Lead ingot automatic feeding precision control system based on visual positioning and multi-dimensional limiting

Abstract

The application discloses a lead ingot automatic feeding precision control system based on visual positioning and multi-dimensional limiting, relates to the technical field of lead sleeve production, and integrates a visual positioning module, a multi-dimensional limiting control module, a precision control core module and a data interaction module to construct a full-process closed-loop control system: the visual positioning provides accurate lead ingot position and posture data, the multi-dimensional limiting realizes dynamic adaptive transfer constraint and state feedback, the precision control core completes multi-parameter collaborative regulation, and the data interaction guarantees information linkage between modules and external systems, so that the lead liquid level, the main machine current and the lead sleeve thickness are collaboratively stabilized through control logic optimization, and the problems of disconnection between positioning and transfer, isolated regulation parameters and insufficient adaptability in traditional technologies are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of lead sleeve production technology, specifically to an automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting. Background Technology

[0002] In the production process of lead-sheathed land and submarine cables, the stability control of lead ingot feeding and molten lead is crucial. Its accuracy determines the uniformity of lead sheath thickness and the final product molding effect. As a key protective layer of the cable, the uniformity of lead sheath thickness has a profound impact on the electrical performance, mechanical performance and service life of the cable. In the continuous production of long-length land and submarine cables, the traditional lead ingot feeding control mode is no longer suitable for the automation and precision control requirements of modern production lines. There is an urgent need to build a precision control system that takes into account both positioning accuracy and control coordination.

[0003] Traditional lead ingot feeding technology has significant shortcomings in visual positioning, multi-dimensional limiting, and collaborative precision control: In the positioning stage, traditional methods rely heavily on manual or simple mechanical positioning, which cannot accurately identify the outline edge, stacking state, and posture parameters of lead ingots. This can easily lead to misalignment and inaccurate feeding due to positioning deviations. In the limiting stage, traditional limiting structures are mostly single-dimensional constraints with fixed thresholds, lacking dynamic adjustment capabilities. They cannot adapt to the transportation needs of lead ingots of different specifications and lack real-time feedback mechanisms for posture stability and position deviation during transportation, making it difficult to achieve dynamic calibration of the transportation trajectory. In terms of precision control logic, traditional technologies often adopt a single-parameter independent control mode, failing to establish a collaborative control relationship between positioning data, transportation status data, lead liquid level, main engine current, and lead sleeve thickness. This prevents the formation of closed-loop control logic, leading to disconnection of parameter control during production. This can easily cause problems such as lead liquid level fluctuations and unstable main engine current, which in turn affect the quality of lead sleeve forming and are difficult to adapt to the process requirements of continuous production of long submarine cables. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting. It can construct a closed-loop control system for the entire process by integrating a visual positioning module, a multi-dimensional limiting control module, a precision control core module, and a data interaction module. Visual positioning provides accurate lead ingot position and attitude data, multi-dimensional limiting realizes dynamically adapted transfer constraints and status feedback, the precision control core completes multi-parameter coordinated regulation, data interaction ensures information linkage between modules and with external systems, and the control logic optimization achieves coordinated stability of lead liquid level, main unit current, and lead sleeve thickness. It effectively solves the problems of disconnection between positioning and transfer, isolated control parameters, and insufficient adaptability in traditional technologies.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: an automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting, the system comprising: a visual positioning module, a multi-dimensional limiting control module, a precision control core module and a data interaction module; The visual positioning module is used to acquire image information of lead ingots, process the images to identify the outline edges, stacking state, position coordinates and posture of the lead ingots, and output positioning data. The multi-dimensional limit control module generates limit control commands based on visual positioning data, and realizes multi-dimensional limit constraints in the lead ingot transfer process through spatial posture calibration and motion trajectory optimization. At the same time, it collects feedback data on the state related to posture stability and position deviation during the lead ingot transfer process. The precision control core module includes a liquid level control unit, a current stabilization unit, and a thickness adjustment unit. It receives positioning data and multi-dimensional limit feedback data, and combines them with production line operating parameters to achieve coordinated control of lead liquid level, main unit current, and lead sleeve thickness. The data interaction module is used to realize data transmission between modules and information interaction with external production management systems.

[0006] Furthermore, the visual positioning module is equipped with a binocular depth camera and a ring light source. The ring light source provides a stable and uniform illumination environment for image acquisition. The binocular depth camera synchronously acquires images of the lead ingots at the storage location, simultaneously obtaining two-dimensional images and three-dimensional depth information of the lead ingots. After acquisition, the images are preprocessed first. Annoying algorithms are used to eliminate image noise caused by environmental interference, and image distortion correction technology is used to correct camera imaging deviations. Subsequently, feature analysis is performed on the preprocessed images to extract key feature points on the surface of the lead ingots. The outline edges of the lead ingots are delineated using template matching, and the stacking state of the lead ingots is identified. Based on the parallax principle and three-dimensional reconstruction technology of the binocular depth camera, a spatial coordinate system is established by combining the pixel coordinate information of the two-dimensional images. The three-dimensional position coordinates of the lead ingots are calculated. Then, the placement angle and tilt of the lead ingots are analyzed using attitude calculation technology. Finally, the outline edges, stacking state, position coordinates, and attitude information of the lead ingots are integrated to output high-precision positioning data.

[0007] Furthermore, after receiving the lead ingot position and posture data output by the visual positioning module, the multi-dimensional limit control module constructs a three-dimensional transport space coordinate system based on the starting point, key nodes along the route, and the ending point of the lead ingot transport. It performs correlation analysis between the specification parameters of the lead ingot and the path characteristics of the transport path to generate dynamic limit parameters adapted to the current lead ingot and path. During the lead ingot transport process, the actual execution data of translation, lifting, and rotation actions are collected in real time and compared with the dynamic limit parameters in real time. For horizontal deviations that occur during translation, the lateral driving force of the transport mechanism is adjusted in real time for correction. For height deviations during lifting, the lifting stroke is finely adjusted based on the position feedback signal. For angular deviations during rotation, the posture compensation of the rotation axis is used to achieve precise calibration. At the same time, combined with the composite structure characteristics of the lower support and side wrapping of the lead ingot gripping fixture, the force feedback of the bottom support and the clamping state data of the side wrapping are integrated into the limit constraint logic to form a closed-loop control.

[0008] Furthermore, the dynamic limit parameters include the horizontal displacement boundary of translational movement, the vertical height range of lifting movement, the angle range of rotational movement, and the speed threshold of each movement.

[0009] Furthermore, the liquid level control unit analyzes the production line speed and the transfer stability data fed back by the multi-dimensional limit control module to establish a correlation logic between speed, transfer status, and feeding frequency. When the multi-dimensional limit feedback transfer is stable, the optimal feeding frequency is matched according to the production line speed; when the multi-dimensional limit feedback transfer has a slight deviation, the feeding interval is dynamically fine-tuned to achieve precise control of the lead liquid level.

[0010] Furthermore, in the liquid level control unit, when there is a slight deviation in the multi-dimensional limit feedback transfer, the feeding interval is dynamically fine-tuned. The specific steps are as follows: collecting the real-time operating speed of the production line. Deviation between real-time lead liquid level and target level Based on the preset time compensation coefficient and liquid level compensation coefficient Through formula The fine-tuning amount of the feeding interval was calculated. ,in This represents the deviation between the actual transport location of the lead ingot and the preset path. This represents the difference between the real-time lead liquid level and the target liquid level; when When the value is positive, it means that the lead ingot transportation lags behind the preset path. A negative value corresponds to a shorter feeding interval to compensate for the difference in feeding timing. When the value is negative, it means that the lead ingot is transported ahead of the preset path. If the value is positive, the feeding interval should be extended to avoid overfeeding. Simultaneously, the liquid level control unit continuously receives feedback signals from the liquid level sensor inside the furnace and dynamically corrects the readings. , The value of is determined to achieve precise control of the lead liquid level.

[0011] Furthermore, the current stabilization unit establishes a correlation model between the main unit current fluctuation and the amount of metal impurities deposited on the screw surface. Combining the lead ingot transfer status data from multi-dimensional limit feedback, a set current fluctuation value is used as a trigger threshold. When the current fluctuation exceeds the threshold, if the multi-dimensional limit feedback transfer is stable, the current is stabilized primarily through the synergistic effect of additive injection and screw speed adjustment. If there is a deviation in the multi-dimensional limit feedback transfer, the feeding posture compensation parameters are finely adjusted while adjusting the current. Through the synergistic effect of the lubricating isolation film formed by the additive, speed optimization, and feeding posture correction, the superimposed influence of screw rotation resistance and feeding deviation is reduced, thereby stabilizing the main unit current.

[0012] Furthermore, the current stabilization unit establishes a correlation model between the main unit current fluctuation and the amount of metal impurity deposition on the screw surface, by collecting multiple sets of main unit current reference values ​​under standard production conditions. Real-time current fluctuation Screw cumulative running time Lead ingot purity parameters and actual amount of impurities deposited on the screw surface Based on the corresponding data, a sample dataset was constructed; based on the dataset, the correlation between impurity deposition and current fluctuation was analyzed, and a lead ingot purity correction factor was introduced. Screw running time decay index and friction coefficient correlation coefficient Establish the formula for the correlation model: ,in This is the current fluctuation-impurity deposition ratio coefficient. This represents the change in screw friction coefficient caused by impurity deposition, and data is collected in real time. , , and The data can be substituted into the model to calculate the estimated amount of impurity deposition on the screw surface. When the set threshold is exceeded, the required amount of additive injection and the adjustment range of screw speed are calculated based on the model to achieve precise suppression of current fluctuations. At the same time, the model coefficients are continuously corrected to optimize adaptability by combining the actual amount of impurity deposition detected by periodic shutdown.

[0013] Furthermore, the thickness adjustment unit collects data on the stability of the lead ingot transport posture and position deviation from the multi-dimensional limit module, real-time current of the main unit, temperature field distribution data inside the lead extrusion furnace, online detection data of lead sleeve thickness, and production line speed signals. This data is incorporated into a multi-objective coupled control logic. Based on a preset precision control coefficient, the mapping relationship between current stability, transport status, and lead sleeve wall thickness uniformity is quantified. The screw speed reference value is dynamically matched to the production line speed. When current fluctuations exceed a set threshold, the linkage current stabilization unit adjusts the amount of zinc stearate injected to reduce screw friction resistance. Simultaneously, the screw speed compensation is finely adjusted based on the transport status deviation. If the thickness detection data deviates from the nominal value, the coordinated parameters of the speed and additive injection are further corrected based on the deviation amplitude, forming a closed-loop control.

[0014] Compared with existing technologies, this lead ingot automatic feeding precision control system based on visual positioning and multi-dimensional limiting has the following advantages: This invention utilizes a visual positioning module to accurately identify the outline, position, and posture of lead ingots through image preprocessing and feature analysis, providing high-precision basic data for subsequent limit control. A multi-dimensional limit control module, based on dynamic limit parameters, calibrates the translation, lifting, and rotation movements of lead ingot transport in real time, and collects feedback data such as posture stability and position deviation. This adapts to the transport needs of lead ingots of different specifications and provides real-time status data for the precision control core module. The precision control core module integrates three major units: liquid level control, current stabilization, and thickness adjustment. It regulates the lead liquid level through a correlation logic of speed, transport status, and feeding frequency. Combined with current fluctuation threshold triggering additive injection and screw speed adjustment, it ultimately achieves precise control of lead sleeve thickness through multi-objective coupled control. The data interaction module ensures real-time data flow between modules and bidirectional communication with the external production management system, supporting dynamic updates of control parameters. Through data linkage and control logic optimization, it reduces modification and maintenance costs, minimizes manual intervention, and significantly improves the uniformity of lead sleeve thickness and production efficiency.

[0015] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0017] Figure 1This is a structural block diagram of an automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional positioning. Figure 2 This is a structural block diagram of the core control module of the automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting. Figure 3 This is a flowchart of an automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional positioning. Detailed Implementation

[0018] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0019] This invention provides an automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting, such as... Figure 1 As shown, by integrating a visual positioning module, a multi-dimensional limit control module, a precision control core module, and a data interaction module, a closed-loop control system for the entire process is constructed. Visual positioning provides precise lead ingot position and attitude data; multi-dimensional limit control enables dynamically adapted transport constraints and status feedback; the precision control core module completes multi-parameter coordinated regulation; data interaction ensures information linkage between modules and with external systems; and control logic optimization achieves coordinated stability of lead liquid level, main unit current, and lead sleeve thickness. This effectively solves problems such as the disconnect between positioning and transport, isolated control parameters, and insufficient adaptability in traditional technologies. The visual positioning module employs binocular visual positioning technology, simultaneously acquiring images from different angles using two identical binocular depth cameras. The parallax information between the images is used to calculate the three-dimensional spatial position of the target object. Combined with a ring light source, stable imaging is achieved. The ring light source has a 360° uniform illumination structure, effectively offsetting the local light and shadow differences caused by reflections and uneven surfaces of the lead ingot, avoiding image feature distortion caused by light and shadow interference, and ensuring the clarity and consistency of image acquisition. The binocular depth cameras simultaneously acquire two-dimensional texture images and three-dimensional depth information of the lead ingot at the storage location, providing complete raw data support for subsequent positioning calculations.

[0020] After image acquisition, image preprocessing techniques are performed sequentially to optimize the original acquired images and improve the accuracy of subsequent analysis. These key steps include denoising and distortion correction. Denoising uses filtering algorithms to filter out image noise caused by interference factors such as ambient light fluctuations and electronic noise from the camera sensor, preventing noise from obscuring the true features of the lead ingot and affecting subsequent recognition accuracy. Distortion correction, based on intrinsic and extrinsic parameter data obtained from camera calibration, corrects the geometric distortion of the image caused by lens optical characteristics, ensuring that the outline of the lead ingot is accurately reproduced in the image and consistent with its actual physical size.

[0021] The preprocessed images are used for feature extraction through template matching technology. The acquired lead ingot images are compared pixel-level with a preset standard lead ingot template. By calculating the image similarity, the contour edges of the lead ingots are accurately delineated. At the same time, the stacking layers, density, and whether there is tilted stacking are identified. Combining the parallax principle of binocular vision with 3D reconstruction technology, the parallax principle states that the same object has a positional difference in images taken by two cameras. This difference can be used to infer the distance between the object and the camera. The 3D reconstruction technology fuses the pixel coordinates and depth information of the 2D images to construct a 3D coordinate system that includes the spatial positional relationship of the lead ingots. The 3D spatial coordinates of the lead ingots are obtained through coordinate conversion. Then, through attitude calculation technology, based on the feature vector analysis of 3D point cloud data (composed of 3D coordinate points acquired by binocular cameras), the orientation parameters such as the placement angle and tilt of the lead ingots relative to the preset reference coordinate system are calculated, and the attitude deviation value is derived. Finally, the contour edges, stacking state, position coordinates, and attitude information of the lead ingots are integrated to output high-precision positioning data, providing accurate basic data support for subsequent transportation control.

[0022] After receiving the positioning data from the visual positioning module, the multi-dimensional limit control module uses spatial coordinate system construction technology to define the three-dimensional coordinate values ​​of each reference point, taking the starting point, key nodes along the route, and the ending point of the lead ingot transfer as reference points. This establishes a three-dimensional transfer spatial coordinate system covering the entire transfer path. This coordinate system can accurately describe the spatial positional relationship of each point on the transfer path, providing a unified reference benchmark for the limit judgment of transfer actions. Based on the above coordinate system, through dynamic limit parameter generation technology, the lead ingot's length, width, height, and other shape specifications are correlated with the spatial characteristics of the transfer path (such as the curvature of the path, the slope of the uphill and downhill sections, and the clearance distance from surrounding equipment). According to the adaptation requirements under different working conditions, dynamic limit parameters are generated, including the horizontal displacement boundary of translational movements, the vertical height range of lifting movements, the angle range of rotational movements, and the speed threshold of each movement, realizing comprehensive and multi-dimensional constraints on the transfer actions.

[0023] During the lead ingot transfer process, the module employs real-time trajectory calibration and closed-loop control technology. Position and angle sensors installed on the transfer mechanism collect real-time execution data of translation, lifting, and rotation movements, comparing this data with dynamic limit parameters. For horizontal deviations during translation, the output force of the transfer mechanism's drive unit is adjusted for real-time correction. For height deviations during lifting, the stroke of the lifting mechanism is fine-tuned based on position feedback signals. For angular deviations during rotation, precise calibration is achieved through the rotation axis's attitude compensation mechanism. Simultaneously, combined with the lead ingot gripping fixture's lower support and side-hugging composite structure, the pressure sensor feedback from the bottom support and the clamping force sensor status data from the side-hugging components are integrated into the limit constraint logic, forming a closed-loop control system. This ensures that the lead ingot's trajectory remains within the dynamic limit parameter range throughout the entire transfer process, preventing deviations, swaying, or collisions.

[0024] When the multi-dimensional limit control module reports a slight deviation in lead ingot transfer, deviation transmission and timing compensation technology is used to synchronize the transfer deviation data to the liquid level control unit of the precision control core module in real time through a signal transmission link. This establishes a correlation channel between the transfer status and liquid level control. Simultaneously, production line operating speed signals and lead liquid level monitoring data are collected. Timing correlation analysis technology is used to establish a mapping relationship between the deviation and the lead ingot feeding time deviation. That is, the transfer deviation will cause the lead ingot to arrive at the feeding port earlier or later, thus affecting the feeding sequence and lead liquid replenishment rhythm. The required fine-tuning amount of the feeding interval is then calculated using a preset formula: ,in, This is a fine-tuning amount for the feeding interval; a positive value indicates an extended feeding interval, while a negative value indicates a shortened feeding interval. This is a transfer deviation compensation coefficient, calibrated based on the transfer mechanism's response speed and path length, used to quantify the impact of transfer deviation on feeding time. This represents the deviation between the actual transport location of the lead ingot and the preset path. This represents the real-time operating speed of the production line, reflecting the consumption of molten lead per unit time. This is the liquid level deviation compensation coefficient, calibrated based on the furnace volume and lead melting efficiency. It is used to quantify the required feed rate due to liquid level deviation. This represents the difference between the real-time lead liquid level and the target liquid level. A positive value indicates that the liquid level is too high, and a negative value indicates that the liquid level is too low.

[0025] In practice, the feeding interval is dynamically adjusted based on the calculation results: when A positive value indicates that the lead ingot transport is delayed beyond the preset path. A negative output corresponds to a shortened feeding interval, allowing subsequent lead ingots to be fed earlier to compensate for the timing difference in feeding the preceding lead ingots; when A negative value indicates that the lead ingot is transported ahead of the preset path. A positive output corresponds to an extended feeding interval, preventing the lead ingots from being fed too centrally and causing the liquid level to rise excessively. Simultaneously, the liquid level control unit continuously receives real-time feedback signals from the in-furnace liquid level sensor and dynamically adjusts its settings based on the liquid level change trend. , The value of should be appropriately increased if the liquid level deviation continues to increase. The absolute value of the liquid level is used to enhance the liquid level compensation, ensuring that the amount of lead ingots fed into the furnace is dynamically matched with the melting rate of lead liquid and the production consumption rate, ultimately achieving precise control of the lead liquid level and avoiding excessive liquid level fluctuations that could affect the stability of the subsequent lead extrusion process.

[0026] like Figure 2 As shown, the core precision control module includes a liquid level control unit, a current stabilization unit, and a thickness adjustment unit. The current stabilization unit adopts data modeling and collaborative control technology. By establishing a correlation model between operating parameters and equipment status, it achieves precise control of the main unit current and ensures the stability of the main unit operation. First, under standard production conditions with stable temperature, a data acquisition card and sensor group are used to synchronously collect real-time current data of the main unit, screw speed and torque parameters, lead ingot purity data, and cumulative running time information. At the same time, the actual deposition amount of metal impurities on the screw surface during different operating cycles is obtained through phased shutdown detection. Based on this, a sample dataset containing multi-dimensional parameters is established.

[0027] Based on this dataset, correlation modeling techniques were employed, and data analysis algorithms (such as regression analysis and machine learning algorithms) were used to uncover the intrinsic correlation between impurity deposition amount and current fluctuation amplitude and torque change. The influence weight of each parameter on impurity deposition was clarified, and the difference between current fluctuation and the benchmark value was used as the core characterization parameter. A lead ingot purity correction factor and screw operating time decay index were introduced to construct a correlation model between current fluctuation and impurity deposition amount. The formula is as follows: ,in, This is an estimated value for the amount of impurities deposited on the screw surface. The current fluctuation-impurity deposition ratio coefficient, obtained by fitting experimental data, quantifies the direct impact of current fluctuation on impurity deposition. This represents the real-time current fluctuation of the host, i.e., the difference between the real-time current and the reference current. This is the reference value for the main unit current, the stable operating current calibrated under standard operating conditions with no impurity deposition. The cumulative operating time of the screw. The screw operating time decay index reflects the changing trend of impurity deposition rate as operating time increases. It is calibrated by fitting multiple sets of time-series data. This is a lead ingot purity correction factor, calibrated based on the lead ingot composition test results. The higher the purity, the better. The closer the value is to 1, the lower the purity. The smaller the value, the better it is used to correct for the influence of the initial impurity content. The coefficient of friction is used to quantify the indirect impact of changes in the friction coefficient on impurity deposition. This represents the change in the screw friction coefficient caused by impurity deposition.

[0028] In actual production, the current stabilization unit receives real-time transfer status data from multi-dimensional limit feedback and the host current signal through the signal acquisition module. , , and When real-time data is input into the aforementioned correlation model, the estimated value of impurity deposition on the screw surface is dynamically calculated; when current fluctuates... When the set threshold is exceeded, it indicates that impurity deposition has led to increased frictional resistance and a rise in the host load. This triggers a combination of additive injection control technology (which injects lubricating additives into the host by controlling the output of the additive injection pump) and screw speed adjustment technology (which changes the screw speed by adjusting the frequency of the screw drive motor). Through model back-calculation, the appropriate additive injection amount and speed adjustment range are determined to precisely suppress current fluctuations and bring the host current back to a stable range. Simultaneously, model iterative correction technology is employed to continuously correct the model's estimated values ​​by comparing the deviations between the model's values ​​and the actual values ​​based on subsequent current stability feedback data and the actual impurity deposition amount detected during periodic shutdowns. , , By using equal coefficient parameters, the accuracy of model calculations is optimized to ensure that the associated model always adapts to changes in production conditions and maintains stable current control.

[0029] The thickness adjustment unit adopts multi-data coupling analysis and precision control coefficient matching. By integrating multi-dimensional production data, it establishes coupling relationships between data and combines preset precision control coefficients to achieve precise control of lead sleeve thickness. Simultaneously, it collects data on lead ingot transfer posture stability and position deviation from the multi-dimensional limit module, real-time current of the host machine, temperature field distribution data inside the lead extrusion furnace, online detection data of lead sleeve thickness, and production line speed signals. The above multi-dimensional data are incorporated into multi-objective coupling control logic.

[0030] The precision control coefficient is determined in advance through experimental calibration technology. The optimal parameter value is determined by multiple sets of experimental data. Specifically, multiple comparative tests are conducted under different lead ingot specifications and production line speeds to record the current stability, transport status, and wall thickness uniformity data under each condition. The current stability is divided into several levels according to the fluctuation amplitude (e.g., Level 1: fluctuation amplitude ≤ 0.5A, Level 2: 0.5A < fluctuation amplitude ≤ 1A, and so on). The transport status is subdivided into categories such as stable, slight deviation, and intermittent deviation according to the magnitude of the offset and stability. The uniformity of lead sleeve wall thickness is defined by the deviation range between the actual wall thickness and the nominal value. A database of the correspondence between the three is established based on the experimental data, and appropriate precision control coefficients are assigned to different combination scenarios. The smaller the current fluctuation and the more stable the transport status, the closer the precision control coefficient value is to the optimal range for maintaining wall thickness uniformity. When the current fluctuation increases or there is a slight deviation in transport, the precision control coefficient is adjusted accordingly.

[0031] In actual production, the precision control core module analyzes the collected multi-dimensional data in real time through the data processing unit to determine the current current stability level and transport status category. It then retrieves the corresponding precision control coefficient from the preset database. This coefficient is used to link the current regulation, transport deviation compensation, and wall thickness correction logic, and dynamically matches the screw speed reference value with the production line speed. When the current fluctuation exceeds the set threshold, the linkage current stabilization unit precisely regulates the amount of additive injected through additive injection control technology to reduce screw friction resistance. At the same time, it fine-tunes the screw speed compensation amount according to the transport status deviation. If the thickness detection data deviates from the nominal value, the coordination parameters of speed and additive injection are further corrected based on the deviation amplitude, forming a closed-loop control system to ensure that the lead sheath thickness is always maintained within the set accuracy range, adapting to the stringent requirements of lead sheath thickness uniformity in the continuous production of long submarine cables.

[0032] The specific control method of the lead ingot automatic feeding precision control system based on visual positioning and multi-dimensional limiting provided by the present invention includes the following steps: (1) After the system starts, the visual positioning module starts the image acquisition function to acquire images of lead ingots at the storage location. The image noise is removed through preprocessing, and then the image is analyzed and processed to output the outline edge, stacking status, position coordinates and posture data of the lead ingots. (2) The multi-dimensional limit control module receives visual positioning data, constructs a lead ingot transfer spatial coordinate system, generates initial limit parameters according to lead ingot specifications and transfer path, and performs real-time calibration of translation, lifting and rotation actions and limit constraints during lead ingot transfer. At the same time, it collects attitude stability and position deviation related status feedback data during the transfer process. (3) The liquid level control unit of the precision control core module synchronously receives visual positioning data, multi-dimensional limit feedback data and production line speed parameters. Through the correlation logic of speed-transfer status-feeding frequency, it determines the feeding frequency and generates feeding control instructions to control the lead liquid level within the set range. (4) The current stabilization unit of the precision control core module monitors the host current data in real time. Combined with the transfer status data of multi-dimensional limit feedback, when the current fluctuation exceeds the set threshold, the collaborative control logic is triggered. The collaborative parameters of additive injection and screw speed adjustment are adjusted according to the transfer status data, and relevant instructions are executed synchronously. (5) The thickness adjustment unit of the precision control core module collects multi-dimensional limit feedback data, temperature field data, current stability data and lead sleeve thickness detection data, optimizes the control parameters through multi-objective coupling, and corrects the relevant parameters of feeding frequency, screw speed and feeding posture; (6) The data interaction module uploads the positioning data, multi-dimensional limit feedback data, liquid level data, current data and thickness detection data in each step to the external production management system, and at the same time receives process adjustment instructions and dynamically updates the system control parameters and multi-dimensional limit parameters.

[0033] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A precision control system for automatic lead ingot feeding based on visual positioning and multi-dimensional limiting, characterized in that, The system includes: a visual positioning module, a multi-dimensional limit control module, a precision control core module, and a data interaction module; The visual positioning module is used to acquire image information of lead ingots, process the images to identify the outline edges, stacking state, position coordinates and posture of the lead ingots, and output positioning data. The multi-dimensional limit control module generates limit control commands based on visual positioning data, and realizes multi-dimensional limit constraints in the lead ingot transfer process through spatial posture calibration and motion trajectory optimization. At the same time, it collects feedback data on the state related to posture stability and position deviation during the lead ingot transfer process. The precision control core module includes a liquid level control unit, a current stabilization unit, and a thickness adjustment unit. It receives positioning data and multi-dimensional limit feedback data, and combines them with production line operating parameters to achieve coordinated control of lead liquid level, main unit current, and lead sleeve thickness. The data interaction module is used to realize data transmission between modules and information interaction with external production management systems.

2. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 1, characterized in that, The visual positioning module is equipped with a binocular depth camera and a ring light source. The ring light source provides a stable and uniform illumination environment for image acquisition. The binocular depth camera synchronously acquires images of the lead ingots at the storage location, simultaneously obtaining two-dimensional images and three-dimensional depth information of the lead ingots. After acquisition, the images are preprocessed first. Annoying algorithms are used to eliminate image noise caused by environmental interference, and image distortion correction technology is used to correct camera imaging deviations. Subsequently, feature analysis is performed on the preprocessed images to extract key feature points on the surface of the lead ingots. The outline edges of the lead ingots are delineated using template matching, and the stacking state of the lead ingots is identified. Based on the parallax principle and three-dimensional reconstruction technology of the binocular depth camera, a spatial coordinate system is established by combining the pixel coordinate information of the two-dimensional images. The three-dimensional position coordinates of the lead ingots are calculated. Then, the placement angle and tilt of the lead ingots are analyzed by attitude calculation technology. Finally, the outline edges, stacking state, position coordinates, and attitude information of the lead ingots are integrated to output high-precision positioning data.

3. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 1, characterized in that, After receiving the lead ingot position and attitude data output by the visual positioning module, the multi-dimensional limit control module constructs a three-dimensional transfer space coordinate system based on the starting point, key nodes along the route, and the ending point of the lead ingot transfer. It performs correlation analysis between the specification parameters of the lead ingot and the path characteristics of the transfer path to generate dynamic limit parameters adapted to the current lead ingot and path. During the lead ingot transfer process, the actual execution data of translation, lifting, and rotation actions are collected in real time and compared with the dynamic limit parameters in real time. For horizontal deviations that occur during translation, the lateral driving force of the transfer mechanism is adjusted in real time for correction. For height deviations during lifting, the lifting stroke is finely adjusted based on the position feedback signal. For angular deviations in rotation, the posture compensation of the rotation axis is used to achieve precise calibration. At the same time, combined with the composite structure characteristics of the lower support and side wrapping of the lead ingot gripping fixture, the force feedback of the bottom support and the clamping state data of the side wrapping are integrated into the limit constraint logic to form a closed-loop control.

4. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 3, characterized in that, The dynamic limit parameters include the horizontal displacement boundary of translational movement, the vertical height range of lifting movement, the angle range of rotational movement, and the speed threshold of each movement.

5. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 1, characterized in that, The liquid level control unit analyzes the transfer stability data fed back by the production line speed and the multi-dimensional limit control module to establish a correlation logic between speed, transfer status and feeding frequency. When the multi-dimensional limit feedback transfer is stable, the optimal feeding frequency is matched according to the production line speed; when the multi-dimensional limit feedback transfer has a slight deviation, the feeding interval is dynamically fine-tuned to achieve precise control of the lead liquid level.

6. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 5, characterized in that, In the liquid level control unit, when there is a slight deviation in the multi-dimensional limit feedback transfer, the feeding interval is dynamically fine-tuned. The specific steps are as follows: collect the real-time operating speed of the production line. Deviation between real-time lead liquid level and target level Based on the preset time compensation coefficient and liquid level compensation coefficient Through formula The fine-tuning amount of the feeding interval was calculated. ,in This represents the deviation between the actual transport location of the lead ingot and the preset path. This represents the difference between the real-time lead liquid level and the target liquid level; when When the value is positive, it means that the lead ingot transportation lags behind the preset path. A negative value corresponds to a shorter feeding interval to compensate for the difference in feeding timing. When the value is negative, it means that the lead ingot is transported ahead of the preset path. If the value is positive, the feeding interval should be extended to avoid overfeeding. Simultaneously, the liquid level control unit continuously receives feedback signals from the liquid level sensor inside the furnace and dynamically corrects the readings. , The value of is determined to achieve precise control of the lead liquid level.

7. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 1, characterized in that, The current stabilization unit establishes a correlation model between the main unit current fluctuation and the amount of metal impurities deposited on the screw surface. Combined with the lead ingot transfer status data from multi-dimensional limit feedback, a set current fluctuation value is used as a trigger threshold. When the current fluctuation exceeds the threshold, if the multi-dimensional limit feedback transfer is stable, the current is stabilized primarily through the synergistic effect of additive injection and screw speed adjustment. If there is a deviation in the multi-dimensional limit feedback transfer, the feeding posture compensation parameters are finely adjusted while the current is adjusted. Through the synergistic effect of the lubricating isolation film formed by the additive, speed optimization, and feeding posture correction, the superimposed influence of screw rotation resistance and feeding deviation is reduced, thereby stabilizing the main unit current.

8. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 7, characterized in that, The current stabilization unit establishes a correlation model between main unit current fluctuations and the amount of metal impurity deposition on the screw surface, by collecting multiple sets of main unit current reference values ​​under standard production conditions. Real-time current fluctuation Screw cumulative running time Lead ingot purity parameters and actual amount of impurities deposited on the screw surface Based on the corresponding data, construct a sample dataset; Based on dataset analysis of the correlation between impurity deposition and current fluctuations, a lead ingot purity correction factor is introduced. Screw running time decay index and friction coefficient correlation coefficient Establish the formula for the correlation model: ,in This is the current fluctuation-impurity deposition ratio coefficient. This represents the change in screw friction coefficient caused by impurity deposition, and data is collected in real time. , , and The data can be substituted into the model to calculate the estimated amount of impurity deposition on the screw surface. When the set threshold is exceeded, the required amount of additive injection and the adjustment range of screw speed are calculated based on the model to achieve precise suppression of current fluctuations. At the same time, the model coefficients are continuously corrected to optimize adaptability by combining the actual amount of impurity deposition detected by periodic shutdown.

9. The automatic lead ingot feeding precision control system based on visual positioning and multi-dimensional limiting as described in claim 1, characterized in that, The thickness adjustment unit collects data on the stability of the lead ingot transport posture and position deviation from the multi-dimensional limit module, real-time current of the main unit, temperature field distribution data inside the lead extrusion furnace, online detection data of lead sleeve thickness, and production line speed signals. This data is incorporated into a multi-objective coupled control logic. Based on a preset precision control coefficient, the mapping relationship between current stability, transport status, and lead sleeve wall thickness uniformity is quantified. The screw speed reference value is dynamically matched to the production line speed. When current fluctuations exceed a set threshold, the linkage current stabilization unit adjusts the amount of zinc stearate injected to reduce screw friction resistance. Simultaneously, the screw speed compensation is finely adjusted based on the transport status deviation. If the thickness detection data deviates from the nominal value, the coordinated parameters of the speed and additive injection are further corrected based on the deviation amplitude, forming a closed-loop control.

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