Sorting equipment motion precision detection device, method and equipment for small wire coils

Abstract

The application discloses a small wire coil sorting equipment motion precision detection device, method and equipment, and belongs to the technical field of power equipment. The device comprises: an image acquisition module, which is used for acquiring video sequence image information of the sorting process of the sorting equipment; a first vibration detection module, which is used for identifying first vibration information of the wire coil placed on the stack; an analysis module, which is used for analyzing that the sorting equipment has a fault risk in the case that the motion flexibility of the video sequence image information is lower than a set threshold and / or in the case that the first vibration information is higher than a first set vibration intensity; and a fault early warning module, which is used for generating a maintenance signal to perform targeted maintenance in a production gap. The scheme can acquire the video sequence image information and vibration information of the sorting process of the sorting equipment in real time, quickly find abnormal conditions of the sorting equipment, automatically give an early warning when an abnormality occurs, avoid unnecessary losses, and improve production efficiency and stability.

Description

Technical Field

[0001] This application belongs to the field of power equipment technology, specifically relating to a motion accuracy detection device, method and equipment for a small wire reel sorting device. Background Technology

[0002] A miniature cable reel is a small reel used for winding and storing cables, typically made of materials such as plastic or cardboard. It is commonly used to store cable, wire, and fiber optic cables, assisting maintenance personnel in cable maintenance, installation, and transportation. Because cables vary in material, specifications, and applications, the miniature cable reels need to be sorted to ensure that cables of the same material, specifications, and purpose are grouped together for easy subsequent use.

[0003] Nowadays, automated production lines are typically used to sort small cable reels. After the cables are sorted into different small reels according to their specifications, materials, and uses, labels are affixed to the small reels. Sorting equipment then groups small cables with the same labels together. However, if the sorting equipment malfunctions, the entire production line will come to a standstill.

[0004] Therefore, how to detect whether there is a fault in the sorting equipment in real time, and promptly issue a fault signal when a fault occurs, so that staff can carry out maintenance on the sorting equipment and ensure the normal operation of the production line, is an urgent problem to be solved in this field. Summary of the Invention

[0005] This application provides a motion accuracy detection device, method, and equipment for a small-diameter wire reel sorting device. The aim is to solve the problem in existing technologies where real-time detection of sorting equipment malfunctions is impossible, leading to production line stoppages due to equipment failure. The motion accuracy detection device for the small-diameter wire reel sorting device can collect real-time video sequence images and vibration information during the sorting process, quickly detect abnormalities, and automatically issue warnings when abnormalities occur, preventing unnecessary production losses due to equipment failures and thus improving production efficiency and stability. It also eliminates the need for manual inspection and maintenance, reducing operating costs.

[0006] In a first aspect, embodiments of this application provide a motion accuracy detection device for a small reel sorting equipment, the device comprising:

[0007] The image acquisition module is used to acquire video sequence image information of the sorting equipment during the sorting process;

[0008] A first vibration detection module is used to identify the first vibration information when the spool is placed on the stack; wherein, the first vibration detection module is disposed at the stack.

[0009] The analysis module is used to analyze the sorting equipment as having a risk of failure when the motion compliance of the video sequence image information is lower than a set threshold, and / or when the first vibration information is higher than a first set vibration intensity.

[0010] The fault warning module is used to generate maintenance signals for targeted repairs during production breaks.

[0011] Furthermore, the device also includes:

[0012] The second vibration detection module is used to identify second vibration information during the sorting process of the sorting equipment; wherein, the second vibration detection module is disposed on the sorting equipment;

[0013] Correspondingly, the analysis module is also used to analyze the sorting equipment as having a risk of failure when the second vibration information is higher than the second set vibration intensity.

[0014] Furthermore, the device also includes:

[0015] The fault analysis module is also used to generate marking information when the second vibration information is higher than the second set vibration intensity;

[0016] The analysis module is also used to determine the target image from the video sequence image information of the sorting process of the sorting equipment acquired by the image acquisition module based on the marking information;

[0017] The analysis module is also used to statistically analyze the real-time posture of the sorting device based on a preset number of target images obtained from a preset number of marked information, and to determine the target axis of the sorting device.

[0018] The fault warning module is also used to generate maintenance signals for the target shaft.

[0019] Furthermore, the analysis module is also used for:

[0020] Determine the fault confidence level of the target shaft; and if the fault confidence level is greater than a set confidence level, generate a trajectory replanning instruction;

[0021] The device further includes:

[0022] The trajectory planning module is used to replan the sorting operation trajectory of the sorting equipment according to the trajectory replanning instruction, so as to reduce the movement amplitude of the target rotating shaft.

[0023] Furthermore, the image acquisition module is also used for:

[0024] Images of the stacked reels after sorting by the sorting equipment are captured;

[0025] The analysis module is also used for:

[0026] In the stacking image, identify whether the distance between the newly added reel and other reels is within a preset distance; if not, generate a sorting accuracy abnormality command.

[0027] The device further includes:

[0028] The precision inspection module is used to generate inspection signals to inspect for precision abnormalities in the sorting equipment during production breaks.

[0029] Furthermore, the analysis module is also used for:

[0030] Identify the running trajectory of the coil in the video sequence image information, and identify whether the deviation between the running trajectory of the coil and the preset running trajectory reaches a preset deviation range;

[0031] If the preset deviation range is reached, a sorting accuracy abnormality instruction will be generated.

[0032] The device further includes:

[0033] The precision inspection module is used to generate inspection signals to inspect for precision abnormalities in the sorting equipment during production breaks.

[0034] Secondly, embodiments of this application provide a method for detecting the motion accuracy of a sorting device for small reels, the method comprising:

[0035] The image acquisition module acquires video sequence image information of the sorting process performed by the sorting equipment.

[0036] The first vibration information is identified by the first vibration detection module when the spool is placed on the stack; wherein, the first vibration detection module is located at the stack.

[0037] The analysis module analyzes the sorting equipment as having a risk of failure if the motion compliance of the video sequence image information is lower than a set threshold, and / or if the first vibration information is higher than a first set vibration intensity.

[0038] Maintenance signals are generated by the fault warning module to enable targeted repairs during production breaks.

[0039] Furthermore, after identifying the first vibration information when the reel is placed on the stack, the method further includes:

[0040] The second vibration detection module is used to identify the second vibration information during the sorting process of the sorting equipment; wherein, the second vibration detection module is installed on the sorting equipment;

[0041] Accordingly, if the motion compliance of the video sequence image information is lower than a set threshold, and / or if the first vibration information is higher than a first set vibration intensity, the analysis further includes determining that the sorting equipment has a risk of failure.

[0042] If the second vibration information is higher than the second set vibration intensity, it is analyzed that the sorting equipment has a risk of failure.

[0043] Furthermore, after identifying the second vibration information during the sorting process by the second vibration detection module, the method further includes:

[0044] When the second vibration information is higher than the second set vibration intensity, the fault analysis module generates marking information.

[0045] Based on the marking information, the target image is determined from the video sequence image information of the sorting process of the sorting equipment acquired by the image acquisition module;

[0046] Based on a preset number of target images obtained from a preset number of marked information, the real-time posture of the sorting device is statistically analyzed to determine the target axis of the sorting device.

[0047] Generate a maintenance signal for the target shaft.

[0048] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0049] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0050] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0051] In this embodiment, an image acquisition module is used to acquire video sequence image information of the sorting equipment during the sorting process; a first vibration detection module is used to identify first vibration information when the reel is placed on the stack; wherein, the first vibration detection module is located at the stack; an analysis module is used to analyze that the sorting equipment has a fault risk when the motion compliance of the video sequence image information is lower than a set threshold, and / or when the first vibration information is higher than a first set vibration intensity; a fault warning module is used to generate maintenance signals for targeted maintenance during production breaks. Through the above-mentioned small reel sorting equipment motion accuracy detection device, video sequence image information and vibration information of the sorting equipment during the sorting process can be acquired in real time, quickly detecting abnormalities in the sorting equipment and automatically issuing warnings when abnormalities occur, avoiding unnecessary losses to production due to equipment failure, thereby improving production efficiency and stability. It can also avoid manual inspection and maintenance, reducing operating costs. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the motion accuracy detection device for the sorting equipment of the small spool provided in Embodiment 1 of this application;

[0053] Figure 2 This is a schematic diagram of the motion accuracy detection device for the sorting equipment of the small spool provided in Embodiment 2 of this application;

[0054] Figure 3 This is a flowchart illustrating the motion accuracy detection method for a small spool sorting device provided in Embodiment 3 of this application;

[0055] Figure 4 This is a schematic diagram of the structure of the electronic device provided in Embodiment 4 of this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0057] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0058] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0059] The motion accuracy detection device, method, and equipment for sorting small reels provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0060] Example 1

[0061] Figure 1 This is a schematic diagram of the motion accuracy detection device for a small reel sorting equipment provided in Embodiment 1 of this application. Figure 1 As shown, it specifically includes the following:

[0062] The image acquisition module is used to acquire video sequence image information of the sorting equipment during the sorting process;

[0063] A first vibration detection module is used to identify the first vibration information when the spool is placed on the stack; wherein, the first vibration detection module is disposed at the stack.

[0064] The analysis module is used to analyze the sorting equipment as having a risk of failure when the motion compliance of the video sequence image information is lower than a set threshold, and / or when the first vibration information is higher than a first set vibration intensity.

[0065] The fault warning module is used to generate maintenance signals for targeted repairs during production breaks.

[0066] Firstly, this solution can be used in scenarios where cameras monitor the sorting process of sorting equipment. Sensors detect vibrations from small reels placed on the sorting equipment and transmit this information to a smart terminal for analysis. If the smart terminal determines a malfunction in the sorting equipment, it generates a maintenance signal, allowing staff to repair the equipment based on this signal.

[0067] Based on the above usage scenarios, it is understood that the subject of this application may be a small reel sorting equipment motion accuracy detection device that integrates monitoring and sorting equipment, detects the vibration information of the sorting equipment, analyzes the vibration information and generates maintenance signals. No further limitations are made here.

[0068] In this solution, the sorting equipment refers to devices that automatically identify and sort small reels of yarn using technologies such as machine vision and machine learning. It typically includes an image acquisition system, an image processing system, and a control system, capable of quickly and accurately identifying and classifying parameters such as the length, diameter, and color of small reels, achieving automated sorting, stacking, and transportation functions, thus improving production efficiency and quality. For example, the sorting equipment can be a robot, which uses its robotic arm to grasp, move, and sort small reels, thereby automating the sorting process. Furthermore, robots can also use vision systems to identify and classify different types of small reels for more efficient sorting.

[0069] Video sequence images of the sorting process can be captured by cameras. These images consist of a continuous series of pictures recorded in real-time by the camera. Each picture contains information about the sorting equipment, including its position and orientation. The video sequence images are typically stored digitally for subsequent processing and analysis.

[0070] A camera can be mounted above the sorting equipment, and video sequence image information can be acquired through the following steps:

[0071] 1. Set the camera parameters, including exposure time, white balance, contrast, and saturation, to ensure that a clear and accurate image is obtained.

[0072] 2. Begin collecting video sequence image information, and record real-time images of the sorting process by the sorting equipment using a camera.

[0073] 3. The acquired video sequence image information is transmitted to the smart terminal via wireless communication technology for subsequent processing and analysis.

[0074] Wireless communication refers to long-distance transmission communication between multiple nodes without transmission through conductors or cables. Wireless communication can be carried out using radios and other wireless devices.

[0075] Based on the above technical solutions, optionally, the image acquisition module 101 is also used for:

[0076] Images of the stacked reels after sorting by the sorting equipment are captured;

[0077] The analysis module 103 is also used for:

[0078] In the stacking image, identify whether the distance between the newly added reel and other reels is within a preset distance; if not, generate a sorting accuracy abnormality command.

[0079] The device further includes:

[0080] The precision inspection module is used to generate inspection signals to inspect for precision abnormalities in the sorting equipment during production breaks.

[0081] In this solution, the stacking image can be a stack consisting of multiple small reels, each of which may have one or more coils. The reels may be connected by supports or solid tubes. The height and number of stacks may vary depending on sorting requirements and may be limited to meet space and safety requirements.

[0082] The camera can capture images of the stacked reels. After each sorting operation, the camera automatically captures images of the stacked reels and transmits them to the smart terminal via wireless communication technology.

[0083] The preset distance refers to the minimum distance that should be maintained between each small wire reel in a stack after sorting by the sorting equipment. This distance may vary depending on the sorting equipment and the size of the wire reels. When managing wire reel stacks, by identifying whether the distance between a newly added wire reel and other reels in the stacking image is within the preset distance, it is possible to determine whether the sorting accuracy is normal, thereby promptly identifying and correcting any abnormalities in the wire reel stacking. If the distance between a newly added wire reel and other reels is not within the preset distance, a sorting accuracy abnormality command will be generated, prompting the operator to handle the situation.

[0084] An abnormal sorting accuracy command can refer to an instruction generated during the stacking management of small wire reels after sorting by the sorting equipment when the distance between a newly added wire reel and other wire reels is not within the preset distance, based on the recognition of the stacking image.

[0085] After acquiring the stacking image, the intelligent terminal can identify and analyze the image to extract the coil information and its location. Then, based on a preset distance, it compares the distance between the newly added coil and other coils to determine if it is within the preset distance. If the distance between the newly added coil and other coils is not within the preset distance, the intelligent terminal will automatically generate a sorting accuracy error command.

[0086] Inspection signals can refer to signals generated during the stacking management of small reels after sorting by sorting equipment, used for inspecting and repairing the sorting equipment when an accuracy abnormality occurs.

[0087] The intelligent terminal can generate abnormal information based on the abnormal sorting accuracy command, including the abnormality type, cause, and location. It can also generate maintenance signals based on the abnormality information, allowing staff to inspect and repair the abnormality of the sorting equipment during production breaks based on the abnormality type, cause, and location.

[0088] This solution allows for the timely detection of sorting accuracy anomalies by collecting and analyzing stacking images, enabling the generation of corresponding instructions for handling and thus preventing potential quality issues and production losses. Furthermore, conducting inspections and maintenance on the sorting equipment during production breaks ensures its normal operation and long-term stability.

[0089] Stacking can refer to a material handling method that involves stacking multiple small reels together according to certain rules. In the stacking of small reels, they are usually arranged according to certain rules, such as being classified by factors such as size, weight, and color. At the same time, the height and stability of the stack also need to be considered to ensure that there is no tilting or collapse.

[0090] The first vibration information can refer to the signal information of the first vibration of the small spool after it is placed on the stack due to gravity and inertia.

[0091] The initial vibration information generated when a spool of yarn is placed on a stack can be identified using a vibration sensor. Specifically, when the spool is placed on the stack, it generates an impact force and vibration signal, which is transmitted to the vibration sensor. The vibration sensor converts these vibration signals into electrical signals and outputs them to a signal processor for processing and analysis. By analyzing the vibration signals, the time and position of the spool's placement on the stack can be determined, thus identifying the initial vibration information. Once the vibration sensor identifies the initial vibration information, it can transmit this information to a smart terminal via wireless communication technology.

[0092] Motion smoothness refers to the smoothness and fluidity of the sorting equipment's movements, that is, the continuity and stability of the movements. It reflects the accuracy, stability, and reliability of the equipment's motion control system, as well as factors such as the actuator's response speed and force control capability.

[0093] If the motion smoothness of the video sequence image information is lower than a set threshold, it may be due to the sorting equipment's movements being insufficiently smooth and fluid. This could be caused by a lag in the sorting equipment, resulting in motion smoothness falling below the set threshold when placing small reels.

[0094] The first set vibration intensity can refer to the threshold vibration intensity generated when a small reel is placed on the stack under normal operating conditions of the sorting equipment. The first set vibration intensity can be set based on the weight and size of the small reel. If the first vibration intensity is higher than the first set vibration intensity, it may be because the sorting equipment placed the small reel on the stack before reaching the designated placement position. Due to gravity, this could cause the first vibration intensity to exceed the first set vibration intensity. Alternatively, it could be that the sorting equipment has reached the placement position but has not yet placed the reel, still applying the force required to place it on the stack, which could also cause the first vibration intensity to exceed the first set vibration intensity.

[0095] The system may pre-store a threshold value for motion compliance and a first set vibration intensity in the smart terminal. When the smart terminal obtains video sequence image information and the first vibration information, it uses computer vision technology to process and analyze the video sequence image information. After analyzing the motion compliance of the sorting equipment, it automatically compares the motion compliance and the first vibration information with the pre-stored threshold value for motion compliance and the first set vibration intensity. If the motion compliance is lower than the threshold value and the first vibration information is higher than the first set vibration intensity, it is determined that the sorting equipment has a risk of failure.

[0096] Based on the above technical solutions, optionally, the analysis module 103 is further used for:

[0097] Identify the running trajectory of the coil in the video sequence image information, and identify whether the deviation between the running trajectory of the coil and the preset running trajectory reaches a preset deviation range;

[0098] If the preset deviation range is reached, a sorting accuracy abnormality instruction will be generated.

[0099] The device further includes:

[0100] The precision inspection module is used to generate inspection signals to inspect for precision abnormalities in the sorting equipment during production breaks.

[0101] In this solution, the reel's trajectory refers to its movement path or trajectory within a video sequence. On a production line, the reel typically moves along a predetermined path or trajectory to complete different production tasks. By identifying and tracking the reel's trajectory, its operating status and position can be monitored in real time, allowing for corresponding control and adjustments.

[0102] The preset running trajectory can be the pre-defined movement path or trajectory that the production line tray should follow under normal circumstances. This preset movement path can be pre-set or adjusted and optimized according to the actual situation of the production line.

[0103] The preset deviation range can refer to the maximum allowable deviation range between the actual running trajectory of the coil and the preset running trajectory during normal production, and can be stored in advance in the smart terminal.

[0104] Smart terminals can use computer vision technology to perform object recognition on processed images. Through feature extraction and object segmentation, they can determine the position and outline of the coil in the video sequence. Then, using the image processing and object recognition results, the motion trajectory of the coil is tracked and identified to determine its movement path. Finally, the actual trajectory of the coil is compared with a preset trajectory, and the deviation and degree of difference between the two are calculated to determine whether the coil's trajectory meets the preset deviation range.

[0105] In this solution, by identifying the running trajectory of the reel in the video sequence image information and judging whether the deviation of the reel's running trajectory from the preset running trajectory reaches the preset deviation range, the accuracy abnormality of the sorting equipment can be detected in time and a maintenance signal can be generated. During the production interval, the accuracy abnormality of the sorting equipment can be inspected and repaired, which can promptly detect and solve equipment problems, improve production efficiency and production line operation stability.

[0106] Maintenance signals can be alarm messages automatically generated when the operating status of sorting equipment is monitored by a smart terminal and an abnormality is detected, prompting maintenance personnel to perform corresponding repairs. Maintenance signals can be displayed through sound, vibration, and light, and the displayed signal format is stored in the smart terminal. When a potential malfunction is detected in the sorting equipment, the smart terminal can automatically generate a pre-set maintenance signal format.

[0107] In this embodiment, an image acquisition module is used to acquire video sequence image information of the sorting equipment during the sorting process; a first vibration detection module is used to identify first vibration information when the reel is placed on the stack; wherein, the first vibration detection module is located at the stack; an analysis module is used to analyze that the sorting equipment has a fault risk when the motion compliance of the video sequence image information is lower than a set threshold, and / or when the first vibration information is higher than a first set vibration intensity; a fault warning module is used to generate maintenance signals for targeted maintenance during production breaks. Through the above-mentioned small reel sorting equipment motion accuracy detection device, video sequence image information and vibration information of the sorting equipment during the sorting process can be acquired in real time, quickly detecting abnormalities in the sorting equipment and automatically issuing warnings when abnormalities occur, avoiding unnecessary losses to production due to equipment failure, thereby improving production efficiency and stability. It can also avoid manual inspection and maintenance, reducing operating costs.

[0108] The motion accuracy detection device for the small reel sorting equipment in this application embodiment can be a device, or it can be a component, integrated circuit, or chip in a terminal. This device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0109] The motion accuracy detection device for the small reel sorting equipment in this embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this embodiment does not specifically limit its use.

[0110] Example 2

[0111] Figure 2 This is a schematic diagram of the motion accuracy detection device for a small reel sorting equipment provided in Embodiment 2 of this application. Figure 2 As shown, it specifically includes the following:

[0112] The device further includes:

[0113] The second vibration detection module 105 is used to identify second vibration information during the sorting process of the sorting equipment; wherein, the second vibration detection module is disposed on the sorting equipment;

[0114] Correspondingly, the analysis module 103 is also used to analyze that the sorting equipment has a risk of failure when the second vibration information is higher than the second set vibration intensity.

[0115] In this solution, a second vibration information can be detected using an accelerometer. This second vibration information refers to the information about the operating status of the sorting equipment obtained by the accelerometer through detecting vibration signals generated during the sorting process. Typically, the second vibration information includes parameters such as the vibration frequency, vibration amplitude, and vibration acceleration of the sorting equipment. By analyzing and comparing these parameters, it can be determined whether the sorting equipment is experiencing any jamming, and then corresponding adjustments and maintenance can be performed.

[0116] An accelerometer can detect vibration signals generated by sorting equipment during the sorting process, and obtain parameters such as the vibration frequency, vibration amplitude, and vibration acceleration of the sorting equipment, thereby identifying secondary vibration information during the sorting process. After identifying the secondary vibration information, the accelerometer will transmit this information to a smart terminal via wireless communication technology.

[0117] The second set vibration intensity can be the vibration intensity value used to determine if the sorting equipment is experiencing a jam. This value can include parameters such as vibration frequency, vibration amplitude, and vibration acceleration. If the second vibration information is higher than the second set vibration intensity, it indicates that the equipment is experiencing a jam, which may continue and lead to equipment failure or damage. Therefore, the equipment should be inspected and repaired immediately to ensure its normal operation and safety. Once the second set vibration intensity is determined, it can be pre-stored in the smart terminal. When the smart terminal receives the second vibration information, it compares it with the second set vibration intensity. If the second vibration information is higher than the second set vibration intensity, it indicates a risk of malfunction in the sorting equipment.

[0118] In this embodiment, by collecting second vibration information and comparing it with a second set vibration intensity, a risk of malfunction in the sorting equipment can be determined. This allows for timely detection of problems, reducing the likelihood of equipment failure and improving its stability and reliability. Simultaneously, it enables timely maintenance and repair, preventing major malfunctions, thereby reducing maintenance costs and downtime, and improving work efficiency and production effectiveness.

[0119] Based on the above technical solutions, optionally, the device further includes:

[0120] The fault analysis module is also used to generate marking information when the second vibration information is higher than the second set vibration intensity;

[0121] The analysis module 103 is also used to determine the target image based on the marking information from the video sequence image information of the sorting process of the sorting equipment acquired by the image acquisition module;

[0122] The analysis module 103 is also used to perform statistics on the real-time posture of the sorting device based on a preset number of target images obtained from a preset number of marked information, and to determine the target axis of the sorting device.

[0123] The fault warning module 104 is also used to generate a maintenance signal for the target shaft.

[0124] In this solution, the tagging information can be the time information at which the intelligent terminal determines that the second vibration information is higher than the second set vibration intensity. If the sorting equipment is a robot, the tagging information can include all the time points when the robot's robotic arm is sorting small reels of yarn and the second vibration information is higher than the second set vibration intensity. Whenever the intelligent terminal analyzes and determines that the second vibration information is higher than the second set vibration intensity, it automatically queries the current system time until one sorting process is completed. All the queried system times are then packaged to generate the tagging information.

[0125] After the tagging information is generated, the smart terminal will query the video sequence image information corresponding to the time point in the tagging information, and identify this image as the target image, until all target images in the sorting process are identified.

[0126] The preset number of markers refers to a set of pre-defined time points during the operation of the sorting equipment, used to record the equipment's status and position information at these points. These time points can be key nodes of the sorting equipment, such as the moments when the equipment starts, stops, turns, or reverses direction. By recording the equipment's status and position information at these time points and comparing it with the target image, the real-time attitude of the equipment at these time points can be determined, and then statistical analysis can be performed to identify the target axis of the equipment. The preset number of target images is consistent with the preset number of markers.

[0127] Real-time attitude refers to the current position and attitude of the sorting equipment, including information such as the equipment's coordinates, attitude angles, linear velocity, and angular velocity. By comparing a preset number of markers with the target image, the current position and attitude of the equipment can be determined, thus enabling real-time attitude statistics. Real-time attitude statistics can help monitor the equipment's operating status and fault conditions, promptly detect abnormalities, and facilitate maintenance and upkeep to ensure the equipment's normal operation.

[0128] The target shaft refers to the part of the sorting equipment that needs repair or replacement when a malfunction occurs during operation. This is typically a critical component such as the equipment's rotating bearings or transmission mechanism. By comparing a preset number of marked information with the target image, the real-time posture and position of the sorting equipment can be determined. This allows for the statistical analysis of equipment malfunctions during operation, further identifying the target shaft for timely repair or replacement, ensuring the normal operation of the equipment.

[0129] Intelligent terminals can combine image processing and data analysis technologies to statistically analyze and identify the real-time posture of sorting equipment, thereby determining the target axis of the equipment. Specifically, after obtaining a preset number of target images, the intelligent terminal first uses image processing technology to enhance, denoise, and segment the images of the sorting equipment to improve image quality and accuracy. For example, computer vision technology can be used to identify the position and posture angle of the equipment, analyze its motion trajectory and speed, and statistically analyze the real-time posture of the sorting equipment at different time points. Then, data analysis technology can be used to statistically analyze the collected equipment operation data. For example, time series analysis can be used to analyze the operating trend and periodic changes of the equipment. If the sorting equipment in this solution is a six-axis robot, the normal operating angle of the shoulder axis should be between 130° and 170°. However, by analyzing the motion trend, it is found that the actual operating angle of the shoulder axis is between 140° and 170°, which further confirms that the shoulder axis is malfunctioning, and the target axis is the shoulder axis.

[0130] If the sorting equipment is a six-axis robot and the target axis is the shoulder axis, the intelligent terminal can generate corresponding maintenance signals based on the type and severity of the shoulder axis failure, such as sending fault alarms and prompting for replacement of parts.

[0131] This solution identifies target images from video sequence images of the sorting process, enabling more accurate analysis of equipment malfunctions. Furthermore, it generates timely maintenance signals for the target shaft when a malfunction occurs, alerting staff to perform necessary maintenance and upkeep. This achieves automated monitoring, fault warning, and maintenance of the equipment, improving its reliability and stability, reducing downtime and maintenance costs, and ultimately increasing production efficiency and economic benefits.

[0132] Based on the above technical solutions, optionally, the analysis module 103 is further used for:

[0133] Determine the fault confidence level of the target shaft; and if the fault confidence level is greater than a set confidence level, generate a trajectory replanning instruction;

[0134] The device further includes:

[0135] The trajectory planning module is used to replan the sorting operation trajectory of the sorting equipment according to the trajectory replanning instruction, so as to reduce the movement amplitude of the target rotating shaft.

[0136] In this scheme, fault reliability refers to the degree of confidence in the judgment result of the target hinge failure, which can be expressed by indicators such as probability or confidence level. In practical applications, due to the influence of factors such as camera resolution and sampling rate, lighting conditions, and background interference, the judgment result of the intelligent terminal on the target hinge failure may have a certain degree of uncertainty. Therefore, it is necessary to evaluate and judge the fault reliability.

[0137] The set confidence level can be a pre-defined threshold or standard used to determine whether the confidence level of the target spindle failure meets the specified requirements. When the intelligent terminal calculates that the confidence level of the target spindle failure reaches or exceeds the set confidence level, it generates a trajectory replanning instruction to adjust and control the sorting equipment accordingly. The set confidence level can be pre-stored in the intelligent terminal.

[0138] Trajectory replanning instructions refer to instructions that automatically judge and calculate the trajectory of sorting equipment and replan and adjust the equipment when a malfunction occurs, through intelligent terminals.

[0139] The intelligent terminal can comprehensively judge the operation of the target rotating shaft through methods such as motion state analysis and anomaly detection, and perform fault diagnosis to determine the reliability of the target rotating shaft's fault. Once the reliability of the target rotating shaft's fault is determined, it can be compared with a pre-stored set reliability. If the reliability of the fault is greater than the set reliability, a trajectory replanning instruction is automatically generated to replan and control the device's operating trajectory.

[0140] During the operation of sorting equipment, the movement amplitude of the target axis can be referred to as the difference in the angle of rotation within one cycle, that is, the maximum value of the rotation angle minus the minimum value. When the sorting equipment is a six-axis robot, the target axis is the shoulder axis, the maximum angle of rotation is 170°, the minimum angle is 130°, and the movement amplitude is 40°.

[0141] The intelligent terminal can calculate the new sorting trajectory of the sorting equipment based on trajectory replanning instructions. For example, when the sorting equipment is a six-axis robot and the target axis is the shoulder axis, the intelligent terminal will automatically select a control scheme, that is, reduce the movement amplitude of the shoulder axis by controlling the movement amplitude of other axes. Specifically, the intelligent terminal will calculate the proportion by which the movement amplitude of other axes increases, and then apply this proportion to the movement parameters of other axes to increase their movement amplitude. As the movement amplitude of other axes increases, the movement amplitude of the shoulder axis will decrease accordingly, which can ensure the stability of the six-axis robot. If the maximum rotation angle of the shoulder axis was previously 170° and the minimum angle was 130°, then after replanning, the maximum rotation angle can be 170° and the minimum angle can be 140°, thus reducing the movement amplitude by 10°.

[0142] After the sorting operation trajectory of the sorting equipment is replanned, the smart terminal can transmit the replanned scheme to the sorting equipment through wireless communication technology, so that the sorting equipment can receive it and move according to the new sorting operation trajectory.

[0143] In this solution, by assessing the reliability of a target shaft malfunction, the existence of a fault can be accurately determined, avoiding misjudgments or omissions and improving the accuracy of fault diagnosis. Furthermore, by replanning the sorting trajectory of the sorting equipment, the movement amplitude of the target shaft can be reduced, thereby enhancing equipment stability and reducing the occurrence of equipment failures.

[0144] Example 3

[0145] Figure 3 This is a flowchart illustrating the motion accuracy detection method for a small reel sorting device provided in Embodiment 3 of this application. Figure 3 As shown, the specific steps include the following:

[0146] S301, acquires video sequence image information of the sorting process of the sorting equipment through the image acquisition module;

[0147] S302, the first vibration information of the spool being placed on the stack is identified by the first vibration detection module; wherein, the first vibration detection module is located at the stack.

[0148] S303, the analysis module analyzes the sorting equipment as having a risk of failure when the motion compliance of the video sequence image information is lower than a set threshold, and / or when the first vibration information is higher than a first set vibration intensity.

[0149] S304 generates maintenance signals through a fault warning module to enable targeted repairs during production breaks.

[0150] Furthermore, after identifying the first vibration information when the reel is placed on the stack, the method further includes:

[0151] The second vibration detection module is used to identify the second vibration information during the sorting process of the sorting equipment; wherein, the second vibration detection module is installed on the sorting equipment;

[0152] Accordingly, if the motion compliance of the video sequence image information is lower than a set threshold, and / or if the first vibration information is higher than a first set vibration intensity, the analysis further includes determining that the sorting equipment has a risk of failure.

[0153] If the second vibration information is higher than the second set vibration intensity, it is analyzed that the sorting equipment has a risk of failure.

[0154] Furthermore, after identifying the second vibration information during the sorting process by the second vibration detection module, the method further includes:

[0155] When the second vibration information is higher than the second set vibration intensity, the fault analysis module generates marking information.

[0156] If the motion compliance of the video sequence image information is lower than a set threshold, and / or if the first vibration information is higher than a first set vibration intensity, the analysis further includes determining that the sorting equipment has a malfunction risk.

[0157] Based on the marking information, the target image is determined from the video sequence image information of the sorting process of the sorting equipment acquired by the image acquisition module;

[0158] Based on a preset number of target images obtained from a preset number of marked information, the real-time posture of the sorting device is statistically analyzed to determine the target axis of the sorting device.

[0159] Generating maintenance signals for targeted repairs during production breaks also includes:

[0160] Generate a maintenance signal for the target shaft.

[0161] In this embodiment, a video sequence image information of the sorting process is acquired by an image acquisition module; a first vibration detection module identifies the first vibration information when the reel is placed on the stack; wherein the first vibration detection module is located at the stack; an analysis module analyzes the sorting equipment as having a risk of failure when the motion compliance of the video sequence image information is lower than a set threshold, and / or when the first vibration information is higher than a first set vibration intensity; a fault warning module generates a maintenance signal for targeted repair during production breaks. Through the above-described method for detecting the motion accuracy of a small reel sorting device, video sequence image information and vibration information of the sorting process can be acquired in real time, quickly detecting abnormalities in the sorting device and automatically issuing warnings when abnormalities occur, avoiding unnecessary losses to production due to equipment failure, thereby improving production efficiency and stability. It also avoids manual inspection and maintenance, reducing operating costs.

[0162] The method for detecting the motion accuracy of a small spool sorting device provided in this embodiment corresponds to the device provided in the above embodiments and has a corresponding execution process and beneficial effects, which will not be repeated here.

[0163] Example 4

[0164] like Figure 4 As shown, this application embodiment also provides an electronic device 400, including a processor 401, a memory 402, and a program or instructions stored in the memory 402 and executable on the processor 401. When the program or instructions are executed by the processor 401, they implement the various processes of the above-described embodiment of the motion accuracy detection device for sorting equipment of small reels and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0165] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0166] Example 5

[0167] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described embodiment of the motion accuracy detection device for sorting equipment of small reels and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0168] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0169] Example 6

[0170] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described embodiment of the motion accuracy detection device for sorting equipment of small reels, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0171] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0172] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0173] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0174] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0175] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of this application, the scope of which is determined by the scope of the claims.

Claims

1. A motion accuracy detection device for a small-sized reel sorting equipment, characterized in that, The device includes: The image acquisition module is used to acquire video sequence image information of the sorting process of the sorting equipment and the stacking image of the reels after sorting by the sorting equipment; A first vibration detection module is used to identify the first vibration information when the spool is placed on the stack; wherein, the first vibration detection module is disposed at the stack. The analysis module is used to analyze whether the sorting equipment has a failure risk when the motion compliance of the video sequence image information is lower than a set threshold and / or when the first vibration information is higher than a first set vibration intensity. The motion compliance includes the smoothness and fluidity of the sorting equipment's motion. The analysis module is also used to identify whether the distance between the newly added reel and other reels in the stacking image is within a preset distance. If not, an abnormal sorting accuracy instruction is generated. A precision inspection module is used to generate inspection signals to inspect for precision abnormalities in the sorting equipment during production breaks. The fault warning module is used to generate maintenance signals for targeted repairs during production breaks.

2. The motion accuracy detection device for the sorting equipment of the small spool according to claim 1, characterized in that, The device further includes: The second vibration detection module is used to identify second vibration information during the sorting process of the sorting equipment; wherein, the second vibration detection module is disposed on the sorting equipment; Correspondingly, the analysis module is also used to analyze the sorting equipment as having a risk of failure when the second vibration information is higher than the second set vibration intensity.

3. The motion accuracy detection device for the sorting equipment of the small spool according to claim 2, characterized in that, The device further includes: The fault analysis module is also used to generate marking information when the second vibration information is higher than the second set vibration intensity; The analysis module is also used to determine the target image from the video sequence image information of the sorting process of the sorting equipment acquired by the image acquisition module based on the marking information; The analysis module is also used to statistically analyze the real-time posture of the sorting device based on a preset number of target images obtained from a preset number of marked information, and to determine the target axis of the sorting device. The fault warning module is also used to generate maintenance signals for the target shaft.

4. The motion accuracy detection device for the sorting equipment of the small spool according to claim 3, characterized in that, The analysis module is also used for: Determine the fault confidence level of the target shaft; and if the fault confidence level is greater than a set confidence level, generate a trajectory replanning instruction; The device further includes: The trajectory planning module is used to replan the sorting operation trajectory of the sorting equipment according to the trajectory replanning instruction, so as to reduce the movement amplitude of the target rotating shaft.

5. The motion accuracy detection device for the sorting equipment of the small spool according to claim 1, characterized in that, The analysis module is also used for: Identify the running trajectory of the coil in the video sequence image information, and identify whether the deviation between the running trajectory of the coil and the preset running trajectory reaches a preset deviation range; If the preset deviation range is reached, a sorting accuracy abnormality instruction will be generated. The device further includes: The precision inspection module is used to generate inspection signals to inspect for precision abnormalities in the sorting equipment during production breaks.

6. A method for detecting the motion accuracy of a small spool sorting device, characterized in that, The method includes: The image acquisition module acquires video sequence images of the sorting process of the sorting equipment, as well as images of the stacked reels after sorting. The first vibration information is identified by the first vibration detection module when the spool is placed on the stack; wherein, the first vibration detection module is located at the stack. The analysis module analyzes the sorting equipment as having a risk of failure when the motion compliance of the video sequence image information is lower than a set threshold, and / or when the first vibration information is higher than a first set vibration intensity. The motion compliance includes the smoothness and fluidity of the sorting equipment's movements. The analysis module is also used to identify whether the distance between the newly added reel and other reels in the stacking image is within a preset distance. If not, an abnormal sorting accuracy instruction is generated. A precision inspection module is used to generate inspection signals to inspect for precision abnormalities in the sorting equipment during production breaks. Maintenance signals are generated by the fault warning module to enable targeted repairs during production breaks.

7. The method for detecting the motion accuracy of a small reel sorting device according to claim 6, characterized in that, After identifying the first vibration information when the spool is placed on the stack, the method further includes: The second vibration detection module is used to identify the second vibration information during the sorting process of the sorting equipment; wherein, the second vibration detection module is installed on the sorting equipment; Accordingly, the method further includes: If the second vibration information is higher than the second set vibration intensity, it is analyzed that the sorting equipment has a risk of failure.

8. The method for detecting the motion accuracy of a small reel sorting device according to claim 7, characterized in that, After identifying the second vibration information during the sorting process of the sorting equipment through the second vibration detection module, the method further includes: When the second vibration information is higher than the second set vibration intensity, the fault analysis module generates marking information. Based on the marking information, the target image is determined from the video sequence image information of the sorting process of the sorting equipment acquired by the image acquisition module; Based on a preset number of target images obtained from a preset number of marked information, the real-time posture of the sorting device is statistically analyzed to determine the target axis of the sorting device. Generate a maintenance signal for the target shaft.

9. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the motion accuracy detection method for a small spool sorting device as described in any one of claims 6-8.

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