Performance detection device and detection method for automobile clutch

Abstract

The invention relates to the technical field of clutch performance detection, in particular to a performance detection device and method for an automobile clutch, and the method comprises the steps: collecting the pressure data and vibration data of the automobile clutch at all collection moments, and obtaining the equivalent friction radius of a friction plate of the automobile clutch, the number of friction surfaces, and the motor torque of a rack; acquiring a performance feedback strength value of the automobile clutch; acquiring an abnormal friction coefficient based on the abnormal condition of the friction coefficient; obtaining a friction influence strength value of the automobile clutch; acquiring corrected pressure data at each acquisition moment based on the friction influence strength value and the pressure data; and calculating the improved friction coefficient of the automobile clutch at each acquisition moment, and detecting the performance of the automobile clutch. According to the invention, the accuracy of performance detection of the automobile clutch is improved.

Description

Technical Field

[0001] The present application relates to the technical field of clutch performance detection, and in particular to a performance detection device and a detection method for a vehicle clutch. Background Art

[0002] With the rapid development of the automobile industry and the growing demand in the maintenance market, the clutch, as a key component of the automobile transmission system, has a direct impact on driving experience and driving safety. With the advancement of sensors, computers and automation technology, clutch detection equipment has become an important tool in the maintenance industry, which can quickly and accurately detect faults and wear through sensor data, improve maintenance efficiency and reduce costs. The existing clutch detection equipment on the market has problems such as limited detection range, single function, and complex operation, which cannot meet the growing maintenance needs. Therefore, the development of high-performance, multi-functional, and easy-to-operate detection equipment has become an industry trend, aiming to improve the intelligence level of detection equipment through technological innovation and realize automatic detection, analysis, diagnosis and other functions.

[0003] In the performance test of the clutch, the test of the friction coefficient is crucial because it is directly related to the clutch's engagement and disengagement efficiency. The appropriate friction coefficient can ensure that the clutch transmits power smoothly and reliably, prevent slipping or excessive wear, and extend the life of the clutch. An improper friction coefficient may lead to unstable power transmission, increased energy consumption, and even safety problems. The change in load directly affects the measurement result of the friction coefficient. When the load increases, the pressure per unit area decreases due to the increase in contact area, thereby reducing the friction coefficient. In addition, the surface film can reduce friction. On the contrary, if the surface film cannot be effectively formed, the friction coefficient will be higher. The error in the friction coefficient will lead to inaccurate clutch performance evaluation, which may cause premature wear of the clutch, performance degradation, or even clutch failure, affecting the driving safety and performance of the vehicle. Therefore, accurate friction coefficient detection is crucial to ensure the performance and life of the clutch. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a performance detection device and detection method for a vehicle clutch. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for detecting performance of a vehicle clutch, the method comprising the following steps:

[0006] Collect the pressure data and vibration data of the automobile clutch at each collection time, and obtain the equivalent friction radius of the friction plate of the automobile clutch, the number of friction surfaces, and the motor torque of the test bench;

[0007] Obtaining a performance feedback intensity value of a vehicle clutch based on the correlation and mutual relationship between pressure data and vibration data;

[0008] Obtaining an abnormal friction coefficient based on an abnormal condition of the friction coefficient;

[0009] Based on the abnormal friction coefficient, the similarity between the pressure data and the friction coefficient, and the similarity between the vibration data and the friction coefficient, the friction influence intensity value of the automobile clutch is obtained;

[0010] Obtaining corrected pressure data at each acquisition moment based on the friction influence intensity value and the pressure data;

[0011] Based on the corrected pressure data, the equivalent friction radius of the friction plate of the automobile clutch, the number of friction surfaces and the motor torque of the test bench, the improved friction coefficient of the automobile clutch at each acquisition moment is obtained, and the performance of the automobile clutch is tested.

[0012] Furthermore, the method for obtaining the performance feedback strength value is:

[0013] The pressure data at all acquisition moments are sorted in chronological order to obtain a pressure data sequence, and the vibration data at all acquisition moments are sorted in chronological order to obtain a vibration data sequence; and the correlation coefficient between the pressure data sequence and the vibration data sequence is calculated;

[0014] Obtaining mean-variance contribution based on the relationship between pressure data and vibration data;

[0015] The absolute value of the correlation coefficient between the pressure data sequence and the vibration data sequence and the product of the mean variance contribution are calculated as the performance feedback intensity value of the automobile clutch.

[0016] Furthermore, the method for obtaining the mean variance contribution is:

[0017] The pressure data sequence and the vibration data sequence are used as the input of the vector autoregression model, and the variance contribution of vibration to pressure and the variance contribution of pressure to vibration are output. The mean of the variance contribution of vibration to pressure and the variance contribution of pressure to vibration are calculated as the mean variance contribution.

[0018] Furthermore, the method for obtaining the abnormal friction coefficient is:

[0019] The sequence of friction coefficients at all acquisition moments sorted in chronological order is taken as the friction coefficient sequence. The Z-Score algorithm is used to calculate the Z score of each friction coefficient in the friction coefficient sequence. The friction coefficient with a Z score greater than the preset score threshold is taken as the abnormal friction coefficient.

[0020] Furthermore, the method for obtaining the friction influence intensity value is:

[0021] A time window of preset length is constructed with the collection time of each abnormal friction coefficient as the center;

[0022] For each time window, the pressure data, vibration data and friction coefficient in the time window are used as inputs of the volatility analysis algorithm, and the Hurst index of the pressure data, the Hurst index of the vibration data and the Hurst index of the friction coefficient in the time window are output respectively;

[0023] Based on the similarity between the pressure data and the friction coefficient, and the similarity between the vibration data and the friction coefficient, the average friction similarity of each time window is obtained;

[0024] The calculation formula of the friction influence strength value is: Where B is the friction impact strength value of the automobile clutch; A is the performance feedback strength value of the automobile clutch, M is the total number of time windows, d m is the average friction similarity of the mth time window, e is a natural constant, H 0,m is the Hurst exponent of the friction coefficient in the mth time window, H i,m is the Hurst exponent of the i-th data in the m-th time window.

[0025] Furthermore, the method for obtaining the average friction similarity is:

[0026] For each time window, the similarity between the pressure data sequence and the friction coefficient sequence, and the similarity between the vibration data sequence and the friction coefficient sequence in the time window are calculated respectively, and the average of the similarity between the pressure data sequence and the friction coefficient sequence, and the similarity between the vibration data sequence and the friction coefficient sequence is calculated as the average friction similarity of each time window.

[0027] Furthermore, the calculation formula of the corrected pressure data is: Wherein, F′ is the corrected pressure data at each acquisition time; F is the pressure data at each acquisition time, k is the preset smoothing coefficient, arctan is the inverse tangent function, π is the pi, and B is the friction influence intensity value of the automobile clutch.

[0028] Further, the calculation formula of the improved friction coefficient is: μ is the improved friction coefficient of the automobile clutch at each sampling time; F′ is the corrected pressure data at each sampling time, R c is the equivalent friction radius of the friction plate of the automobile clutch, T c is the motor torque of the test bench, and Z is the number of friction surfaces of the vehicle clutch.

[0029] Further, the performance of the automobile clutch is tested, including:

[0030] For the improved friction coefficient of the automobile clutch at each collection moment, when the friction coefficient is within a preset qualified range of the friction coefficient, the performance of the automobile clutch is qualified; otherwise, the performance of the automobile clutch is unqualified.

[0031] In a second aspect, an embodiment of the present application further provides a performance detection device for a vehicle clutch, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned methods when executing the computer program.

[0032] This application has at least the following beneficial effects:

[0033] The present application proposes a performance detection device and a detection method for an automobile clutch, which uses a piezoelectric force sensor and a vibration sensor for data acquisition, and can accurately measure the pressure data applied by a dry clutch friction plate friction coefficient test bench and the vibration data during the friction process, so as to provide accurate basic data for subsequent analysis; in view of the complex interaction problem between pressure and vibration, a performance feedback strength value is constructed to reflect the linear correlation and dynamic interaction strength between pressure and vibration, so as to solve the problem that the overall interaction strength between pressure and vibration cannot be quantified, so as to more accurately evaluate their influence on the measurement accuracy of the clutch friction coefficient; in view of the relationship between the friction coefficient fluctuation and the pressure and vibration changes, the abnormal friction coefficient is obtained, and a friction influence strength value is constructed to reflect the influence strength of the load and surface film on the clutch friction coefficient, so as to exclude the influence of other factors in the friction coefficient fluctuation that are not related to the pressure and vibration changes, so as to more clearly identify the influence degree of pressure and vibration on the stability of the friction coefficient; and the friction influence strength value is used to correct the pressure data, and then the improved friction coefficient is calculated based on the corrected pressure data, and the friction coefficient calculation is improved to achieve accurate calculation of the friction coefficient, improve the accuracy and stability of the friction coefficient measurement, and detect the performance of the automobile clutch according to the improved friction coefficient, so as to improve the accuracy of the performance detection of the automobile clutch. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 A flowchart of a method for detecting the performance of a vehicle clutch provided in one embodiment of the present application;

[0036] Figure 2A flowchart for obtaining an improved friction coefficient is provided for one embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of a performance detection device and detection method of a vehicle clutch proposed in the present application, its specific implementation, structure, features and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0039] The specific scheme of a performance detection device and detection method for an automobile clutch provided by the present application is described in detail below with reference to the accompanying drawings.

[0040] See also Figure 1 , which shows a flow chart of a method for detecting the performance of a vehicle clutch provided by an embodiment of the present application, the method comprising the following steps:

[0041] Step S1, collecting pressure data and vibration data of the automobile clutch at each collection time, obtaining the equivalent friction radius of the friction plate of the automobile clutch, the number of friction surfaces and the motor torque of the test bench.

[0042] The load in the clutch performance detection process refers to the load pressure that the clutch bears during actual operation. In the present application, a dry clutch friction plate friction coefficient test bench is used to obtain the friction coefficient and pressure data of the automobile clutch at each collection time, and the equivalent friction radius of the friction plate of the automobile clutch, the number of friction surfaces and the motor torque of the bench are obtained. The process of obtaining data using a dry clutch friction plate friction coefficient test bench is a well-known technology and will not be described in detail in this embodiment.

[0043] In the friction coefficient test process, "surface film" usually refers to a thin film formed between the two contact surfaces of the clutch and the dry clutch friction plate friction coefficient test bench. The cause of this film is uncertain. It may be composed of wear products of friction materials, lubricants, environmental pollutants or chemical reaction products. The vibration of the clutch during engagement and separation can reflect the existence of the surface film. Therefore, a vibration sensor is installed at the connection between the dry clutch friction plate friction coefficient test bench and the clutch to be tested to obtain vibration data at each collection moment during the friction detection process. In this embodiment, the time interval of each collection moment is 0.02 seconds. The implementer can select other values ​​according to actual conditions.

[0044] Step S2, obtaining the performance feedback intensity value of the automobile clutch based on the correlation and mutual relationship between the pressure data and the vibration data; obtaining the abnormal friction coefficient based on the abnormal condition of the friction coefficient; obtaining the friction influence intensity value of the automobile clutch based on the abnormal friction coefficient, the similarity between the pressure data and the friction coefficient, and the similarity between the vibration data and the friction coefficient.

[0045] In the test process of friction coefficient, the increase of load will increase the pressure per unit area, and the surface film can effectively reduce friction. When the load increases, the greater the load, the more likely it is to damage the surface film, resulting in an increase in the friction coefficient, that is, the integrity and uniformity of the surface film will also affect the response of the friction coefficient to load changes. If the surface film can be effectively formed and remain stable, it can reduce the change in friction coefficient caused by the increase in load and play a certain buffering role. On the contrary, if the surface film is unstable or uneven, the increase in load may cause a significant change in the friction coefficient.

[0046] From the above analysis, it can be seen that in the clutch performance test, there is a complex feedback relationship between pressure and vibration. Changes in pressure will affect the friction characteristics of the clutch, and then affect the generation and propagation of vibration. Specifically, when the pressure increases, the contact area of ​​the clutch increases, which may lead to changes in the friction coefficient, thereby causing an increase in vibration. In addition, changes in pressure may also affect the formation and stability of the clutch surface film, thereby affecting the frequency and amplitude of the vibration.

[0047] The pressure data at all acquisition moments are sorted in chronological order to obtain a pressure data sequence, and the vibration data at all acquisition moments are sorted in chronological order to obtain a vibration data sequence; the correlation coefficient between the pressure data sequence and the vibration data sequence is calculated. The correlation coefficient selected in this embodiment is the Pearson correlation coefficient, and the implementer can select other correlation coefficients according to actual conditions. The calculation method of the correlation coefficient is a well-known technology and will not be elaborated in this embodiment.

[0048] In order to reflect the degree of mutual influence between pressure data and vibration data, the pressure data sequence and the vibration data sequence are used as the input of the vector autoregression model, and the variance contribution of vibration to pressure and the variance contribution of pressure to vibration are output. The mean of the variance contribution of vibration to pressure and the variance contribution of pressure to vibration are calculated as the mean variance contribution. Among them, the vector autoregression model (VAR for short) is a statistical model used for multivariate time series analysis, which is used to analyze the relationship between multiple variables. It is a well-known technology and will not be described in detail in this embodiment.

[0049] In order to reflect the overall interaction strength between the pressure data and the vibration data, the performance feedback strength value of the automobile clutch is obtained based on the correlation and mean variance contribution between the pressure data sequence and the vibration data sequence. The acquisition method is: calculate the product of the absolute value of the correlation coefficient between the pressure data sequence and the vibration data sequence and the mean variance contribution as the performance feedback strength value of the automobile clutch.

[0050] It should be noted that the correlation coefficient between the pressure data sequence and the vibration data sequence represents the linear relationship between pressure change and vibration change. The larger its absolute value is, the stronger the linear relationship between pressure and vibration is, the greater the feedback strength of the automobile clutch is, and the performance feedback strength value increases accordingly. The mean variance contribution represents the average of the variance contribution of pressure change to vibration change and the variance contribution of vibration change to pressure change in the vector autoregression model, reflecting the strength of the causal relationship between pressure and vibration changes. The larger the mean variance contribution is, the stronger the dynamic interaction between pressure and vibration is, which further indicates that the interaction between pressure and vibration is stronger, the greater the feedback strength of the feedback system is, and the performance feedback strength value increases accordingly.

[0051] The performance feedback strength value combines the linear correlation between pressure and vibration and the strength of the dynamic interaction, quantifying the overall interaction strength between pressure and vibration. The larger the value, the stronger the interaction between pressure and vibration, and the more likely it is to affect the performance and stability of the clutch during friction coefficient measurement.

[0052] The friction coefficient is the ratio of friction force to normal pressure. During the friction test, if the pressure is unstable and fluctuates, the friction coefficient will fluctuate. For example, during the clutch engagement process, if the pressure suddenly increases, the friction force will also increase accordingly, resulting in a short-term fluctuation in the friction coefficient. The presence of the surface film will affect the friction performance of the clutch. The vibration sensor can detect the vibration caused by the unevenness or thickness change of the surface film during the friction process. When the surface film is thicker or uneven, a larger vibration will be generated during the friction process. This vibration will cause fluctuations in friction force, thereby affecting the measurement of the friction coefficient. For example, the shedding or uneven wear of the surface film will cause an instantaneous change in friction force, resulting in a short-term fluctuation in the friction coefficient.

[0053] In order to analyze whether the fluctuation of the friction coefficient is related to the change of pressure and vibration, the sequence composed of the friction coefficients at all the acquisition moments sorted in chronological order is taken as the friction coefficient sequence, and the Z-Score algorithm is used to calculate the Z score of each friction coefficient in the friction coefficient sequence, and a preset score threshold is set. In this embodiment, the value of the preset score threshold is 3, and the implementer can select other values ​​according to the actual situation. The friction coefficient with a Z score greater than the preset score threshold is taken as an abnormal friction coefficient. Z-Score (standard score) is a statistical tool for measuring the relative distance between a data point and the mean of a data set, and is used to identify abnormal values. It is a well-known technology and will not be described in detail in this embodiment.

[0054] Furthermore, a time window with a length of N is constructed with the collection time of each abnormal friction coefficient as the center. In this embodiment, the value of N is 51, and the implementer can select other values ​​according to actual conditions.

[0055] For each time window, the pressure data, vibration data and friction coefficient in the time window are respectively used as inputs of the volatility analysis algorithm, and the Hurst index of the pressure data, the Hurst index of the vibration data and the Hurst index of the friction coefficient in the time window are respectively output. Among them, the volatility analysis algorithm is a well-known technology and will not be described in detail in this embodiment. In addition, the Hurst index reflects the autocorrelation of the data in the time series and reflects the hidden long-term trend. It is a well-known technology and will not be described in detail here.

[0056] Furthermore, for each time window, the similarity between the pressure data sequence and the friction coefficient sequence, and the similarity between the vibration data sequence and the friction coefficient sequence in the time window are calculated respectively, and the average of the similarity between the pressure data sequence and the friction coefficient sequence, and the similarity between the vibration data sequence and the friction coefficient sequence is calculated as the average friction similarity of each time window; in this embodiment, cosine similarity is selected as the similarity measurement method, and the implementer can select other similarities according to actual conditions.

[0057] In order to reflect the influence of load and surface film on the friction coefficient of the clutch, the friction influence intensity value of the automobile clutch is calculated based on the performance feedback intensity value, average friction similarity, and the autocorrelation of pressure data, vibration data and friction coefficient in the time series. The calculation formula is: Where B is the friction impact strength value of the automobile clutch; A is the performance feedback strength value of the automobile clutch, M is the total number of time windows, d m is the average friction similarity of the mth time window, e is a natural constant, H 0,m is the Hurst exponent of the friction coefficient in the mth time window, H i,m is the Hurst exponent of the ith data in the mth time window, where the ith data includes vibration data and pressure data.

[0058] It should be noted that the performance feedback intensity value reflects the linear correlation and dynamic interaction intensity between pressure and vibration. The larger the performance feedback intensity value, the stronger the interaction between pressure and vibration, and the greater the feedback intensity of the feedback system, that is, the more significant the impact of pressure change on vibration and the impact of vibration on pressure. It is used as the internal feedback weight of the subsequent pressure and vibration impact on the clutch friction coefficient. The larger its value, the greater the weight calculated based on the subsequent impact; the larger the value of the average friction similarity, the higher the similarity between the friction coefficient data and the pressure data or vibration data, that is, within the time window, the more consistent the change trend of the friction coefficient is with the change trend of pressure or vibration, that is, the greater the possibility of the impact of pressure and vibration on the friction coefficient, and the greater the friction impact intensity value; (H 0,m -H i,m ) is smaller, indicating that the difference between the friction coefficient data and the pressure data or vibration data in self-similarity and long memory is smaller, that is, the lower their similarity in time series characteristics is, the greater the impact on the clutch friction coefficient, and the greater the friction influence intensity value; conversely, the smaller the friction influence intensity value is.

[0059] The friction influence intensity value combines the interaction intensity between pressure and vibration, the similarity between the friction coefficient and the pressure and vibration data, and the difference in their time series characteristics. It reflects the influence of load and surface film on the friction coefficient of the clutch. The larger the friction influence intensity value, the more significant the influence of load and surface film on the friction coefficient of the clutch. That is, during the friction test, the changes in pressure and vibration have a greater impact on the stability of the friction coefficient, which may cause large fluctuations in the friction coefficient, thereby affecting the performance of the clutch.

[0060] Step S3, obtaining the corrected pressure data at each acquisition time based on the friction influence intensity value and the pressure data; obtaining the improved friction coefficient of the vehicle clutch at each acquisition time based on the corrected pressure data, the equivalent friction radius of the friction plate of the vehicle clutch, the number of friction surfaces and the motor torque of the test bench, and detecting the performance of the vehicle clutch.

[0061] Through the above analysis and calculation, the friction influence intensity combines the interaction intensity between pressure and vibration, the similarity between the friction coefficient and the pressure and vibration data, and the differences in their time series characteristics, thereby reflecting the influence of load and surface film on the friction coefficient of the clutch. The greater the friction influence intensity, the more significant the influence of pressure and vibration on the friction coefficient, and the more likely it is to cause large fluctuations in the friction coefficient, thereby affecting the performance of the clutch. By real-time monitoring of the friction influence intensity, the influence of the current pressure on the friction coefficient calculation can be determined.

[0062] Based on the above analysis, the pressure data at each acquisition time is corrected according to the friction influence intensity. The correction formula is: Wherein, F′ is the corrected pressure data at each acquisition moment; F is the pressure data at each acquisition moment, k is a preset smoothing coefficient, the value of which is 0.3 in this embodiment, and the implementer may select other values ​​according to actual conditions, arctan is the inverse tangent function, π is the pi, and B is the friction influence intensity value of the automobile clutch.

[0063] It should be noted that when the friction influence intensity value is larger, the pressure data and vibration data have a more significant impact on the friction coefficient, which is more likely to cause a large fluctuation in the friction coefficient, thereby affecting the performance of the clutch. Therefore, when the friction influence intensity value is larger, the correction amount of the pressure data is increased, and the correction degree of F' is increased to compensate for the fluctuation of the friction coefficient caused by the interaction of pressure and vibration, thereby improving the accuracy and stability of the friction coefficient measurement; conversely, the correction amount of the pressure data is reduced. Among them, k is the preset smoothing coefficient used to smooth the mapping range of the pressure data, so that the size of the corrected pressure data will not change too drastically relative to the original pressure data, thereby maintaining the stability of the data.

[0064] Furthermore, in order to calculate the friction coefficient more accurately while considering the load and surface film, the improved friction coefficient of the automobile clutch at each acquisition time is calculated based on the corrected pressure data. The calculation formula is: μ is the improved friction coefficient of the automobile clutch at each sampling time; F′ is the corrected pressure data at each sampling time, R c is the equivalent friction radius of the friction plate of the automobile clutch, T c is the motor torque of the test bench, and Z is the number of friction surfaces of the vehicle clutch. Among them, the improved friction coefficient acquisition flow chart is as follows Figure 2 shown.

[0065] At this point, the improved friction coefficient of the automobile clutch at each acquisition moment is obtained, so that a more accurate friction coefficient can be obtained under the condition of considering the load and the surface film, and the performance of the automobile clutch is tested according to the improved friction coefficient, thereby improving the accuracy of the performance test of the automobile clutch. The specific method is as follows:

[0066] A preset qualified range of friction coefficient is set. In this embodiment, the selected range is [0.25, 0.6]. For the improved friction coefficient of the automobile clutch at each collection moment, when the friction coefficient is within the preset qualified range of friction coefficient, the performance of the automobile clutch is qualified; otherwise, the performance of the automobile clutch is unqualified.

[0067] Based on the same inventive concept as the above method, an embodiment of the present application also provides a performance detection device for a vehicle clutch, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned performance detection methods for a vehicle clutch are implemented.

[0068] It should be noted that the above sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0070] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for detecting the performance of a vehicle clutch, characterized in that: The method comprises the following steps: Collect the pressure data, vibration data and friction coefficient of the automobile clutch at each collection time, and obtain the equivalent friction radius of the friction plate of the automobile clutch, the number of friction surfaces and the motor torque of the test bench; Obtaining a performance feedback intensity value of a vehicle clutch based on the correlation and mutual relationship between pressure data and vibration data; Obtaining an abnormal friction coefficient based on an abnormal condition of the friction coefficient; Based on the abnormal friction coefficient, the similarity between the pressure data and the friction coefficient, and the similarity between the vibration data and the friction coefficient, the friction influence intensity value of the automobile clutch is obtained; Obtaining corrected pressure data at each acquisition moment based on the friction influence intensity value and the pressure data; Based on the corrected pressure data, the equivalent friction radius of the friction plate of the automobile clutch, the number of friction surfaces and the motor torque of the test bench, the improved friction coefficient of the automobile clutch at each acquisition moment is obtained, and the performance of the automobile clutch is tested.

2. A method for detecting the performance of a vehicle clutch as claimed in claim 1, characterized in that: The method for obtaining the performance feedback intensity value is: The pressure data at all acquisition moments are sorted in chronological order to obtain a pressure data sequence, and the vibration data at all acquisition moments are sorted in chronological order to obtain a vibration data sequence; and the correlation coefficient between the pressure data sequence and the vibration data sequence is calculated; Obtaining mean-variance contribution based on the relationship between pressure data and vibration data; The absolute value of the correlation coefficient between the pressure data sequence and the vibration data sequence and the product of the mean variance contribution are calculated as the performance feedback intensity value of the automobile clutch.

3. A method for detecting the performance of an automobile clutch as claimed in claim 2, characterized in that: The method for obtaining the mean variance contribution is: The pressure data sequence and the vibration data sequence are used as the input of the vector autoregression model, and the variance contribution of vibration to pressure and the variance contribution of pressure to vibration are output. The mean of the variance contribution of vibration to pressure and the variance contribution of pressure to vibration are calculated as the mean variance contribution.

4. A method for detecting the performance of a vehicle clutch as claimed in claim 1, characterized in that: The method for obtaining the abnormal friction coefficient is: The sequence of friction coefficients at all acquisition moments sorted in chronological order is taken as the friction coefficient sequence. The Z-Score algorithm is used to calculate the Z score of each friction coefficient in the friction coefficient sequence. The friction coefficient with a Z score greater than the preset score threshold is taken as the abnormal friction coefficient.

5. A method for detecting the performance of an automobile clutch as claimed in claim 2, characterized in that: The method for obtaining the friction influence intensity value is: A time window of preset length is constructed with the collection time of each abnormal friction coefficient as the center; For each time window, the pressure data, vibration data and friction coefficient in the time window are used as inputs of the volatility analysis algorithm, and the Hurst index of the pressure data, the Hurst index of the vibration data and the Hurst index of the friction coefficient in the time window are output respectively; Based on the similarity between the pressure data and the friction coefficient, and the similarity between the vibration data and the friction coefficient, the average friction similarity of each time window is obtained; The calculation formula of the friction influence strength value is: Where B is the friction impact strength value of the automobile clutch; A is the performance feedback strength value of the automobile clutch, M is the total number of time windows, d m is the average friction similarity of the mth time window, e is a natural constant, H 0,m is the Hurst exponent of the friction coefficient in the mth time window, H i,m is the Hurst exponent of the i-th data in the m-th time window.

6. A method for detecting the performance of a vehicle clutch as claimed in claim 5, characterized in that: The method for obtaining the average friction similarity is: For each time window, the similarity between the pressure data sequence and the friction coefficient sequence, and the similarity between the vibration data sequence and the friction coefficient sequence in the time window are calculated respectively, and the average of the similarity between the pressure data sequence and the friction coefficient sequence, and the similarity between the vibration data sequence and the friction coefficient sequence is calculated as the average friction similarity of each time window.

7. A method for detecting the performance of a vehicle clutch as claimed in claim 1, characterized in that: The calculation formula of the corrected pressure data is: Wherein, F′ is the corrected pressure data at each acquisition time; F is the pressure data at each acquisition time, k is the preset smoothing coefficient, arctan is the inverse tangent function, π is the pi, and B is the friction influence intensity value of the automobile clutch.

8. A method for detecting the performance of an automobile clutch as claimed in claim 1, characterized in that: The calculation formula of the improved friction coefficient is: v is the improved friction coefficient of the automobile clutch at each sampling time; F′ is the corrected pressure data at each sampling time, R c is the equivalent friction radius of the friction plate of the automobile clutch, T c is the motor torque of the test bench, and Z is the number of friction surfaces of the vehicle clutch.

9. A method for detecting the performance of a vehicle clutch as claimed in claim 1, characterized in that: The detection of the performance of the automobile clutch comprises: For the improved friction coefficient of the automobile clutch at each collection moment, when the friction coefficient is within a preset qualified range of the friction coefficient, the performance of the automobile clutch is qualified; otherwise, the performance of the automobile clutch is unqualified.

10. A performance detection device for a vehicle clutch, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of a method for detecting the performance of an automobile clutch as described in any one of claims 1 to 9 are implemented.

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