Friction plate quality characteristic mean value optimization method

Abstract

The invention discloses a friction plate quality characteristic mean value optimization method, and belongs to the technical field of friction plate detection. The method comprises the steps that an exponential function is used for establishing a friction plate abrasion loss time-varying model; collecting measurement data of the friction plate in each test stage, and fitting the model of the friction plate abrasion loss changing along with time according to the measurement data to obtain model parameters; and determining a friction plate quality characteristic mean value based on the friction plate wear loss time-varying model. According to the method, the quality characteristic change of the friction plate is modeled by using the exponential function, the wear process of the friction plate is described more accurately, the distribution density function of the service life of the product is further determined according to the improved quality characteristic mean value of the friction plate, and the service life and the quality loss of the friction plate are predicted. And the calculation result is more in line with the actual situation, so that more accurate data support is provided for maintenance plans and preventive maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of friction plate detection, and in particular to a method for optimizing a mean value of quality characteristics of a friction plate. Background Art

[0002] Clutch friction plates are key components in the transmission system of passenger cars, ensuring smooth starting and gear shifting. When the car starts or shifts gears, the clutch friction plates are subject to the huge output force of the power system during the merging and separation process. Due to repeated use, the friction plates may wear and deform, and their key performance indicators will change accordingly, and eventually they may suddenly break, which will cause danger. The high quality and reliability of clutch friction plates are not only related to the smoothness and comfort of the car's start, but also directly affect driving safety. Therefore, when designing these friction plates, it is necessary to ensure that their lifespan can meet the quality and reliability requirements.

[0003] The wear process of friction plates involves complex physical and chemical changes, including but not limited to changes in surface roughness, material fatigue, changes in microstructure, etc. Therefore, monitoring and predicting the quality characteristics of friction plates is the key to ensuring the reliable operation of mechanical systems. At present, it is often assumed that the mean change of the quality characteristics of friction plates follows a linear change over time, but in reality, the quality degradation process of friction plates is often not linear. Due to changes in environmental conditions, the non-uniformity of material properties, and the interaction of multiple wear mechanisms, the quality change of friction plates often shows nonlinear characteristics. This nonlinearity may manifest as slow initial wear, followed by accelerated wear, and finally entering a relatively stable wear state. Therefore, choosing a suitable quality characteristic change model can accurately calculate the quality loss of the product and predict the service life of the product. Summary of the invention

[0004] In view of the defects of the prior art, the present invention proposes to use an exponential function to model the quality characteristic changes of the friction plate. The exponential model can describe those processes that change rapidly over time, such as the process of rapid degradation in the early stage and then gradually stabilizing. In the quality monitoring and prediction of the friction plate, the use of the exponential model can more accurately describe its wear process, thereby providing more accurate data support for maintenance planning and preventive maintenance.

[0005] In order to achieve the above object, the present invention proposes a method for optimizing the mean value of friction plate quality characteristics, comprising the following steps:

[0006] (1) Use the exponential function to establish a model of friction plate wear variation over time;

[0007] (2) collecting measurement data of the friction plate at each test stage, and fitting a model of the change of the wear amount of the friction plate over time according to the measurement data to obtain model parameters;

[0008] (3) Determine the mean value of the friction plate quality characteristics based on the model of friction plate wear variation over time.

[0009] Furthermore, the model of the friction plate wear variation over time is:

[0010] w(t)=t(ae bt +ct+d)

[0011] Among them: a, b, c, d are model parameters.

[0012] Furthermore, the mean value of the friction plate quality characteristic is:

[0013] μ x (t) = μ x (0)+αW(t)t≥0

[0014] Where: μ x (t) is the mean value of the friction plate quality characteristics with service time t, α is the service parameter, μ x (0) is the initial value of the mean value of the friction plate quality characteristic, that is, the friction plate quality characteristic at time t=0.

[0015] Furthermore, the measurement data is obtained by establishing a friction plate wear test system on a test bench.

[0016] Furthermore, the friction plate test stages include: an initial running-in stage, a stable wear stage and a rapid wear stage.

[0017] The present invention also provides a method for predicting the service life of a friction plate, based on the above-mentioned method for optimizing the mean value of the friction plate quality characteristics, comprising:

[0018] The friction plate quality characteristic distribution is obtained according to the friction plate quality characteristic mean value;

[0019] The service life of the friction lining is predicted based on the probability of the quality characteristics exceeding the specification range and being scrapped.

[0020] Furthermore, the mean value μ of the friction plate quality characteristic with service time t is x (t) and variance σ x (t) Specifically:

[0021]

[0022] Where: w(t) is the friction plate wear variation model w (t) =t(ae bt +c t +d), a, b, c, d are model parameters; Δ, β are service parameters, μ x(0) is the mean value of the friction plate quality characteristic at the initial moment, σ x (0) is the friction plate quality characteristic variance at the initial moment;

[0023] The friction plate quality characteristics obey the normal distribution at any time, and its probability density function is:

[0024]

[0025] The probability of passing at time t is:

[0026]

[0027] The probability that the quality characteristic is out of specification and thus scrapped is:

[0028]

[0029] Furthermore, the life density function is obtained to complete the prediction of the service life of the friction plate:

[0030]

[0031] Where: x(t) is the mass characteristic of the friction plate with a service time of t; I(t) is the wear rate; T L is the lower limit of the function, T U is the functional upper limit; K n is the normalization constant.

[0032] Further, a prediction of friction plate mass loss is obtained based on the service life of the friction plate;

[0033]

[0034] Where: C m is the mass loss when wrapping quality characteristic value; r is the annual interest rate; L LC is the average mass loss of the friction plate.

[0035] Beneficial effects of the present invention:

[0036] The present invention utilizes an exponential function to model the changes in the quality characteristics of the friction plate, more accurately describes the wear process of the friction plate, and further determines the distribution density function of the product service life based on the improved quality characteristic mean of the friction plate, and predicts the service life and quality loss of the friction plate, so that the calculation results are more in line with the actual situation, thereby providing more accurate data support for maintenance planning and preventive maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Schematic diagram of the process flow of the method for optimizing the mean value of the friction plate quality characteristics according to an embodiment of the present invention.

[0038] Figure 2 It is a schematic diagram of the wear law curve of the friction plate according to an embodiment of the present invention.

[0039] Figure 3 Schematic diagram of average mass loss and service life of the friction plate according to an embodiment of the present invention.

[0040] Figure 4 Schematic diagram of probability distribution density of the service life of the friction plate according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The present invention will be further explained below in conjunction with the accompanying drawings and embodiments.

[0042] Embodiment 1:

[0043] like Figure 1 As shown, an embodiment of the present invention provides a method for optimizing the mean value of friction plate quality characteristics, comprising:

[0044] S101. Use an exponential function to establish a friction plate wear variation model over time.

[0045] Analyze the working conditions of the friction plate and divide the wear of the friction plate into the following stages:

[0046] Initial running-in phase: This is the phase when a new friction pad is first put into use. During this phase, the high points on the friction pad surface will first contact the corresponding friction surface, resulting in local wear. As use progresses, these high points will gradually be smoothed out, making the friction pad surface more uniform. Wear at this stage is relatively fast, but it usually does not cause serious damage.

[0047] Stable wear stage: When the friction plate surface is worn flat, it enters the stable wear stage. The wear rate in this stage is relatively stable, and the friction coefficient is also relatively stable. The wear is mainly due to the gradual wear of the material caused by long-term friction and load.

[0048] Rapid wear stage: When the friction plate is nearing the end of its service life, rapid wear may occur. This may be due to the loss of friction plate material reaching a critical point, causing the friction coefficient to increase and the wear rate to accelerate. This stage may be accompanied by more friction heat and the generation of wear particles.

[0049] From the above analysis, it can be seen that the quality change of the friction plate often shows nonlinear characteristics. This nonlinearity may be manifested as slow wear in the early stage, followed by accelerated wear, and finally entering a relatively stable wear state. The exponential function is very consistent in describing this nonlinear change, and can describe those processes that change rapidly over time, such as the process of rapid degradation in the early stage and then gradually stabilizing. Therefore, in the quality monitoring and prediction of the friction plate, using the exponential model as a model of the change of friction plate wear over time can more accurately describe its wear process, thereby providing more accurate data support for maintenance planning and preventive maintenance. The model is expressed as;

[0050] w(t)=t(ae bt +ct+d)

[0051] Among them: a, b, c, d are model parameters.

[0052] S102, collecting measurement data of the friction plate at each test stage, and fitting a model of the change of the wear amount of the friction plate over time according to the measurement data to obtain model parameters.

[0053] In the embodiment of the present invention, a clutch friction plate wear test system is established on a test bench to conduct a friction plate wear law test (clutch friction plate reliability test).

[0054] Description of the test plan: The speed difference of each friction plate engagement is 800-1000r / min, the engagement oil pressure is 1.5MPa, the sliding time is 0.5-0.6s, and the separation time is 0.1-0.2s. The clutch lubrication and control oil circuits use a total of 20L of oil, and the sampling position is the clutch box control oil pressure inlet. An initial oil sample is collected 20 minutes after the start of the test, and thereafter, an oil sample is collected every 800 engagements. According to the above-mentioned working condition analysis of the friction plate, the relevant data are measured at different test stages, and the measured data are shown in the following table:

[0055] Table 1

[0056]

[0057] According to the above data, the model of friction plate wear variation over time is fitted, and a≈0.01476, b≈-0.00014, c≈7.89636*e-08, d≈0.00147 are obtained. The fitting curve is as follows: Figure 2 The changing trend of the fitting curve is basically consistent with the wear data, and the average error is about 4.3077%. It can be seen that the wear data is well fitted.

[0058] S103: Determine a mean value of the friction plate quality characteristics based on the friction plate wear variation model over time.

[0059] μx (t) = μ x (0)+αW(t)t≥0

[0060] Where: μ x (t) is the mean value of the friction plate quality characteristics with service time t, α is the service parameter, μ x (0) is the initial value of the mean value of the friction plate quality characteristic, that is, the friction plate quality characteristic at time t=0.

[0061] Embodiment 2:

[0062] The embodiment of the present invention further provides a method for predicting the service life of a friction plate, comprising:

[0063] The friction plate quality characteristic distribution is obtained according to the friction plate quality characteristic mean value.

[0064] According to the above, the mean value μ of the friction plate quality characteristic with service time t x (t) and variance σ x (t) Specifically:

[0065]

[0066] Where: w(t) is the friction plate wear variation model w(t) = t(ae bt +ct+d), a, b, c, d are model parameters; Δ, β are service parameters, μ x (0) is the mean value of the friction plate quality characteristic at the initial moment, σ x (0) is the friction plate quality characteristic variance at the initial moment.

[0067] Assuming that the friction plate quality characteristics are a normal random process, and the product quality characteristics obey the normal distribution at any time, the probability density function under the normal distribution can be obtained. The improved friction plate quality characteristics mean and variance are brought into the friction plate probability density function, and the density function can be obtained:

[0068]

[0069] The service life of the friction lining is predicted based on the probability of scrapping due to quality characteristics exceeding the specification range.

[0070] The probability of passing at time t is:

[0071]

[0072] The probability of a quality characteristic being out of specification and thus scrapped is:

[0073]

[0074] Furthermore, the life density function is obtained to complete the prediction of the service life of the friction plate:

[0075]

[0076] Where: x(t) is the mass characteristic of the friction plate with a service time of t; I(t) is the wear rate; T L is the lower limit of the function, T U is the functional upper limit; K n is the normalization constant.

[0077] Furthermore, based on the prediction of the service life of the friction plate, the prediction of the mass loss of the friction plate is obtained:

[0078]

[0079] Where: C m is the mass loss when the wrapping quality characteristic value is reached, r is the annual interest rate; L LC is the average mass loss of the friction plate.

[0080] The total thickness of the clutch friction plate is a x The mass loss of the friction plate during its service period is calculated as the key quality feature. The total thickness dimension and tolerance of the friction plate are Therefore, Δ=0.1mm, T x =3.2mm, T L =3.1mm, T U =3.3mm. The present value of the loss of scrapped friction plate is C m =200, which is the price of the friction plate, and N represents the real-time engagement times of the friction plate (which can correspond to the service time). Through the friction plate bench test data, the wear curve is fitted to obtain a≈0.01476; b≈-0.00014; c≈7.89636*e-08; d≈0.00147, and the distribution parameters μ of a batch of friction plates are measured x (0) = 3.19765 mm, σ X (0) = 0.015269 mm, and the friction plate mass loss is predicted under the condition of service parameters α = -0.0009, β = 0.0006, and r = 10%. Substitute the above related parameters into the friction plate mass loss L LC In the formula, the relationship between the average mass loss of the friction plate and the service time is obtained by numerical calculation as follows: Figure 3 As shown in the figure, it can be seen that the mass loss of this batch of friction plates begins to increase significantly between 18 and 25 thousand clutch engagements, and after 35 thousand engagements, the average mass loss of the friction plates no longer increases and stabilizes at a constant value, so the service life of this batch of friction plates is roughly between 18 and 35 thousand engagements.

[0081] According to the relevant parameters of the friction plate, the probability distribution density function of the friction plate service life is calculated, such as Figure 4 As shown in the figure, it can be seen that the service life of the friction plate is approximately subject to a log-normal distribution. This shows that if the change in the service quality characteristics of the friction plate is a normal distribution random process, the product life distribution based on the tolerance requirements will be a log-normal distribution.

[0082] from Figure 4 It can be seen that the average life of the product is about 26,000 times, and the product life is almost distributed between 18,000 and 35,000 times. According to the experimental results, the service life of the wet clutch friction plate is about 26,000 times, which is close to the result.

[0083] Although the content of the present invention is described in detail through the above embodiments, it should be recognized that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some of the technical features therein with equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Therefore, the protection scope of the present invention should be defined by the attached claims.

Claims

1. A method for optimizing the mean value of friction plate quality characteristics, characterized in that: (1) Use the exponential function to establish a model of friction plate wear variation over time; (2) collecting measurement data of the friction plate at each test stage, and fitting a model of the change of the wear amount of the friction plate over time according to the measurement data to obtain model parameters; (3) Determine the mean value of the friction plate quality characteristics based on the model of friction plate wear variation over time.

2. The method for optimizing the mean value of friction plate quality characteristics according to claim 1, characterized in that: The model of friction plate wear variation over time is: w(t)=t(ae bt +ct+d) Among them: a, b, c, d are model parameters.

3. The method for optimizing the mean value of friction plate quality characteristics according to claim 2, characterized in that: The friction plate quality characteristic mean is: m x (t)=μ x (0)+αW(t)t≥0 Where: μ x (t) is the mean value of the friction plate quality characteristics with service time t, α is the service parameter, μ x (0) is the initial value of the mean value of the friction plate quality characteristic, that is, the friction plate quality characteristic at time t=0.

4. The method for optimizing the mean value of friction plate quality characteristics according to claim 1 is characterized in that: the measurement data is obtained by establishing a friction plate wear test system on a test bench.

5. The method for optimizing the mean value of friction plate quality characteristics according to claim 1, characterized in that: The friction plate test stages include: an initial running-in stage, a stable wear stage and a rapid wear stage.

6. A method for predicting the service life of a friction plate, based on the method for optimizing the mean value of the friction plate quality characteristics according to any one of claims 1 to 5, characterized in that: The friction plate quality characteristic distribution is obtained according to the friction plate quality characteristic mean value; The service life of the friction lining is predicted based on the probability of the quality characteristics exceeding the specification range and being scrapped.

7. The method for predicting the service life of a friction plate according to claim 6, characterized in that: The mean value μ of the friction plate quality characteristic with service time t x (t) and variance σ x (t) Specifically: Where: w(t) is the friction plate wear variation model w(t) = t(ae bt +ct+d), a, b, c, d are model parameters; α, β are service parameters, μ x (0) is the mean value of the friction plate quality characteristic at the initial moment, σ x (0) is the variance of the friction plate quality characteristic at the initial moment; the friction plate quality characteristic obeys the normal distribution at any time, and its probability density function is: The probability of passing at time t is: The probability that the quality characteristic is out of specification and thus scrapped is: Furthermore, the life density function is obtained to complete the prediction of the service life of the friction plate: Where: x(t) is the mass characteristic of the friction plate with a service time of t; I(t) is the wear rate; T L is the lower limit of the function, T U is the functional upper limit; K n is the normalization constant.

8. The method for predicting the service life of a friction plate according to claim 7, characterized in that: Obtaining a prediction of friction plate mass loss based on the friction plate service life; Where: C m is the mass loss when wrapping quality characteristic value; r is the annual interest rate; L LC is the average mass loss of the friction plate.

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