Roller linear guide pair precision retention evaluation method based on parameterized model
By constructing a multi-physics coupled precision degradation theoretical model and employing parametric simulation analysis, the high cost and low efficiency problems of precision retention assessment for roller linear guide pairs in existing technologies are solved, enabling rapid and accurate precision prediction and optimization decision-making.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING UNIV OF TECH
- Filing Date
- 2026-03-04
- Publication Date
- 2026-06-05
AI Technical Summary
Existing technologies for evaluating the accuracy retention of roller linear guide pairs are costly, time-consuming, and lack systematic parameter influence analysis tools, making it difficult to quickly and accurately predict their long-term accuracy degradation behavior.
A multi-physics coupled accuracy degradation theoretical model is constructed. The influence of different design and operating parameters on the accuracy retention of the guide rail pair is analyzed through parametric simulation. An evaluation method is formed, including model building, parameter setting, simulation analysis and decision support.
It achieves rapid and accurate precision-maintaining prediction, reduces R&D costs, improves prediction accuracy, provides systematic decision support, and is applicable to guideway pair evaluation and optimization throughout the entire life cycle.
Smart Images
Figure CN122154201A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of high-end CNC machine tools and precision equipment manufacturing technology, specifically to a method for evaluating the accuracy retention of roller linear guide pairs. It is particularly suitable for predicting the accuracy degradation behavior of guide pairs during long-term operation in the design and use stages, and making optimization decisions accordingly. Background Technology
[0002] As a core transmission and support component of high-end equipment such as CNC machine tools and machining centers, the precision retention of roller linear guide pairs directly determines the machining accuracy, reliability, and service life of the entire machine. During long-term service, the motion accuracy of the guide pairs will gradually degrade due to various factors such as alternating loads, friction and wear, vibration and impact.
[0003] Currently, research and practice on the accuracy retention of guide rail pairs mainly suffer from the following shortcomings: First, they rely on long-term bench tests or field monitoring to obtain accuracy degradation data, which is costly, time-consuming, and difficult to cover all possible combinations of working conditions; second, existing theoretical models mostly focus on the analysis of single physical processes (such as pure wear or pure deformation), failing to fully couple multiple time-varying and nonlinear effects such as wear, elastic deformation, and creep, resulting in limited prediction accuracy; third, there is a lack of systematic parameter influence analysis tools, making it difficult for designers or users to quickly assess the comprehensive impact of changes in key parameters such as roller size, quantity, material, preload, load, and speed on long-term accuracy retention.
[0004] Therefore, developing a method that can quickly and accurately predict the accuracy degradation trajectory of roller linear guide pairs based on theoretical models and through parametric simulation, and quantitatively evaluate their retention, is of great significance for realizing the proactive design, intelligent selection, and precise maintenance of guide pairs. Summary of the Invention
[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method for evaluating the accuracy retention of roller linear guide pairs based on a parametric model. This method can integrate a multi-physics coupled accuracy degradation theoretical model and, through efficient parametric simulation, quickly reveal the influence of different design parameters and operating conditions on the long-term accuracy behavior of the guide pair, thereby achieving a forward-looking evaluation and optimization guidance for accuracy retention.
[0006] To achieve the above objectives, the present invention adopts the following technical solution:
[0007] A method for evaluating the accuracy retention of roller linear guide pairs based on a parametric model is proposed. Its core lies in constructing a complete technical chain encompassing "model building, parameter setting, simulation analysis, pattern extraction, and decision support." The specific steps are as follows:
[0008] Step 1: Establish a theoretical model for the accuracy degradation of roller linear guide pairs.
[0009] This model is a multiphysics coupled ensemble prediction model, mainly consisting of three sub-modules:
[0010] 1. Elastic Contact Deformation Submodule: Based on Hertz contact theory and Palmgren empirical formula, calculate the normal elastic contact deformation δi between the roller and the raceway under the action of preload and external load.
[0011] 2. Wear Evolution Submodule: Based on Archard's adhesive wear theory and modified by introducing the elastic creep effect, the normal wear depth h of the raceway surface is calculated. The key formula is h = (KA · Q ·μe ·S) / (H · A), where the sliding distance is determined by the elastic creep coefficient μe and the running distance S. KA is the adhesive wear coefficient, Q is the normal contact load, μe is the elastic creep coefficient, S is the running distance, H is the material hardness, and A is the contact area.
[0012] 3. Comprehensive Displacement Output Submodule: Geometrically synthesizes elastic deformation and wear depth to calculate the total displacement δZ and δY of each row of rollers in the Z (vertical) and Y (horizontal) directions, thereby deriving the accuracy errors such as the straightness of the guide pair.
[0013] Step 2: Set up the parameter system required for evaluation.
[0014] The factors affecting accuracy retention are parameterized, forming two types of parameter sets:
[0015] Basic structural parameters: number of rollers n, roller diameter d, roller material hardness H, contact angle α, preload F0, etc.
[0016] Operating parameters: Z-axis working load Fz, Y-axis working load Fy, overturning moment Mx, operating speed v, total operating mileage S, etc.
[0017] Step 3: Perform parametric simulation analysis.
[0018] Based on the model from step 1 and the parameter set from step 2, a simulation experiment was designed and executed. The controlled variable method was employed.
[0019] When performing "load influence analysis", the structural parameters and velocity are fixed, and Fz, Fy, and Mx are changed in a stepwise manner.
[0020] When performing "velocity influence analysis", the structural parameters and loads are fixed, and v is changed in a stepwise manner.
[0021] When performing "structural sensitivity analysis", the operating parameters are fixed, and n, d, H, etc. are changed respectively.
[0022] Each simulation calculates and outputs the evolution curves of δZ, δY, and rotation angle θX from the initial state to the specified running distance S.
[0023] Step 4: Extract the accuracy degradation pattern and establish a mapping relationship.
[0024] Post-processing and analysis of the large amount of simulation data generated in step 3:
[0025] 1. Plot a set of accuracy (e.g., straightness) degradation curves with mileage under different parameter conditions.
[0026] 2. Quantitatively analyze the impact of each parameter on key indicators such as accuracy degradation rate and steady-state error value. For example, determine that for every increase of ΔF in load, the stable straightness error increases by ΔL.
[0027] 3. By using curve fitting, establish an approximate mapping function between key parameters (such as maximum load Pmax, speed v, hardness H) and accuracy life (such as the mileage ST when straightness reaches the threshold T), such as ST = f(Pmax, v, H).
[0028] Step 5: Generate evaluation conclusions and optimization strategies.
[0029] Based on the patterns and mapping relationships established in step 4, the following conclusions can be drawn that can guide practical application:
[0030] Evaluation conclusion: The accuracy retention of a specific guide rail pair under target working conditions is rated (e.g., excellent, good, medium, poor), and its accuracy life is predicted.
[0031] Optimization Strategy: Design Optimization: Recommend the most economical combination of roller diameter, hardness, and quantity to meet the target life requirements; Usage Recommendations: Specify the maximum allowable working load and speed range for different precision requirements.
[0032] Compared with the prior art, the present invention has the following significant advantages:
[0033] Highly efficient and cost-effective: By replacing or reducing a large number of physical experiments through computer simulation, long-term accurate behavior can be predicted quickly during the design phase or before use, significantly shortening the R&D cycle and reducing verification costs.
[0034] The model is more comprehensive and accurate: the established degradation theory model couples elastic deformation, wear and creep, which is more consistent with the actual complex failure physics of the guide rail pair and improves the accuracy of long-term prediction.
[0035] Analysis Systems, Decision Science: Parametric simulation methods can systematically and comprehensively reveal the influence and interaction of multiple parameters, making design optimization and maintenance decisions based on evidence, shifting from "experience-driven" to "model and data-driven".
[0036] Widely applicable and highly adaptable: This method and system can be used not only for performance prediction and scheme comparison in the design phase of new products, but also for condition assessment, remaining life prediction and maintenance plan formulation of in-service machine tool guideways, covering the entire life cycle of application scenarios. Attached Figure Description
[0037] Figure 1 This is an overall flowchart of the evaluation method described in this invention.
[0038] Figure 2 This is a schematic diagram illustrating the calculation principle of the accuracy degradation theoretical model described in this invention.
[0039] Figure 3 The curves show the degradation of the straightness of the guide rail pair with mileage under different load conditions in Example 1.
[0040] Figure 4 The curves showing the degradation of the straightness of the guide rail pair with mileage under different roller diameters in Example 2 are shown.
[0041] Figure 5 The curves show the evolution of the straightness of the guide rail pair with the running mileage under different roller hardness in Example 3. Detailed Implementation
[0042] Figure 1 This is a flowchart of the method of the present invention. To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in detail below. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the present invention.
[0043] Example 1: Analysis of the Influence of Load on Accuracy Retention
[0044] This embodiment demonstrates how to use the method of the present invention to analyze the impact of working load on the accuracy retention of a certain type I roller linear guide pair.
[0045] Step 1 / 2: Establish the accuracy degradation model of this guide rail pair. Set the basic parameters: number of rollers n=30, diameter d=6.5mm, hardness H=630HV, and preload level is medium preload. Set the running speed v=100m / min and the target analysis mileage S=1.1×10^7m.
[0046] Step 3: Define three sets of load conditions for parametric simulation:
[0047] Operating condition A (light load): Fz=155.5kN, Fy=155.5kN, Mx=10.27kN·m
[0048] Operating condition B (medium load): Fz = 205.5 kN, Fy = 205.5 kN, Mx = 12.27 kN·m
[0049] Operating condition C (heavy load): Fz = 255.5 kN, Fy = 255.5 kN, Mx = 14.27 kN·m
[0050] Step 4: Perform the simulation to obtain the following results. Figure 3 The three straightness degradation curves shown are analyzed to show that:
[0051] All curves exhibit a typical pattern of rapid degradation in the initial stage, slowing down in the middle stage, and gradually stabilizing in the later stage.
[0052] The greater the load, the higher the straightness error value throughout the entire process. When S = 1.1 × 10^7 m, the straightness of condition C is about 5.2 μm higher than that of condition A.
[0053] Increased load accelerates the initial degradation rate.
[0054] Step 5: Conclusion and Recommendations. For this type of guide rail, if the straightness error is required to be no more than 15μm after running for 1.1×10^7m, it is recommended that the maximum working load should not exceed operating condition B (Fz=205.5kN, Fy=205.5kN, Mx=12.27kN·m). To extend the high-precision life, light-load operation should be used as much as possible while meeting process requirements.
[0055] Example 2: Analysis of the Influence of Roller Diameter on Precision Retention
[0056] This embodiment analyzes the influence of a key structural parameter—the roller diameter d.
[0057] Step 1 / 2: The model and most parameters are the same as in Example 1, with the fixed load being Condition B (medium load).
[0058] Step 3: Set the roller diameter d to 5.5mm, 6.5mm, and 7.5mm respectively for simulation.
[0059] Step 4: Obtain as follows Figure 4 The straightness degradation curve is shown. Analysis shows that:
[0060] The diameter of the rollers has a significant impact on accuracy retention. The smaller the diameter, the greater the straightness error throughout the entire service life.
[0061] When d=5.5mm, the error is much greater than that of d=6.5mm and 7.5mm, and no obvious stable plateau period is observed, indicating that small-diameter rollers may continue to wear relatively quickly under this load.
[0062] Step 5: Formulate design recommendations. To ensure good accuracy retention, rollers with a diameter of not less than 6.5 mm should be selected under this load condition. Based on the curve trend, the improvement gained from increasing the diameter from 6.5 mm to 7.5 mm (error reduction of approximately 3.5 μm) is less than the gain from increasing from 5.5 mm to 6.5 mm (error reduction of approximately 5 μm). Considering both cost and performance, 6.5 mm is the optimal choice.
[0063] Example 3: Analysis of the Influence of Roller Material Hardness on Precision Retention
[0064] This embodiment analyzes the influence of material hardness H.
[0065] Step 1 / 2: The model and parameters are the same as in Example 1, with the fixed load being condition B and the roller diameter d = 6.5 mm.
[0066] Step 3: Set the equivalent hardness H of the roller to 230HV (low), 630HV (medium), and 1430HV (high) respectively for simulation. Here, hardness mainly affects the material hardness parameter H in the Archard wear formula.
[0067] Step 4: Obtain as follows Figure 5 The Z-axis deformation evolution curve shown (representing wear-dominated deformation) indicates that:
[0068] Material hardness is one of the most effective parameters for inhibiting wear and improving precision retention.
[0069] Increasing the hardness from 230HV to 630HV reduces the stable deformation by approximately 65%; increasing it from 630HV to 1430HV further reduces it by approximately 55%.
[0070] High-hardness materials allow the guide rail pair to enter a stable stage with low wear rate more quickly.
[0071] Step 5: Formulate material selection and process recommendations. For machine tools requiring high precision and long service life, high-quality guideway steel with a hardness of not less than 630HV should be given priority, and the surface hardness of the raceway should be increased as much as possible through appropriate heat treatment processes. Although the cost of high-hardness materials increases, the benefits of extended precision and service life are significant.
Claims
1. A method for evaluating the accuracy retention of roller linear guide pairs based on a parametric model, characterized in that, Includes the following steps: Step 1: Construct a multi-physics coupled accuracy degradation theoretical model; the model includes an elastic contact deformation submodule, a wear evolution submodule, and a comprehensive displacement output submodule; The elastic contact deformation submodule is based on Hertz contact theory and Palmgren empirical formula to calculate the normal elastic contact deformation δi between the roller and the raceway under the action of preload and external load. The wear evolution submodule is based on Archard's adhesive wear theory and incorporates the elastic creep effect for correction. It calculates the normal wear depth h of the raceway surface, which is expressed as h = (KA · Q · μe · S) / (H · A), where the sliding distance is determined by the elastic creep rate μe and the running distance S; KA is the adhesive wear coefficient, Q is the normal contact load, μe is the elastic creep rate, S is the running distance, H is the material hardness, and A is the contact area. The integrated displacement output submodule geometrically synthesizes the elastic deformation and wear depth, calculates the total displacement δZ and δY of each column of rollers in the Z and Y directions, and then derives the straightness error of the guide pair. Step 2: Set up the parameter system; Parameterize the factors that affect accuracy retention to form a set of basic structural parameters and a set of operating condition parameters; The set of basic structural parameters includes at least: number of rollers n, roller diameter d, roller material hardness H, contact angle α, and preload F0; The set of operating condition parameters includes at least: Z-axis working load Fz, Y-axis working load Fy, overturning moment Mx, operating speed v, and total operating mileage S; Step 3: Perform parametric simulation analysis; Based on the accuracy degradation theoretical model and the parameter system, simulation experiments are conducted using the controlled variable method, and load influence analysis, velocity influence analysis and structural sensitivity analysis are performed respectively; When performing load influence analysis, the structural parameters and operating speed are fixed, and Fz, Fy, and Mx are changed in a stepwise manner. When performing velocity effect analysis, the structural parameters and loads are fixed, and v is changed in a stepwise manner; When performing structural sensitivity analysis, the operating parameters are fixed, and n, d, and H are changed respectively; Each simulation calculates and outputs the evolution curves of δZ, δY, and rotation angle θX from the initial state to the specified running mileage S; Step 4: Extract the accuracy degradation law; Process the simulation data, plot a cluster of accuracy degradation curves under different parameter conditions, quantify the influence of each parameter on the accuracy degradation rate and steady-state error value, and establish the mapping function ST = f(Pmax, v, H) between key parameters and accuracy lifetime through curve fitting. Step 5: Generate evaluation conclusions and optimization strategies; Based on the aforementioned accuracy degradation law and mapping function, rate the accuracy retention of specific guide rail pairs under target working conditions and predict their accuracy life; Simultaneously, generate design optimization schemes and usage recommendations. The design optimization schemes are economical combinations of roller diameter, hardness, and quantity that meet the target life requirements, and the usage recommendations are the maximum allowable working load and speed range under different accuracy requirements.
2. The method for evaluating the accuracy retention of roller linear guide pairs based on a parametric model according to claim 1, characterized in that, In the wear evolution submodule of step 1, the elastic creep effect is quantified by the elastic creep rate μe, which is determined by the contact stress distribution and relative sliding velocity field between the roller and the raceway.
3. The method for evaluating the accuracy retention of roller linear guide pairs based on a parametric model according to claim 1, characterized in that, The simulation analysis process in step 3 adopts the controlled variable method, that is, when a single variable changes, the other parameters remain unchanged at the baseline value, so as to isolate the independent influence of each factor on the accuracy degradation.
4. The method for evaluating the accuracy retention of roller linear guide pairs based on a parametric model according to claim 1, characterized in that, In the accuracy-life mapping function ST = f(Pmax, v, H) in step 4, Pmax is the maximum contact stress, v is the operating speed, and H is the material hardness. This function is used to characterize the accuracy retention time under different working conditions and material matching.
5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method for evaluating the accuracy retention of roller linear guide pairs based on a parametric model as described in any one of claims 1 to 4.