Operation control method and system for flaw detection maintenance robot

Abstract

The invention discloses an operation control method and system for a flaw detection maintenance robot, and relates to the technical field of photovoltaic power station operation and maintenance. The method comprises the following steps: importing a GIS map of a photovoltaic station into a target robot, planning an inspection path, and driving the target robot to move; when the target robot moves to the station area, controlling directional unfolding of the mechanical arm in a preset unfolding posture, triggering a multi-modal flaw detection module integrated at the tail end of the mechanical arm, executing concurrent detection under multi-modal orientation, and determining a detection signal set; and returning a detection signal set, carrying out signal distribution updating along with the detection process, and determining a flaw detection sheet and sending the flaw detection sheet to the operation and maintenance mobile terminal for alarming by executing modal independent detection and multi-modal spatial distribution fusion. The technical problem of low inspection efficiency of the photovoltaic power station under the complex terrain in the prior art is solved, and the technical effect of improving the inspection efficiency of the photovoltaic power station is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power station operation and maintenance, and in particular to an operation control method and system for a flaw detection and maintenance robot. Background Art

[0002] Photovoltaic power stations are exposed to complex outdoor environments for extended periods, subject to weathering and mechanical vibration. Structural defects such as pile corrosion and truss cracks frequently occur, posing a serious threat to the safe operation of the power stations. However, the current operation and maintenance of photovoltaic power stations faces numerous technical bottlenecks, severely hindering improvements in efficiency and quality. While traditional wheeled or tracked robots are used in some scenarios, their design limitations typically result in ground clearances of less than 10 cm and obstacle clearance capabilities below 15 cm. This makes them inadequate for complex terrain, such as gaps between photovoltaic panel supports and gravel terrain. This results in nearly half of the station area becoming inspection "blind spots," preventing comprehensive and effective coverage. During flaw detection operations, the conflict between the narrow clearance beneath photovoltaic panels and the rigid mounting method of the robotic arm has become increasingly prominent. During operation, the robotic arm is prone to collision with the photovoltaic panels, potentially damaging them and hindering the proper performance of flaw detection. At the same time, existing flaw detection equipment is highly dependent on manual measurement, which is not only inefficient but also greatly affected by human factors. The missed detection rate remains high and it is difficult to meet the power station's demand for precise flaw detection. Summary of the Invention

[0003] The present application provides an operation control method and system for a flaw detection and maintenance robot, which solves the technical problem of low inspection efficiency of photovoltaic power stations in complex terrain in the prior art.

[0004] In a first aspect of the present application, a method for controlling an operation of a flaw detection and maintenance robot is provided, the method comprising:

[0005] The GIS map of the photovoltaic station is imported into the target robot, the inspection route is planned, and the target robot is driven to move, wherein the target robot is equipped with a triangular crawler chassis, and the crawler inclination angle is adaptively adjusted in the second order according to the track terrain; when the target robot moves to the station area, it controls the directional deployment of the robotic arm with a preset deployment posture, triggers the multimodal flaw detection module integrated at the end of the robotic arm, performs concurrent detection under multimodal orientation, and determines the detection signal set, wherein the detection signal set is identified by a time-space code; the detection signal set is transmitted back, and the signal distribution is updated as the detection process progresses. By performing modal independent detection and multimodal spatial distribution fusion, the flaw detection inspection order is determined and sent to the operation and maintenance mobile terminal for alarm.

[0006] A second aspect of the present application provides an operation control system for a flaw detection and maintenance robot, the system comprising:

[0007] The mobile component is used to import the photovoltaic station GIS map into the target robot, plan the inspection path, and drive the target robot to move, wherein the target robot is equipped with a triangular crawler chassis, and the crawler inclination angle is adaptively adjusted according to the track terrain for second-order equal position; the detection component is used to control the directional deployment of the robotic arm with a preset deployment posture when the target robot moves to the station area, trigger the multi-modal flaw detection module integrated at the end of the robotic arm, perform concurrent detection under multi-modal orientation, and determine the detection signal set, wherein the detection signal set is identified by a time-space code; the alarm component is used to transmit the detection signal set back, update the signal distribution as the detection process progresses, and determine the flaw detection inspection order by performing modal independent detection and multi-modal spatial distribution fusion and send it to the operation and maintenance mobile terminal for alarm.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The GIS map of the photovoltaic station is imported into the target robot, and the inspection route is planned to drive the target robot to move. The target robot is equipped with a triangular crawler chassis, and the crawler inclination angle is adaptively adjusted according to the track terrain in the second order. When the target robot moves to the station area, it controls the directional deployment of the robotic arm in a preset deployment posture, triggering the multimodal flaw detection module integrated at the end of the robotic arm, performing concurrent detection under multimodal orientation, and determining the detection signal set, wherein the detection signal set is identified by a time-space code. The detection signal set is transmitted back, and the signal distribution is updated as the detection progresses. By performing modal independent detection and multimodal spatial distribution fusion, the flaw detection inspection order is determined and sent to the operation and maintenance mobile terminal for alarm. This solves the technical problem of low inspection efficiency of photovoltaic power stations in complex terrain in the existing technology, and achieves the technical effect of improving the inspection efficiency of photovoltaic power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic flow chart of an operation control method for a flaw detection and maintenance robot provided in an embodiment of the present application;

[0012] Figure 2 A schematic diagram of the structure of an operation control system for a flaw detection and maintenance robot provided in an embodiment of the present application.

[0013] Description of the reference numerals: moving component 11 , detecting component 12 , alarm component 13 . DETAILED DESCRIPTION

[0014] The present application solves the technical problem of low inspection efficiency of photovoltaic power stations in complex terrain in the prior art by providing an operation control method and system for a flaw detection and maintenance robot.

[0015] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0016] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0017] Example 1, as Figure 1 As shown, the present application provides an operation control method for a flaw detection and maintenance robot, wherein the method includes:

[0018] The photovoltaic station GIS map is imported into the target robot, the inspection path is planned, and the target robot is driven to move. The target robot is equipped with a triangular track chassis, and the track inclination angle is adaptively adjusted according to the track terrain in the second order.

[0019] By importing the GIS map of the photovoltaic site into the target robot, the system can plan the inspection route according to the geographic information of the site and drive the target robot to move along the preset path.

[0020] The target robot is equipped with a triangular track chassis designed to improve its maneuverability and stability, making it particularly suitable for complex and uneven terrain. The target robot utilizes adaptive track inclination technology, adjusting the track angle in real time to adapt to varying terrain.

[0021] Track inclination is adjusted using a second-order equal-position adjustment method. When changes in the track terrain are detected, the system adaptively adjusts the track's inclination. Specifically, the system first determines the path's slope and terrain undulations, performs preliminary inclination adjustments using first-order adjustment, and then fine-tunes the track using second-order adjustment. This ensures the robot remains stable during travel, preventing tilting or slipping, and improving the efficiency and safety of inspection tasks.

[0022] When the robot travels over uneven terrain, the system independently adjusts the inclination of its two tracks, allowing each track to adapt to the undulations of the ground where it is located. These adjustments maintain the robot on a stable horizontal plane, ensuring balance and stability during movement. The inclination of each track is adjustable (0-30°), and coupled with a differential steering algorithm, it can adapt to gravel and muddy roads with slopes of ≤40°, with a minimum turning radius of ≤0.5m.

[0023] Furthermore, the robotic arm is a multi-degree-of-freedom folding arm, which can be stored in the internal structure of the robot. A multi-modal flaw detection module is integrated at the end of the robotic arm, wherein the front-end components of the multi-modal flaw detection module include at least an ultrasonic flaw detector, an electromagnetic eddy current sensor, and an infrared thermal imager.

[0024] The robotic arm features multiple degrees of freedom, folding arms with high flexibility and adjustability, enabling it to perform complex tasks. Its retractable design allows it to be stored within the robot's internal structure when not in use, optimizing space usage and protecting it from external damage. When the robot needs to perform inspection tasks, the arm can be deployed from its retracted state and positioned appropriately for the task.

[0025] The end of the robotic arm is integrated with a multi-modal flaw detection module, which is designed to enable it to perform multiple flaw detection technologies in the same working cycle, increasing the comprehensiveness and accuracy of the detection. Specifically, the front-end components of the multi-modal flaw detection module include at least an ultrasonic flaw detector, an electromagnetic eddy current sensor, and an infrared thermal imager. The ultrasonic flaw detector is mainly used to detect internal cracks in the foundation pile (accuracy ±0.1mm), and the electromagnetic eddy current sensor is used to identify rust on the surface of the truss (resolution 0.5mm). 2 ), while infrared thermal imagers can provide temperature distribution maps and monitor overheating of electrical connection points (temperature sensitivity 0.1°C).

[0026] Furthermore, the ultrasonic flaw detector uses the foundation pile as the scanning target and the scanning method is along the axial direction of the foundation pile; the electromagnetic eddy current sensor uses the truss surface as the scanning target and the grid detection with a preset grid spacing as the scanning method; the infrared thermal imager uses the electrical junction box as the scanning target and the wiring panoramic view as the scanning method.

[0027] Ultrasonic flaw detectors, electromagnetic eddy current sensors, and infrared thermal imagers each employ different scanning methods to comprehensively inspect photovoltaic station equipment. Specifically, the ultrasonic flaw detector scans the foundation piles along their axial direction, with a set frequency of 2.5MHz and a step accuracy of 1mm. By emitting high-frequency sound waves and receiving the reflected signals, the ultrasonic flaw detector can detect defects such as cracks or voids within the foundation piles, ensuring their structural integrity. The electromagnetic eddy current sensor scans the truss surface using a grid-based detection method with a preset grid spacing (5mm). The electromagnetic eddy current sensor uses the principle of electromagnetic induction to detect surface and near-surface defects in conductive materials. Its grid-based scanning method covers every location on the truss surface, ensuring comprehensive detection of potential cracks, corrosion, or other surface defects. The infrared thermal imager scans the electrical junction box using a panoramic wiring scan method, capturing panoramic thermal images (at a frame rate of 30Hz) to identify overheating anomalies. Infrared thermal imagers detect overheating or faults by detecting thermal radiation from electrical junction boxes. Thermal imaging technology can provide real-time visualization of the junction box's temperature distribution, promptly identifying hotspots caused by short circuits, poor contact, or excessive loads. Panoramic wiring scanning ensures efficient thermal imaging of the entire junction box surface, accurately identifying potential temperature anomalies.

[0028] Using three different flaw detection technologies, the robot can conduct comprehensive and efficient inspections of foundation piles, truss surfaces, and electrical junction boxes in photovoltaic stations, promptly identifying potential structural problems or equipment failures and improving the safety and reliability of operations and maintenance.

[0029] Furthermore, before the track inclination angle is adaptively adjusted according to the track terrain for the second-order isotropic adjustment, an isotropic adjustment module is constructed, including:

[0030] The first undulation inclination angle based on the road condition characteristics is used as the first-order control target, and the first-order nodes are deployed; the inclination angle variables of the upper control node and the lower control node are used as the second-order control targets, and the second-order nodes are deployed; the first-order nodes and the second-order nodes are sequentially cascaded to determine the equal-order adjustment module.

[0031] Before the track inclination angle is adaptively adjusted according to the trajectory terrain for the second-order isotropic adjustment, an isotropic adjustment module is constructed to accurately adjust the track inclination angle according to the terrain characteristics of the photovoltaic station, thereby ensuring the target robot's stable movement and efficient inspection in complex terrain.

[0032] Specifically, based on the road conditions of the photovoltaic station, the first undulation inclination angle is set as the first-order control target. The first undulation inclination angle represents the initial inclination angle that needs to be adjusted on uneven terrain to adapt to the undulating changes in the terrain. The first-order control target calculates the appropriate initial inclination adjustment value by analyzing factors such as the slope of the path and the undulation of the terrain to ensure that the track can move smoothly and remain stable. According to the set first-order control target, the system deploys the first-order node to control the inclination angle of the track.

[0033] Based on the first-order adjustments, the tilt angle variables of the upper and lower control nodes serve as second-order control targets. This second-order target is used to eliminate tilt problems caused by minor errors or uneven terrain during the first-order control process. Based on this second-order target, the system deploys second-order nodes for more precise track adjustments. These second-order nodes precisely control the track adjustments, ensuring the robot's stability and maneuverability in complex terrain, and preventing minor imbalances that could cause the robot to tilt or slip.

[0034] By sequentially cascading first-order and second-order nodes, an isotropic adjustment module is constructed. Based on this module, the system can dynamically adapt to terrain changes along the path, adjusting the track's inclination angle in real time during travel to ensure the robot maintains stable operation.

[0035] Furthermore, the flaw detection and maintenance robot includes independently driven first and second tracks; the isostatic adjustment module is deployed at the first control end of the first track and the second control end of the second track, and synchronization timestamp constraints are established between the first and second control ends. The flaw detection and maintenance robot includes independently driven first and second tracks, and the two tracks can be independently controlled and driven to adapt to different terrains and movement requirements.

[0036] During robot movement, the track's inclination needs to be precisely controlled based on the terrain's undulations. Therefore, an isotropic adjustment module is deployed at the first control terminal of the first track and the second control terminal of the second track. This allows the inclination of the first and second tracks to be independently adjusted based on their respective terrain conditions, ensuring the robot remains stable during travel and adapting to complex terrain.

[0037] To ensure coordination and synchronization between the two tracks, the system establishes a synchronization timestamp constraint between the first and second control terminals. This ensures that the inclination adjustment of the two tracks is synchronized according to the same time step, preventing the robot from becoming unbalanced or tilting due to asynchronous adjustment during movement. This timestamp constraint enables the system to precisely control the movement of the two tracks, ensuring stability and efficiency in complex terrain, and improving the performance and accuracy of the flaw detection and maintenance robot.

[0038] Furthermore, the track inclination angle is adaptively adjusted according to the track terrain in a second-order isotropic manner, including:

[0039] As the vehicle moves based on the inspection path, the real-time path conditions are determined; based on the real-time path conditions, the equal-position adjustment module deployed at the first control end executes a first-order inclination decision based on the road condition fluctuation characteristics to determine the first-order road condition inclination; the upper track inclination of the upper control node is retrieved, and the difference between the first-order road condition inclination and the upper track inclination is calculated as the second-order adjustment inclination; based on the second-order adjustment inclination, the first track is driven to perform track inclination control.

[0040] Preferably, as the robot moves along the inspection path, the system determines the path conditions in real time based on the data fed back by the sensors, and analyzes the undulations and slope changes of the terrain; based on the real-time path conditions, the equal-position adjustment module deployed at the first control end executes a first-order inclination decision based on the road condition undulation characteristics, and determines the first-order road condition inclination for preliminary matching of the terrain undulations, that is, according to the path ground characteristics, such as slope and height difference, calculates a suitable preliminary inclination adjustment value; after the first-order inclination decision is completed, the system calls the upper track inclination of the upper control node, calculates the difference between the first-order road condition inclination and the upper track inclination, and obtains the second-order adjustment inclination for further fine adjustment; finally, according to the second-order adjustment inclination, the first track is driven to perform inclination control to achieve precise adjustment of the track posture, thereby ensuring that the robot can maintain overall balance and stability in complex terrain, and improving the continuity and safety of the inspection operation.

[0041] When the target robot moves to the station area, it controls the directional deployment of the robotic arm in a preset deployment posture, triggers the multimodal flaw detection module integrated at the end of the robotic arm, performs concurrent detection under multimodal orientation, and determines the detection signal set, wherein the detection signal set is identified by a time-space code.

[0042] Once the target robot moves to the designated inspection area of ​​the photovoltaic plant, the system controls the robot to assume a preset deployment posture and prepare for operation. This preset deployment posture is the initial parameter for the robot arm's deployment, set based on the plant's inspection mission requirements, ensuring rapid deployment of the robot arm in the optimal position. The control system then drives the robot arm to deploy in a targeted manner. The robot arm performs multi-degree-of-freedom adjustments based on the target inspection position and posture commands, allowing the end-of-line flaw detection module to accurately position itself toward the inspection target. Upon deployment, the multimodal flaw detection module integrated into the end-of-line flaw detection module is triggered and activated. The module's various built-in flaw detection sensors (such as ultrasonic flaw detectors, electromagnetic eddy current sensors, and infrared thermal imagers) are synchronously activated, performing concurrent detection operations in accordance with the multimodal orientation requirements. Concurrent detection under multimodal orientation enables the parallel collection of multi-dimensional detection information from different sensors, improving detection efficiency and comprehensiveness. During the detection process, various detection signals are collected to form a detection signal set. Each data item in the signal set is associated with a unique space-time code, which identifies the spatial location and timestamp of the detection data acquisition, ensuring the accuracy of subsequent data processing, location determination, and fault analysis.

[0043] Furthermore, the robot arm is controlled to deploy in a predetermined posture, triggering the multi-modal flaw detection module integrated at the end of the robot arm to perform concurrent detection under multi-modal orientation, including:

[0044] Taking the storage structure interface of the robot's manipulator arm as a reference point, determine the detection target moving along the trajectory, wherein the detection target includes a spatial distance and a spatial azimuth; identify the detection target, use the spatial distance as an arm length constraint, perform multi-degree-of-freedom adjustment based on the manipulator arm, and determine a first adjustment scheme, wherein the first adjustment scheme performs directional deployment of the manipulator arm; determine a multimodal directional viewing angle based on the spatial azimuth; perform directional adjustment on the front-end component according to the multimodal directional viewing angle, and determine a second adjustment scheme; combine the first adjustment scheme and the second adjustment scheme as a detection scheme to perform concurrent detection under multimodal orientation.

[0045] Specifically, the system uses the storage structure interface of the robot's manipulator arm as a reference point and dynamically determines the detection target based on the robot's position changes along the inspection trajectory. The detection target consists of two parameters: spatial distance and spatial azimuth, which describe the target's relative position in three-dimensional space. After identifying the detection target, the system uses the detection target's spatial distance as the arm length constraint. In combination with the multi-degree-of-freedom motion capabilities of the manipulator arm, it performs posture adjustments on the manipulator arm, generating a first adjustment scheme. This first adjustment scheme controls the manipulator arm to deploy in the appropriate direction and length, achieving directional deployment positioning. Subsequently, based on the spatial azimuth of the detection target, the system determines the multimodal directional viewing angle required for flaw detection and optimizes the sensor orientation for different detection modalities (such as ultrasonic, electromagnetic eddy current, and infrared thermal imaging). Based on this multimodal directional viewing angle, the multimodal front-end assembly at the end of the manipulator arm is further precisely adjusted in angle and direction to form a second adjustment scheme. Finally, the system combines the first and second adjustment schemes to form a complete detection scheme. Based on this detection scheme, the system synchronously triggers each flaw detection sensor to perform concurrent detection under multimodal directional positioning, ensuring the spatial accuracy of the detection task and the completeness of the detection coverage.

[0046] Furthermore, the multimodal flaw detection module includes an arm span unit and a multimode control unit; the first adjustment scheme is determined based on the arm span unit; the second adjustment scheme is determined based on the multimode control unit, wherein the multimode control unit includes multimodal branches corresponding to each front-end component, and the scanning target-scanning method is used as the underlying logic driving training.

[0047] The multimodal flaw detection module consists of an arm span unit and a multimodal control unit. The system uses the arm span unit to determine the initial adjustment scheme. The arm span unit is responsible for the extension and positioning of the robotic arm, ensuring that the flaw detection equipment at the end of the robotic arm accurately reaches the inspection target and maintains a stable working posture. The arm span unit is adjusted based on the target's spatial distance constraints and target azimuth, ensuring that the robotic arm provides the optimal detection angle and range when performing flaw detection tasks.

[0048] Based on this, the system determines the second adjustment scheme through the multi-mode control unit. The multi-mode control unit is responsible for controlling and coordinating the operating modes of multiple flaw detection sensors at the end of the robotic arm, including ultrasonic flaw detectors, electromagnetic eddy current sensors, and infrared thermal imagers. Each sensor has a corresponding adjustment scheme based on its characteristics and scanning requirements.

[0049] The multi-mode control unit contains multi-modal branches corresponding to each front-end component, each branch is responsible for controlling the operation of the corresponding flaw detection module (such as ultrasonic flaw detectors, electromagnetic eddy current sensors, infrared thermal imagers, etc.). Each flaw detection module has its own unique scanning target and scanning mode. Therefore, the multi-mode control unit uses the scanning target-scanning mode as the underlying logic to drive the scanning mode of each flaw detection module and perform corresponding training and optimization. Specifically, the scanning target refers to the object that the flaw detection module needs to detect, such as foundation piles, truss surfaces, or electrical junction boxes, while the scanning mode refers to the specific operating mode when the flaw detection module performs the detection task. For example, an ultrasonic flaw detector may need to scan along a specific axis, while an infrared thermal imager requires a panoramic perspective scan. The multi-mode control unit automatically adjusts the scanning parameters and operating mode of each flaw detection module according to its characteristics, ensuring that each sensor can perform its task in its optimal working state. Through this underlying logic drive based on the target and mode, the system can effectively coordinate the work of multiple flaw detection modules, achieve efficient multi-modal concurrent detection, and optimize the comprehensiveness and accuracy of the flaw detection task.

[0050] Through the synergistic effect of the arm span unit and the multi-mode control unit, the system can accurately adjust the working posture of the robotic arm and the scanning mode of the sensor according to different flaw detection requirements, thereby realizing efficient concurrent detection of multi-modal flaw detection modules in complex environments.

[0051] The detection signal set is transmitted back, and the signal distribution is updated as the detection process progresses. By performing modal independent detection and multimodal spatial distribution fusion, the flaw detection order is determined and sent to the operation and maintenance mobile terminal for alarm.

[0052] As the flaw detection module performs multimodal concurrent detection, the system collects and transmits detection signal sets in real time. These signals contain data collected by various flaw detection modules (such as ultrasonic flaw detectors, electromagnetic eddy current sensors, and infrared thermal imagers), identified by time-space codes. These signals are continuously updated as the detection progresses, and signal distribution updates ensure that the system can obtain the latest detection data in real time for subsequent processing.

[0053] The system processes these returned detection signals by performing modal-independent detection and multimodal spatial distribution fusion. Modal-independent detection means that each detection module performs independent signal analysis based on its own operating principle, while multimodal spatial distribution fusion combines the detection results of each modality to form a complete and comprehensive set of detection signals, providing more comprehensive detection information. Based on the fused detection results, the system determines a flaw detection inspection order and sends it to the operation and maintenance mobile terminal as an alert. Upon receiving the alert, operation and maintenance personnel can respond quickly and conduct further analysis and repair of the detected fault.

[0054] Furthermore, it also includes:

[0055] A low battery threshold is set. When the battery level of the target robot is lower than the low battery threshold, a battery replacement instruction is generated. According to the battery replacement instruction, the target robot is driven to autonomously navigate to the battery replacement station, and the auxiliary arm span unit drives the robotic arm to perform autonomous battery replacement control from the battery pack placement position to the battery assembly card position.

[0056] The system sets a low battery threshold. When the battery level of the target robot is lower than the low battery threshold, a battery replacement instruction is automatically generated. The low battery threshold is a preset standard (such as less than 15%) to ensure that the robot can be charged or the battery replaced in time when the battery level is insufficient to continue the task. According to the battery replacement instruction, the system drives the target robot to autonomously navigate to the battery swap station. Autonomous navigation means that the robot plans the path in the environment in real time based on its built-in navigation system and sensors, avoids obstacles, and successfully reaches the battery swap station. After arriving at the battery swap station, the auxiliary arm span unit performs the battery swap operation by driving the robotic arm. The end of the robotic arm controls the removal and replacement of the battery pack. Through the precise movement of the robotic arm, it ensures that the battery pack can be safely removed from the battery pack placement position and accurately placed in the battery assembly card position. The entire battery swap process does not require human intervention. The robot can automatically complete the battery replacement task to ensure the robot's continuous operation capability during operation and maintenance.

[0057] In summary, the embodiments of the present application have at least the following technical effects:

[0058] The GIS map of the photovoltaic station is imported into the target robot, and the inspection route is planned to drive the target robot to move. The target robot is equipped with a triangular crawler chassis, and the crawler inclination angle is adaptively adjusted according to the track terrain in the second order. When the target robot moves to the station area, it controls the directional deployment of the robotic arm in a preset deployment posture, triggering the multimodal flaw detection module integrated at the end of the robotic arm, performing concurrent detection under multimodal orientation, and determining the detection signal set, wherein the detection signal set is identified by a time-space code. The detection signal set is transmitted back, and the signal distribution is updated as the detection progresses. By performing modal independent detection and multimodal spatial distribution fusion, the flaw detection inspection order is determined and sent to the operation and maintenance mobile terminal for alarm. This solves the technical problem of low inspection efficiency of photovoltaic power stations in complex terrain in the existing technology, and achieves the technical effect of improving the inspection efficiency of photovoltaic power stations.

[0059] Embodiment 2 is based on the same inventive concept as the operation control method for the flaw detection and maintenance robot in the above embodiment. Figure 2 As shown, the present application provides an operation control system for a flaw detection and maintenance robot, wherein the system includes:

[0060] The mobile component 11 is used to import the photovoltaic station GIS map into the target robot, plan the inspection path, and drive the target robot to move, wherein the target robot is equipped with a triangular crawler chassis, and the crawler inclination angle is adaptively adjusted according to the track terrain for second-order equal position; the detection component 12 is used to control the directional deployment of the robotic arm with a preset deployment posture when the target robot moves to the station area, trigger the multi-modal flaw detection module integrated at the end of the robotic arm, perform concurrent detection under multi-modal orientation, and determine the detection signal set, wherein the detection signal set is identified by a time-space code; the alarm component 13 is used to transmit the detection signal set back, update the signal distribution as the detection process progresses, and determine the flaw detection inspection order by performing modal independent detection and multi-modal spatial distribution fusion and sending it to the operation and maintenance mobile terminal for alarm.

[0061] Furthermore, the detection component 12 is used to perform the following method:

[0062] The robotic arm is a multi-degree-of-freedom folding arm that can be stored in the internal structure of the robot. A multi-modal flaw detection module is integrated at the end of the robotic arm, wherein the front-end components of the multi-modal flaw detection module include at least an ultrasonic flaw detector, an electromagnetic eddy current sensor, and an infrared thermal imager.

[0063] Furthermore, the detection component 12 is used to perform the following method:

[0064] The ultrasonic flaw detector uses the foundation pile as the scanning target and scans along the axial direction of the foundation pile; the electromagnetic eddy current sensor uses the truss surface as the scanning target and uses grid detection with a preset grid spacing as the scanning method; the infrared thermal imager uses the electrical junction box as the scanning target and uses the wiring panorama as the scanning method.

[0065] Furthermore, the mobile component 11 is used to perform the following method:

[0066] The first undulation inclination angle based on the road condition characteristics is used as the first-order control target, and the first-order nodes are deployed; the inclination angle variables of the upper control node and the lower control node are used as the second-order control targets, and the second-order nodes are deployed; the first-order nodes and the second-order nodes are sequentially cascaded to determine the equal-order adjustment module.

[0067] Furthermore, the mobile component 11 is used to perform the following method:

[0068] The flaw detection and maintenance robot includes an independently driven first crawler and a second crawler; the isotropic adjustment module is deployed at the first control end of the first crawler and the second control end of the second crawler, and a synchronization timestamp constraint is established between the first control end and the second control end.

[0069] Furthermore, the mobile component 11 is used to perform the following method:

[0070] As the vehicle moves based on the inspection path, the real-time path conditions are determined; based on the real-time path conditions, the equal-position adjustment module deployed at the first control end executes a first-order inclination decision based on the road condition fluctuation characteristics to determine the first-order road condition inclination; the upper track inclination of the upper control node is retrieved, and the difference between the first-order road condition inclination and the upper track inclination is calculated as the second-order adjustment inclination; based on the second-order adjustment inclination, the first track is driven to perform track inclination control.

[0071] Furthermore, the detection component 12 is used to perform the following method:

[0072] Taking the storage structure interface of the robot's manipulator arm as a reference point, determine the detection target moving along the trajectory, wherein the detection target includes a spatial distance and a spatial azimuth; identify the detection target, use the spatial distance as an arm length constraint, perform multi-degree-of-freedom adjustment based on the manipulator arm, and determine a first adjustment scheme, wherein the first adjustment scheme performs directional deployment of the manipulator arm; determine a multimodal directional viewing angle based on the spatial azimuth; perform directional adjustment on the front-end component according to the multimodal directional viewing angle, and determine a second adjustment scheme; combine the first adjustment scheme and the second adjustment scheme as a detection scheme to perform concurrent detection under multimodal orientation.

[0073] Furthermore, the detection component 12 is used to perform the following method:

[0074] The multimodal flaw detection module includes an arm span unit and a multimode control unit; the first adjustment scheme is determined based on the arm span unit; the second adjustment scheme is determined based on the multimode control unit, wherein the multimode control unit includes multimodal branches corresponding to each front-end component, and the scanning target-scanning method is used as the underlying logic driving training.

[0075] Furthermore, the mobile component 11 is used to perform the following method:

[0076] A low battery threshold is set. When the battery level of the target robot is lower than the low battery threshold, a battery replacement instruction is generated. According to the battery replacement instruction, the target robot is driven to autonomously navigate to the battery replacement station, and the auxiliary arm span unit drives the robotic arm to perform autonomous battery replacement control from the battery pack placement position to the battery assembly card position.

[0077] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0079] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. An operation control method for a flaw detection and maintenance robot, characterized in that: The method comprises: Import the GIS map of the photovoltaic station into the target robot, plan the inspection path, and drive the target robot to move. The target robot is equipped with a triangular crawler chassis, and the crawler inclination angle is adaptively adjusted according to the track terrain in a second-order isotropic manner. When the target robot moves to the station area, the robot arm is controlled to be deployed in a predetermined deployment posture, and the multi-modal flaw detection module integrated at the end of the robot arm is triggered to perform concurrent detection under multi-modal orientation and determine a detection signal set, wherein the detection signal set is identified by a time-space code; The detection signal set is transmitted back, and the signal distribution is updated as the detection process progresses. By performing modal independent detection and multimodal spatial distribution fusion, the flaw detection order is determined and sent to the operation and maintenance mobile terminal for alarm.

2. The operation control method for a flaw detection and maintenance robot according to claim 1, characterized in that: The robotic arm is a multi-degree-of-freedom folding arm that can be stored in the internal structure of the robot. A multi-modal flaw detection module is integrated at the end of the robotic arm, wherein the front-end components of the multi-modal flaw detection module include at least an ultrasonic flaw detector, an electromagnetic eddy current sensor, and an infrared thermal imager.

3. The operation control method for a flaw detection and maintenance robot according to claim 2, characterized in that: The ultrasonic flaw detector uses the foundation pile as the scanning target and scans along the axial direction of the foundation pile; the electromagnetic eddy current sensor uses the truss surface as the scanning target and uses grid detection with a preset grid spacing as the scanning method; the infrared thermal imager uses the electrical junction box as the scanning target and uses the wiring panorama as the scanning method.

4. The operation control method for a flaw detection and maintenance robot according to claim 1, wherein: Before the track inclination angle is adaptively adjusted according to the track terrain for the second-order equal-position adjustment, the equal-position adjustment module is constructed, including: The first-order node is deployed with the first undulation inclination angle based on road condition characteristics as the first-order control target; The inclination angle variable between the upper control node and the lower control node is used as the second-order control target, and the second-order nodes are deployed; The first-order nodes and the second-order nodes are sequentially cascaded to determine an equal-level adjustment module.

5. The operation control method for a flaw detection and maintenance robot according to claim 4, characterized in that: The flaw detection and maintenance robot includes a first crawler and a second crawler that are independently driven; The isochronous adjustment module is deployed on the first control end of the first crawler and the second control end of the second crawler, and a synchronization timestamp constraint is established between the first control end and the second control end.

6. The operation control method for a flaw detection and maintenance robot according to claim 5, characterized in that: The track inclination angle is adjusted according to the track terrain, including: Determining real-time path conditions as the patrol route moves; Based on the real-time path terrain conditions, the equal position adjustment module deployed at the first control terminal performs a first-order inclination angle decision based on the road condition fluctuation characteristics to determine the first-order road condition inclination angle; Retrieving the upper track inclination angle of the upper control node, and calculating the difference between the first-order road condition inclination angle and the upper track inclination angle as the second-order adjustment inclination angle; According to the second-order adjusted inclination angle, the first crawler belt is driven to perform crawler belt inclination control.

7. The operation control method for a flaw detection and maintenance robot according to claim 3, characterized in that: The robot arm is controlled to deploy in a preset posture, triggering the multi-modal flaw detection module integrated at the end of the robot arm to perform concurrent detection under multi-modal orientation, including: Using the storage structure interface of the robot arm as a reference point, determine the detection target under trajectory movement, wherein the detection target includes spatial distance and spatial azimuth; Identifying the detection target, using the spatial distance as an arm length constraint, performing multi-degree-of-freedom adjustment based on the robotic arm, and determining a first adjustment scheme, wherein the first adjustment scheme performs directional deployment of the robotic arm; Determining a multimodal directional viewing angle based on the spatial orientation angle; Directionally adjusting the front-end component according to the multimodal directional viewing angle to determine a second adjustment scheme; The first adjustment scheme and the second adjustment scheme are combined as a detection scheme to perform concurrent detection under multi-modal orientation.

8. The operation control method for a flaw detection and maintenance robot according to claim 7, characterized in that: The multi-mode flaw detection module includes an arm span unit and a multi-mode control unit; Determining the first adjustment scheme according to the arm span unit; The second adjustment scheme is determined according to the multi-mode control unit, wherein the multi-mode control unit includes multi-modal branches corresponding to each front-end component, and uses a scan target-scan method as the underlying logic drive training.

9. The operation control method for a flaw detection and maintenance robot according to claim 8, characterized in that: The method further comprises: Setting a low battery threshold, when the battery level of the target robot is lower than the low battery threshold, generating a battery replacement instruction; According to the battery replacement instruction, the target robot is driven to autonomously navigate to the battery replacement station, and the auxiliary arm span unit drives the robotic arm to perform autonomous battery replacement control from the battery pack placement position to the battery assembly card position.

10. An operation control system for a flaw detection and maintenance robot, characterized in that: A system for implementing the operation control method for a flaw detection and maintenance robot according to any one of claims 1 to 9, the system comprising: The mobile component is used to import the GIS map of the photovoltaic station into the target robot, plan the inspection path, and drive the target robot to move. The target robot is equipped with a triangular track chassis, and the track inclination angle is adaptively adjusted according to the track terrain in the second order. A detection component is used to control the directional deployment of the manipulator arm in a preset deployment posture when the target robot moves to the station area, trigger the multi-modal flaw detection module integrated at the end of the manipulator arm, perform concurrent detection under multi-modal orientation, and determine a detection signal set, wherein the detection signal set is identified by a time-space code; The alarm component is used to transmit the detection signal set back, update the signal distribution as the detection process progresses, determine the flaw detection order by performing modal independent detection and multimodal spatial distribution fusion, and send it to the operation and maintenance mobile terminal for alarm.

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