Adsorption control method of magnetic glove and magnetic glove

Abstract

The invention relates to the field of distribution network hot-line work, and discloses an adsorption control method of a magnetic glove and the magnetic glove, and the method comprises the steps: obtaining an object image of a to-be-adsorbed target object, inputting the extracted comprehensive feature data into a preset adsorption magnetic force prediction model for prediction, and according to the predicted adsorption magnetic force, carrying out the adsorption control of the to-be-adsorbed target object. Controlling the magnetic glove to adsorb the target object, obtaining a real-time pressure value of adsorption, performing real-time fine adjustment on the adsorption magnetic force, obtaining the adsorption magnetic force after real-time fine adjustment, and controlling the magnetic glove to adsorb the target object in real time according to the adsorption magnetic force after real-time fine adjustment; according to the method, picking of the fine metal parts is comprehensively optimized through a cooperation mechanism of intelligent magnetic regulation and control and real-time pressure feedback, the problems that the fine metal parts are difficult to pick up and are prone to falling off during installation in traditional hot-line work are solved, the operation efficiency is remarkably improved, meanwhile, the part slipping probability is greatly reduced, and violation behaviors in work are effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of live-line work on power distribution networks, and more particularly to a method for controlling the adsorption of magnetic gloves and the magnetic gloves themselves. Background Technology

[0002] In the field of live-line working on power distribution networks, while existing live-line working glove systems (including sweat-absorbing cotton gloves, insulating gloves, and puncture-resistant gloves) provide basic mechanical protection, they have significant shortcomings in scenarios involving the handling of small metal parts. Specifically, when workers are working at heights inside the insulated bucket of an insulated bucket truck, they must wear multiple layers of protective gloves to pick up and install metal parts such as nuts, springs, and washers with diameters ranging from 6mm to 22mm. Due to the physical limitations of traditional gloves, workers cannot directly pinch these small parts with their fingers and are forced to use thin iron or aluminum wire to pick them up one by one, resulting in a lengthy and inefficient process. More seriously, when installing washers, springs, and nuts on 6mm-22mm screws, the lack of effective fixing force between the gloves and the parts often leads to slippage, frequently causing Class C and D violations and significantly increasing operational safety risks, creating a vicious cycle of inconvenience, inefficiency, and safety hazards. Summary of the Invention

[0003] Based on this, it is necessary to address the above-mentioned problems by proposing an adsorption control method for magnetic gloves and a magnetic glove. Through the synergistic mechanism of intelligent magnetic force regulation and real-time pressure feedback, the method comprehensively optimizes the picking up of small metal parts, solving the problems of difficulty in picking up small metal parts and easy detachment during installation in traditional live-line work. This significantly improves operational efficiency, greatly reduces the probability of parts slipping, effectively reduces violations during operation, and significantly reduces the safety risks of high-altitude operations. Ultimately, this forms an efficient, safe, and compliant operation technology system, providing reliable technical support for live-line work in distribution networks.

[0004] To achieve the above objectives, the present invention provides, in a first aspect, a method for controlling the adsorption of a magnetic glove, the method comprising: Obtain an image of the target object to be adsorbed; Feature extraction is performed on the object image to obtain comprehensive feature data, and the comprehensive feature data is input into a preset adsorption magnetic force prediction model to obtain the adsorption magnetic force; Based on the adsorption magnetic force, the magnetic gloves are controlled to adsorb the target object; After the magnetic glove adsorbs the target object, the real-time pressure value between the magnetic glove and the target object is obtained, and the magnetic force of adsorption is fine-tuned in real time according to the real-time pressure value to obtain the adsorption magnetic force after real-time fine-tuning. Based on the real-time fine-tuned magnetic force, the magnetic gloves are controlled to adsorb the target object in real time.

[0005] Optionally, the step of fine-tuning the adsorption magnetic force in real time based on the real-time pressure value to obtain the fine-tuned adsorption magnetic force includes: Based on the comprehensive feature data, obtain the stable adsorption pressure value of the target object being adsorbed and moved by the magnetic glove; The real-time pressure deviation value is determined based on the real-time pressure value and the stable adsorption pressure value. Based on the real-time pressure deviation value, the adsorption magnetic force is finely adjusted in real time to obtain the adsorption magnetic force after real-time fine adjustment.

[0006] Optionally, the comprehensive feature data includes object type and object size, and the step of obtaining the stable adsorption pressure value of the target object being adsorbed and moved by the magnetic glove based on the comprehensive feature data includes: Based on the object type and the object size, the object mass and friction coefficient are matched in a preset matching table to obtain the object mass of the target object and the friction coefficient between the target object and the magnetic glove; The stable adsorption pressure value is determined based on the mass of the object and the coefficient of friction.

[0007] Optionally, determining the stable adsorption pressure value based on the object's mass and the coefficient of friction includes: Using formula Determine the stable adsorption pressure value; in, The stable adsorption pressure value is... The mass of the object. The friction coefficient is... It is the acceleration due to gravity. It is a cosine function. To preset the adsorption surface tilt angle, It is a sine function. This is the preset acceleration.

[0008] Optionally, the step of fine-tuning the adsorption magnetic force in real time based on the real-time pressure deviation value to obtain the fine-tuned adsorption magnetic force includes: If the real-time pressure deviation value meets the preset pressure deviation range, the adsorption magnetic force is used as the adsorption magnetic force after real-time fine-tuning. If the real-time pressure deviation value does not meet the preset pressure deviation range and the real-time pressure deviation value is greater than the upper limit of the preset pressure deviation range, the adsorption magnetic force is reduced in real time by a preset step size to obtain the real-time fine-tuned adsorption magnetic force. If the real-time pressure deviation value does not meet the preset pressure deviation range and the real-time pressure deviation value is less than the lower limit of the preset pressure deviation range, the adsorption magnetic force is increased in real time according to the preset step size to obtain the real-time fine-tuned adsorption magnetic force.

[0009] Optionally, the method further includes: The real-time pressure deviation values ​​at each moment from the start time of the magnetic glove adsorbing the target object to the current time are obtained; The cumulative pressure deviation value is determined based on the real-time pressure deviation value at each moment; The rate of change of the pressure deviation value is determined based on the real-time pressure deviation value at the current moment; Using a PID control algorithm, the preset step size is determined based on the real-time pressure deviation value at the current moment, the accumulated pressure deviation value, and the rate of change of the pressure deviation value.

[0010] Optionally, the step of using a PID control algorithm to determine the preset step size based on the real-time pressure deviation value at the current moment, the accumulated pressure deviation value, and the rate of change of the pressure deviation value includes: Using formula Determine the preset step size; in, The preset step size, , and These are the proportional coefficient, integral coefficient, and derivative coefficient of the PID control algorithm, respectively. The real-time pressure deviation value at the current moment. The accumulated pressure deviation value, For the current time, Let be the real-time pressure deviation value at time t. The rate of change of the pressure deviation value is denoted as .

[0011] Optionally, the comprehensive feature data includes object type and object size, and the step of extracting features from the object image to obtain the comprehensive feature data includes: The object image is input into a preset object recognition model to obtain the object type and object size of the target object.

[0012] Optionally, the method further includes: Get key operation commands based on user key presses; The magnetic gloves are controlled to release the target object according to the button operation instructions.

[0013] To achieve the above objectives, the present invention provides a magnetic glove in a second aspect, the magnetic glove comprising a live-working glove, a magnetic block, an array pressure sensor, a miniature camera, and a controller; The index fingertip of the live-line working glove has an inner cavity, in which the magnetic block is embedded. An array pressure sensor is provided between the inner wall of the inner cavity near the outside and the magnetic block. A miniature camera is provided next to the magnetic block. The inner cavity has an opening through which the miniature camera communicates with the outside. The magnetic block, the array pressure sensor, and the miniature camera are all connected to the controller. The magnetic block is used to attract the target object to be attracted; The miniature camera is used to capture images of the target object and obtain an image of the target object. The array pressure sensor is used to detect the real-time pressure value between the magnetic block and the target object after the magnetic block attracts the target object; The controller is used to perform the adsorption control method for the magnetic gloves as described in any one of the first aspects.

[0014] To achieve the above objectives, the present invention provides, in a third aspect, an adsorption control device for a magnetic glove, the device comprising: The acquisition module is used to acquire an image of the target object to be adsorbed. The feature extraction and model prediction module is used to extract features from the object image, obtain comprehensive feature data, and input the comprehensive feature data into a preset adsorption magnetic force prediction model to obtain the adsorption magnetic force. An initial adsorption control module is used to control the magnetic gloves to adsorb the target object based on the adsorption magnetic force. The real-time fine-tuning module is used to obtain the real-time pressure value between the magnetic glove and the target object after the magnetic glove adsorbs the target object, and to fine-tune the adsorption magnetic force in real time according to the real-time pressure value to obtain the adsorption magnetic force after real-time fine-tuning. The real-time adsorption control module is used to control the magnetic gloves to adsorb the target object in real time based on the real-time fine-tuned magnetic force.

[0015] To achieve the above objectives, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the adsorption control method for the magnetic gloves as described in any one of the first aspects.

[0016] To achieve the above objectives, the present invention provides a computer device in a fifth aspect, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the adsorption control method for the magnetic gloves as described in any one of the first aspects.

[0017] The present invention offers the following advantages: The method acquires an image of the target object to be adsorbed, extracts features from the image to obtain comprehensive feature data, and inputs this data into a preset magnetic adsorption force prediction model to obtain the magnetic adsorption force. Based on this force, the magnetic glove is controlled to adsorb the target object. After the glove adsorbs the object, the real-time pressure value between the glove and the object is acquired, and the magnetic adsorption force is fine-tuned in real-time based on this pressure value. Finally, the glove is controlled to adsorb the target object in real-time based on the fine-tuned magnetic adsorption force. In other words, through the synergistic mechanism of intelligent magnetic force control and real-time pressure feedback, the picking up of small metal parts is comprehensively optimized, solving the problems of difficulty in picking up small metal parts and easy detachment during installation in traditional live-line work. This significantly improves operational efficiency, greatly reduces the probability of parts slipping, effectively reduces violations during operations, and significantly reduces the safety risks of high-altitude operations. Ultimately, this forms an efficient, safe, and compliant operational technology system, providing reliable technical support for live-line work in power distribution networks. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] in: Figure 1 This is a schematic diagram of an adsorption control method for a magnetic glove according to an embodiment of this application; Figure 2 This is a schematic diagram of an adsorption control device for a magnetic glove in an embodiment of this application; Figure 3 This is a diagram showing the internal structure of a computer device in some embodiments. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In the field of live-line working on power distribution networks, while existing live-line working glove systems (including sweat-absorbing cotton gloves, insulating gloves, and puncture-resistant gloves) provide basic mechanical protection, they have significant shortcomings in scenarios involving the handling of small metal parts. Specifically, when workers are working at heights inside the insulated bucket of an insulated bucket truck, they must wear multiple layers of protective gloves to pick up and install metal parts such as nuts, springs, and washers with diameters ranging from 6mm to 22mm. Due to the physical limitations of traditional gloves, workers cannot directly pinch these small parts with their fingers and are forced to use thin iron or aluminum wire to pick them up one by one, resulting in a lengthy and inefficient process. More seriously, when installing washers, springs, and nuts on 6mm-22mm screws, the lack of effective fixing force between the gloves and the parts often leads to slippage, frequently causing Class C and D violations and significantly increasing operational safety risks, creating a vicious cycle of inconvenience, inefficiency, and safety hazards.

[0022] To address the aforementioned issues, this application proposes an adsorption control method for magnetic gloves and a magnetic glove itself. Through a collaborative mechanism of intelligent magnetic force regulation and real-time pressure feedback, the method comprehensively optimizes the picking up of small metal parts, solving the problems of difficulty in picking up small metal parts and easy detachment during installation in traditional live-line work. This significantly improves operational efficiency, greatly reduces the probability of parts slipping, effectively reduces violations during operations, and significantly reduces the safety risks of high-altitude operations. Ultimately, it forms an efficient, safe, and compliant operational technology system, providing reliable technical support for live-line work in distribution networks. The specific implementation principle will be described in detail in the following embodiments.

[0023] This application provides a method for controlling the adsorption of magnetic gloves in its first aspect.

[0024] Please see Figure 1 This is a schematic diagram of an adsorption control method for a magnetic glove according to an embodiment of this application. The method includes: Step 110: Obtain an image of the target object to be adsorbed.

[0025] In some embodiments, the target object to be adsorbed includes, but is not limited to, metal parts such as nuts, springs, and washers of various specifications.

[0026] Step 120: Extract features from the object image to obtain comprehensive feature data, and input the comprehensive feature data into the preset adsorption magnetic force prediction model to obtain the adsorption magnetic force.

[0027] Here, the preset adsorption magnetic force prediction model refers to a model that has been trained in advance and is used to predict the output adsorption magnetic force based on the comprehensive feature data of the input.

[0028] For comprehensive feature data, in some embodiments, comprehensive feature data includes, but is not limited to, object type, object size, object texture, object shape, etc.

[0029] In some embodiments, the training method for the preset magnetic adsorption prediction model involves acquiring images of metal parts such as nuts, springs, and washers of various specifications. Feature extraction is then performed on each of these images to obtain comprehensive feature data for the various specifications of the metal parts. An operator then uses experimental magnetic gloves to apply the required magnetic force to these metal parts. The comprehensive feature data and magnetic force of these metal parts are then input into the initial magnetic adsorption prediction model for training. Once the model has been trained to a certain extent, the preset magnetic adsorption prediction model is obtained. The determination of when the model can be applied after training can be made by setting a loss function.

[0030] Regarding the model type for the initial adsorption magnetic force prediction model, in some embodiments, the operator may choose an existing machine learning model or a deep learning network model according to actual needs, and no limitation is made here.

[0031] Step 130: Based on the magnetic attraction force, control the magnetic gloves to attract the target object.

[0032] In some embodiments, magnetic gloves can be obtained by embedding an adjustable magnetic block into a puncture-resistant glove.

[0033] Regarding the adsorption method for the target object, in some embodiments, the magnetic blocks in the magnetic gloves can be controlled to generate the same magnetic force as the adsorption magnetic force to adsorb the target object.

[0034] Step 140: After the magnetic glove adsorbs the target object, obtain the real-time pressure value between the magnetic glove and the target object, and adjust the magnetic force in real time according to the real-time pressure value to obtain the adjusted magnetic force.

[0035] Regarding the method of obtaining real-time pressure values, in some embodiments, an array pressure sensor can be provided in the magnetic glove to obtain real-time pressure values ​​through the array pressure sensor.

[0036] It should be noted that since the magnetic force of adsorption is predicted by a preset magnetic force prediction model, it is capable of adsorbing the target object. However, in order to avoid unstable adsorption or excessive adsorption during the movement of the target object by the magnetic glove, the real-time pressure value between the magnetic glove and the target object is required to precisely adjust the magnetic force in real time. This allows for real-time fine-tuning of the magnetic force during movement, thereby improving the adsorption effect.

[0037] Step 150: Based on the real-time fine-tuned magnetic force, control the magnetic gloves to adsorb the target object in real time.

[0038] After real-time fine-tuning of the magnetic adsorption force, in some embodiments, the magnetic blocks in the magnetic gloves can be controlled in real time to generate the same magnetic force as the real-time fine-tuned magnetic adsorption force to adsorb the target object.

[0039] In this embodiment, the synergistic mechanism of intelligent magnetic control and real-time pressure feedback comprehensively optimizes the picking of small metal parts, solving the problems of difficulty in picking up small metal parts and easy detachment during installation in traditional live-line work. This significantly improves operational efficiency, greatly reduces the probability of parts slipping, effectively reduces violations during operation, and significantly reduces the safety risks of high-altitude operations. Ultimately, it forms an efficient, safe, and compliant operation technology system, providing reliable technical support for live-line work in distribution networks.

[0040] In addition to the aforementioned beneficial effects, the magnetic glove's adsorption control method and the magnetic glove itself also have the following advantages: Reduced operator fatigue: In traditional methods, workers use thin iron or aluminum wires to pick up small metal parts one by one, requiring frequent adjustments to tools and body posture. Prolonged operation easily leads to muscle fatigue in the arms, wrists, and other areas. The magnetic glove of this application, however, directly adsorbs parts through intelligent magnetic control, reducing unnecessary movements and force, and lowering operator fatigue. Especially during long-term high-altitude work, it effectively improves the operator's strength and endurance, ensuring continuous operation; Improved operational accuracy: Due to physical limitations, traditional gloves make it difficult for operators to directly grasp small parts, resulting in low operational accuracy. The magnetic glove of this application... The magnetic gloves can precisely control the magnetic force of adsorption based on the comprehensive characteristic data of the target object, achieving precise adsorption. Furthermore, under a real-time pressure feedback mechanism, the magnetic force can be fine-tuned according to actual conditions, further improving the accuracy of adsorption. This allows operators to more accurately install parts into designated positions, reducing repetitive operations and errors caused by inaccurate operation. It also enhances operator confidence: In traditional operation methods, parts frequently slip off, increasing the difficulty and risk of the operation and causing psychological pressure and frustration for operators. The magnetic gloves of this application significantly reduce the probability of parts slipping, allowing operators to complete tasks more smoothly, thereby enhancing their confidence and approaching the work with a more positive attitude. Finally, it improves the standardization of operations: The magnetic gloves, through a preset magnetic force prediction model and a real-time pressure feedback mechanism, achieve intelligent control of the magnetic force, ensuring a relatively uniform standard and procedure for each adsorption operation. This helps improve the standardization of live-line work on the entire distribution network, reducing inconsistencies in work quality caused by individual differences in operators and their operating habits, and improving the overall work level. It also shortens the training cycle: traditional methods require operators to spend a significant amount of time practicing techniques for picking up parts using thin iron or aluminum wires, and mastering the key points of operating under multiple layers of protective gloves, resulting in a lengthy training period. In contrast, the magnetic gloves of this application are relatively simple and intuitive to operate; operators only need to understand the adsorption control method and basic operating procedures, and can complete the training in a shorter period. The magnetic gloves are easy to operate, significantly shortening the training cycle and reducing training costs; they also extend glove lifespan: in traditional operations, workers may overstretch or twist gloves to pick up small parts, easily damaging the protective structure and shortening the gloves' lifespan. The magnetic gloves of this application use magnetic force to attract parts, reducing physical damage to the gloves, extending their lifespan, and lowering replacement costs; and they reduce equipment maintenance costs: because the magnetic gloves of this application improve work efficiency and accuracy, they reduce the probability of equipment damage and malfunctions caused by improper operation, thereby reducing equipment maintenance costs. For example, when installing parts, they reduce the possibility of parts slipping and impacting the equipment, protecting the integrity of the equipment.

[0041] In one feasible implementation, step 140 in the above embodiment, which involves real-time fine-tuning of the adsorption magnetic force based on the real-time pressure value to obtain the real-time fine-tuned adsorption magnetic force, includes: obtaining a stable adsorption pressure value for the target object to be adsorbed and moved by the magnetic glove based on comprehensive feature data; determining a real-time pressure deviation value based on the real-time pressure value and the stable adsorption pressure value; and fine-tuning the adsorption magnetic force based on the real-time pressure deviation value to obtain the real-time fine-tuned adsorption magnetic force.

[0042] In some embodiments, the difference between the real-time pressure deviation value and the stable adsorption pressure value can be used as the real-time pressure deviation value.

[0043] It should be noted that the stable adsorption pressure value refers to the pressure value at which the target object is stably adsorbed during the process of being adsorbed and moved by the magnetic glove. It can be obtained by the operator through experiments on the stable adsorption pressure value of various specifications of metal parts such as nuts, springs, and washers by the magnetic glove. Multiple pressure values ​​can be obtained for each specification of metal part through experiments, and the maximum value is generally taken.

[0044] In this embodiment of the application, by obtaining the stable adsorption pressure value of the target object being attracted and moved by the magnetic glove, the magnetic force of adsorption can be finely adjusted in real time, so as to achieve more precise real-time fine adjustment of the magnetic force of adsorption and further improve the adsorption effect and work quality.

[0045] Understandably, by obtaining the stable adsorption pressure value of the target object being attracted and moved by the magnetic glove based on comprehensive feature data, a precise reference benchmark is provided for fine-tuning the magnetic force. This is because the pressure value required for stable adsorption varies for metal parts of different specifications. Clarifying this value allows for more targeted adjustments. By determining the real-time pressure deviation value based on the real-time pressure value and the stable adsorption pressure value, the difference between the current adsorption state and the ideal stable adsorption state can be clearly understood. Finally, the magnetic force is fine-tuned in real time based on the real-time pressure deviation value, resulting in a finely tuned magnetic force. This ensures that the magnetic force remains in the most suitable state during the adsorption and movement of the target object, avoiding unstable or excessively strong adsorption, effectively improving the accuracy and stability of adsorption, and thus enhancing the quality and efficiency of the entire operation.

[0046] In one feasible implementation, the comprehensive feature data in the above embodiments includes object type and object size.

[0047] In the above embodiments, obtaining the stable adsorption pressure value of the target object being attracted and moved by the magnetic glove based on comprehensive feature data includes: matching the object mass and friction coefficient in a preset matching table according to the object type and size to obtain the object mass of the target object and the friction coefficient between the target object and the magnetic glove; and determining the stable adsorption pressure value based on the object mass and friction coefficient.

[0048] The preset matching table can be set in advance by the operator based on a large number of experiments.

[0049] In this embodiment, a stable adsorption pressure value is determined by matching the object mass and friction coefficient using a preset matching table. This allows for more accurate and efficient acquisition of the stable adsorption pressure value, improves the accuracy of fine-tuning the adsorption magnetic force, and ensures the quality of the operation.

[0050] Understandably, this approach, which defines comprehensive feature data as object type and size, and then matches object mass and friction coefficient in a pre-defined matching table based on these two key pieces of information, has significant advantages. On the one hand, object type and size are important factors affecting object mass and friction coefficient; using them as the basis for matching makes the matching results more consistent with reality, improving the accuracy of obtaining object mass and friction coefficient. On the other hand, the pre-defined matching table is set up in advance based on a large number of experiments. Operators do not need to perform complex calculations or multiple experiments on-site; they can quickly match the required data from the table and thus quickly determine the stable adsorption pressure value. This allows for precise adjustments to the adsorption magnetic force in real time based on the real-time pressure value, avoiding unstable or excessive adsorption, effectively improving the accuracy and stability of adsorption, and ensuring the quality and efficiency of the entire operation.

[0051] In one feasible implementation, determining the stable adsorption pressure value based on the object's mass and coefficient of friction in the above embodiments includes: Using formula Determine the stable adsorption pressure value; in, To stabilize the adsorption pressure value, For the mass of the object, The coefficient of friction, It is the acceleration due to gravity. It is a cosine function. To preset the adsorption surface tilt angle, It is a sine function. This is the preset acceleration.

[0052] It should be noted that the preset adsorption surface tilt angle refers to the maximum adsorption surface tilt angle during the process of the target object being adsorbed and moved by the magnetic glove; the preset acceleration refers to the maximum acceleration during the process of the target object being adsorbed and moved by the magnetic glove; both the preset adsorption surface tilt angle and the preset acceleration can be preset by the operator based on a large number of experiments.

[0053] In this embodiment of the application, a specific formula is used to provide a scientific and accurate calculation method for determining the stable adsorption pressure value, ensuring the accuracy of fine-tuning the adsorption magnetic force and improving the quality of the operation.

[0054] Understandably, determining a stable adsorption pressure value using a formula that includes parameters such as object mass, coefficient of friction, gravitational acceleration, preset adsorption surface inclination angle, and preset acceleration is a highly scientific and precise method. Each parameter setting is based on practical evidence. The preset adsorption surface inclination angle and preset acceleration are pre-set by operators based on numerous experiments, reflecting the actual working conditions of the target object during the magnetic glove's adsorption and movement. Calculations based on these parameters yield a stable adsorption pressure value that more closely matches reality. This provides a precise reference for subsequent real-time fine-tuning of the magnetic force based on the real-time pressure value, effectively avoiding unstable or excessively strong adsorption, thereby improving the accuracy and stability of adsorption and ensuring the quality and efficiency of the entire operation.

[0055] In one feasible implementation, the real-time fine-tuning of the adsorption magnetic force based on the real-time pressure deviation value in the above embodiments to obtain the real-time fine-tuned adsorption magnetic force includes: when the real-time pressure deviation value meets the preset pressure deviation range, using the adsorption magnetic force as the real-time fine-tuned adsorption magnetic force; when the real-time pressure deviation value does not meet the preset pressure deviation range and is greater than the upper limit of the preset pressure deviation range, decreasing the adsorption magnetic force in real-time by a preset step size to obtain the real-time fine-tuned adsorption magnetic force; and when the real-time pressure deviation value does not meet the preset pressure deviation range and is less than the lower limit of the preset pressure deviation range, increasing the adsorption magnetic force in real-time by a preset step size to obtain the real-time fine-tuned adsorption magnetic force.

[0056] The preset pressure deviation range and preset step size can both be preset by the operator based on extensive experience, experiments, or statistics.

[0057] In this embodiment, by comparing the real-time pressure deviation value with the preset pressure deviation range, the adsorption magnetic force can be precisely, flexibly and scientifically adjusted in real time, ensuring adsorption stability and accuracy, and improving the quality of operation.

[0058] Understandably, when the real-time pressure deviation value meets the preset pressure deviation range, the original adsorption magnetic force is used as the real-time fine-tuned adsorption magnetic force. This approach avoids unnecessary adjustments, ensuring that the original appropriate adsorption force is maintained when the adsorption state is stable, saving operation steps and energy consumption. When the real-time pressure deviation value does not meet the preset range and exceeds the upper limit, the adsorption magnetic force is reduced in real time by a preset step size. This prevents high power consumption due to excessive adsorption and avoids damage between the inner cavity and outer wall of the magnetic glove, reducing the lifespan of the magnetic glove. This ensures that the adsorption force matches the actual needs. When the real-time pressure deviation value is less than the lower limit of the preset range, the adsorption magnetic force is increased in real time by a preset step size. This prevents unstable adsorption from causing the target object to slip off, ensuring the reliability of adsorption. By making targeted adjustments based on different real-time pressure deviation values, precise, flexible, and scientific real-time fine-tuning of the adsorption magnetic force is achieved, thereby ensuring the stability and accuracy of adsorption and improving the overall quality of the operation.

[0059] In one feasible implementation, the method in the above embodiments further includes: obtaining real-time pressure deviation values ​​at each time from the start time of the magnetic glove adsorbing the target object to the current time; determining the cumulative pressure deviation value based on the real-time pressure deviation value at each time; determining the pressure deviation value change rate based on the real-time pressure deviation value at the current time; and using a PID control algorithm to determine a preset step size based on the real-time pressure deviation value at the current time, the cumulative pressure deviation value, and the pressure deviation value change rate.

[0060] In this embodiment, the preset step size is determined by comprehensively considering the current real-time pressure deviation value, the cumulative pressure deviation value, and the rate of change of the pressure deviation value using a PID control algorithm. This achieves accurate dynamic determination of the preset step size, ensuring the scientific nature and stability of real-time fine-tuning of the adsorption magnetic force, and improving the quality and efficiency of the operation.

[0061] Understandably, by acquiring the real-time pressure deviation values ​​from the start of the magnetic glove's adsorption of the target object to the current moment, and determining the cumulative pressure deviation value and the rate of change of pressure deviation value accordingly, a PID control algorithm is used to comprehensively consider the current real-time pressure deviation value, the cumulative pressure deviation value, and the rate of change of pressure deviation value to determine the preset step size. This method can comprehensively and accurately reflect the dynamic changes in pressure deviation during the adsorption process. The determination of the preset step size is not based on a single, static factor, but rather integrates historical and current pressure deviation information. In this way, when making real-time fine adjustments to the adsorption magnetic force based on the real-time pressure deviation value, adjustments can be made according to a more scientific and reasonable preset step size, avoiding over- or under-adjustment caused by improper step size setting. This ensures that the real-time fine adjustment of the adsorption magnetic force is always in the most suitable state, thereby guaranteeing the stability and accuracy of adsorption and effectively improving the quality and efficiency of the entire operation.

[0062] In one feasible implementation, the PID control algorithm used in the above embodiments determines a preset step size based on the real-time pressure deviation value, the accumulated pressure deviation value, and the rate of change of the pressure deviation value at the current moment, including: Using formula Determine the preset step size; in, To preset the step size, , and These are the proportional coefficient, integral coefficient, and derivative coefficient of the PID control algorithm. This represents the real-time pressure deviation value at the current moment. To accumulate the pressure deviation value, For the current moment, Let be the real-time pressure deviation value at time t. This represents the rate of change of the pressure deviation value.

[0063] In this embodiment, a preset step size is determined by combining a specific formula with a PID control algorithm, which achieves accurate dynamic determination of the preset step size, ensuring the scientific nature and stability of real-time fine-tuning of the adsorption magnetic force, and improving the quality and efficiency of the operation.

[0064] Understandably, by acquiring the real-time pressure deviation values ​​of the target object at various times, determining the cumulative pressure deviation value and the rate of change of the pressure deviation value, and then using a specific formula combined with a PID control algorithm, the preset step size is determined by comprehensively considering the current real-time pressure deviation value, the cumulative pressure deviation value, and the rate of change of the pressure deviation value. This method comprehensively and accurately reflects the dynamic changes of pressure deviation during the adsorption process, ensuring that the determination of the preset step size does not rely on a single static factor, but rather integrates historical and current pressure deviation information. Thus, when fine-tuning the adsorption magnetic force in real time based on the real-time pressure deviation value, adjustments can be made according to a more scientific and reasonable preset step size, avoiding over-adjustment or under-adjustment, ensuring that the real-time fine-tuning of the adsorption magnetic force is in the most suitable state, thereby guaranteeing the stability and accuracy of adsorption, and effectively improving the quality and efficiency of the operation.

[0065] In one feasible implementation, the comprehensive feature data in the above embodiments includes object type and object size.

[0066] Step 120 in the above embodiment involves extracting features from the object image to obtain comprehensive feature data, including: inputting the object image into a preset object recognition model to obtain the object type and object size of the target object.

[0067] Here, the preset object recognition model refers to a model that has been trained in advance and is used to predict the type and size of the output object based on the input object image.

[0068] In some embodiments, the training method for the preset object recognition model can involve acquiring images of metal parts such as nuts, springs, and washers of various specifications. The operator can then label the object type and size. The images of the metal parts such as nuts, springs, and washers of various specifications, along with the object type and size, are then input into the initial object recognition model for training. Once the training reaches a certain level, the preset object recognition model can be obtained. The method for determining when the model can be applied after training can be determined by setting a loss function.

[0069] Regarding the model type of the initial object recognition model, in some embodiments, the operator may choose an existing machine learning model or a deep learning network model according to actual needs, and no limitation is made here.

[0070] In this embodiment, the object type and size are predicted by a preset object recognition model, which improves the efficiency and accuracy of feature extraction, ensures the accuracy of adsorption magnetic force prediction, and helps improve the quality and efficiency of the operation.

[0071] Understandably, by inputting an object image into a pre-set object recognition model to obtain the object type and size as comprehensive feature data, and by having the pre-set object recognition model trained on a large amount of data, it can quickly and accurately identify the object type and size in the image. Compared with manual feature extraction or other complex methods, this greatly improves the efficiency of feature extraction and is more accurate. The accurate comprehensive feature data is input into the pre-set adsorption magnetic force prediction model, which can provide a reliable basis for predicting the precise adsorption magnetic force, thereby ensuring the precise control of the adsorption magnetic force in subsequent adsorption operations, effectively avoiding unstable or excessive adsorption, improving the accuracy and stability of adsorption, and ultimately helping to improve the quality and efficiency of the entire operation.

[0072] In one feasible implementation, the method in the above embodiments further includes: acquiring key operation instructions based on the user's key operation; and controlling the magnetic gloves to release the target object according to the key operation instructions.

[0073] Regarding the method of obtaining key operation commands, in some embodiments, key operation commands are generated in response to the user's key operation.

[0074] In this embodiment, key operation instructions are generated and obtained through user key operations, enabling precise release of the target object and improving operational flexibility and safety.

[0075] Understandably, during the operation, the user generates and obtains key operation instructions through key presses, and controls the magnetic gloves to release the target object based on these instructions. This operation method provides operators with a direct and convenient means of control. Operators can accurately release parts at the appropriate time according to actual work needs, without complicated operation procedures, which greatly improves the flexibility of the operation. At the same time, accurate release avoids safety risks caused by improper release of parts, such as parts falling and injuring equipment or personnel, further ensuring the safety of the operation and helping to carry out the overall operation efficiently, safely and smoothly.

[0076] In a second aspect, this application provides a magnetic glove that includes a live-working glove, a magnetic block, an array of pressure sensors, a miniature camera, and a controller.

[0077] The glove for working with live wires has an inner cavity at the fingertip, with a magnetic block embedded in the cavity. An array of pressure sensors is located between the inner wall of the cavity and the magnetic block on the side closest to the outside. A miniature camera is located next to the magnetic block. The inner cavity has an opening through which the miniature camera communicates with the outside. The magnetic block, the array of pressure sensors, and the miniature camera are all connected to the controller.

[0078] In one feasible implementation, a magnetic block is used to attract a target object to be attracted; a miniature camera is used to capture an image of the target object; an array pressure sensor is used to detect the real-time pressure value between the magnetic block and the target object after the magnetic block attracts the target object; and a controller is used to execute the magnetic glove attraction control method as described in any of the first aspects.

[0079] It should be noted that live-line working gloves refer to puncture-resistant gloves; the magnetic block refers to a magnetic block with adjustable magnetic force, and the magnetic block can be made of soft, strong magnetic material; the controller can control the magnetic force generated by the magnetic block.

[0080] In other embodiments, the magnetic glove also includes a button, with the button located between the inner cavity on the side away from the outside and the magnetic block.

[0081] In this embodiment, the magnetic glove includes a live-line working glove, a magnetic block, an array pressure sensor, a miniature camera, and a controller. The magnetic glove has a scientific and reasonable structural design, which effectively improves the adsorption accuracy and operational safety, and helps to achieve efficient, stable, and flexible live-line work.

[0082] Understandably, this magnetic glove features an inner cavity at the fingertip of the index finger of the live-work glove, embedding an adjustable magnetic block. This design allows the magnetic block to precisely act on the target object, facilitating flexible operation and accurate adsorption. An array of pressure sensors positioned between the inner wall of the inner cavity and the magnetic block near the outside can detect the pressure value between the two objects in real time after the magnetic block adsorbs the target object. This provides accurate data for real-time fine-tuning of the magnetic force, preventing unstable or excessive adsorption and ensuring the stability and accuracy of the adsorption. A miniature camera positioned next to the magnetic block connects to the outside through an opening in the inner cavity, capturing images of the target object. This provides a basis for obtaining comprehensive feature data and predicting the magnetic force, improving the accuracy of magnetic force prediction. The controller connects to the magnetic block, array of pressure sensors, and miniature camera, executing the magnetic glove's adsorption control method. It comprehensively regulates the operation of each component, achieving a collaborative mechanism of intelligent magnetic force control and real-time pressure feedback, comprehensively improving work quality and efficiency.

[0083] In addition, buttons are set between the inner cavity and the magnetic block on the side away from the outside. Based on the user's button operation, button operation commands are generated and obtained, which can control the magnetic gloves to release the target object, giving the operator a direct and convenient means of control, improving the flexibility and safety of the operation, and avoiding safety risks caused by improper release of parts.

[0084] In a third aspect, this application provides an adsorption control device for magnetic gloves.

[0085] Please see Figure 2 This is a schematic diagram of an adsorption control device for a magnetic glove according to an embodiment of this application. The device 210 includes: The acquisition module 211 is used to acquire an object image of the target object to be adsorbed; The feature extraction and model prediction module 212 is used to extract features from the object image, obtain comprehensive feature data, and input the comprehensive feature data into the preset adsorption magnetic force prediction model to obtain the adsorption magnetic force. The initial adsorption control module 213 is used to control the magnetic gloves to adsorb the target object based on the magnetic force. The real-time fine-tuning module 214 is used to obtain the real-time pressure value between the magnetic glove and the target object after the magnetic glove adsorbs the target object, and to fine-tune the adsorption magnetic force in real time according to the real-time pressure value to obtain the adsorption magnetic force after real-time fine-tuning. The real-time adsorption control module 215 is used to control the magnetic gloves to adsorb target objects in real time based on the adsorption magnetic force after real-time fine-tuning.

[0086] In this embodiment, the relevant contents of the acquisition module 211, feature extraction and model prediction module 212, initial adsorption control module 213, real-time fine-tuning module 214 and real-time adsorption control module 215 can be found in the following references. Figure 1 The contents of the illustrated embodiments will not be repeated here.

[0087] It should be noted that the device 210 of this application also includes other modules. It can be understood that the method of this application and the device 210 have a one-to-one correspondence. Therefore, the other modules of the device 210 of this application are the contents corresponding to the method of this application in the above embodiments.

[0088] In this embodiment, the synergistic mechanism of intelligent magnetic control and real-time pressure feedback comprehensively optimizes the picking of small metal parts, solving the problems of difficulty in picking up small metal parts and easy detachment during installation in traditional live-line work. This significantly improves operational efficiency, greatly reduces the probability of parts slipping, effectively reduces violations during operation, and significantly reduces the safety risks of high-altitude operations. Ultimately, it forms an efficient, safe, and compliant operation technology system, providing reliable technical support for live-line work in distribution networks.

[0089] In addition to the aforementioned beneficial effects, the magnetic glove's adsorption control device and the magnetic glove itself also have the following advantages: Reduced operator fatigue: In traditional methods, workers use thin iron or aluminum wires to pick up small metal parts one by one, requiring frequent adjustments to tools and body posture. Prolonged operation easily leads to muscle fatigue in the arms and wrists. The magnetic glove of this application, however, directly adsorbs parts through intelligent magnetic control, reducing unnecessary movements and force, thus lowering operator fatigue. Especially during long-term high-altitude work, it effectively improves the operator's strength and endurance, ensuring continuous operation; Improved operational accuracy: Due to physical limitations, traditional gloves make it difficult for operators to directly grasp small parts, resulting in low operational accuracy. The magnetic glove of this application... The magnetic gloves can precisely control the magnetic force of adsorption based on the comprehensive characteristic data of the target object, achieving precise adsorption. Furthermore, under a real-time pressure feedback mechanism, the magnetic force can be fine-tuned according to actual conditions, further improving the accuracy of adsorption. This allows operators to more accurately install parts into designated positions, reducing repetitive operations and errors caused by inaccurate operation. It also enhances operator confidence: In traditional operation methods, parts frequently slip off, increasing the difficulty and risk of the operation and causing psychological pressure and frustration for operators. The magnetic gloves of this application significantly reduce the probability of parts slipping, allowing operators to complete tasks more smoothly, thereby enhancing their confidence and approaching the work with a more positive attitude. Finally, it improves the standardization of operations: The magnetic gloves, through a preset magnetic force prediction model and a real-time pressure feedback mechanism, achieve intelligent control of the magnetic force, ensuring a relatively uniform standard and procedure for each adsorption operation. This helps improve the standardization of live-line work on the entire distribution network, reducing inconsistencies in work quality caused by individual differences in operators and their operating habits, and improving the overall work level. It also shortens the training cycle: traditional methods require operators to spend a significant amount of time practicing techniques for picking up parts using thin iron or aluminum wires, and mastering the key points of operating under multiple layers of protective gloves, resulting in a lengthy training period. In contrast, the magnetic gloves of this application are relatively simple and intuitive to operate; operators only need to understand the adsorption control device and basic operating procedures, and can complete the training in a shorter period. The magnetic gloves are easy to operate, significantly shortening the training cycle and reducing training costs; they also extend glove lifespan: in traditional operations, workers may overstretch or twist gloves to pick up small parts, easily damaging the protective structure and shortening the gloves' lifespan. The magnetic gloves of this application use magnetic force to attract parts, reducing physical damage to the gloves, extending their lifespan, and lowering replacement costs; and they reduce equipment maintenance costs: because the magnetic gloves of this application improve work efficiency and accuracy, they reduce the probability of equipment damage and malfunctions caused by improper operation, thereby reducing equipment maintenance costs. For example, when installing parts, they reduce the possibility of parts slipping and impacting the equipment, protecting the integrity of the equipment.

[0090] In a fourth aspect, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform an adsorption control method for a magnetic glove as described in any of the first aspects.

[0091] This application provides a computer device in a fifth aspect, including a memory and a processor, the memory storing a computer program, which, when executed by the processor, causes the processor to perform an adsorption control method for a magnetic glove as described in any of the first aspects.

[0092] Figure 3 The diagram illustrates the internal structure of a computer device in some embodiments. This computer device may specifically be a terminal, a server, or a gateway. Figure 3 As shown, the computer device includes a processor, memory, and network interface connected via a system bus.

[0093] The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When executed by a processor, this computer program causes the processor to perform the steps in the above method embodiments. The internal memory may also store a computer program, which, when executed by a processor, causes the processor to perform the steps in the above method embodiments. Those skilled in the art will understand that... Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0094] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods.

[0095] Any references to memory, storage, database, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0096] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0097] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

Claims

1. A method for controlling the adsorption of magnetic gloves, characterized in that, The method includes: Obtain an image of the target object to be adsorbed; Feature extraction is performed on the object image to obtain comprehensive feature data, and the comprehensive feature data is input into a preset adsorption magnetic force prediction model to obtain the adsorption magnetic force; Based on the adsorption magnetic force, the magnetic gloves are controlled to adsorb the target object; After the magnetic glove adsorbs the target object, the real-time pressure value between the magnetic glove and the target object is obtained, and the magnetic force of adsorption is fine-tuned in real time according to the real-time pressure value to obtain the adsorption magnetic force after real-time fine-tuning. Based on the real-time fine-tuned magnetic force, the magnetic gloves are controlled to adsorb the target object in real time.

2. The adsorption control method for the magnetic gloves according to claim 1, characterized in that, The step of fine-tuning the adsorption magnetic force in real time based on the real-time pressure value to obtain the fine-tuned adsorption magnetic force includes: Based on the comprehensive feature data, obtain the stable adsorption pressure value of the target object being adsorbed and moved by the magnetic glove; The real-time pressure deviation value is determined based on the real-time pressure value and the stable adsorption pressure value. Based on the real-time pressure deviation value, the adsorption magnetic force is finely adjusted in real time to obtain the adsorption magnetic force after real-time fine adjustment.

3. The adsorption control method for the magnetic gloves according to claim 2, characterized in that, The comprehensive feature data includes object type and object size. The step of obtaining a stable adsorption pressure value for the target object to be attracted and moved by the magnetic glove based on the comprehensive feature data includes: Based on the object type and the object size, the object mass and friction coefficient are matched in a preset matching table to obtain the object mass of the target object and the friction coefficient between the target object and the magnetic glove; The stable adsorption pressure value is determined based on the mass of the object and the coefficient of friction.

4. The adsorption control method for the magnetic gloves according to claim 3, characterized in that, Determining the stable adsorption pressure value based on the object's mass and the coefficient of friction includes: Using formula Determine the stable adsorption pressure value; in, The stable adsorption pressure value is... The mass of the object. The friction coefficient is... It is the acceleration due to gravity. It is a cosine function. To preset the adsorption surface tilt angle, It is a sine function. This is the preset acceleration.

5. The adsorption control method for the magnetic gloves according to claim 2, characterized in that, The step of fine-tuning the adsorption magnetic force in real time based on the real-time pressure deviation value to obtain the fine-tuned adsorption magnetic force includes: If the real-time pressure deviation value meets the preset pressure deviation range, the adsorption magnetic force is used as the adsorption magnetic force after real-time fine-tuning. If the real-time pressure deviation value does not meet the preset pressure deviation range and the real-time pressure deviation value is greater than the upper limit of the preset pressure deviation range, the adsorption magnetic force is reduced in real time by a preset step size to obtain the real-time fine-tuned adsorption magnetic force. If the real-time pressure deviation value does not meet the preset pressure deviation range and the real-time pressure deviation value is less than the lower limit of the preset pressure deviation range, the adsorption magnetic force is increased in real time according to the preset step size to obtain the real-time fine-tuned adsorption magnetic force.

6. The adsorption control method for the magnetic gloves according to claim 5, characterized in that, The method further includes: The real-time pressure deviation values ​​at each moment from the start time when the magnetic glove adsorbs the target object to the current time are obtained; The cumulative pressure deviation value is determined based on the real-time pressure deviation value at each moment; The rate of change of the pressure deviation value is determined based on the real-time pressure deviation value at the current moment; Using a PID control algorithm, the preset step size is determined based on the real-time pressure deviation value at the current moment, the accumulated pressure deviation value, and the rate of change of the pressure deviation value.

7. The adsorption control method for the magnetic glove according to claim 6, characterized in that, The step size is determined using a PID control algorithm based on the real-time pressure deviation value, the accumulated pressure deviation value, and the rate of change of the pressure deviation value. This includes: Using formula Determine the preset step size; in, The preset step size, , and These are the proportional coefficient, integral coefficient, and derivative coefficient of the PID control algorithm, respectively. The real-time pressure deviation value at the current moment. The accumulated pressure deviation value, For the current time, Let be the real-time pressure deviation value at time t. The rate of change of the pressure deviation value is denoted as .

8. The adsorption control method for the magnetic gloves according to claim 1, characterized in that, The comprehensive feature data includes object type and object size. The step of extracting features from the object image to obtain the comprehensive feature data includes: The object image is input into a preset object recognition model to obtain the object type and object size of the target object.

9. The adsorption control method for the magnetic gloves according to claim 1, characterized in that, The method further includes: Get key operation commands based on user key presses; According to the button operation command, the magnetic gloves are controlled to release the target object.

10. A magnetic glove, characterized in that, The magnetic gloves include live working gloves, magnetic blocks, array pressure sensors, miniature cameras, and controllers; The index fingertip of the live-line working glove has an inner cavity, in which the magnetic block is embedded. An array pressure sensor is provided between the inner wall of the inner cavity near the outside and the magnetic block. A miniature camera is provided next to the magnetic block. The inner cavity has an opening through which the miniature camera communicates with the outside. The magnetic block, the array pressure sensor, and the miniature camera are all connected to the controller. The magnetic block is used to attract the target object to be attracted; The miniature camera is used to capture images of the target object and obtain an image of the target object. The array pressure sensor is used to detect the real-time pressure value between the magnetic block and the target object after the magnetic block attracts the target object; The controller is used to perform the adsorption control method for the magnetic gloves as described in any one of claims 1 to 9.

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