CN114282441B - An equivalent model of friction kinematic pair and its modeling method - Google Patents
An equivalent model of friction kinematic pair and its modeling method Download PDFInfo
- Publication number
- CN114282441B CN114282441B CN202111616885.4A CN202111616885A CN114282441B CN 114282441 B CN114282441 B CN 114282441B CN 202111616885 A CN202111616885 A CN 202111616885A CN 114282441 B CN114282441 B CN 114282441B
- Authority
- CN
- China
- Prior art keywords
- friction
- equation
- friction force
- frequency
- pair
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000012360 testing method Methods 0.000 claims abstract description 39
- 238000001228 spectrum Methods 0.000 claims abstract description 18
- 230000004044 response Effects 0.000 claims abstract description 9
- 238000010586 diagram Methods 0.000 claims description 15
- 230000003595 spectral effect Effects 0.000 claims description 7
- 230000002068 genetic effect Effects 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000007619 statistical method Methods 0.000 claims description 2
- 238000011089 mechanical engineering Methods 0.000 abstract description 2
- 238000006073 displacement reaction Methods 0.000 description 14
- 230000000694 effects Effects 0.000 description 9
- 229920007019 PC/ABS Polymers 0.000 description 7
- 230000005284 excitation Effects 0.000 description 7
- 238000001914 filtration Methods 0.000 description 6
- 238000005259 measurement Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000010183 spectrum analysis Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- 238000009827 uniform distribution Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/06—Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Biophysics (AREA)
- Software Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computational Linguistics (AREA)
- Computer Hardware Design (AREA)
- Medical Informatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Genetics & Genomics (AREA)
- Biomedical Technology (AREA)
- Geometry (AREA)
- Data Mining & Analysis (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Feedback Control In General (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
本发明属于机械工程领域，具体涉及一种摩擦运动副等效模型及其建模方法，对摩擦副的摩擦力试验数据按高低频段分别进行统计分析建模并进行叠加，构造能同时反映摩擦副高低频特性的等效模型；针对摩擦副的低频段摩擦力特性，引入正压力输入信息并对传统的LuGre模型进行变形得到摩擦力响应与摩擦副相对速度及正压力输入的隐式关系；针对摩擦副的高频段摩擦力特性，引入正压力输入信息并结合幂函数形式的摩擦力自功率谱假设，得到摩擦力响应与摩擦副正压力的隐式关系。本发明提出的等效模型不但能反映了摩擦力与正压力和相对速度的关系，而且可以表达宽频带的摩擦力特性，具有良好的适用性。
The present invention belongs to the field of mechanical engineering, and specifically relates to an equivalent model of a friction kinematic pair and a modeling method thereof. The friction test data of the friction pair are statistically analyzed and modeled according to high and low frequency bands and superimposed to construct an equivalent model that can simultaneously reflect the high and low frequency characteristics of the friction pair; for the low-frequency friction characteristics of the friction pair, positive pressure input information is introduced and the traditional LuGre model is deformed to obtain the implicit relationship between the friction response and the relative speed of the friction pair and the positive pressure input; for the high-frequency friction characteristics of the friction pair, positive pressure input information is introduced and combined with the friction self-power spectrum hypothesis in the form of a power function, the implicit relationship between the friction response and the positive pressure of the friction pair is obtained. The equivalent model proposed by the present invention can not only reflect the relationship between friction, positive pressure and relative speed, but also can express the wide-band friction characteristics, and has good applicability.
Description
Technical Field
The invention belongs to the field of mechanical engineering, and particularly relates to a friction kinematic pair equivalent model and a modeling method thereof.
Background
Friction is a natural phenomenon in which objects contact each other under normal pressure, surface asperities are engaged with each other, and when relative sliding occurs or there is a tendency for relative sliding, resistance against sliding is generated on the contact surface, wherein the resistance is referred to as frictional force. The friction mechanism is quite complex, and there has been a great deal of research on the characteristics of friction pairs, namely the relationship between the friction force response and the input motion conditions (positive pressure, tangential relative speed, etc.) of the friction pairs, and also tends to present quite complex conditions, and the friction characteristics are also affected by factors affecting the properties of the friction pairs, particularly the properties of the friction contact surfaces. Classical coulomb friction law considers that sliding friction force is in direct proportion to positive pressure, but later researches show that the sliding friction force is not always in direct proportion to positive pressure and is closely related to relative movement speed, and various complex phenomena such as Stribeck effect, macroscopic sliding time lag, pre-sliding displacement lag and the like exist, and the friction force also often presents the characteristic of a wide frequency band.
In view of the complex characteristics of the friction pair and the complex mechanism for generating friction force, no method for effectively completing theoretical modeling of the friction pair exists at present, so that an empirical model or a semi-empirical model of the friction pair can be built only by a test method. As for the empirical or semi-empirical model of the friction pair, there are already many kinds of models, such as the lu gre model, the GW model, the fractal contact model, the Stribeck model, the Karnopp model, the Dahl model, the GMS model, the GBM model, etc., which are relatively simple and complex, but are mainly characterized by low frequency characteristics of friction force, and generally do not include high frequency characteristics.
In practical engineering, low-frequency vibration excitation causes secondary friction excitation of friction pairs in a mechanical system, and high-frequency noise is often radiated, which means that high-frequency vibration of a structure is excited, so that high-frequency characteristics of friction force are necessarily focused. Therefore, the invention provides a novel friction kinematic pair equivalent model which can represent the friction force characteristics of a wide frequency band and has a relatively simple form so as to be used for the forced vibration response prediction, analysis, design and control of a local nonlinear mechanical system comprising the friction pair.
Disclosure of Invention
The invention aims to provide a friction kinematic pair equivalent model and a modeling method thereof, which can characterize the friction force characteristics of a broadband, and have a relatively simple form so as to be used for predicting, analyzing, designing and controlling the forced vibration response of a local nonlinear mechanical system containing friction pairs.
In order to achieve the above purpose, the invention provides an equivalent model of a friction kinematic pair and a modeling method thereof, wherein the equivalent model can reflect the high-low frequency characteristics of the friction pair by respectively carrying out statistical analysis modeling and superposition on friction force test data of the friction pair according to the high-low frequency bands;
Aiming at the low-frequency band friction force characteristic of the friction pair, introducing positive pressure input information and deforming a traditional LuGre model to obtain an implicit relation between friction force response and relative speed and positive pressure input of the friction pair;
and introducing positive pressure input information according to the high-frequency band friction characteristic of the friction pair and combining friction self-power spectrum assumption in a power function form to obtain an implicit relation between friction response and positive pressure of the friction pair.
Further, the mathematical equation of the friction kinematic pair equivalent model is as follows:
f(N)=aNb+c
Wherein F (N, v) is the friction force output by the friction pair equivalent model and is a function of the friction pair positive pressure N and the tangential relative movement speed v, z is an introduced intermediate variable, usually a function of time, t represents time and ω represents frequency, s (N, v), F (N) and R (N, ω) are all introduced intermediate functions, R (t) is the friction force time history of a high frequency band, the self-power spectral density of the friction force time history is R (N, ω), the rest parameters are to-be-determined coefficients, and the to-be-determined parameters are determined for the specific friction pair, namely the material of the friction pair and the friction contact surface property, and are to-be-determined uniquely.
Further, the undetermined parameters of the friction pair equivalent model can be identified and determined through friction test data, so that the equivalent model modeling of the specific friction pair can be completed. Specific steps of modeling the equivalent model of any specific friction pair include:
S1, carrying out friction test on a friction auxiliary sample piece and recording a friction test related signal, S2, preprocessing the test signal, obtaining a friction force-relative motion speed, a friction force-positive pressure scatter diagram and a friction force self-power spectrum, S3, determining high-frequency-band friction force model parameters based on a least square method, S4, identifying low-frequency-band friction force model parameters based on a least square method and a genetic algorithm, and S5, overlapping to obtain a complete equivalent model.
The equivalent model provided by the invention can reflect the relation between friction force and positive pressure and relative speed, can express the friction force characteristic of a broadband, and has good applicability.
Drawings
FIG. 1 is a photograph of a typical friction pair material standard;
FIG. 2 is a typical measured friction signal and relative displacement signal for a standard sample friction pair test;
FIG. 3 is a self-power spectrum of the friction high-frequency part of the friction pair PC/ABS-PC/ABS under the excitation of positive pressure 30N and triangular displacement wave with the speed of 3 mm/s;
FIG. 4 friction pair PC/ABS-PC/ABS triangular displacement wave excitation friction force-velocity curve and friction force-positive pressure curve fitting effect;
FIG. 5 is an iteration effect of a friction pair PC/ABS-PC/ABS positive pressure 30N, a low-frequency band part friction force time course model under the excitation of a 1mm/s triangular displacement wave;
FIG. 6 shows the effect of predicting the equivalent model of the friction force time history under the excitation of the friction pair PC/ABS-PC/ABS triangular displacement wave;
FIG. 7 is a graph of modeled predicted friction time history versus measured values for other typical friction pairs using an equivalent model of the present invention.
Detailed Description
Further details are provided below with reference to the specific embodiments.
On the basis of the collection and analysis of friction test signals of a large number of friction sub-standard samples, the friction characteristics are statistically analyzed and observed, the characteristics of the low frequency band are basically consistent with the existing research conclusion, the characteristics of the high frequency band show power function characteristics, namely the friction self-power spectrum decays according to a nonlinear power function law along with the increase of frequency, and generally, the friction of the high frequency band increases along with the increase of positive pressure, but the correlation with the relative movement speed is not obvious. Therefore, the invention provides an equivalent model for superposing the low-frequency band characteristic and the high-frequency band characteristic, namely, the model structure is divided into a low-frequency band and a high-frequency band, and the corresponding frequency band filtering signals of the test data are also adopted in the identification of the model parameters. Aiming at a low-frequency band model, the traditional LuGre model is considered to have clear physical meaning and a simpler form, namely fewer model parameters to be identified, and the friction characteristics which can be represented comprise maximum static friction force which is larger than sliding friction force, pre-sliding displacement hysteresis, stribeck effect and sliding friction time lag, so that the traditional LuGre model is adopted, a positive pressure relation is introduced to carry out proper modification on a model structure so as to represent the more complete friction characteristics of the low-frequency band, a friction self-power spectrum power function model containing positive pressure input is directly constructed aiming at a high-frequency band model, the friction time history of the high-frequency band can be further obtained by combining a random phase in consideration of the randomness of a high-frequency friction signal, and then the complete friction output of the whole frequency band can be obtained by directly superposing the low-frequency band friction in a time domain.
According to the thought, the invention provides a novel broadband friction equivalent model of the friction kinematic pair, which is shown as follows.
f(N)=aNb+c (4)
Equation (1) expresses that the friction force F (N, v) output by the friction pair equivalent model is calculated by the low frequency band partAnd the high-frequency part r (t) is directly overlapped in the time domain and is a hidden function of the positive pressure N of the friction pair and the tangential relative movement speed v, wherein z is an introduced intermediate variable, and is usually a function of time t. The friction force of the low-frequency part is given by equations (2) - (4), the equation (4) expresses the power function relation of the friction force f (N) and the positive pressure, the equation (3) expresses the relation of the friction force s (N, v) and the positive pressure and the relative movement speed, N 0 is the reference positive pressure, the equation (2) gives a differential equation met by the intermediate variable z, and obviously, for a given N, v, z and the first derivative thereof can be solved by the equation (2), so that the friction force time history of the low-frequency part is determined. The friction of the high band part is given by equation (5), where ω represents the frequency, ω 0 is the high and low band demarcation frequency, R (N, ω) is the self-power spectral density function of the friction of the high band part, and the high band friction time history R (t) can be found by inverse fourier transform, taking into account the random nature of the friction of the high band part, assuming a random phase spectrum. The rest parameters in the equations (1) - (5) are the undetermined coefficients of the equivalent model, and are determined for the specific friction pair, namely the material of the friction pair and the friction contact surface property, and the undetermined parameters are required to be determined uniquely.
Aiming at any friction kinematic pair, the model structure provided by the invention is shown in equations (1) - (5), wherein the undetermined coefficient can be determined through experimental identification, so that the modeling of the equivalent model of the friction kinematic pair is completed. The method comprises the following specific steps.
S1, performing a friction test on the friction auxiliary sample piece and recording a friction test related signal.
This step should prepare a standard friction pair test piece for the target friction pair, whose material and contact surface properties (surface hardness, roughness, etc.) are consistent with the target friction pair. The friction test should synchronously record positive pressure, friction force and tangential relative motion displacement or speed signals of the friction pair, and should comprise a pre-sliding state and a macroscopic sliding state of the friction pair. The friction pair reciprocating sliding test can be carried out, and the friction pair unidirectional sliding test can also be carried out. Different friction test modes are selected, and different friction pair friction force test devices or equipment are often required. The invention recommends a triangular wave displacement excited friction pair reciprocating sliding friction test, can rapidly carry out the test and acquire signals such as friction force in a required friction state, can acquire relevant information of a friction pair pre-sliding stage in a reversing section of relative reciprocating sliding, can acquire relevant information of a friction pair macroscopic sliding stage in other stable sliding sections at a constant speed, and is convenient for modeling use. The friction pair relative sliding test is usually carried out under a given positive pressure, each test comprises a stable sliding state with a given speed and a transition state from rest to the given speed, and the positive pressure and the speed are adjusted to obtain friction test signals of various states required by modeling.
S2, preprocessing the test signals, and obtaining a friction force-relative movement speed, a friction force-positive pressure scatter diagram and a friction force self-power spectrum.
And filtering the actually measured friction force signals to obtain low-frequency-band friction force signals and high-frequency-band friction force signals respectively. The relative motion displacement signal and the velocity signal (if only one signal is recorded, the other signal can be obtained by differentiation or integration of the two signals) are mutually referenced with the low-frequency band friction signal, so that the friction force of macroscopic sliding and pre-sliding stages is easily distinguished, and the friction force of a constant-velocity sliding section is also easily distinguished. The friction-relative movement speed scatter diagram can be obtained by using the friction signals of the sliding sections with different constant speeds under the given positive pressure, and the friction-positive pressure scatter diagram can be obtained by using the friction signals of the sliding sections with different constant speeds under the different positive pressures. Similarly, a high-frequency band friction-positive pressure scatter diagram can be obtained by utilizing the high-frequency band friction signal, and a self-power spectrogram can be obtained by carrying out spectrum analysis on the high-frequency band friction signal under a given reference positive pressure.
S3, determining high-frequency band friction model parameters based on a least square method.
And (3) determining undetermined parameters in the equation (5) based on a least square method by using the high-frequency-band friction force-positive pressure scatter diagram and the high-frequency-band friction force self-power spectrogram, so as to determine a frequency spectrum model of the high-frequency-band friction force.
S4, identifying low-frequency band friction model parameters based on a least square method and a genetic algorithm.
Each of the undetermined parameters in equations (4) and (3) can be determined based on the least square method using the friction-positive pressure scatter diagram and the friction-relative movement speed scatter diagram of the low frequency band, respectively. And then the friction force time history and the corresponding relative movement speed time history of the low frequency band and the identified intermediate functions s (N, v) and f (N) are utilized to calculate undetermined parameters sigma 0 and sigma 1 in equations (1) and (2) based on a genetic algorithm (of course, other mature optimization algorithms can be selected).
S5, overlapping to obtain a complete equivalent model.
Taking into consideration the random nature of the friction force of the high frequency band, assuming that the friction force has a random phase spectrum, then utilizing the identified and obtained self-power spectral density function of the friction force of the high frequency band, namely (5), the time course of the friction force, namely the friction force r (t) of the high frequency band, can be obtained through inverse Fourier transform, and then the friction force r (t) of the high frequency band is matched with the friction force of the low frequency band obtained in the step S4And superposing to obtain complete friction force output. So far, all undetermined parameters and functions in equivalent model equations (1) - (5) are determined, and the complete equivalent model of the target friction kinematic pair is obtained.
Examples:
Fig. 1 is a photograph of a typical sample of material constituting a friction pair. Aiming at a specific friction pair standard sample, a self-grinding reciprocating friction testing machine is adopted to conduct friction test, related actual measurement signals are obtained, then an equivalent model of the friction pair is established according to the method, and the friction force predicted by the equivalent model is compared with the actual measurement friction force, so that the effectiveness of the equivalent model is illustrated. The specific implementation and results are as follows.
The first step is to install the friction pair standard sample piece on a special friction testing machine, load different positive pressures, set different speeds to perform triangular wave displacement excitation, enable the friction pair sample piece to perform tangential reciprocating relative motion, record the time course of friction force and relative displacement, and typical friction force and relative displacement actual measurement signals are shown in figure 2. During the test, the ambient temperature is 20+/-5 ℃ and the humidity is 75% -85%. The positive pressure and relative velocity selected for the test conditions are shown in table 1.
TABLE 1 test conditions
Selecting test data of different speeds under 30N pressure, carrying out 2Hz low-pass filtering on the friction time history, comparing the relative displacement with the speed time history, solving a friction average value for a friction signal in a constant-speed sliding stage to obtain a friction-speed scatter diagram, selecting test data of 3mm/s speeds under different positive pressures, carrying out 2Hz low-pass filtering on the friction time history to obtain a friction-positive pressure scatter diagram, selecting 30N,3mm/s test data, intercepting the friction time history in one direction of reciprocating motion for removing the fundamental wave influence of the reciprocating motion, subtracting a direct current component, carrying out power spectral density estimation on the direct current component to obtain a friction power spectral density curve of a high-frequency band part, and carrying out high-pass filtering (cut-off frequency is 2 Hz) on the friction time history, and then carrying out spectral analysis on a filtered signal to obtain the friction power spectral density curve of the high-frequency band part, wherein the results are basically the same.
And thirdly, establishing a high-frequency part friction model. That is, based on the least square method, the undetermined parameters in the self-power spectrum model (i.e. equation (5)) are obtained according to the actually measured power spectrum density curve of the friction force of the high-frequency part, fig. 3 shows the comparison between the calculated curve and the actually measured curve of the friction force self-power spectrum model of the high-frequency part, and then the friction force time history of the high-frequency part is obtained by means of inverse fourier transform assuming that a random phase spectrum (uniform distribution) exists.
And fourthly, establishing a low-frequency part friction model. Firstly, based on a least square method, respectively utilizing a friction force-positive pressure scatter diagram and a friction force-speed scatter diagram which are obtained by analyzing measured signals, respectively fitting a f (N) =aN b +c friction force-positive pressure curve and a friction force-positive pressure curveThe friction force-speed curve is used for solving undetermined parameters a, b, c, mu c、μs、vc、σ2 and delta s, and the fitting effects of a friction force-speed scatter diagram and a friction force-positive pressure scatter diagram of a friction test of a PC/ABS-PC/ABS material auxiliary sample are shown in fig. 4. Here, the reference positive pressure is taken to be 30N. And then adopting a genetic algorithm, taking the error standard deviation of the friction time history calculated by the low-frequency-band friction model and the low-pass filtering time history of the experimental measured friction force 2Hz under the working conditions of 30N and 3mm/s as an objective function, and iterating out the parameter sigma 0、σ1 when the objective function is minimum, namely determining the low-frequency-band part friction model, wherein the comparison between the low-frequency-band part friction model prediction and the actual measured time history is shown in FIG. 5.
And fifthly, directly superposing the friction force of the low-frequency part and the friction force of the high-frequency part in a time domain to obtain the total friction force of the friction pair equivalent model, namely, all undetermined parameters in friction pair equivalent model equations (1) - (5) are determined, modeling of the friction pair equivalent model is completed, and by using the equivalent model, all intermediate functions and intermediate variables in equations (1) - (5) and finally equivalent model output required to be calculated, namely, friction force time history, can be calculated as long as the model input, namely, the time history of positive pressure and relative speed (comprising the condition of constant) is given. FIG. 6 shows the effect of comparing the measured time course of friction with the predicted time course of friction of an equivalent model under typical conditions of a friction test of a secondary sample of PC/ABS-PC/ABS material.
Obviously, the PC/ABS-PC/ABS material friction pair equivalent model established by the method can accurately predict the friction force time course, and in fact, the friction pair equivalent model has similar effects for other typical material friction pairs, and FIG. 7 shows comparison of typical actual measured friction force time course and equivalent model prediction time course, the sizes and change trends of the two are basically consistent, so that the equivalent model well represents the dynamics characteristics of the friction pair.
It should be noted that, in the present invention, unless explicitly specified and limited otherwise, terms such as "mounted," "connected," "fixed," and the like are to be construed broadly and include, for example, either fixedly connected or detachably connected or integrally connected, either directly or indirectly connected through an intermediate medium, and also include communication between the two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
The foregoing is merely exemplary embodiments of the present application, and specific structures and features that are well known in the art are not described in detail herein. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present application, and these should also be considered as the scope of the present application, which does not affect the effect of the implementation of the present application and the utility of the patent. The protection scope of the present application is subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (1)
1. A friction kinematic pair equivalent model and a modeling method thereof are characterized in that the friction force test data of a friction pair are respectively subjected to statistical analysis modeling according to high and low frequency bands and are overlapped to construct an equivalent model capable of reflecting the high and low frequency characteristics of the friction pair;
the mathematical equation of the equivalent model is as follows:
f(N)=aNb+c (4)
Wherein F (N, v) is the friction force output by the friction pair equivalent model and is formed by the low-frequency part The friction force of the low frequency band part is given by an equation (2) to (4), the equation (4) expresses the power function relation of the friction force f (N) and the positive pressure, the equation (3) expresses the relation of the friction force s (N, v) and the positive pressure and the relative motion speed, N 0 is a reference positive pressure, the equation (2) gives a differential equation met by an intermediate variable z, for a given N, v, z and a first derivative thereof can be solved by the equation (2) so as to determine the time history of the friction force of the low frequency band part, the friction force of the high frequency band part is given by the equation (5), wherein omega represents the frequency, omega 0 is the high and low frequency band boundary frequency, R (N, omega) is the self-power spectrum density function of the friction force of the high frequency band part, the random property of the friction force is considered, the random phase is assumed, the high frequency band friction time can be calculated by taking the random phase into account, the equation of the friction force of the high frequency band part can be calculated by Fourier, the equation (0、σ1、μc、μs、μc、σ2、vs、δ、h0) can be determined by the equation of the equivalent of the low frequency, and the motion time of the equation (alpha ) can be determined by using the equation of the low frequency and the relative motion time of the equation (alpha, the equation) and the motion time of the equation (alpha) to be determined by using the equation of the equation (25) and the relative velocity to be determined by the time history of the equation of the low frequency, v) and f (N), based on genetic algorithm, solving the undetermined parameters sigma 0 and sigma 1 in equations (1) and (2), taking into account the random nature of the high-frequency friction, assuming that the high-frequency friction has a random phase spectrum, then utilizing the identified high-frequency friction self-power spectral density function, namely (5), solving the time course, namely the high-frequency friction r (t), through inverse Fourier transform, and then superposing with the low-frequency friction obtained in step S4 to obtain complete friction output;
Aiming at the low-frequency band friction force characteristic of the friction pair, introducing positive pressure input information and deforming a traditional LuGre model to obtain an implicit relation between friction force response and relative speed and positive pressure input of the friction pair;
Aiming at the high-frequency band friction characteristic of the friction pair, positive pressure input information is introduced, and the implicit relation between the friction response and the positive pressure of the friction pair is obtained by combining friction self-power spectrum assumption of a power function form;
The method comprises the following specific steps of identifying and determining the parameters to be determined of the equivalent model through friction test data so as to complete the equivalent model modeling of a specific friction pair, wherein the specific steps of the equivalent model modeling of any specific friction pair comprise:
S1, carrying out friction test on a friction auxiliary sample piece and recording a friction test related signal, S2, preprocessing the test signal, obtaining a friction force-relative motion speed, a friction force-positive pressure scatter diagram and a friction force self-power spectrum, S3, determining high-frequency-band friction force model parameters based on a least square method, S4, identifying low-frequency-band friction force model parameters based on a least square method and a genetic algorithm, and S5, overlapping to obtain a complete equivalent model.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111616885.4A CN114282441B (en) | 2021-12-27 | 2021-12-27 | An equivalent model of friction kinematic pair and its modeling method |
| PCT/CN2022/139144 WO2023125026A1 (en) | 2021-12-27 | 2022-12-14 | Friction kinematic pair equivalent model and building method therefor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111616885.4A CN114282441B (en) | 2021-12-27 | 2021-12-27 | An equivalent model of friction kinematic pair and its modeling method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114282441A CN114282441A (en) | 2022-04-05 |
| CN114282441B true CN114282441B (en) | 2025-01-14 |
Family
ID=80876380
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111616885.4A Active CN114282441B (en) | 2021-12-27 | 2021-12-27 | An equivalent model of friction kinematic pair and its modeling method |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN114282441B (en) |
| WO (1) | WO2023125026A1 (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114282441B (en) * | 2021-12-27 | 2025-01-14 | 振声(重庆)科技发展有限责任公司 | An equivalent model of friction kinematic pair and its modeling method |
| CN118088288B (en) * | 2024-04-26 | 2024-07-19 | 潍柴动力股份有限公司 | Engine oil pressure control method and related equipment |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111766198A (en) * | 2020-07-09 | 2020-10-13 | 重庆大学 | A method and device for dynamic friction test of materials based on folding pendulum |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102004016288B3 (en) * | 2004-04-02 | 2005-08-18 | Daimlerchrysler Ag | Determining friction value between vehicle tire, road involves evaluating tire vibration characteristic(s), especially frequency spectrum and/or time domain spectrum, by evaluating data using physical and/or phenomenological model approach |
| CN101907557B (en) * | 2010-07-30 | 2011-12-21 | 北京宇航系统工程研究所 | System for accurately testing friction damping |
| CN103175775A (en) * | 2013-03-12 | 2013-06-26 | 北京机械设备研究所 | Test system for friction of cylinder sleeve piston ring based on direct transmission of linear motor |
| CN106596087B (en) * | 2016-12-12 | 2019-07-05 | 山东大学 | A kind of device and method of novel achievable whole assembly Friction identification |
| CN108414105B (en) * | 2018-01-29 | 2019-12-10 | 北京航空航天大学 | A dynamic temperature measurement method for coupling simulation and experiment of dry friction pair |
| CN109214128B (en) * | 2018-10-25 | 2023-02-28 | 北京信息科技大学 | A Modeling Method for the Distribution Characteristics of Lubrication Flow Field in the Sliding Process of Wet Friction Pairs |
| CN111272535B (en) * | 2020-02-11 | 2022-08-16 | 武汉科技大学 | Fretting sliding composite friction and wear test system and operation method thereof |
| CN114282441B (en) * | 2021-12-27 | 2025-01-14 | 振声(重庆)科技发展有限责任公司 | An equivalent model of friction kinematic pair and its modeling method |
-
2021
- 2021-12-27 CN CN202111616885.4A patent/CN114282441B/en active Active
-
2022
- 2022-12-14 WO PCT/CN2022/139144 patent/WO2023125026A1/en active Application Filing
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111766198A (en) * | 2020-07-09 | 2020-10-13 | 重庆大学 | A method and device for dynamic friction test of materials based on folding pendulum |
Non-Patent Citations (1)
| Title |
|---|
| 轻载机器人动力学参数辨识中的关节摩擦力辨识;张铁;李秋奋;邹焱飚;;润滑与密封;20200715(07);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2023125026A1 (en) | 2023-07-06 |
| CN114282441A (en) | 2022-04-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114282441B (en) | An equivalent model of friction kinematic pair and its modeling method | |
| Yen et al. | Applying the self-organization feature map (SOM) algorithm to AE-based tool wear monitoring in micro-cutting | |
| Sorsa et al. | Quantitative prediction of residual stress and hardness in case-hardened steel based on the Barkhausen noise measurement | |
| Wang et al. | Vision and sound fusion-based material removal rate monitoring for abrasive belt grinding using improved LightGBM algorithm | |
| Lu et al. | Prognosis of bearing degradation using gradient variable forgetting factor RLS combined with time series model | |
| Głowacz et al. | Recognition of rotor damages in a DC motor using acoustic signals | |
| Ma et al. | Double Gaussian potential stochastic resonance method and its application in centrifugal fan blade crack detection | |
| Noman et al. | A scale independent flexible bearing health monitoring index based on time frequency manifold energy & entropy | |
| CN101598596A (en) | Analyze the particularly method and apparatus of the noise of vehicle of noise source | |
| Feng et al. | Model-based surface roughness estimation using acoustic emission signals | |
| Lu et al. | Accumulated wear degradation prediction of railway friction block considering the evolution of contact status | |
| Sun et al. | Characteristic parameter extraction of running-in attractors based on phase trajectory and grey relation analysis | |
| Hao et al. | A fractal model of acoustic emission signals in sliding friction | |
| Griffin et al. | Real-time simulation of neural network classifications from characteristics emitted by acoustic emission during horizontal single grit scratch tests | |
| Shanling et al. | Real-time rubber quality model based on CNN-LSTM deep learning theory | |
| CN105975995A (en) | Fuzzy-preference-relation-based multi-vibration-signal fusion method | |
| Hirsch et al. | A simple model for friction evolution infretting | |
| Łępicka et al. | Analysis of tribological behaviour of titanium nitride-coated stainless steel with the use of wavelet-based methods | |
| Almeida et al. | Experimental analysis of dynamic interaction between a centrifugal compressor and its casing | |
| Zhou et al. | Signal de-noising in gear pitting fault identification by an improved singular value decomposition method | |
| Cheng et al. | Convolutive blind source separation in the frequency domain of mechanical noise for gas turbines based on bounded component analysis | |
| Wang et al. | Study on weak signal feature extraction based on asymmetric hybrid bistable stochastic resonance | |
| Yee et al. | Characterization and utilization of noisy displacement signals from simple shear device using linear and kernel regression methods | |
| Chen et al. | Fast robust enhanced trend filter: A promising tool for automatically extracting high precision friction coefficient under unknown noise | |
| Zhang et al. | Intelligent fault diagnosis of rotating machine based on SVMs and EMD method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230710 Address after: 402760 No.92 Donglin Avenue, Biquan street, Bishan District, Chongqing Applicant after: Zhensheng (Chongqing) Technology Development Co.,Ltd. Address before: 400044 No. 174, positive street, Shapingba District, Chongqing Applicant before: Chongqing University |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |