Hanging lug hooking monitoring system, method and device and readable storage medium

Abstract

The invention provides a hanging lug hooking monitoring system, method and device and a readable storage medium. The system comprises a visual recognition device, a depth recognition device, an industrial computer and alarm prompting equipment. The visual identification device is fixedly installed on the crown block hook and used for capturing image data of the crown block hook and the steel ladle hanging lug and extracting position information of the crown block hook and the steel ladle hanging lug; the depth identification device is fixedly arranged on the crown block hook and is used for measuring the relative distance between the crown block hook and the steel ladle hanging lug and extracting the distance information between the crown block hook and the steel ladle hanging lug; the industrial computer is used for judging the hooking state of the crown block hook according to the position information and the distance information and judging whether potential safety hazards exist in the hooking state or not according to a preset safety standard; and the alarm prompting equipment is used for sending out alarm prompting information when the industrial computer judges that the hook entering state has the potential safety hazard.

Description

Technical Field

[0001] The present invention relates to the field of industrial automation monitoring technology, and more particularly to a hook-in monitoring system, method, device and readable storage medium. Background Art

[0002] In the steel smelting production process, the accurate docking of the overhead crane hook and the ladle hook is a key link to ensure production safety and efficiency. However, the existing technology has significant defects in this link, which brings considerable challenges to industrial production.

[0003] Traditionally, the connection between the crane hook and the ladle lug mainly relies on the operator's experience and intuition. This manual judgment method is not only inefficient, but also prone to errors, especially in conditions such as poor light, obstructed vision or operator fatigue, which is more likely to cause safety accidents. In addition, existing monitoring systems can often only provide single image information and lack accurate measurement of depth and position information, resulting in the system being unable to accurately determine whether the crane hook has been correctly hooked into the ladle lug, and thus unable to issue a timely warning.

[0004] Specifically, the image acquisition equipment of the existing monitoring system can only capture two-dimensional image information, which cannot accurately reflect the actual distance and relative position between the overhead crane hook and the ladle hook. Even if some systems are equipped with distance measuring equipment, they often cannot provide reliable data support due to their limited accuracy and stability.

[0005] In addition, the existing systems also have deficiencies in data processing and judgment logic. For example, some systems can only perform simple processing and analysis on image information, and cannot accurately extract the edge information and contour information of the overhead crane hook and the ladle hook, and thus cannot accurately judge their position and relative distance. At the same time, the existing systems are often too simple in judgment logic and lack the necessary verification and error correction mechanisms, resulting in a high rate of false alarms and missed alarms. Summary of the invention

[0006] In view of the above problems, the purpose of the present invention is to provide a system, method, device and readable storage medium for monitoring the ear hooks, which captures images and depth data through high-definition cameras and depth cameras, uses visual models and depth recognition technology to perform position recognition and distance measurement, and realizes accurate monitoring and safety assessment of the ear hook situation.

[0007] In order to achieve the above object, the present invention is implemented through the following technical solutions: In a first aspect, the present invention discloses an ear hook monitoring system, comprising: a visual recognition device, a depth recognition device, an industrial computer and an alarm prompt device; the industrial computer is respectively connected to the visual recognition device, the depth recognition device and the alarm prompt device; The visual recognition device is fixedly mounted on the crane hook and is used to capture image data of the crane hook and the ladle lug, and extract position information of the crane hook and the ladle lug; The depth identification device is fixedly mounted on the crane hook and is used to measure the relative distance between the crane hook and the ladle hanging ear and extract the distance information between the crane hook and the ladle hanging ear; The industrial computer is used to determine the hooking state of the overhead travelling crane hook according to the position information and the distance information, and to determine whether there is a safety hazard in the hooking state according to a preset safety standard; The alarm prompt device is used to issue an alarm prompt message when the industrial computer determines that there is a safety hazard in the hooking state.

[0008] Furthermore, the system further comprises: an RFID reader and a workstation camera; the RFID reader and the workstation camera are respectively connected to the industrial computer data; The RFID reader is installed on the overhead crane to identify the RFID tag installed on the workstation, obtain the tag information of the workstation, and send it to the industrial computer; The workstation camera is set at each workstation to collect the video signal of the corresponding workstation and send it to the industrial computer; The industrial computer is used to display the video signal collected by the camera of the corresponding workstation according to the label information of the workstation.

[0009] Further, the visual recognition device includes: a camera and an image processing unit; The camera is used to capture image data of the overhead crane hook and the ladle hanging lug; The image processing unit is used for: Using a filter to perform denoising on the image data; The histogram equalization technology is applied to adjust the grayscale distribution of the image data, and the edge detection algorithm and contour tracking algorithm are used to extract the edge information and contour information of the crane hook and the ladle hook in the image data; Based on edge information and contour information, the built-in image recognition model is used to extract the position information of the overhead crane hook and the ladle hook, including relative position and absolute position.

[0010] Further, the depth recognition device includes a depth camera and a depth processing unit; The depth camera is used to capture the depth image data of the overhead crane hook and the ladle hanging lug; The depth processing unit is used for: Performing denoising, filtering, and correction processing on the depth image data; Extract feature points of the crane hook and the ladle lug from the depth image data, and match the extracted feature points with pre-stored feature points through a feature matching algorithm to determine the absolute positions of the crane hook and the ladle lug; The relative distance between the crane hook and the ladle hanging ear is calculated based on the absolute positions of the crane hook and the ladle hanging ear.

[0011] In a second aspect, the present invention further discloses a method for monitoring ear hook entry, comprising: Collect image data of the crane hook and ladle lug in real time, and extract the position information of the crane hook and ladle lug; Real-time measurement of the relative distance between the crane hook and the ladle hanging ear, and extraction of the distance information between the crane hook and the ladle hanging ear; Determine the relative distance between the overhead travelling crane hook and the ladle hook according to the position information and the distance information, and judge whether the relative distance is lower than a preset distance threshold; When the relative distance is higher than a preset distance threshold, it is determined that there is a safety hazard in the hooking state of the overhead travelling crane hook, and an alarm prompt message is issued.

[0012] Furthermore, the real-time acquisition of image data of the overhead crane hook and the ladle hanging lug, and the extraction of position information of the overhead crane hook and the ladle hanging lug, includes: Capture image data of the crane hook and ladle lugs; Using a filter to perform denoising on the image data; The histogram equalization technology is applied to adjust the grayscale distribution of the image data, and the edge detection algorithm and contour tracking algorithm are used to extract the edge information and contour information of the crane hook and the ladle hook in the image data; Based on edge information and contour information, the built-in image recognition model is used to extract the position information of the overhead crane hook and the ladle hook, including relative position and absolute position.

[0013] Further, the real-time measurement of the relative distance between the overhead crane hook and the ladle hanging lug, and the extraction of the distance information between the overhead crane hook and the ladle hanging lug, includes: Capture depth image data of the crane hook and ladle lugs; Performing denoising, filtering, and correction processing on the depth image data; Extract feature points of the crane hook and the ladle lug from the depth image data, and match the extracted feature points with pre-stored feature points through a feature matching algorithm to determine the absolute positions of the crane hook and the ladle lug; The relative distance between the crown block hook and the ladle hanging ear is calculated based on the absolute positions of the crown block hook and the ladle hanging ear as the first relative distance.

[0014] Further, determining the relative distance between the overhead travelling crane hook and the ladle hook according to the position information and the distance information, and judging whether the relative distance is lower than a preset distance threshold, comprises: Based on the position information of the overhead travelling crane hook and the ladle hanging lug, a relative distance between the overhead travelling crane hook and the ladle hanging lug is calculated as a second relative distance; Determine whether the first relative distance and the second relative distance are the same; If not, the monitoring fails and an alarm message is directly issued; If so, it is determined whether the first relative distance is lower than a preset distance threshold; if so, the hooking state of the overhead travelling crane hook is safe; if not, there is a safety hazard in the hooking state of the overhead travelling crane hook.

[0015] In a third aspect, the present invention further discloses a device for monitoring ear hooks, comprising: A memory, used for storing a hook-entry monitoring program; A processor is used to implement the steps of the ear hook monitoring method as described in any one of the above items when executing the ear hook monitoring program.

[0016] In a fourth aspect, the present invention further discloses a readable storage medium, on which a hanging ear hook monitoring program is stored, and when the hanging ear hook monitoring program is executed by a processor, the steps of the hanging ear hook monitoring method as described in any one of the above items are implemented.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention combines visual model, depth recognition and RFID technology, and has lower equipment cost compared with the existing technology. Visual model and depth recognition technology can replace some high-cost sensors and imaging equipment, reducing the overall investment of the system. In addition, the application of RFID technology simplifies system wiring and reduces hardware equipment and maintenance costs.

[0018] 2. The present invention uses a variety of technical means to monitor the hooking of the ear, which effectively improves the reliability and accuracy of the system. The visual model and deep recognition technology can effectively cope with various environmental conditions and reduce the possibility of false alarms and missed alarms. At the same time, RFID technology can automatically switch the video signal to ensure that the operator can receive accurate video signals and improve operational safety.

[0019] 3. The structure of the present invention is simple and easy to install and deploy. Visual model, depth recognition and RFID technology are mature technologies with a wide range of applications. In addition, the system operation interface is friendly, operators can quickly get started, and reduce training costs.

[0020] 4. The present invention can monitor the connection status of the hook and the lug in real time, and automatically determine whether the hook has hooked the lug through an algorithm, which reduces the need for manual intervention and improves production efficiency and safety.

[0021] 5. The present invention can be applied not only to high-risk environments such as steel production workshops, but also to other fields that require precise monitoring and automatic control, such as precision manufacturing, logistics warehousing, etc.

[0022] 6. The advantages of the present invention are low cost, high reliability, easy deployment and operation, and real-time monitoring and automatic judgment capabilities. These advantages make the present invention have a wide market application prospect and are expected to provide various enterprises with an efficient and safe solution for monitoring the ear hook.

[0023] It can be seen that compared with the prior art, the present invention has outstanding substantive features and significant progress, and the beneficial effects of its implementation are also obvious. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0025] Figure 1 It is a system structure diagram of a specific implementation mode of the present invention.

[0026] Figure 2 It is a method flow chart of a specific implementation mode of the present invention.

[0027] In the figure, 1. visual recognition device; 2. depth recognition device; 3. industrial computer; 4. alarm prompt device; 5. RFID reader; 6. workstation camera; 11. camera; 12. image processing unit; 21. depth camera; 22. depth processing unit. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] See also Figure 1As shown, this embodiment provides an ear hook monitoring system, including: a visual recognition device 1, a depth recognition device 2, an industrial computer 3, an alarm prompt device 4, an RFID reader 5 and a workstation camera 6; the industrial computer 3 is data-connected with the visual recognition device 1, the depth recognition device 2, the alarm prompt device 4, the RFID reader 5 and the workstation camera 6 respectively.

[0030] The visual recognition device 1 is fixedly mounted on the crane hook, and is used to capture image data of the crane hook and the ladle lug, and extract position information of the crane hook and the ladle lug.

[0031] In a specific implementation, the visual recognition device 1 includes: a camera 11 and an image processing unit 12 .

[0032] The camera 11 is used to capture image data of the overhead crane hook and the ladle hook.

[0033] The image processing unit 12 is used for: Using a filter to perform denoising on the image data; The histogram equalization technology is applied to adjust the grayscale distribution of the image data, and the edge detection algorithm and contour tracking algorithm are used to extract the edge information and contour information of the crane hook and the ladle hook in the image data; Based on edge information and contour information, the built-in image recognition model is used to extract the position information of the overhead crane hook and the ladle hook, including relative position and absolute position.

[0034] It can be seen that in this system, a camera 11 is provided in the visual recognition device, which is fixedly installed on one side of the crane hook to capture image data of the crane hook and the ladle lug. The camera 11 can be a high-definition camera. At the same time, the captured image is processed by the image processing unit 12 to extract the position information of the hook and the lug.

[0035] The depth identification device 2 is fixedly mounted on the crane hook, and is used to measure the relative distance between the crane hook and the ladle hanging ear, and to extract the distance information between the crane hook and the ladle hanging ear.

[0036] In a specific implementation, the depth recognition device 2 includes a depth camera 21 and a depth processing unit 22 .

[0037] The depth camera 21 is used to capture the depth image data of the overhead crane hook and the ladle hook. The depth camera 21 adopts a monocular / binocular depth camera.

[0038] The depth processing unit 22 is used for: Performing denoising, filtering, and correction processing on the depth image data; Extract feature points of the crane hook and the ladle lug from the depth image data, and match the extracted feature points with pre-stored feature points through a feature matching algorithm to determine the absolute positions of the crane hook and the ladle lug; The relative distance between the crane hook and the ladle hanging ear is calculated based on the absolute positions of the crane hook and the ladle hanging ear.

[0039] It can be seen that in this system, the depth recognition device is provided with a depth camera 21, which is fixedly installed on one side of the overhead crane hook to measure the relative distance between the overhead crane hook and the ladle hanging ear. At the same time, the measured depth data is processed by the depth processing unit 22 to extract the distance information between the hook and the hanging ear.

[0040] The RFID reader 5 is arranged on the overhead travelling crane and is used to identify the RFID tag installed on the workstation, obtain the tag information of the workstation, and send it to the industrial computer 3 .

[0041] The workstation camera 6 is arranged at each workstation to collect the video signal of the corresponding workstation and send it to the industrial computer 3 .

[0042] The industrial computer 3 is used to determine the hooking state of the overhead travelling crane hook according to the position information and distance information, and to determine whether there is a safety hazard in the hooking state according to preset safety standards; and is also used to display the video signal collected by the camera of the corresponding workstation according to the label information of the workstation.

[0043] In a specific implementation, the industrial computer 3 can use the visual model to perform position recognition and monocular / binocular depth recognition technology to perform composite confirmation based on the image data and distance data to determine the hooking status of the hook. The industrial computer 3 is responsible for processing and analyzing data, identifying the connection status of the hook and the hook, and judging whether there is a safety hazard based on the preset safety standards.

[0044] The alarm prompt device 4 is used to issue an alarm prompt message when the industrial computer 3 determines that there is a safety hazard in the hooking state.

[0045] Specifically, when the industrial computer 3 determines that the hooking condition of the hook does not meet the safety standard, the alarm prompt device 4 will issue an alarm prompt message to remind the operator to handle it in time. The alarm prompt device 4 can be a light alarm device, a sound alarm device or other suitable alarm methods.

[0046] In addition, the system realizes the integration of RFID technology through the cooperation of RFID reader 5, workstation camera 6 and industrial computer 3. Specifically, RFID reader 5 is installed on the overhead crane, and RFID tags are installed on each workstation in the steel production workshop. Each RFID tag has a unique identification code, which is used to identify different workstations. When the RFID reader 5 reads the tag information of a specific workstation, the industrial computer 3 automatically switches the video signal to the workstation camera 6 of the workstation, so that the overhead crane operator can observe the connection process of the hook and the lug in real time.

[0047] When switching signals, the industrial computer 3 can integrate the position recognition results of the visual model, the distance data of the depth recognition, and the workstation information provided by the RFID technology to conduct comprehensive monitoring and judgment. This ensures that when the crane operator operates at different workstations, he can receive the video signal of the corresponding workstation, thereby improving the accuracy and efficiency of the operation.

[0048] See also Figure 2 As shown, the present invention also discloses a method for monitoring ear hook entry, comprising the following steps: S1: collect image data of the crane hook and the ladle lug in real time, and extract the position information of the crane hook and the ladle lug.

[0049] In a specific implementation, firstly, a high-definition camera fixedly installed on one side of the crane hook is used to capture image data of the crane hook and the ladle hook, and the captured image data is used as input and transmitted to the image processing unit.

[0050] Then, a Gaussian filter or a mean filter is used to perform denoising on the image data to reduce noise interference in the image. Next, a histogram equalization technique is applied to adjust the grayscale distribution of the image data to improve the contrast and clarity of the image.

[0051] Then, edge detection algorithms such as the Canny edge detector or the Sobel operator are used to extract the edge information of the crane hook and the ladle lug in the image data, and the contour information of the crane hook and the ladle lug in the image data is extracted through the contour tracking algorithm. Image segmentation methods such as threshold segmentation and region growing are applied to separate the hook and lug parts in the image from the background. For complex image scenes, image segmentation methods based on machine learning, such as convolutional neural networks (CNN), can be used.

[0052] Finally, based on the edge information and contour information, the built-in image recognition model, such as the convolutional neural network (CNN), is used to extract the position information of the overhead crane hook and the ladle hook, including the relative position and absolute position.

[0053] S2: Real-time measurement of the relative distance between the overhead crane hook and the ladle hanging ear, and extraction of distance information between the overhead crane hook and the ladle hanging ear.

[0054] In a specific implementation, firstly, a monocular / binocular depth camera fixedly installed on the side of the overhead traveling crane hook is used to capture depth image data of the overhead traveling crane hook and the ladle hanging lug.

[0055] Then, the depth image data is subjected to denoising, filtering, and correction processing. Specifically, a filter is applied to the depth data for denoising, such as a Gaussian filter, a mean filter, etc. The depth data is corrected to eliminate the effects of camera distortion and error. A data smoothing algorithm is used to make the depth data smoother and more continuous.

[0056] At this time, advanced feature extraction algorithms such as SIFT, SURF, and ORB are used to extract the feature points of the crane hook and the ladle lug in the depth image data. The extracted feature points are matched with the pre-stored feature points through the feature matching algorithm to determine the absolute positions of the crane hook and the ladle lug.

[0057] Finally, based on the absolute positions of the crane hook and the ladle hanging ear, a three-dimensional geometric algorithm is used to calculate the relative distance between the crane hook and the ladle hanging ear as the first relative distance.

[0058] S3: Determine the relative distance between the overhead travelling block hook and the ladle hook according to the position information and the distance information, and judge whether the relative distance is lower than a preset distance threshold.

[0059] In a specific implementation, based on the position information of the crown block hook and the ladle hanging lug, the relative distance between the crown block hook and the ladle hanging lug is calculated as the second relative distance.

[0060] At this time, it is determined whether the first relative distance and the second relative distance are the same.

[0061] If not, the monitoring fails and an alarm prompt message is issued directly.

[0062] If so, it is further determined whether the first relative distance is lower than a preset distance threshold; if so, the hooked state of the overhead travelling crane hook is safe; if not, there is a safety hazard in the hooked state of the overhead travelling crane hook.

[0063] S4: When the relative distance is higher than a preset distance threshold, it is determined that there is a safety hazard in the hooking state of the overhead travelling crane hook, and an alarm prompt message is issued.

[0064] The present invention also discloses a device for monitoring ear hooking, comprising a processor and a memory; wherein the processor implements the steps of the ear hooking monitoring method as described in any one of the above items when executing the ear hooking monitoring program stored in the memory.

[0065] Furthermore, the ear hook monitoring device in this embodiment may further include: The input interface is used to obtain the externally imported ear hook monitoring program and save the obtained ear hook monitoring program to the memory, and can also be used to obtain various instructions and parameters transmitted by the external terminal device and transmit them to the processor so that the processor can use the above various instructions and parameters to carry out corresponding processing. In this embodiment, the input interface can specifically include but is not limited to a USB interface, a serial interface, a voice input interface, a fingerprint input interface, a hard disk reading interface, etc.

[0066] The output interface is used to output various data generated by the processor to the terminal device connected thereto, so that other terminal devices connected to the output interface can obtain various data generated by the processor. In this embodiment, the output interface may specifically include but is not limited to a USB interface, a serial interface, etc.

[0067] The communication unit is used to establish a remote communication connection between the ear hook monitoring device and an external server so that the ear hook monitoring device can mount the image file to the external server. In this embodiment, the communication unit may specifically include but is not limited to a remote communication unit based on wireless communication technology or wired communication technology.

[0068] The keyboard is used to obtain various parameter data or instructions input by the user by tapping the keycaps in real time.

[0069] The display is used to display the relevant information of the hook-in monitoring process in real time.

[0070] The mouse can be used to assist users in inputting data and simplify user operations.

[0071] The present invention also discloses a readable storage medium, wherein the readable storage medium includes a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable hard disk, a CD-ROM, or any other form of storage medium known in the technical field. The readable storage medium stores a hook-hanging monitoring program, and when the hook-hanging monitoring program is executed by a processor, the steps of the hook-hanging monitoring method described in any one of the above items are implemented.

[0072] In summary, the present invention captures images and depth data through a high-definition camera and a depth camera, and uses visual models and depth recognition technology to perform position recognition and distance measurement, thereby achieving accurate monitoring and safety assessment of the ear hook situation.

[0073] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. As for the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0074] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0075] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, 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 interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0076] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0077] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each module may exist physically separately, or two or more modules may be integrated into one unit.

[0078] Similarly, each processing unit in each embodiment of the present invention may be integrated into one functional module, or each processing unit may exist physically, or two or more processing units may be integrated into one functional module.

[0079] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0080] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0081] The above is a detailed introduction to the ear hook monitoring system, method, device and readable storage medium provided by the present invention. Specific examples are used herein 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. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the scope of protection of the present invention.

Claims

1. A hook-in monitoring system, characterized in that: include: A visual recognition device, a depth recognition device, an industrial computer and an alarm prompt device; the industrial computer is respectively connected with the visual recognition device, the depth recognition device and the alarm prompt device in data connection; The visual recognition device is fixedly mounted on the crane hook and is used to capture image data of the crane hook and the ladle lug, and extract position information of the crane hook and the ladle lug; The depth identification device is fixedly mounted on the crane hook and is used to measure the relative distance between the crane hook and the ladle hanging ear and extract the distance information between the crane hook and the ladle hanging ear; The industrial computer is used to determine the hooking state of the overhead travelling crane hook according to the position information and the distance information, and to determine whether there is a safety hazard in the hooking state according to a preset safety standard; The alarm prompt device is used to issue an alarm prompt message when the industrial computer determines that there is a safety hazard in the hooking state.

2. The ear hook monitoring system according to claim 1, characterized in that: Also includes: RFID reader and workstation camera; RFID reader and workstation camera are respectively connected to industrial computer data; The RFID reader is installed on the overhead crane to identify the RFID tag installed on the workstation, obtain the tag information of the workstation, and send it to the industrial computer; The workstation camera is set at each workstation to collect the video signal of the corresponding workstation and send it to the industrial computer; The industrial computer is used to display the video signal collected by the camera of the corresponding workstation according to the label information of the workstation.

3. The ear hook monitoring system according to claim 1, characterized in that: The visual recognition device includes: a camera and an image processing unit; The camera is used to capture image data of the overhead crane hook and the ladle hanging lug; The image processing unit is used for: Using a filter to perform denoising on the image data; The histogram equalization technology is applied to adjust the grayscale distribution of the image data, and the edge detection algorithm and contour tracking algorithm are used to extract the edge information and contour information of the crane hook and the ladle hook in the image data; Based on edge information and contour information, the built-in image recognition model is used to extract the position information of the overhead crane hook and the ladle hook, including relative position and absolute position.

4. The ear hook monitoring system according to claim 3, characterized in that: The depth recognition device includes a depth camera and a depth processing unit; The depth camera is used to capture the depth image data of the overhead crane hook and the ladle hanging lug; The depth processing unit is used for: Performing denoising, filtering, and correction processing on the depth image data; Extract feature points of the crane hook and the ladle lug from the depth image data, and match the extracted feature points with pre-stored feature points through a feature matching algorithm to determine the absolute positions of the crane hook and the ladle lug; The relative distance between the crane hook and the ladle hanging ear is calculated based on the absolute positions of the crane hook and the ladle hanging ear.

5. A method for monitoring the hooking of a lug, characterized in that: The method adopts the hook-entry monitoring system as claimed in any one of claims 1 to 4; The method comprises: Collect image data of the crane hook and ladle lug in real time, and extract the position information of the crane hook and ladle lug; Real-time measurement of the relative distance between the crane hook and the ladle hanging ear, and extraction of the distance information between the crane hook and the ladle hanging ear; Determine the relative distance between the overhead travelling crane hook and the ladle hook according to the position information and the distance information, and judge whether the relative distance is lower than a preset distance threshold; When the relative distance is higher than a preset distance threshold, it is determined that there is a safety hazard in the hooking state of the overhead travelling crane hook, and an alarm prompt message is issued.

6. The method for monitoring ear hook entry according to claim 5, characterized in that: The real-time acquisition of image data of the crane hook and the ladle hanging lug, and the extraction of position information of the crane hook and the ladle hanging lug, includes: Capture image data of the crane hook and ladle lugs; Using a filter to perform denoising on the image data; The histogram equalization technology is applied to adjust the grayscale distribution of the image data, and the edge detection algorithm and contour tracking algorithm are used to extract the edge information and contour information of the crane hook and the ladle hook in the image data; Based on edge information and contour information, the built-in image recognition model is used to extract the position information of the overhead crane hook and the ladle hook, including relative position and absolute position.

7. The method for monitoring ear hook entry according to claim 6, characterized in that: The real-time measurement of the relative distance between the overhead crane hook and the ladle hanging ear, and the extraction of the distance information between the overhead crane hook and the ladle hanging ear, includes: Capture depth image data of the crane hook and ladle lugs; Performing denoising, filtering, and correction processing on the depth image data; Extract feature points of the crane hook and the ladle lug from the depth image data, and match the extracted feature points with pre-stored feature points through a feature matching algorithm to determine the absolute positions of the crane hook and the ladle lug; The relative distance between the crown block hook and the ladle hanging ear is calculated based on the absolute positions of the crown block hook and the ladle hanging ear as the first relative distance.

8. The method for monitoring ear hook entry according to claim 7, characterized in that: Determining the relative distance between the overhead travelling crane hook and the ladle hook according to the position information and the distance information, and judging whether the relative distance is lower than a preset distance threshold, comprises: Based on the position information of the overhead travelling crane hook and the ladle hanging lug, a relative distance between the overhead travelling crane hook and the ladle hanging lug is calculated as a second relative distance; Determine whether the first relative distance and the second relative distance are the same; If not, the monitoring fails and an alarm message is directly issued; If so, it is determined whether the first relative distance is lower than a preset distance threshold; if so, the hooking state of the overhead travelling crane hook is safe; if not, there is a safety hazard in the hooking state of the overhead travelling crane hook.

9. A hook-in monitoring device, characterized in that: include: A memory, used for storing a hook-entry monitoring program; A processor, used for implementing the steps of the ear hook monitoring method as described in any one of claims 5 to 8 when executing the ear hook monitoring program.

10. A readable storage medium, characterized in that: The readable storage medium stores an ear hook monitoring program, and when the ear hook monitoring program is executed by the processor, the steps of the ear hook monitoring method according to any one of claims 5 to 8 are implemented.

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