True module matching and database optimization method for the design of high-strength silicone oil vibration dampers

Abstract

The present invention discloses a true module matching and database optimization method for the design of high-strength silicone oil shock absorbers, which specifically relates to the field of data processing technology. By combining the structural parameters and application conditions of the shock absorber, a preliminary mechanical simulation system integrating the coupling model is established to form a preliminary true module, and the measured damping data under multiple temperatures and multiple rates are obtained through dynamic loading tests. The advanced parameter optimization algorithm is used for iterative correction to complete high-precision true module matching, and the true module parameters and corresponding damping performance indexes optimized under different design schemes are systematically archived into a database. Through internal data quality evaluation and intelligent optimization of the database, the data reliability and retrieval efficiency are continuously improved, thereby achieving accurate prediction and efficient design of the damping performance of the silicone oil shock absorber under extreme temperature and high-speed working conditions, and greatly improving the consistency, adaptability and engineering application reliability of the shock absorber design.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a true module matching and database optimization method for designing a high-strength silicone oil vibration damper. Background Art

[0002] In the design of high-strength silicone oil vibration dampers, true module matching refers to ensuring that model parameters (such as rheological properties and damping characteristics) are highly consistent with the actual silicone oil behavior through precise measurement and calculation; while database optimization refers to building and continuously improving the material and structural performance database based on a large amount of experimental and simulation data, thereby quickly and accurately supporting the selection and adjustment of vibration damper design schemes, improving design efficiency and performance reliability.

[0003] The existing technology has the following shortcomings:

[0004] Existing design methods for high-strength silicone oil shock absorbers typically address temperature effects (e.g., the Arrhenius viscosity model) and shear rate effects (e.g., the power-law fluid model) separately. In practical applications, such as cold-region railway trains and high-altitude rescue equipment, these two factors produce complex nonlinear coupling during low-temperature, high-speed movement, leading to significant damping response lag or mechanical instability. Existing technologies fail to accurately capture the dual-variable temperature-shear rate coupling characteristics of silicone oil, resulting in significant deviations in design performance under actual operating conditions. Summary of the Invention

[0005] The purpose of the present invention is to provide a true module matching and database optimization method for the design of high-strength silicone oil vibration dampers to address the shortcomings of the background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a true module matching and database optimization method for the design of high-strength silicone oil vibration dampers, comprising:

[0007] Collect rheological properties test data of silicone oil materials at multiple temperature points and multiple shear rate conditions;

[0008] Based on the rheological properties test data, an Arrhenius temperature effect model and a power-law shear rate effect model of silicone oil were constructed respectively, and a cross-coupling correction term was introduced to form a temperature-shear rate dual-variable coupled viscosity model.

[0009] According to the shock absorber structural parameters and application conditions, a preliminary mechanical simulation model is established, and a two-variable coupled viscosity model is integrated into the simulation model to obtain a preliminary true module;

[0010] Conduct dynamic loading tests to obtain measured damping response data of the shock absorber at different temperatures and movement rates;

[0011] Compare the simulated output with the measured output, and use the parameter optimization algorithm to adjust the parameters of the preliminary real module until the error between the simulated output and the measured data under various test conditions meets the preset accuracy requirements, thus completing the real module matching;

[0012] The true module parameters and corresponding damping performance indicators optimized under different design schemes are classified and stored in the database, and the database is optimized according to the internal data quality of the database.

[0013] Preferably, collecting the rheological properties test data of the silicone oil material includes: at multiple set temperature points, including -50°C to 100°C and multiple shear rate ranges including to Under the condition of 400 nm, a rotational rheometer or capillary rheometer is used to perform constant shear rate scanning and constant shear stress scanning tests, and the shear stress and apparent viscosity values ​​are recorded.

[0014] Preferably, constructing a temperature-shear rate dual variable coupled viscosity model includes: fitting the influence of temperature on viscosity based on the Arrhenius equation under fixed shear rate conditions, fitting the influence of shear rate on viscosity based on a power-law fluid model under fixed temperature conditions, and introducing a cross-coupling correction term by analyzing the modulation law of temperature on the power-law model parameters K and n to form a joint function model of viscosity with respect to temperature and shear rate.

[0015] Preferably, establishing a preliminary mechanical simulation model includes:

[0016] Based on the shock absorber's piston diameter, cavity size, damping hole diameter, and silicone oil filling volume parameters, finite element analysis software was used to construct a multi-physics field simulation model including piston motion, throttling channel flow, and temperature field changes, and the dual-variable coupled viscosity model was integrated in the fluid region.

[0017] Preferably, a dynamic loading test is performed: under different set temperature points and different movement rate conditions, a servo-hydraulic fatigue testing machine is used to perform sinusoidal wave, triangular wave or step wave loading, and displacement, velocity, damping force and temperature data are collected synchronously in real time, force-displacement curves and force-velocity curves are drawn, and the equivalent damping coefficient and hysteresis energy loss parameters are extracted.

[0018] Preferably, the parameters in the preliminary true module are adjusted using a parameter optimization algorithm, specifically including:

[0019] Determine the optimization goal to minimize the error between simulation output and measured data;

[0020] Define the objective function, ;in: To simulate the damping force at moment i, is the measured damping force at moment i, W is the number of data points;

[0021] Set the real module parameters to be optimized and define the number of particle swarms; each particle represents a set of real module parameter combinations to be optimized; the initial position of the particle is randomly generated within the allowable range of each parameter; the initial velocity of the particle is also randomly generated;

[0022] Initially set the inertia weight of the particle swarm winit;

[0023] After each iteration, the inertia weight is dynamically adjusted;

[0024] For each iteration: each particle adjusts its speed and position based on its own historical best position and the current best position in the group;

[0025] For each particle, run the simulation model according to its corresponding parameter group; calculate its objective function value as fitness; update the historical optimal position pbesti of each particle; update the global optimal position gbest of the group;

[0026] The stopping condition is that the maximum number of iterations is reached or the error index of the optimal particle is lower than the preset threshold;

[0027] The optimized real module parameters are input into the simulation system to complete the matching of the final simulation and measured data to obtain the final real module.

[0028] Preferably, the database is optimized according to the quality of the internal data of the database, including obtaining the temperature shear response uniformity value: at each test temperature and each shear rate Under the combination, collect the corresponding shock absorber output damping force , all test data are classified and sorted according to different temperature shear points to form a matrix M; for each temperature , calculate the average damping force corresponding to all shear rates, which is recorded as: ; Where m is the number of shear rates;

[0029] For each temperature , calculate the standard deviation of the damping force at all shear rates , the expression is: ; Define the damping force uniformity ratio at each temperature for: ; Average the uniformity ratios at all temperature points to obtain the overall temperature shear response uniformity value UK, which is expressed as: ; where q is the number of temperature points.

[0030] Preferably, obtain the energy dissipation stability index: at different temperatures and each shear rate Under working conditions, collect the energy dissipation value of the single cycle hysteresis loop , get a two-dimensional energy matrix R; all The energy values ​​are arranged into a one-dimensional sequence in the order of testing, denoted as E(k), where k = 1, 2, …, N, and N is the total number of samples. Applying discrete Fourier transform to the energy sequence E(k) yields its frequency domain expression: ; Where: X(f) is the complex amplitude at frequency component f; E(k) is the kth energy sample value; is the Fourier transform kernel function; calculate the energy density of each frequency component: ;in, Represents the energy intensity at frequency f; set a frequency threshold ; Calculate the sum of low-frequency energy separately: ;Summary of high frequency energy: ; Define the energy dissipation stability index is the ratio of low-frequency energy to total energy, and the expression is: .

[0031] Preferably, the temperature shear response uniformity value and the energy dissipation stability index are normalized so that they are both between [0, 1], and the normalized temperature shear response uniformity value and the energy dissipation stability index are weighted averaged and summed to obtain the internal data quality score of the database.

[0032] Preferably, the obtained internal database data quality score value is compared with the preset score threshold. If the internal database data quality score value is greater than or equal to the preset score threshold, it means that the overall data quality between the internal samples of the database is high. At this time, the database can be directly used for shock absorber true module deduction and rapid retrieval without additional optimization processing; if the internal database data quality score value is less than the preset score threshold, it means that there is a sample unevenness problem in the database, and the database needs to be further optimized.

[0033] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0034] 1. This invention significantly improves the ability to accurately describe the rheological behavior of silicone oil materials under extreme environments by introducing multiple temperature and shear rate conditions during the silicone oil rheological property testing phase and constructing a temperature-shear rate dual-variable viscosity model with a cross-coupling correction term. Combining the construction of a preliminary mechanical simulation model, dynamic loading test calibration, and the application of advanced parameter optimization algorithms, a close match between the simulation model and actual damping response data is achieved, resolving the problem of poor adaptability to operating conditions caused by the separate processing of temperature and shear rate in existing technologies. This ensures the reliability and stability of high-strength silicone oil shock absorbers in extreme operating conditions such as cold regions and plateaus.

[0035] 2. This invention systematically organizes optimized true module parameters and corresponding damping performance indicators into a database, introduces the temperature-shear response uniformity value and the energy dissipation stability index as data quality evaluation indicators, and combines normalization processing and weighted scoring methods to achieve intelligent self-optimization of the database. By dynamically evaluating and updating the quality of the database internal data, it not only improves the consistency and representativeness of the samples in the database, but also ensures the reliability of rapid retrieval, accurate deduction, and performance prediction in the subsequent shock absorber design process, significantly improving overall design efficiency and the precision level of engineering applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0037] Figure 1 This is a mind map of the method of the present invention. DETAILED DESCRIPTION

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0039] For examples, see Figure 1 As shown, the true module matching and database optimization method for designing a high-strength silicone oil vibration damper described in this embodiment includes:

[0040] Collect rheological properties test data of silicone oil materials at multiple temperature points and multiple shear rate conditions;

[0041] Based on the rheological properties test data, an Arrhenius temperature effect model and a power-law shear rate effect model of silicone oil were constructed respectively, and a cross-coupling correction term was introduced to form a temperature-shear rate dual-variable coupled viscosity model.

[0042] According to the shock absorber structural parameters and application conditions, a preliminary mechanical simulation model is established, and a two-variable coupled viscosity model is integrated into the simulation model to obtain a preliminary true module;

[0043] Conduct dynamic loading tests to obtain measured damping response data of the shock absorber at different temperatures and movement rates;

[0044] Compare the simulated output with the measured output, and use the parameter optimization algorithm to adjust the parameters of the preliminary real module until the error between the simulated output and the measured data under various test conditions meets the preset accuracy requirements, thus completing the real module matching;

[0045] The true module parameters and corresponding damping performance indicators optimized under different design schemes are classified and stored in the database, and the database is optimized according to the internal data quality of the database.

[0046] Collect rheological performance test data of silicone oil materials at multiple temperature points and multiple shear rate conditions, including:

[0047] Select representative types of high-strength silicone oil to ensure batch consistency;

[0048] The samples need to be sealed and stored to avoid water absorption or contamination, especially before low-temperature testing, they need to be degassed (such as vacuum degassing).

[0049] The temperature points cover the extreme range of possible use of silicone oil, usually set at 8 points: -50°C, -30°C, -10°C, 0°C, 25°C, 50°C, 75°C, and 100°C;

[0050] If silicone oil is suitable for a wider environment (such as aviation, deep sea), the temperature point should be extended to -70°C or above 120°C.

[0051] Shear rates range from very low to very high strain rates and are generally set at 、 ;

[0052] If you need to simulate impact loads, you also need to collect data at higher shear rates (such as ) below.

[0053] Use a high-precision rotational rheometer or capillary rheometer; test modes include constant shear rate sweep and constant shear stress sweep; the temperature control system must ensure that the temperature fluctuation during the sample test is less than ±0.1°C; choose a rotor system that is suitable for the viscosity range of the silicone oil, such as cone-plate, flat plate, or double cylinder.

[0054] Preheat or precool the sample in the rheometer's temperature control system for at least 20 minutes to ensure uniform temperature. Monitor the sample's core temperature in real time and begin testing once the set temperature has been reached.

[0055] At each temperature point, gradually apply the preset shear rate from low to high (or high to low to verify hysteresis); at each shear rate, record the shear stress and corresponding viscosity at equilibrium; ensure that the stability time at each shear rate point is not less than 10 seconds, and collect the average value; for high shear rates, use instantaneous scanning technology to reduce the heat accumulation effect.

[0056] Repeat the test for each temperature-shear combination at least three times and take the average value to reduce accidental errors; check whether the sample undergoes obvious physical changes (such as blistering, delamination, color change, etc.) after the test and exclude abnormal data.

[0057] Record the shear stress (Pa)-shear rate at each temperature point curve; calculate the corresponding apparent viscosity (Pa·s) curve; indicate whether rheological phenomena such as yield stress, shear thinning, and shear thickening are present; if significant viscoelasticity is found (for example, filler particles are added to silicone oil), additional storage modulus (G') and loss modulus (G'') data must be recorded.

[0058] Verify the consistency and trend rationality of shear scan data at different temperatures; if sudden changes or abnormal fluctuations occur, retest and record the cause of the abnormality; perform preliminary fitting on the final data, such as Arrhenius fitting (ln viscosity vs. 1 / temperature) and power law fitting (logarithmic relationship between stress and shear rate), to verify the rationality of the data.

[0059] Based on the rheological properties test data, the Arrhenius temperature effect model and the power-law shear rate effect model of silicone oil were constructed respectively, and the cross-coupling correction term was introduced to form a temperature-shear rate dual-variable coupled viscosity model.

[0060] Collect silicone oil at different temperatures (T) and different shear rates Rheological properties data under shear stress and the value of the apparent viscosity η;

[0061] Under constant shear rate conditions, the viscosity at each temperature point is extracted , and fitting the Arrhenius equation to establish a model for the effect of temperature on viscosity: ;in, is the theoretical reference viscosity, is the rheological activation energy, R is the universal gas constant, and T is the absolute temperature (unit K).

[0062] Under fixed temperature conditions, the viscosity at each shear rate point is extracted , and fitting the power law fluid model, the influence model of shear rate on viscosity is established: ; Where K is the consistency coefficient of the fluid, and n is the flow behavior index (n<1 indicates shear thinning, and n>1 indicates shear thickening).

[0063] The influence trend of temperature change on the power law parameters K and n was analyzed, the modulation relationship of temperature on the power law model parameters was extracted, and the preliminary cross-influence law was obtained;

[0064] Based on the above preliminary model, a two-variable modified viscosity model that introduces temperature-shear rate cross-coupling is constructed in the form of: ; Among them, K and n can be expressed as a function of temperature T, reflecting the dynamic modulation effect of temperature on shear behavior;

[0065] Train the model on all experimental data sets using a global fitting method (e.g., nonlinear least squares fitting) to determine the parameters of the final bivariate model and ensure that the overall fitting error is below a set threshold.

[0066] Verify the fitting accuracy and extrapolation capability, make predictions on test data that are not involved in modeling, and evaluate the applicability of the model under actual engineering conditions. If the error exceeds the allowable range, adjust the coupling correction term.

[0067] According to the structural parameters and application conditions of the shock absorber, a preliminary mechanical simulation model is established, and a two-variable coupled viscosity model is integrated into the simulation model to obtain a preliminary true module.

[0068] Collect the basic design parameters of the shock absorber, including: piston diameter, stroke, cavity size; damping hole diameter, number of holes, channel geometry; silicone oil filling amount and initial pressure (if any).

[0069] Clarify the application parameters, including: expected operating temperature range (e.g. -40°C to 80°C); piston speed range (e.g. 0.01 m / s to 10 m / s); loading mode (unidirectional loading, bidirectional loading, impact, vibration).

[0070] Use finite element analysis (FEA) or multiphysics simulation tools (such as ANSYS Fluent, COMSOL Multiphysics);

[0071] The internal modeling details of the shock absorber include: the relative motion of the piston and the cavity; the flow path and boundary conditions in the damping orifice; and the silicone oil material model is defined as a rheologically responsive material rather than a simple Newtonian fluid.

[0072] Set dynamic boundary conditions: apply periodic displacement or velocity input to the piston; use no-slip boundary conditions on the wall; set the temperature field to multi-level changes or steady-state settings.

[0073] In the fluid region, the viscosity η of silicone oil is defined as the temperature T and the shear rate The function is: ;

[0074] Import the customized two-variable function into the simulation software as a user-defined material subroutine (such as a UDF script). Ensure that the fluid unit dynamically adjusts the viscosity based on the local temperature and shear rate at each moment. If the simulation platform does not directly support two-variable viscosity, use multitable interpolation or a weakly coupled substep algorithm.

[0075] Run the simulation and output: damping force-displacement curve (Fd curve); damping force-velocity curve (Fv curve); internal shear rate and temperature distribution field of silicone oil; determine the integrity and continuity of the simulation output characteristic curve within the set temperature and velocity range; use the overall dynamic response characteristics of the shock absorber obtained by simulation as a preliminary true module for subsequent actual measurement matching and optimization steps.

[0076] Conduct dynamic loading tests to obtain measured damping response data of the shock absorber at different temperatures and different movement rates, including:

[0077] Test equipment selection: Servo-hydraulic fatigue testing machine or electric vibration table system with the ability to precisely control piston displacement / velocity; equipped with a high-sensitivity displacement sensor (such as LVDT) and a damping force sensor (such as a load cell); equipped with a high- and low-temperature environmental chamber with an adjustable temperature range of generally -60°C to 120°C; equipped with a data acquisition system with a sampling frequency of at least 1000 Hz to ensure complete recording of dynamic responses.

[0078] Install the silicone oil shock absorber to be tested on the loading platform using a rigid fixture; ensure coaxial installation to eliminate eccentricity and initial stress; check the internal oil filling status and sealing integrity of the shock absorber to avoid test abnormalities.

[0079] Set several temperature points according to actual application requirements, such as: -40°C, 0°C, 25°C, 60°C, 90°C; cover the service temperature range of the shock absorber, and try to cover extreme low and high temperature environments.

[0080] Before the test, the entire shock absorber is placed in a temperature-controlled chamber and stabilized for at least 30 minutes. The actual temperature of the sample is monitored in real time using a built-in temperature sensor to ensure that the sample reaches and stabilizes at the target temperature (fluctuation <±1°C).

[0081] The motion mode setting mainly adopts sine wave loading, triangle wave loading, or step loading; the motion amplitude range is such as ±20 mm, ±50 mm, which can be selected according to the actual application.

[0082] Rate (frequency) setting: Low speed: 0.01 m / s to 0.1 m / s; Medium speed: 0.5 m / s to 2 m / s; High speed: 5 m / s to 10 m / s. The rate setting can be adjusted according to actual usage. In particular, high strain rate testing requires attention to the equipment's acceleration capability.

[0083] At each temperature point, dynamic loading with different movement rates is applied in sequence; each loading condition is cycled at least 3 to 5 times to observe the stability and repeatability of the damping characteristics.

[0084] Real-time synchronous acquisition: displacement data (x, unit: mm); force data (F, unit: N); time data (t, unit: ms); and temperature change data are recorded at the same time to ensure that the temperature deviation during loading is within the allowable range.

[0085] Draw the force-displacement curve (Fx) to observe the energy dissipation (the hysteresis loop area represents energy dissipation); draw the force-velocity curve (Fv) to analyze the changes in the relationship between damping force and velocity; calculate key parameters such as the equivalent viscous damping coefficient and hysteresis energy loss.

[0086] Check whether there is force signal drift, sudden jump, or abnormal noise; eliminate test data with abnormal vibration, leakage, structural failure, etc.

[0087] Each set of test data is classified and archived according to the temperature-motion rate combination; a standardized damping performance data package is formed for subsequent real module parameter calibration.

[0088] Compare the simulated output with the measured output, and use the parameter optimization algorithm to adjust the parameters of the preliminary real module until the error between the simulated output and the measured data under various test conditions meets the preset accuracy requirements, completing the real module matching. Specifically, this includes:

[0089] Determine the optimization goal: minimize the error between simulation output and measured data;

[0090] Define an error evaluation metric (objective function), such as root mean square error (RMSE) or sum of relative error (SRE); ;in: To simulate the damping force at moment i, is the measured damping force at moment i, W is the number of data points, and the real module parameters to be optimized are set, such as: 、 ;K, n in the power law model; coupling term correction coefficient;

[0091] Define the number of particles in the swarm (usually 20 to 50 particles);

[0092] Each particle represents a set of true module parameter combinations to be optimized;

[0093] The initial position of the particles is randomly generated within the allowable range of each parameter;

[0094] The initial velocity of the particles is also randomly generated, and the maximum velocity is appropriately limited to avoid excessive jumps.

[0095] Initially set the inertia weight of the particle swarm winit (for example, 0.9);

[0096] After each iteration, the inertia weight is dynamically adjusted;

[0097] For each iteration:

[0098] Each particle adjusts its speed and position based on its own historical best position and the current best position in the group, thus continuously approaching the area with the minimum error: ;in: is the velocity of the i-th particle, is the position of the i-th particle (parameter group), is the particle’s own historical optimal position, is the global optimal position, is a random number between [0,1], is the learning factor (usually set to 1.5-2.0). w is the inertia weight, which is often used to control the influence of the particle's current velocity on its next step velocity.

[0099] For each particle, run the simulation model according to its corresponding parameter set;

[0100] Calculate its objective function value (error size) as fitness;

[0101] Update the historical optimal position pbesti of each particle;

[0102] Update the global optimal position gbest of the group.

[0103] Stop condition: The maximum number of iterations is reached or the error index of the optimal particle is lower than the preset threshold (for example, the overall error is less than 2%). If not met, continue iteration.

[0104] Output the optimal parameter combination; input the optimized real module parameters into the simulation system; complete the final matching of simulation and measured data to obtain the final real module.

[0105] After each shock absorber design and real module parameter optimization is completed, the following information will be archived and stored in the database:

[0106] True module parameters include: reference viscosity , rheological activation energy Consistency coefficient (K), flow index (n), temperature-shear coupling correction factor, etc.

[0107] The corresponding damping performance indicators include: peak damping force, average damping force, hysteresis energy dissipation (hysteresis loop area), temperature sensitivity coefficient, rate sensitivity coefficient, etc.

[0108] Design features include piston diameter, channel cross-sectional area, number of orifices, operating temperature range, and shear rate range.

[0109] Each piece of data is indexed by design number-operating condition number and stored in categories to form a structured database for easy subsequent rapid retrieval and analysis.

[0110] In order to avoid database expansion redundancy and improve retrieval and deduction efficiency, it is necessary to intelligently optimize the existing database. First, a feature extraction algorithm is used to extract the core influencing characteristic parameters of each sample. The secondary parameters with less influence are initially screened out, and the parameters that have a decisive influence on the change in damping performance are retained. The core influencing characteristic parameters include the temperature shear response uniformity value, which characterizes the consistency and smoothness of the damping performance change at different temperatures and different shear rates; and the energy dissipation stability index, which measures the degree of fluctuation of the hysteresis loop energy loss area under different working conditions;

[0111] The method for obtaining the temperature shear response uniformity value is as follows: and each shear rate Under the combination, collect the corresponding shock absorber output damping force All test data are divided into different temperature shear points (i.e. each group 、 ) are classified and sorted to form a matrix M; for each temperature , calculate the average damping force corresponding to all shear rates, which is recorded as: ; Where m is the number of shear rates;

[0112] For each temperature , calculate the standard deviation of the damping force at all shear rates , the expression is: ; Define the damping force uniformity ratio at each temperature for: , reflecting the consistency of the damping response at each shear rate.

[0113] The uniformity ratios at all temperature points are averaged to obtain the overall temperature shear response uniformity value UK, which is expressed as: ; where q is the number of temperature points.

[0114] When the temperature-shear response uniformity value is low (close to zero), it indicates that the damping force of the shock absorber changes relatively smoothly under different temperature and shear rate conditions, and the performance is consistent across all operating conditions. This indicates that the sample quality within the database is high, the data distribution is uniform, and it accurately reflects the intrinsic behavior of silicone oil materials, making it suitable as a reliable basis for true module deduction and rapid retrieval.

[0115] Conversely, a high temperature-shear response uniformity value indicates that the damping force fluctuates dramatically at different temperatures and shear rates, with poor consistency between samples and the presence of significant discreteness or outliers. This reflects low data quality within the database, potentially due to testing errors, uneven data distribution, or insufficient samples for specific operating conditions. Further optimization and correction are necessary, such as removing outliers and supplementing key missing conditions.

[0116] The energy dissipation stability index is obtained as follows:

[0117] At different temperatures and shear rate Under working conditions, collect the energy dissipation value of the single cycle hysteresis loop , and obtain a two-dimensional energy matrix R;

[0118] All The energy values ​​are arranged into a one-dimensional sequence in the order of testing, denoted as E(k), where k = 1, 2, …, N, and N is the total number of samples. Applying discrete Fourier transform to the energy sequence E(k) yields its frequency domain expression: ; Where: X(f) is the complex amplitude at frequency component f; E(k) is the kth energy sample value; is the Fourier transform kernel function; calculate the energy density of each frequency component: ; Where P(f) represents the energy intensity at frequency f; set a frequency threshold (For example, select the first 10% of the entire frequency range as the low-frequency area); calculate the sum of the low-frequency energy separately: ;Summary of high frequency energy: (Note: The actual frequency range is only N / 2 because the data above the Nyquist frequency is mirrored after DFT.)

[0119] Defining the Energy Dissipation Stability Index is the ratio of low-frequency energy to total energy, and the expression is: ;in: The closer it is to 1, the more energy is concentrated in low frequencies and the performance is stable; The smaller it is, the greater the energy fluctuation and the poorer the stability.

[0120] The temperature shear response uniformity value and the energy dissipation stability index are normalized so that they are both between [0, 1]. The normalized temperature shear response uniformity value and the energy dissipation stability index are weighted averaged and summed to obtain the internal data quality score of the database.

[0121] The obtained database internal data quality score is compared with the preset scoring threshold. If the database internal data quality score is greater than or equal to the preset scoring threshold, it indicates that the samples within the database perform well in terms of temperature shear response and energy dissipation stability, the data distribution is reasonable and uniform, and the overall data quality meets the requirements of high-reliability design. At this point, the database can be directly used for shock absorber real module deduction and rapid retrieval without additional optimization processing.

[0122] If the database's internal data quality score is less than the preset threshold, it indicates significant performance fluctuations or sample inhomogeneity within the database. The consistency of the temperature-shear response or the stability of energy dissipation fall short of expectations, and the overall data quality is insufficient to support high-precision real-module simulations. Further database optimization is required, including removing abnormal samples, supplementing key operating condition data, and reconstructing the feature space to improve overall data quality.

[0123] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0124] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0125] It should be understood that the term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist at the same time, and B exists alone, where A and B may be singular or plural. In addition, the character " / " herein generally indicates that the objects associated with each other are in an "or" relationship, but it may also indicate an "and / or" relationship, which can be understood by referring to the context. A person of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0126] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A true module matching and database optimization method for the design of high-strength silicone oil vibration dampers, characterized by: include: Collect rheological properties test data of silicone oil materials at multiple temperature points and multiple shear rate conditions; Based on rheological properties test data, an Arrhenius temperature effect model and a power-law shear rate effect model of silicone oil were constructed respectively, and a cross-coupling correction term was introduced to form a temperature-shear rate dual-variable coupled viscosity model, including: fitting the temperature effect relationship on viscosity based on the Arrhenius equation under fixed shear rate conditions, fitting the shear rate effect on viscosity based on the power-law fluid model under fixed temperature conditions, and introducing a cross-coupling correction term by analyzing the modulation law of temperature on the power-law model parameters K and n to form a joint function model of viscosity with respect to temperature and shear rate; According to the shock absorber structural parameters and application conditions, a preliminary mechanical simulation model is established, and a two-variable coupled viscosity model is integrated into the simulation model to obtain a preliminary true module; The establishment of a preliminary mechanical simulation model includes: based on the shock absorber's piston diameter, cavity size, damping hole diameter, and silicone oil filling volume parameters, using finite element analysis software to construct a multi-physics simulation model that includes piston motion, throttling channel flow, and temperature field changes, and integrating the dual-variable coupled viscosity model in the fluid region; Conduct dynamic loading tests to obtain measured damping response data of the shock absorber at different temperatures and movement rates; Compare the simulated output with the measured output, and use the parameter optimization algorithm to adjust the parameters of the preliminary real module until the error between the simulated output and the measured data under various test conditions meets the preset accuracy requirements, thus completing the real module matching; The true module parameters and corresponding damping performance indicators optimized under different design schemes are classified and stored in the database, and the database is optimized according to the internal data quality of the database.

2. The true module matching and database optimization method for high-strength silicone oil vibration damper design according to claim 1 is characterized in that: Collecting the rheological properties test data of silicone oil materials includes: at multiple set temperature points, including -50°C to 100°C and multiple shear rate ranges including to , use a rotational rheometer or capillary rheometer to perform constant shear rate scanning and constant shear stress scanning tests, and record the shear stress and apparent viscosity values.

3. The true module matching and database optimization method for high-strength silicone oil vibration damper design according to claim 1 is characterized in that: Conduct dynamic loading tests: At different set temperature points and different motion rate conditions, a servo-hydraulic fatigue testing machine is used to perform sinusoidal, triangular, or step wave loading. Displacement, velocity, damping force, and temperature data are collected synchronously in real time. Force-displacement and force-velocity curves are plotted, and the equivalent damping coefficient and hysteresis energy loss parameters are extracted.

4. The true module matching and database optimization method for high-strength silicone oil vibration damper design according to claim 3 is characterized in that: Use parameter optimization algorithms to adjust the parameters in the preliminary true module, including: Determine the optimization goal to minimize the error between simulation output and measured data; Define the objective function, ;in: To simulate the damping force at moment i, is the measured damping force at moment i, W is the number of data points; Set the true module parameters to be optimized and define the number of particle swarms; each particle represents a set of true module parameter combinations to be optimized; the initial position of the particle is randomly generated within the allowable range of each parameter; the initial velocity of the particle is also randomly generated; Initially set the inertia weight of the particle swarm winit; After each iteration, the inertia weight is dynamically adjusted; For each iteration: each particle adjusts its speed and position based on its own historical best position and the current best position in the group; For each particle, run the simulation model according to its corresponding parameter group; calculate its objective function value as fitness; update the historical optimal position pbesti of each particle; update the global optimal position gbest of the group; The stopping condition is determined as reaching the maximum number of iterations or the error index of the optimal particle is lower than the preset threshold; The optimized real module parameters are input into the simulation system to complete the matching of the final simulation and measured data to obtain the final real module.

5. The true module matching and database optimization method for high-strength silicone oil vibration damper design according to claim 4 is characterized in that: Optimize the database based on the internal data quality, including obtaining the temperature shear response uniformity value: at each test temperature and each shear rate Under the combination, collect the corresponding shock absorber output damping force , all test data are classified and sorted according to different temperature shear points to form a matrix M; for each temperature , calculate the average damping force corresponding to all shear rates, which is recorded as: ; Where m is the number of shear rates; For each temperature , calculate the standard deviation of the damping force at all shear rates , the expression is: ; Define the damping force uniformity ratio at each temperature for: ; Average the uniformity ratios at all temperature points to obtain the overall temperature shear response uniformity value UK, which is expressed as: ; where q is the number of temperature points.

6. The true module matching and database optimization method for high-strength silicone oil vibration damper design according to claim 5, characterized in that: Obtaining the energy dissipation stability index: at different temperatures and shear rate Under working conditions, collect the energy dissipation value of the single cycle hysteresis loop , get a two-dimensional energy matrix R; all The energy values ​​are arranged into a one-dimensional sequence in the order of testing, denoted as E(k), where k = 1, 2, …, N, and N is the total number of samples. Applying discrete Fourier transform to the energy sequence E(k) yields its frequency domain expression: ; Where: X(f) is the complex amplitude at frequency component f; E(k) is the kth energy sample value; is the Fourier transform kernel function; calculate the energy density of each frequency component: ; Where P(f) represents the energy intensity at frequency f; set a frequency threshold ; Calculate the sum of low-frequency energy separately: ;Summary of high frequency energy: ; Define the energy dissipation stability index is the ratio of low-frequency energy to total energy, and the expression is: .

7. The true module matching and database optimization method for high-strength silicone oil vibration damper design according to claim 6, characterized in that: The temperature shear response uniformity value and the energy dissipation stability index are normalized so that they are both between [0, 1]. The normalized temperature shear response uniformity value and the energy dissipation stability index are weighted averaged and summed to obtain the internal data quality score of the database.

8. The true module matching and database optimization method for high-strength silicone oil vibration damper design according to claim 7, characterized in that: The obtained database internal data quality score is compared with the preset score threshold. If the database internal data quality score is greater than or equal to the preset score threshold, it indicates that the overall data quality among the samples in the database is high. At this time, the database can be directly used for shock absorber true module deduction and rapid retrieval without additional optimization processing. If the database internal data quality score is less than the preset score threshold, it indicates that there is a sample unevenness problem in the database, and the database needs to be further optimized.

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