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CN-121973100-A - Piston pin polishing monitoring system

CN121973100ACN 121973100 ACN121973100 ACN 121973100ACN-121973100-A

Abstract

The invention belongs to the technical field of precision machining, and particularly relates to a piston pin polishing monitoring system, which is used for acquiring data such as a temperature field, stress, surface morphology and the like through a multi-dimensional sensing array, correcting thermal deformation deviation through combining a multi-physical field coupling model, constructing a self-adaptive decision frame through deep reinforcement learning DRL, optimizing a polishing strategy through digital twin verification, integrating LIBS material identification and multi-process linkage, realizing rapid adaptation of 12 kinds of materials, balancing real-time control and global optimization based on an edge-cloud collaborative framework, and newly increasing environmental protection safety monitoring to meet the green manufacturing standard. The invention solves the problems of low precision, poor adaptability and high cost of the traditional system, ensures that the surface roughness of the piston pin is less than or equal to 0.8 mu m, improves the qualification rate to 99 percent, and is suitable for mass production of high-precision piston pins.

Inventors

  • CHEN JIAN
  • TAO QUN

Assignees

  • 杭州双象汽车零部件有限公司

Dates

Publication Date
20260505
Application Date
20251229

Claims (10)

  1. 1. The piston pin polishing monitoring system is characterized by comprising a data acquisition module, a data analysis and intelligent decision module, a control execution module, a man-machine interaction module and an edge-cloud cooperation platform, wherein the data acquisition module is used for synchronously acquiring basic parameters, multiple physical field parameters, material characteristic parameters and environment-friendly safety parameters in the polishing process, the data analysis and intelligent decision module fuses acquired data and generates an optimized control strategy, the control execution module drives an execution mechanism according to the strategy, the man-machine interaction module provides a visual operation and intervention interface, and the edge-cloud cooperation platform realizes cooperation of local real-time control and global process optimization.
  2. 2. The piston pin polishing monitoring system according to claim 1, wherein the data acquisition module comprises a basic parameter sensing unit and a multi-physical-field sensing unit, the basic parameter sensing unit comprises a displacement sensor with resolution of 0.01 mu m, a temperature sensor with precision of +/-0.5 ℃ and a vibration sensor with frequency response of 0.5-10kHz, and the multi-physical-field sensing unit comprises an infrared thermal imager with resolution of 640 multiplied by 512, a micro-strain sensor with precision of +/-1 mu epsilon and a laser scanner with precision of +/-0.002 mm and is used for acquiring temperature field distribution, stress strain and three-dimensional point cloud data of a surface.
  3. 3. The piston pin polishing monitoring system according to claim 1, wherein the data acquisition module further comprises a material and process sensing unit, the unit comprises a laser-induced breakdown spectrometer LIBS with a wavelength range of 200-1000nm and a roughness sensor with a measurement range of 0.02-10 mu mRa, the LIBS is used for analyzing the identification accuracy of the element components on the surface of a workpiece to 98%, and the roughness sensor is used for acquiring the roughness data of the machined surface in real time.
  4. 4. The wrist pin polishing monitoring system according to claim 1, wherein the data acquisition module further comprises an environment-friendly safety sensing unit, the environment-friendly safety sensing unit comprises a dust concentration sensor with the accuracy of 0.1mg/m < 3 >, a noise sensor with the measuring range of 30-130dB and a piezoelectric sensor with the accuracy of +/-2%, and the dust and noise sensor are linked to a dust removing device, and the piezoelectric sensor is used for detecting workpiece clamping force.
  5. 5. A wrist pin grinding monitoring system according to claim 1, wherein the data analysis and intelligent decision module comprises a multi-physical field coupling analysis submodule which builds a temperature field-stress field-surface morphology coupling model based on the formula sigma=E× (epsilon+alpha×DeltaT), wherein sigma is stress, E is elastic modulus, epsilon is strain, alpha is thermal expansion coefficient, deltaT is temperature difference, and when the stress exceeds 10% of material yield strength or the temperature gradient is more than 5 ℃ per mm, the automatic correction surface curvature calculation deviation correction quantity is less than or equal to 0.0005mm -1 .
  6. 6. The wrist pin polishing monitoring system according to claim 1, wherein the data analysis and intelligent decision module comprises a reinforcement learning self-adaptive decision sub-module, the sub-module adopts a depth deterministic strategy gradient DDPG algorithm to construct an Actor-Critic network, the surface accuracy standard reaching rate is more than or equal to 99%, the energy consumption reduction rate is more than or equal to 15% and the grinding wheel service life extension rate is more than or equal to 20% are integrated rewarding functions, each time 100 workpieces are processed, strategy iteration is completed, and a new strategy is required to be applied after passing a digital twin virtual environment verification passing rate is more than 95%.
  7. 7. The piston pin polishing monitoring system according to claim 1, wherein the data analysis and intelligent decision module comprises a material identification and process matching sub-module, the sub-module identifies 12 types of piston pin materials containing ceramics and composite materials through LIBS data classification, and invokes a preset process library to realize parameter self-configuration within 1 minute, wherein the process library comprises parameter templates such as a grinding wheel type, polishing force of 0.1-1MPa, rotating speed of 1000-5000r/min and the like.
  8. 8. The piston pin polishing monitoring system according to claim 1, wherein the control execution module comprises a basic parameter adjustment unit and an adaptive execution unit, the basic parameter adjustment unit is used for linking the automatic grinding wheel changing mechanism to change the tool time to be less than or equal to 15 seconds when the grinding wheel wear rate is more than 0.01mm/min, the cooling flow is adjusted to be improved by 30% and the feed speed is reduced by 20% when the temperature is more than 100 ℃, and the adaptive execution unit is used for realizing feed adjustment with the resolution of 0.01 mu m by adopting a piezoelectric controller, and the response time is less than or equal to 20ms.
  9. 9. The wrist pin grinding monitoring system according to claim 1, wherein the control execution module further comprises a multi-process linkage unit for linking the grinding wheel grinder and the ultrasonic polisher at a frequency of 20-40kHz, automatically switching to a polishing process when the real-time roughness Ra is more than 0.4 μm, controlling the process conversion error to be less than or equal to 0.0005mm, and compensating and correcting the deviation through a feed shaft.
  10. 10. The piston pin polishing monitoring system of claim 1, wherein the edge-cloud cooperation platform achieves clock synchronization error of less than or equal to 0.1ms through TSN, an edge node industrial PC is responsible for controlling response time in real time of less than or equal to 20ms, the cloud platform converges 100+ equipment data to optimize global parameters through a federal learning FedAvg algorithm, and a unified feed quantity correction scheme is pushed to +/-0.0005 mm when diameter deviation of batch workpieces is greater than 0.002 mm.

Description

Piston pin polishing monitoring system Technical Field The invention belongs to the technical field of precision machining, and particularly relates to a piston pin polishing monitoring system. Background The piston pin is used as a key force transmission component in the engine, the surface roughness of the piston pin is less than or equal to 0.8 mu m, the dimensional accuracy tolerance is less than or equal to +/-0.001 mm, and the mechanical property directly influences the running efficiency and the service life of the engine. The existing piston pin polishing monitoring technology has the following key defects: 1. Multiple physical field coupling analysis of absence The traditional system only monitors single parameters such as temperature, vibration and the like independently, and does not consider the dynamic coupling relation of the local high temperature of a temperature field reaching 150 ℃ and the contact stress of a stress field reaching 500MPa with the surface morphology in the polishing process, so that the thermal deformation error is more than or equal to 0.002mm or the cracking rate of a workpiece caused by stress overload is as high as 3% -5%. 2. Adaptive strategy curing and generalization ability is weak The suitability of the piston pin for aluminum alloy, ceramic and other different materials is poor depending on a preset threshold value or a fixed algorithm such as PID control, the qualification rate of special material workpieces is only 60% -70%, the parameters cannot be optimized autonomously through process iteration, and the response lag is more than or equal to 100ms when the piston pin is in face of abnormal working conditions such as sudden abrasion of a grinding wheel. 3. Multi-process cooperation and insufficient material recognition Only a single grinding wheel polishing process is covered, the subsequent polishing and honing process is not linked, the process conversion error is more than or equal to 0.001mm, the intelligent material identification mechanism is lacked, the parameters are required to be manually switched, the change time is more than or equal to 30 minutes, and the requirement of a flexible production line is difficult to meet. 4. Cost and synergy imbalance The cost of the high-precision system depends on an imported sensor such as a laser scanner to account for 60%, the manufacturing cost of a single system is more than or equal to 20 ten thousand yuan, and the local closed-loop control is adopted, so that the global optimization of the process parameters of multiple devices cannot be realized, and the consistency deviation of batch processing is more than or equal to 0.003mm. 5. Environment-friendly safety monitoring blank The method does not relate to the environmental protection problems that the dust concentration is often more than 5mg/m < 3 >, the noise is more than or equal to 90dB and the like in the polishing process, and the potential safety hazard caused by the fact that the deviation of the loose power value of workpiece clamping is more than or equal to 20 percent is not met, and the method does not meet the standard requirements of GBZ2.1-2019, ISO12100 and the like. Therefore, there is a need to construct a new generation of wrist pin grinding monitoring system that combines multidimensional sensing, intelligent decision making, flexible adaptation and green safety features. Disclosure of Invention The invention aims to solve the problems of insufficient consideration of the traditional piston pin polishing monitoring system on the multi-physical field coupling effect, weak generalization capability of a self-adaptive strategy, poor multi-process cooperativity, high cost and environmental protection safety deficiency, and provides an intelligent monitoring system which has high precision, high adaptability, low cost and meets environmental protection safety standards. The invention discloses a piston pin polishing monitoring system, which comprises a data acquisition module, a data analysis and intelligent decision module, a control execution module, a man-machine interaction module and an edge-cloud cooperation platform, wherein the modules are cooperated to realize accurate control of the whole piston pin polishing process, and the specific structure is as follows: 1. Data acquisition module The module realizes the comprehensive perception of the polishing process through the multi-dimensional sensing array, and comprises the following steps: Basic parameter sensing unit The displacement sensor adopts a Kernel LK-G80 laser displacement sensor with the resolution of 0.01 mu m and the sampling frequency of 1kHz, is arranged at the tail end of a grinding wheel feeding shaft, monitors the feeding displacement precision of the grinding wheel relative to a piston pin to +/-0.0005 mm in real time, and calculates the polishing depth; The temperature sensor adopts a thermocouple K type, the temperature measurement range is-50-300 ℃, the precision is