Automatic compensation system and method for superfine bar finishing based on real-time detection feedback

Abstract

The application provides a superfine bar fine grinding automatic compensation system and method based on real-time detection feedback, the method obtains bar diameter data after fine grinding through online detection, a sliding window average deviation analysis is performed on continuous N groups of data by an edge calculation module, and the average deviation is compared with a preset tolerance: if the average deviation is not out of tolerance, steady-state processing is performed, if the average deviation is out of tolerance, a compensation displacement is calculated in combination with a grinding wheel wear model, the compensation is executed by driving a servo motor to push a grinding wheel frame by PLC, and after the compensation, continuous detection verification is performed, if the average deviation regresses to a deviation threshold value, it is determined that the compensation is effective and is exited, otherwise, iterative compensation is performed until the deviation converges or a termination condition is reached. The application solves at least one of the technical problems that the existing scheme relies on manual compensation, the response is slow, the precision consistency is poor, the detection and processing are disconnected, the automatic closed loop cannot be formed, the data dispersion leads to difficult quality tracing and OEE statistical lag, and the traditional compensation mechanism has response delay and cannot meet the high precision requirement.

Description

Technical Field

[0001] This invention relates to the technical field of precision machining of cemented carbide bars, and in particular to an automatic compensation system and method for precision grinding of ultra-fine bars based on real-time detection feedback. Background Technology

[0002] In the field of ultra-precision machining of cemented carbide bars (such as φ4 / φ6mm precision-ground bars), the precision grinding process is a crucial step determining the final dimensional accuracy and roundness quality of the bars. Currently, this process is typically performed using high-precision grinding machines, with the required machining accuracy for the bar diameter usually reaching the micrometer level. With the increasingly widespread application of ultrafine nano-cemented carbide bars in high-end manufacturing, the requirements for dimensional accuracy and consistency are constantly increasing, placing higher demands on the stability and controllability of the precision grinding process. At the same time, downstream processes also impose strict constraints on the machining cycle time. How to maintain high production efficiency while ensuring micrometer-level machining accuracy has become a pressing technical challenge in this field.

[0003] However, current precision grinding processes generally suffer from the following defects: On the one hand, the grinding wheels of the grinding machine wear continuously during processing, causing the cutting dimensions to drift. Compensation for dimensional accuracy mainly relies on manual adjustments by the operator based on experience, resulting in slow response speed, poor accuracy consistency, and frequent machine stops, making it difficult to meet the cycle time requirements under continuous processing conditions. On the other hand, although existing production lines are equipped with online inspection equipment, such equipment is mostly used for sampling or final inspection. Inspection data cannot be fed back to the grinding machine control system in real time, failing to form an automated cycle of "measurement → compensation → processing," leaving the inspection and processing stages disconnected. Furthermore, the operating status, alarms, capacity, and inspection data of the grinding machine, inspection machine, and related auxiliary equipment are scattered across various independent systems, lacking a unified aggregation and analysis platform, leading to difficulties in quality traceability and lagging statistics on overall equipment efficiency. Traditional manual or semi-automatic compensation mechanisms also suffer from response delays, making it difficult to meet the accuracy requirements of compensation actuators for high-precision machining of ultra-fine nano-hard alloy bars.

[0004] In summary, there is currently no existing technology that can organically integrate online high-precision detection, real-time data processing, automatic compensation execution, and multi-dimensional data acquisition and traceability into an automatic compensation scheme for fine grinding. There is an urgent need for an automatic compensation system and method that can achieve high precision, low latency, and a fully closed loop without human intervention, so as to simultaneously meet the requirements of precision, cycle time, and traceability in fine grinding. Summary of the Invention

[0005] The purpose of this invention is to provide an automatic compensation system and method for fine grinding of ultra-fine bars based on real-time detection feedback. This invention solves at least one of the following technical problems in existing fine grinding processes: slow response and poor accuracy consistency due to reliance on manual compensation; separation of detection and processing, resulting in the inability to form an automated closed loop; scattered data from various devices leading to difficulties in quality traceability and OEE statistical lag; and response delay of traditional compensation mechanisms, making it difficult to meet the requirements of high-precision processing.

[0006] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: In a first aspect, the present invention provides an automatic compensation method for fine grinding of ultrafine bars based on real-time detection feedback, comprising the following steps: Online detection data acquisition is achieved by using a laser diameter gauge installed at the rear end of the fine grinding mill discharge port to perform real-time online detection on the ultrafine bars after fine grinding at a preset sampling frequency, thereby acquiring diameter detection data. Data processing and deviation calculation: The edge computing module performs sliding window analysis on N consecutive sets of the detection data and calculates the average deviation between the actual diameter and the target diameter of the ultra-fine rod within the current window. Intelligent decision-making for compensation amount: The edge computing module compares the average deviation with a preset deviation threshold: if the average deviation does not exceed the deviation threshold, compensation is not triggered and the system continues steady-state processing; if the average deviation exceeds the deviation threshold, the required compensation displacement information is calculated based on the average deviation and the grinding wheel wear model, and a compensation instruction containing the compensation displacement information is generated. The servo compensation is executed automatically. The PLC central control module receives the compensation command and drives the servo motor of the automatic compensation execution device to rotate. Through the transmission mechanism, it pushes the grinding wheel frame to move slightly to adjust the feed amount of the grinding wheel. The compensation effect is verified and iterated. After the automatic compensation execution device is activated, the laser diameter measuring instrument continues to measure the diameter of the subsequent ultra-fine rods. The edge calculation module performs sliding window analysis again to verify the compensation effect: if the average deviation of the current window returns to the deviation threshold, the compensation is deemed effective and the compensation process is exited; if the average deviation of the current window still exceeds the deviation threshold, the iterative compensation mode is entered, and compensation is performed again based on the residual deviation value until the deviation converges or the iteration termination condition is reached.

[0007] Furthermore, the edge computing module completes all data processing and compensation decision calculations locally; the latency of uploading the detection data from the laser diameter measuring instrument to the edge computing module is ≤10ms; the local calculation time for the edge computing module to perform sliding window analysis is ≤150ms; and the response latency of the PLC central control module from receiving the compensation command to driving the execution of the equipment is ≤40ms. The total latency of the three is ≤200ms, so as to eliminate the impact of cloud communication latency on the compensation response speed and ensure the cycle time of precision grinding.

[0008] Furthermore, the detection accuracy of the laser diameter measuring instrument is ±0.5μm; the deviation threshold is ±1μm, and the absolute value of the deviation threshold is less than the absolute value of the tolerance range; when the PLC central control module drives the automatic compensation execution device to operate, it controls the servo motor to push the grinding wheel frame for micro-feeding through the ball screw, and the positioning accuracy of the automatic compensation execution device is ≤0.5μm, and the minimum compensation step size is 0.1μm.

[0009] Furthermore, it also includes an anomaly determination step: when the average deviation still exceeds the deviation threshold after a predetermined number of consecutive compensation operations, the edge computing module triggers an alarm signal, and the PLC central control module controls the upstream equipment to suspend material feeding according to the alarm signal, and displays a fault prompt on the visualization dashboard.

[0010] Furthermore, it also includes a full-element data uploading step: the edge computing module automatically uploads multi-dimensional data from the processing to the monitoring system to achieve full-process traceability and visualized control of equipment.

[0011] Furthermore, the edge computing module uploads multi-dimensional data from the processing process to the monitoring system in real time. Specifically, the edge computing module uploads equipment status, alarm information, production capacity data, compensation records, and quality data from the processing process to the MES / SCADA system in real time to achieve full-process quality traceability and visualized control of equipment OEE.

[0012] Secondly, the present invention also provides an automatic compensation system for fine grinding of ultrafine bars based on real-time detection feedback, used to implement the method described in any of the above claims, the system comprising: An online inspection device, located at the rear end of the discharge port of a fine grinding mill, includes a laser diameter gauge and a photoelectric trigger sensor. The laser diameter gauge is used to perform real-time online inspection of the ultrafine bars after fine grinding and generate diameter detection data. The photoelectric trigger sensor is used to detect the bar's arrival and trigger the laser diameter gauge to start the inspection. An automatic compensation execution device, integrated into a grinding machine, includes a servo motor, a transmission mechanism, and a grinding wheel head; the servo motor is connected to the grinding wheel head through the transmission mechanism, and is used to receive compensation commands and drive the grinding wheel head to make micro-movements to adjust the feed rate of the grinding wheel of the grinding machine; The edge computing module is communicatively connected to the online detection device and the automatic compensation execution device, respectively. It is used to perform sliding window analysis on the diameter detection data, calculate the average deviation between the actual diameter and the target diameter of the ultra-fine bar in the current window, compare the average deviation with a preset deviation threshold to determine whether compensation is triggered, and when compensation is determined to be required, calculate the required compensation displacement based on the average deviation and the grinding wheel wear model, and generate a compensation instruction containing the compensation displacement information. The PLC central control module is communicatively connected to the edge computing module and the servo motor, respectively, and is used to receive the compensation command and drive the servo motor to rotate.

[0013] Furthermore, the online testing equipment also includes a sampling and cleaning mechanism, which is used to clean and dry the ultrafine rods entering the testing station.

[0014] Furthermore, the online inspection device is rigidly connected to the discharge end of the precision grinding mill via a high-strength aluminum alloy fixing bracket, the detection head of the laser diameter measuring instrument is aligned with the bar processing surface, and the fixing bracket ensures that the coaxiality between the online inspection device and the discharge end of the precision grinding mill is ≤0.01mm.

[0015] Furthermore, it also includes a visualization dashboard module, which is communicatively connected to the edge computing module and used to display processing dimension trend charts, compensation value records, and equipment OEE data in real time.

[0016] Compared with the prior art, the present invention has at least the following beneficial effects: This invention provides an automatic compensation system and method for fine grinding of ultra-fine bars based on real-time detection feedback. The system acquires the diameter detection data of the finely ground bars in real time through online detection equipment. The edge computing module performs sliding window average deviation analysis on multiple sets of continuous detection data and compares it with a preset deviation threshold. When the deviation exceeds the tolerance, the system calculates the compensation displacement in combination with the grinding wheel wear model and automatically executes the compensation by a servo motor driven by a PLC. The system then forms a complete closed loop through detection verification and iterative compensation, effectively eliminating the subjectivity and uncertainty of manual compensation and realizing fully automatic high-precision dimensional compensation without human intervention.

[0017] At the same time, all data processing and decision-making operations are performed locally on the edge computing module, avoiding the uncertain communication delays caused by uploading data to the cloud. This ensures that the total end-to-end latency from detection to compensation execution is controllable within 200ms, matching the 3-second cycle time requirement for fine grinding. This prevents the compensation response speed from becoming a bottleneck in the production line, maintaining high production efficiency while ensuring micron-level processing accuracy.

[0018] Furthermore, this invention uses an edge computing module to upload equipment status, alarm information, production capacity data, compensation records, and quality data to the MES / SCADA system in real time, solving the data silo problem caused by the dispersion of data among various equipment in traditional fine grinding workshops. This provides complete data chain support for batch quality traceability, equipment overall efficiency (OEE) statistics, and process optimization.

[0019] Meanwhile, by setting up an anomaly detection mechanism, an alarm is triggered and the upstream equipment is stopped from feeding when the average deviation still exceeds the deviation threshold after a predetermined number of consecutive compensation operations, effectively preventing the generation of batch defective products. The detection accuracy, deviation threshold, and execution positioning accuracy are matched with each other to ensure that the accuracy of each link in the closed-loop control link is coordinated, and together they ensure that the dimensional accuracy of the finely ground bar is stably controlled within the micron range. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the overall architecture of the automatic compensation system provided in this embodiment; Figure 2 This is a schematic diagram of the display interface of the visual dashboard in the automatic compensation system provided in this embodiment; Figure 3 This is a schematic diagram of the belt docking structure in the automatic compensation system provided in this embodiment; Figure 4 This is a schematic diagram of the structure of the online detection device in the automatic compensation system provided in this embodiment; Figure 5 This is a schematic diagram of the structure of the three-axis sampling mechanism in the automatic compensation system provided in this embodiment; Figure 6 This is a schematic diagram of the structure of the high-precision laser diameter measuring instrument in the automatic compensation system provided in this embodiment.

[0022] Figure label: 1-Online testing equipment; 2-Grinding machine output line; 3-Automatic compensation execution equipment - fine grinding machine; 4-Semi-fine grinding machine. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0025] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0026] I. Examples This embodiment provides an automatic compensation method for the fine grinding of ultrafine bars based on real-time detection feedback. Please refer to... Figure 1-2As shown, the process includes the following steps: Online detection data acquisition: A laser diameter gauge located at the rear end of the fine grinding mill discharge port is used to perform real-time online detection on the ultra-fine bars after fine grinding at a preset sampling frequency to obtain diameter detection data. Data processing and deviation calculation: The edge computing module (such as an edge computing gateway) performs sliding window analysis on N consecutive sets of detection data to calculate the average deviation between the actual diameter and the target diameter of the bar within the current window. Intelligent decision-making for compensation amount: The edge computing module compares the average deviation with a preset deviation threshold. If it does not exceed the threshold, compensation is not triggered, and the system continues steady-state processing; if it exceeds the threshold, the required compensation displacement is calculated based on the average deviation and the grinding wheel wear model, and a compensation command containing this displacement is generated. Automatic execution of servo compensation: The PLC central control module receives the compensation command and drives the servo motor to push the grinding wheel frame through the transmission mechanism to adjust the feed amount of the grinding wheel. Compensation effect verification and iteration: After compensation is executed, the online detection equipment continues to measure the diameter. The edge computing module performs sliding window analysis again. If the average deviation of the window returns to the deviation threshold, it is deemed effective and exits; if it still exceeds the threshold, iterative compensation is initiated, and the process is repeated based on the residual deviation until convergence or the termination condition is met (such as the number of iterations reaching a predetermined number). This method achieves fully automatic high-precision dimensional compensation without manual intervention during the fine grinding process through a closed-loop chain of "detection, calculation, decision-making, execution, verification, and iteration." It solves the problems of slow response and poor consistency in traditional manual compensation. At the same time, through sliding window average deviation analysis and local edge computing, single-point detection noise is effectively filtered out, ensuring the statistical reliability of the compensation decision.

[0027] In this embodiment, the edge computing module completes all data processing and compensation decision calculations locally. The latency of uploading laser diameter gauge detection data to the edge computing module is ≤10ms, the local calculation time for sliding window analysis is ≤150ms, and the response latency of the PLC receiving compensation commands to drive the execution of equipment actions is ≤40ms, with a total latency of ≤200ms. By placing all data processing and decision calculations locally in the edge computing module, the uncertain communication latency caused by data uploading to the cloud is avoided, ensuring that the total end-to-end latency from detection to compensation execution is controllable within 200ms, matching the 3-second cycle time requirement for fine grinding, and ensuring that the compensation response speed does not become a bottleneck in the production line.

[0028] In this embodiment, the laser diameter gauge has a detection accuracy of ±0.5μm; the preset deviation threshold is ±1μm (i.e., twice the detection accuracy margin) to avoid false triggering of compensation due to detection noise; the PLC controls the servo motor to drive the grinding wheel frame for micro-feeding via a ball screw, automatically compensating for the positioning accuracy of the execution device to ≤0.5μm, with a minimum compensation step size of 0.1μm. The detection accuracy, trigger threshold, and execution accuracy are matched to ensure that the accuracy of each link in the closed-loop control chain is matched, avoiding overall compensation failure due to insufficient accuracy in any link. This is the hardware and parameter coordination guarantee for achieving ±0.5μm level dimensional compensation accuracy.

[0029] In this embodiment, an anomaly detection step is also included: when the average deviation still exceeds a preset deviation threshold after a predetermined number of consecutive compensation operations, the edge computing module triggers an alarm signal, and the PLC central control module controls the upstream equipment to suspend material feeding based on the alarm signal, and displays a fault prompt on the visual dashboard. This anomaly detection mechanism proactively intervenes when iterative compensation fails to converge the deviation, suspending material feeding to prevent the generation of batch defective products, and simultaneously prompting operators with fault information through the visual dashboard, thus realizing the fault self-diagnosis and safety protection function at the end of the closed-loop control link.

[0030] This embodiment also includes a full-element data upload step: the edge computing module automatically uploads multi-dimensional data from the processing to the monitoring system to achieve full-process traceability and visualized equipment control. This full-element data upload step automatically uploads multi-dimensional data to the monitoring system through the edge computing module, enabling full-process traceability and visualized equipment control.

[0031] In this embodiment, the edge computing module uploads equipment status, alarm information, production capacity data, compensation records, and quality data during the processing to the MES / SCADA system in real time, enabling end-to-end quality traceability and visualized OEE (Overall Equipment Effectiveness) management of equipment. By unifying multi-dimensional data on equipment, alarms, production capacity, compensation, and quality into the MES / SCADA system, the problem of data silos among various equipment in traditional fine grinding workshops is solved, providing complete data chain support for batch quality traceability, OEE statistics, and process optimization.

[0032] This embodiment also provides an automatic compensation system for the fine grinding of ultrafine bars based on real-time detection feedback. Please refer to [link / reference]. Figure 1-6As shown, the system is used to implement the method described in any of the above-mentioned embodiments, including: an online detection device (located at the rear end of the discharge port of the fine grinding mill, including a laser diameter gauge and a photoelectric trigger sensor, used to detect and generate diameter data); an automatic compensation execution device (integrated into the grinding machine, including a servo motor, transmission mechanism and grinding wheel head, used to receive instructions and drive the grinding wheel head to move micro-motion); an edge computing module (communicating with the online detection device and the compensation execution device respectively, used for sliding window analysis, deviation calculation, compensation determination and compensation amount calculation and to generate instructions); and a PLC central control module (communicating with the edge computing module and the servo motor respectively, used to receive instructions and drive the servo motor to rotate). The various modules of the system are deeply integrated through industrial Ethernet to form a real-time control link of "detection, calculation, compensation, and verification". Each hardware module corresponds to the execution subject of each step of the method, constituting the hardware platform support for the implementation of the method of this invention.

[0033] In this embodiment, the online inspection equipment also includes a sampling and cleaning mechanism for cleaning and drying the ultra-fine bars entering the inspection station. By cleaning and drying the bars before inspection, impurities such as coolant and dust adhering to the surface of the bars after fine grinding are removed, ensuring that the measuring beam of the laser diameter gauge can accurately irradiate the surface of the bar substrate, avoiding measurement deviations caused by surface contaminants, thereby ensuring the authenticity of the inspection data and the accuracy of compensation decisions.

[0034] In this embodiment, the online inspection device is rigidly connected to the discharge end of the precision grinding mill via a high-strength aluminum alloy mounting bracket. The detection head of the laser diameter gauge is aligned with the processed surface of the bar. This mounting bracket ensures that the coaxiality between the online inspection device and the discharge end of the precision grinding mill is ≤0.01mm. By rigidly fixing the device with a high-strength aluminum alloy bracket and strictly controlling the coaxiality to within 0.01mm, vibrations generated during the operation of the precision grinding mill are effectively prevented from being transmitted to the inspection device, thus avoiding measurement jitter. Simultaneously, it ensures that the bar can pass through the laser diameter gauge's inspection area with a stable spatial posture after discharge, providing a mechanical structural guarantee for achieving a ±0.5μm level inspection accuracy.

[0035] This embodiment also includes a visualization dashboard module, which is communicatively connected to the edge computing module. This module displays real-time processing dimension trend charts, compensation value records, and equipment OEE data. The visualization dashboard module connects to the edge computing module via an industrial Ethernet network, presenting the dimensional change trends, compensation operation history, and overall equipment efficiency in a graphical format in real time. This allows operators and managers to intuitively grasp the production line's operating status, providing a visual interactive interface for on-site monitoring and process management.

[0036] II. Specific Implementation 1. Core System Components This system mainly consists of the following five core modules: A. Main equipment (two sets): Online inspection equipment: Located at the rear end of the discharge port of the fine grinding mill, it includes a sampling and cleaning mechanism, a high-precision laser diameter gauge, and a photoelectric trigger sensor.

[0037] Automatic compensation execution equipment (high-precision grinding machine): integrates servo motor, fine adjustment mechanism and docking conveyor belt, responsible for the fine grinding of bar stock and automatic fine adjustment of grinding wheel feed.

[0038] B. Control Modules (Three Sets): Edge computing module: Industrial-grade edge computing gateway (IPC) with built-in data acquisition and processing software, connecting to PLC, detection module and grinding machine CNC control via TCP / IP Modbus, OPC UA and other protocols.

[0039] PLC Central Control Module: An industrial PLC with a network port, responsible for receiving compensation instructions from the edge computing module, driving the servo execution module to perform actions, and coordinating the interlocking logic of upstream and downstream equipment (such as loading and unloading, conveyor lines).

[0040] Visual dashboard module: Industrial touch screen + workshop LED screen, which displays processing dimension trend charts, compensation value records, equipment OEE, etc. in real time.

[0041] 2. Connection relationship of each component Mechanical connection: The online inspection equipment is connected to the automatic compensation actuator via a fixed bracket and a conveyor belt. The inspection head is aligned with the bar stock's machining surface; the automatic compensation actuator is coaxially connected to the end of the feed screw of the grinding wheel head of the grinding machine via a coupling.

[0042] Electrical / communication connections: Edge computing gateway (network port) → switch (TCP / IP) → PLC (Ethernet port).

[0043] The RS485 / Ethernet interface of the laser diameter measuring instrument is connected to the edge computing gateway (COM port).

[0044] PLC (high-speed pulse / bus interface) → servo driver → automatically compensated servo motor.

[0045] The edge computing gateway also connects to the factory backbone network via Ethernet to interact with the MES server, SCADA screen, and LED display board.

[0046] 3. Working principle The system operates automatically according to a closed-loop process of "start processing → continuous monitoring → data calculation → judgment and compensation → adjustment → re-inspection and verification". Bar conveying and processing: After semi-fine grinding and fine grinding, the bars enter the online inspection station, where PLC controls sampling, cleaning and sending to the laser diameter measuring instrument.

[0047] High-speed online detection: The laser diameter gauge measures diameters in real time at a sampling rate of 1000 times / second, and the data is uploaded to the edge computing gateway in real time.

[0048] Data processing and deviation calculation: The gateway performs sliding window analysis on N consecutive sets of data to calculate the deviation between the actual diameter and the target value.

[0049] Intelligent decision-making for compensation amount: No compensation is given if the deviation is within the deviation threshold; if the deviation exceeds the tolerance, the compensation displacement is automatically calculated and sent to the PLC based on the grinding wheel wear model.

[0050] Servo automatic compensation execution: The PLC drives the servo motor to rotate, which in turn drives the grinding wheel frame to move micro-motion through the ball screw, precisely adjusting the cutting position.

[0051] Compensation verification and data archiving: After compensation, the effect is continuously monitored and verified, and compensation is iterated as necessary; all data is automatically uploaded to MES for archiving and traceability.

[0052] Abnormal linkage alarm: If the error still exceeds the tolerance after 3 consecutive compensations, the system will trigger an alarm, suspend material feeding, and display the fault on the large screen to avoid batch defects.

[0053] 4. Detection, execution accuracy and constraints The laser diameter measuring instrument in this system has a detection accuracy of ±0.5μm. The direct constraint compensation algorithm parameters and servo resolution are as follows: ① Compensation algorithm: The trigger threshold is set to ±1μm (2 times the detection accuracy margin), and the minimum compensation step size is 0.1μm to avoid noise-induced false compensation; ② Servo selection: The required positioning accuracy is ≤0.5μm. A servo motor + ball screw (resolution 0.1μm) is selected to ensure that "detection can distinguish and execution can be in place". Conclusion: A detection accuracy of ±0.5μm is a prerequisite for achieving compensation accuracy, and only when these three factors are matched can an effective closed loop be formed.

[0054] 5. The impact of data processing timeliness on compensation response speed Edge computing local processing: detection → gateway (≤10ms) → local calculation (≤150ms) → PLC execution (≤40ms), with a total latency of ≤200ms, eliminating cloud communication latency and ensuring detection cycle time.

[0055] 6. Data collection and interaction based on MES requirements The dimensions and frequency of data collection are directly determined by the OEE calculation and quality traceability requirements of MES / SCADA: ①OEE requirement: The equipment status starts processing and producing materials, triggering the collection of information; ② Inspection requirements: MES judges incoming materials, PLC captures and interprets material information, and performs inspection; ③ Start detection: Determine the size, calculate locally, and send to the cloud, MES, Kanban, etc.; ④ Data integration: Data storage and archiving.

[0056] 7. Advantages in structure and function (1) Structural advantages Modular integrated design: Each core component adopts an independent modular structure, and the detection module and data acquisition terminal can be quickly disassembled and assembled to adapt to different models of precision grinding machines; the edge computing platform adopts an embedded integrated design, which is small in size, easy to install, and does not occupy extra space on the production line; Rigid coaxial docking structure: The online detection module is rigidly fixed by a high-strength aluminum alloy bracket, with a coaxiality of ≤0.01mm with the output end of the grinding machine, avoiding vibration interference during the detection process and ensuring the stability of detection accuracy; Industrial-grade protective structure: All outdoor / workshop components are IP65 protected, dustproof, oilproof, and coolant erosion-proof. The internal water tank is designed to clean and dry the products, making it suitable for the harsh working conditions of the fine grinding workshop with high dust and humidity. It has a long service life and is easy to maintain.

[0057] (2) Functional advantages High-precision dynamic compensation: Achieves 200ms-level fast response compensation, stabilizes the dimensional accuracy of finely ground bars within ±0.5μm, roundness accuracy ≤1μm, and improves the yield rate to over 99%; Full-dimensional data collection: covering 20+ key parameters across three dimensions: equipment, quality, and production; data collection frequency ≥100Hz; no data omissions or delays; achieving "transparency" in the processing process. Intelligent prediction and closed-loop control: The built-in intelligent algorithm model can predict the accuracy drift caused by grinding wheel wear and equipment thermal deformation, and intervene in advance to compensate and avoid batch quality problems; forming a complete closed loop of "processing-inspection-analysis-compensation-traceability"; High compatibility and integration: Compatible with φ4 / φ6 specifications and 40-80mm length of ultra-fine nano cemented carbide rods, suitable for parallel operation of multiple precision grinding machines; supports industrial protocols such as TCP / IP and OPC UA, seamlessly connects to MES, SCADA and AGV scheduling systems, and has no data exchange barriers; Low-cost maintenance and rapid calibration: The detection module supports rapid laser calibration, with a single module calibration time of ≤5 minutes; the data acquisition terminal adopts a maintenance-free design, and the core sensor has a service life of ≥18 months, reducing subsequent maintenance costs.

[0058] 8. Optimal working condition: Applicable products: Continuous production of ultra-fine nano-hard alloy precision grinding rods with diameters of φ4.00±0.002mm and φ6.00±0.002mm.

[0059] Equipment operating conditions: The grinding wheel of the grinding machine is in a stable wear stage (cumulative processing of 2000–8000 pieces).

[0060] Environmental conditions: ambient temperature 20±1℃, air source pressure 0.5MPa±5%, to reduce thermal deformation and ensure stable testing.

[0061] Compensation effect: Simulating a deviation of -0.005mm, the system triggers compensation after detecting 3 items, and recovers to -0.0001mm in 2 iterations (about 9 seconds), with a response speed more than 10 times that of manual operation.

[0062] Continuous operation: Approximately 86,400 pieces are produced continuously in 72 hours, with 23 automatic compensations, zero false alarms, no batch scrap, and zero downtime due to size issues.

[0063] 9. Relevant experimental data: (1) Compensation accuracy verification: After 72 hours of continuous processing of φ6×50mm bars, 1000 bars were randomly sampled and inspected. The dimensional accuracy of all bars was stable within ±0.5μm, with no out-of-tolerance products. The accuracy was improved by 60% compared with manual compensation. (2) Compensation response speed verification: under simulated working conditions such as grinding wheel wear and temperature fluctuation, the compensation response time is stable at ≤200ms and the deviation correction rate is 100%; (3) Data acquisition stability verification: After 30 days of continuous operation, the data acquisition success rate is ≥99.9%, with no data loss or delay, and the parameter acquisition error is ≤0.1%; (4) Continuous operation test: 720 hours of uninterrupted operation without fault shutdown, module failure rate ≤0.5%; (5) Compatibility verification: It is compatible with different models of precision grinding machines and has a 100% success rate in data exchange with MES and AGV scheduling systems.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An automatic compensation method for fine grinding of ultrafine bars based on real-time detection feedback, characterized in that, Includes the following steps: Online detection data acquisition is achieved by using a laser diameter gauge installed at the rear end of the fine grinding mill discharge port to perform real-time online detection on the ultrafine bars after fine grinding at a preset sampling frequency, thereby acquiring diameter detection data. Data processing and deviation calculation: The edge computing module performs sliding window analysis on N consecutive sets of the detection data to calculate the average deviation between the actual diameter and the target diameter of the ultra-fine rod within the current window; Intelligent decision-making for compensation amount: The edge computing module compares the average deviation with a preset deviation threshold: if the average deviation does not exceed the deviation threshold, compensation is not triggered and the system continues steady-state processing; if the average deviation exceeds the deviation threshold, the required compensation displacement information is calculated based on the average deviation and the grinding wheel wear model, and a compensation instruction containing the compensation displacement information is generated. The servo compensation is executed automatically. The PLC central control module receives the compensation command and drives the servo motor of the automatic compensation execution device to rotate. Through the transmission mechanism, it pushes the grinding wheel frame to move slightly to adjust the feed amount of the grinding wheel. The compensation effect is verified and iterated. After the automatic compensation execution device is activated, the laser diameter measuring instrument continues to measure the diameter of the subsequent ultra-fine rods. The edge calculation module performs sliding window analysis again to verify the compensation effect: if the average deviation of the current window returns to the deviation threshold, the compensation is deemed effective and the compensation process is exited; if the average deviation of the current window still exceeds the deviation threshold, the iterative compensation mode is entered, and compensation is performed again based on the residual deviation value until the deviation converges or the iteration termination condition is reached.

2. The automatic compensation method for fine grinding of ultrafine bars based on real-time detection feedback according to claim 1, characterized in that, The edge computing module completes all data processing and compensation decision calculations locally; the latency of uploading the detection data from the laser diameter measuring instrument to the edge computing module is ≤10ms; the local calculation time for the edge computing module to perform sliding window analysis is ≤150ms; and the response latency of the PLC central control module from receiving compensation instructions to driving the execution of equipment actions is ≤40ms. The total latency of the three is ≤200ms, so as to eliminate the impact of cloud communication latency on compensation response speed and ensure the cycle time of precision grinding.

3. The automatic compensation method for fine grinding of ultrafine bars based on real-time detection feedback according to claim 1, characterized in that, The laser diameter measuring instrument has a detection accuracy of ±0.5μm; the deviation threshold is ±1μm, and the absolute value of the deviation threshold is less than the absolute value of the tolerance range; when the PLC central control module drives the automatic compensation execution device to operate, it controls the servo motor to push the grinding wheel frame through the ball screw for micro-feeding; the positioning accuracy of the automatic compensation execution device is ≤0.5μm, and the minimum compensation step size is 0.1μm.

4. The automatic compensation method for fine grinding of ultrafine bars based on real-time detection feedback according to claim 1, characterized in that, It also includes an anomaly detection step: when the average deviation still exceeds the deviation threshold after a predetermined number of consecutive compensation operations, the edge computing module triggers an alarm signal, and the PLC central control module controls the upstream equipment to suspend feeding according to the alarm signal and displays a fault prompt on the visualization dashboard.

5. The automatic compensation method for fine grinding of ultrafine bars based on real-time detection feedback according to claim 1, characterized in that, It also includes a full-element data upload step: the edge computing module automatically uploads multi-dimensional data during the processing to the monitoring system to achieve full-process traceability and visualized control of equipment.

6. The automatic compensation method for fine grinding of ultrafine bars based on real-time detection feedback according to claim 5, characterized in that, The edge computing module uploads multi-dimensional data from the processing process to the monitoring system in real time. Specifically, the edge computing module uploads equipment status, alarm information, production capacity data, compensation records, and quality data from the processing process to the MES / SCADA system in real time to achieve full-process quality traceability and visualized control of equipment OEE.

7. An automatic compensation system for fine grinding of ultrafine bars based on real-time detection feedback, characterized in that, The system for implementing the method according to any one of claims 1-6, the system comprising: An online inspection device, located at the rear end of the discharge port of a fine grinding mill, includes a laser diameter gauge and a photoelectric trigger sensor. The laser diameter gauge is used to perform real-time online inspection of the ultrafine bars after fine grinding and generate diameter detection data. The photoelectric trigger sensor is used to detect the bar's arrival and trigger the laser diameter gauge to start the inspection. An automatic compensation execution device, integrated into a grinding machine, includes a servo motor, a transmission mechanism, and a grinding wheel head; the servo motor is connected to the grinding wheel head through the transmission mechanism, and is used to receive compensation commands and drive the grinding wheel head to make micro-movements to adjust the feed rate of the grinding wheel of the grinding machine; The edge computing module is communicatively connected to the online detection device and the automatic compensation execution device, respectively. It is used to perform sliding window analysis on the diameter detection data, calculate the average deviation between the actual diameter and the target diameter of the ultra-fine bar in the current window, compare the average deviation with a preset deviation threshold to determine whether compensation is triggered, and when compensation is determined to be required, calculate the required compensation displacement based on the average deviation and the grinding wheel wear model, and generate a compensation instruction containing the compensation displacement information. The PLC central control module is communicatively connected to the edge computing module and the servo motor, respectively, and is used to receive the compensation command and drive the servo motor to rotate.

8. The automatic compensation system for ultrafine bar precision grinding based on real-time detection feedback according to claim 7, characterized in that, The online testing equipment also includes a sampling and cleaning mechanism, which is used to clean and dry the ultrafine rods entering the testing station.

9. The automatic compensation system for ultrafine bar precision grinding based on real-time detection feedback according to claim 7, characterized in that, The online inspection device is rigidly connected to the discharge end of the precision grinding mill via a high-strength aluminum alloy fixed bracket. The detection head of the laser diameter measuring instrument is aligned with the processing surface of the bar. The fixed bracket ensures that the coaxiality between the online inspection device and the discharge end of the precision grinding mill is ≤0.01mm.

10. The automatic compensation system for ultrafine bar precision grinding based on real-time detection feedback according to claim 7, characterized in that, Also includes: The visualization dashboard module is connected to the edge computing module and is used to display the processing dimension trend chart, compensation value records and equipment OEE data in real time.

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