A method for identification and dynamic modeling of friction coefficient of floating spline

Abstract

The present invention provides a floating spline friction coefficient identification and dynamic modeling method, which relates to the technical field of dynamic characteristic research. The present invention systematically collects and analyzes acoustic emission signals of different components in a spline system, combined with correlation analysis of static friction coefficient and dynamic friction coefficient, so as to not only comprehensively reflect the dynamic characteristics of multi-component friction coupling, but also introduces a warning threshold and an adjustment index mechanism to make the model parameter correction more adaptive and accurate, thereby significantly improving the modeling accuracy and reliability of the system.

Description

Technical Field

[0001] The invention relates to the technical field of dynamic characteristic research, and in particular to a floating spline friction coefficient identification and dynamic modeling method. Background Art

[0002] The traditional spline connection structure mainly relies on tooth meshing to transmit torque. Although it has a simple structure and is easy to manufacture, it is easily affected by problems such as wear and looseness during use, which leads to reduced transmission efficiency and shortened component life. In recent years, with the continuous improvement of mechanical system requirements for precision and reliability, floating spline systems have gradually become a research hotspot. By allowing a certain range of axial and radial displacements, floating spline systems can effectively alleviate stress concentration and improve system working stability. However, even floating spline systems face challenges such as complex friction coupling and difficulty in accurately describing dynamic characteristics in practical applications. Traditional floating spline friction analysis methods often ignore the friction coupling effect between multiple components, making it difficult to fully reflect the dynamic characteristics of the system, limiting their promotion and application in high-precision application scenarios.

[0003] In the prior art, the publication number is CN114239186A, and the name is a method and system for dynamic modeling and parameter determination of a wet friction clutch considering a spline pair. The method includes the following steps: the spline pairs of the active end and the driven end of the multi-plate wet friction clutch are equivalent to a spring damping system, and a dynamic equivalent model of the multi-plate wet friction clutch including the spline pair is constructed; based on the dynamic equivalent model, a dynamic mathematical model of the multi-plate wet friction clutch including the spline pair is constructed; the dynamic mathematical model is solved to determine the dynamic parameters of the multi-plate wet friction clutch; the dynamic parameters include torque, angular displacement, and moment of inertia. By constructing a dynamic equivalent model of the multi-plate wet friction clutch including a spline pair, the dynamic parameters of the spline connection between the inner and outer hubs of the clutch and the friction plate and the dual steel plate are solved, thereby realizing the study of the dynamic characteristics of the spline connection between the inner and outer hubs of the clutch and the friction plate and the dual steel plate;

[0004] The existing floating spline dynamics modeling methods mainly focus on the preliminary analysis of geometric parameters and material properties, but lack systematic research on the friction coupling effect of multiple components. Most of the current studies usually use simplified models in the process of modeling and parameter determination, ignoring the correlation analysis between acoustic emission signals and friction coefficients, which limits the accuracy and reliability of the model. In addition, the existing models lack dynamics and adaptability in parameter adjustment strategies and cannot effectively cope with parameter changes in actual working conditions.

[0005] The above information disclosed in the above Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide a floating spline friction coefficient identification and dynamic modeling method to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A floating spline friction coefficient identification and dynamic modeling method, the specific steps include:

[0009] Acquire the acoustic emission signal history data of the interacting components, and the static friction coefficient and the dynamic friction coefficient corresponding to the acoustic emission signal history data, wherein the interacting components include the spline shaft and the spline sleeve, and perform friction coupling correlation analysis on the acoustic emission signal history data and the corresponding static friction coefficient and dynamic friction coefficient;

[0010] The number of acquisitions in the current acquisition cycle is set to an odd number n, and the acoustic emission signal data of the interacting components in the floating spline system are collected n times. Based on the friction coupling correlation analysis, the static friction coefficient and the dynamic friction coefficient corresponding to the acoustic emission signal data in the current acquisition cycle are obtained;

[0011] Between the spline shaft and the spline sleeve, the warning thresholds of the static friction coefficient and the dynamic friction coefficient in the current acquisition cycle are determined to be Q1 and U1 respectively, and the first screening value associated with each parameter in the acoustic emission signal is set according to the warning threshold Q1, and the second screening value associated with each parameter in the acoustic emission signal is set according to the warning threshold U1. Finally, the first screening value and the second screening value are used as the main screening strategy;

[0012] Using the first screening value and the second screening value in the main screening strategy to perform hierarchical screening on the acoustic emission signal data collected n times to obtain a first screening data set and a second screening data set;

[0013] The first screening data set is analyzed and processed to generate a first evaluation coefficient, which is used to correlate and evaluate the changing trend of the static friction coefficient between the spline shaft and the spline sleeve. The second screening data set is analyzed and processed to generate a second evaluation coefficient, which is used to correlate and evaluate the changing trend of the dynamic friction coefficient between the spline shaft and the spline sleeve.

[0014] Furthermore, the first screening data set and the second screening data set, as well as the first evaluation coefficient and the second evaluation coefficient, specifically include:

[0015] Acquire the acoustic emission signal index measurement value data collected n times between the spline shaft and the spline sleeve. In each collection, if at least two of the frequency, amplitude and energy measurement values ​​are within The acoustic emission signal is included in the first screening data set if at least two of the frequency, amplitude and energy measurement values ​​are within the first screening value corresponding to the first screening value. The acoustic emission signals meeting the requirements are included in the second screening data set;

[0016] Define the acoustic emission signal marker set in the first screening data set as {a1, a2, ..., aj, ..., am}, where aj represents the index of the ajth acquisition, and am represents the index of the amth acquisition;

[0017] The acoustic emission signal marker set in the second screening data set is defined as {b1, b2, ..., bj, ..., bm}, wherein bj represents the index of the bj-th acquisition, bm represents the index of the bm-th acquisition, and am+bm≤n;

[0018] Calculate the acoustic emission signal index collected for the ajth time as follows: , the calculation formula is as follows:

[0019]

[0020] in, is the acoustic emission frequency collected at the ajth time; is the acoustic emission amplitude collected at the ajth time, is the acoustic emission energy collected for the ajth time;

[0021] Calculate the acoustic emission signal index collected for the bjth time as follows: , the calculation formula is as follows:

[0022]

[0023] in, is the acoustic emission frequency collected for the bjth time; is the acoustic emission amplitude collected at the bjth time, is the acoustic emission energy collected for the bjth time;

[0024] Define the first evaluation coefficient as , the calculation formula is as follows:

[0025]

[0026] Define the second evaluation coefficient as , the calculation formula is as follows:

[0027]

[0028] Among them, C1 and C2 are both positive terms, which are used to avoid and When the denominator is 0;

[0029] set up and The value ranges of are (0, M1) and (0, M2), M1 and M2 are both positive numbers;

[0030] when The closer it is to 0, the greater the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0031] when The closer it is to M1, the smaller the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0032] when The closer it is to 0, the greater the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve;

[0033] when The closer it is to M2, the smaller the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve is.

[0034] Furthermore, the third screening data set and the fourth screening data set, as well as the third evaluation coefficient and the fourth evaluation coefficient, specifically include:

[0035] Acquire the acoustic emission signal index measurement value data collected n times between the load transfer component and the spline shaft. In each collection, if at least two of the frequency, amplitude and energy measurement values ​​are within The acoustic emission signal is included in the third screening data set if at least two of the frequency, amplitude and energy measurement values ​​are within the corresponding third screening value. The acoustic emission signals meeting the requirements are included in the fourth screening data set;

[0036] Define the acoustic emission signal marker set in the third screening data set as {c1, c2, ..., cj, ..., cm}, where cj represents the index of the cj-th acquisition, and cm represents the index of the cm-th acquisition;

[0037] The acoustic emission signal marker set in the fourth screening data set is defined as {d1, d2, ..., dj, ..., dm}, wherein dj represents the index of the dj-th acquisition, dm represents the index of the dm-th acquisition, and cm+dm≤n;

[0038] Calculate the acoustic emission signal index collected for the cjth time as follows: , the calculation formula is as follows:

[0039]

[0040] in, is the acoustic emission frequency collected at the cjth time; is the acoustic emission amplitude collected at the cjth time, is the acoustic emission energy collected for the cjth time;

[0041] Calculate the acoustic emission signal index collected for the djth time as follows: , the calculation formula is as follows:

[0042]

[0043] in, is the acoustic emission frequency collected for the djth time; is the acoustic emission amplitude collected at the djth time, is the acoustic emission energy collected for the djth time;

[0044] Define the third evaluation coefficient as , the calculation formula is as follows:

[0045]

[0046] Define the fourth evaluation coefficient as , the calculation formula is as follows:

[0047]

[0048] Among them, C3 and C4 are both positive terms, which are used to avoid and When the denominator is 0;

[0049] set up and The value ranges of are (0, M3) and (0, M4), M3 and M4 are both positive numbers;

[0050] when The closer it is to 0, the greater the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0051] when The closer it is to M3, the smaller the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0052] when The closer it is to 0, the greater the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve;

[0053] when The closer it is to M4, the smaller the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve.

[0054] Furthermore, the static friction coefficient adjustment index is used to provide a first adjustment strategy for the warning thresholds Q1 and Q2 of the static friction coefficient, respectively, including:

[0055] The static friction coefficient adjustment index is defined as JM, and the calculation formula is as follows:

[0056]

[0057] in, , are the weight values ​​of the corresponding evaluation coefficients, ;

[0058] The value range of the static friction coefficient adjustment index JM is set to (0, R1), where R1 is a positive number, and the comparison thresholds of JM are set to r1 and r2 respectively. The closer JM is to 0, the better. The greater the change trend, the closer JM is to R1, indicating The smaller the change trend, and the value range of r1 and r2 is within (0, R1), r1<r2;

[0059] The first adjustment strategy is as follows:

[0060] When the value of JM is in the range of (0, r1), the following adjustment formula is provided for Q1:

[0061]

[0062] Among them, on the basis of the spline shaft and the spline sleeve, is the adjusted warning threshold of static friction coefficient;

[0063] When the value of JM is in the range of (r2, R1), the following adjustment formula is provided for Q2:

[0064]

[0065] Among them, between the load transfer component and the spline shaft, is the adjusted warning threshold of static friction coefficient;

[0066] The dynamic friction coefficient adjustment index is used to provide a second adjustment strategy for the warning thresholds U1 and U2 of the dynamic friction coefficient, respectively, including:

[0067] The dynamic friction coefficient adjustment index is defined as DM, and the calculation formula is as follows:

[0068]

[0069] in, , are the weight values ​​of the corresponding evaluation coefficients, ;

[0070] The value range of the static friction coefficient adjustment index DM is set to (0, H1), where H1 is a positive number, and the comparison thresholds of DM are set to h1 and h2 respectively. The closer DM is to 0, the better. The greater the change trend, the closer DM is to H1, indicating The smaller the change trend, and the value range of h1 and h2 is within (0, H1), h1<h2;

[0071] The second adjustment strategy is as follows:

[0072] When the DM value is in the range of (0, h1), the following adjustment formula is provided for U1:

[0073]

[0074] Among them, on the basis of the spline shaft and the spline sleeve, is the adjusted warning threshold of dynamic friction coefficient;

[0075] When the DM value is in the range of (h2, H1), the following adjustment formula is provided for U2:

[0076]

[0077] Among them, between the load transfer component and the spline shaft, is the adjusted static friction coefficient warning threshold.

[0078] Compared with the prior art, the beneficial effects of the present invention are as follows: by systematically collecting and analyzing the acoustic emission signals of different components in the spline system, combined with the correlation analysis of the static friction coefficient and the dynamic friction coefficient, it can not only comprehensively reflect the dynamic characteristics of the friction coupling of multiple components, but also introduce the mechanism of warning thresholds and adjustment indexes to make the model parameter correction more adaptive and accurate, thereby significantly improving the modeling accuracy and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 It is a schematic diagram of the overall method flow of the present invention. DETAILED DESCRIPTION

[0080] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0081] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0082] Embodiment 1

[0083] See also Figure 1 , the present invention provides a technical solution:

[0084] A floating spline friction coefficient identification and dynamic modeling method, the specific steps include:

[0085] Step S1: Acquire historical data of acoustic emission signals of interacting components, and static friction coefficients and dynamic friction coefficients corresponding to the historical data of acoustic emission signals, wherein the interacting components include between the spline shaft and the spline sleeve, and between the load transfer component and the spline shaft, and the acoustic emission signal includes an acoustic emission frequency parameter, an acoustic emission amplitude parameter, and an acoustic emission energy parameter, and perform friction coupling correlation analysis on the historical data of the acoustic emission signals and the corresponding static friction coefficients and dynamic friction coefficients, respectively, to obtain the A1 group of correlation analysis results between the spline shaft and the spline sleeve, and the A2 group of correlation analysis results between the load transfer component and the spline shaft;

[0086] Step S2: setting the number of acquisitions in the current acquisition cycle to an odd number n, collecting acoustic emission signal data of the interacting components in the floating spline system n times, and obtaining the static friction coefficient and dynamic friction coefficient corresponding to the acoustic emission signal data in the current acquisition cycle based on friction coupling correlation analysis;

[0087] Step S3: between the spline shaft and the spline sleeve, based on the acoustic emission signal data, the static friction coefficient and the dynamic friction coefficient, first determine the warning thresholds of the static friction coefficient and the dynamic friction coefficient in the current acquisition cycle as Q1 and U1 respectively, set the first screening value associated with each parameter in the acoustic emission signal according to the warning threshold Q1, and set the second screening value associated with each parameter in the acoustic emission signal according to the warning threshold U1, and finally, use the first screening value and the second screening value as the main screening strategy;

[0088] Step S4: between the load transfer component and the spline shaft, based on the acoustic emission signal data, the static friction coefficient and the dynamic friction coefficient, firstly, respectively determine the warning thresholds of the static friction coefficient and the dynamic friction coefficient in the current acquisition cycle as Q2 and U2, respectively, set the third screening value associated with each parameter in the acoustic emission signal according to the warning threshold Q2, and set the fourth screening value associated with each parameter in the acoustic emission signal according to the warning threshold U2, and finally, use the third screening value and the fourth screening value as the secondary screening strategy;

[0089] Step S5: using the first screening value and the second screening value in the main screening strategy to perform hierarchical screening on the acoustic emission signal data collected n times to obtain a first screening data set and a second screening data set;

[0090] Step S6: Analyze and process the first screening data set to generate a first evaluation coefficient, which is used to correlate and evaluate the change trend of the static friction coefficient between the spline shaft and the spline sleeve; analyze and process the second screening data set to generate a second evaluation coefficient, which is used to correlate and evaluate the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve;

[0091] Step S7: In the current collection cycle, the acoustic emission signal data collected n times are graded and screened using the third screening value and the fourth screening value in the secondary screening strategy to obtain a third screening data set and a fourth screening data set;

[0092] Step S8: Analyze and process the third screening data set to generate a third evaluation coefficient, which is used to correlate and evaluate the change trend of the static friction coefficient between the load transfer component and the spline shaft; analyze and process the fourth screening data set to generate a fourth evaluation coefficient, which is used to correlate and evaluate the change trend of the dynamic friction coefficient between the load transfer component and the spline shaft;

[0093] Step S9: obtaining the first evaluation coefficient and the third evaluation coefficient, and performing analysis and processing to generate a static friction coefficient adjustment index; obtaining the second evaluation coefficient and the fourth evaluation coefficient, and performing analysis and processing to generate a dynamic friction coefficient adjustment index;

[0094] Step S10: Select the Coulomb friction model as the friction torque model, and adjust the index by combining the normal force and the static friction coefficient to correct the static friction torque; adjust the index by combining the normal force and the dynamic friction coefficient to correct the dynamic friction torque; couple the corrected friction torque model with the dynamic equation of the floating spline system to form a complete floating spline dynamic model;

[0095] Step S11: Using the static friction coefficient adjustment index, provide a first adjustment strategy for the warning thresholds Q1 and Q2 of the static friction coefficient, and obtain the adjusted warning thresholds in turn. , At the same time, the dynamic friction coefficient adjustment index is used to provide a second adjustment strategy for the warning thresholds U1 and U2 of the dynamic friction coefficient, and the adjusted warning thresholds are obtained in turn. , , the adjusted warning threshold is input into the corresponding position in step S3 and step S4 of the next collection cycle for updating and replacement.

[0096] S10.1: Select the Coulomb friction model as the basic model, obtain the initial values ​​of the static friction coefficient and the dynamic friction coefficient through actual measurement or reference, and calculate the normal force based on the system load and contact geometry;

[0097] Combine the normal force and the friction coefficient to adjust the index and correct the static friction moment; Combine the normal force and the friction coefficient to adjust the index and correct the dynamic friction moment;

[0098] The modified friction torque model is coupled with the dynamic equation of the floating spline system to form a complete floating spline dynamic model;

[0099] S10.1.1: Determine the basic dynamic equations of the floating spline system, including but not limited to the equations of motion, moment balance equations, and energy conservation equations;

[0100] S10.1.2: Introduce the friction torque term in the modified friction torque model into the dynamic equation, considering its point of action and direction in the system;

[0101] S10.1.3: Ensure the consistency of the friction torque model with the dynamic equations in mathematical form, and perform mathematical transformations and simplifications;

[0102] S10.1.4: Solve the coupled dynamic equations numerically or analytically to obtain the dynamic response of the system;

[0103] S10.2: Perform simulation calculation on the floating spline dynamics model to verify the accuracy and effectiveness of the model;

[0104] S10.2.1: Select simulation software or programming environment and input parameters and initial conditions of floating spline dynamic model;

[0105] S10.2.2: Run the simulation program and record the dynamic response of the system under different working conditions, such as displacement, velocity, acceleration, and friction torque;

[0106] S10.2.3: Compare simulation results with experimental data or theoretical predictions to evaluate the accuracy of the model;

[0107] S10.2.4: Adjust model parameters based on simulation results until the simulation results are highly consistent with the actual system behavior;

[0108] S10.3: Based on the floating spline dynamics model, propose optimization design suggestions and improvement strategies to guide the design and maintenance of floating spline systems in actual engineering applications;

[0109] S10.3.1: Analyze simulation results to identify key parameters and design bottlenecks in the system;

[0110] S10.3.2: Propose targeted design optimization suggestions, including material selection, structural improvement, and lubrication method optimization;

[0111] S10.3.3: Develop a system maintenance strategy, including regular inspection, lubrication management, and fault warning;

[0112] S10.3.4: Document the optimization design suggestions and improvement strategies for reference and implementation by engineering and technical personnel.

[0113] Further explanation: Acquisition of acoustic emission signals of interacting components in n-fold floating spline system, as well as static friction coefficient and dynamic friction coefficient, the acquisition steps are as follows:

[0114] 1) According to the structural characteristics of the floating spline system, a high-precision acoustic emission sensor is selected. In this embodiment, a piezoelectric acoustic emission sensor is used. The sensor is installed between the spline shaft and the spline sleeve, and at the corresponding installation positions of the contact surface between the load transfer component and the spline shaft. The installation positions are determined according to the evaluation of the expert group;

[0115] Use a standard sound source to calibrate the acoustic emission sensor to ensure its measurement accuracy; during the calibration process, record the sensitivity and frequency response characteristics of the sensor;

[0116] 2) In a laboratory environment, control the temperature and humidity environmental parameters to ensure that the external environment has minimal impact on the acoustic emission signal during data collection;

[0117] The acquisition frequency of the acoustic emission signal was set to 1 MHz, the sampling rate to 10 MS / s, and the acquisition time to 10 s to ensure that all acoustic emission characteristics between interacting components could be captured;

[0118] According to the actual use, the relative movement speed between the spline shaft and the spline sleeve is set to 0.1m / s, and the transmission force of the load transmission component is set to 100N.

[0119] Turn on the data acquisition system, and record the acoustic emission signals between the spline shaft and the spline sleeve, and between the load transfer component and the spline shaft under different working conditions; during the acquisition process, record the acoustic emission frequency parameters, acoustic emission amplitude parameters, and acoustic emission energy parameters;

[0120] The acoustic emission frequency parameter is marked as f: the main frequency of the acoustic emission signal, in Hz;

[0121] The acoustic emission amplitude parameter is marked as A: the peak amplitude of the acoustic emission signal, in V;

[0122] The acoustic emission energy parameter is marked as E: the total energy of the acoustic emission signal during the acquisition time, in units of V^2·s;

[0123] While acquiring the acoustic emission signal, the static friction coefficient and the dynamic friction coefficient are measured;

[0124] The static and dynamic friction coefficients between the spline shaft and the spline hub, and between the spline shaft and the load transmission component are measured using a predetermined method (standard friction tester);

[0125] Mark the measured static friction coefficient and dynamic friction coefficient with the corresponding acoustic emission signal data in a one-to-one correspondence;

[0126] 4) Use a bandpass filter to filter the collected acoustic emission signal data to remove high-frequency noise and low-frequency interference, and only retain the valid signals within the target frequency range;

[0127] The frequency spectrum of the filtered acoustic emission signal data is analyzed by using fast Fourier transform (FFT) to obtain the acoustic emission signal index, which includes the extraction of characteristic parameters of acoustic emission frequency f, acoustic emission amplitude A and acoustic emission energy E;

[0128] Under different static friction states and dynamic friction states, the acoustic emission signal indicators collected each time are stored in a database to form historical data of the acoustic emission signal.

[0129] Further explanation: friction coupling correlation analysis is performed on the historical data of acoustic emission signals and the corresponding static friction coefficient and dynamic friction coefficient, and the A1 group correlation analysis results between the spline shaft and the spline sleeve, and the A2 group correlation analysis results between the load transfer component and the spline shaft are obtained, which specifically include:

[0130] The pre-processed acoustic emission signal data is used to conduct friction coupling correlation analysis with the static friction coefficient and the dynamic friction coefficient;

[0131] The number of the current collection cycle is marked to form a set {1, 2, ..., i, ..., n}, where i represents the index of the i-th collection, and n represents the index of the current n-th collection. The acoustic emission signal index of the i-th collection between the spline shaft and the spline sleeve is set to ,definition The calculation formula is:

[0132]

[0133] in, is the acoustic emission frequency collected for the i-th time; is the acoustic emission amplitude collected at the i-th time, is the acoustic emission energy collected for the i-th time;

[0134] , , is the weight of the corresponding parameter, and ,These weights were determined by an expert group through experimental data;

[0135] 1) Correlation analysis of static friction coefficient:

[0136] Set the acoustic emission signal index for the i-th collection The corresponding static friction coefficient is ;

[0137] Using linear regression model To analyze, and are model parameters, determined by the least squares method and Parameter value;

[0138] 2) Correlation analysis of dynamic friction coefficient:

[0139] Set the acoustic emission signal index for the i-th collection The corresponding dynamic friction coefficient is ;

[0140] Using multiple regression model To analyze, , and are model parameters, Indicates the rate of change of the acoustic emission signal index, determined by the least squares method , and Parameter value;

[0141] The above 1) and 2) correlation analysis results are used as the A1 group correlation analysis results applied to the spline shaft and the spline sleeve;

[0142] 3) Set the acoustic emission signal index collected for the i-th time between the load transfer component and the spline shaft to ,definition The calculation formula is:

[0143]

[0144] in, is the acoustic emission frequency collected for the i-th time; is the acoustic emission amplitude collected at the i-th time, is the acoustic emission energy collected for the i-th time;

[0145] , , is the weight of the corresponding parameter, and ,These weights were determined by an expert group through experimental data;

[0146] 4) Correlation analysis of static friction coefficient:

[0147] Set the acoustic emission signal index for the i-th collection The corresponding static friction coefficient is ;

[0148] Using linear regression model To analyze, and are model parameters, determined by the least squares method and Parameter value;

[0149] 5) Correlation analysis of dynamic friction coefficient:

[0150] Set the acoustic emission signal index for the i-th collection The corresponding dynamic friction coefficient is ;

[0151] Using multiple regression model To analyze, , and are model parameters, Indicates the rate of change of the acoustic emission signal index, determined by the least squares method , and Parameter value;

[0152] The above 4) and 5) correlation analysis results are used as the A2 group of correlation analysis results applied between the load transmission component and the spline shaft.

[0153] Further explanation: the first screening value and the second screening value are used as the main screening strategy, and the third screening value and the fourth screening value are used as the secondary screening strategy, specifically including:

[0154] In the current acquisition cycle, the elastic modulus and Poisson's ratio of the spline shaft, the spline sleeve and the load transfer component are measured, and the corresponding contact model is selected according to the contact type between the spline shaft and the spline sleeve, wherein the contact type includes line contact or surface contact, and the contact model includes Hertz contact model and elastic-plastic contact model;

[0155] According to the determined contact model, the average values ​​of the static friction coefficient and the dynamic friction coefficient between the spline shaft and the spline sleeve are determined and marked as and , and the mean values ​​of the static and dynamic friction coefficients between the load transfer component and the spline shaft, respectively, are marked as and ;

[0156] 1.1) According to the correlation analysis results of group A1, the warning thresholds of static friction coefficient and dynamic friction coefficient are determined as Q1 and U1 respectively;

[0157] The threshold calculation formula obtained through statistical analysis is:

[0158]

[0159]

[0160] in, and are the average values ​​of the static friction coefficient and the dynamic friction coefficient between the spline shaft and the spline sleeve, and are the standard deviations of the static friction coefficient and dynamic friction coefficient between the spline shaft and the spline sleeve, and is the empirical coefficient; and Determined by an expert group through experimental data, no further elaboration is given;

[0161] According to the warning threshold Q1 of the static friction coefficient, the first screening value of the frequency, amplitude and energy in the acoustic emission signal index is set. The calculation formula of the first screening value is:

[0162]

[0163] in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold Q1 into the first screening value of the corresponding acoustic emission parameter, , , are the first screening values ​​of frequency, amplitude and energy, respectively; , and Determined by an expert group through experimental data, no further elaboration is given;

[0164] According to the warning threshold value U1 of the dynamic friction coefficient, the second screening value of the frequency, amplitude and energy in the acoustic emission signal index is set;

[0165] The calculation formula for the second screening value is:

[0166]

[0167] in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold U1 into the second screening value of the corresponding acoustic emission parameter, , , are the second screening values ​​of frequency, amplitude and energy respectively; , and Determined by an expert group through experimental data, no further elaboration is given;

[0168] The first filter value , , and the second filter value , , Serves as the basis for a master screening strategy;

[0169] 1.2) According to the correlation analysis results of group A2, the warning thresholds of static friction coefficient and dynamic friction coefficient are determined as Q2 and U2 respectively;

[0170] The threshold calculation formula obtained through statistical analysis is:

[0171]

[0172]

[0173] in, and are the average values ​​of the static friction coefficient and the dynamic friction coefficient between the load transfer component and the spline shaft, and are the standard deviations of the static friction coefficient and the dynamic friction coefficient between the load transfer component and the spline shaft, and is the empirical coefficient; and Determined by an expert group through experimental data, no further elaboration is given;

[0174] According to the warning threshold Q2 of the static friction coefficient, the third screening value of the frequency, amplitude and energy in the acoustic emission signal index is set. The calculation formula of the third screening value is:

[0175]

[0176] in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold Q2 into the first screening value of the corresponding acoustic emission parameter, , , are the third screening values ​​of frequency, amplitude and energy respectively; , and Determined by an expert group through experimental data, no further elaboration is given;

[0177] According to the warning threshold value U2 of the dynamic friction coefficient, the fourth screening value of the frequency, amplitude and energy in the acoustic emission signal index is set;

[0178] The calculation formula for the fourth screening value is:

[0179]

[0180] in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold U2 into the second screening value of the corresponding acoustic emission parameter, , , are the fourth screening values ​​of frequency, amplitude and energy, respectively; , and Determined by an expert group through experimental data, no further elaboration is given;

[0181] The third filter value , , and the fourth filter value , , Serves as the basis for a secondary screening strategy.

[0182] Further explanation: the first screening data set and the second screening data set, as well as the first evaluation coefficient and the second evaluation coefficient, specifically include:

[0183] Acquire the acoustic emission signal index measurement value data collected n times between the spline shaft and the spline sleeve. In each collection, if at least two of the frequency, amplitude and energy measurement values ​​are within The acoustic emission signal is included in the first screening data set if at least two of the frequency, amplitude and energy measurement values ​​are within the first screening value corresponding to the first screening value. The acoustic emission signals meeting the requirements are included in the second screening data set;

[0184] Define the acoustic emission signal marker set in the first screening data set as {a1, a2, ..., aj, ..., am}, where aj represents the index of the ajth acquisition, and am represents the index of the amth acquisition;

[0185] The acoustic emission signal marker set in the second screening data set is defined as {b1, b2, ..., bj, ..., bm}, wherein bj represents the index of the bj-th acquisition, bm represents the index of the bm-th acquisition, and am+bm≤n;

[0186] Calculate the acoustic emission signal index collected for the ajth time as follows: , the calculation formula is as follows:

[0187]

[0188] in, is the acoustic emission frequency collected at the ajth time; is the acoustic emission amplitude collected at the ajth time, is the acoustic emission energy collected for the ajth time;

[0189] Calculate the acoustic emission signal index collected for the bjth time as follows: , the calculation formula is as follows:

[0190]

[0191] in, is the acoustic emission frequency collected for the bjth time; is the acoustic emission amplitude collected at the bjth time, is the acoustic emission energy collected for the bjth time;

[0192] Define the first evaluation coefficient as , the calculation formula is as follows:

[0193]

[0194] Define the second evaluation coefficient as , the calculation formula is as follows:

[0195]

[0196] Among them, C1 and C2 are both positive terms, which are used to avoid and When the denominator is 0;

[0197] set up and The value ranges of are (0, M1) and (0, M2), M1 and M2 are both positive numbers;

[0198] when The closer it is to 0, the greater the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0199] when The closer it is to M1, the smaller the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0200] when The closer it is to 0, the greater the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve;

[0201] when The closer it is to M2, the smaller the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve is.

[0202] Further explanation: the third screening data set and the fourth screening data set, as well as the third evaluation coefficient and the fourth evaluation coefficient, specifically include:

[0203] Acquire the acoustic emission signal index measurement value data collected n times between the load transfer component and the spline shaft. In each collection, if at least two of the frequency, amplitude and energy measurement values ​​are within The acoustic emission signal is included in the third screening data set if at least two of the frequency, amplitude and energy measurement values ​​are within the corresponding third screening value. The acoustic emission signals meeting the requirements are included in the fourth screening data set;

[0204] Define the acoustic emission signal marker set in the third screening data set as {c1, c2, ..., cj, ..., cm}, where cj represents the index of the cj-th acquisition, and cm represents the index of the cm-th acquisition;

[0205] The acoustic emission signal marker set in the fourth screening data set is defined as {d1, d2, ..., dj, ..., dm}, wherein dj represents the index of the dj-th acquisition, dm represents the index of the dm-th acquisition, and cm+dm≤n;

[0206] Calculate the acoustic emission signal index collected for the cjth time as follows: , the calculation formula is as follows:

[0207]

[0208] in, is the acoustic emission frequency collected at the cjth time; is the acoustic emission amplitude collected at the cjth time, is the acoustic emission energy collected for the cjth time;

[0209] Calculate the acoustic emission signal index collected for the djth time as follows: , the calculation formula is as follows:

[0210]

[0211] in, is the acoustic emission frequency collected for the djth time; is the acoustic emission amplitude collected at the djth time, is the acoustic emission energy collected for the djth time;

[0212] Define the third evaluation coefficient as , the calculation formula is as follows:

[0213]

[0214] Define the fourth evaluation coefficient as , the calculation formula is as follows:

[0215]

[0216] Among them, C3 and C4 are both positive terms, which are used to avoid and When the denominator is 0;

[0217] set up and The value ranges of are (0, M3) and (0, M4), M3 and M4 are both positive numbers;

[0218] when The closer it is to 0, the greater the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0219] when The closer it is to M3, the smaller the trend of the static friction coefficient between the spline shaft and the spline sleeve;

[0220] when The closer it is to 0, the greater the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve;

[0221] when The closer it is to M4, the smaller the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve.

[0222] Further explanation: using the static friction coefficient adjustment index, a first adjustment strategy is provided for the warning thresholds Q1 and Q2 of the static friction coefficient, specifically including:

[0223] The static friction coefficient adjustment index is defined as JM, and the calculation formula is as follows:

[0224]

[0225] in, , are the weight values ​​of the corresponding evaluation coefficients, ,and , Determined by the expert group through experimental data, no further elaboration is given;

[0226] The value range of the static friction coefficient adjustment index JM is set to (0, R1), where R1 is a positive number, and the comparison thresholds of JM are set to r1 and r2 respectively. The closer JM is to 0, the better. The greater the change trend, the closer JM is to R1, indicating The smaller the change trend, and the value range of r1 and r2 is within (0, R1), ; The specific values ​​of r1 and r2 are determined by the expert group through experimental data and will not be elaborated on here;

[0227] Determine the initial values ​​of the static and dynamic friction coefficients between the interacting parts by actual measurements and calculate the normal force based on the contact geometry;

[0228] The static friction torque correction rule is as follows:

[0229] The initial value and static friction torque between the spline shaft and the spline sleeve are defined as , The initial value and static friction torque between the load transfer component and the spline shaft are , ;

[0230] When JM takes the value in the range of (0, r1), the variation trend of the friction torque is in the high range;

[0231] Corrected static friction torque between spline shaft and spline hub The ratio is the initial value of static friction torque 75%-100%, that is ,in is the correction factor, The value range is between 0.75 and 1.0;

[0232] Corrected static friction torque between the load transmission component and the spline shaft The ratio is the initial value of static friction torque 73%-100%, that is ,in is the correction factor, The value range is between 0.73 and 1.0;

[0233] When the JM value is in the range of [r1, r2], the variation trend of the friction torque is in the medium range;

[0234] Corrected static friction torque between spline shaft and spline hub The ratio is the initial value of static friction torque 50%-75%, The value range is between 0.5 and 0.75;

[0235] Corrected static friction torque between the load transmission component and the spline shaft The ratio is the initial value of static friction torque 53%-69%, The value range is between 0.53 and 0.69;

[0236] When JM takes the value in the range of (r2, R1), the variation trend of the friction torque is in the low range;

[0237] Corrected static friction torque between spline shaft and spline hub The ratio is the initial value of static friction torque 25%-50%, The value range is between 0.25 and 0.5;

[0238] Corrected static friction torque between the load transmission component and the spline shaft The ratio is the initial value of static friction torque 24%-53%, The value range is between 0.24 and 0.53;

[0239] The first adjustment strategy is as follows:

[0240] When the value of JM is in the range of (0, r1), the following adjustment formula is provided for Q1:

[0241]

[0242] Among them, on the basis of the spline shaft and the spline sleeve, is the adjusted warning threshold of static friction coefficient;

[0243] When the value of JM is in the range of (r2, R1), the following adjustment formula is provided for Q2:

[0244]

[0245] Among them, between the load transfer component and the spline shaft, is the adjusted warning threshold of static friction coefficient;

[0246] The dynamic friction coefficient adjustment index is used to provide a second adjustment strategy for the warning thresholds U1 and U2 of the dynamic friction coefficient, respectively, including:

[0247] The dynamic friction coefficient adjustment index is defined as DM, and the calculation formula is as follows:

[0248]

[0249] in, , are the weight values ​​of the corresponding evaluation coefficients, ,and , Determined by the expert group through experimental data, no further elaboration is given;

[0250] The value range of the static friction coefficient adjustment index DM is set to (0, H1), where H1 is a positive number, and the comparison thresholds of DM are set to h1 and h2 respectively. The closer DM is to 0, the better. The greater the change trend, the closer DM is to H1, indicating The smaller the change trend, and the range of h1 and h2 is within (0, H1), h1<h2; the specific values ​​of h1 and h2 are determined by the expert group through experimental data and will not be elaborated;

[0251] The correction rule for dynamic friction torque is as follows:

[0252] The initial value and dynamic friction torque between the spline shaft and the spline sleeve are defined as , The initial value and dynamic friction torque between the load transfer component and the spline shaft are , ;

[0253] When DM takes the value in the range of (0, h1), the variation trend of the system dynamic friction torque is high level;

[0254] Corrected dynamic friction torque between spline shaft and spline sleeve The ratio is the initial value of dynamic friction torque 75%-100%, that is ,in The value range is between 0.75 and 1.0;

[0255] Correction of dynamic friction torque between load transmission components and spline shaft The ratio is the initial value of dynamic friction torque 74%-100%, that is ,in The value range is between 0.74 and 1.0;

[0256] When the DM value is in the range of [h1,h2], the change trend of the system dynamic friction torque is medium level;

[0257] Corrected dynamic friction torque between spline shaft and spline sleeve The ratio is the initial value of dynamic friction torque 58%-73% of The value range is between 0.58 and 0.73;

[0258] Correction of dynamic friction torque between load transmission components and spline shaft The ratio is the initial value of dynamic friction torque 47%-65% of The value range is between 0.47 and 0.65;

[0259] When the DM value is in the range of (h2, H1), the change trend of the system dynamic friction torque is low level;

[0260] Corrected dynamic friction torque between spline shaft and spline sleeve The ratio is the initial value of dynamic friction torque 25%-46% of The value range is between 0.25 and 0.46;

[0261] Correction of dynamic friction torque between load transmission components and spline shaft The ratio is the initial value of dynamic friction torque 17%-38% of The value range is between 0.17 and 0.38;

[0262] The second adjustment strategy is as follows:

[0263] When the DM value is in the range of (0, h1), the following adjustment formula is provided for U1:

[0264]

[0265] Among them, on the basis of the spline shaft and the spline sleeve, is the adjusted warning threshold of dynamic friction coefficient;

[0266] When the DM value is in the range of (h2, H1), the following adjustment formula is provided for U2:

[0267]

[0268] Among them, between the load transfer component and the spline shaft, is the adjusted static friction coefficient warning threshold.

[0269] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0270] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0271] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0272] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A floating spline friction coefficient identification and dynamic modeling method, characterized in that: The specific steps include: Acquire the acoustic emission signal history data of the interacting components, and the static friction coefficient and the dynamic friction coefficient corresponding to the acoustic emission signal history data, wherein the interacting components include between the spline shaft and the spline sleeve, and between the load transfer component and the spline shaft, and perform friction coupling correlation analysis on the acoustic emission signal history data and the corresponding static friction coefficient and dynamic friction coefficient respectively; The number of acquisitions in the current acquisition cycle is set to an odd number n, and the acoustic emission signal data of the interacting components in the floating spline system are collected n times. Based on the friction coupling correlation analysis, the static friction coefficient and the dynamic friction coefficient corresponding to the acoustic emission signal data in the current acquisition cycle are obtained; Between the spline shaft and the spline sleeve, the warning thresholds of the static friction coefficient and the dynamic friction coefficient in the current acquisition cycle are determined to be Q1 and U1 respectively, and the first screening value associated with each parameter in the acoustic emission signal is set according to the warning threshold Q1, and the second screening value associated with each parameter in the acoustic emission signal is set according to the warning threshold U1. Finally, the first screening value and the second screening value are used as the main screening strategy; Between the load transfer component and the spline shaft, the warning threshold of the static friction coefficient in the current acquisition cycle is determined to be Q2, and the third screening value associated with each parameter in the acoustic emission signal is set according to the warning threshold Q2. Finally, the third screening value is used as a secondary screening strategy; Using the first screening value and the second screening value in the main screening strategy to perform hierarchical screening on the acoustic emission signal data collected n times to obtain a first screening data set and a second screening data set; The acoustic emission signal data collected n times are graded and screened using the third screening value in the secondary screening strategy to obtain a third screening data set; the third screening data set is analyzed and processed to generate a third evaluation coefficient, which is used to correlate and evaluate the change trend of the static friction coefficient between the load transfer component and the spline shaft; Analyze and process the first screening data set to generate a first evaluation coefficient, the first evaluation coefficient is used to correlate and evaluate the change trend of the static friction coefficient between the spline shaft and the spline sleeve, analyze and process the second screening data set to generate a second evaluation coefficient, the second evaluation coefficient is used to correlate and evaluate the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve; The first evaluation coefficient and the third evaluation coefficient are obtained, analyzed and processed, and a static friction coefficient adjustment index is generated. The static friction coefficient adjustment index is used to provide a first adjustment strategy for the warning thresholds Q1 and Q2 of the static friction coefficient, respectively, specifically including: Define the static friction coefficient adjustment index as JM, set the value range of the static friction coefficient adjustment index JM to (0, R1), where R1 is a positive number, and set the two comparison thresholds of JM to r1 and r2 respectively. Use the static friction coefficient adjustment index to provide the first adjustment strategy for the warning thresholds Q1 and Q2 of the static friction coefficient, and obtain the adjusted warning thresholds in turn. , ; The first adjustment strategy is as follows: When the value of JM is in the range of (0, r1), the following adjustment formula is provided for Q1: ； in, is the third evaluation coefficient; is the first evaluation coefficient; based on the spline shaft and spline sleeve, is the adjusted static friction coefficient warning threshold; When JM is in the range of [r1, r2], Q1 and Q2 remain unchanged; When the value of JM is in the range of (r2, R1), the following adjustment formula is provided for Q2: ； Among them, between the load transfer component and the spline shaft, is the adjusted static friction coefficient warning threshold.

2. A floating spline friction coefficient identification and dynamic modeling method according to claim 1, characterized in that: The acoustic emission signal includes an acoustic emission frequency parameter, an acoustic emission amplitude parameter and an acoustic emission energy parameter, and the A1 group of correlation analysis results between the spline shaft and the spline sleeve, and the A2 group of correlation analysis results between the load transfer component and the spline shaft are obtained respectively; Acquisition of acoustic emission signal data of the interacting components in the n-fold floating spline system, as well as static friction coefficient and dynamic friction coefficient, the acquisition steps are as follows: The acoustic emission frequency parameter is marked as f, the acoustic emission amplitude parameter is marked as A, and the acoustic emission energy parameter is marked as E. While acquiring the acoustic emission signal, the static friction coefficient and the dynamic friction coefficient are measured; Mark the measured static friction coefficient and dynamic friction coefficient with the corresponding acoustic emission signal data in a one-to-one correspondence; A bandpass filter is used to filter the collected acoustic emission signal data; The filtered acoustic emission signal data is subjected to spectrum analysis using fast Fourier transform to obtain acoustic emission signal indicators, which include extracted characteristic parameters of acoustic emission frequency f, acoustic emission amplitude A and acoustic emission energy E; Under different static friction states and dynamic friction states, the acoustic emission signals collected each time are stored in a database to form historical data of the acoustic emission signals.

3. A floating spline friction coefficient identification and dynamic modeling method according to claim 2, characterized in that: The historical data of acoustic emission signals are subjected to friction coupling correlation analysis with the corresponding static friction coefficient and dynamic friction coefficient, and the A1 group correlation analysis results between the spline shaft and the spline sleeve, and the A2 group correlation analysis results between the load transfer component and the spline shaft are obtained, including: Mark the number of the current collection cycle to form a set {1, 2, ..., i, ..., n}, where i represents the index of the i-th collection and n represents the index of the current n-th collection; The acoustic emission signal index collected for the i-th time between the spline shaft and the spline sleeve is set as ,definition The calculation formula is: ； in, is the acoustic emission frequency collected for the i-th time; is the acoustic emission amplitude collected at the i-th time, is the acoustic emission energy collected for the i-th time; , , is the weight of the corresponding parameter, and ; 1) Correlation analysis of static friction coefficient: Set the acoustic emission signal index for the i-th collection The corresponding static friction coefficient is ; Using linear regression model To analyze, and are model parameters, determined by the least squares method and Parameter value; 2) Correlation analysis of dynamic friction coefficient: Set the acoustic emission signal index for the i-th collection The corresponding dynamic friction coefficient is ; Using multiple regression model To analyze, , and are model parameters, Indicates the rate of change of the acoustic emission signal index, determined by the least squares method , and Parameter value; The above 1) and 2) correlation analysis results are used as the A1 group correlation analysis results applied to the spline shaft and the spline sleeve; 3) Set the acoustic emission signal index collected for the i-th time between the load transfer component and the spline shaft to ,definition The calculation formula is: ； in, is the acoustic emission frequency collected for the i-th time; is the acoustic emission amplitude collected at the i-th time, is the acoustic emission energy collected for the i-th time; , , is the weight of the corresponding parameter, and ; 4) Correlation analysis of static friction coefficient: Set the acoustic emission signal index for the i-th collection The corresponding static friction coefficient is ; Using linear regression model To analyze, and are model parameters, determined by the least squares method and Parameter value; 5) Correlation analysis of dynamic friction coefficient: Set the acoustic emission signal index for the i-th collection The corresponding dynamic friction coefficient is ; Using multiple regression model To analyze, , and are model parameters, Indicates the rate of change of the acoustic emission signal index, determined by the least squares method , and Parameter value; The above 4) and 5) correlation analysis results are used as the A2 group of correlation analysis results applied between the load transmission component and the spline shaft.

4. A floating spline friction coefficient identification and dynamic modeling method according to claim 3, characterized in that: The first screening value and the second screening value are used as the main screening strategy, specifically including: Determine the average values ​​of the static friction coefficient and the dynamic friction coefficient between the spline shaft and the spline sleeve, and mark them as and , and the mean values ​​of the static and dynamic friction coefficients between the load transfer component and the spline shaft, respectively, are marked as and ; 1.1) According to the correlation analysis results of group A1, the warning thresholds of static friction coefficient and dynamic friction coefficient are determined as Q1 and U1 respectively; According to the warning threshold Q1 of the static friction coefficient, the first screening value of the frequency, amplitude and energy in the acoustic emission signal index is set. The calculation formula of the first screening value is: ； in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold Q1 into the first screening value of the corresponding acoustic emission parameter, , , are the first screening values ​​of frequency, amplitude and energy, respectively; According to the warning threshold value U1 of the dynamic friction coefficient, the second screening value of the frequency, amplitude and energy in the acoustic emission signal index is set; The calculation formula for the second screening value is: ； in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold U1 into the second screening value of the corresponding acoustic emission parameter, , , are the second screening values ​​of frequency, amplitude and energy respectively; The first filter value , , and the second filter value , , Serves as the basis for a master screening strategy.

5. A floating spline friction coefficient identification and dynamic modeling method according to claim 4, characterized in that: Between the load transfer component and the spline shaft, it also includes determining the warning threshold value of the dynamic friction coefficient in the current acquisition cycle as U2, and setting the fourth screening value associated with each parameter in the acoustic emission signal according to the warning threshold value U2, and using the fourth screening value as a secondary screening strategy; The third screening value and the fourth screening value are used as the secondary screening strategy, specifically including: 1.2) According to the correlation analysis results of group A2, the warning thresholds of static friction coefficient and dynamic friction coefficient are determined as Q2 and U2 respectively; According to the warning threshold Q2 of the static friction coefficient, the third screening value of the frequency, amplitude and energy in the acoustic emission signal index is set. The calculation formula of the third screening value is: ； in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold Q2 into the first screening value of the corresponding acoustic emission parameter, , , are the third screening values ​​of frequency, amplitude and energy respectively; According to the warning threshold value U2 of the dynamic friction coefficient, the fourth screening value of the frequency, amplitude and energy in the acoustic emission signal index is set; The calculation formula for the fourth screening value is: ； in, , and is the proportional coefficient of frequency, amplitude and energy, which is used to convert the warning threshold U2 into the second screening value of the corresponding acoustic emission parameter, , , are the fourth screening values ​​of frequency, amplitude and energy, respectively; The third filter value , , and the fourth filter value , , Serves as the basis for a secondary screening strategy.

6. A floating spline friction coefficient identification and dynamic modeling method according to claim 5, characterized in that: The first screening data set and the second screening data set, as well as the first evaluation coefficient and the second evaluation coefficient, specifically include: Define the acoustic emission signal marker set in the first screening data set as {a1, a2, ..., aj, ..., am}, where aj represents the index of the ajth acquisition, and am represents the index of the amth acquisition; The acoustic emission signal marker set in the second screening data set is defined as {b1, b2, ..., bj, ..., bm}, wherein bj represents the index of the bj-th acquisition, bm represents the index of the bm-th acquisition, and am+bm≤n; Calculate the acoustic emission signal index collected for the ajth time as follows: , the calculation formula is as follows: ； in, is the acoustic emission frequency collected at the ajth time; is the acoustic emission amplitude collected at the ajth time, is the acoustic emission energy collected for the ajth time; Calculate the acoustic emission signal index collected for the bjth time as follows: , the calculation formula is as follows: ； in, is the acoustic emission frequency collected for the bjth time; is the acoustic emission amplitude collected at the bjth time, is the acoustic emission energy collected for the bjth time; Define the first evaluation coefficient as , the calculation formula is as follows: ； Define the second evaluation coefficient as , the calculation formula is as follows: ； Among them, C1 and C2 are both positive terms, which are used to avoid and When the denominator is 0; set up and The value ranges of are (0, M1) and (0, M2), M1 and M2 are both positive numbers; when The closer it is to 0, the greater the trend of the static friction coefficient between the spline shaft and the spline sleeve; when The closer it is to M1, the smaller the trend of the static friction coefficient between the spline shaft and the spline sleeve; when The closer it is to 0, the greater the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve; when The closer it is to M2, the smaller the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve is.

7. A floating spline friction coefficient identification and dynamic modeling method according to claim 6, characterized in that: In the current collection cycle, the acoustic emission signal data collected n times are graded and screened using the third screening value and the fourth screening value in the secondary screening strategy to obtain a third screening data set and a fourth screening data set; The third screening data set and the fourth screening data set, as well as the third evaluation coefficient and the fourth evaluation coefficient, specifically include: Define the acoustic emission signal marker set in the third screening data set as {c1, c2, ..., cj, ..., cm}, where cj represents the index of the cj-th acquisition, and cm represents the index of the cm-th acquisition; The acoustic emission signal marker set in the fourth screening data set is defined as {d1, d2, ..., dj, ..., dm}, wherein dj represents the index of the dj-th acquisition, dm represents the index of the dm-th acquisition, and cm+dm≤n; Calculate the acoustic emission signal index collected for the cjth time as follows: , the calculation formula is as follows: ； in, is the acoustic emission frequency collected at the cjth time; is the acoustic emission amplitude collected at the cjth time, is the acoustic emission energy collected for the cjth time; Calculate the acoustic emission signal index collected for the djth time as follows: , the calculation formula is as follows: ； in, is the acoustic emission frequency collected for the djth time; is the acoustic emission amplitude collected at the djth time, is the acoustic emission energy collected for the djth time; Analyze and process the fourth screening data set to generate a fourth evaluation coefficient, where the fourth evaluation coefficient is used to correlate and evaluate a change trend of a dynamic friction coefficient between the load transfer component and the spline shaft; Define the third evaluation coefficient as , the calculation formula is as follows: ； Define the fourth evaluation coefficient as , the calculation formula is as follows: ； Among them, C3 and C4 are both positive terms, which are used to avoid and When the denominator is 0; set up and The value ranges of are (0, M3) and (0, M4), M3 and M4 are both positive numbers; when The closer it is to 0, the greater the trend of the static friction coefficient between the spline shaft and the spline sleeve; when The closer it is to M3, the smaller the trend of the static friction coefficient between the spline shaft and the spline sleeve; when The closer it is to 0, the greater the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve; when The closer it is to M4, the smaller the change trend of the dynamic friction coefficient between the spline shaft and the spline sleeve.

8. A floating spline friction coefficient identification and dynamic modeling method according to claim 7, characterized in that: The Coulomb friction model is selected as the friction torque model, and the static friction torque is corrected by combining the normal force and the static friction coefficient adjustment index; the corrected friction torque model is coupled with the dynamic equation of the floating spline system to form a complete floating spline dynamic model; The JM calculation formula is as follows: ； in, , are the weight values ​​of the corresponding evaluation coefficients, ; The closer JM is to 0, the The greater the change trend, the closer JM is to R1, indicating The smaller the change trend, and the value range of r1 and r2 is within (0, R1), ; The static friction torque correction rule is as follows: The initial value and static friction torque between the spline shaft and the spline sleeve are defined as , The initial value and static friction torque between the load transfer component and the spline shaft are , ; When JM takes the value in the range of (0, r1), the variation trend of the friction torque is in the high range; When the JM value is in the range of [r1, r2], the variation trend of the friction torque is in the medium range; When JM is in the range of (r2, R1), the variation trend of the friction torque is in the low range.

9. A floating spline friction coefficient identification and dynamic modeling method according to claim 8, characterized in that: The second evaluation coefficient and the fourth evaluation coefficient are obtained, and analyzed and processed to generate a dynamic friction coefficient adjustment index; the dynamic friction torque is corrected by combining the normal force and the dynamic friction coefficient adjustment index; The dynamic friction coefficient adjustment index is used to provide a second adjustment strategy for the warning thresholds U1 and U2 of the dynamic friction coefficient, respectively, including: The dynamic friction coefficient adjustment index is defined as DM, and the calculation formula is as follows: ； in, , are the weight values ​​of the corresponding evaluation coefficients, ; The value range of the static friction coefficient adjustment index DM is set to (0, H1), where H1 is a positive number, and the comparison thresholds of DM are set to h1 and h2 respectively. The closer DM is to 0, the better. The greater the change trend, the closer DM is to H1, indicating The smaller the change trend, and the value range of h1 and h2 is within (0, H1), h1<h2; The correction rule for dynamic friction torque is as follows: The initial value and dynamic friction torque between the spline shaft and the spline sleeve are defined as , The initial value and dynamic friction torque between the load transfer component and the spline shaft are , ; When DM takes the value in the range of (0, h1), the variation trend of the system dynamic friction torque is high level; When the DM value is in the range of [h1,h2], the change trend of the system dynamic friction torque is medium level; When the DM value is in the range of (h2, H1), the change trend of the system dynamic friction torque is low level; Using the dynamic friction coefficient adjustment index, a second adjustment strategy is provided for the warning thresholds U1 and U2 of the dynamic friction coefficient, and the adjusted warning thresholds are obtained in turn. , , input the adjusted warning threshold into the corresponding position in the next collection cycle for update and replacement; The second adjustment strategy is as follows: When the DM value is in the range of (0, h1), the following adjustment formula is provided for U1: ； Among them, on the basis of the spline shaft and the spline sleeve, is the adjusted warning threshold of dynamic friction coefficient; When the DM value is in the range of [h1, h2], both U1 and U2 remain unchanged; When the DM value is in the range of (h2, H1), the following adjustment formula is provided for U2: ； Among them, between the load transfer component and the spline shaft, is the adjusted static friction coefficient warning threshold.

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