A method, device and electronic equipment for controlling a crane hoist

Abstract

A method, device and electronic equipment for controlling a crane hoist relate to the field of lifting machinery. In this method, an image sequence of the hoist is obtained; feature extraction and target detection are performed on each image to obtain the pixel coordinates of the two ends of the hoist; the tilt angle of the hoist in each image is calculated to obtain a swing angle sequence; it is determined whether the hoist is in an abnormal swing state, and the target swing angle is determined from the swing angle sequence; if it is determined that the hoist is in an abnormal swing state, the swing angle difference of the target swing angle relative to the preset swing angle range is calculated; based on the swing angle difference, a compensation force is generated and applied to the hoist, and the compensation direction of the compensation force is opposite to the swing direction of the hoist. By implementing the technical solution provided in this application, a compensation force is automatically generated based on the swing angle difference, abnormal swinging of the hoist is suppressed, and the safety of the lifting operation is improved.

Description

Technical Field

[0001] The present application relates to a field, and in particular to a method, device and electronic equipment for controlling a crane hoist. Background Art

[0002] With the continuous advancement of industrial automation and intelligentization, cranes and crane-mounted spreaders are increasingly used in manufacturing, port logistics, construction, and other fields. These devices play a vital role in improving operational efficiency and reducing labor costs. Cranes and spreaders are particularly indispensable for heavy object handling and precise positioning.

[0003] Currently, due to the complex and ever-changing operating environment, numerous external disturbances, and the inherent flexibility of spreaders, spreaders are prone to swinging during operation. This swinging spreader can cause the load to sway and impact. Traditional methods rely on operators manually adjusting and stabilizing the spreader, which can easily lead to safety accidents and pose a low safety risk.

[0004] Therefore, there is an urgent need for a method, device and electronic equipment for controlling a crane hoist. Summary of the Invention

[0005] The present application provides a method, device and electronic equipment for controlling a crane's hoist, which automatically generates a compensation force according to a swing angle difference, suppresses abnormal swinging of the hoist, and improves the safety of lifting operations.

[0006] In a first aspect of the present application, a method for controlling a crane spreader is provided, the method comprising: acquiring an image sequence of the spreader, the image sequence comprising a plurality of continuous images; performing feature extraction and target detection on each of the images to obtain pixel coordinates of both ends of the spreader; calculating, based on the pixel coordinates, the inclination angle of the spreader in each of the images to obtain a swing angle sequence; judging, based on the swing angle sequence, whether the spreader is in an abnormal swing state, and determining a target swing angle from the swing angle sequence; if it is determined that the spreader is in an abnormal swing state, calculating a swing angle difference between the target swing angle and a preset swing angle range, the swing angle difference being an offset of the target swing angle relative to the preset swing angle range; generating a compensation force based on the swing angle difference, and applying the compensation force to the spreader, the compensation direction of the compensation force being opposite to the swing direction of the spreader.

[0007] By adopting the above technical solution, a continuous image sequence of the spreader is acquired, feature extraction and target detection are performed on the images, the spreader's tilt angle is calculated to obtain a swing angle sequence, the spreader's abnormal swing state is determined, the target swing angle is determined, the swing angle difference is calculated, and a compensation force is generated and applied to the spreader. This achieves real-time monitoring and active control of the spreader's swing state. By analyzing and judging the swing angle sequence, abnormal swing states of the spreader can be accurately identified, providing a basis for subsequent control decisions. Generating a compensation force based on the swing angle difference and applying it to the spreader can effectively suppress abnormal swing of the spreader, quickly restoring it to a safe and stable working state, avoiding manual operation and improving the safety and reliability of lifting operations.

[0008] Optionally, judging whether the spreader is in an abnormal swinging state based on the swinging angle sequence and determining a target swinging angle from the swinging angle sequence specifically includes: calculating statistical characteristic values of the swinging angle sequence, the statistical characteristic values including a mean, a square, a maximum value and a minimum value; if the swinging angle values included in the swinging angle sequence are all within the preset swinging angle range, and the variance is less than a preset variance threshold, determining that the spreader is in a normal swinging state, and using the mean as the target swinging angle; if the swinging angle values included in the swinging angle sequence are all within the preset swinging angle range, and the variance is greater than or equal to a preset variance threshold, determining that the spreader is in an abnormal swinging state, and using the sum of the mean and the variance weighted according to a preset weight as the target swing angle; if the maximum value or the minimum value is not within the preset swinging angle range, determining that the spreader is in an abnormal swinging state, and using the maximum value or the minimum value as the target swing angle.

[0009] By employing this technical solution, by calculating the mean, variance, maximum, and minimum statistical eigenvalues of the swing angle sequence and comprehensively considering the average level, dispersion, and extreme values of the swing angle, it is possible to accurately determine whether the spreader is in an abnormal swing state and determine the appropriate target swing angle. By leveraging the statistical characteristics of the swing angle sequence, it is possible to accurately identify different degrees of abnormal swing. This method, through statistical eigenvalues and graded judgment, enables a detailed assessment and classification of the spreader's swing state, providing a reliable basis for subsequent control decisions and improving the detection rate of abnormal swing and control effectiveness.

[0010] Optionally, calculating the inclination angle of the sling in each of the images based on the pixel coordinates to obtain a swing angle sequence specifically includes: converting the pixel coordinates at both ends of the sling into spatial coordinates in a world coordinate system; calculating the swing angle corresponding to the sling in each of the images based on the spatial coordinates to obtain the swing angle sequence.

[0011] By employing this technical solution, information mapping and state reconstruction from a two-dimensional image to three-dimensional space are achieved by converting the pixel coordinates at the two ends of the spreader into spatial coordinates in a world coordinate system and calculating the spreader's swing angle based on these spatial coordinates. Converting the pixel coordinates to the world coordinate system yields the three-dimensional coordinates of the spreader's two end points, accurately describing the spreader's spatial position and orientation. This method enables accurate assessment of the spreader's swing state. By converting image coordinates to spatial coordinates, visual information is closely linked to the physical world, providing a reliable data foundation for subsequent mechanical analysis and control execution.

[0012] Optionally, converting the pixel coordinates at both ends of the sling into spatial coordinates in the world coordinate system specifically includes: establishing a conversion relationship between the camera coordinate system and the world coordinate system; obtaining the camera's extrinsic parameter matrix, and converting the pixel coordinates into coordinates in the camera coordinate system according to the extrinsic parameter matrix; and converting the coordinates in the camera coordinate system into the spatial coordinate system in the world coordinate system according to the conversion relationship.

[0013] By adopting the above technical solution, a conversion relationship between the camera coordinate system and the world coordinate system is established. The pixel coordinates are converted to the camera coordinate system using the camera extrinsic parameter matrix. Then, the camera coordinates are converted to the world coordinate system based on the coordinate system conversion relationship. This achieves a precise mapping of image coordinates to spatial coordinates. This method utilizes the basic principles of machine vision and photogrammetry. Through the construction and conversion of coordinate systems, it achieves a precise correspondence between image information and spatial information. Through the layer-by-layer conversion of coordinate systems, the local pixel coordinates are connected to the global world coordinates, realizing the transmission and sharing of visual information between different reference systems.

[0014] Optionally, if it is determined that the sling is in an abnormal swinging state, before calculating the swing angle difference of the target swing angle relative to the preset swing angle range, the method also includes: obtaining the upper limit value and the lower limit value of the preset swing angle range; calculating the average value of the upper limit value and the lower limit value, and determining the average value as the preset swing angle; subtracting the preset swing angle from the target swing angle to obtain the swing angle difference.

[0015] By adopting the above technical solution, after determining that the spreader is in an abnormal swing state, the upper and lower limits of the preset swing angle range are obtained, the average value is calculated as the preset swing angle, and the target swing angle is subtracted from the preset swing angle to obtain the swing angle difference, which quantifies the degree to which the spreader's swing state deviates from the normal working range. The preset swing angle range reflects the safe allowable range of the spreader's swing, and the upper and lower limits correspond to the maximum and minimum values of the swing angle under normal working conditions. By averaging the upper and lower limits, a characteristic angle representing the normal swing state can be obtained, which serves as a reference for subsequent deviation calculations. The target swing angle obtained by actual measurement is subtracted from the preset swing angle to obtain the deviation value between the two, which intuitively reflects the size and direction of the spreader's swing state deviating from the normal working range.

[0016] Optionally, the formula for generating the compensation force according to the swing angle difference is specifically:

[0017] F=m(g·tanα+L·α''+2ζwn·(θ'-α')+wn²·(θ-α))

[0018] Wherein, F is the compensation force, m is the total mass of the sling and the load, g is the acceleration of gravity, L is the equivalent suspension length of the sling, θ is the target swing angle, α is the preset swing angle, θ-α is the swing angle difference, θ' is the target angular velocity, α' is the preset angular velocity, α'' is the preset angular acceleration, ζ is the damping ratio, and wn is the natural frequency of the system.

[0019] By adopting the above technical solution, a compensation force calculation formula based on a physical model is proposed. This formula comprehensively considers multiple key parameters of the spreader swing system, such as the total mass of the spreader and the load, gravitational acceleration, the spreader's equivalent suspension length, the target swing angle, the preset swing angle, the swing angle difference, the target angular velocity, the preset angular velocity, the preset angular acceleration, the damping ratio, and the natural frequency, to generate a compensation force that is appropriate for the swing state and control objectives. Based on the dynamic model of the spreader swing, this formula describes the system forces from four perspectives: gravity, inertia, damping, and elasticity. By linearly combining these terms, a comprehensive compensation force expression is derived, which can generate corresponding compensation force effects under different swing states.

[0020] Optionally, after generating a compensation force based on the swing angle difference and applying the compensation force to the sling, the method further includes: obtaining historical swing angle differences; judging the swing trend of the sling based on the historical swing angle differences, and constructing a fitting curve based on the swing trend; predicting the predicted swing angle difference of the sling within a preset time based on the fitting curve; and generating a predicted compensation force based on the predicted swing angle difference.

[0021] By adopting the above technical solution, we further introduce an a priori control strategy based on historical swing angle differences and trend prediction, in addition to the generation and application of compensation force. By obtaining historical swing angle differences over a period of time, we can determine the changing trend of the spreader's swing state, construct a mathematical fitting curve, and use this fitting curve to predict the swing angle differences over a period of time. This is then used to generate a predicted compensation force. By extrapolating the swing angle differences at future moments, we can, to a certain extent, proactively understand the development and changes of the spreader's swing state and take appropriate control measures in advance.

[0022] In a second aspect of the present application, a crane control device for a spreader is provided, the device comprising: an acquisition module and a processing module, wherein: the acquisition module is configured to acquire an image sequence of the spreader, the image sequence comprising a plurality of consecutive images; the processing module is configured to perform feature extraction and target detection on each of the images to obtain pixel coordinates of both ends of the spreader; the processing module is further configured to calculate, based on the pixel coordinates, the inclination angle of the spreader in each of the images to obtain a swing angle sequence; the processing module is further configured to determine, based on the swing angle sequence, whether the spreader is in an abnormal swing state and to determine a target swing angle from the swing angle sequence; the processing module is further configured to calculate, if it is determined that the spreader is in an abnormal swing state, a swing angle difference between the target swing angle and a preset swing angle range, the swing angle difference being an offset of the target swing angle from the preset swing angle range; the processing module is further configured to generate a compensation force based on the swing angle difference and apply the compensation force to the spreader, wherein the compensation direction of the compensation force is opposite to the swing direction of the spreader.

[0023] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs any of the methods described above.

[0024] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions. When the instructions are executed, any one of the methods described above is executed.

[0025] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0026] 1. By acquiring a continuous image sequence of the spreader, performing feature extraction and target detection on the images, calculating the spreader's tilt angle to obtain a swing angle sequence, determining whether the spreader is in an abnormal swing state, determining the target swing angle, calculating the swing angle difference, generating a compensation force, and applying it to the spreader, the system achieves real-time monitoring and active control of the spreader's swing state. By analyzing and determining the swing angle sequence, abnormal spreader swing states can be accurately identified, providing a basis for subsequent control decisions. Generating a compensation force based on the swing angle difference and applying it to the spreader effectively suppresses abnormal spreader swing, quickly restoring the spreader to a safe and stable operating state, and improving the safety and reliability of lifting operations.

[0027] 2. By calculating the mean, variance, maximum, and minimum statistical eigenvalues of the swing angle sequence and comprehensively considering the average level, dispersion, and extreme values of the swing angle, it is possible to accurately determine whether the spreader is in an abnormal swing state and determine the appropriate target swing angle. By leveraging the statistical characteristics of the swing angle sequence, this method can accurately identify different degrees of abnormal swing. Through statistical eigenvalues and graded judgment, this method achieves a detailed assessment and classification of the spreader's swing state, providing a reliable basis for subsequent control decisions and improving the detection rate of abnormal swing and control effectiveness.

[0028] 3. By converting the pixel coordinates at the two ends of the spreader into spatial coordinates in the world coordinate system and calculating the spreader's swing angle based on these spatial coordinates, information mapping and state reconstruction from a two-dimensional image are achieved. Converting the pixel coordinates to the world coordinate system yields the three-dimensional coordinates of the spreader's two end points, accurately describing the spreader's spatial position and orientation. This method enables accurate assessment of the spreader's swing state. This conversion from image coordinates to spatial coordinates closely links visual information with the physical world, providing a reliable data foundation for subsequent mechanical analysis and control execution. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a flow chart of a method for controlling a crane spreader disclosed in an embodiment of the present application;

[0030] Figure 2 This is a module schematic diagram of a crane spreader control device disclosed in an embodiment of the present application;

[0031] Figure 3 This is a structural diagram of an electronic device disclosed in an embodiment of the present application.

[0032] Description of the accompanying drawings: 201, acquisition module; 202, processing module; 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0034] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0035] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0036] This application provides a method for controlling a crane hoist. Figure 1 , Figure 1 This is a flow chart of a method for controlling a crane's spreader provided in an embodiment of the present application. The method is applied to a crane controller and includes steps S101 to S107, which are as follows:

[0037] Step S101: Acquire an image sequence of a spreader, where the image sequence includes a plurality of continuous images.

[0038] In step S101, the controller acquires a sequence of images of the spreader. To achieve this, the controller is connected to one or more visual sensors (e.g., industrial cameras). These visual sensors are pre-installed on the crane by the user to clearly capture the spreader's motion.

[0039] Step S102: performing feature extraction and target detection on each image to obtain the pixel coordinates of the two ends of the spreader.

[0040] In step S102, the controller performs feature extraction on each image in the received image sequence. Through feature extraction, the controller extracts key information from the image that can effectively characterize the sling's characteristics, such as its shape, texture, and edges. Feature extraction methods include SIFT (Scale Invariant Feature Transform), SURF (Speeded Up Robust Features), and ORB (Oriented FAST and Rotation BRIEF). Preferably, in the embodiment of the present application, the SIFT algorithm is employed. The controller first converts the image into a grayscale image and then detects local extreme points at different scales of the image. Through a series of screening and optimization steps, the controller removes low-contrast and unstable key points, ultimately obtaining a set of scale- and rotation-invariant feature points. Each feature point corresponds to a 128-dimensional feature descriptor, which is used to characterize the gradient information of the area surrounding the point.

[0041] After completing feature extraction, the controller further performs target detection to determine the specific location of the sling in the image. Target detection can determine the bounding box and category label of the sling in the image. Target detection algorithms include Faster R-CNN, YOLO (You Only Look Once), and SSD (Single Shot MultiBox Detector). Preferably, the present application adopts the YOLO algorithm. The controller first divides the image into several grids, and each grid is responsible for predicting a set of bounding boxes and category probabilities. The controller performs feature extraction on the image through a convolutional neural network to obtain the prediction results for each grid. Finally, based on the confidence and category probability of the prediction results, the bounding box containing the sling is filtered out, and its position and size information is output. Through target detection, the controller can obtain the pixel coordinates of the sling in the image. Specifically, the two ends of the sling usually correspond to the two vertices of the bounding box, and the controller can directly read the pixel coordinates of these two vertices, such as (x1, y1) and (x2, y2).

[0042] For example, the controller uses the YOLO algorithm to detect an object in an image of a spreader and generates two bounding boxes, one for each of the spreader's left and right ends. The coordinates of the top-left and bottom-right corners of the bounding boxes are (100, 200) and (300, 400), respectively. After post-processing and coordinate conversion, the controller outputs the pixel coordinates of the spreader's ends as (110, 210) and (290, 390).

[0043] Step S103: Calculate the tilt angle of the spreader in each image based on the pixel coordinates to obtain a swing angle sequence.

[0044] In step S103 , the pixel coordinates of the two ends of the spreader are converted into spatial coordinates in the world coordinate system; based on the spatial coordinates, the swing angles of the spreader corresponding to each image are calculated to obtain a swing angle sequence.

[0045] In one possible implementation, the pixel coordinates at both ends of the sling are converted into spatial coordinates in a world coordinate system, specifically including: establishing a conversion relationship between the camera coordinate system and the world coordinate system; obtaining the camera's extrinsic parameter matrix, and converting the pixel coordinates into coordinates in the camera coordinate system based on the extrinsic parameter matrix; and converting the coordinates in the camera coordinate system into a spatial coordinate system in the world coordinate system based on the conversion relationship.

[0046] Specifically, the controller calculates the tilt angle of the spreader in each frame of the image based on the pixel coordinates at both ends of the spreader, thereby obtaining a sequence of swing angles that changes with time. First, the controller converts the pixel coordinates into spatial coordinates in the world coordinate system. This is because the pixel coordinates are only two-dimensional coordinates on the image plane and cannot directly reflect the actual position and posture of the spreader in three-dimensional space. In order to complete this conversion, the controller establishes a mapping relationship between the camera coordinate system and the world coordinate system. The origin of the camera coordinate system is located at the optical center of the camera, the Z axis coincides with the optical axis of the camera, and the X axis and Y axis are parallel to the horizontal and vertical directions of the image plane, respectively. The world coordinate system is a fixed global reference system, and its origin and coordinate axis directions can be set according to actual needs (such as the initial position of the spreader, the base of the crane), which is not limited in this application.

[0047] In order to establish the conversion relationship between the two coordinate systems, the controller obtains the camera's intrinsic parameter matrix and extrinsic parameter matrix. The intrinsic parameter matrix contains the camera's focal length and principal point coordinate information, which is used to describe the projection transformation during the camera imaging process. The extrinsic parameter matrix includes the position and orientation of the camera coordinate system relative to the world coordinate system, and consists of a rotation matrix R and a translation vector t. After obtaining the camera's intrinsic parameter matrix and extrinsic parameter matrix, the controller converts the pixel coordinates (u, v) into world coordinates (X, Y, Z) through the following steps:

[0048] According to the intrinsic parameter matrix, the pixel coordinates (u, v) are converted to normalized coordinates (x, y, 1) in the camera coordinate system. Using the extrinsic parameter matrix, the normalized coordinates (x, y, 1) in the camera coordinate system are converted to coordinates (X, Y, Z) in the world coordinate system. Specifically, let the camera intrinsic parameter matrix be K and the extrinsic parameter matrix be [R|t], then the conversion relationship can be expressed as:

[0049] ;

[0050] Where Z is the scale factor to be determined, which can be determined by the known length of the spreader or other constraints. The controller can obtain the world coordinates P1 (X1, Y1, Z1) and P2 (X2, Y2, Z2) of the two ends of the spreader through the above formula. The controller then calculates the tilt angle θ of the spreader in the current image:

[0051] ;

[0052] The controller arranges the tilt angles corresponding to each frame of the image in chronological order, and obtains an angle sequence {θ1, θ2, ..., θ n}.

[0053] For example, suppose the controller receives a frame of a spreader image. After feature extraction and target detection, the pixel coordinates of the two ends of the spreader are obtained as (100, 200) and (300, 400), respectively. Through camera calibration, the controller has obtained the camera's intrinsic parameter matrix K and extrinsic parameter matrix [R|t]. According to the conversion relationship, the controller first converts the pixel coordinates into normalized coordinates in the camera coordinate system, and then converts them to the world coordinate system using the extrinsic parameter matrix, obtaining the spatial coordinates P1 (1.2, 3.4, 5.6) and P2 (2.3, 4.5, 6.7) of the two ends of the spreader. Substituting into the formula, we can calculate the tilt angle θ = 63.4° of the spreader in the current image. By repeating this process, the controller can obtain a complete swing angle sequence.

[0054] Step S104: judging whether the spreader is in an abnormal swing state according to the swing angle sequence, and determining a target swing angle from the swing angle sequence.

[0055] In step S104, the statistical characteristic values of the swing angle sequence are calculated, and the statistical characteristic values include the mean, the square, the maximum value and the minimum value; if the swing angle values included in the swing angle sequence are all within the preset swing angle range, and the variance is less than the preset variance threshold, it is determined that the spreader is in a normal swing state, and the mean is used as the target swing angle; if the swing angle values included in the swing angle sequence are all within the preset swing angle range, and the variance is greater than or equal to the preset variance threshold, it is determined that the spreader is in an abnormal swing state, and the sum of the mean and the variance weighted according to the preset weight is used as the target swing angle; if the maximum value or the minimum value is not within the preset swing angle range, it is determined that the spreader is in an abnormal swing state, and the maximum value or the minimum value is used as the target swing angle.

[0056] Specifically, the controller extracts statistical features from the swing angle sequence to obtain statistical feature values, which include mean, variance, maximum and minimum values. Among them, the mean reflects the average level of the swing angle, the variance reflects the discreteness of the swing angle, and the maximum and minimum values reflect the extreme values of the swing angle. The controller first determines whether all the swing angle values in the swing angle sequence fall within the preset swing angle range. If the maximum or minimum value in the swing angle sequence exceeds the preset swing angle range, it is determined that the sling is in an abnormal swing state, and the maximum or minimum value is used as the target swing angle. In the case where both the maximum and minimum values are outside the preset swing angle range, the controller selects the value that exceeds the preset swing angle range more as the target swing angle.

[0057] For example, assume the preset swing angle range is [-20°, 20°] and the current swing angle sequence is {-25°, -18°, 22°, 15°, 30°}. The controller first calculates the maximum value θmax and minimum value θmin of the sequence: maximum value θmax = 30°; minimum value θmin = -25°. Both θmax and θmin exceed the preset swing angle range [-20°, 20°]. The controller further calculates the degree to which they exceed the range: Δθmax = 30° - 20° = 10°; Δθmin = -20° - (-25°) = 5°. Since Δθmax > Δθmin, the controller outputs the maximum value θmax = 30° as the target swing angle θtarget.

[0058] If all swing angle values in the swing angle sequence are within the preset swing angle range, the controller next determines whether the variance is less than a preset variance threshold. If the variance is less than the preset variance threshold, it indicates that the swing angle changes are relatively stable and the spreader is swinging normally. In this case, the controller can directly use the mean value as the target swing angle.

[0059] If all swing angle values in the swing angle sequence are within the preset swing angle range, but the variance σ² is greater than or equal to the preset variance, this indicates significant swing angle variation and an abnormal swing condition. In this case, using only the mean μ as the target swing angle may not fully reflect the actual swing situation. Therefore, the controller weights the mean μ and the variance σ² according to preset weights to determine a comprehensive target angle. The target swing angle θ = w*μ + (1-w)*σ², where w is the weight coefficient, 0 ≤ w ≤ 1.

[0060] It should be noted that the preset swing angle range defines the safe interval of the swing angle of the sling, and the upper and lower limits of the preset range can be determined based on factors such as the design parameters of the sling, the working environment, and safety regulations; the preset variance threshold is used to judge the degree of discreteness of the swing angle sequence, which can be determined through simulation experiments or field experience; the preset weight coefficient is used to balance the contribution of the mean and variance to the target swing angle, and the value of the preset weight coefficient w can be set based on experience or simulation experiments. This application does not limit the specific values of the preset swing angle range, the preset variance threshold, and the preset weight coefficient.

[0061] Step S105: If it is determined that the spreader is in an abnormal swing state, a swing angle difference between the target swing angle and the preset swing angle range is calculated, where the swing angle difference is an offset of the target swing angle relative to the preset swing angle range.

[0062] Before step S105, the method further includes: obtaining the upper limit and lower limit of the preset swing angle range; calculating the average of the upper limit and lower limit, and determining the average as the preset swing angle; subtracting the preset swing angle from the target swing angle to obtain the swing angle difference.

[0063] Specifically, the controller obtains the upper limit θmax and lower limit θmin of the preset swing angle range. For example, if the current preset swing angle range is [-12°, 12°], θmin = -12° and θmax = 12°. The controller then calculates the midpoint of the preset swing angle range, namely the preset swing angle α. The preset swing angle α represents the ideal equilibrium position of the spreader's swing, approximated by the average of the upper and lower limits. Specifically, the formula for calculating the preset swing angle α is: α = (θmax + θmin) / 2. Continuing with the above example, if the preset swing angle range is [-12°, 12°], then: α = (12° + (-12°)) / 2 = 0°. This indicates that within the current preset swing angle range, the ideal equilibrium position of the spreader's swing is 0°. The controller then compares the preset swing angle α with the target swing angle θ and calculates the difference between them, namely the swing angle difference Δθ. This difference reflects the degree to which the spreader's actual swing state deviates from the ideal equilibrium position. The formula for calculating the swing angle difference Δθ is: Δθ = θ - α. Assuming the current target swing angle θ is 15° and the preset swing angle α is 0°, then: Δθ = 15° - 0° = 15°. This indicates that the actual swing state of the spreader is offset to the right by 15° relative to the ideal equilibrium position.

[0064] Step S106: generating a compensation force according to the swing angle difference, and applying the compensation force to the spreader, wherein the compensation direction of the compensation force is opposite to the swing direction of the spreader.

[0065] In step S106, the formula for generating the compensation force according to the swing angle difference and the swing amplitude difference is as follows:

[0066] F=m(g·tanα+L·α''+2ζw n ·(θ'-α')+w n ²·(θ-α))

[0067] Where F is the compensation force, m is the total mass of the sling and the load, g is the acceleration of gravity, L is the equivalent suspension length of the sling, θ is the target swing angle, α is the preset swing angle, θ-α is the swing angle difference, θ' is the target angular velocity, α' is the preset angular velocity, α'' is the preset angular acceleration, ζ is the damping ratio, and w n is the natural frequency of the system.

[0068] Specifically, the controller calculates a compensation force based on the aforementioned formula, with the direction of the compensation force being opposite to the spreader's swing direction. This is to counteract any abnormal spreader swing and quickly restore it to its preset equilibrium position. The controller determines the spreader's swing direction based on the sign of the swing angle difference θ - α and accordingly determines the direction of the compensation force. For example, a positive value of θ - α indicates a rightward deviation of the spreader, and the compensation force should be applied to the left. A negative value of θ - α indicates a leftward deviation of the spreader, and the compensation force should be applied to the right.

[0069] In the above formula, m(g·tanα) represents the total mass of the spreader and load, g represents the acceleration due to gravity, and α represents the preset swing angle. This term represents the gravitational moment of the spreader near its equilibrium position. When the spreader deviates from its equilibrium position, gravity generates a torque attempting to pull the spreader back to equilibrium. The magnitude of this torque is related to the spreader's mass, the acceleration due to gravity, and the angle of deviation from equilibrium. tanα represents the tangent of the preset swing angle. Within a small angular range, tanα is approximately equal to α, so this term can be roughly considered mgα, meaning it is proportional to the angular deviation. In L·α'', L represents the spreader's equivalent suspension length, and α'' represents the preset angular acceleration. This term represents the moment of inertia generated by the spreader's angular acceleration. According to Newton's second law, acceleration is proportional to force. When the spreader experiences angular acceleration, it generates a moment of inertia in the opposite direction of the acceleration, affecting the spreader's swing. The magnitude of this moment of inertia is related to the spreader's moment of inertia (which is related to its mass and suspension length) and the magnitude of the angular acceleration. L·α'' is actually the product of the moment of inertia and angular acceleration. 2ζwn·(α'-θ') where ζ represents the damping ratio and w nRepresents the natural frequency of the system, α' represents the preset angular velocity, θ' represents the target angular velocity, and this item represents the damping torque related to the speed deviation. In actual systems, there will always be a certain amount of damping, which will cause the swing speed of the spreader to gradually decay. The damping torque is proportional to the swing speed of the spreader, and its direction is opposite to the speed. 2ζwn·(α'-θ') is actually a damping torque that is proportional to the speed deviation. When the actual swing speed (target angular velocity) of the spreader is greater than the preset angular velocity (θ'>α'), this torque is positive and has a deceleration effect; when the actual swing speed (target angular velocity) is less than the preset angular velocity (θ'<α'), this torque is negative and has an acceleration effect. ζ and wn are parameters related to the damping characteristics and natural frequency of the system, which determine the magnitude of the damping torque. w n w in ²·(θ-α) n represents the natural frequency of the system, θ represents the target swing angle, and α represents the preset swing angle. This term represents the elastic torque associated with the angular deviation. In a sling swing system, there is usually a linearized elastic restoring torque that attempts to pull the sling back to the equilibrium position. This torque is proportional to the angular deviation of the sling from the equilibrium position. wn²·(θ-α) is actually an elastic torque proportional to the angular deviation. When the actual swing angle (target swing angle) of the sling is greater than the preset swing angle (θ>α), this torque is positive and has a pulling effect; when the actual swing angle (target swing angle) is less than the preset swing angle (θ<α), this torque is negative and has a pushing effect. wn² represents the elastic coefficient, which determines the magnitude of the elastic torque. It is related to the natural frequency of the system and reflects the stiffness characteristics of the system. Adding these four terms gives the complete expression for the compensation force F. This compensation force comprehensively considers the gravity effect, inertia effect, damping effect and elastic effect during the swing of the spreader, and can generate corresponding control torque according to the actual swing state of the spreader to effectively compensate and correct the swing of the spreader.

[0070] After step S106, the method further includes: obtaining historical swing angle differences; judging the swing trend of the spreader based on the historical swing angle differences, and constructing a fitting curve based on the swing trend; predicting the predicted swing angle difference of the spreader within a preset time based on the fitting curve; and generating a predicted compensation force based on the predicted swing angle difference.

[0071] Specifically, the controller obtains historical swing angle difference data. The historical swing angle difference data can come from the swing angle difference calculated in real time in the previous step, and is accumulated and managed through a data acquisition and storage mechanism. The controller sorts the historical swing angle difference data according to timestamps to form a time series that reflects the changes in the swing state of the spreader. For example, the controller can collect the swing angle difference every 0.1 seconds and store it in a circular buffer, retaining the most recent 100 data points. The controller obtains a historical swing angle difference sequence covering the past 10 seconds. Next, the controller analyzes the historical swing angle difference data to determine the changing trend of the spreader's swing state. The controller achieves this by smoothing and performing differential operations on the historical swing angle difference data. For example, the controller can apply a sliding average filter to the historical swing angle difference data to remove high-frequency noise and short-term disturbances and extract the smooth trend of the swing angle difference. The controller can perform first-order difference on the smoothed historical swing angle difference data to obtain the rate of change of the swing angle difference, and judge the development trend of the swing state of the spreader according to the sign and size of the rate of change, such as swinging to the left, swinging to the right, and tending to stability.

[0072] After determining the trend of the spreader's swing state, the controller establishes a mathematical model to describe how the swing angle difference changes over time. This is achieved by curve fitting the historical swing angle difference data. Specifically, the controller selects a function form that is compatible with the historical swing angle difference data, such as a polynomial, exponential, or trigonometric function. The order or parameters of the function are determined based on the distribution of the historical swing angle difference data. The controller uses least squares and gradient descent optimization algorithms to estimate the function coefficients or parameter values by minimizing the error between the fitted curve and the actual data points.

[0073] After determining the fitting curve model, the controller uses the current moment as the starting point for extrapolation, selects an appropriate prediction time length, such as 0.5 seconds, and substitutes it into the fitting curve function to calculate the predicted swing angle difference at the predicted time point. The predicted swing angle difference reflects the potential deviation of the spreader's swing state if it develops along the current trend to the predicted time point.

[0074] For example, assuming the swing angle difference at the current moment t0 is 2°, the controller fits the quadratic polynomial function y=0.1x²+0.5x+2 based on the historical swing angle difference data. The controller substitutes the predicted time point t1=t0+0.5 into this function and calculates the predicted swing angle difference y1=0.1×(t0+0.5)²+0.5×(t0+0.5)+2=2.6°. The controller predicts that after 0.5 seconds, the swing angle difference of the spreader may increase from 2° to 2.6°. Finally, the controller generates a corresponding predicted compensation force based on the predicted swing angle difference and substitutes the predicted swing angle difference into the previous compensation force calculation formula.

[0075] By fitting and extrapolating historical swing angle difference data, the spreader's swing state over a period of time is predicted. Based on this, a predicted compensation force is generated to predictively control and correct the spreader's swing. This method leverages the historical variation of the spreader's swing state, providing a degree of foresight and continuity, and can achieve smoother and more accurate control.

[0076] Reference Figure 2 The present application also provides a crane sling control device, which is a controller. The controller includes an acquisition module 201 and a processing module 202. The acquisition module 201 is used to acquire an image sequence of the sling, where the image sequence includes multiple continuous images; the processing module 202 is used to perform feature extraction and target detection on each image to obtain pixel coordinates of both ends of the sling; the processing module 202 is also used to calculate the inclination angle of the sling in each image based on the pixel coordinates to obtain a swing angle sequence; the processing module 202 is also used to determine whether the sling is in an abnormal swing state based on the swing angle sequence, and determine a target swing angle from the swing angle sequence; the processing module 202 is also used to calculate the swing angle difference of the target swing angle relative to a preset swing angle range if it is determined that the sling is in an abnormal swing state, where the swing angle difference is the offset of the target swing angle relative to the preset swing angle range; the processing module 202 is also used to generate a compensation force based on the swing angle difference and apply the compensation force to the sling, where the compensation direction of the compensation force is opposite to the swing direction of the sling.

[0077] In one possible embodiment, the processing module 202 determines whether the spreader is in an abnormal swinging state based on the swing angle sequence, and determines a target swing angle from the swing angle sequence, specifically including: the processing module 202 calculates the statistical characteristic values of the swing angle sequence, and the statistical characteristic values include the mean, square, maximum value and minimum value; if the swing angle values included in the swing angle sequence are all within the preset swing angle range, and the variance is less than the preset variance threshold, the processing module 202 determines that the spreader is in a normal swinging state, and uses the mean as the target swing angle; if the swing angle values included in the swing angle sequence are all within the preset swing angle range, and the variance is greater than or equal to the preset variance threshold, the processing module 202 determines that the spreader is in an abnormal swinging state, and uses the sum of the mean and the variance weighted according to the preset weight as the target swing angle; if the maximum value or the minimum value is not within the preset swing angle range, the processing module 202 determines that the spreader is in an abnormal swinging state, and uses the maximum value or the minimum value as the target swing angle.

[0078] In one possible implementation, the processing module 202 calculates the tilt angle of the sling in each image based on the pixel coordinates to obtain a swing angle sequence, specifically including: the processing module 202 converts the pixel coordinates at both ends of the sling into spatial coordinates in the world coordinate system; the processing module 202 calculates the swing angle corresponding to the sling in each image based on the spatial coordinates to obtain a swing angle sequence.

[0079] In one possible implementation, the processing module 202 converts the pixel coordinates at both ends of the sling into spatial coordinates in the world coordinate system, specifically including: the processing module 202 establishes a conversion relationship between the camera coordinate system and the world coordinate system; the acquisition module 201 obtains the extrinsic parameter matrix of the camera, and converts the pixel coordinates into coordinates in the camera coordinate system according to the extrinsic parameter matrix; the processing module 202 converts the coordinates in the camera coordinate system into the spatial coordinate system in the world coordinate system according to the conversion relationship.

[0080] In one possible embodiment, if the processing module 202 determines that the sling is in an abnormal swinging state, then before the processing module 202 calculates the swing angle difference between the target swing angle and the preset swing angle range, it also includes: the acquisition module 201 obtains the upper limit value and the lower limit value of the preset swing angle range; the processing module 202 calculates the average value of the upper limit value and the lower limit value, and determines the average value as the preset swing angle; the processing module 202 subtracts the preset swing angle from the target swing angle to obtain the swing angle difference.

[0081] In a possible implementation, the formula for generating the compensation force according to the swing angle difference is specifically:

[0082] F=m(g·tanα+L·α''+2ζwn·(θ'-α')+wn²·(θ-α))

[0083] Where F is the compensation force, m is the total mass of the sling and the load, g is the acceleration of gravity, L is the equivalent suspension length of the sling, θ is the target swing angle, α is the preset swing angle, θ-α is the swing angle difference, θ' is the target angular velocity, α' is the preset angular velocity, α'' is the preset angular acceleration, ζ is the damping ratio, and wn is the natural frequency of the system.

[0084] In one possible embodiment, after the processing module 202 generates a compensation force based on the swing angle difference and applies the compensation force to the sling, it also includes: the acquisition module 201 acquires the historical swing angle difference; the processing module 202 determines the swing trend of the sling based on the historical swing angle difference, and constructs a fitting curve based on the swing trend; the processing module 202 predicts the predicted swing angle difference of the sling within a preset time based on the fitting curve; and generates a predicted compensation force based on the predicted swing angle difference.

[0085] It should be noted that the above embodiments provide devices that implement their functions using only the division of the above functional modules as examples. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0086] This application also provides an electronic device. Figure 3 , Figure 3 3. This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0087] The communication bus 302 is used to implement the connection and communication between these components.

[0088] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0089] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0090] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 305, as well as accesses data stored in the memory 305, to perform various server functions and process data. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 301 but implemented as a separate chip.

[0091] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also optionally be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 The memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a crane hoist control method.

[0092] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the application program of a crane hoist control method stored in the memory 305. When executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0093] The present application further provides a computer-readable storage medium storing instructions, which, when executed by one or more processors 301 , enable the electronic device 300 to perform one or more of the methods described in the above embodiments.

[0094] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0096] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0097] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0098] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0099] The foregoing is merely an exemplary embodiment of the present disclosure and is not intended to limit the scope of the present disclosure. In other words, any equivalent variations and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the disclosure and the practical implications thereof.

[0100] This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not described herein. The description and examples are to be considered as exemplary only, and the scope and spirit of the present disclosure are to be defined by the claims.

Claims

1. A method for controlling a crane spreader, characterized in that: The method comprises: Acquire an image sequence of the spreader, wherein the image sequence includes a plurality of continuous images; Performing feature extraction and target detection on each of the images to obtain pixel coordinates of both ends of the spreader; Calculating the tilt angle of the spreader in each of the images according to the pixel coordinates to obtain a swing angle sequence; determining whether the spreader is in an abnormal swing state according to the swing angle sequence, and determining a target swing angle from the swing angle sequence; If it is determined that the spreader is in an abnormal swing state, calculating a swing angle difference between the target swing angle and a preset swing angle range, wherein the swing angle difference is an offset of the target swing angle relative to the preset swing angle range; generating a compensation force according to the swing angle difference, and applying the compensation force to the spreader, wherein the compensation direction of the compensation force is opposite to the swing direction of the spreader; The step of judging whether the spreader is in an abnormal swing state according to the swing angle sequence and determining a target swing angle from the swing angle sequence specifically includes: Calculating statistical characteristic values of the swing angle sequence, wherein the statistical characteristic values include mean, variance, maximum value and minimum value; If the swing angle values included in the swing angle sequence are all within the preset swing angle range and the variance is less than a preset variance threshold, it is determined that the spreader is in a normal swing state, and the mean is used as the target swing angle; If all the swing angle values included in the swing angle sequence are within the preset swing angle range and the variance is greater than or equal to a preset variance threshold, it is determined that the spreader is in an abnormal swing state, and a sum of the mean and the variance weighted according to a preset weight is used as the target swing angle; If the maximum value or the minimum value is not within the preset swing angle range, it is determined that the spreader is in an abnormal swing state, and the maximum value or the minimum value is used as the target swing angle; If it is determined that the spreader is in an abnormal swing state, before calculating the swing angle difference between the target swing angle and the preset swing angle range, the method further includes: Obtaining an upper limit value and a lower limit value of the preset swing angle range; Calculating an average of the upper limit value and the lower limit value, and determining the average value as a preset swing angle; Subtracting the preset swing angle from the target swing angle to obtain the swing angle difference; The formula for generating the compensation force according to the swing angle difference is specifically: F=m(g·tanα+L·α''+2ζw n ·(θ'-α')+w n ²·(θ-α)) Wherein, F is the compensation force, m is the total mass of the sling and the load, g is the acceleration of gravity, L is the equivalent suspension length of the sling, θ is the target swing angle, α is the preset swing angle, θ-α is the swing angle difference, θ' is the target angular velocity, α' is the preset angular velocity, α'' is the preset angular acceleration, ζ is the damping ratio, and w n is the natural frequency of the system.

2. The method according to claim 1, characterized in that Calculating the tilt angle of the spreader in each of the images according to the pixel coordinates to obtain a swing angle sequence specifically includes: Converting the pixel coordinates of the two ends of the spreader into spatial coordinates in a world coordinate system; The swing angle of the sling corresponding to each of the images is calculated according to the spatial coordinates to obtain the swing angle sequence.

3. The method according to claim 2, characterized in that The converting the pixel coordinates at both ends of the spreader into spatial coordinates in a world coordinate system specifically includes: Establish the transformation relationship between the camera coordinate system and the world coordinate system; Obtaining an extrinsic parameter matrix of the camera, and converting the pixel coordinates into coordinates in the camera coordinate system according to the extrinsic parameter matrix; According to the conversion relationship, the coordinates in the camera coordinate system are converted into the space coordinate system in the world coordinate system.

4. The method according to claim 1, wherein After generating a compensation force according to the swing angle difference and applying the compensation force to the spreader, the method further includes: Get the historical swing angle difference; Determining a swing trend of the spreader according to the historical swing angle differences, and constructing a fitting curve according to the swing trend; Predicting a predicted swing angle difference of the spreader within a preset time according to the fitting curve; A predicted compensation force is generated according to the predicted swing angle difference.

5. A crane control device, characterized in that: The device is used to execute the method according to any one of claims 1 to 4, and the device comprises an acquisition module (201) and a processing module (202), wherein: The acquisition module (201) is used to acquire an image sequence of the spreader, wherein the image sequence includes a plurality of continuous images; The processing module (202) is used to perform feature extraction and target detection on each of the images to obtain pixel coordinates of both ends of the spreader; The processing module (202) is further configured to calculate the tilt angle of the sling in each of the images based on the pixel coordinates to obtain a swing angle sequence; The processing module (202) is further configured to determine whether the spreader is in an abnormal swing state based on the swing angle sequence, and determine a target swing angle from the swing angle sequence; The processing module (202) is further configured to calculate a swing angle difference between the target swing angle and a preset swing angle range if it is determined that the spreader is in an abnormal swing state, wherein the swing angle difference is an offset of the target swing angle relative to the preset swing angle range; The processing module (202) is further configured to generate a compensation force according to the swing angle difference, and apply the compensation force to the sling, wherein the compensation direction of the compensation force is opposite to the swing direction of the sling.

6. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 4 is executed.

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