Intelligent dynamic positioning stamping control system and method for bearing part

Abstract

The invention relates to the technical field of stamping dies, in particular to an intelligent bearing part dynamic positioning stamping control system which comprises a sensor module, a control module and a control module. The sensor module comprises a position sensor used for monitoring the position and the motion state of a bearing part in real time and a pressure sensor used for detecting pressure changes in the stamping process; the position sensor is a laser displacement sensor or a visual sensor; according to the scheme, the sensor module collects data such as the position of a bearing part and stamping pressure in real time, analysis and processing are conducted in combination with an intelligent algorithm of the control module, and the execution module is precisely driven to achieve dynamic positioning and stamping control; and meanwhile, the man-machine interaction module is utilized, so that an operator can conveniently and flexibly set parameters and monitor production. According to the system and method, high-precision and automatic dynamic positioning and stamping of the bearing part are achieved, the production efficiency and the product quality are remarkably improved, the adaptability of the system to diversified production requirements is enhanced, and the equipment failure risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of stamping dies, and in particular to a dynamic positioning stamping control system and method for an intelligent bearing component. Background Art

[0002] Dynamic positioning and stamping control of bearing parts is a key link in the bearing manufacturing process. Its accuracy and efficiency directly affect the quality of bearings and the production efficiency of enterprises. Traditional dynamic positioning and stamping control systems for bearing parts mostly rely on manual operation or simple mechanical positioning devices, which have many shortcomings. On the one hand, manual positioning is limited by the operator's experience and proficiency, and positioning accuracy is difficult to guarantee, resulting in large dimensional deviations of the stamped bearing parts and a high scrap rate. On the other hand, simple mechanical positioning devices have poor flexibility and cannot adapt to the production needs of bearing parts of different models and specifications. In addition, there is a lack of real-time monitoring and feedback mechanisms during the stamping process, making it difficult to dynamically adjust parameters such as pressure and position. The equipment operation is unstable and production efficiency is low.

[0003] To this end, this paper proposes an intelligent bearing component dynamic positioning and stamping control system and method. This system uses a sensor module to collect real-time data such as bearing component position and stamping pressure. This data is analyzed and processed using an intelligent algorithm in a control module, which then precisely drives an execution module to achieve dynamic positioning and stamping control. Furthermore, a human-computer interaction module facilitates flexible parameter setting and production monitoring by operators. This system and method achieves high-precision, automated dynamic positioning and stamping of bearing components, significantly improving production efficiency and product quality, enhancing the system's adaptability to diverse production needs, and reducing the risk of equipment failure. Summary of the Invention

[0004] Technical problems to be solved: Problems that rely heavily on manual operation or simple mechanical positioning devices.

[0005] In view of the deficiencies in the prior art, the present invention provides a dynamic positioning and stamping control system and method for intelligent bearing components, thereby solving the technical problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] An intelligent bearing component dynamic positioning stamping control system, the system comprising:

[0008] A sensor module comprising a position sensor for real-time monitoring of the position and motion state of the bearing, and a pressure sensor for detecting pressure changes during the stamping process. The position sensor is a laser displacement sensor or a visual sensor. The laser displacement sensor acquires position information by emitting a laser beam to detect the distance from the surface of the bearing, and the visual sensor acquires position and posture information of the bearing by capturing an image and performing image recognition.

[0009] A control module, composed of an industrial computer or a programmable logic controller, is used to receive signals from the sensor module, perform analysis and processing, and issue control instructions based on preset algorithms and parameters. The control module uses a model predictive control algorithm to establish a mathematical model of the dynamic positioning and stamping process of the bearing component, uses the model to predict the future system state, optimizes the control strategy based on the prediction results, and adjusts the control instructions through rolling optimization and feedback correction;

[0010] An execution module, comprising a motor, a cylinder drive device and a stamping die, wherein the drive device controls the movement of the stamping die according to the instructions of the control module to achieve dynamic positioning and stamping operations on the bearing component;

[0011] The human-computer interaction module is used by operators to set system parameters, monitor system operating status and make intervention adjustments; the human-computer interaction module is equipped with a touch screen, supports graphical interface operation, and can intuitively display system parameters, real-time operating data and fault alarm information.

[0012] In one possible implementation, the position sensor is a laser displacement sensor or a visual sensor. The laser displacement sensor acquires position information by emitting a laser beam to detect the surface distance of the bearing component, and the visual sensor acquires the position and posture information of the bearing component by capturing an image and performing image recognition.

[0013] In one possible implementation, the control module adopts a model predictive control algorithm, establishes a mathematical model of the dynamic positioning and stamping process of the bearing parts, uses the model to predict the future system state, optimizes the control strategy based on the prediction results, and adjusts the control instructions through rolling optimization and feedback correction.

[0014] In one possible implementation, a method for controlling dynamic positioning and stamping of an intelligent bearing component applied to the above-mentioned dynamic positioning and stamping control system of an intelligent bearing component includes the following steps:

[0015] Step 1: The position sensor collects the position information of the bearing in real time and transmits it to the control module;

[0016] Step 2: The control module compares the received position information with the preset target position, calculates the deviation value, generates a control instruction through the control algorithm, and drives the driving device in the execution module to adjust the position of the bearing component to complete dynamic positioning;

[0017] Step 3: After the bearing is positioned, the pressure sensor starts to monitor the pressure changes during the stamping process and transmits the pressure signal to the control module;

[0018] Step 4: The control module adjusts the movement speed and pressure of the stamping die in real time according to the pressure signal to ensure that the stamping process is carried out according to the preset process parameters.

[0019] In a possible implementation, during the position adjustment process, a PID control algorithm is used to control the driving device to achieve fast and accurate position adjustment.

[0020] In one possible implementation, when the control module adjusts the stamping die movement speed and pressure in real time according to the pressure signal, it uses a fuzzy control algorithm, takes the pressure deviation and the deviation change rate as input, obtains the output control quantity through fuzzy reasoning, and then adjusts the stamping die movement parameters.

[0021] In one possible implementation, after each stamping is completed, the system automatically analyzes the stamping data, including the pressure curve, position accuracy, etc., and compares it with the standard data. If it is found that the deviation exceeds the allowable range, the subsequent stamping parameters are automatically corrected.

[0022] In one possible implementation, a system self-check step is also included. Before the system starts, the control module performs a self-check on the sensor module, execution module, human-computer interaction module, and data storage module to ensure that each module functions normally. If a fault is detected, detailed fault information is displayed through the human-computer interaction module and the system startup is prohibited.

[0023] Beneficial effects compared with existing technologies:

[0024] 1. This solution uses high-precision sensors to collect real-time data on the bearing's position and motion status. This, combined with a control module to rapidly calculate deviations and drive adjustments in the execution module, enables precise dynamic positioning of the bearing. Compared to traditional manual or static positioning methods, this significantly improves positioning accuracy and efficiency, enabling bearings to enter the stamping station with greater precision, reducing product defects caused by positioning errors and laying the foundation for high-quality stamping processing.

[0025] 2. In this solution, pressure sensors are used to monitor pressure changes during the stamping process. The control module adjusts the stamping die speed and pressure in real time based on preset process parameters and actual pressure signals, achieving refined control of the stamping process. This avoids problems such as bearing deformation and damage caused by uneven pressure and improper speed, effectively improving the qualified rate of stamped products and reducing scrap rates and production costs.

[0026] 3. In this solution, the system integrates automated dynamic positioning and stamping control functions, combines with a human-machine interaction module to achieve flexible parameter setting, and ensures safe equipment operation through fault diagnosis and alarm mechanisms, thus realizing an intelligent and efficient production process. It reduces manual intervention, improves production efficiency, and enhances the system's adaptability to different bearing models and process requirements. At the same time, it ensures the safety of equipment and personnel, and comprehensively improves the company's production efficiency and competitiveness. DETAILED DESCRIPTION

[0027] The preferred embodiments of the present invention are described in detail. However, the present invention can be implemented in various forms, so the present invention is not limited to the embodiments described below.

[0028] The technical solution in the embodiments of the present application is to solve the problems of the above-mentioned background technology, and the overall idea is as follows:

[0029] Example 1:

[0030] This embodiment introduces an intelligent bearing dynamic positioning and stamping control system. The system is primarily composed of a sensor module, a control module, an execution module, a human-computer interaction module, and a communication module. These modules work together to achieve precise control of the dynamic positioning and stamping process of the bearing. The system architecture adopts a layered design, from bottom-level data collection to upper-level decision-making and control, forming an organic whole. Data exchange between each layer is carried out through standardized communication protocols.

[0031] 1. Sensor module

[0032] 1.1. Position sensor selection and layout

[0033] A high-precision laser displacement sensor (model: Keyence LK-G80) was selected. This sensor has a measurement range of 0-300mm and a repeatability of up to ±0.1μm, which can meet the high-precision requirements for dynamic positioning of bearing parts. Sensors are placed at the entrance, key intermediate positions, and stamping stations of the bearing part transmission track. Two laser displacement sensors are installed at the entrance, distributed diagonally, to obtain the initial position and posture information of the bearing part when it enters the system. A sensor is placed every 1000mm in the middle of the transmission track to monitor the position deviation of the bearing part during transmission in real time. Four sensors are placed around the stamping station to accurately measure the position and angular deviation of the bearing part when it arrives at the stamping station.

[0034] 1.2. Pressure sensor selection and installation

[0035] A strain gauge pressure sensor (model: HBMPW10AC3) with a range of 0-500kN and an accuracy of 0.05% is used to accurately measure pressure changes during the stamping process. The pressure sensor is installed between the upper die holder of the stamping die and the press slide. A dedicated mounting fixture ensures close contact between the sensor, the die, and the slide, ensuring accurate transmission of the pressure signal. An elastic gasket is placed between the sensor and the mounting fixture to cushion the impact during the stamping process and protect the sensor.

[0036] 1.3 Other sensor configurations

[0037] In addition to position sensors and pressure sensors, a temperature sensor (model: Pt100) is also configured to monitor the temperature changes of the stamping die during long-term operation to prevent the die from overheating and affecting the stamping quality. A vibration sensor (model: PCB352C03) is installed on the press body and bearing transmission equipment to monitor the vibration of the equipment in real time and promptly detect potential equipment failures.

[0038] 2. Control module

[0039] 2.1 Hardware Selection

[0040] The control module utilizes a high-performance industrial computer (Intel Core i7-12700K processor, 32GB memory, 1TB solid-state drive) paired with a programmable logic controller (PLC, Siemens S7-1500). The industrial computer is responsible for running complex control algorithms, data processing, and human-machine interface programs; the PLC is used to implement real-time control and logic processing of field equipment. The two communicate via an Ethernet interface to ensure real-time and stable data transmission.

[0041] 2.2 Software Design

[0042] The control software is developed based on the Windows 10 operating system, using Visual Studio 2022 as the development platform and written in C# language. The software mainly includes data acquisition module, control algorithm module, equipment monitoring module and human-computer interaction interface module.

[0043] 2.2.1. Data acquisition module: Communicates with sensors through the OPCUA protocol to collect sensor data such as position, pressure, temperature, vibration, etc. in real time, and filters the collected data to remove noise interference and improve data accuracy;

[0044] 2.2.2 Control Algorithm Module: This module integrates a dynamic positioning algorithm based on model predictive control (MPC) and a stamping process control algorithm. The MPC algorithm predicts the position change over a period of time based on the current position and motion state of the bearing. It calculates the optimal control variable through rolling optimization and drives the actuator to adjust the position of the bearing. The stamping process control algorithm adjusts the speed and pressure of the stamping die in real time based on the pressure value fed back by the pressure sensor to ensure that the stamping process meets process requirements.

[0045] 2.2.3. Equipment monitoring module: monitors the operating status of sensors, actuators, motors and other equipment in real time. When equipment failure or abnormality is detected, it immediately issues an alarm signal and takes corresponding protective measures, such as stopping equipment operation and cutting off power supply.

[0046] 2.2.4 Human-machine interaction interface module: A user-friendly interface is designed, through which operators can set system parameters (such as bearing model, stamping process parameters, control algorithm parameters, etc.), view equipment operating status, query and analyze historical data, and generate reports;

[0047] 3. Execution module

[0048] 3.1 Motor drive system

[0049] A servo motor (model: Mitsubishi HG-KN43J-S100) paired with a high-precision planetary reducer (reduction ratio: 1:10) is used as the drive device for bearing transmission and mold movement. The servo motor has a rated power of 400W and a rated speed of 3000r / min. The position control accuracy can reach ±1 pulse, which can meet the system's requirements for high-precision motion control. The motor driver (model: Mitsubishi MR-JE-40A) controls the servo motor's speed and direction through pulse and direction signals, and supports real-time torque control and position feedback functions to ensure the stability and accuracy of the motor's operation.

[0050] 3.2 Cylinder drive system

[0051] Auxiliary actions, such as the rapid opening and closing of molds and the clamping of bearings, are driven by pneumatic cylinders. The SMC standard cylinder (model: MGPM20-50Z) is used, with a bore of 20 mm, a stroke of 50 mm, and an operating pressure range of 0.1-0.7 MPa. The cylinder's movement is controlled by a solenoid valve (model: VQZ3151-5LZD-01), which switches on and off via the output signal of the PLC, thereby controlling the cylinder's extension and retraction. Magnetic switches (model: D-Z73) are installed at both ends of the cylinder to detect the cylinder's position and provide feedback to the PLC.

[0052] 3.3 Stamping Die

[0053] The stamping die is designed and manufactured according to different bearing models. It uses alloy steel (such as Cr12MoV) and undergoes heat treatment processes such as quenching and tempering to improve the hardness and wear resistance of the die. The die design complies with the die design specifications to ensure the structural strength and stability of the die. The die is equipped with positioning pins and guide mechanisms to ensure the accuracy and reliability of the die during the stamping process. At the same time, to facilitate die replacement and maintenance, a quick-change die structure is adopted, and the die can be quickly installed and removed through hydraulic or pneumatic clamps.

[0054] 4. Human-computer interaction module

[0055] 4.1 Hardware Selection

[0056] A 15-inch industrial touch screen (model: Weiluntong MT8150iE) was selected as the hardware device for the human-machine interface. This touch screen features high resolution (1024×768), wide viewing angle, strong anti-interference capabilities, and supports multi-touch operation, making it convenient for operators to set parameters and monitor equipment. The touch screen communicates with the industrial computer via an Ethernet interface to achieve real-time data interaction.

[0057] 4.2 Software Design

[0058] Design human-computer interaction interface software based on touch screen development environment (EasyBuilderPro); the interface is mainly divided into main interface, parameter setting interface, equipment monitoring interface, historical data query interface and alarm interface;

[0059] 4.2.1. Main interface: displays the overall operating status of the system, including equipment start and stop status, current production quantity, alarm information prompts, etc.

[0060] 4.2.2 Parameter setting interface: The operator can set the bearing model, stamping process parameters (such as stamping speed, pressure, holding time, etc.), control algorithm parameters, etc. on this interface; after the parameter setting is completed, the data is transmitted to the industrial computer and PLC via Ethernet;

[0061] 4.2.3. Equipment monitoring interface: Real-time display of sensor data, motor operating status, cylinder position status, mold temperature and other equipment operating information, presented intuitively in the form of charts and numbers, allowing operators to understand the equipment operating status in a timely manner;

[0062] 4.2.4. Historical data query interface: supports querying historical production data and equipment operation data such as position data, pressure data, temperature data, etc. by time, bearing model, etc., and can generate reports and curves to facilitate data analysis and production management;

[0063] 4.2.5. Alarm interface: When the system detects a device failure or abnormality, the alarm interface will immediately pop up an alarm message, displaying detailed information such as the alarm type, alarm time, and alarm location, accompanied by an audible and visual alarm prompt. The operator can view the alarm history through the alarm interface and confirm and handle the alarm;

[0064] 5. Communication module

[0065] The system uses a communication method that combines Ethernet and fieldbus. Industrial computers communicate with PLCs and touch screens via Ethernet, using the TCP / IP protocol to achieve high-speed data transmission and remote monitoring. Sensors communicate with PLCs via the fieldbus (PROFINET protocol), transmitting sensor data to the PLC in real time. Actuators (servo motor drivers, solenoid valves, etc.) communicate with the PLC via a dedicated communication interface (such as the SSCNET III / H bus for Mitsubishi servo motors) to ensure accurate transmission and execution of control commands. Furthermore, an OPC UA interface is reserved to facilitate data sharing and interaction in order to integrate the system with enterprise management systems (such as MES systems).

[0066] Example 2:

[0067] This embodiment, based on Example 1, describes a method for controlling the dynamic positioning and stamping of an intelligent bearing component. The method mainly includes five steps: data acquisition, state prediction, control decision-making, instruction execution, and feedback correction, forming a closed-loop control circuit.

[0068] 1. Data collection and preprocessing

[0069] 1.1 Data Collection

[0070] After the system is started, the sensor module collects the position, pressure, temperature, vibration and other data of the bearing in real time according to the set sampling frequency (the sampling frequency of the position sensor is 1000Hz, the sampling frequency of the pressure sensor is 500Hz, and the sampling frequency of the temperature sensor and vibration sensor is 100Hz); the position sensor collects the X, Y, and Z coordinates of the bearing on the transmission track and the rotation angle around the X, Y, and Z axes; the pressure sensor collects the real-time pressure value during the stamping process; the temperature sensor collects the temperature of the mold surface; and the vibration sensor collects parameters such as vibration acceleration, velocity, and displacement of the equipment.

[0071] 1.2 Data Preprocessing

[0072] The collected data is first filtered. The Kalman filter algorithm is used to filter the position and pressure data to remove noise interference and improve data accuracy. For temperature and vibration data, the median filter algorithm is used to eliminate random interference. Then, the pre-processed data is normalized and mapped to the [0, 1] interval to facilitate subsequent algorithm processing.

[0073] 2. Dynamic positioning based on model predictive control

[0074] 2.1 System Modeling

[0075] A mathematical model of the bearing transmission system is established. The motion of the bearing is considered as a rigid body motion. Factors such as the friction of the transmission track and the motor driving force are considered to establish the state space equation. The state variables of the system are set as x = [x1, x2, x3, θ1, θ2, θ3] T , where x1, x2, x3 are the positions of the bearing in the X, Y, and Z directions respectively, and θ1, θ2, θ3 are the rotation angles of the bearing around the X, Y, and Z axes respectively; the control variable is u = [u1, u2] T , where u1 is the speed of the servo motor and u2 is the direction of the motor. According to Newton's laws of motion and the rigid body rotation equation, the state space model of the system is: Where A is the system matrix, B is the input matrix, C is the output matrix, w is the process noise, and v is the measurement noise;

[0076] 2.2. Rolling Optimization

[0077] At each sampling moment, according to the current system state x(k) and the prediction time domain N p , control time domain N c (Assume N p =10, N c =5), predict the future N p The system status at a moment;

[0078] By solving the optimization problem, we can get the future N c The optimal control sequence at each moment is u(k|k),u(k+1|k),…,u(k+N c -1|k)}, the optimization objective function is: Where yd(i) is the desired system output (i.e., the target position and posture of the bearing), Q is the output error weight matrix, and R is the control variable weight matrix. After solving the above optimization problem and obtaining the optimal control sequence, only the first control variable u(k|k) is applied to the system. At the next sampling moment, the above process is repeated to achieve rolling optimization.

[0079] 2.3 Feedback Correction

[0080] At each sampling moment, the actual measured system output y(k) is compared with the predicted output y(k|k), and the prediction error e(k) = y(k) - y(k|k) is calculated. The model is corrected based on the prediction error, and the system state estimate is updated to improve the model's prediction accuracy. The state feedback correction method is used to multiply the prediction error by the correction gain matrix K and add it to the state estimate to obtain the corrected state estimate:

[0081] 3. Stamping process control based on fuzzy control

[0082] 3.1 Fuzzy Controller Design

[0083] The input variables of the fuzzy controller are the pressure deviation ΔP and the pressure deviation change rate during the stamping process. The output variables are the stamping die's velocity adjustment Δv and pressure adjustment ΔF;

[0084] Fuzzy: Pressure deviation ΔP, pressure deviation change rate The speed adjustment Δv and pressure adjustment ΔF are divided into different fuzzy subsets, such as {NB / NM / NS / ZO / PS / PM / PB} (representing negative large, negative medium, negative small, zero, positive small, positive medium, and positive large, respectively). The membership function of each fuzzy subset is determined according to the actual physical quantity range, and a triangular membership function is used.

[0085] Fuzzy rule formulation: According to stamping process experience and expert knowledge, a fuzzy control rule table is formulated; for example, when the pressure deviation ΔP is positive and the pressure deviation change rate is When it is positive, the movement speed and pressure of the stamping die should be reduced, that is, the speed adjustment Δv is negative and the pressure adjustment ΔF is negative;

[0086] Fuzzy reasoning: Using the Mamdani reasoning method, fuzzy reasoning is performed based on the fuzzy subsets of input variables and the fuzzy control rule table to obtain the fuzzy subsets of output variables;

[0087] Clarification: The center of gravity method is used to clarify the output fuzzy subset obtained by fuzzy reasoning to obtain accurate speed adjustment Δv and pressure adjustment ΔF;

[0088] 3.2 Stamping process control

[0089] During the stamping process, the pressure value of the pressure sensor is collected in real time to calculate the pressure deviation ΔP and the pressure deviation change rate. This is input into the fuzzy controller to obtain the speed adjustment Δv and pressure adjustment ΔF. The speed adjustment Δv is then sent to the servo motor driver to adjust the movement speed of the stamping die. The pressure adjustment ΔF is sent to the hydraulic system of the press to adjust the stamping pressure to ensure that the stamping process meets the process requirements.

[0090] 4. Control instruction execution and feedback

[0091] 4.1 Instruction Execution

[0092] The control module generates control instructions based on the dynamic positioning algorithm and the stamping process control algorithm, and sends the instructions to the execution module through the communication module. For the dynamic positioning control instructions of the bearing, the speed and direction of the servo motor are controlled to drive the bearing transmission equipment to accurately position the bearing to the stamping station. For the stamping process control instructions, the movement speed of the servo motor and the hydraulic system of the press are controlled to achieve precise control of the stamping die.

[0093] 4.2 Feedback and Adjustment

[0094] After the execution module executes the control command, the sensor module collects data such as the position of the bearing and the pressure during the stamping process in real time and feeds this data back to the control module. Based on the feedback data, the control module determines whether the system has achieved the expected control target. If not, the control module re-performs state prediction, control decision-making, and command execution until the system reaches a stable state, achieving precise control of the dynamic positioning of the bearing and the stamping process.

[0095] 5. System debugging and optimization

[0096] 5.1 System Debugging

[0097] After the system is installed, it is time to debug the system. First, the sensors are calibrated to ensure the accuracy of the sensor measurement data. Then, the actuators are debugged under no-load conditions to check the operation of the motors, cylinders, and other equipment, and the equipment parameters are adjusted to achieve optimal working conditions. Finally, the system is debugged to simulate the actual production process, test the overall performance of the system, and check whether the communication between the modules is normal and whether the control algorithm is effective.

[0098] 5.2 System Optimization

[0099] Optimize the system based on the problems found during system debugging and actual production operation data. Adjust the parameters of the control algorithm, such as the prediction time domain, control time domain, and weight matrix in model predictive control, and the fuzzy rules and membership functions in fuzzy control, to improve the control accuracy and response speed of the system. Optimize the operating parameters of the equipment, such as the motor speed and cylinder pressure, to improve the operating efficiency and stability of the equipment. At the same time, expand and improve the functions of the system according to production needs, such as adding support for new bearing models and optimizing the human-machine interaction interface.

[0100] In summary, as the bearing slowly enters the positioning area along the transmission line, high-precision laser position sensors installed on both sides of the transmission line begin to operate. These sensors can perform thousands of detections per second, and with an ultra-high accuracy of ±0.01mm, they can quickly detect position offsets and posture changes of the bearing during transmission. The sensors transmit the collected position and posture data in the form of electrical signals to the control module in real time.

[0101] The control module, the "brain" of the system, consists of a high-performance industrial computer and Advantech's PCI-1710 data acquisition card, running dedicated control software developed on the LabVIEW platform. The data acquisition card receives electrical signals from sensors and converts them into digital signals that the computer can process. The control software first filters these raw data to remove noise caused by factors such as electromagnetic interference, ensuring data accuracy.

[0102] The control software then compares the processed data with the preset target position and calculates the bearing's deviation in the X, Y, and Z directions. For example, if the bearing is detected to be 0.2mm off target in the X direction, 0.15mm off in the Y direction, and 0.1mm off in the Z direction, the control software uses a model-predictive control algorithm, combining the bearing's motion state and the system's dynamic characteristics, to predict the bearing's position change trend over a period of time and generate precise control instructions based on the predicted results.

[0103] After the control command is generated, it is transmitted to the execution module via an electrical connection. Upon receiving the command, the servo motor in the execution module immediately drives the high-precision linear guide rail. With its high response speed and precise angular control capabilities, the servo motor converts the motor's rotational motion into linear motion of the linear guide rail in the X, Y, and Z directions via a high-precision ball screw, thereby adjusting the position of the bearing. During the adjustment process, the laser position sensor continuously monitors the position changes of the bearing and feeds the new data back to the control module. The control module continuously adjusts the control command based on the feedback data until the bearing is precisely positioned on the stamping station, with a positioning accuracy of up to ±0.05mm.

[0104] When the bearing is positioned, the control module sends a stamping command to the hydraulic press. The hydraulic press is equipped with an advanced proportional valve and servo control system, which performs stamping operations according to preset stamping process parameters. During the stamping process, a pressure sensor installed on the stamping die monitors the changes in stamping pressure in real time at a sampling frequency of 1000Hz and feeds the data back to the control module.

[0105] If during the stamping process, the pressure sensor detects that the pressure exceeds the preset threshold (such as the pressure suddenly rises to 1200kN), or the laser position sensor detects that the bearing position is offset, the control module will immediately issue an alarm signal and take corresponding measures according to the severity of the abnormal situation; if it is a slight pressure fluctuation, the control module will fine-tune the stamping pressure by adjusting the proportional valve of the hydraulic press; if the position offset is more serious, the control module will suspend stamping, restart the positioning process, and re-position the bearing to ensure the safety and quality of the stamping process.

[0106] Finally, it should be noted that the above embodiments are merely examples for the purpose of illustrating the present invention and are not intended to limit the embodiments. Those skilled in the art will readily appreciate that other variations or modifications based on the above description are possible. It is not necessary and impossible to provide an exhaustive list of all embodiments. However, obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. An intelligent bearing dynamic positioning stamping control system, characterized in that: The system comprises: A sensor module comprising a position sensor for real-time monitoring of the position and motion state of the bearing, and a pressure sensor for detecting pressure changes during the stamping process. The position sensor is a laser displacement sensor or a visual sensor. The laser displacement sensor acquires position information by emitting a laser beam to detect the distance from the surface of the bearing, and the visual sensor acquires position and posture information of the bearing by capturing an image and performing image recognition. A control module, composed of an industrial computer or a programmable logic controller, is used to receive signals from the sensor module, perform analysis and processing, and issue control instructions based on preset algorithms and parameters. The control module uses a model predictive control algorithm to establish a mathematical model of the dynamic positioning and stamping process of the bearing component, uses the model to predict the future system state, optimizes the control strategy based on the prediction results, and adjusts the control instructions through rolling optimization and feedback correction; An execution module, comprising a motor, a cylinder drive device and a stamping die, wherein the drive device controls the movement of the stamping die according to the instructions of the control module to achieve dynamic positioning and stamping operations on the bearing component; The human-computer interaction module is used by operators to set system parameters, monitor system operating status and make intervention adjustments; the human-computer interaction module is equipped with a touch screen, supports graphical interface operation, and can intuitively display system parameters, real-time operating data and fault alarm information.

2. The intelligent bearing dynamic positioning and stamping control system according to claim 1, characterized in that: The position sensor is a laser displacement sensor or a visual sensor. The laser displacement sensor obtains position information by emitting a laser beam to detect the surface distance of the bearing component. The visual sensor obtains the position and posture information of the bearing component by capturing an image and performing image recognition.

3. The intelligent bearing dynamic positioning and stamping control system according to claim 1, characterized in that: The control module adopts a model predictive control algorithm, establishes a mathematical model of the dynamic positioning and stamping process of the bearing parts, uses the model to predict the future system state, optimizes the control strategy based on the prediction results, and adjusts the control instructions through rolling optimization and feedback correction.

4. A method for controlling dynamic positioning and stamping of an intelligent bearing component applied to a dynamic positioning and stamping control system of an intelligent bearing component according to claims 1 to 3, characterized in that: The following steps are involved: Step 1: The position sensor collects the position information of the bearing in real time and transmits it to the control module; Step 2: The control module compares the received position information with the preset target position, calculates the deviation value, generates a control instruction through the control algorithm, and drives the driving device in the execution module to adjust the position of the bearing component to complete dynamic positioning; Step 3: After the bearing is positioned, the pressure sensor starts to monitor the pressure changes during the stamping process and transmits the pressure signal to the control module; Step 4: The control module adjusts the movement speed and pressure of the stamping die in real time according to the pressure signal to ensure that the stamping process is carried out according to the preset process parameters.

5. The method for dynamic positioning and stamping control of an intelligent bearing component according to claim 4, characterized in that: During the position adjustment process, a PID control algorithm is used to control the drive device to achieve fast and accurate position adjustment.

6. The method for dynamic positioning and stamping control of an intelligent bearing component according to claim 4, characterized in that: When the control module adjusts the stamping die movement speed and pressure in real time according to the pressure signal, it uses a fuzzy control algorithm, takes the pressure deviation and the deviation change rate as input, obtains the output control quantity through fuzzy reasoning, and then adjusts the stamping die movement parameters.

7. The method for dynamic positioning and stamping control of an intelligent bearing component according to claim 4, characterized in that: After each stamping is completed, the system automatically analyzes the stamping data, including pressure curve, position accuracy, etc., and compares it with the standard data. If it is found that the deviation exceeds the allowable range, the subsequent stamping parameters will be automatically corrected.

8. The method for dynamic positioning and stamping control of an intelligent bearing component according to claim 4, characterized in that: It also includes a system self-check step. Before the system starts, the control module performs a self-check on the sensor module, execution module, human-computer interaction module and data storage module to ensure that each module functions normally. If a fault is detected, detailed fault information is displayed through the human-computer interaction module and the system startup is prohibited.