentially outputs a fall command to each walking unit, causing each walking unit to move toward the photovoltaic module surface in a fall sequence corresponding to the lifting sequence of the walking units.

[0188] Based on the position feedback of each walking unit, it is determined whether the corresponding walking unit has reached a stable walking position. Based on the change of the normal component of the running acceleration of the corresponding walking unit before and after contacting the photovoltaic module surface and the change of the negative pressure chamber pressure of the corresponding negative pressure chamber, the contact recovery state of the corresponding walking unit is determined.

[0189] When the corresponding walking unit reaches a stable walking position and the pressure of the corresponding negative pressure chamber enters the stable range before overcoming the obstacle, the corresponding walking unit is recorded as having completed contact recovery; when the pressure of the corresponding negative pressure chamber does not enter the stable range before overcoming the obstacle, the photovoltaic cleaning robot remains in a stopped walking state, and the pressure of the corresponding negative pressure chamber continues to be adjusted according to the pressure adjustment sequence of the negative pressure chamber.

[0190] After each walking unit completes contact restoration, the pressure compensation value of the negative pressure chamber is gradually cancelled according to the pressure adjustment sequence of the negative pressure chamber, so that the pressure of each negative pressure chamber is restored to the stable range before overcoming the obstacle. The photovoltaic cleaning robot is then judged to have returned to a stable walking state based on the attitude angle and running acceleration.

[0191] When the negative pressure chamber pressure, attitude angle, and running acceleration all enter the corresponding pre-obstacle stability range, the current moment is determined as the end moment of the current obstacle crossing action cycle; the time interval between the start of each walking unit's descent and the end moment is configured as the reset phase, and new cable assembly status data is generated during the contact recovery phase.

[0192] S4.6: Organize the status data of newly added cable components in the current obstacle crossing action cycle according to the action stage identifier, and calculate the current cycle damage increment of each cable segment.

[0193] Added cable assembly status data during the obstacle approach phase, load transfer phase, obstacle crossing phase, and contact recovery phase, and write them into the data record of the current obstacle crossing action cycle according to the sampling timestamp, cable segment identifier, and action phase identifier.

[0194] Specifically, the cable component status data added during the obstacle approach phase is classified into the adsorption phase and the turning phase according to the control command type; the cable component status data added during the load transfer phase is classified into the wheel lifting phase; the cable component status data added during the obstacle crossing phase is classified into the crossing phase; and the cable component status data added during the contact recovery phase is classified into the reset phase.

[0195] The newly added cable component status data in the current obstacle crossing action cycle is processed according to the time alignment method in step S2.2. For sampling records with asynchronous markers, the corresponding sampling records are not used to construct the multi-stress state at the same time. For sampling records where the conductor resistance measurement state is a state to be supplemented, the corresponding mechanical state parameters and electrothermal state parameters are retained, and the corresponding conductor resistance is not used for damage correction for the time being.

[0196] Based on the calculation methods in steps S2.3 and S2.4, update the mechanical stress sequence, thermal stress sequence, and electrical load sequence of each cable segment respectively; based on the cycle counting and cumulative damage calculation methods in step S2.6, calculate the periodic model damage of each cable segment in the current obstacle crossing action cycle, and calculate the stage model damage corresponding to the adsorption stage, turning stage, wheel lifting stage, crossing stage, and reset stage according to the action stage identifier.

[0197] The periodic model damage amount of the current obstacle crossing action cycle is used as the current periodic damage increment of the corresponding cable segment, and the maximum value in the stage model damage amount and the action stage identifier corresponding to the maximum value are recorded.

[0198] For obstacle crossing cycles marked as insufficient attachment margin cycles or obstacle crossing cycles that have encountered obstacle crossing termination conditions, the damage increment of the current cycle is still calculated based on the cable assembly status data added before the stopping time, and an incomplete cycle marker is added to the data record of the current obstacle crossing cycle.

[0199] S4.7: Update the cumulative damage of each cable segment based on the conductor resistance change during the current obstacle crossing cycle, and update the cumulative cable damage and remaining cable life.

[0200] According to the temperature correction method in step S2.7, the conductor resistance of each cable segment in the current obstacle crossing action cycle is converted to the conductor resistance reference temperature to obtain the temperature-corrected conductor resistance corresponding to the current obstacle crossing action cycle, and the relative change in conductor resistance is updated according to the temperature-corrected conductor resistance and the corresponding reference conductor resistance.

[0201] The resistance-based damage value of the corresponding cable segment is updated based on the correlation between the relative change in conductor resistance and resistance damage. When the updated resistance-based damage value is greater than the cumulative damage value of the corresponding cable segment, the cumulative damage value of the corresponding cable segment is increased based on the resistance-based damage value; when the updated resistance-based damage value is less than or equal to the cumulative damage value of the corresponding cable segment, the cumulative damage value of the corresponding cable segment is retained, resulting in the updated cumulative damage value of the cable segment.

[0202] When there are sampling records in the current obstacle crossing action cycle where the conductor resistance measurement status is pending, the resistance characterization damage amount is not updated according to the corresponding sampling record. When the corresponding supplementary conductor resistance is obtained later, the supplementary conductor resistance is written into the corresponding sampling record, and the resistance characterization damage amount and the cumulative damage amount of the corresponding cable segment are updated again.

[0203] The maximum value in the updated cumulative damage of each cable segment is updated to the cumulative damage of the control system cable assembly, and the cable segment identifier corresponding to the updated cumulative damage is recorded.

[0204] The average periodic damage increment of each cable segment is updated based on the current periodic damage increment of each cable segment in the most recent obstacle crossing action cycles. The remaining number of obstacle crossing action cycles for each cable segment is recalculated based on the preset damage failure threshold, the updated cumulative damage of the cable segment, and the updated average periodic damage increment.

[0205] The minimum value among the remaining obstacle crossing action cycles is updated to the remaining cable lifespan, and the cable segment identifier corresponding to the updated remaining cable lifespan and the action stage identifier with the largest stage model damage in the current obstacle crossing action cycle are recorded.

[0206] S4.8: Based on the current cycle damage increment, real-time attachment safety margin, and obstacle crossing termination reason, adjust the obstacle crossing control parameters for the next obstacle crossing cycle.

[0207] The damage deviation for the current obstacle-crossing action cycle is determined by the difference between the current cycle damage increment of each cable segment and the average cycle damage increment of the corresponding cable segment. When the current cycle damage increment is greater than the average cycle damage increment, and the difference between the two is greater than a preset damage deviation threshold, the corresponding cable segment is recorded as the cable segment to be reduced in damage, and the action stage with the largest damage in the stage model is marked as the action stage to be corrected.

[0208] It should be noted that the preset damage deviation threshold is determined based on the fluctuation range of the current cycle damage increment of the most recent completed obstacle crossing action cycles under the same obstacle crossing mode category. The preset damage deviation threshold is a value between 1.5 times and 2 times the standard deviation of the current cycle damage increment. When the number of the most recent completed obstacle crossing action cycles is less than the preset number, the preset damage deviation threshold is 20% of the average cycle damage increment.

[0209] When the cable segment to be reduced is a flexible bending segment, and the correction action stage is the wheel lifting stage, extend the lifting time interval between the walking unit that produces the smallest bending radius and the adjacent walking unit in the next obstacle crossing cycle, and reduce the lifting speed of the corresponding walking unit to correct the lifting sequence of the walking units in the next obstacle crossing cycle.

[0210] When the cable segment to be reduced is a flexible bending segment and the correction action phase is a turning phase, reduce the turning angle executed in a single step in the next obstacle crossing cycle, and allocate the remaining turning angle to multiple turning actions in the obstacle approach phase.

[0211] When the cable to be reduced is segmented into connecting segments and the correction action phase is a crossing phase, reduce the obstacle crossing speed of the next obstacle crossing cycle and extend the time interval for the corresponding walking unit to maintain the raised position, thereby correcting the obstacle crossing speed and the lifting sequence of the walking unit in the next obstacle crossing cycle.

[0212] When the cable to be reduced is segmented into fixed segments and the correction action is in the adsorption or reset stage, the time interval between adjacent negative pressure chamber pressure adjustment actions is extended, and the negative pressure chamber pressure adjustment sequence of the next obstacle crossing cycle is rearranged in the order from the side that has not entered the obstacle area to the side that has entered the obstacle area.

[0213] When the current obstacle crossing cycle has an insufficient adhesion margin cycle or the obstacle crossing is stopped because the real-time adhesion safety margin is less than the preset safety margin lower limit, the target value of the negative pressure chamber pressure on the side that has not entered the obstacle area in the next obstacle crossing cycle is increased first, the obstacle crossing speed is reduced, and the time interval between the lifting actions of adjacent walking units is extended; the parameter correction priority corresponding to the adhesion safety margin is higher than the parameter correction priority corresponding to the remaining life of the cable.

[0214] When obstacle crossing is aborted due to a bending radius less than the minimum permissible bending radius, an axial tensile force greater than the permissible axial tensile force, or a conductor temperature higher than the permissible conductor temperature, the negative pressure chamber pressure adjustment sequence, walking unit lifting sequence, obstacle crossing speed, or turning angle related to the corresponding action stage in the next obstacle crossing cycle are derating adjusted according to the corresponding cable segment identification and action stage identification.

[0215] The corrected negative pressure chamber pressure adjustment sequence, walking unit lifting sequence, obstacle crossing speed, and turning angle are used to form the obstacle crossing control parameters for the next obstacle crossing cycle. The obstacle crossing control parameters for the next obstacle crossing cycle are written into the corresponding parameter records in the preset obstacle crossing parameter library according to the obstacle crossing mode category corresponding to obstacle height, obstacle width, and obstacle edge direction.

[0216] Therefore, the changes in attachment status, the incremental damage from multiple stress fields in each cable segment, and the changes in conductor resistance generated during the current obstacle crossing cycle are all fed back to the obstacle crossing control parameters of the next obstacle crossing cycle, so that subsequent obstacle crossing actions under the same or similar obstacle conditions are adjusted according to the updated cable life status and attachment status.

[0217] In summary, this invention, by collecting operational status parameters of the photovoltaic cleaning robot and multi-dimensional status parameters of the control system's cable assemblies, and by managing the cable assemblies in segments, achieves synchronous perception of the robot's operational status and the cable's stress state. This provides an accurate data foundation for subsequent life assessment and obstacle-crossing control, improving the comprehensiveness of status perception under complex working conditions. By constructing sequences of cable mechanical stress, thermal stress, and electrical loads, and dynamically correcting the multi-stress field life model in conjunction with conductor resistance changes, accurate assessment of cable cumulative damage and remaining life is achieved. This ensures that life prediction truly reflects the cable's service status, providing a basis for control strategy optimization and preventative maintenance, and improving cable operational reliability. By using the attachment safety margin, obstacle geometry parameters, and cable remaining life as joint constraints, obstacle-crossing control parameters are generated, achieving coordinated optimization of attachment capability, obstacle-crossing performance, and cable life. This enables the robot to adaptively adjust its obstacle-crossing strategy for different obstacles and working conditions, reducing cable stress damage while ensuring attachment stability and improving the obstacle-crossing success rate under complex working conditions. By continuously updating the cumulative cable damage and remaining life based on the real-time status during obstacle-crossing execution and correcting the control parameters for the next obstacle-crossing cycle, closed-loop optimization of the obstacle-crossing control strategy is achieved. This allows the control parameters to be dynamically adjusted according to the equipment status, further improving the robot's safety, stability, and environmental adaptability during long-term continuous operation.

[0218] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An adaptive attachment and obstacle-crossing control method for a photovoltaic cleaning robot under complex working conditions, characterized in that, include: The negative pressure chamber pressure, attitude angle, running acceleration, obstacle geometry parameters, bending radius, torsion angle, axial tension, conductor temperature, current and conductor resistance of the control system cable assembly are obtained. The control system cable assembly is divided into fixed section, movable bending section and connection section to form cable assembly status data. Align the cable assembly status data according to the action sequence of adsorption, turning, lifting wheel, crossing and resetting, construct the mechanical stress sequence, thermal stress sequence and electrical load sequence of each cable segment, and correct the multi-stress field life model according to the change of conductor resistance to calculate the cumulative damage and remaining life of the cable. The attachment safety margin is calculated based on the negative pressure chamber pressure, the attitude angle, and the running acceleration. The obstacle geometry parameters, the remaining cable life, and the attachment safety margin are used together as constraints to determine the negative pressure chamber pressure adjustment sequence, the walking unit lifting sequence, the obstacle crossing speed, and the turning angle, thus forming obstacle crossing control parameters. The photovoltaic cleaning robot is controlled to sequentially execute obstacle approach, load transfer, obstacle crossing and contact recovery according to the obstacle crossing control parameters. The cumulative damage and remaining life of the cable are updated based on the newly added cable component status data during the execution, and the obstacle crossing control parameters for the next obstacle crossing cycle are corrected.

2. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 1, characterized in that, The formation of the obstacle crossing control parameters includes: The attachment safety margin at the start of the current obstacle crossing action cycle is calculated based on the negative pressure chamber pressure, attitude angle, and running acceleration. The obstacle crossing mode category of the current obstacle crossing action cycle is determined by the obstacle geometry parameters, and initial obstacle crossing control parameters are generated based on the obstacle crossing mode category. The initial obstacle crossing control parameters are subjected to first-level constraints to obtain first-level obstacle crossing control parameters; The first-level obstacle crossing control parameters are constrained by the attachment safety margin to obtain the second-level obstacle crossing control parameters. Based on the obstacle height, obstacle width, obstacle approach distance, and obstacle edge direction in the obstacle geometry parameters, a third-level constraint is applied to the second-level obstacle crossing control parameters to obtain the obstacle crossing control parameters.

3. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 2, characterized in that, The obstacle crossing modes include low obstacle crossing modes, medium-height obstacle crossing modes, and high obstacle crossing modes, as well as single-sided obstacle crossing modes and double-sided obstacle crossing modes.

4. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 3, characterized in that, The first level of constraints includes: When the weakest cable segment type is an active bending segment and the target action stage is the wheel lifting stage, the remaining cable life is used as the upper limit constraint to reduce the lifting speed corresponding to the initial walking unit lifting sequence in the initial obstacle crossing control parameters, and a priority lifting mark is set for the walking unit that produces the smallest bending radius in the initial walking unit lifting sequence, so as to reduce the peak bending stress borne by the active bending segment in the wheel lifting stage. When the weakest cable segment type is the active bending segment and the target action stage is the turning stage, the remaining lifespan of the cable is used as the upper limit constraint to reduce the angular velocity corresponding to the initial turning angle in the initial obstacle crossing control parameters, and a turning limit mark is set for the walking unit that generates the maximum torsion angle in the turning stage in the initial walking unit lifting sequence, so as to reduce the peak torsional shear stress borne by the active bending segment in the turning stage. When the weakest cable segment is a connecting segment and the target action phase is a crossing phase, the remaining lifespan of the cable is used as an upper limit constraint to reduce the initial obstacle crossing speed in the initial obstacle crossing control parameters and extend the lifting action duration corresponding to the initial walking unit lifting sequence in the initial obstacle crossing control parameters, so as to reduce the bending and torsional combined stress borne by the connecting segment in the crossing phase. When the weakest cable segment type is the fixed segment and the target action stage is the adsorption stage or the reset stage, the remaining lifespan of the cable is used as the upper limit constraint to reduce the rate of change of the negative pressure chamber pressure corresponding to the initial negative pressure chamber pressure adjustment sequence in the initial obstacle crossing control parameters, so as to reduce the axial tensile force fluctuation borne by the fixed segment in the adsorption stage and the reset stage.

5. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 4, characterized in that, The weakest cable segment type is any one of the following: fixed segment, movable bending segment, or connecting segment; the target action stage is any one of the following: adsorption stage, turning stage, wheel lifting stage, crossing stage, and reset stage.

6. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 2, characterized in that, The second level of constraints includes: The obstacle crossing speed in the first-level obstacle crossing control parameters is reduced, and the reduced obstacle crossing speed is recorded as the obstacle crossing speed derating value; the target value of the negative pressure chamber pressure in each negative pressure chamber in the negative pressure chamber pressure adjustment sequence in the first-level obstacle crossing control parameters is increased, and the increased target value of the negative pressure chamber pressure is recorded as the negative pressure chamber pressure compensation value; the time interval between the lifting action of the walking unit that produces the smallest bending radius and the lifting action of other walking units in the lifting sequence of the walking unit in the first-level obstacle crossing control parameters is extended, so as to reduce the center of gravity transfer speed of the photovoltaic cleaning robot in the wheel lifting stage.

7. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 2, characterized in that, The third-level constraint includes: Based on the obstacle approach distance and the obstacle crossing speed derating value or the obstacle crossing speed in the first-level obstacle crossing control parameters, calculate the approach time required for the photovoltaic cleaning robot to reach the edge of the obstacle near the robot's side; when the approach time is less than the preset approach time lower limit, add a pre-pressurization command to the negative pressure chamber pressure adjustment sequence in the second-level obstacle crossing control parameters. The heading angle correction of the photovoltaic cleaning robot when crossing obstacles is determined based on the angle between the direction of the obstacle edge and the lateral direction of the photovoltaic cleaning robot's body coordinate system. Based on the difference between the obstacle width and the lateral width of the photovoltaic cleaning robot, a group lifting strategy for the walking units of the photovoltaic cleaning robot during the crossing process is determined.

8. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 7, characterized in that, The pre-pressurization command initiates the negative pressure establishment action corresponding to the negative pressure compensation value of the negative pressure chamber before the photovoltaic cleaning robot reaches the edge of the obstacle near the robot's side.

9. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 1, characterized in that, The cumulative damage to the cable and the remaining lifespan of the cable include: The cumulative damage of the multi-stress field life model is calculated based on the mechanical stress sequence, thermal stress sequence, and electrical load sequence. The cumulative damage amount of the multi-stress field life model is corrected based on the change in conductor resistance to obtain the cumulative damage amount of cable segments. The cumulative damage to the cable and the remaining lifespan of the cable are calculated based on the cumulative damage to each cable segment.

10. The adaptive attachment and obstacle-crossing control method for photovoltaic cleaning robots under complex working conditions as described in claim 9, characterized in that, The multi-stress field life model is constructed based on accelerated life test data of control system cable assemblies.

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