Crane swing angle detection method and device based on data fusion and storage medium

Abstract

The invention relates to a crane swing angle detection method and device based on data fusion and a storage medium, and belongs to the technical field of crane detection. The method comprises the steps that position information of a lifting hook is determined based on image data, collected by a binocular camera, of the lifting hook; the binocular camera is mounted on a lifting rope of the crane; acquiring angle change information of the lifting hook based on a gyroscope; the gyroscope is mounted on a lifting hook of the crane; and determining the swing angle of the crane based on the position information and the angle change information. According to the crane swing angle detection method based on data fusion, spatial position information is provided through the binocular camera, angle change information is provided through the gyroscope, data of binocular vision and data of the gyroscope are fused, high-precision three-dimensional position information provided by the binocular camera and the angle change information provided by the gyroscope are utilized, and the swing angle of the crane is detected. And the precision and the reliability of swing angle detection are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of crane detection, and in particular to a crane swing angle detection method, device and storage medium based on data fusion. Background Art

[0002] With the rapid development of ports and docks, bulk cargo bridge cranes play an important role in cargo loading and unloading, and their efficient operation is directly related to the production efficiency and economic benefits of ports. However, the hook is prone to swing during lifting and transportation, which seriously affects the safety and stability of the operation.

[0003] Traditional swing angle detection methods mostly use a single sensor. The existing methods can provide certain swing angle information, but are easily interfered with in complex environments, resulting in reduced detection accuracy and unable to meet the requirements of high precision and real-time performance. Summary of the invention

[0004] In view of this, it is necessary to provide a crane swing angle detection method, device and storage medium based on data fusion to solve the problem of low accuracy of existing swing angle detection methods.

[0005] In order to solve the above problems, the present invention provides a crane swing angle detection method based on data fusion, comprising: Determine the position information of the hook based on the image data of the hook collected by the binocular camera; the binocular camera is installed on the lifting rope of the crane; Obtaining angle change information of the hook based on a gyroscope; the gyroscope is installed on the hook of the crane; Based on the position information and the angle change information, a swing angle of the crane is determined.

[0006] In a possible implementation, the determining the position information of the hook based on the image data of the hook collected by the binocular camera includes: Using the Canny edge detection algorithm and the contour detection algorithm to extract the contour image of the hook in the image data; Extracting feature points from the contour image and matching them to obtain matching points; Based on the calibration parameters and the disparity of the matching points, obtaining the depth information of the matching points; Based on the depth information and the image coordinates, the position information of the hook is determined.

[0007] In a possible implementation, determining the swing angle of the crane based on the position information and the angle change information includes: Converting the position information into swing angle information; Based on the swing angle information, the angle change information and the dynamic model of the hook, predict the swing angle and swing angle speed at the next moment; The swing angle and the swing angular velocity at the next moment are fused by using a Kalman filter to obtain the swing angle of the crane.

[0008] In a possible implementation, before determining the position information of the hook based on the image data of the hook collected by the binocular camera, the method further includes: The binocular camera is calibrated to obtain calibration parameters of the binocular camera; the calibration parameters include intrinsic parameters and extrinsic parameters.

[0009] In a possible implementation, before determining the position information of the hook, the method further includes: Preprocessing the image data; The pre-processing includes at least one of the following: Grayscale, filter or denoise.

[0010] The present invention also provides a crane swing angle detection device based on data fusion, comprising: A first determination module is used to determine the position information of the hook based on the image data of the hook collected by the binocular camera; An acquisition module, used for acquiring angle change information of the hook based on a gyroscope; the binocular camera is installed on the lifting rope of the crane; the gyroscope is installed on the hook of the crane; The second determination module is used to determine the swing angle of the crane based on the position information and the angle change information.

[0011] In a possible implementation, the method further includes: The display module is used to display the swing angle of the crane.

[0012] On the other hand, the present invention also provides an electronic device, including a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the crane swing angle detection method based on data fusion described in any of the above implementations.

[0013] On the other hand, the present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the crane swing angle detection method based on data fusion described in any of the above implementations is implemented.

[0014] On the other hand, the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the crane swing angle detection method based on data fusion described in any of the above implementations.

[0015] The beneficial effects of the present invention are as follows: the crane swing angle detection method, device and storage medium based on data fusion provided by the present invention, the binocular camera can use two cameras to simultaneously shoot the hook, obtain the three-dimensional position of the hook through parallax calculation, and the gyroscope obtains the angle change information of the hook, and the angle change information may include the rotation angle, angular velocity or angular displacement and other change information of the hook, the binocular camera provides spatial position information, the gyroscope provides angle change information, and by fusing the binocular vision and gyroscope data, the high-precision three-dimensional position information provided by the binocular camera and the angle change information provided by the gyroscope are used to improve the accuracy and reliability of the swing angle detection. By using the multi-sensor data fusion method, the errors and limitations that a single sensor may face are overcome, the robustness and stability of the crane swing angle detection method are improved, and the accurate detection of the crane swing angle is effectively realized, thereby improving the safety and efficiency of the crane operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 One of the method flow charts of an embodiment of a crane swing angle detection method based on data fusion provided by the present invention; Figure 2 A schematic diagram of the installation of a binocular camera and a gyroscope provided by the present invention; Figure 3 A structural schematic diagram of an embodiment of a crane swing angle detection system based on data fusion provided by the present invention; Figure 4 A second method flow chart of an embodiment of a crane swing angle detection method based on data fusion provided by the present invention; Figure 5 A schematic structural diagram of an embodiment of a crane swing angle detection device based on data fusion provided by the present invention; Figure 6 A schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0019] In the description of the embodiments of the present invention, unless otherwise specified, "multiple" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" may mean: A exists alone, A and B exist at the same time, and B exists alone.

[0020] The descriptions of "first", "second", etc. involved in the embodiments of the present invention are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the technical features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0021] Figure 1 One of the method flow charts of an embodiment of the crane swing angle detection method based on data fusion provided by the present invention is as follows: Figure 1 As shown, the crane swing angle detection method based on data fusion includes: S101, determining the position information of the hook based on the image data of the hook collected by the binocular camera; the binocular camera is installed on the lifting rope of the crane; S102, obtaining angle change information of the hook based on a gyroscope; the gyroscope is installed on the hook of the crane; S103. Determine a swing angle of the crane based on the position information and the angle change information.

[0022] It should be noted that before performing swing angle detection, a binocular camera and a gyroscope need to be installed. Figure 2 The schematic diagram of the installation of the binocular camera and the gyroscope provided by the present invention is as follows: Figure 2 As shown in the figure, a binocular camera is first installed on the upper end of the lifting rope to ensure that the field of view covers the working range of the lifting device. Then a gyroscope is firmly installed on the hook of the crane. The sensor continuously monitors the angular movement of the hook and provides real-time rotation data.

[0023] The swing angle refers to the inclination angle of the crane arm on the horizontal plane or the angle of the hook relative to the horizontal plane.

[0024] Compared with the prior art, the crane swing angle detection method based on data fusion provided by the embodiment of the present invention can use two cameras to simultaneously shoot the hook, obtain the three-dimensional position of the hook through parallax calculation, and obtain the angle change information of the hook through the gyroscope. The angle change information may include the rotation angle, angular velocity or angular displacement of the hook. The binocular camera provides spatial position information, and the gyroscope provides angle change information. By fusing the binocular vision and gyroscope data, the high-precision three-dimensional position information provided by the binocular camera and the angle change information provided by the gyroscope are used to improve the accuracy and reliability of the swing angle detection. By using the multi-sensor data fusion method, the errors and limitations that a single sensor may face are overcome, the robustness and stability of the crane swing angle detection method are improved, and the accurate detection of the crane swing angle is effectively realized, thereby improving the safety and efficiency of the crane operation.

[0025] In some embodiments of the present invention, before determining the position information of the hook based on the image data of the hook collected by the binocular camera, the method further includes: The binocular camera is calibrated to obtain calibration parameters of the binocular camera; the calibration parameters include intrinsic parameters and extrinsic parameters.

[0026] Binocular camera calibration: build a camera model, use the checkerboard calibration method, place the calibration plate, and take multiple pictures at different positions and angles.

[0027] In each calibration image, the corner features of the calibration plate are extracted and matched with the actual 3D coordinates of the calibration plate.

[0028] Use Zhang Zhengyou calibration to solve the intrinsic and extrinsic parameters of the camera.

[0029] The calibration results are applied to new images to check whether the corrected images meet expectations to verify the calibration accuracy.

[0030] Optionally, the gyroscope can also be calibrated to remove noise and bias.

[0031] The crane swing angle detection method based on data fusion provided by the embodiment of the present invention calibrates the binocular camera to ensure that the image data obtained from the binocular camera can be accurately converted into position information in three-dimensional space. Through calibration, the distortion in the image can be eliminated and the projection relationship of the camera can be accurately calculated, so as to effectively obtain the position of the hook in space and further ensure the detection accuracy.

[0032] In some embodiments of the present invention, before determining the position information of the hook, the method further includes: Preprocessing the image data; The pre-processing includes at least one of the following: Grayscale, filter or denoise.

[0033] In some embodiments of the present invention, determining the position information of the hook based on the image data of the hook collected by the binocular camera includes: Using the Canny edge detection algorithm and the contour detection algorithm to extract the contour image of the hook in the image data; Extracting feature points from the contour image and matching them to obtain matching points; Based on the calibration parameters and the disparity of the matching points, obtaining the depth information of the matching points; Based on the depth information and the image coordinates, the position information of the hook is determined.

[0034] Gray-scaling, filtering or denoising the acquired image data can reduce the complexity of calculation and improve the accuracy of image detection.

[0035] Then, the Canny edge detection algorithm and contour detection algorithm are used to extract the contour image of the hook in the image, and the extracted contour is subjected to shape matching and position inspection to ensure that the shape of the contour conforms to the hook characteristics and that the identified contour is within a reasonable range.

[0036] The identified hook contour information is output to obtain an output image, feature points are extracted and matched in the output image, and the parallax of the matching points is calculated.

[0037] The depth information of each matching point is calculated based on the disparity and calibration parameters, and finally the position of the hook in three-dimensional space is obtained by combining the image coordinates and depth information.

[0038] The crane swing angle detection method based on data fusion provided in an embodiment of the present invention can use two cameras to simultaneously capture image data of the hook through a binocular camera, and perform edge detection and contour extraction, accurately identify the three-dimensional contour of the hook, and obtain high-precision three-dimensional position information of the hook through parallax calculation.

[0039] In some embodiments of the present invention, determining the swing angle of the crane based on the position information and the angle change information includes: Converting the position information into swing angle information; Based on the swing angle information, the angle change information and the dynamic model of the hook, predict the swing angle and swing angle speed at the next moment; The swing angle and the swing angular velocity at the next moment are fused by using a Kalman filter to obtain the swing angle of the crane.

[0040] The three-dimensional position information (usually in the camera coordinate system) provided by the binocular camera can be converted into the local coordinate system or global coordinate system of the crane through coordinate transformation. Based on the converted position information, the swing angle of the hook relative to the crane base can be calculated.

[0041] The dynamic model of the hook is established according to its physical properties (such as mass, length, damping, etc.).

[0042] The current swing angle information, angle change information and dynamic model are combined to predict the swing angle and swing angle velocity at the next moment.

[0043] Data fusion is performed using a Kalman filter, which is an optimized estimation algorithm that combines information from multiple data sources to provide a more accurate state estimate.

[0044] The Kalman filter iteratively updates estimates of the pendulum angle and pendulum angular velocity by taking into account the dynamic model of the system (system equations) and the observed data (measurement equations).

[0045] The Kalman filter is also able to handle noise and uncertainty, ensuring reliable estimates even in the presence of interference.

[0046] The swing angle estimation value obtained by the Kalman filter is output to the display device.

[0047] Therefore, according to the estimated swing angle, the control strategy of the crane is adjusted to reduce the swing and improve the stability and safety of the operation.

[0048] The crane swing angle detection method based on data fusion provided in an embodiment of the present invention can process the data of the binocular camera and the gyroscope in real time by adopting a data fusion algorithm, so as to realize the real-time detection of the hook swing angle. The crane operating environment is complex and changeable, and factors such as light and occlusion may affect the detection result. The present invention makes up for the shortcomings of a single visual sensor in a complex environment through the combination of binocular vision and a gyroscope, and enhances the environmental adaptability of the system.

[0049] Figure 3 A structural schematic diagram of an embodiment of a crane swing angle detection system based on data fusion provided by the present invention is shown in FIG. Figure 3 As shown in the figure, the swing angle detection system includes a binocular camera installed on the upper end of the bridge crane rope, a gyroscope installed on the hook, an image processing module, a data fusion module, and a terminal device for display and recording. The binocular camera is used to identify the position and depth information of the spreader, and the gyroscope obtains the angle change information of the hook. The data fusion module fuses the data of the binocular camera and the gyroscope to accurately calculate the swing angle of the hook. The system can monitor the swing of the hook in real time and provide accurate swing angle data.

[0050] Figure 4 The second method flow chart of an embodiment of the crane swing angle detection method based on data fusion provided by the present invention is as follows: Figure 4 As shown, the crane swing angle detection method based on data fusion includes: S401. Install binocular camera and gyroscope and connect all devices.

[0051] First, a binocular camera is installed on the upper end of the lifting rope to ensure that the field of view covers the working range of the lifting equipment. Then a gyroscope is firmly installed on the hook of the crane. The sensor continuously monitors the angular movement of the hook and provides real-time rotation data. Finally, the binocular camera, gyroscope, image processing module, data fusion module and terminal device that displays the data are connected.

[0052] S402: Calibrate the binocular camera, solve the internal and external parameters of the camera, and verify the calibration accuracy.

[0053] Binocular camera calibration: build a camera model, use the checkerboard calibration method, place the calibration plate, take multiple pictures at different positions and angles, extract the corner features of the calibration plate in each calibration image, and correspond them to the actual 3D coordinates of the calibration plate. Use Zhang Zhengyou calibration to solve the intrinsic and extrinsic parameters of the camera. Apply the calibration results to the new image and check whether the corrected image meets expectations to verify the calibration accuracy.

[0054] S403, pre-processing the image, extracting the hook outline through edge detection and contour detection algorithms, and performing three-dimensional reconstruction.

[0055] Carry out hook position detection, grayscale the acquired image, filter and denoise it to reduce the complexity of calculation and improve the accuracy of detection.

[0056] The Canny edge detection algorithm and contour detection algorithm are used to extract the contour of the hook in the image, and the extracted contour is subjected to shape matching and position verification to ensure that the shape of the contour conforms to the hook characteristics and that the identified contour is within a reasonable range.

[0057] The identified hook contour information is output, feature points are extracted and matched in the output image, and the parallax of the matching points is calculated.

[0058] The depth information of each matching point is calculated based on the parallax and calibration parameters, and finally the position of the sling in three-dimensional space is obtained by combining the image coordinates and depth information.

[0059] S404, calculating the hook swing angle using the Kalman filter algorithm based on the obtained data information of the hook and the gyroscope.

[0060] Data fusion processing is performed. First, the three-dimensional position information of the spreader is obtained through the binocular camera and converted into swing angle information, and the angle change information of the hook is obtained from the gyroscope.

[0061] Subsequently, the swing angle and angular velocity at the next moment are predicted based on the dynamic model of the hook, and the data from the binocular camera and gyroscope are fused using the Kalman filter to update the estimated values ​​of the swing angle and angular velocity.

[0062] S405. The terminal device displays and records the swing angle data in real time.

[0063] Finally, the fused swing angle data is transmitted to the terminal device for display and recording.

[0064] The present invention realizes real-time monitoring of the three-dimensional position and swing angle of the hook through the combination of binocular camera and gyroscope. The system accurately identifies the three-dimensional contour of the hook through camera calibration, image preprocessing, edge detection and contour extraction, and uses Kalman filtering algorithm to fuse the binocular vision and gyroscope data to update the swing angle of the hook in real time.

[0065] The traditional hook swing angle detection method relies on a single sensor, which is easily affected by environmental interference and the detection is not accurate enough. The fusion technology of the present invention significantly improves the accuracy and real-time performance of hook swing angle detection, enhances the robustness and stability of the system, and is particularly suitable for bulk cargo bridge cranes in complex operating environments such as ports, significantly improving the safety and efficiency of operations. Compared with traditional methods, the present invention provides a high-precision, real-time detection solution, effectively solves the problems of environmental interference and unreliable detection, ensures the smooth progress of the operation process, and has significant practical value and promotion prospects.

[0066] In order to better implement the crane swing angle detection method based on data fusion in the embodiment of the present invention, on the basis of the crane swing angle detection method based on data fusion, the embodiment of the present invention also provides a crane swing angle detection device based on data fusion. Figure 5 A structural schematic diagram of an embodiment of a crane swing angle detection device based on data fusion provided by the present invention is shown in FIG. Figure 5 As shown, the crane swing angle detection device 500 based on data fusion includes: A first determination module 510 is used to determine the position information of the hook based on the image data of the hook collected by the binocular camera; The acquisition module 520 is used to acquire the angle change information of the hook based on the gyroscope; the binocular camera is installed on the lifting rope of the crane; the gyroscope is installed on the hook of the crane; The second determination module 530 is used to determine the swing angle of the crane based on the position information and the angle change information.

[0067] The crane swing angle detection device 500 based on data fusion provided in the above embodiment can implement the technical solution described in the above embodiment of the crane swing angle detection method based on data fusion. The specific implementation principles of the above modules or units can refer to the corresponding contents in the embodiment of the crane swing angle detection method based on data fusion, which will not be repeated here.

[0068] Optionally, it also includes: The display module is used to display the swing angle of the crane.

[0069] like Figure 6 As shown, the present invention also provides an electronic device 600. The electronic device 600 includes a processor 601, a memory 602 and a display 603. Figure 6 Only some components of the electronic device 600 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0070] In some embodiments, the processor 601 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 602, such as the crane swing angle detection method based on data fusion in the present invention.

[0071] In some embodiments, the processor 601 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processor 601 may be local or remote. In some embodiments, the processor 601 may be implemented in a cloud platform. In some embodiments, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-cloud, etc., or any combination thereof.

[0072] In some embodiments, the memory 602 may be an internal storage unit of the electronic device 600, such as a hard disk or memory of the electronic device 600. In other embodiments, the memory 602 may also be an external storage device of the electronic device 600, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the electronic device 600.

[0073] Furthermore, the memory 602 may include both an internal storage unit of the electronic device 600 and an external storage device. The memory 602 is used to store application software installed in the electronic device 600 and various data.

[0074] In some embodiments, the display 603 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an organic light-emitting diode (OLED) touch device, etc. The display 603 is used to display information on the electronic device 600 and to display a visual user interface. The components 601-603 of the electronic device 600 communicate with each other via a system bus.

[0075] In one embodiment, when the processor 601 executes the crane swing angle detection program based on data fusion in the memory 602, the following steps may be implemented: Determine the position information of the hook based on the image data of the hook collected by the binocular camera; the binocular camera is installed on the lifting rope of the crane; Obtaining angle change information of the hook based on a gyroscope; the gyroscope is installed on the hook of the crane; Based on the position information and the angle change information, a swing angle of the crane is determined.

[0076] It should be understood that: when the processor 601 executes the crane swing angle detection program based on data fusion in the memory 602, in addition to the above functions, other functions can also be realized. For details, please refer to the description of the corresponding method embodiment above.

[0077] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 600 mentioned, and the electronic device 600 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, etc. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft or other operating systems. The above-mentioned portable electronic device may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 600 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0078] Correspondingly, an embodiment of the present invention also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, it can implement the steps or functions of the crane swing angle detection method based on data fusion provided in the above-mentioned method embodiments.

[0079] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the steps or functions of the crane swing angle detection method based on data fusion provided in the above-mentioned method embodiments.

[0080] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the computer program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0081] The above is a detailed introduction to the crane swing angle detection method, device and storage medium based on data fusion provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A crane swing angle detection method based on data fusion, characterized in that: include: Determine the position information of the hook based on the image data of the hook collected by the binocular camera; The binocular camera is installed on the lifting rope of the crane; Obtaining angle change information of the hook based on the gyroscope; The gyroscope is mounted on the hook of the crane; Based on the position information and the angle change information, a swing angle of the crane is determined.

2. The crane swing angle detection method based on data fusion according to claim 1 is characterized in that: The method of determining the position information of the hook based on the image data of the hook collected by the binocular camera includes: Using the Canny edge detection algorithm and the contour detection algorithm to extract the contour image of the hook in the image data; Extracting feature points from the contour image and matching them to obtain matching points; Based on the calibration parameters and the disparity of the matching points, obtaining the depth information of the matching points; Based on the depth information and the image coordinates, the position information of the hook is determined.

3. The crane swing angle detection method based on data fusion according to claim 1 is characterized in that: The step of determining the swing angle of the crane based on the position information and the angle change information comprises: Converting the position information into swing angle information; Based on the swing angle information, the angle change information and the dynamic model of the hook, predict the swing angle and swing angle speed at the next moment; The swing angle and the swing angular velocity at the next moment are fused by using a Kalman filter to obtain the swing angle of the crane.

4. The crane swing angle detection method based on data fusion according to claim 1 is characterized in that: Before determining the position information of the hook based on the image data of the hook collected by the binocular camera, the method further includes: The binocular camera is calibrated to obtain calibration parameters of the binocular camera; the calibration parameters include intrinsic parameters and extrinsic parameters.

5. The crane swing angle detection method based on data fusion according to claim 1 is characterized in that: Before determining the position information of the hook, the method further comprises: Preprocessing the image data; The pre-processing includes at least one of the following: Grayscale, filter or denoise.

6. A crane swing angle detection device based on data fusion, characterized in that: include: A first determination module is used to determine the position information of the hook based on the image data of the hook collected by the binocular camera; An acquisition module is used to acquire angle change information of the hook based on a gyroscope; the binocular camera is installed on the lifting rope of the crane; The gyroscope is mounted on the hook of the crane; The second determination module is used to determine the swing angle of the crane based on the position information and the angle change information.

7. The crane swing angle detection device based on data fusion according to claim 6 is characterized in that: Also includes: The display module is used to display the swing angle of the crane.

8. An electronic device, characterized in that: comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the crane swing angle detection method based on data fusion as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the crane swing angle detection method based on data fusion as described in any one of claims 1 to 5 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the crane swing angle detection method based on data fusion as described in any one of claims 1 to 5 is implemented.

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