Steel bar binding machine operation control method and device based on intelligent path planning

Abstract

The invention relates to a steel bar binding machine operation control method based on intelligent path planning, and the method comprises the steps: obtaining an accurate and efficient optimal operation path through a path planning algorithm according to an initial position, an end position and a to-be-operated position through which the steel bar binding machine must pass of the steel bar binding machine; in the actual application scene of the reinforcing steel bar binding machine, the theoretical time length for binding and the unit distance movement time length between the nodes should be the same, the delay level value between the node sections is calculated on the basis, and an obviously overlarge value (that is, the unit processing time is too long) is found out on the basis of the delay level value; and performing continuous efficiency analysis on the node segment based on the delay level value, performing machine maintenance early warning to inform an administrator to check when an efficiency fluctuation event exists, evaluating the fluctuation condition of the value in the monitoring period in the above monitoring period, and informing operation and maintenance personnel to perform maintenance check when the fluctuation condition is too large. The reinforcing steel bar binding machine is ensured to be in a high-efficiency state, and development of actual business is facilitated.

Description

Technical Field

[0001] This invention relates to the technical field of rebar tying machines, and in particular to a rebar tying machine operation control method and device based on intelligent path planning. Background Technology

[0002] Rebar tying machines are widely used in the field of rebar tying due to their advantages of being fast and efficient, saving manpower, standardized operation, high safety, and 3-4 times more efficient than manual labor.

[0003] Existing rebar tying machines typically operate in a semi-automatic mode, requiring manual operation to move the machine to the designated position for rebar tying. This method still demands a significant workforce and requires workers to have a high level of knowledge about rebar tying machines. Furthermore, while some rebar tying machines possess intelligent path planning capabilities, their maintenance is difficult to manage. When problems arise, it's challenging to quickly pinpoint the exact time of the fault, necessitating thorough quality checks throughout the entire process, resulting in lower efficiency. Summary of the Invention

[0004] The purpose of this invention is to at least address one of the shortcomings of the prior art and provide a rebar tying machine operation control method based on intelligent path planning.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] Specifically, a method for controlling the operation of a rebar tying machine based on intelligent path planning is proposed, including the following:

[0007] The stop position of the operation is recorded as the termination position, and the current position of the rebar tying machine is recorded as the initial position;

[0008] Acquire the first image data captured by the camera, and perform image recognition based on the image data to obtain the location to be worked;

[0009] The work path is obtained by path planning based on the initial position, the ending position, and the position to be worked.

[0010] The rebar tying machine operates based on the work path control;

[0011] In addition, during the operation, the initial position, the position to be operated, and the termination position are regarded as path nodes. The movement time T1 between each pair of adjacent path nodes, i.e., node segments, is calculated and the actual straight-line distance L between the nodes is obtained.

[0012] Calculate T1 / L+T2 and record it as the delay level value of the current node segment. Determine whether the delay level value of any node segment is higher than the first threshold. If so, mark the node segment as abnormal and issue an alarm.

[0013] Based on the delay level, continuous efficiency analysis is performed on the node segment, and when there is an efficiency fluctuation event, machine maintenance warning is issued to notify the administrator for review.

[0014] Furthermore, specifically, the task path is obtained by using Dijkstra's algorithm to plan the path based on the initial position, the ending position, and the position to be worked.

[0015] Furthermore, specifically, the process of performing continuous efficiency analysis on node segments based on delay level values, and issuing machine maintenance early warnings when efficiency fluctuation events occur, includes:

[0016] Set up a monitoring window such that there are exactly Q consecutive node segments in each monitoring window, and establish a two-dimensional plane coordinate system with the node segment number as the x-axis coordinate and the delay level value as the y-axis coordinate. At this time, there are Q first data points in the two-dimensional plane coordinate system of the data in the monitoring window. Curve fitting is performed on these Q first data points to obtain the delay level curve under the current monitoring window.

[0017] The monitoring window is shifted to the right so that there are exactly Q consecutive node segments in the monitoring window after the shift that are continuous with those in the monitoring window before the shift. At this time, there are Q second data points in the two-dimensional plane coordinate system of the monitoring window.

[0018] The delay level curve is shifted to the right by Q units to obtain the time-domain aligned delay level curve.

[0019] At this point, the shortest distances from the Q second data points to the time-domain aligned delay horizontal curve are calculated to obtain the Q shortest distances;

[0020] The number of shortest distances exceeding the distance scale threshold among the Q shortest distances is denoted as M;

[0021] Determine if M is greater than the scale threshold. If it is greater than the scale threshold, determine that there is an efficiency fluctuation event. If it is not greater than the scale threshold, determine that there is no efficiency fluctuation event.

[0022] Furthermore, the method also includes real-time automatic obstacle avoidance during the operation, wherein the automatic obstacle avoidance includes,

[0023] The system acquires second image data from a camera and radar data from a ranging lidar in real time. It performs image recognition on the second image data to obtain the location of the first obstacle and analyzes the radar data to obtain the location of the second obstacle. Based on the locations of the first and second obstacles, it determines the final location of the obstacle and performs automatic obstacle avoidance based on the final location.

[0024] Furthermore, specifically, the process of determining the final location of the obstacle includes:

[0025] First, define the world coordinate system WCS as fixed on the horizontal plane, with the origin O(0,0), the X-axis as the forward direction, and the Y-axis as the horizontal direction. The camera coordinate system CCS is based on the camera's optical center as the origin, and the ranging lidar coordinate system LS is based on the laser emitter, with the measurement direction parallel to the camera's optical axis on the horizontal plane.

[0026] The coordinate transformation relationship between the camera and the ranging lidar is obtained by hand-eye calibration. After distortion correction of the camera data, the position of the first obstacle (X_cam, Y_cam) is obtained by recognition through a lightweight CNN.

[0027] The location of the second obstacle, i.e., the distance d between the obstacle and the rebar tying machine, is obtained by analyzing the radar data;

[0028] The final position of the obstacle is obtained by solving for (X_cam, Y_cam) and distance d based on the constraint relationship.

[0029] Furthermore, specifically, the final position of the obstacle is obtained by solving for (X_cam, Y_cam) and distance d based on the constraint relationship, including:

[0030] Based on the camera's field of view constraint, we can obtain:

[0031]

[0032] Where f_x and f_y are the focal lengths of the camera in the x and y axes, respectively;

[0033] Laser ranging radar exists:

[0034]

[0035] Where X_laser and Y_laser are the x and y coordinates of the second obstacle's position, respectively;

[0036] Since the measurement direction of the ranging lidar is parallel to the horizontal plane and the optical axis of the camera, Y_laser = 0.

[0037] At this point, the conversion from CCS coordinates to WCS exists:

[0038] X_world = X_cam + T_x;

[0039] Y_world = Y_cam + T_y;

[0040] Based on the hand-eye alignment relationship, we have:

[0041] t*f_x = X_laser + T_x;

[0042] t*f_y=Y_laser+T_y;

[0043] Solving the above relationship yields:

[0044]

[0045] Y_world = t*f_y + T_y;

[0046] The final position of the obstacle, i.e., its world coordinates, is:

[0047] X_world = d + T_x;

[0048]

[0049] Where T_x and T_y are the translational components of the camera and the ranging lidar in the x and y axes, respectively, in the hand-eye calibration relationship.

[0050] Furthermore, specifically, automatic obstacle avoidance based on the final position includes:

[0051] A preset safety distance is established. It is determined whether the number P of obstacles smaller than the preset safety distance is 1. If so, the next node to be reached in the work path is obtained, and the rebar tying machine is controlled to deflect at a preset angle between the obstacle and the next node to be reached to avoid the obstacle. If the number of obstacles is greater than 1, the distance D between each pair of obstacles is calculated based on the final position of the obstacles, and all pairs of obstacles with a distance D greater than a distance threshold are found. The pair of obstacles closest to the next node to be reached is selected, and the rebar tying machine is controlled to move towards the midpoint of the line connecting the pairs of obstacles to avoid the obstacle.

[0052] This invention also proposes a rebar tying machine operation control device based on intelligent path planning, comprising the following:

[0053] The position acquisition module is used to acquire the work stop position as the termination position and the current position of the rebar tying machine as the initial position.

[0054] The image acquisition module is used to acquire the first image data captured by the camera, and to perform image recognition based on the image data to obtain the position to be worked.

[0055] The job path planning module is used to plan the job path based on the initial position, the ending position, and the position to be done.

[0056] The operation control module is used to control the rebar tying machine to perform operations based on the operation path.

[0057] The anomaly analysis module is used to treat the initial position, the position to be done, and the termination position as path nodes during the operation, to calculate the movement time T1 between any two adjacent path nodes, i.e., node segments, and to obtain the actual straight-line distance L between the nodes.

[0058] Calculate T1 / L+T2 and record it as the delay level value of the current node segment. Determine whether the delay level value of any node segment is higher than the first threshold. If so, mark the node segment as abnormal and issue an alarm.

[0059] Based on the delay level, continuous efficiency analysis is performed on the node segment, and when there is an efficiency fluctuation event, machine maintenance warning is issued to notify the administrator for review.

[0060] The beneficial effects of this invention are as follows:

[0061] This invention proposes a method and device for controlling the operation of a rebar tying machine based on intelligent path planning. First, based on the initial position, ending position, and necessary work locations of the rebar tying machine, an accurate and efficient optimal work path is obtained through a path planning algorithm. After completing the path planning, considering that in the actual application scenario of the rebar tying machine, the theoretical time for tying and the unit distance movement time between nodes should be the same, the delay level value between node segments is calculated based on this, and significantly excessive values ​​(i.e., unit processing time is too long) are identified and alarms are triggered. The fluctuation of this value in the current monitoring period is evaluated based on the previous monitoring period. When the fluctuation is too large, the operation and maintenance personnel are notified to inspect and check, ensuring that the rebar tying machine is in a high-efficiency state to facilitate the actual operation. Attached Figure Description

[0062] The above and other features of this disclosure will become more apparent from the detailed description of the embodiments illustrated in conjunction with the accompanying drawings. In the accompanying drawings, the same reference numerals denote the same or similar elements. Obviously, the drawings described below are merely some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort. In the drawings:

[0063] Figure 1 The diagram shows a flowchart of the rebar tying machine operation control method based on intelligent path planning according to the present invention.

[0064] Figure 2 The diagram shown is a structural schematic of a rebar tying machine in a preferred embodiment of the present invention. Detailed Implementation

[0065] The following will provide a clear and complete description of the concept, specific structure, and technical effects of the present invention in conjunction with embodiments and accompanying drawings, so as to fully understand the purpose, solution, and effects of the present invention. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The same reference numerals used throughout the accompanying drawings indicate the same or similar parts.

[0066] Example 1, referring to Figure 1 This invention proposes a rebar tying machine operation control method based on intelligent path planning, including the following:

[0067] Step 110: Obtain the work stop position and record it as the termination position, and record the current position of the rebar tying machine as the initial position;

[0068] Step 120: Obtain the first image data captured by the camera, and perform image recognition based on the image data to obtain the location to be worked;

[0069] Step 130: Based on the initial position, the ending position, and the position to be worked, perform path planning to obtain the work path;

[0070] Step 140: Control the rebar tying machine to perform operations based on the work path.

[0071] In addition, during the operation, the initial position, the position to be operated, and the termination position are regarded as path nodes. The movement time T1 between each pair of adjacent path nodes, i.e., node segments, is calculated and the actual straight-line distance L between the nodes is obtained.

[0072] Calculate T1 / L+T2 and record it as the delay level value of the current node segment. Determine whether the delay level value of any node segment is higher than the first threshold. If so, mark the node segment as abnormal and issue an alarm.

[0073] Based on the delay level, continuous efficiency analysis is performed on the node segment, and when there is an efficiency fluctuation event, machine maintenance warning is issued to notify the administrator for review.

[0074] In this embodiment 1, firstly, based on the initial position, termination position, and necessary work positions of the rebar tying machine, an accurate and efficient optimal work path is obtained through a path planning algorithm. After completing the path planning, considering that in the actual application scenario of the rebar tying machine, the theoretical time for tying and the unit distance movement time between nodes should be the same, the delay level value between node segments is calculated based on this, and a significantly excessive value (i.e., the unit processing time is too long) is identified and an alarm is issued. The fluctuation of this value in the current monitoring period is evaluated based on the previous monitoring period. When the fluctuation is too large, the operation and maintenance personnel are notified to carry out maintenance and inspection to ensure that the rebar tying machine is in a high-efficiency state, which is conducive to the actual business operation.

[0075] Reference Figure 2 Furthermore, as a preferred embodiment, the automatic rebar tying machine used in this invention includes the following:

[0076] MCU module;

[0077] The camera module, electrically connected to the MCU module, is used for image acquisition of the work area;

[0078] The ranging radar, also known as the ranging lidar, is electrically connected to the MCU module and is used to emit ultrasonic waves for active ranging and to detect the surrounding environment and obstacles.

[0079] The path planning module is electrically connected to the MCU and is used for planning the job path;

[0080] The communication module, electrically connected to the MCU, is built based on 5G technology and is used to enable the automatic rebar tying machine to communicate and interact with other terminal devices;

[0081] The power module, electrically connected to the MCU, is used to drive the tracked vehicle of the automatic rebar tying machine.

[0082] The power module, electrically connected to the MCU module, is used to supply power to the entire automatic rebar tying machine;

[0083] After receiving the work area image captured by the camera module, the MCU module performs image recognition on the work area image to obtain the image recognition result. Based on the image recognition result, the path planning module plans the work path and actively avoids obstacles by using the distance measuring radar feedback data. During this process, the communication module sends real-time work information and automatic rebar binding machine equipment information to the cloud for display. The cloud can remotely and actively control the MCU module to operate.

[0084] In this preferred embodiment, based on cameras, ranging radar, intelligent voice, and mobile network communication, the unmanned, intelligent, efficient, and low-cost rebar tying on construction sites can be achieved, while also enabling 24 / 7 uninterrupted operation. Furthermore, it can fully utilize mobile communication to provide cloud monitoring and control functions, bringing convenience to rebar tying users on construction sites. After the camera module acquires images of the work area, it first performs connected component analysis preprocessing on each image to eliminate background noise interference and interference from other small contours. Then, the preprocessed image set is input into a pre-trained neural network for analysis of the work location, which can significantly improve the operating efficiency of the neural network and the accuracy of the results.

[0085] During operation, the MCU receives information from the camera and ranging radar, receives commands from the voice module, and calculates the tracked vehicle's motion parameters through the intelligent path planning module, sending these parameters to the tracked vehicle's drive motor. The battery module provides power to the system. After the tracked vehicle reaches the designated location, the MCU controls the intelligent lashing machine to perform the lashing operation. After one node is lashed, the next node is lashed, and so on, until the entire area is lashed. The communication module sends the real-time operation information and vehicle information to the cloud for display, and the cloud can also remotely control the main control board.

[0086] In a preferred embodiment of the present invention, the work path is obtained by using the Dijkstra algorithm to perform path planning based on the initial position, the ending position, and the position to be worked.

[0087] In this preferred embodiment, considering the actual needs in the scenario of rebar tying (high work efficiency is required), Dijkstra's algorithm is used for path planning to find the shortest path and ensure work efficiency.

[0088] As a preferred embodiment of the present invention, specifically, the process of performing continuous efficiency analysis on node segments based on delay level values ​​and issuing machine maintenance early warnings when efficiency fluctuation events occur includes:

[0089] Set up a monitoring window such that there are exactly Q consecutive node segments in each monitoring window, and establish a two-dimensional plane coordinate system with the node segment number as the x-axis coordinate and the delay level value as the y-axis coordinate. At this time, there are Q first data points in the two-dimensional plane coordinate system of the data in the monitoring window. Curve fitting is performed on these Q first data points to obtain the delay level curve under the current monitoring window.

[0090] The monitoring window is shifted to the right so that the moved monitoring window contains exactly Q consecutive node segments that are continuous with the monitoring window before the shift (that is, the number of node segments between two adjacent monitoring windows is the same, both are Q and are continuous with each other). At this time, the data in the monitoring window has Q second data points in the two-dimensional plane coordinate system.

[0091] The delay level curve is shifted to the right by Q units to obtain the time-domain aligned delay level curve.

[0092] At this point, the shortest distances from the Q second data points to the time-domain aligned delay horizontal curve are calculated to obtain the Q shortest distances;

[0093] The number of shortest distances exceeding the distance scale threshold among the Q shortest distances is denoted as M;

[0094] Determine if M is greater than the scale threshold. If it is greater than the scale threshold, determine that there is an efficiency fluctuation event. If it is not greater than the scale threshold, determine that there is no efficiency fluctuation event.

[0095] In this preferred embodiment, the above monitoring cycle (i.e. the node segment content included in the previous monitoring window) is used to assess the fluctuation of the value in the current monitoring cycle. When the fluctuation is too large, the operation and maintenance personnel are notified to carry out inspection and maintenance to ensure that the rebar tying machine is in a high-efficiency state and facilitates the actual operation.

[0096] In a preferred embodiment of the present invention, the method further includes real-time automatic obstacle avoidance during the operation, wherein the automatic obstacle avoidance includes...

[0097] The system acquires second image data from a camera and radar data from a ranging lidar in real time. It performs image recognition on the second image data to obtain the location of the first obstacle and analyzes the radar data to obtain the location of the second obstacle. Based on the locations of the first and second obstacles, it determines the final location of the obstacle and performs automatic obstacle avoidance based on the final location.

[0098] In a preferred embodiment of the present invention, the process of determining the final position of the obstacle specifically includes:

[0099] First, define the world coordinate system WCS as fixed on the horizontal plane, with the origin O(0,0), the X-axis as the forward direction, and the Y-axis as the horizontal direction. The camera coordinate system CCS is based on the camera's optical center as the origin, and the ranging lidar coordinate system LS is based on the laser emitter, with the measurement direction parallel to the camera's optical axis on the horizontal plane.

[0100] The coordinate transformation relationship between the camera and the ranging lidar is obtained by hand-eye calibration. After distortion correction of the camera data, the position of the first obstacle (X_cam, Y_cam) is obtained by recognition through a lightweight CNN.

[0101] The location of the second obstacle, i.e., the distance d between the obstacle and the rebar tying machine, is obtained by analyzing the radar data;

[0102] The final position of the obstacle is obtained by solving for (X_cam, Y_cam) and distance d based on the constraint relationship.

[0103] In a preferred embodiment of the present invention, specifically, the final position of the obstacle is obtained by solving for (X_cam, Y_cam) and distance d based on the constraint relationship.

[0104] Based on the camera's field of view constraint, we can obtain:

[0105]

[0106] Where f_x and f_y are the focal lengths of the camera in the x and y axes, respectively;

[0107] Laser ranging radar exists:

[0108]

[0109] Where X_laser and Y_laser are the x and y coordinates of the second obstacle's position, respectively;

[0110] Since the measurement direction of the ranging lidar is parallel to the horizontal plane and the optical axis of the camera, Y_laser = 0.

[0111] At this point, the conversion from CCS coordinates to WCS exists:

[0112] X_world = X_cam + T_x;

[0113] Y_world = Y_cam + T_y;

[0114] Based on the hand-eye alignment relationship, we have:

[0115] t*f_x = X_laser + T_x;

[0116] t*f_y=Y_laser+T_y;

[0117] Solving the above relationship yields:

[0118]

[0119] Y_world = t*f_y + T_y;

[0120] The final position of the obstacle, i.e., its world coordinates, is:

[0121] X_world = d + T_x;

[0122]

[0123] Where T_x and T_y are the translational components of the camera and the ranging lidar in the x and y axes, respectively, in the hand-eye calibration relationship.

[0124] In this preferred embodiment, by means of the above method, the world position coordinates of the obstacle can be quickly determined by combining image recognition of the image captured by the camera with the ranging data of the ranging lidar.

[0125] As a preferred embodiment of the present invention, specifically, automatic obstacle avoidance based on the final position includes:

[0126] A preset safety distance is established. It is determined whether the number P of obstacles smaller than the preset safety distance is 1. If so, the next node to be reached in the work path is obtained, and the rebar tying machine is controlled to deflect at a preset angle between the obstacle and the next node to be reached to avoid the obstacle. If the number of obstacles is greater than 1, the distance D between each pair of obstacles is calculated based on the final position of the obstacles, and all pairs of obstacles with a distance D greater than a distance threshold are found. The pair of obstacles closest to the next node to be reached is selected, and the rebar tying machine is controlled to move towards the midpoint of the line connecting the pairs of obstacles to avoid the obstacle.

[0127] In this preferred embodiment, considering the obstacle avoidance characteristics of the actual working scenario of the rebar tying machine, namely that there are not many obstacles and most of the obstacles are not complicated, the actual position of the obstacle group is first obtained quickly by the camera and the ranging lidar, and then the obstacle avoidance is carried out quickly according to the relative positional relationship between the obstacle group and the planned path, so as to ensure safe obstacle avoidance while ensuring work efficiency.

[0128] Example 2: The present invention also proposes a rebar tying machine operation control device based on intelligent path planning, comprising the following:

[0129] The position acquisition module is used to acquire the work stop position as the termination position and the current position of the rebar tying machine as the initial position.

[0130] The image acquisition module is used to acquire the first image data captured by the camera, and to perform image recognition based on the image data to obtain the position to be worked.

[0131] The job path planning module is used to plan the job path based on the initial position, the ending position, and the position to be done.

[0132] The operation control module is used to control the rebar tying machine to perform operations based on the operation path.

[0133] The anomaly analysis module is used to treat the initial position, the position to be done, and the termination position as path nodes during the operation, to calculate the movement time T1 between any two adjacent path nodes, i.e., node segments, and to obtain the actual straight-line distance L between the nodes.

[0134] Calculate T1 / L+T2 and record it as the delay level value of the current node segment. Determine whether the delay level value of any node segment is higher than the first threshold. If so, mark the node segment as abnormal and issue an alarm.

[0135] Based on the delay level, continuous efficiency analysis is performed on the node segment, and when there is an efficiency fluctuation event, machine maintenance warning is issued to notify the administrator for review.

[0136] Although the description of the invention has been quite detailed and particularly of several described embodiments, it is not intended to limit it to any of these details or embodiments or any particular embodiment, but should be considered as providing a broad possible interpretation of the claims by referring to the appended claims and taking into account the prior art, thereby effectively covering the intended scope of the invention. Furthermore, the invention has been described above with respect to embodiments foreseeable by the inventors in order to provide a useful description, and non-substantial modifications to the invention that have not yet been foreseen may still represent equivalent modifications.

[0137] The above description is merely a preferred embodiment of the present invention. The present invention is not limited to the above-described embodiments. Any embodiment that achieves the technical effects of the present invention using the same means should fall within the protection scope of the present invention. Within the protection scope of the present invention, various modifications and variations can be made to the technical solutions and / or implementation methods.

Claims

1. A method for controlling the operation of a rebar tying machine based on intelligent path planning, characterized in that, Including the following: The stop position of the operation is recorded as the termination position, and the current position of the rebar tying machine is recorded as the initial position; Acquire the first image data captured by the camera, and perform image recognition based on the image data to obtain the location to be worked; The work path is obtained by path planning based on the initial position, the ending position, and the position to be worked. The rebar tying machine operates based on the work path control; In addition, during the operation, the initial position, the position to be operated, and the termination position are regarded as path nodes. The movement time T1 between each pair of adjacent path nodes, i.e., node segments, is calculated and the actual straight-line distance L between the nodes is obtained. Calculate T1 / L+T2 and record it as the delay level value of the current node segment. Determine whether the delay level value of any node segment is higher than the first threshold. If so, mark the node segment as abnormal and issue an alarm. Based on the delay level, continuous efficiency analysis is performed on the node segment, and when there is an efficiency fluctuation event, machine maintenance warning is issued to notify the administrator for review.

2. The rebar tying machine operation control method based on intelligent path planning according to claim 1, characterized in that, Specifically, the task path is obtained by using Dijkstra's algorithm to plan the path based on the initial position, the ending position, and the position to be worked.

3. The rebar tying machine operation control method based on intelligent path planning according to claim 1, characterized in that, Specifically, the process of performing continuous efficiency analysis on node segments based on delay level values ​​and issuing machine maintenance early warnings when efficiency fluctuation events occur includes: Set up a monitoring window such that there are exactly Q consecutive node segments in each monitoring window, and establish a two-dimensional plane coordinate system with the node segment number as the x-axis coordinate and the delay level value as the y-axis coordinate. At this time, there are Q first data points in the two-dimensional plane coordinate system of the data in the monitoring window. Curve fitting is performed on these Q first data points to obtain the delay level curve under the current monitoring window. The monitoring window is shifted to the right so that there are exactly Q consecutive node segments in the monitoring window after the shift that are continuous with those in the monitoring window before the shift. At this time, there are Q second data points in the two-dimensional plane coordinate system of the monitoring window. The delay level curve is shifted to the right by Q units to obtain the time-domain aligned delay level curve. At this point, the shortest distances from the Q second data points to the time-domain aligned delay horizontal curve are calculated to obtain the Q shortest distances; The number of shortest distances exceeding the distance scale threshold among the Q shortest distances is denoted as M; Determine if M is greater than the scale threshold. If it is greater than the scale threshold, determine that there is an efficiency fluctuation event. If it is not greater than the scale threshold, determine that there is no efficiency fluctuation event.

4. The rebar tying machine operation control method based on intelligent path planning according to claim 1, characterized in that, The method also includes real-time automatic obstacle avoidance during the operation, wherein the automatic obstacle avoidance includes... The system acquires second image data from a camera and radar data from a ranging lidar in real time. It performs image recognition on the second image data to obtain the location of the first obstacle and analyzes the radar data to obtain the location of the second obstacle. Based on the locations of the first and second obstacles, it determines the final location of the obstacle and performs automatic obstacle avoidance based on the final location.

5. The rebar tying machine operation control method based on intelligent path planning according to claim 4, characterized in that, Specifically, the process of determining the final location of an obstacle includes: First, define the world coordinate system WCS as fixed on the horizontal plane, with the origin O(0,0), the X-axis as the forward direction, and the Y-axis as the horizontal direction. The camera coordinate system CCS is based on the camera's optical center as the origin, and the ranging lidar coordinate system LS is based on the laser emitter, with the measurement direction parallel to the camera's optical axis on the horizontal plane. The coordinate transformation relationship between the camera and the ranging lidar is obtained by hand-eye calibration. After distortion correction of the camera data, the position of the first obstacle (X_cam, Y_cam) is obtained by recognition through a lightweight CNN. The location of the second obstacle, i.e., the distance d between the obstacle and the rebar tying machine, is obtained by analyzing the radar data; The final position of the obstacle is obtained by solving for (X_cam, Y_cam) and distance d based on the constraint relationship.

6. The rebar tying machine operation control method based on intelligent path planning according to claim 5, characterized in that, Specifically, the final position of the obstacle is obtained by solving for (X_cam, Y_cam) and distance d based on the constraint relationship, including: Based on the camera's field of view constraint, we can obtain: Where f_x and f_y are the focal lengths of the camera in the x and y axes, respectively; Laser ranging radar exists: Where X_laser and Y_laser are the x and y coordinates of the second obstacle's position, respectively; Since the measurement direction of the ranging lidar is parallel to the horizontal plane and the optical axis of the camera, Y_laser = 0. At this point, the conversion from CCS coordinates to WCS exists: X_world = X_cam + T_x; Y_world = Y_cam + T_y; Based on the hand-eye alignment relationship, we have: t*f_x = X_laser + T_x; t*f_y=Y_laser+T_y; Solving the above relationship yields: Y_world = t*f_y + T_y; The final position of the obstacle, i.e., its world coordinates, is: X_world = d + T_x; Where T_x and T_y are the translational components of the camera and the ranging lidar in the x and y axes, respectively, in the hand-eye calibration relationship.

7. The rebar tying machine operation control method based on intelligent path planning according to claim 4, characterized in that, Specifically, automatic obstacle avoidance based on the final position includes: A preset safety distance is established. It is determined whether the number P of obstacles smaller than the preset safety distance is 1. If so, the next node to be reached in the work path is obtained, and the rebar tying machine is controlled to deflect at a preset angle between the obstacle and the next node to be reached to avoid the obstacle. If the number of obstacles is greater than 1, the distance D between each pair of obstacles is calculated based on the final position of the obstacles, and all pairs of obstacles with a distance D greater than a distance threshold are found. The pair of obstacles closest to the next node to be reached is selected, and the rebar tying machine is controlled to move towards the midpoint of the line connecting the pairs of obstacles to avoid the obstacle.

8. A rebar tying machine operation control device based on intelligent path planning, characterized in that, Including the following: The position acquisition module is used to acquire the work stop position as the termination position and the current position of the rebar tying machine as the initial position. The image acquisition module is used to acquire the first image data captured by the camera, and to perform image recognition based on the image data to obtain the position to be worked. The job path planning module is used to plan the job path based on the initial position, the ending position, and the position to be done. The operation control module is used to control the rebar tying machine to perform operations based on the operation path. The anomaly analysis module is used to treat the initial position, the position to be worked, and the termination position as path nodes during the operation, to calculate the movement time T1 between each pair of adjacent path nodes, i.e., node segments, and to obtain the actual straight-line distance L between the nodes. Calculate T1 / L+T2 and record it as the delay level value of the current node segment. Determine whether the delay level value of any node segment is higher than the first threshold. If so, mark the node segment as abnormal and issue an alarm. Based on the delay level, continuous efficiency analysis is performed on the node segment, and when there is an efficiency fluctuation event, machine maintenance warning is issued to notify the administrator for review.

Images