A method and system for predicting a grinding metamorphic layer of a raceway of a rolling bearing

Abstract

This disclosure provides a fusion-based method and system for predicting the modified layer of a rolling bearing raceway during grinding, belonging to the field of rolling bearing raceway grinding modified layer prediction. The method includes constructing a virtual system model and collecting the geometric dimensions and material properties of the rolling bearing workpiece to be predicted in physical space; acquiring processing parameters and temperature data affecting the subsurface quality of the raceway during the grinding process; using these parameters and temperature data for real-time data interaction and data analysis processing within the virtual system to obtain simulation results and data analysis results; and inputting the simulation results and data analysis results into a fusion algorithm to predict the modified layer morphology during the bearing raceway grinding process, significantly improving the quality of the rolling bearing raceway.

Description

Technical Field

[0001] This disclosure relates to the field of predicting the modified layer of the raceway grinding of rolling bearings, and specifically to a method and system for predicting the modified layer of the raceway grinding of fusion-type rolling bearings. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] As the working interface of a rolling bearing, the subsurface quality of the raceway directly affects the bearing's service life and performance. During the grinding process of rolling bearing raceways, to meet the stringent usage requirements, high demands are placed on the subsurface quality. Numerous machining parameters, such as grinding wheel linear speed, workpiece rotation speed, and feed rate, all influence this subsurface quality, making it difficult to guarantee the stability of the machined bearing's quality. Therefore, accurate real-time prediction of the bearing raceway subsurface quality is crucial for improving bearing raceway quality.

[0004] Currently, the main method for predicting the grinding modified layer is to make real-time predictions by analyzing data. However, due to differences in the processing of data features and algorithms, the results vary greatly, and there is a drawback of untimely prediction.

[0005] Digital twin technology, as a model reflecting the actual processing state, can predict the product's state during processing in real time, thereby improving product quality. It replicates the physical space within a virtual system, achieving a mapping from the real system to the virtual system. Then, based on the virtual system, it can predict and optimize the processing in the real system. Due to its ability to reflect the real state in real time, digital twin technology can be applied to predicting grinding-induced altered layers. Real-time interaction and prediction can be achieved by establishing a virtual system model within the digital twin. However, due to the differences between the established model and the physical space, biased prediction results may occur.

[0006] In summary, the inventors have found that existing methods for predicting the modified layer of the raceway grinding process in rolling bearings, including those based on data analysis and those based on digital twins, have shortcomings. Summary of the Invention

[0007] To address the aforementioned issues, this disclosure proposes a method and system for predicting the modified layer of the bearing raceway during grinding. Targeting a crucial parameter affecting bearing raceway quality—the modified layer—the method combines digital twin model prediction with data analysis to predict the subsurface quality of the bearing raceway during the grinding process, thereby ensuring consistent bearing raceway quality.

[0008] According to some embodiments, the present disclosure adopts the following technical solutions:

[0009] A method for predicting the modified layer of the raceway grinding in a fusion-type rolling bearing includes:

[0010] A virtual system model based on a digital twin physical space is constructed, and the geometric dimensions and material properties of the rolling bearing workpiece to be predicted in the physical space are collected and input into the virtual system model.

[0011] The processing parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway are obtained. The parameters and temperature data are then used for real-time data interaction and data analysis processing in the virtual system to obtain the simulation results and data analysis results of the virtual system.

[0012] The simulation results and data analysis results of the virtual system are input into the fusion algorithm to predict the microstructure of the modified layer during the grinding process of bearing raceways.

[0013] According to some embodiments, this disclosure also adopts the following technical solutions:

[0014] A fusion-type predictive system for the modified layer of the raceway grinding of rolling bearings, comprising a virtual system and a data analysis system;

[0015] The virtual system includes a physical model consisting of a CAD model and a dynamic contact algorithm, a grinding kinematics model and boundary conditions, used to obtain the processing parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway, and to perform real-time data interaction with the physical space during the processing to obtain simulation results.

[0016] The data analysis system is used for data processing to obtain data analysis results.

[0017] Furthermore, it also includes an infrared thermometer, used to measure the temperature of the subsurface layer of the workpiece during processing, thereby obtaining the morphology of the modified layer.

[0018] Beneficial effects

[0019] Compared with the prior art, the beneficial effects of this disclosure are as follows:

[0020] 1. Based on the altered layer that affects and represents the surface quality of the workpiece, this disclosure comprehensively considers various factors and, based on the fusion algorithm of digital twin and data analysis, realizes the prediction of the microstructure of the altered layer during the grinding process of rolling bearing raceways, which greatly improves the quality of rolling bearing raceways.

[0021] 2. In the prediction of grinding modified layers based on digital twin technology, the virtual system of the digital twin is mapped to the physical space in real time. The data of the virtual system comes from the physical space, which not only ensures timeliness but also ensures the consistency between the virtual system and the physical space, greatly improving the accuracy of digital twin technology.

[0022] 3. In the prediction based on digital twin technology in this disclosure, the modeling software Twin Builder and the modeling language Modelica are used for modeling, which meets the modeling requirements of the virtual system of digital twin technology and ensures the accuracy of the system.

[0023] 4. In the results of the rolling bearing raceway grinding process based on data analysis, the Abaqus software is used to perform finite element analysis of the temperature field during the grinding process to determine the influence of the processing parameters on the temperature, thereby obtaining the influence of the processing parameters on the modified layer. This allows for the prediction of the modified layer during the grinding process. Attached Figure Description

[0024] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0025] Figure 1 This is a system block diagram illustrating the working principle of Embodiment 1 of this disclosure;

[0026] Figure 2 This is a block diagram of a digital twin virtual system according to Embodiment 1 of this disclosure;

[0027] Figure 3 This is a flowchart of the temperature field analysis in Embodiment 1 of this disclosure. Detailed implementation method:

[0028] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0029] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0030] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0031] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0032] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0033] Example 1

[0034] As described in the background section, in the grinding process of rolling bearing raceways, high requirements are placed on the subsurface quality to meet the stringent performance requirements of the bearings. Numerous machining parameters, such as wheel speed, workpiece rotation speed, and feed rate, affect the surface quality, making it difficult to guarantee the stability of the machined bearing quality. Therefore, accurately acquiring the subsurface quality of the bearing raceway in real time is crucial for improving its overall quality. Grinding altered layer prediction methods are mainly divided into two types: models based on digital twin technology and data analysis prediction systems. Both methods have their advantages in predicting grinding altered layers, but they also have shortcomings. Furthermore, there is currently no prediction method based on digital twin models for predicting grinding altered layers in bearing raceways.

[0035] In view of the above, one embodiment of this disclosure provides a method for predicting the modified layer of the raceway grinding in a fusion-type rolling bearing, such as... Figure 1 As shown, it includes the following steps:

[0036] A virtual system model based on a digital twin physical space is constructed, and the geometric dimensions and material properties of the rolling bearing workpiece to be predicted in the physical space are collected and input into the virtual system model.

[0037] The processing parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway are obtained. The parameters and temperature data are then used for real-time data interaction and data analysis processing in the virtual system to obtain the simulation results and data analysis results of the virtual system.

[0038] The simulation results and data analysis results of the virtual system are input into the fusion algorithm to predict the quality of the modified layer during the grinding process of the bearing raceway.

[0039] Specifically, a virtual system is constructed in the digital twin technology. A virtual system model based on the digital twin physical space is built, and the geometric dimensions and material properties of the rolling bearing workpiece to be predicted in the physical space are collected and input into the virtual system model, so that the physical properties of the physical space and the virtual system are the same.

[0040] The machining parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway are obtained. The machining parameters that affect the subsurface quality of the raceway are the grinding wheel linear speed of the machine tool, the workpiece rotation speed, and the feed speed.

[0041] The virtual system includes a physical model, a grinding dynamics model, and boundary conditions of the virtual system.

[0042] Figure 2 As shown, the physical model, grinding kinematic model, and boundary conditions of the rolling bearing raceway grinding process are obtained by establishing CAD models of the workpiece and machine tool and using dynamic contact algorithms, which serve as the basis for constructing a virtual system. Then, the virtual system in digital twin technology is built using the software Twin Builder.

[0043] As one example, the specific process of establishing the CAD model of the workpiece and the machine tool and the dynamic contact algorithm is as follows:

[0044] A 3D model of the grinding work area, including the grinding wheel, workpiece, support, and grinding wheel spindle, is drawn. Its material properties are consistent with those in the solid space. The grinding wheel is regarded as a rigid body and the workpiece is regarded as a soft body. The contact force can be calculated.

[0045] Specifically, a grinding kinematic model can be established by considering the kinematic relationship between the grinding wheel and the workpiece;

[0046] It is necessary to model the behavioral rules in the virtual system, that is, the boundary conditions corresponding to the model, including the grinding wheel linear velocity, workpiece rotation speed and feed rate, so that the motion of the established physical model in the virtual space remains consistent with the real space.

[0047] Furthermore, the parameters and temperature data are used for real-time data interaction and data analysis processing in the virtual system's processing procedure to obtain simulation results and data analysis results of the virtual system.

[0048] Specifically, the physical space provides data for the virtual system and data analysis system in digital twin technology, including workpieces, machine tools and infrared thermometers. The grinding wheel linear speed, workpiece rotation speed and feed speed, as well as the temperature data measured by the infrared thermometer during processing, are transmitted to the digital twin virtual system and data analysis system via Wi-Fi, Bluetooth and other means.

[0049] On one hand, by utilizing the material properties and geometric dimensions of the workpiece, the grinding wheel linear speed of the machine tool, the workpiece rotation speed and feed rate, and the temperature data measured by an infrared thermometer during processing, real-time data interaction and mapping are performed in various models of the virtual system. The virtual system receives processing parameters and temperature data from the physical space in real time, realizing interaction with the physical space, continuously updating the virtual system, and completing the prediction. Simulation results are then obtained.

[0050] On the other hand, the collected processing parameters and temperature information in the physical space are subjected to data analysis and processing. Specifically, the data analysis and processing includes:

[0051] The acquired machining parameters and temperature data affecting the subsurface quality of the raceway in the solid space are processed, input into a data acquisition card, and stored in a database. Signal processing includes setting the sampling frequency, sampling interval, sampling duration, and signal amplification. The entire grinding process is divided into several time periods, and the root mean square value of the grinding temperature data in each time period is calculated as the effective value. After data feature extraction, the data is input into Abaqus for simulation.

[0052] For example, to extract the time-domain features of a data signal, based on the root mean square (RMS) value in the time domain, as shown in the following formula:

[0053]

[0054] The processed data is then input into the Abaqus software.

[0055] like Figure 3 As shown, by inputting the processing parameters into Abaqus software, a finite element simulation of the temperature field during the grinding process can be obtained, thereby enabling the prediction of the modified layer.

[0056] Specifically, the process involves analyzing the microscopic interaction between abrasive grains and workpiece material in the grinding arc zone, determining the heat distribution ratio, establishing a grinding force model and the applied heat flux density, and creating a finite element model of the rolling bearing raceway. By inputting data into the solid space, the grinding temperature field can be calculated, thereby predicting the altered layer. For example, for GCr15 bearing steel, tempering occurs when the grinding temperature exceeds 150℃, forming a dark layer structure. Therefore, after obtaining the grinding temperature field, the thickness of the dark layer can be determined based on the temperature at different depths.

[0057] Furthermore, when a single abrasive grain passes through the grinding arc zone, it goes through three stages: friction, plowing, and cutting. By establishing the relationship between grinding force and abrasive grain diameter and depth of cut based on each stage, a grinding force model can be obtained.

[0058] Furthermore, the proportion of heat generated in the grinding arc zone that is transferred to the workpiece varies, and the distribution of grinding force, total heat flux density, and heat flux density transferred to the workpiece in the grinding arc zone can be obtained based on the heat distribution ratio model.

[0059] Furthermore, by applying the heat flux density of the input workpiece as a moving heat source to the finite element model, the distribution of the grinding temperature field can be calculated. The magnitude and distribution of the heat flux density of the input workpiece depend on the distribution of grinding force and heat distribution ratio within the grinding arc zone;

[0060] Furthermore, the finite element model can be obtained by setting element type, material model, mesh generation, initial and boundary conditions, etc.

[0061] Furthermore, the results output from the digital twin model and the results obtained from data analysis are input into the fusion algorithm to predict the microstructure of the modified layer during the grinding process of the bearing raceway.

[0062] The fusion algorithm uses the UPF algorithm (Uniform Kalman Particle Filter algorithm).

[0063] One embodiment of this disclosure provides a prediction system for the grinding altered layer of a fusion-type rolling bearing raceway, comprising:

[0064] Virtual systems and data analysis systems;

[0065] The virtual system includes a physical model consisting of a CAD model and a dynamic contact algorithm, a grinding kinematics model and boundary conditions, used to obtain the processing parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway, and to perform real-time data interaction with the physical space during the processing to obtain simulation results.

[0066] The data analysis system is used for data processing to obtain data analysis results.

[0067] It also includes an infrared thermometer, used to measure the temperature of the subsurface layer of the workpiece during processing, thereby obtaining the morphology of the modified layer.

[0068] The physical space is configured with workpieces, machine tools, and infrared thermometers to provide data for virtual systems and data analysis systems in digital twin technology;

[0069] It provides the material properties and geometric dimensions of the workpiece, the linear speed of the grinding wheel of the machine tool, the rotational speed of the workpiece and the feed rate, and the infrared thermometer is responsible for measuring the temperature during processing;

[0070] The temperature measured by the infrared measuring instrument is transmitted to the digital twin virtual system and data analysis system via Wi-Fi, Bluetooth and other means;

[0071] The virtual system of digital twin technology is configured as a physical model consisting of a CAD model and a dynamic contact algorithm, combined with a grinding kinematics model and boundary conditions;

[0072] Furthermore, simulation results are obtained from virtual systems built using the modeling software Twin Builder.

[0073] The data analysis system is configured to collect information, process the obtained data, and then input it into the Abaqus software.

[0074] Abaqus software can provide finite element simulations of the temperature field during the grinding process, thereby enabling the prediction of the modified layer.

[0075] Using the above system, the following method steps are specifically implemented:

[0076] A virtual system model based on a digital twin physical space is constructed, and the geometric dimensions and material properties of the rolling bearing workpiece to be predicted in the physical space are collected and input into the virtual system model.

[0077] The processing parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway are obtained. The parameters and temperature data are then used for real-time data interaction and data analysis processing in the virtual system to obtain the simulation results and data analysis results of the virtual system.

[0078] The simulation results and data analysis results of the virtual system are input into the fusion algorithm to predict the microstructure of the modified layer during the grinding process of bearing raceways.

[0079] The above description is merely a preferred embodiment of this disclosure and is not intended to limit this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

[0080] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A method for predicting a grinding damage layer of a raceway of a rolling bearing, characterized in that, include: A virtual system model based on a digital twin physical space is constructed, and the geometric dimensions and material properties of the rolling bearing workpiece to be predicted in the physical space are collected and input into the virtual system model. The processing parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway are obtained. The parameters and temperature data are then used for real-time data interaction and data analysis processing in the virtual system to obtain the simulation results and data analysis results of the virtual system. The data analysis and processing includes: processing the acquired machining parameters and temperature data affecting the subsurface quality of the raceway in the physical space, inputting them into a data acquisition card after signal processing, storing them in a database, extracting data features, and then inputting them into Abaqus for simulation, including: The processing parameters and temperature data are input into Abaqus to analyze the microscopic interaction between the abrasive grains and the workpiece material in the grinding arc zone. A finite element model of the rolling bearing raceway is established, and boundary conditions are set. By determining the heat distribution ratio, establishing the grinding force model, and applying the heat flux density, the grinding temperature field is calculated using the data input from the solid. The thickness of the grinding dark layer is determined based on the temperature at different depths. The simulation results and data analysis results of the virtual system are input into the fusion algorithm to predict the microstructure of the modified layer during the grinding process of bearing raceways.

2. A method of predicting a grinding damage layer of a raceway of a rolling bearing according to claim 1, characterized in that, The machining parameters that affect the subsurface quality of the raceway are the grinding wheel linear speed, workpiece rotation speed, and feed rate of the machine tool.

3. A method of predicting a grinding damage layer of a raceway of a rolling bearing according to claim 1, characterized in that, The virtual system includes a physical model, a grinding dynamics model, and boundary conditions of the virtual system.

4. The method for predicting the modified layer of the raceway grinding in a fusion-type rolling bearing as described in claim 3, characterized in that, By establishing CAD models of the workpiece and machine tool and using dynamic contact algorithms to obtain physical models, the physical models, grinding kinematic models, and boundary conditions of the rolling bearing raceway grinding process are analyzed. A virtual system in digital twin technology is then established using Twin Builder.

5. The method for predicting the modified layer of the raceway grinding in a fusion-type rolling bearing as described in claim 1, characterized in that, Temperature data during processing is obtained using an infrared thermometer.

6. The method for predicting the modified layer of the raceway grinding in a fusion-type rolling bearing as described in claim 1, characterized in that, The fusion algorithm employs the insensitive Kalman particle filter algorithm.

7. A prediction system for the ground modified layer of a fusion-type rolling bearing raceway, specifically implementing the prediction method for the ground modified layer of a fusion-type rolling bearing raceway as described in any one of claims 1-6, characterized in that, Including virtual systems and data analysis systems; The virtual system includes a physical model consisting of a CAD model and a dynamic contact algorithm, a grinding kinematics model and boundary conditions, used to obtain the processing parameters and temperature data that affect the subsurface quality of the raceway during the grinding process of the rolling bearing raceway, and to perform real-time data interaction with the physical space during the processing to obtain simulation results. The data analysis system is used for data processing to obtain data analysis results.

8. The prediction system for the modified layer of the raceway grinding of a fusion-type rolling bearing as described in claim 7, characterized in that, It also includes an infrared thermometer, used to measure the temperature of the subsurface layer of the workpiece during processing, thereby obtaining the morphology of the modified layer.

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