Intelligent monitoring obstacle avoidance system of marine folding arm crane

Abstract

The utility model provides an intelligent monitoring obstacle avoidance system of an ocean folding arm crane, which relates to the technical field of ship hoisting and comprises a high-definition binocular camera, a high-definition binocular camera, a laser radar, a laser ranging sensor, an acceleration sensor, a control device, a high-performance controller and a monitoring system. An image processing unit, a point cloud processing unit, a three-dimensional reconstruction unit, an obstacle avoidance planning unit and an obstacle avoidance control unit are arranged in the high-performance controller, the high-definition binocular camera and the high-definition binocular camera are in communication feedback connection with the image processing unit, and the laser radar is in communication feedback connection with the point cloud processing unit and the three-dimensional reconstruction unit in sequence. The laser ranging sensor, the acceleration sensor, the image processing unit and the three-dimensional reconstruction unit are in communication feedback connection with the obstacle avoidance planning unit, and the obstacle avoidance planning unit, the obstacle avoidance control unit and the control device are in communication feedback connection in sequence. According to the utility model, intelligent obstacle avoidance of the folding arm crane can be realized, and the obstacle avoidance effect and quality are improved.

Description

Technical Field

[0001] The utility model relates to the technical field of ship lifting, in particular to an intelligent monitoring and obstacle avoidance system of a marine folding arm crane. Background Art

[0002] An offshore folding arm crane is a type of crane installed on a ship or offshore platform for lifting cargo or equipment. It mainly includes a base, a slewing mechanism, a folding arm, a hook and other components, and can adapt to different working radiuses and spatial operations. At present, traditional folding arm cranes are only equipped with limiters installed at key locations such as the hook, folding arm, and slewing mechanism. The limiters are used to send signals or cut off the power supply when the preset limit value is reached, thereby preventing the folding arm crane from having a collision accident. However, in actual use, the limiter can only work when the folding arm crane reaches the limit value, and it cannot predict and avoid obstacles in advance, and it cannot achieve intelligent obstacle avoidance, which has a certain impact on the safety of the folding arm crane. Utility Model Content

[0003] The purpose of the utility model is to provide an intelligent monitoring and obstacle avoidance system for an ocean folding arm crane, which realizes timely and effective intelligent obstacle avoidance by performing all-round monitoring of the folding arm crane and obstacle information processing, improves the obstacle avoidance effect and quality, meets complex ocean operation conditions, and improves safety.

[0004] The above technical objectives of the utility model are achieved through the following technical solutions:

[0005] An intelligent monitoring and obstacle avoidance system for an offshore folding arm crane comprises a high-definition binocular camera which is obliquely mounted above the hook of the folding arm crane and aligned with the center line of the hook, and whose lens faces the front and bottom of the folding arm crane;

[0006] There are four high-definition single-lens cameras evenly installed at the four corners below the slewing mechanism of the folding arm crane, and their lenses face the surrounding environment of the folding arm crane;

[0007] A laser radar is mounted on the top of the cab, aligned with the centerline of the knuckle boom crane and facing the periphery of the knuckle boom crane;

[0008] The laser distance measuring sensor and the acceleration sensor are respectively installed on the left and right sides of the hook of the folding arm crane, perpendicular to the center line of the hook, and the laser distance measuring sensor faces downward;

[0009] A control device connected to the folding arm crane control to control the movement and lifting operation of the folding arm crane;

[0010] A high-performance controller, wherein the high-definition binocular camera, the high-definition monocular camera, the laser radar, the laser ranging sensor and the acceleration sensor are all connected to the high-performance controller for communication feedback, and the high-performance controller is connected to the control device for communication control;

[0011] A monitoring system, wherein the control device and the high-performance controller are connected to the monitoring system for communication feedback, and the monitoring system displays the operating status and environmental information of the knuckle boom crane in real time;

[0012] The high-performance controller is provided with an image processing unit, and the high-definition binocular camera and the high-definition monocular camera are connected to the image processing unit for communication and feedback;

[0013] A point cloud processing unit, wherein the laser radar is connected to the point cloud processing unit for feedback communication;

[0014] A three-dimensional reconstruction unit, wherein the point cloud processing unit is connected to the three-dimensional reconstruction unit for feedback communication;

[0015] The obstacle avoidance planning unit, the laser ranging sensor, the acceleration sensor, the image processing unit and the three-dimensional reconstruction unit are connected to the obstacle avoidance planning unit for communication feedback;

[0016] The obstacle avoidance control unit is connected to the obstacle avoidance planning unit for communication feedback, and the obstacle avoidance control unit is connected to the control device for communication.

[0017] By adopting the above technical solutions, the high-definition binocular camera collects image information in front of and below the folding arm crane, and measures the distance information between the hook and the hoisted object and the obstacles in front and below. The high-definition monocular camera collects image information around the folding arm crane and monitors the dangerous areas around the folding arm crane. The laser radar scans the environment around the folding arm crane and measures the distance and angle of obstacles in all directions, which is convenient for building a three-dimensional point cloud map. The laser rangefinder measures the distance between the folding arm crane hook and the hoisted object, and the acceleration sensor detects the swing of the hook and the hoisted object.

[0018] The data collected by the high-definition binocular camera, high-definition monocular camera, laser radar, laser ranging sensor and acceleration sensor are communicated and fed back to the high-performance controller. Through the processing of each unit in the high-performance controller, the obstacle avoidance command for controlling the movement and hoisting of the folding arm crane is output. The control device controls the movement and hoisting operation of the folding arm crane, and controls the folding arm crane to avoid obstacles after receiving the obstacle avoidance command from the high-performance controller. The monitoring system displays the operating status and environmental information of the folding arm crane in real time.

[0019] The image processing unit receives the image information fed back by the high-definition binocular camera and the high-definition monocular camera, and identifies the position and shape of the obstacle from it; the point cloud processing unit receives the point cloud data fed back by the laser radar and performs centralized processing; the 3D reconstruction unit receives the point cloud data output by the point cloud processing unit, constructs a 3D map of the surrounding environment of the folding arm crane, and locates the position and posture of the folding arm crane. The obstacle avoidance planning unit plans a safe, smooth and optimal motion trajectory based on the current position and target position of the folding arm crane, the point cloud data fed back by the point cloud processing unit and the 3D reconstruction unit, and the obstacle information displayed on the 3D map. The obstacle avoidance control unit generates the rotation, folding, telescopic, lifting, hoisting and other action commands for controlling the folding arm crane to avoid obstacles based on the motion trajectory planned by the obstacle avoidance planning unit, and transmits them to the control device so that the control device can control the folding arm crane to perform corresponding actions to avoid obstacles.

[0020] The utility model utilizes a combination of a high-definition binocular camera, a high-definition monocular camera, a laser radar, a laser ranging sensor, and an acceleration sensor to achieve all-round monitoring of the folding arm crane, and processes information on obstacles around the folding arm crane through the image processing unit, point cloud processing unit, and three-dimensional reconstruction unit in the high-performance controller. The obstacle avoidance planning unit and the obstacle avoidance control unit are used to achieve timely and effective intelligent obstacle avoidance of the folding arm crane, thereby improving the obstacle avoidance effect and quality, meeting complex marine operating conditions, and improving safety.

[0021] Furthermore, the image processing unit is provided with a convolutional neural network and a binocular vision module, the point cloud processing unit is provided with an iterative closest point module and an octree module, the three-dimensional reconstruction unit is provided with a multi-threading module and a GPU acceleration module; the obstacle avoidance planning unit is provided with a nonlinear planning module, and the obstacle avoidance control unit is provided with a fuzzy control module.

[0022] By adopting the above technical solutions, the convolutional neural network and binocular vision module can improve the recognition rate and real-time performance of the image. The convolutional neural network extracts features from the image and performs classification and regression. The binocular vision module uses the parallax of the two lenses in the high-definition binocular camera to calculate the depth information in the image. The convolutional neural network and the binocular vision module jointly improve the recognition efficiency and accuracy of the image processing unit for the position and shape of obstacles. The iterative closest point module finds the optimal correspondence and transformation by minimizing the distance between the two sets of point clouds. The octree module stores the point cloud in cube nodes at different levels to achieve compression and indexing of the point cloud. The iterative closest point module and the octree module are used to improve the accuracy and speed of the point cloud processing unit for point cloud processing. The multi-threaded module and the GPU acceleration module in the three-dimensional reconstruction unit use the parallel computing capabilities of multi-core processors and graphics processors to effectively improve the operating efficiency of three-dimensional reconstruction. The nonlinear programming module can solve the optimal solution of the nonlinear objective function under some nonlinear constraints. The fuzzy control module uses fuzzy logic to process uncertainty and fuzziness information to achieve fuzzy reasoning and control of the system. The nonlinear programming module and the fuzzy control module can effectively improve the safety and stability of obstacle avoidance.

[0023] Furthermore, the control device is connected to a manual control unit and an automatic control unit, and the obstacle avoidance control unit is connected to the control device through communication control via the automatic control unit.

[0024] By adopting the above technical solution, the manual control unit can manually control obstacle avoidance by manually operating the control device, and the obstacle avoidance control unit controls the control unit through the automatic control unit to perform intelligent obstacle avoidance. The two obstacle avoidance modes can be flexibly selected to effectively improve the scope of application and meet the obstacle avoidance needs under different conditions.

[0025] Furthermore, the automatic control unit is connected to an obstacle avoidance mode unit and a non-obstacle avoidance mode unit, and the automatic control unit controls the control device to avoid obstacles or not to avoid obstacles through communication between the obstacle avoidance mode unit and the non-obstacle avoidance mode unit.

[0026] By adopting the above technical solution, the automatic control unit can control the control device to operate the folding arm crane to avoid obstacles or not avoid obstacles by switching the avoidance mode unit and the non-obstacle avoidance mode unit, so as to meet the actual needs of obstacle avoidance or non-obstacle avoidance under different conditions, and flexibly select obstacle avoidance or non-obstacle avoidance under automatic control conditions, thereby effectively improving the scope of application.

[0027] Furthermore, a control switching switch is connected between the manual control unit and the automatic control unit, and an obstacle avoidance switching switch is connected between the obstacle avoidance mode unit and the non-obstacle avoidance mode unit.

[0028] By adopting the above technical solution, the manual control unit and the automatic control unit are switched by the control switch, so as to realize the rapid switching between manual control and automatic control. The obstacle avoidance mode unit and the non-obstacle avoidance mode unit are switched by the obstacle avoidance switch, so as to realize the rapid switching between the obstacle avoidance mode and the non-obstacle avoidance mode. The structure is simple, the operation is convenient and the effect is obvious.

[0029] Furthermore, the monitoring system is connected to a display unit, and a number of sub-display units are arranged in the display unit. The high-definition binocular camera, high-definition monocular camera, lidar, laser ranging sensor, acceleration sensor, image processing unit, point cloud processing unit, three-dimensional reconstruction unit, obstacle avoidance planning unit, and obstacle avoidance control unit are all connected to corresponding sub-display units for communication feedback.

[0030] By adopting the above technical scheme, the display unit includes several sub-display units, and the relevant data collected by the high-definition binocular camera, the high-definition monocular camera, the laser radar, the laser ranging sensor, and the acceleration sensor, the image information processed and output by the image processing unit, the point cloud information output by the point cloud processing unit, the three-dimensional information output by the three-dimensional reconstruction unit, the obstacle avoidance trajectory output by the obstacle avoidance planning unit, and the obstacle avoidance command output by the obstacle avoidance control unit are respectively displayed in the corresponding sub-display units, so that the operator can intuitively understand various types of information.

[0031] Furthermore, the obstacle avoidance planning unit is connected to an alarm unit, and the alarm unit is one or more of a photoelectric alarm and a voice alarm.

[0032] By adopting the above technical solution, when the obstacle avoidance planning unit outputs the obstacle avoidance motion trajectory to the obstacle avoidance control unit, the alarm unit is fed back to give an alarm, reminding the staff to pay attention to the upcoming obstacle avoidance of the folding arm crane, and at the same time reminding the staff to observe whether the obstacle avoidance action of the folding arm crane is accurate, thereby improving safety and avoiding accidental injuries. Among them, the alarm unit is one or more of a photoelectric alarm and a voice alarm, which can directly prompt the staff on site through photoelectric / voice, further improving safety.

[0033] Furthermore, the high-performance controller communication feedback is connected to a database, and the data received and input by the image processing unit, point cloud processing unit, three-dimensional reconstruction unit, obstacle avoidance planning unit, and obstacle avoidance control unit in the high-performance controller are all stored in the database.

[0034] By adopting the above technical solution, the data received and input by the image processing unit, point cloud processing unit, 3D reconstruction unit, obstacle avoidance planning unit, and obstacle avoidance control unit are all stored in the database, so that historical data can be preserved for easy tracing.

[0035] In summary, the utility model has the following beneficial effects:

[0036] 1. The utility model realizes all-round monitoring of the folding arm crane by setting a high-definition binocular camera, a high-definition monocular camera, a laser radar, a laser ranging sensor, and an acceleration sensor to obtain the surrounding environment and obstacle information of the folding arm crane, providing a comprehensive and accurate basis for intelligent obstacle avoidance and improving the effect and quality of intelligent obstacle avoidance;

[0037] 2. The image processing unit in the utility model improves the recognition rate and real-time performance of the image through the convolutional neural network and the binocular vision module, and improves the efficiency and accuracy of the image processing unit in recognizing the position and shape of obstacles; the point cloud processing unit effectively improves the accuracy and speed of point cloud processing through the iterative nearest point module and the octree module; the three-dimensional reconstruction unit utilizes the parallel computing capabilities of the multi-core processor and the graphics processor through the multi-threading module and the GPU acceleration module, and effectively improves the operating efficiency of the three-dimensional reconstruction; the obstacle avoidance planning unit and the obstacle avoidance control unit effectively improve the safety and stability of obstacle avoidance through the nonlinear planning module and the fuzzy control module;

[0038] 3. The utility model provides a variety of modes such as manual control, automatic control, obstacle avoidance, and non-obstacle avoidance through a manual control unit, an automatic control unit, an obstacle avoidance mode unit, and a non-obstacle avoidance mode unit, which can be freely selected by users to meet the usage requirements of different scenarios and effectively improve the scope of application. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the overall structure of an intelligent monitoring and obstacle avoidance system for an offshore folding arm crane.

[0040] In the figure, 1. high-definition binocular camera; 2. high-definition monocular camera; 3. laser radar; 4. laser ranging sensor; 5. acceleration sensor; 6. control device; 61. manual control unit; 62. automatic control unit; 63. control switching switch; 64. obstacle avoidance mode unit; 65. non-obstacle avoidance mode unit; 66. obstacle avoidance switching switch; 7. high-performance controller; 71. image processing unit; 711. convolutional neural network; 712. binocular vision module; 72. point cloud processing unit; 721. iterative closest point module; 722. octree module; 73. three-dimensional reconstruction unit; 731. multi-threading module; 732. GPU acceleration module; 74. obstacle avoidance planning unit; 741. nonlinear planning module; 75. obstacle avoidance control unit; 751. fuzzy control module; 8. monitoring system; 81. display unit; 811. sub-display unit; 9. alarm unit; 91. photoelectric alarm; 92. voice alarm; 10. database. DETAILED DESCRIPTION

[0041] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0042] An intelligent monitoring and obstacle avoidance system for an offshore folding arm crane, such as Figure 1 As shown, it includes a high-definition binocular camera 1, a high-definition monocular camera 2, a laser radar 3, a laser ranging sensor 4, an acceleration sensor 5, a control device 6, a high-performance controller 7 and a monitoring system 8. The high-definition binocular camera 1, the high-definition monocular camera 2, the laser radar 3, the laser ranging sensor 4 and the acceleration sensor 5 are all connected to the high-performance controller 7 for communication feedback, the high-performance controller 7 is connected to the control device 6 for communication control, the control device 6 and the high-performance controller 7 are connected to the monitoring system 8 for communication feedback, and the control device 6 is connected to the folding arm crane control to control the movement and hoisting operation of the folding arm crane.

[0043] like Figure 1 As shown, the high-definition binocular camera 1, the high-definition monocular camera 2, the laser radar 3, the laser ranging sensor 4 and the acceleration sensor 5 are used to collect information about the external environment and obstacles of the folding arm crane, and feed it back to the high-performance controller 7. The high-performance controller 7 outputs an obstacle avoidance control command through information processing. The control device 6 controls the folding arm crane to avoid obstacles according to the obstacle avoidance control command. The monitoring system 8 displays the operating status and environmental information of the folding arm crane in real time.

[0044] Specifically, the high-definition binocular camera 1 is installed obliquely above the hook of the folding arm crane, aligned with the center line of the hook, and its lens faces the front and bottom of the folding arm crane to collect image information in front of and below the folding arm crane, measure the distance information of obstacles, and transmit the image data to the high-performance controller 7. Four high-definition monocular cameras 2 are evenly installed at the four corners below the slewing mechanism of the folding arm crane, and its lens faces the surrounding environment of the folding arm crane to collect image information around the folding arm crane, monitor the dangerous area around the folding arm crane, and transmit the image data to the high-performance controller 7. The high-definition binocular camera 1 and the high-definition monocular camera 2 can obtain images with high resolution and high dynamic range, have the characteristics of high-speed transmission and low power consumption, and can improve the clarity and stability of the image.

[0045] The laser radar 3 is installed on the top of the cab, aligned with the center line of the folding arm crane, and facing the surroundings of the folding arm crane. It scans the surrounding environment of the folding arm crane to measure the distance and angle of obstacles, and transmits the point cloud data to the high-performance controller 7. The laser radar 3 can obtain high-density and high-precision point cloud data, has the characteristics of high frequency and high reliability, and can improve the integrity and accuracy of the point cloud. The laser rangefinder 4 and the acceleration sensor 5 are respectively installed on the left and right sides of the hook of the folding arm crane, perpendicular to the center line of the hook, and the laser rangefinder 4 faces downward, which is used to measure the distance between the folding arm crane hook and the hoisted object. The acceleration sensor 5 is used to measure the swing of the hook and the hoisted object, and transmits the relevant data to the high-performance controller 7.

[0046] In this embodiment, if Figure 1 As shown, an image processing unit 71, a point cloud processing unit 72, a three-dimensional reconstruction unit 73, an obstacle avoidance planning unit 74 and an obstacle avoidance control unit 75 are provided in the high-performance controller 7; the high-definition binocular camera 1 and the high-definition monocular camera 2 are connected to the image processing unit 71 for communication and feedback; the laser radar 3 is connected to the point cloud processing unit 72 for communication and feedback, and the point cloud processing unit 72 is connected to the three-dimensional reconstruction unit 73 for communication and feedback; the laser ranging sensor 4, the acceleration sensor 5, the image processing unit 71 and the three-dimensional reconstruction unit 73 are connected to the obstacle avoidance planning unit 74 for communication and feedback; the obstacle avoidance planning unit 74 is connected to the obstacle avoidance control unit 75 for communication and feedback, and the obstacle avoidance control unit 75 is connected to the control device 6 for communication and feedback.

[0047] like Figure 1 As shown, the high-definition binocular camera 1 and the high-definition monocular camera 2 transmit the collected obstacle image data in front of, below, on the left and right sides and behind the folding arm crane to the image processing unit 71. The image processing unit 71 processes the image data and outputs the obstacle information to the obstacle avoidance planning unit 74. The laser radar 3 transmits the collected environment data of the folding arm crane to the point cloud processing unit 72, processes the point cloud data, and then transmits the point cloud data to the three-dimensional reconstruction unit 73. The three-dimensional reconstruction unit 73 constructs a three-dimensional map around the folding arm crane according to the point cloud data, locates the position and posture of the folding arm crane, and transmits the three-dimensional map and the position and posture information to the obstacle avoidance planning unit 74. The obstacle avoidance planning unit 74 plans a safe, smooth and optimal motion trajectory based on the received position and posture information, obstacle information, distance and acceleration information fed back by the laser ranging sensor 4 and the acceleration sensor 5, and inputs the motion trajectory to the obstacle avoidance control unit 75. The obstacle avoidance control unit 75 outputs control commands for controlling the folding arm crane's rotation, folding arm, extension, lifting, hoisting and other actions to the control device 6 based on the motion trajectory. The control device 6 controls the folding arm crane to perform relevant operations to avoid obstacles based on the control commands.

[0048] Specifically, Figure 1 As shown, a convolutional neural network 711 and a binocular vision module 712 are provided in the image processing unit 71. The convolutional neural network 711 and the binocular vision module 712 can improve the recognition rate and real-time performance of the image. The convolutional neural network 711 utilizes a deep learning model to extract features from the image and perform classification and regression. The binocular vision module 712 utilizes the parallax of the two lenses in the high-definition binocular camera 1 to calculate the depth information in the image through binocular vision technology. The convolutional neural network 711 and the binocular vision module 712 jointly improve the recognition efficiency and accuracy of the image processing unit 71 for the position and shape of obstacles.

[0049] like Figure 1As shown, an iterative closest point module 721 and an octree module 722 are provided in the point cloud processing unit 72. The iterative closest point module 721 minimizes the distance between two groups of point clouds through the iterative closest point technology to find the optimal correspondence and transformation. The octree module 722 uses the octree technology to store the point cloud in cube nodes at different levels to achieve compression and indexing of the point cloud, thereby improving the accuracy and speed of the point cloud processing unit 72 in processing the point cloud. A multithreading module 731 and a GPU acceleration module 732 are provided in the 3D reconstruction unit 73. The multithreading module 731 and the GPU acceleration module 732 use the parallel computing capabilities of multi-core processors and graphics processors to effectively improve the operating efficiency of 3D reconstruction.

[0050] like Figure 1 As shown, a nonlinear programming module 741 is provided in the obstacle avoidance planning unit 74, and a fuzzy control module 751 is provided in the obstacle avoidance control unit 75. The nonlinear programming module 741 can solve the optimal solution of the nonlinear objective function by using the nonlinear programming technology under certain nonlinear constraints. The fuzzy control module 751 uses the fuzzy control technology to process the uncertainty and fuzzy information to realize the fuzzy reasoning and control of the system. The nonlinear programming module 741 and the fuzzy control module 751 can effectively improve the safety and stability of obstacle avoidance.

[0051] like Figure 1 As shown, in order to further meet the control requirements of different usage scenarios, the control device 6 is connected to a manual control unit 61 and an automatic control unit 62, and a control switching switch 63 is connected between the manual control unit 61 and the automatic control unit 62, and the obstacle avoidance control unit 75 is connected to the control device 6 through the automatic control unit 62. In addition, the automatic control unit 62 is connected to an obstacle avoidance mode unit 64 and a non-obstacle avoidance mode unit 65, and an obstacle avoidance switching switch 66 is connected between the obstacle avoidance mode unit 64 and the non-obstacle avoidance mode unit 65, and the automatic control unit 62 controls the control device to avoid obstacles or not avoid obstacles through the obstacle avoidance mode unit 64 and the non-obstacle avoidance mode unit 65. Manual control or automatic control can be switched freely, and obstacle avoidance or non-obstacle avoidance can be flexibly selected under automatic control, effectively meeting the obstacle avoidance requirements under different conditions.

[0052] like Figure 1 As shown, the monitoring system 8 is connected to a display unit 81, and a plurality of sub-display units 811 are arranged in the display unit 81. The high-definition binocular camera 1, the high-definition monocular camera 2, the laser radar 3, the laser ranging sensor 4, the acceleration sensor 5, the image processing unit 71, the point cloud processing unit 72, the three-dimensional reconstruction unit 73, the obstacle avoidance planning unit 74, and the obstacle avoidance control unit 75 are all connected to the corresponding sub-display units 811 for communication feedback, and the relevant information is respectively displayed in the corresponding sub-display units 811, so that the operator can intuitively understand various types of information.

[0053] like Figure 1 As shown, the obstacle avoidance planning unit 74 is connected to the alarm unit 9. When the obstacle avoidance planning unit 74 outputs the obstacle avoidance motion trajectory to the obstacle avoidance control unit 75, the alarm unit 9 is fed back to alarm at the same time, prompting the staff to pay attention to the folding arm crane to avoid obstacles. At the same time, the staff can be reminded to observe whether the obstacle avoidance action of the folding arm crane is accurate, thereby improving safety and avoiding accidental injuries. Among them, the alarm unit 9 is one or more of a photoelectric alarm 91 and a voice alarm 92, which directly prompts the staff on site through photoelectric / voice to further improve safety.

[0054] like Figure 1 As shown, the high-performance controller 7 is connected to the database 10 for communication feedback. The data received and input by the image processing unit 71, the point cloud processing unit 72, the three-dimensional reconstruction unit 73, the obstacle avoidance planning unit 74, and the obstacle avoidance control unit 75 in the high-performance controller 7 are all stored in the database 10. The database 10 is used to save historical data for easy tracing.

[0055] The above description shows and describes the preferred embodiments of the utility model. As mentioned above, it should be understood that the utility model is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the utility model concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art do not depart from the spirit and scope of the utility model, and should be within the scope of protection of the claims attached to the utility model.

Claims

1. An intelligent monitoring and obstacle avoidance system for an offshore folding arm crane, characterized in that: It comprises a high-definition binocular camera (1), which is installed obliquely above the hook of the folding arm crane, aligned with the center line of the hook, and its lens faces the front and bottom of the folding arm crane; Four high-definition single-lens cameras (2) are provided and evenly installed at the four corners below the slewing mechanism of the folding arm crane, and the lenses thereof face the surrounding environment of the folding arm crane; A laser radar (3) is mounted on the top of the cab, aligned with the centerline of the knuckle boom crane and facing the periphery of the knuckle boom crane; The laser distance measuring sensor (4) and the acceleration sensor (5) are respectively installed on the left and right sides of the hook of the folding arm crane, perpendicular to the center line of the hook, and the laser distance measuring sensor (4) faces downward; A control device (6) is connected to the folding arm crane control system to control the movement and lifting operation of the folding arm crane; A high-performance controller (7), wherein the high-definition binocular camera (1), the high-definition monocular camera (2), the laser radar (3), the laser ranging sensor (4) and the acceleration sensor (5) are all connected to the high-performance controller (7) for communication feedback, and the high-performance controller (7) is connected to the control device (6) for communication control; A monitoring system (8), wherein the control device (6) and the high-performance controller (7) are connected to the monitoring system (8) for communication feedback, and the monitoring system (8) displays the operating status and environmental information of the folding arm crane in real time; The high-performance controller (7) is provided with an image processing unit (71), and the high-definition binocular camera (1) and the high-definition monocular camera (2) are connected to the image processing unit (71) for communication feedback; A point cloud processing unit (72), the laser radar (3) being connected to the point cloud processing unit (72) for communication feedback; A three-dimensional reconstruction unit (73), wherein the point cloud processing unit (72) is connected to the three-dimensional reconstruction unit (73) for communication feedback; The obstacle avoidance planning unit (74), the laser distance measuring sensor (4), the acceleration sensor (5), the image processing unit (71) and the three-dimensional reconstruction unit (73) are connected to the obstacle avoidance planning unit (74) for communication feedback; An obstacle avoidance control unit (75), the obstacle avoidance planning unit (74) is connected to the obstacle avoidance control unit (75) by communication feedback, and the obstacle avoidance control unit (75) is connected to the control device (6) by communication.

2. The intelligent monitoring and obstacle avoidance system for an offshore folding arm crane according to claim 1 is characterized in that: The control device (6) is connected to a manual control unit (61) and an automatic control unit (62), and the obstacle avoidance control unit (75) is connected to the control device (6) through a communication control method via the automatic control unit (62).

3. The intelligent monitoring and obstacle avoidance system for an offshore folding arm crane according to claim 2 is characterized in that: The automatic control unit (62) is connected to an obstacle avoidance mode unit (64) and a non-obstacle avoidance mode unit (65), and the automatic control unit (62) controls the control device (6) to avoid obstacles or not avoid obstacles through communication between the obstacle avoidance mode unit (64) and the non-obstacle avoidance mode unit (65).

4. The intelligent monitoring and obstacle avoidance system for an offshore folding arm crane according to claim 3 is characterized in that: A control switching switch (63) is connected between the manual control unit (61) and the automatic control unit (62), and an obstacle avoidance switching switch (66) is connected between the obstacle avoidance mode unit (64) and the non-obstacle avoidance mode unit (65).

5. The intelligent monitoring and obstacle avoidance system for an offshore folding arm crane according to claim 1 is characterized in that: The monitoring system (8) is connected to a display unit (81), a plurality of sub-display units (811) are arranged in the display unit (81), and the high-definition binocular camera (1), the high-definition monocular camera (2), the laser radar (3), the laser ranging sensor (4), the acceleration sensor (5), the image processing unit (71), the point cloud processing unit (72), the three-dimensional reconstruction unit (73), the obstacle avoidance planning unit (74), and the obstacle avoidance control unit (75) are all connected to the corresponding sub-display units (811) for communication feedback.

6. The intelligent monitoring and obstacle avoidance system for an offshore folding arm crane according to claim 1, characterized in that: The obstacle avoidance planning unit (74) is connected to an alarm unit (9), and the alarm unit (9) is one or more of a photoelectric alarm (91) and a voice alarm (92).

7. The intelligent monitoring and obstacle avoidance system for an offshore folding arm crane according to claim 1, characterized in that: The high-performance controller (7) is connected to a database (10) for communication feedback, and data received and input by an image processing unit (71), a point cloud processing unit (72), a three-dimensional reconstruction unit (73), an obstacle avoidance planning unit (74), and an obstacle avoidance control unit (75) in the high-performance controller (7) are all stored in the database (10).

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