A method and system for reducing noise of friction vibration signal of sliding friction pair

Abstract

The present invention provides a method and system for reducing the noise of a friction vibration signal of a sliding friction pair, which belongs to the field of friction signal noise reduction, and includes obtaining a vibration signal of a sliding friction pair in a normal operating state as a first vibration signal; obtaining a vibration signal of a sliding friction pair in an abnormal wear operating state as a second vibration signal. The first vibration signal and the second vibration signal are decomposed and processed by an empirical mode decomposition (EMD) method to obtain a plurality of first IMF components and a plurality of second IMF components. The correlation coefficient between the IMF components in the same frequency band is calculated, and the IMF components with a correlation coefficient greater than a set threshold are retained, and the vibration signal is reconstructed using the retained IMF components. The wear state of the friction pair is identified by the vibration signal after noise reduction processing, thereby improving the reliability and service life of the equipment.

Description

Technical Field

[0001] The invention belongs to the field of friction signal noise reduction processing, and in particular relates to a method and system for reducing the noise of a friction vibration signal of a sliding friction pair. Background Art

[0002] Friction vibration is a signal generated during the relative motion of the friction pair. The wear state of the friction pair can be identified by real-time monitoring of the friction vibration signal. Sliding friction pair systems are widely present in mechanical transmissions and are one of the key links in achieving motion transmission and conversion between mechanical parts. Detection of the wear state of the friction pair is conducive to reducing equipment failures and downtime caused by wear, thereby improving the reliability and service life of the equipment, and can achieve the goal of preventive maintenance of equipment safety.

[0003] However, the vibration signal generated by the friction of the sliding friction pair is very weak and often mixed with other vibration signals. It is difficult for the unprocessed vibration signal to accurately reflect the wear state of the friction pair. Therefore, it is necessary to perform noise reduction on the measured vibration signal so as to identify the wear state of the friction pair through the vibration signal. In practice, the noise reduction of vibration signals mostly uses filtering methods or wavelet transformation methods. Among them, the filtering method has poor filtering effect on friction vibration signals with nonlinear and non-stationary characteristics, and the amount of calculation is large. The wavelet transformation method requires processing the boundaries of the signal. Different boundary processing methods will affect the results of the transformation. If the boundary processing is improper, it may cause signal distortion or introduce additional noise, and it is necessary to select a suitable wavelet basis according to the characteristics of the signal, which is difficult. Summary of the invention

[0004] In order to solve the problem of reducing the noise of the vibration signal generated by the friction of a sliding friction pair, the present invention provides a method and system for reducing the noise of the friction vibration signal of a sliding friction pair.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A method for reducing noise of friction vibration signals of a sliding friction pair, specifically comprising the following steps:

[0007] Acquire a vibration signal of the sliding friction pair in a normal operation state as a first vibration signal; acquire a vibration signal of the sliding friction pair in an abnormal wear operation state as a second vibration signal;

[0008] Decomposing the first vibration signal and the second vibration signal respectively by using an empirical mode decomposition (EMD) method to obtain a plurality of first IMF components and a plurality of second IMF components;

[0009] Calculate the correlation coefficient of the IMF components in the same frequency band between the multiple first IMF components and the multiple second IMF components, retain the IMF components whose correlation coefficients meet the set conditions in the first IMF components and the second IMF components, perform signal reconstruction according to the signal retained in the first IMF component to obtain a normal reconstructed signal; perform signal reconstruction according to the signal retained in the second IMF component to obtain a wear reconstructed signal; the normal reconstructed signal and the wear reconstructed signal are the vibration signals after noise reduction; wherein, calculate the correlation coefficient of the IMF components in the same frequency band between the multiple first IMF components and the multiple second IMF components, specifically through the following steps:

[0010] Select two IMF components of the same frequency band as and , use signal To approximate the signal , It is expressed as:

[0011] ;

[0012] in, are real coefficients; is the approximate error signal;

[0013] According to the error signal Energy Get the coefficient of the error signal energy value, according to which the error signal energy is minimized The value is calculated to approximate the minimum error signal energy value , according to the energy value of the minimum error signal Get the correlation coefficient , specifically:

[0014] ;

[0015] in, is the approximate minimum error signal energy value; for The normalized value of Indicates signal energy.

[0016] Preferably, the step of using an empirical mode decomposition (EMD) method to decompose the first vibration signal and the second vibration signal respectively comprises the following steps:

[0017] S1. Determine the original signal to be decomposed The local minimum and local maximum of the curve are connected by the cubic spline interpolation curve to form the lower envelope. and upper envelope ;

[0018] S2. Calculate the average value curve of the upper envelope and the lower envelope ;

[0019] S3, the original signal to be decomposed Subtract to get a new sequence ;like Satisfy the IMF component stop condition, the is the original signal to be decomposed The first IMF component IMF1;

[0020] S4. If The IMF component stopping condition is not met. It will be set as the signal to be decomposed, and the calculation from step S1 to step S4 will be repeated. times until The stopping condition is met;

[0021] S5, the original signal , and get the remaining signal , IMF1 represents the high-frequency part of the signal to be decomposed;

[0022] S6, the remaining signal As the signal to be decomposed, the calculations from step S1 to step S5 are performed again to obtain , that is, the second IMF component IMF2; repeat times, namely:

[0023] ;

[0024] when When it is a monotonic function, the decomposition stops and the original signal to be decomposed is It is expressed as:

[0025] ;

[0026] in, is the remaining term, which indicates the changing trend of the signal.

[0027] Preferably, the error signal Energy Get the coefficient of the error signal energy value, according to which the error signal energy is minimized The value is calculated to approximate the minimum error signal energy value , specifically:

[0028] ;

[0029] ;

[0030] ;

[0031] in, for The normalized value of .

[0032] Preferably, the setting condition is specifically to set a threshold of the correlation coefficient, and retain the IMF components whose correlation coefficients are greater than the set threshold.

[0033] Preferably, the abnormal wear of the friction pair specifically includes adhesive wear, abrasive wear, fatigue wear and corrosive wear.

[0034] The present invention also provides a sliding friction pair friction vibration signal noise reduction system, which specifically includes:

[0035] The data acquisition module is used to acquire the vibration signal of the sliding friction pair in a normal operation state as a first vibration signal; and to acquire the vibration signal of the sliding friction pair in an abnormal wear operation state as a second vibration signal.

[0036] The data processing module is used to decompose the first vibration signal and the second vibration signal respectively by using an empirical mode decomposition (EMD) method to obtain a plurality of first IMF components and a plurality of second IMF components.

[0037] A noise reduction module is used to calculate the correlation coefficient of the IMF components of the same frequency band between the multiple first IMF components and the multiple second IMF components, retain the IMF components whose correlation coefficients meet the set conditions in the first IMF components and the second IMF components, perform signal reconstruction according to the signal retained in the first IMF component to obtain a normal reconstructed signal; perform signal reconstruction according to the signal retained in the second IMF component to obtain a wear reconstructed signal; the normal reconstructed signal and the wear reconstructed signal are the vibration signals after noise reduction; wherein, the correlation coefficient of the IMF components of the same frequency band between the multiple first IMF components and the multiple second IMF components is calculated, specifically through the following steps:

[0038] Select two IMF components of the same frequency band as and , use signal To approximate the signal , It is expressed as:

[0039] ;

[0040] in, are real coefficients; is the approximate error signal;

[0041] According to the error signal Energy Get the coefficient of the error signal energy value, according to which the error signal energy is minimized The value is calculated to approximate the minimum error signal energy value , according to the energy value of the minimum error signal Get the correlation coefficient , specifically:

[0042] ;

[0043] in, is the approximate minimum error signal energy value; for The normalized value of Indicates signal energy.

[0044] The present invention also provides a computer device, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps described in the method for reducing noise of friction vibration signals of sliding friction pairs.

[0045] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is loaded by a processor, the steps described in the method for reducing noise of friction vibration signals of sliding friction pairs can be executed.

[0046] The method for reducing noise of friction vibration signals of sliding friction pairs provided by the present invention has the following beneficial effects:

[0047] The present invention obtains the vibration signals of the sliding friction pair in the normal operation state and the abnormal wear operation state, decomposes and processes them through the EMD method, obtains multiple IMF components, and can perform frequency modulation or amplitude modulation on the IMF components according to the needs, improve the speed of decomposing the signal, and achieve the processing of the signal with nonlinear and non-stationary characteristics such as friction vibration. The correlation coefficient between the IMF components in the same frequency band is calculated, and the correlation analysis is performed, and the IMF components with correlation coefficients greater than the set threshold are retained. The signal reconstruction using the retained IMF components is the signal after noise reduction, which is convenient for the subsequent identification of the wear state of the friction pair through the vibration signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 The present invention is a flowchart of a method for reducing noise of a friction vibration signal of a sliding friction pair according to an embodiment of the present invention.

[0050] Figure 2 Schematic diagram of a normal signal in an embodiment of the present invention.

[0051] Figure 3 Schematic diagram of wear signal in an embodiment of the present invention.

[0052] Figure 4 This is a diagram of the normal signal decomposition result in an embodiment of the present invention.

[0053] Figure 5 This is a diagram showing the decomposition results of the wear signal in an embodiment of the present invention.

[0054] Figure 6 Result diagram of correlation coefficients between signal IMF components in an embodiment of the present invention.

[0055] Figure 7 Schematic diagram of a signal after noise reduction of a normal signal in an embodiment of the present invention.

[0056] Figure 8 Schematic diagram of the signal after the wear signal is denoised in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0058] Example

[0059] The present invention provides a method for reducing noise of friction vibration signal of sliding friction pair, such as Figure 1 As shown, the specific steps include:

[0060] Step 1: Collect the vibration signal of the sliding friction pair in the normal operation state and save it as the first vibration signal. Collect the vibration signal of the sliding friction pair in the abnormal wear operation state as the second vibration signal. The wear state includes abnormal wear such as adhesive wear, abrasive wear, fatigue wear and corrosive wear. Figure 2 is a normal signal; Figure 3 A sign of wear.

[0061] Step 2: Decompose the first vibration signal and the second vibration signal respectively using EMD and its improved method, and obtain multiple IMF components of the first vibration signal and the second vibration signal respectively. EMD and its improved method include: EMD, integrated empirical mode EEMD, complementary set empirical mode decomposition CEEMD, and improved complete set empirical mode decomposition CEEMDAN.

[0062] (1) For the original signal to be decomposed First, determine its local minimum and local maximum, and connect all local minimum and local maximum values ​​through the cubic spline interpolation curve to form the lower envelope and upper envelope .

[0063] (2) Find the average value curve of the upper and lower envelopes ,Right now:

[0064] .

[0065] (3) The original signal to be decomposed The mean curve Subtract to get a new sequence , this sequence removes the low-frequency components of the original signal, namely:

[0066] ;

[0067] if If the IMF component stopping condition is met, then The original signal to be decomposed The first IMF component of is denoted as IMF1.

[0068] (4) If If the IMF component stopping condition is not met, then It will be set as the signal to be decomposed, and steps (1) to (3) will be calculated again, and the cycle will continue. times until The stopping condition is met, namely:

[0069] ;

[0070] make ,but is IMF1, which contains the high-frequency part of the signal to be decomposed.

[0071] (5) The original signal minus , and obtain the residual signal without the high-frequency part ,Right now:

[0072] ;

[0073] Will As the signal to be decomposed, the operation is performed again according to steps (1) to (5), thereby obtaining , which is IMF2. Repeat this process times, namely:

[0074] ;

[0075] when is a monotonic function, the decomposition stops, and the original signal to be decomposed It can be expressed as:

[0076] ;

[0077] In the formula, is the remaining term, which indicates the changing trend of the signal.

[0078] The original signal is decomposed into IMF and a remainder. Represents the components of the original signal in different frequency bands from high to low. Indicates the changing trend of the signal. Figure 4 and Figure 5 These are the decomposition results of normal signal and wear signal respectively.

[0079] Step 3: Calculate the correlation coefficients between the IMF components of the same frequency band in the first vibration signal and the second vibration signal respectively, and retain the IMF components whose correlation coefficients are greater than a set threshold.

[0080] The correlation coefficient can be used to quantitatively measure the correlation between two signals. To approximate the signal hour, It can be expressed as:

[0081] ;

[0082] In the formula, are real coefficients; is the approximate error signal. Error signal Energy Specifically:

[0083] ;

[0084] To minimize the energy of the error signal Values ​​must satisfy:

[0085] ;

[0086] From this, we can use Indicated The best coefficient ,Right now:

[0087] ;

[0088] Substituting this into the error signal Energy The approximate minimum error signal energy value is obtained Specifically:

[0089] ;

[0090] The first term on the right side of the formula represents the original signal The energy of the above formula is normalized to obtain:

[0091] ;

[0092] make , The relative error is:

[0093] ;

[0094] Will Signal and The correlation coefficient of .

[0095] Furthermore, according to the integral Schwarz inequality,

[0096] ;

[0097] We can get:

[0098] ;

[0099] Correlation coefficient It can be used to describe the similarity or dependence of two signal waveforms. ,and When and The waveform and polarity are the same at the same time scale, only the amplitude is enlarged or reduced, and we get ;when ,and When , it means that the two signals have the same waveform at the same time scale, opposite polarity, and also have scaled amplitude. .therefore, It shows that the waveforms of the two signals are the same at the same time scale. On the contrary, if the correlation coefficient , which is equivalent to The numerator of is 0, that is indicate signal and Not relevant. , The closer it is to 1, the higher the approximation degree of the two signals is, the smaller the approximation error is, that is, the higher the correlation between the two signals is; conversely, The closer it is to 0, the lower the approximation degree of the two signals, the larger the approximation error, that is, the smaller the correlation between the two signals. Figure 6 is the correlation coefficient between the IMF components of the signal.

[0100] Therefore, when When , the two signals are slightly correlated; When , the two signals are correlated; When , the two signals are significantly correlated; , the two signals are highly correlated.

[0101] Step 4: Reconstruct the signal using the retained IMF components to obtain a normal reconstructed signal and a worn reconstructed signal. The reconstructed signal is the signal after noise reduction, such as Figure 7 and Figure 8 They are the reconstructed signals of normal signal and wear signal respectively.

[0102] The beneficial effects of the present invention are as follows: the EMD method is used to adaptively decompose the signal according to the intrinsic characteristics of the signal itself, thereby obtaining IMF components with frequency components arranged from high to low, wherein each IMF contains different time measurement characteristics, contains the real physical meaning of the original signal, and can perform a deeper adaptive multi-resolution analysis on the signal; at the same time, the IMF components can be frequency modulated or amplitude modulated as needed, and the speed of decomposing the signal can be increased by changing the instantaneous frequency and amplitude, so that the EMD method can process signals with nonlinear and non-stationary characteristics such as friction vibration. The method of the present invention can improve the accuracy of identifying the wear state of the friction pair through the friction vibration signal.

[0103] The present invention also provides a sliding friction pair friction vibration signal noise reduction system, which specifically includes:

[0104] The data acquisition module is used to acquire the vibration signal of the sliding friction pair in a normal operation state as a first vibration signal; and to acquire the vibration signal of the sliding friction pair in an abnormal wear operation state as a second vibration signal.

[0105] The data processing module is used to decompose the first vibration signal and the second vibration signal respectively by using an empirical mode decomposition (EMD) method to obtain a plurality of first IMF components and a plurality of second IMF components.

[0106] A noise reduction module is used to calculate the correlation coefficients of the IMF components of the same frequency band between the multiple first IMF components and the multiple second IMF components, retain the IMF components whose correlation coefficients meet the set conditions in the first IMF components and the second IMF components, reconstruct the signal according to the signal retained in the first IMF component to obtain a normal reconstructed signal; reconstruct the signal according to the signal retained in the second IMF component to obtain a wear reconstructed signal; the normal reconstructed signal and the wear reconstructed signal are the vibration signals after noise reduction; wherein, the correlation coefficients of the IMF components of the same frequency band between the multiple first IMF components and the multiple second IMF components are calculated, specifically through the following steps:

[0107] Select two IMF components of the same frequency band as and , use signal To approximate the signal , It is expressed as:

[0108] ;

[0109] in, are real coefficients; is the approximate error signal;

[0110] According to the error signal Energy Get the coefficient of the error signal energy value, according to the minimum energy of the error signal The value is calculated to approximate the minimum error signal energy value , according to the minimum error signal energy value Get the correlation coefficient , specifically:

[0111] ;

[0112] in, is the approximate minimum error signal energy value; for The normalized value of Indicates signal energy.

[0113] Each module in the above-mentioned sliding friction pair friction vibration signal noise reduction system can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0114] The present invention also provides a computer device, including a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps in an embodiment of a method for reducing noise of a friction vibration signal of a sliding friction pair. The specific implementation method can be found in the method embodiment, which will not be described in detail here.

[0115] Furthermore, the present invention also provides a non-temporary computer-readable storage medium containing instructions, and a computer program is stored on the storage medium. For example, a memory containing instructions, the above instructions can be executed by a processor of a computer device to complete the above method. For example, a non-temporary computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device. When the computer program is executed by the processor, it can implement the steps in an embodiment of a method for reducing the noise of a friction vibration signal of a sliding friction pair. The specific implementation method can be found in the method embodiment, which will not be repeated here.

[0116] It should be understood by those skilled in the art that embodiments of the present invention may provide methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as a combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0120] It should be pointed out that the specific implementation methods described above can enable those skilled in the art to understand the invention more comprehensively, but do not limit the invention in any way. Therefore, although the invention has been described in detail in this specification and embodiments, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the patent for the invention. Any figure mark in the claims should not be regarded as limiting the claims involved. Any simple change or equivalent replacement of the technical solution that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention belongs to the protection scope of the present invention.

Claims

1. A method for reducing noise of friction vibration signal of sliding friction pair, characterized in that: The following steps are involved: Acquire a vibration signal of the sliding friction pair in a normal operation state as a first vibration signal; acquire a vibration signal of the sliding friction pair in an abnormal wear operation state as a second vibration signal; Decomposing the first vibration signal and the second vibration signal respectively by using an empirical mode decomposition (EMD) method to obtain a plurality of first IMF components and a plurality of second IMF components; Calculate the correlation coefficient of the IMF components in the same frequency band between the multiple first IMF components and the multiple second IMF components, retain the IMF components whose correlation coefficients meet the set conditions in the first IMF components and the second IMF components, perform signal reconstruction according to the signal retained in the first IMF component to obtain a normal reconstructed signal; perform signal reconstruction according to the signal retained in the second IMF component to obtain a wear reconstructed signal; the normal reconstructed signal and the wear reconstructed signal are the vibration signals after noise reduction; wherein, calculate the correlation coefficient of the IMF components in the same frequency band between the multiple first IMF components and the multiple second IMF components, specifically through the following steps: Select two IMF components of the same frequency band as x(t) and y(t), use signal y(t) to approximate signal x(t), x(t) is expressed as: x(t)=k xy y(t)+e(t); Among them, k xy is a real coefficient; e(t) is the approximate error signal; According to the energy ∈ of the approximate error signal e(t), the real coefficient k of the error signal energy is obtained xy value, according to which the error signal energy is minimized xy The value is calculated to approximate the minimum error signal energy value ∈ min , according to the minimum error signal energy value ∈ min Get the correlation coefficient r xy , specifically: Among them, ∈ min is the approximate minimum error signal energy value; ∈ min The normalized value of Represents the energy of the signal x(t).

2. A method for reducing noise of friction vibration signal of sliding friction pair according to claim 1, characterized in that: The method of using the empirical mode decomposition (EMD) method to decompose the first vibration signal and the second vibration signal respectively specifically comprises the following steps: S1. Determine the local minimum and local maximum of the original signal x1(t) to be decomposed, and connect all the local minimum and local maximum through the cubic spline interpolation curve to form the lower envelope y low (t) and the upper envelope y up (t); S2, calculating the average value curve m1(t) of the upper envelope and the lower envelope; S3, subtracting the original signal to be decomposed x1(t) from the average value curve m1(t) to obtain a new sequence h1(t); if h1(t) satisfies the IMF component stopping condition, h1(t) is the first IMF component IMF1 of the original signal to be decomposed x1(t); S4, if h1(t) does not meet the IMF component stop condition, h1(t) will be set as the signal to be decomposed, and the calculation from step S1 to step S4 will be repeated for k times until h1(t) meets the IMF component stop condition. 1k (t) the stopping condition is met; S5, subtract c1(t) from the original signal to be decomposed x1(t) to obtain a residual signal Res1(t), wherein c1(t) is IMF1, which represents the high frequency part of the signal to be decomposed; S6, taking the residual signal Res1(t) as the signal to be decomposed, and performing the operations from step S1 to step S5 again, to obtain c2(t), i.e., the second IMF component IMF2; repeat n times, i.e.: When Res n When (t) is a monotonic function, the decomposition stops and the original signal x1(t) to be decomposed is expressed as: Among them, Res n (t) is the residual term, which indicates the changing trend of the signal.

3. The method for reducing noise of friction vibration signal of sliding friction pair according to claim 1, characterized in that: The real coefficient k of the error signal energy is obtained according to the energy ∈ of the approximate error signal e(t): xy value, according to which the error signal energy is minimized xy The value is calculated to approximate the minimum error signal energy value ∈ min , specifically: in, for∈ min The normalized value of 4. The method for reducing noise of friction vibration signal of sliding friction pair according to claim 1, characterized in that: The setting condition specifically sets a threshold of the correlation coefficient, and retains the IMF components whose correlation coefficients are greater than the set threshold.

5. The method for reducing noise of friction vibration signal of sliding friction pair according to claim 1, characterized in that: The abnormal wear of the friction pair specifically includes adhesive wear, abrasive wear, fatigue wear and corrosive wear.

6. A sliding friction pair friction vibration signal noise reduction system, characterized in that: include: A data acquisition module, used to acquire a vibration signal of the sliding friction pair in a normal operating state as a first vibration signal; Acquire a vibration signal of the sliding friction pair in an abnormal wear operation state as a second vibration signal; A data processing module, used for respectively decomposing the first vibration signal and the second vibration signal by using an empirical mode decomposition (EMD) method to obtain a plurality of first IMF components and a plurality of second IMF components; A noise reduction module is used to calculate the correlation coefficient of the IMF components of the same frequency band between the multiple first IMF components and the multiple second IMF components, retain the IMF components whose correlation coefficients meet the set conditions in the first IMF components and the second IMF components, perform signal reconstruction according to the signal retained in the first IMF component to obtain a normal reconstructed signal; perform signal reconstruction according to the signal retained in the second IMF component to obtain a wear reconstructed signal; the normal reconstructed signal and the wear reconstructed signal are the vibration signals after noise reduction; wherein, the correlation coefficient of the IMF components of the same frequency band between the multiple first IMF components and the multiple second IMF components is calculated, specifically through the following steps: Select two IMF components of the same frequency band as x(t) and y(t), use signal y(t) to approximate signal x(t), x(t) is expressed as: x(t)=k xy y(t)+e(t); Among them, k xy is a real coefficient; e(t) is the approximate error signal; According to the energy ∈ of the approximate error signal e(t), the real coefficient k of the error signal energy is obtained xy value, according to which the error signal energy is minimized xy The value is calculated to approximate the minimum error signal energy value ∈ min , according to the minimum error signal energy value ∈ min Get the correlation coefficient r xy , specifically: Among them, ∈ min is the approximate minimum error signal energy value; ∈ min The normalized value of Represents the energy of the signal x(t).

7. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is loaded into a processor, it can execute the steps of the method according to any one of claims 1 to 5.

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