An adaptive blank size cold header feed device

Abstract

The application relates to the field of mechanical equipment and intelligent control technology, in particular to a cold header feeding device self-adapting to blank specifications, which comprises the following modules: a blank feeding module realizes automatic and orderly blank feeding, supports mixed blank feeding and queue management of multiple specifications; an intelligent sensing module realizes real-time collection of three-dimensional geometric features and surface texture information of the blank through laser profile scanning and visual image recognition double modes, and obtains detection results in combination with a multispectral analysis technology; a control module realizes matching analysis according to the detection results and a preset process parameter library, and realizes real-time generation of a dynamic control program through an embedded intelligent algorithm; a self-adaptive adjustment module dynamically adjusts the feeding channel width, the clamping mechanism posture and clamping force, the feeding step distance and speed according to the dynamic control program; and a safety protection module realizes real-time monitoring of the equipment operation state, fault early warning and autonomous shutdown protection. Therefore, the problems of low change type efficiency and poor precision are solved.

Description

Technical Field

[0001] This application relates to the fields of mechanical equipment and intelligent control technology, and in particular to a cold heading machine feeding device that adapts to billet specifications. Background Technology

[0002] As a core processing equipment for hardware products such as fasteners and automotive parts, the adaptability of the feeding device in cold heading machines directly determines processing efficiency, product accuracy, and production costs. Traditional cold heading machine feeding devices are mostly designed with fixed specifications. When processing blanks of different diameters and lengths, manual disassembly and adjustment of the channel width, fixture size, and feeding step distance are required. This is not only time-consuming and labor-intensive (each changeover takes 30-60 minutes), but also has limited accuracy, easily leading to problems such as blank clamping damage and feeding deviation, thus affecting product yield. At the same time, the demand for flexible production with small batches and multiple varieties is increasing, highlighting the limitations of traditional feeding devices and necessitating an intelligent feeding solution that can automatically adapt to multiple blank specifications. Summary of the Invention

[0003] This application provides a cold heading machine feeding device that adapts to billet specifications to solve problems such as low changeover efficiency and poor accuracy.

[0004] The first aspect of this application provides an adaptive billet feeding device for a cold heading machine, comprising: a billet feeding module, an intelligent sensing module, a control module, an adaptive adjustment module, and a safety protection module. The billet feeding module is used to achieve automatic and orderly feeding of billets, supporting mixed feeding and queue management of billets of multiple specifications. The intelligent sensing module is connected to the billet feeding module and collects the three-dimensional geometric features and surface texture information of the billet in real time through a dual-mode laser contour scanning and visual image recognition. Combined with multispectral analysis technology, it accurately detects the billet diameter, roundness deviation, length, and material characteristics to obtain detection results. The control module is connected to the intelligent sensing module and is used to perform matching analysis based on the detection results and a preset process parameter library, generating a dynamic control program in real time through an embedded intelligent algorithm. The adaptive adjustment module is connected to the control module and employs a variable-diameter flexible wheel set and an electric servo gripper collaborative mechanism to dynamically adjust the feeding channel width, clamping mechanism posture and clamping force, feeding step distance, and speed according to the dynamic control program. The safety protection module is used to monitor the equipment operating status in real time, realizing fault warning and autonomous shutdown protection.

[0005] Optionally, the billet feeding module includes: a sorting unit and a conveying unit, wherein the sorting unit is used to put mixed-specification billets into the feeding port in batches, remove billets exceeding the size limit by a vibrating screen, and the remaining billets enter the intelligent sorting area by a conveyor belt and are allocated to the corresponding storage partitions according to a preset specification range; the conveying unit is used to receive billet demand signals from the control module, extract billets from the corresponding storage partitions according to the demand specifications, calibrate the extracted billets to a uniform axial posture, and continuously and smoothly convey them to the intelligent sensing module in a single-column queue.

[0006] Optionally, the intelligent sensing module includes: a laser contour scanning unit, a visual image recognition unit, a multispectral analysis unit, and a data fusion processing unit. The laser contour scanning unit uses a high-precision laser displacement sensor to collect radial cross-sectional contour data of the billet. A rotation drive component drives the sensor to rotate 360° radially along the billet, and combined with edge extraction and fitting algorithms, calculates the actual diameter and roundness deviation of the billet. The visual image recognition unit uses an industrial camera and telecentric lens to collect image information perpendicular to the billet conveying direction. Through image segmentation, grayscale processing, and endpoint positioning algorithms, it accurately identifies the positions of the two end faces of the billet and calculates the actual length of the billet. The multispectral analysis unit uses a multi-band spectral sensor to emit visible and near-infrared light in the 400-1000nm range to irradiate the billet surface, collects the reflected spectral signal, and compares it with a preset spectral database of different materials such as steel, aluminum, and copper using a spectral feature matching algorithm to identify the billet material characteristics. The data fusion processing unit integrates the data acquired by the above three units to obtain a comprehensive detection result including billet diameter, roundness deviation, length, and material.

[0007] Optionally, the control module includes: a matching analysis unit and a modular program generation unit. The matching analysis unit receives the detection results and performs deep matching and multi-objective optimization analysis with a preset process knowledge base and material database to determine the most suitable combination of process parameters for the current billet. The modular program generation unit decomposes the functions of adjusting the width of the feeding channel, controlling the posture and clamping force of the clamping mechanism, and adjusting the feeding step distance and speed into independent program modules. Based on the combination of process parameters, it quickly calls the corresponding modules through embedded algorithms and completes parameter assignment and logical linkage to generate a dynamic control program.

[0008] Optionally, the adaptive adjustment module includes: a variable-diameter flexible wheel set channel adjustment unit, an electric servo flexible clamping adjustment unit, and a feeding step distance and speed adjustment unit. The variable-diameter flexible wheel set channel adjustment unit adaptively adjusts the opening and closing dimensions of the feeding channel according to the channel width parameters in the dynamic control program to achieve stable conveying of billets of different diameters. The electric servo flexible clamping adjustment unit adjusts the posture and clamping force of the clamping mechanism according to the clamping parameters in the dynamic control program to achieve clamping of billets of different materials and specifications. The feeding step distance and speed adjustment unit adjusts the feeding step distance and speed according to the feeding step distance and speed in the dynamic control program, achieving precise control of the feeding step distance and smooth switching of the speed through servo drive and displacement closed-loop feedback.

[0009] Optionally, the safety protection module includes: a status monitoring unit and a fault early warning unit. The status monitoring unit is used to collect status data in real time from key parts and operating parameters of the feeding device through multi-dimensional sensors. The fault early warning unit is used to receive the status data, compare and analyze it with a preset safety threshold, and implement differentiated responses using a three-level graded early warning mechanism. For a minor abnormality (Level 1), an audible and visual warning is triggered, and the control module is linked to fine-tune the equipment parameters to achieve self-correction. For a moderate abnormality (Level 2), a high-frequency audible and visual alarm is switched on, and the feeding action is paused, while simultaneously displaying the fault location, cause, and troubleshooting suggestions. For a severe abnormality (Level 3), a shutdown signal is immediately triggered.

[0010] The second aspect of this application provides a feeding method for a cold heading machine that adapts to billet specifications, comprising the following steps: automatic and orderly feeding of billets is achieved through a billet feeding module, supporting mixed feeding and queue management of billets of multiple specifications; real-time acquisition of the three-dimensional geometric features and surface texture information of the billet through dual-mode laser contour scanning and visual image recognition, combined with multispectral analysis technology to accurately detect the billet diameter, roundness deviation, length, and material characteristics, obtaining detection results; matching analysis is performed based on the detection results and a preset process parameter library, and a dynamic control program is generated in real-time through an embedded intelligent algorithm; an adaptive adjustment mechanism using a variable-diameter flexible wheel set and an electric servo gripper is adopted to dynamically adjust the feeding channel width, clamping mechanism posture and clamping force, feeding step distance and speed according to the dynamic control program; and real-time monitoring of equipment operating status is implemented to achieve fault warning and autonomous shutdown protection.

[0011] A third aspect of this application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform a cold heading machine feeding method for adaptive billet specifications as described in the above embodiments.

[0012] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement a cold heading machine feeding method for adaptive billet specifications as described in the above embodiments.

[0013] A fifth aspect of this application provides a computer program product storing a computer program that, when executed by a processor, implements a cold heading machine feeding method for adaptive billet specifications as described in the above embodiments.

[0014] The beneficial effects of using the present invention are as follows: This application embodiment achieves mixed feeding and queue management of billets of various specifications through a billet feeding module; the intelligent sensing module collects data through dual modes of laser contour scanning and visual image recognition, combined with multispectral technology for precise multi-directional detection, enabling rapid acquisition of all-dimensional characteristic parameters of the billet; the control module dynamically matches process parameters and generates customized control programs, while the adaptive adjustment module, through a variable-diameter flexible wheel set and an electric servo gripper collaborative mechanism, achieves adaptive and precise control of the feeding channel, clamping parameters, and feeding cycle. Combined with the safety protection module's full-condition monitoring and fault warning shutdown function, this not only significantly shortens billet changeover time, improves feeding accuracy and stability, reduces billet surface damage rate and manual operation costs, but also ensures continuous and safe operation of the equipment, adapting to the needs of small-batch, multi-variety flexible production. Thus, it solves problems such as low changeover efficiency and poor accuracy.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a schematic diagram of a cold heading machine feeding device with adaptive billet specifications provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a cold heading machine feeding method with adaptive billet specifications according to an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0017] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0018] The following description, with reference to the accompanying drawings, describes an adaptive billet specification feeding device for a cold heading machine according to an embodiment of this application. Addressing the issues of low changeover efficiency and poor accuracy mentioned in the background art, this application provides an adaptive billet specification feeding device for a cold heading machine. In this system, a billet feeding module enables mixed feeding and queue management of billets of multiple specifications; an intelligent sensing module acquires data through dual-mode laser contour scanning and visual image recognition, combined with multispectral technology for precise multi-directional detection, quickly obtaining full-dimensional characteristic parameters of the billet; a control module dynamically matches process parameters and generates a customized control program; and an adaptive adjustment module, through a variable-diameter flexible wheel assembly and an electric servo gripper mechanism, achieves adaptive and precise control of the feeding channel, clamping parameters, and feeding cycle. Combined with a safety protection module providing full-condition monitoring and fault warning shutdown functions, this system not only significantly shortens billet changeover time, improves feeding accuracy and stability, reduces billet surface damage rate and manual operation costs, but also ensures continuous and safe operation of the equipment, adapting to the needs of small-batch, multi-variety flexible production. Thus, it solves the problems of low changeover efficiency and poor accuracy.

[0019] Specifically, Figure 1 This is a schematic diagram of a cold heading machine feeding device with adaptive billet specifications provided in an embodiment of this application.

[0020] like Figure 1 As shown, the cold heading machine feeding device 10 with adaptive billet specifications includes a billet feeding module 100, an intelligent sensing module 200, a control module 300, an adaptive adjustment module 400, and a safety protection module 500.

[0021] The billet feeding module 100 is used to realize the automatic and orderly feeding of billets, supporting mixed feeding and queue management of billets of multiple specifications; the intelligent sensing module 200 is connected to the billet feeding module 100, and collects the three-dimensional geometric features and surface texture information of the billet in real time through dual modes of laser contour scanning and visual image recognition, and accurately detects the billet diameter, roundness deviation, length and material characteristics by combining multispectral analysis technology to obtain the detection results; the control module 300 is connected to the intelligent sensing module 200, and is used to perform matching analysis with the preset process parameter library based on the detection results, and generate dynamic control programs in real time through embedded intelligent algorithms; the adaptive adjustment module 400 is connected to the control module 300, and adopts a variable diameter flexible wheel group and electric servo gripper collaborative mechanism to dynamically adjust the feeding channel width, clamping mechanism posture and clamping force, feeding step distance and speed according to the dynamic control program; the safety protection module 500 is used to monitor the equipment operating status in real time, and realize fault warning and autonomous shutdown protection.

[0022] It is understood that the embodiments of this application realize mixed feeding and queue management of billets of various specifications through the billet feeding module; the intelligent sensing module collects data through dual modes of laser contour scanning and visual image recognition, and combines multispectral technology for precise multi-directional detection, which can quickly obtain the full-dimensional characteristic parameters of the billet; the control module dynamically matches process parameters and generates customized control programs, and the adaptive adjustment module realizes adaptive and precise control of the feeding channel, clamping parameters and feeding cycle through the coordinated mechanism of variable diameter flexible wheel group and electric servo gripper. Combined with the safety protection module's full-condition monitoring and fault early warning shutdown function, it not only greatly shortens the billet changeover time, improves feeding accuracy and stability, reduces the billet surface damage rate and manual operation costs, but also ensures the continuous and safe operation of the equipment, adapting to the flexible production needs of small batch and multi-variety production.

[0023] In this embodiment of the application, the billet feeding module includes: a sorting unit and a conveying unit.

[0024] The sorting unit is used to put batches of mixed-specification billets into the feeding port, remove billets that exceed the size limit by a vibrating screen, and the remaining billets enter the intelligent sorting area by a conveyor belt and are allocated to the corresponding storage areas according to the preset specification range. The conveying unit is used to receive the billet demand signal from the control module, extract the billets from the corresponding storage areas according to the demand specifications, calibrate the extracted billets to a uniform axial posture, and continuously and smoothly convey them to the intelligent sensing module in a single queue.

[0025] Specifically, the vibrating screen of the sorting unit adopts a double-layer adjustable structure. The aperture of the upper screen can be adjusted according to the maximum billet diameter threshold (20mm), while the aperture of the lower screen is adapted to the minimum billet diameter (3mm). Through 100-200Hz adjustable frequency vibration, it quickly removes unqualified billets with diameters exceeding the φ3-20mm range, with a screening efficiency ≥99.5%. The intelligent sorting area is equipped with three sets of infrared size detection sensors, corresponding to three specification ranges: small (φ3-8mm), medium (φ8-15mm), and large (φ15-20mm). As the billets pass through, they can be quickly classified and simultaneously sent to the corresponding storage compartment. The storage compartment has a built-in material level sensor that provides real-time feedback on the material quantity and links with the feeding port for replenishment. The conveying unit adopts a rodless cylinder pushing structure with a posture calibration channel. Two sets of differential flexible friction wheels are symmetrically arranged in the calibration channel to drive the billet to rotate around its own axis. At the same time, the posture of the billet end face is detected by visual positioning sensors on both sides until the axial deviation from the conveying direction is ≤0.5°. After the posture calibration is completed, the pushing component pushes the billet to the queue track at a uniform interval of 5-8mm to ensure that the billet fed into the intelligent sensing module has a uniform posture and is arranged in an orderly manner.

[0026] For example, when the processing requirement is a steel billet with a diameter of φ10mm (medium specification) and a length of 50mm, the sorting unit first uses a vibrating screen to remove billets with a diameter exceeding 3-20mm. The remaining billets are identified as medium specification by an infrared sensor and then sent to the corresponding storage area. The conveying unit receives the demand signal from the control module, extracts the billet from the storage area, calibrates its attitude by a differential friction wheel, and then continuously pushes it to the intelligent sensing module in a single-column queue with a 5mm interval to ensure the continuity and accuracy of subsequent inspection work.

[0027] It is understood that the embodiments of this application realize the automatic screening, classification and standardized conveying of mixed specification billets through the coordinated cooperation of the sorting unit and the conveying unit. There is no need for manual sorting and posture adjustment, which not only avoids human operation errors, but also greatly improves the feeding efficiency. It provides standardized preconditions for subsequent accurate detection and adaptive adjustment, and adapts to the flexible needs of multi-specification mixed production.

[0028] In this embodiment, the intelligent sensing module includes: a laser contour scanning unit, a visual image recognition unit, a multispectral analysis unit, and a data fusion processing unit.

[0029] The unit comprises three main components: a laser contour scanning unit and a data fusion unit. The laser contour scanning unit uses a high-precision laser displacement sensor to collect radial cross-sectional contour data of the billet. The sensor is rotated 360° radially along the billet by a rotation drive component. Combined with edge extraction and fitting algorithms, the actual diameter and roundness deviation of the billet are calculated. The visual image recognition unit uses an industrial camera and a telecentric lens to collect image information perpendicular to the billet conveying direction. Through image segmentation, grayscale processing, and endpoint positioning algorithms, the unit accurately identifies the positions of the two end faces of the billet and calculates the actual length of the billet. The multispectral analysis unit uses a multi-band spectral sensor to emit visible and near-infrared light in the 400-1000nm range to irradiate the surface of the billet and collects the reflected spectral signal. Through a spectral feature matching algorithm, the signal is compared with a preset spectral database of different materials such as steel, aluminum, and copper to identify the material characteristics of the billet. The data fusion processing unit integrates the data obtained by the above three units to obtain a comprehensive detection result including the billet diameter, roundness deviation, length, and material.

[0030] Specifically, the laser contour scanning unit uses a laser displacement sensor with a measurement accuracy of ±0.01mm and a scanning frequency of 500Hz. The rotation drive assembly moves the sensor to scan and collect over 1000 contour data points per revolution. The least squares method is used to fit the circular cross-section of the billet, calculating the actual diameter and roundness deviation. The visual image recognition unit acquires images using a 20-megapixel industrial CCD camera and a telecentric lens. The images are processed using a threshold segmentation algorithm to remove background interference, and edge detection is used to locate the two ends of the billet, calculating the actual length of the billet. The spectral sensor can collect reflection signals from over 200 bands within the 400-1000nm range, comparing the spectral curves with a preset database to identify the billet's material characteristics. The data fusion processing unit integrates the data acquired by the above three units to obtain a comprehensive detection result including the billet's diameter, roundness deviation, length, and material.

[0031] It should be noted that the process of fitting the circular cross-section of the billet using the least squares method is as follows: First, a two-dimensional coordinate system is established, with the rotation center of the laser sensor as the origin. Each collected data point is converted into (x, y) coordinate values ​​in the coordinate system, and outliers caused by vibration and ambient light interference are simultaneously removed (the removal threshold is set to ±0.03 mm to avoid outliers affecting the fitting accuracy). Then, a circle fitting objective function is constructed, assuming the equation of the ideal circle is (xa)² + (yb)² = R² (where (a, b) are the coordinates of the center of the circle, and R is the radius of the circle). The least squares method solves for the optimal center coordinates and radius by minimizing the sum of the squares of the distances from all data points to the ideal circle. After fitting, twice the calculated radius R is taken as the actual diameter of the billet; the roundness deviation is obtained by calculating the difference between the maximum and minimum distances from all data points to the ideal circle.

[0032] The image is segmented using a thresholding algorithm to remove background interference. Specifically, the acquired 20-megapixel color image is first converted to grayscale, transforming the RGB three-channel image into a single-channel grayscale image. Grayscale histogram analysis is used to determine the grayscale value distribution ranges of the billet and the background. Due to the reflective properties of the metal, the grayscale values ​​in the billet area are concentrated in the 180-255 range, while the grayscale values ​​in the background area (track, environment) are concentrated in the 0-80 range. Subsequently, an adaptive thresholding algorithm is used, automatically setting a dynamic threshold based on the bimodal peaks and valleys of the grayscale histogram. Areas with grayscale values ​​above the threshold are identified as the billet foreground, while areas below the threshold are identified as the background and set to black. Simultaneously, for grayscale gradient areas at the image edges, morphological opening operations (erosion followed by dilation) are used to eliminate isolated noise and smooth background edges, ensuring the billet area has a complete outline and clear edges.

[0033] After background removal, edge detection algorithms are used to accurately locate the two ends of the billet, achieving high-precision measurement of the billet length. First, the Canny edge detection algorithm is used to extract edges from the preprocessed billet image: The first step involves Gaussian filtering (with a Gaussian kernel size of 5×5) to reduce image noise and prevent noise from being mistaken for edges; the second step calculates the gradient magnitude and direction of each pixel to capture areas of drastic gray-level changes at the billet edge; the third step uses a dual-threshold method (high threshold 200, low threshold 100) to filter valid edges, eliminate false edges, and retain the complete outline of the billet. Since the billet is cylindrical, its outline in the axial image consists of two parallel longitudinal edges, with the two ends being the vertical intersection points of these edges. The equations of the two longitudinal edges are fitted using Hough linear transform, and then, combined with the image coordinate system, the coordinate difference between the upper and lower endpoints of the two lines is calculated. This difference represents the pixel length of the billet in the image. Finally, the pixel length is converted into the actual physical length based on camera calibration parameters.

[0034] The reflectance spectrum signal acquired by the spectral sensor is denoised by using a smoothing filtering algorithm to eliminate interference from ambient light and sensor noise, resulting in a smooth reflectance spectrum curve of the billet. Then, the reflectance values ​​of the curve in characteristic bands are extracted. These characteristic bands are the characteristic absorption / reflection bands of electronic transitions in different metal materials. Specifically, steel corresponds to the 580nm and 850nm bands, aluminum to the 550nm and 780nm bands, and copper to the 620nm and 900nm bands. Spectral curve comparison involves comparing the extracted characteristic band reflectance with the spectral curves of standard materials in a preset database. A cosine similarity algorithm is used to calculate the similarity between the curve to be detected and the standard curve. When the similarity is ≥99.5%, the material is identified as the corresponding material.

[0035] It is understood that the embodiments of this application, through the deep integration of laser, vision, and multispectral technologies, achieve simultaneous high-precision detection of billet geometry, morphological features, and material composition, significantly improving the measurement comprehensiveness and reliability of traditional single-sensor solutions. The overall process not only eliminates the need for manual intervention, greatly reducing human error and detection time, but also provides multi-dimensional, high-precision billet data support for the control module, ensuring the accuracy and adaptability of subsequent adaptive adjustments.

[0036] In this embodiment, the control module includes: a matching analysis unit and a modular program generation unit.

[0037] The matching analysis unit receives the detection results and performs deep matching and multi-objective optimization analysis with the preset process knowledge base and material database to determine the most suitable combination of process parameters for the current billet. The modular program generation unit decomposes the functions of feeding channel width adjustment, clamping mechanism posture and clamping force control, and feeding step distance and speed adjustment into independent program modules. Based on the combination of process parameters, the corresponding modules are quickly called through embedded algorithms to complete parameter assignment and logical linkage, thereby generating a dynamic control program.

[0038] Specifically, the pre-set process knowledge base stores adaptation parameters for over 100 commonly used billet specifications, covering core parameters such as feeding channel width, clamping force, feeding step distance, and speed. The material database contains the physical properties (hardness, ductility) of materials such as steel, aluminum, and copper, along with corresponding process compensation parameters. A multi-objective optimization algorithm is employed, aiming for "highest feeding accuracy, minimum billet damage, and optimal cycle time." Combined with the real-time processing cycle time of the cold heading machine (e.g., 50 pieces / minute), the Pareto optimal parameter set is solved in real-time from the pre-set process knowledge base to determine the most suitable combination of process parameters for the current billet. The modular program generation unit decomposes the functions of feeding channel width adjustment, clamping mechanism posture and clamping force control, and feeding step distance and speed adjustment into independent program modules. Through an embedded PLC algorithm, the corresponding modules are quickly called, parameter assignments are completed, and logical linkages are established to generate a dynamic control program.

[0039] It should be noted that the specific execution process of the multi-objective optimization algorithm for real-time solution of the Pareto optimal parameter set is as follows: First, the quantitative indicators and constraints of the three major optimization objectives are clarified. The feeding accuracy objective is quantified as feeding position error ≤ ±0.02mm and channel-to-bill gap ≤ 0.03mm, with constraints of channel width adjustment range 3-22mm and step pitch adjustment accuracy ±0.02mm; the billet damage objective is quantified as clamping force fluctuation ≤ ±0.05MPa and no plastic deformation, with constraints of clamping force not exceeding 30% of the yield strength of the corresponding material (e.g., the upper limit of clamping force for aluminum billets is 0.25MPa); the cycle time adaptation objective is quantified as the difference between the feeding cycle and the cold heading machine processing cycle ≤ 0.02s, with constraints of feeding speed range 50-300mm / s and synchronization with the cold heading machine station switching action.

[0040] Within the parameter range of the pre-set process knowledge base, multiple initial parameter combinations are generated (the initial sample size is set to 50 groups). Each group of parameters covers four core parameters: channel width, clamping force, feeding step distance, and speed. Then, all initial parameter combinations are graded using non-dominated sorting to select non-dominated solutions (i.e., solutions where no other parameter combination is superior to all objectives), forming the initial Pareto front. For the solutions in the initial Pareto front, combined with the real-time processing cycle of the cold heading machine (50 pieces / minute corresponding to a single-piece processing cycle of 1.2s), the objective function value of each solution is calculated: the feeding accuracy score is determined by both position error and channel clearance; the smaller the error, the higher the score; the billet damage score combines the clamping force and material compensation parameters to avoid exceeding the damage threshold; the cycle time adaptation score is calculated based on the matching degree between the feeding cycle and the processing cycle; the better the synchronization, the higher the score. By employing an elite retention strategy and crossover mutation operations, the initial Pareto front is iteratively optimized (the number of iterations is set to 30 to ensure convergence), continuously eliminating inferior solutions and generating better solutions, eventually converging to obtain a stable Pareto optimal parameter set. The final combination of process parameters is then determined from the Pareto optimal parameter set.

[0041] After receiving the optimal combination of process parameters output by the matching analysis unit, the embedded PLC algorithm quickly matches the corresponding program module through a preset module mapping table. Specifically, based on core parameters such as channel width, clamping force, and feeding step distance in the parameter combination, it automatically calls the three independent modules mentioned above, with a call response time ≤0.01s. Subsequently, according to the parameter protocols of each module, the optimal parameters are precisely assigned to the corresponding modules: the target width and adjustment rate are assigned to the channel width adjustment module, specifying the threshold value for the adjusted position; the target clamping force, centering error threshold, and elastic buffer compression amount are assigned to the clamping mechanism module, and the pressure adjustment coefficient corresponding to the material is simultaneously issued; the target step distance, feeding speed, and acceleration / deceleration time constant are assigned to the step distance / speed adjustment module, specifying the S-shaped acceleration / deceleration curve parameters. During the assignment process, the algorithm automatically verifies whether the parameters are within the preset threshold range of the module (e.g., the clamping force does not exceed the upper limit corresponding to the material's yield strength). If any parameter abnormalities are found, they are immediately fed back to the control module, triggering parameter re-correction to ensure the accuracy of the assignment.

[0042] The embedded PLC algorithm establishes a linkage relationship between three modules through internal logic instructions and signal interaction mechanisms, realizing orderly coordination of "channel adjustment → clamping calibration → feeding execution" to ensure precise matching of action timing with the cold heading machine's processing cycle. The specific linkage logic is as follows: After the feeding channel width adjustment module completes its adjustment, it sends a "channel ready" signal to the PLC via a standardized interface. The PLC then sends a start command to the clamping mechanism module. After starting, the clamping mechanism module first completes the three-jaw centering calibration, and then adjusts the clamping force in a closed loop according to the assigned value. When the pressure sensor feedback indicates that the clamping force is stable at the target value (fluctuation ≤ ±0.05MPa) and the centering error meets the standard, it sends a "clamping ready" signal. After receiving this signal, the PLC, combined with the station ready signal fed back by the cold heading machine host, sends a feeding command to the feeding step distance and speed adjustment module. The module executes the feeding action according to the preset step distance, speed, and acceleration / deceleration curve. After feeding to the desired position, it sends a "feeding complete" signal, forming a complete feeding control cycle. Meanwhile, the algorithm supports dynamic adjustment of timing logic, which can fine-tune the action interval of each module according to the processing cycle of the cold heading machine, ensuring that the feeding cycle and the processing cycle are precisely synchronized without any lag or lead.

[0043] It is understood that the embodiments of this application achieve precise adaptation of process parameters and efficient generation of control programs through multi-objective optimization of the matching analysis unit and rapid programming of the modular program generation unit. The modular architecture not only ensures the flexibility of program generation, but also facilitates subsequent functional expansion and maintenance. At the same time, the coordinated optimization with the cold heading machine processing cycle ensures the precise synchronization of feeding and processing actions, and improves the overall production coordination.

[0044] In this embodiment, the adaptive adjustment module includes: a variable diameter flexible wheel set channel adjustment unit, an electric servo flexible clamping adjustment unit, and a feeding step distance and speed adjustment unit.

[0045] The variable diameter flexible wheel set channel adjustment unit is used to adaptively adjust the opening and closing size of the feeding channel according to the channel width parameter in the dynamic control program, so as to realize the stable conveying of billets of different diameters; the electric servo flexible clamping adjustment unit is used to adjust the posture and clamping force of the clamping mechanism according to the clamping parameters in the dynamic control program, so as to realize the clamping of billets of different materials and specifications; the feeding step distance and speed adjustment unit is used to adjust the feeding step distance and speed respectively according to the feeding step distance and speed in the dynamic control program, and realize the precise control of the feeding step distance and the smooth switching of speed through servo drive and displacement closed-loop feedback.

[0046] Specifically, the variable-diameter flexible wheel set channel adjustment unit adopts a symmetrically arranged variable-diameter flexible wheel set as its core structure. Each wheel set is driven by a micro servo motor to achieve synchronous opening and closing of a ball screw, with an adjustment range covering 3-22mm. It can accurately match blanks with a diameter of φ3-20mm, and the adjustment accuracy reaches ±0.01mm. The surface of the flexible wheel set is coated with a high-polymer wear-resistant elastic material, which has both cushioning and wear resistance, reducing contact wear between the blank and the wheel set. At the same time, the wheel set has a built-in pressure sensor component that collects the contact pressure data between the blank and the wheel set in real time and feeds it back to the control module. With the error compensation algorithm of the matching analysis unit, the channel width is dynamically fine-tuned to maintain the contact pressure within a reasonable range of 0.05-0.1MPa, which avoids blank conveying deviation and blank deformation caused by excessive compression, thus ensuring conveying stability.

[0047] The electro-servo flexible clamping adjustment unit adopts an integrated structure of electro-servo grippers and elastic buffer components. The grippers feature a three-jaw linkage design, achieving synchronous extension and retraction via a servo motor-driven bevel gear transmission. The clamping range is dynamically adapted to the channel width, ensuring precise alignment of the billet center with the cold heading machine's machining station (alignment error ≤ 0.02mm). Each gripper incorporates a pressure sensor and an adjustable elastic buffer. Based on the clamping parameters in the dynamic control program, it automatically adjusts the clamping force and buffer compression. For hard materials such as steel, the clamping force is maintained at 0.3-0.5MPa, with a buffer compression of 1-2mm; for soft materials such as aluminum and copper, the clamping force is adjusted to 0.1-0.2MPa, with a buffer compression of 2-3mm. A PID closed-loop algorithm corrects the clamping force in real time to prevent plastic deformation or surface damage to the billet. Simultaneously, the grippers can fine-tune the clamping point according to the billet length: for billets ≤ 50mm in length, the center is clamped; for billets > 50mm in length, the distance from each end is clamped at 1 / 3 of the length, improving clamping stability.

[0048] The feeding step distance and speed adjustment unit adopts a drive combination of servo motor + planetary reducer + ball screw. The feeding step distance is infinitely adjustable by controlling the motor rotation angle, with an adjustment range of 20-150mm. The speed adjustment achieves smooth switching from 50-300mm / s through frequency conversion control. The start-stop phase adopts an S-shaped acceleration and deceleration curve to weaken inertial impact and avoid billet posture deviation. The unit has a built-in displacement sensor to collect feeding stroke data in real time and feed it back to the control module 300 to form a closed-loop control, ensuring that the feeding step distance and speed are accurately matched with the control program requirements.

[0049] For example, after receiving the control program of "channel width 10.01mm, clamping force 0.38MPa, feeding step distance 49.98mm, speed 150mm / s", the variable diameter flexible wheel set channel adjustment unit 410 drives the wheel set to open and close synchronously to 10.01mm. The pressure sensor monitors the contact pressure in real time and feeds it back to the control module for fine adjustment to 0.08MPa. The electric servo flexible clamping adjustment unit 420 drives the three jaws to open in linkage, adjusts the clamping force to 0.38MPa, and buffers the compression amount to 1.5mm, clamping the middle of the billet and aligning it with the processing station. The feeding step distance and speed adjustment unit 430 pushes the billet with an S-shaped acceleration and deceleration curve at a step distance of 49.98mm and a speed of 150mm / s. The displacement sensor feeds back the stroke data, and closed-loop correction ensures the accuracy of the feeding position.

[0050] It is understood that the embodiments of this application achieve full-dimensional adaptive control of the feeding channel, clamping parameters, and feeding cycle through the coordinated action of the three major adjustment units. The combination design of variable diameter flexible wheel set and electric servo flexible clamping takes into account both conveying stability and billet protection. Servo drive and closed-loop feedback mechanism ensure adjustment accuracy, effectively adapt to the feeding needs of billets of multiple specifications and materials, and greatly improve the reliability and accuracy of the feeding process.

[0051] In this embodiment, the security protection module includes: a status monitoring unit and a fault early warning unit.

[0052] The status monitoring unit is used to collect real-time data on key parts and operating parameters of the feeding device through multi-dimensional sensors to obtain status data. The fault early warning unit is used to receive status data, compare and analyze it with preset safety thresholds, and implement differentiated responses using a three-level graded early warning mechanism. When a minor abnormality occurs at level one, an audible and visual warning is triggered and the control module is linked to fine-tune equipment parameters to achieve self-correction. When a moderate abnormality occurs at level two, a high-frequency audible and visual alarm is switched on and the feeding action is suspended, while the fault location, cause, and troubleshooting suggestions are displayed simultaneously. When a severe abnormality occurs at level three, a shutdown signal is immediately triggered.

[0053] Specifically, the status monitoring unit is equipped with vibration sensors, temperature sensors, pressure sensors, leakage current detection components, and infrared jamming sensors. Vibration sensors are installed on moving parts such as servo motors and ball screws to monitor vibration amplitude (safety threshold ≤ 0.8g); temperature sensors collect the temperature of motors and drive components (safety threshold ≤ 85℃); pressure sensors monitor abnormal fluctuations in clamping force and channel contact pressure (fluctuation threshold ± 0.05MPa); leakage current detection components monitor the stability of circuit voltage and current in real time; and infrared jamming sensors detect the blockage of billets in the feeding channel and queue track. All sensor data are collected 10 times per second and transmitted synchronously to the fault early warning unit. The fault warning unit has a built-in safety threshold database and adopts a three-level warning mechanism: Level 1 warning (vibration 0.6-0.8g, temperature 75-85℃), triggers a flashing green light and a low-frequency buzzer, and links the control module to reduce the feeding speed and fine-tune the clamping force; Level 2 warning (vibration > 0.8g, temperature > 85℃, clamping force fluctuation > ±0.05MPa, slight jamming), switches to flashing red light and a high-frequency buzzer, suspends the feeding action, and displays the fault location (e.g., "servo motor temperature too high"), cause, and troubleshooting suggestions (e.g., "check if the cooling fan is working properly") on the human-machine interface; Level 3 warning (severe vibration > 1.2g, electrical leakage, sensor failure, severe jamming), immediately triggers a stop signal, cuts off the power supply between the feeding device and the cold heading machine main unit, and locks the moving parts.

[0054] For example, when the temperature of the electric servo motor rises to 86℃, the status monitoring unit collects temperature data and transmits it to the fault early warning unit. After comparing it with the safety threshold (≤85℃), a level two early warning is triggered, a high-frequency audible and visual alarm is activated, the feeding action is paused, the human-machine interface displays "servo motor temperature too high" and prompts "check the cooling fan and clean the heat dissipation channel"; if the operator does not handle it in time, the temperature rises to 90℃, and it is upgraded to a level three early warning, immediately triggering a stop signal to cut off the power supply and prevent the motor from burning out.

[0055] It is understood that the embodiments of this application, through the full-dimensional collection of the status monitoring unit and the hierarchical response of the fault early warning unit, realize the early prediction and differentiated protection of equipment operation risks. This not only avoids minor abnormalities from escalating into serious faults, but also enables rapid shutdown in the event of major risks, thereby maximizing the protection of operator safety, equipment operation safety and production continuity, and reducing losses caused by faults.

[0056] The following is a detailed description of a cold heading machine feeding device that adapts to different billet specifications, using specific embodiments: For automotive parts manufacturing, it is necessary to process φ5mm (small size) aluminum billets (30mm in length), φ12mm (medium size) steel billets (80mm in length), and φ18mm (large size) copper billets (the three sizes are mixed and fed). The cold heading machine has a processing cycle of 60 pieces / minute.

[0057] First, a batch of mixed billets of three specifications are placed into the feeding port of the billet feeding module. The sorting unit uses a double-layer vibrating screen to remove unqualified billets with a diameter exceeding 3-20mm. The remaining billets are sorted by infrared sensors and then sent to the small, medium, and large specification storage areas respectively. According to the cold heading machine processing instructions, the control module sends the demand signals of the three specifications of billets to the conveying unit in sequence. The conveying unit extracts the billets from the corresponding storage areas, calibrates their attitude using differential friction wheels, and then pushes them to the intelligent sensing module in a single queue.

[0058] The intelligent sensing module's laser contour scanning unit rotates to obtain diameter and roundness deviation, the visual image recognition unit detects length, the multispectral analysis unit identifies material, and the data fusion processing unit integrates and outputs comprehensive detection results (such as "φ5mm, roundness deviation 0.02mm, length 29.97mm, material aluminum") and transmits them to the control module.

[0059] The matching analysis unit of the control module retrieves the preset database and, combined with the processing cycle of 60 pieces / minute, optimizes and determines the process parameters (channel width 5.01mm, clamping force 0.15MPa, feeding step distance 29.97mm, speed 200mm / s). The modular program generation unit calls the corresponding module to generate a dynamic control program, which is then transmitted to the adaptive adjustment module.

[0060] The adaptive adjustment module's variable diameter flexible wheel set channel adjustment unit adjusts the channel width to 5.01mm, and the pressure sensor provides feedback data and fine-tunes the contact pressure to 0.06MPa; the electric servo flexible clamping adjustment unit adjusts the three-jaw clamping force to 0.15MPa, with a buffer compression of 2.5mm, clamping the middle of the billet and aligning it with the processing station; the feeding step distance and speed adjustment unit pushes the billet with an S-shaped acceleration and deceleration curve at a step distance of 29.97mm and a speed of 200mm / s, and the displacement sensor uses a closed-loop correction to correct the position accuracy.

[0061] The safety protection module monitors the status of each component in real time. When the clamping force of the aluminum billet fluctuates to 0.21MPa (exceeding the ±0.05MPa threshold), a level two warning is triggered, a high-frequency audible and visual alarm is activated, the feeding action is paused, and the human-machine interface displays "Abnormal fluctuation in clamping force, check the pressure sensor." After the operator troubleshoots and resets the sensor, the equipment resumes operation. When changing between three specifications of billets, no manual adjustment is required. The device automatically completes sorting, detection, parameter adaptation and adjustment, with a changeover time of ≤1 minute. Compared with traditional feeding devices (changeover time 30 minutes), the efficiency is improved by 96.7%. The feeding position accuracy is ±0.02mm, the billet damage rate is 0.08%, and the product qualification rate is improved by 2.3%, fully adapting to the needs of flexible production of multiple specifications.

[0062] In summary, the embodiments of this application realize automatic sorting, accurate detection, adaptive parameter matching, and safety protection of multi-specification billets, which significantly shortens changeover time, improves feeding accuracy and production efficiency, reduces billet damage rate and labor costs, and ensures safe operation of equipment through graded early warning and closed-loop protection. It effectively adapts to the flexible production needs of small batches and multiple varieties, and provides important technical support for the intelligent upgrading of the cold heading machine processing industry. It has significant practicality and promotion value.

[0063] Next, referring to the accompanying drawings, a cold heading machine feeding method with adaptive billet specifications is described according to an embodiment of this application.

[0064] Specifically, Figure 2 A flowchart illustrating a cold heading machine feeding method with adaptive billet specifications provided in an embodiment of this application.

[0065] like Figure 2 As shown, the feeding method for a cold heading machine with adaptive billet specifications includes the following steps: In step S101, the billet feeding module realizes the automatic and orderly feeding of billets, and supports the mixed feeding and queue management of billets of multiple specifications.

[0066] Specifically, mixed-size billets are batched into the feeding port, and billets exceeding the specified size are removed by a vibrating screen. The remaining billets are conveyed to the intelligent sorting area and allocated to the corresponding storage zones according to preset specification ranges. Upon receiving a billet demand signal from the control module, billets are extracted from the corresponding storage zones according to the required specifications. The extracted billets are calibrated to a uniform axial orientation and continuously and smoothly conveyed to the intelligent sensing module in a single-column queue.

[0067] It is understood that the embodiments of this application realize the automated sorting, classification and standardized conveying of mixed specification billets. The transformation from disordered feeding to orderly feeding can be completed without manual intervention, which not only greatly improves the feeding efficiency, but also provides standardized preconditions for subsequent high-precision detection through attitude calibration, effectively adapting to the feeding needs of flexible production of multiple specifications.

[0068] In step S102, the three-dimensional geometric features and surface texture information of the billet are collected in real time through dual-mode laser contour scanning and visual image recognition. Combined with multispectral analysis technology, the billet diameter, roundness deviation, length and material properties are accurately detected to obtain the detection results.

[0069] Specifically, a high-precision laser displacement sensor is used to collect radial cross-sectional contour data of the billet. A rotary drive assembly drives the sensor to rotate 360° radially along the billet, and edge extraction and fitting algorithms are used to calculate the actual diameter and roundness deviation of the billet. An industrial camera with a telecentric lens acquires image information perpendicular to the billet conveying direction. Image segmentation, grayscale processing, and endpoint positioning algorithms are used to accurately identify the positions of the two end faces of the billet and calculate its actual length. A multi-band spectral sensor emits visible and near-infrared light in the 400-1000nm range to illuminate the billet surface, collecting the reflected spectral signals. A spectral feature matching algorithm is used to compare these signals with a pre-set spectral database of different materials such as steel, aluminum, and copper to identify the billet's material characteristics. The acquired data are then integrated to obtain a comprehensive detection result including billet diameter, roundness deviation, length, and material composition.

[0070] It is understood that the embodiments of this application construct a multi-dimensional precision detection system of "geometric detection + material recognition". The combination of laser-vision dual mode and multispectral technology significantly improves the detection accuracy and comprehensiveness compared with the traditional single detection method. At the same time, data fusion ensures the reliability of the results and provides accurate data support for subsequent process parameter matching, thus ensuring the quality of material feeding and processing from the source.

[0071] In step S103, the detection results are matched and analyzed with the preset process parameter library, and a dynamic control program is generated in real time through an embedded intelligent algorithm.

[0072] Specifically, the test results are received and subjected to deep matching and multi-objective optimization analysis with a pre-set process knowledge base and material database to determine the most suitable combination of process parameters for the current billet. The functions of adjusting the width of the feeding channel, controlling the posture and clamping force of the clamping mechanism, and adjusting the feeding step distance and speed are decomposed into independent program modules. Based on the process parameter combination, the corresponding modules are quickly called through embedded algorithms to complete parameter assignment and logical linkage, thereby generating a dynamic control program.

[0073] It is understood that the embodiments of this application ensure the balance and adaptability of parameter combinations through multi-objective optimization algorithms, and the modular programming architecture takes into account the flexibility and scalability of the program, realizing the efficient conversion from detection results to control instructions, and providing accurate execution basis for adaptive adjustment.

[0074] In step S104, an adaptive adjustment mechanism that combines a variable-diameter flexible wheel set with an electric servo gripper is used to dynamically adjust the width of the feeding channel, the posture and clamping force of the clamping mechanism, and the feeding step distance and speed according to the dynamic control program.

[0075] Specifically, based on the channel width parameter in the dynamic control program, the opening and closing dimensions of the feeding channel are adaptively adjusted to achieve stable conveying of billets of different diameters. Based on the clamping parameters in the dynamic control program, the posture and clamping force of the clamping mechanism are adjusted to achieve clamping of billets of different materials and specifications. Based on the feeding step distance and speed in the dynamic control program, the feeding step distance and speed are adjusted respectively, and through servo drive and displacement closed-loop feedback, precise control of the feeding step distance and smooth switching of speed are achieved.

[0076] It is understood that the embodiments of this application, through the collaborative design of variable diameter flexible wheel set and electric servo gripper, take into account both conveying stability and billet protection. Servo drive and closed-loop feedback mechanism ensure adjustment accuracy, effectively adapt to the feeding needs of billets of multiple specifications and materials, and realize the precise implementation from control command to execution action.

[0077] In step S105, the operating status of the equipment is monitored in real time to achieve fault early warning and autonomous shutdown protection.

[0078] Specifically, multi-dimensional sensors are used to collect real-time data on key components and operating parameters of the feeding device to obtain status data. This status data is then compared and analyzed with preset safety thresholds. A three-level graded early warning mechanism is employed to implement differentiated responses. For Level 1 minor anomalies, an audible and visual warning is triggered, and the control module is linked to fine-tune equipment parameters for self-correction. For Level 2 moderate anomalies, a high-frequency audible and visual alarm is switched on, and the feeding operation is paused, simultaneously displaying the fault location, cause, and troubleshooting suggestions. For Level 3 severe anomalies, a shutdown signal is immediately triggered.

[0079] It is understood that the embodiments of this application construct a comprehensive security protection system. The three-level early warning mechanism realizes the prediction, control and loss prevention of faults, which not only prevents minor abnormalities from escalating into serious faults, but also maximizes the safety of operators, equipment stability and production continuity, and reduces the losses caused by faults.

[0080] The following section will elaborate on a feeding method for a cold heading machine that adapts to different billet specifications. For automotive parts manufacturing, it is necessary to alternately process φ5mm aluminum billets (30mm in length), φ12mm steel billets (80mm in length), and φ18mm copper billets (three specifications are mixed and fed). The cold heading machine has a processing cycle of 60 pieces / minute. First, the mixed billets are batched into the feeding port. A vibrating screen removes unqualified billets, and infrared sensors sort them to the corresponding storage areas. The conveying unit extracts the billets according to the control module's instructions, calibrates their posture, and then conveys them to the intelligent sensing module in a single queue. A laser sensor scans and determines that the φ5mm aluminum billet has a diameter of 4.99mm and a roundness deviation of 0.02mm. A vision camera measures the length to be 29.97mm, and a multispectral sensor identifies it as aluminum. The detection results are integrated and output. A multi-objective optimization algorithm is used to match the optimal parameter combination: channel width 5.01mm, clamping force 0.15MPa, feeding step distance 29.97mm, and speed 200mm / s, generating a dynamic control program. The adaptive adjustment mechanism adjusts parameters according to the program, setting the channel width to 5.01mm and stabilizing the three-jaw clamping force at 0.15MPa. It pushes the billet at a speed of 200mm / s using an S-shaped curve, with a step distance accuracy of ±0.02mm. Throughout the process, sensors monitor the status of each component in real time. When the aluminum billet clamping force fluctuates to 0.21MPa, a level two warning is triggered, pausing feeding and prompting a check of the pressure sensor. Operation resumes after the fault is resolved. No manual adjustment is required when changing between the three billet specifications, with a changeover time of ≤1 minute, a feeding damage rate of 0.08%, and a product qualification rate improvement of 2.3%, fully adapting to flexible production needs.

[0081] In summary, this application's embodiments construct a complete cold heading machine feeding method encompassing "automatic feeding - precise detection - intelligent matching - adaptive adjustment - safety protection," achieving automated and intelligent feeding of billets of various specifications and materials. Compared to traditional feeding methods, it significantly reduces changeover time and labor costs, substantially improves feeding accuracy, stability, and production efficiency, while ensuring production safety through tiered early warning systems. It effectively adapts to the flexible production needs of small batches and diverse varieties, providing crucial technical support for the intelligent upgrading of the cold heading machine processing industry, and possesses significant practicality and promotional value.

[0082] Figure 3 is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 301, the processor 302, and the computer program stored on the memory 301 and capable of running on the processor 302.

[0083] When the processor 302 executes the program, it implements the cold heading machine feeding method with adaptive billet specifications provided in the above embodiments.

[0084] Furthermore, electronic devices also include: Communication interface 303 is used for communication between memory 301 and processor 302.

[0085] The memory 301 is used to store computer programs that can run on the processor 302.

[0086] The memory 301 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0087] If the memory 301, processor 302, and communication interface 303 are implemented independently, then the communication interface 303, memory 301, and processor 302 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0088] Optionally, in a specific implementation, if the memory 301, processor 302, and communication interface 303 are integrated on a single chip, then the memory 301, processor 302, and communication interface 303 can communicate with each other through an internal interface.

[0089] Processor 302 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0090] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for feeding a cold heading machine with adaptive billet specifications.

[0091] This application also provides a computer program product, which stores a computer program that, when executed by a processor, implements the above-described adaptive billet specification cold heading machine feeding method.

[0092] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0093] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0094] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0095] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0096] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

Claims

1. A feeding device for a cold heading machine that adapts to billet specifications, characterized in that, include: The system includes a billet feeding module, an intelligent sensing module, a control module, an adaptive adjustment module, and a safety protection module. The billet feeding module is used to realize the automatic and orderly feeding of billets, and supports the mixed feeding and queue management of billets of multiple specifications. The intelligent sensing module is connected to the billet feeding module. It collects the three-dimensional geometric features and surface texture information of the billet in real time through dual modes of laser contour scanning and visual image recognition. Combined with multispectral analysis technology, it accurately detects the billet diameter, roundness deviation, length, and material characteristics to obtain the detection results. The control module is connected to the intelligent sensing module and is used to perform matching analysis with the preset process parameter library based on the detection results, and generate a dynamic control program in real time through embedded intelligent algorithms; The adaptive adjustment module is connected to the control module and adopts a variable diameter flexible wheel set and an electric servo gripper collaborative mechanism to dynamically adjust the feeding channel width, clamping mechanism posture and clamping force, feeding step distance and speed according to the dynamic control program. The safety protection module is used to monitor the equipment's operating status in real time, enabling fault warning and autonomous shutdown protection.

2. The cold heading machine feeding device with adaptive billet specifications according to claim 1, characterized in that, The billet feeding module includes: a sorting unit and a conveying unit, wherein... The sorting unit is used to put mixed specification billets into the feeding port in batches, remove billets that exceed the size limit by vibrating screen, and the remaining billets enter the intelligent sorting area by conveyor belt and are allocated to the corresponding storage area according to the preset specification range. The conveying unit is used to receive the billet demand signal from the control module, extract the billet from the corresponding storage zone according to the demand specifications, calibrate the extracted billet to a uniform axial posture, and continuously and smoothly convey it to the intelligent sensing module in a single queue.

3. The cold heading machine feeding device with adaptive billet specifications according to claim 1, characterized in that, The intelligent sensing module includes: a laser contour scanning unit, a visual image recognition unit, a multispectral analysis unit, and a data fusion processing unit, wherein... The laser contour scanning unit is used to collect the radial cross-sectional contour data of the billet using a high-precision laser displacement sensor. The sensor is driven to rotate 360° along the radial direction of the billet by a rotation drive component. Combined with edge extraction and fitting algorithms, the actual diameter and roundness deviation of the billet are calculated. The visual image recognition unit is used to acquire image information perpendicular to the billet conveying direction through an industrial camera and a telecentric lens, and accurately identify the positions of the two end faces of the billet through image segmentation, grayscale processing and endpoint positioning algorithms, and calculate the actual length of the billet. The multispectral analysis unit is used to emit visible and near-infrared light in the range of 400-1000nm to irradiate the surface of the billet using a multi-band spectral sensor, collect the reflected spectral signal, and compare it with a preset spectral database of different materials such as steel, aluminum, and copper through a spectral feature matching algorithm to identify the material characteristics of the billet. The data fusion processing unit is used to integrate the data obtained by the above three units to obtain a comprehensive test result including billet diameter, roundness deviation, length, and material.

4. The cold heading machine feeding device with adaptive billet specifications according to claim 1, characterized in that, The control module includes: a matching analysis unit and a modular program generation unit, wherein... The matching analysis unit is used to receive the detection results, perform deep matching and multi-objective optimization analysis with the preset process knowledge base and material database, and determine the most suitable combination of process parameters for the current billet. The modular program generation unit is used to decompose the functions of feeding channel width adjustment, clamping mechanism posture and clamping force control, and feeding step distance and speed adjustment into independent program modules. Based on the process parameter combination, the corresponding module is quickly called through the embedded algorithm to complete parameter assignment and logical linkage, thereby generating a dynamic control program.

5. The cold heading machine feeding device with adaptive billet specifications according to claim 1, characterized in that, The adaptive adjustment module includes: a variable-diameter flexible wheel channel adjustment unit, an electro-servo flexible clamping adjustment unit, and a feeding step distance and speed adjustment unit, wherein... The variable diameter flexible wheel set channel adjustment unit is used to adaptively adjust the opening and closing size of the feeding channel according to the channel width parameter in the dynamic control program, so as to realize the stable conveying of billets of different diameters. The electric servo flexible clamping adjustment unit is used to adjust the posture and clamping force of the clamping mechanism according to the clamping parameters in the dynamic control program, so as to achieve clamping of blanks of different materials and specifications. The feeding step distance and speed adjustment unit is used to adjust the feeding step distance and speed according to the feeding step distance and speed in the dynamic control program. Through servo drive and displacement closed-loop feedback, it realizes precise control of the feeding step distance and smooth switching of speed.

6. The cold heading machine feeding device with adaptive billet specifications according to claim 1, characterized in that, The security protection module includes: a status monitoring unit and a fault early warning unit, wherein... The status monitoring unit is used to collect status data in real time from key parts and operating parameters of the feeding device through multi-dimensional sensors. The fault early warning unit is used to receive the status data, compare and analyze it with the preset safety threshold, and implement differentiated response using a three-level graded early warning mechanism. When the first level is a minor abnormality, an audible and visual warning is triggered and the control module is linked to fine-tune the equipment parameters to achieve self-correction. When the second level is a moderate abnormality, a high-frequency audible and visual alarm is switched and the feeding action is suspended, and the fault location, cause and troubleshooting suggestions are displayed simultaneously. When the third level is a severe abnormality, a shutdown signal is immediately triggered.

7. A feeding method for a cold heading machine that adapts to billet specifications, characterized in that, Includes the following steps: The billet feeding module enables automatic and orderly feeding of billets, supporting mixed feeding and queue management of billets of multiple specifications. The three-dimensional geometric features and surface texture information of the billet are acquired in real time through dual modes of laser contour scanning and visual image recognition. Combined with multispectral analysis technology, the billet diameter, roundness deviation, length and material properties are accurately detected to obtain the detection results. Based on the detection results, a matching analysis is performed with a preset process parameter library, and a dynamic control program is generated in real time through an embedded intelligent algorithm. An adaptive adjustment mechanism is adopted, which combines a variable-diameter flexible wheel set with an electric servo gripper, to dynamically adjust the width of the feeding channel, the posture and clamping force of the clamping mechanism, and the feeding step distance and speed according to the dynamic control program. Real-time monitoring of equipment operating status enables fault early warning and autonomous shutdown protection.

8. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement the cold heading machine feeding method for adaptive billet specifications as described in claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement a cold heading machine feeding method with adaptive billet specifications as described in claim 7.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement the cold heading machine feeding method for adaptive billet specifications as described in claim 7.

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