CN-121680267-B - Gear machining forging process control method and system

CN121680267BCN 121680267 BCN121680267 BCN 121680267BCN-121680267-B

Abstract

The application discloses a control method and a control system for a gear machining forging process, and relates to the technical field of gear machining forging process control; the method comprises the steps of detecting local hardness of a workpiece to obtain local hardness distribution data of the workpiece, simulating a cutting process of the workpiece according to the hardness distribution data and initial machining parameters, collecting cutting forces generated by cutting points in the cutting process in real time, adjusting the initial machining parameters according to the cutting forces to generate first machining parameters, cutting the workpiece by the first machining parameters, collecting surface images of the workpiece after cutting, generating finishing parameters of the workpiece after cutting according to the surface images of the workpiece, and finishing the workpiece after cutting by the finishing parameters to ensure that microscopic waves on the surface of the workpiece are eliminated in the finishing process. The application can realize detection of the local hardness of the workpiece, adjust the processing parameters according to the detection result and the cutting force, effectively eliminate microscopic waves on the surface of the workpiece in the cutting and finishing processes, and improve the processing precision and consistency of gears.

Inventors

ZHOU JIANSHE
ZHAO XIAOGUANG
ZHOU JIANLIN
REN TIELIN
ZHAO DONGSHENG

Assignees

浙江鸿程传动机械有限公司

Dates

Publication Date: 20260508
Application Date: 20260211

Claims (8)

1. A method of controlling a gear machining forging process, comprising: detecting the local hardness of the workpiece to obtain local hardness distribution data of the workpiece; simulating a cutting process of the workpiece according to the local hardness distribution data of the workpiece and the initial processing parameters, and collecting cutting forces generated by each cutting point in the cutting process in real time; adjusting the initial machining parameters according to the cutting force of each cutting point to generate first machining parameters, and cutting the workpiece by adopting the first machining parameters; Collecting a workpiece surface image after cutting is completed, and generating finishing parameters after the cutting of the workpiece according to microscopic waves of the workpiece surface in the workpiece surface image; finishing the cut workpiece by adopting finishing parameters to ensure that microscopic waves on the surface of the workpiece are eliminated in the finishing process; the step of simulating the cutting process of the workpiece according to the local hardness distribution data of the workpiece and the initial processing parameters and collecting the cutting force generated by each cutting point in the cutting process in real time further comprises the following steps: Simulating the local conductivity change condition of the machine tool spindle bearing according to the cutting force of each cutting point and a preset machine tool spindle bearing health model, and collecting the local simulated conductivity data of the machine tool spindle bearing in real time; Collecting local conductivity data of a main shaft bearing of a machine tool in real time in the process of cutting a workpiece by adopting a first processing parameter; judging whether early recessive wear exists in a main shaft bearing of the machine tool according to the local simulation conductivity data and the local conductivity data; Under the condition that the spindle bearing of the machine tool has early recessive wear, executing the steps of collecting the surface image of the workpiece after cutting and the subsequent steps; the method further comprises the following steps in the process of cutting the workpiece by adopting the first processing parameters: collecting first microscopic vibration speed data of the cutter blade tip in real time; the method for judging whether the early recessive wear exists in the main shaft bearing of the machine tool according to the local simulation conductivity data and the local conductivity data further comprises the following steps: When early recessive wear exists on a machine tool spindle bearing, simulating micro-vibration conditions generated by the machine tool spindle bearing and a cutter clamping system, and acquiring second micro-vibration speed data of the cutter tip in real time in the simulation process; The step of cutting the workpiece by adopting the first processing parameter further comprises the following steps: quantifying micro-vibration data of the cutter tip according to the first micro-vibration speed data and the second micro-vibration speed data; Predicting first microscopic waves formed on the surface of the workpiece after cutting is completed according to the micro-vibration data; the step of generating finishing parameters after the workpiece cutting is completed according to the microscopic ripples of the surface of the workpiece in the workpiece surface image specifically comprises the following steps: and generating finishing parameters after the workpiece cutting is finished according to the micro-corrugation on the surface of the workpiece in the workpiece surface image and the first micro-corrugation formed on the surface of the workpiece.
2. The method of claim 1, wherein the step of detecting the local hardness of the workpiece to obtain the local hardness distribution data of the workpiece comprises: transmitting ultrasonic signals to the workpiece by adopting an ultrasonic transducer and receiving the ultrasonic signals after penetrating the workpiece; calculating the density and the elastic modulus of different positions inside the workpiece according to the transmitted and received ultrasonic signals; and calculating the hardness of different positions in the workpiece according to the density and the elastic modulus to obtain the local hardness distribution data of the workpiece.
3. The method of claim 1, wherein the step of detecting the local hardness of the workpiece to obtain the local hardness distribution data of the workpiece comprises: Transmitting an aggregate ultrasonic signal to the workpiece by adopting an aggregate ultrasonic transducer and receiving the ultrasonic signal scattered back from the inside of the workpiece; According to the transmitted gathered ultrasonic signals and the scattered ultrasonic signals, calculating the density and distribution data of the nanoscale hard particles in the workpiece to obtain the local hardness distribution data of the workpiece; according to the local hardness distribution data and the initial processing parameters of the workpiece, simulating the cutting process of the workpiece, and collecting the cutting force generated by each cutting point in the cutting process in real time specifically comprises the following steps: And simulating the cutting process of the workpiece according to the density and distribution data of the nanoscale hard particles in the local hardness distribution data of the workpiece, the initial processing parameters and the preset cutter blade tip atomic-level geometric model, and collecting the transient cutting force formed at the collision position of the cutter blade tip atoms and the hard particle atoms in the cutting process in real time to obtain the cutting force generated by each cutting point in the cutting process.
4. The method of claim 3, wherein the step of adjusting the initial machining parameters according to the cutting force of each cutting point to generate the first machining parameters, and cutting the workpiece with the first machining parameters comprises: Calculating the transient impact force, the impact duration and the impact frequency when the cutter blade tip is contacted with the hard particles according to the transient cutting force formed at the collision position of the cutter blade tip atoms and the hard particle atoms; Acquiring a target area, wherein the target area is an area in which the duration time of the transient impact force generated when the cutter blade tip contacts with the hard particles is smaller than the preset time and the impact frequency exceeds the preset frequency, and adjusting parameters of initial processing parameters when the cutter blade tip is used for the target area according to the position, the transient impact force and the impact frequency of the target area to generate first processing parameters, wherein the first processing parameters comprise piezoelectric driving signals of the cutter blade tip when the cutter blade tip is used for the target area; the workpiece is cut using the first processing parameter to inhibit transient impact forces between the tool tip and the hard particles.
5. The gear machining forging process control method according to any one of claims 1 to 4, wherein capturing the image of the surface of the workpiece after cutting is completed specifically comprises: transmitting a linearly polarized laser beam with a set wavelength to the surface of the workpiece after cutting is completed; Collecting P polarized light and S polarized light scattered back from the surface of the workpiece at multiple angles; calculating the intensity ratio and the phase difference of the P polarized light and the S polarized light scattered back by each angle; calculating the density and depth of forming submicron pits and/or scratches on the surface of the workpiece according to the intensity ratio and the phase difference, And generating a workpiece surface image with submicron pits and/or scratches on the surface according to the calculation result.
6. The method of claim 1, further comprising the step of, during cutting of the workpiece using the first machining parameter: collecting bearing rotating speed, bearing geometric parameters and first cutting force of each first cutting point of a machine tool spindle in real time; calculating the local contact pressure and the shear rate of the bearing contact area according to the bearing rotating speed, the bearing geometric parameters and the first cutting force of each first cutting point; When the local contact pressure exceeds a preset pressure value and the shear rate exceeds a preset rate value, simulating the depolymerization, the re-polymerization and the local insulating microgel forming process of the nanoscale polymer in the lubricating oil, and calculating the volume fraction and the insulating characteristic data of the local insulating microgel; according to the volume fraction and the insulation characteristic data and the effective medium theory, calculating to obtain interfered local conductivity data of a machine tool spindle bearing; according to the interfered local conductivity data, calibrating the local conductivity data acquired in the process of cutting the workpiece by adopting the first processing parameters to obtain local conductivity calibration data; And judging whether the machine tool spindle bearing has early hidden wear or not according to the local simulated conductivity data and the local conductivity data, wherein the local conductivity data adopted in the step of judging whether the machine tool spindle bearing has early hidden wear is calibrated local conductivity calibration data.
7. The method for controlling a gear machining forging process according to claim 6, wherein, According to the interfered local conductivity data, calibrating the local conductivity data acquired in the process of cutting the workpiece by adopting the first processing parameter, and further comprising the following steps of: comparing the local conductivity calibration data with a preset health threshold; When the duration time of the local conductivity calibration data exceeding the preset health threshold reaches or exceeds the set time, evaluating the early recessive wear risk level of the main shaft bearing of the machine tool according to the size of the local conductivity calibration data; And generating a machining parameter adjustment strategy according to the early recessive wear risk level and the residual time of the workpiece cutting process, wherein the machining parameter adjustment strategy is used for guiding a system to progressively adjust the first machining parameter in real time in the subsequent process of cutting the workpiece.
8. A gear machining forging process control system for performing the steps of the method of any one of claims 1 to 7, comprising: the detection module is used for detecting the local hardness of the workpiece to obtain local hardness distribution data of the workpiece; The simulation module is used for simulating the cutting process of the workpiece according to the local hardness distribution data of the workpiece and the initial processing parameters, and collecting cutting forces generated by each cutting point in the cutting process in real time; The cutting module is used for adjusting the initial machining parameters according to the cutting force of each cutting point, generating first machining parameters, and cutting the workpiece by adopting the first machining parameters; the generating module is used for acquiring a workpiece surface image after cutting is completed and generating finishing parameters after the cutting of the workpiece according to microscopic waves of the workpiece surface in the workpiece surface image; And the finishing module is used for finishing the cut workpiece by adopting finishing parameters so as to ensure that microscopic waves on the surface of the workpiece are eliminated in the finishing process.

Description

Gear machining forging process control method and system Technical Field The application relates to the technical field of control of gear machining and forging processes, in particular to a control method and a control system of a gear machining and forging process. Background In intelligent gear forging workshops for high-end equipment manufacturing, product quality consistency and production efficiency face hidden challenges. The existing automatic production line depends on cutting parameters (cutting depth, feeding speed, main shaft rotating speed and the like) set based on the average characteristics of materials, and can meet the conventional production, but is difficult to cope with the fine fluctuation of raw materials. Even if the blank hardness is within the specification allowable range, batch differences, alloy composition fluctuations, or heat treatment fine adjustments may still bias its physical properties toward the upper hardness limit. The traditional control system lacks real-time sensing capability, and when the standard parameter processing is continued, the cutting resistance can be obviously increased, and the load exceeding the design value for a long time forms a hidden threat to the machine tool. Excessive cutting resistance can damage the stability of a lubricating oil film of the main shaft bearing, lead to direct contact of metal, accelerate uneven abrasion of rolling bodies and rollaway nest, and further cause high-frequency micro-amplitude irregular vibration. The vibration is difficult to monitor and early warn through the conventional method, but can be transmitted to the cutting edge of the cutter, and microscopic waves which are difficult to detect through the conventional measurement are formed on the surface of the workpiece. These microscopic defects cannot be eliminated in the finish machining link, but may be amplified, and the finish machining uses the rough machining surface as a reference, so that key indexes such as gear tooth profile precision, tooth direction precision, surface roughness and the like fluctuate in batches, and the requirements of high-end equipment on interchangeability and reliability of parts are seriously affected. In view of the above, there is a need in the art for improvements. Disclosure of Invention The application discloses a control method and a control system for a gear machining forging process, and aims to solve the problems that in the prior art, due to the fact that the hardness of raw materials is in an allowable range but fine fluctuation exists, cutting resistance is continuously high, recessive abrasion and irregular micro-vibration of a machine tool spindle bearing are caused, microscopic waves which are difficult to perceive are formed on the surface of a gear machining finally, the waves are reserved and even amplified in subsequent finish machining, and the accuracy consistency of a final gear product is obviously reduced. The technical scheme of the application is as follows: in a first aspect, the application discloses a gear machining forging process control method, comprising the steps of: detecting the local hardness of the workpiece to obtain local hardness distribution data of the workpiece; simulating a cutting process of the workpiece according to the local hardness distribution data of the workpiece and the initial processing parameters, and collecting cutting forces generated by each cutting point in the cutting process in real time; adjusting the initial machining parameters according to the cutting force of each cutting point to generate first machining parameters, and cutting the workpiece by adopting the first machining parameters; Collecting a workpiece surface image after cutting is completed, and generating finishing parameters after the cutting of the workpiece according to microscopic waves of the workpiece surface in the workpiece surface image; and (3) carrying out finish machining on the cut workpiece by adopting the finish machining parameters so as to ensure that microscopic waves on the surface of the workpiece are eliminated in the finish machining process. According to the technical scheme, the method and the device can detect the local hardness of the workpiece, and adjust the processing parameters according to the detection result and the cutting force, so that the surface quality of the workpiece is effectively controlled in the cutting and finishing processes, microscopic waves are eliminated, the processing precision and consistency of the gear are improved, and the problem that the processing precision is unstable due to the fact that the traditional method cannot cope with the tiny change of raw materials and equipment abrasion is solved. Further, according to the local hardness distribution data of the workpiece and the initial processing parameters, the step of simulating the cutting process of the workpiece and collecting the cutting force generated by each cutting point in the cutting