Friction and wear detection device, characterization method and system based on acoustic emission signals

Abstract

The application provides a friction and wear detection device, a characterization method and a system based on acoustic emission signals, comprising an acoustic emission clamp for a pin-on-disc friction and wear tester and an acoustic emission signal acquisition and measurement test bench; the acoustic emission clamp comprises a fixing rod, a signal connector, an acoustic emission sensor, a locking nut and a pin sample; the acoustic emission signal acquisition and measurement test bench comprises an acoustic emission sensor, a signal amplifier and an acoustic emission signal acquisition board card. The application monitors and analyzes the acoustic emission signals on the surface of the sample, reflects the changes of the sample surface in the friction and wear process in real time, thereby accurately characterizing the friction and wear performance of the sample, without disassembling the sample, and has the advantage of real-time monitoring.

Description

Technical Field

[0001] This invention relates to the field of material friction and wear detection technology, and more specifically, to a friction and wear detection device, characterization method, and system based on acoustic emission signals. Background Technology

[0002] Tribology and wear testing technology is an important research area in engineering. It is widely used in various industrial equipment and mechanical systems to evaluate the tribological properties of materials in order to design and improve various mechanical systems and industrial equipment. Therefore, the study of tribological mechanisms and behaviors has important practical significance.

[0003] Pin-disc friction and wear testing is a method for evaluating the friction and wear properties of materials, widely used in the assessment of the friction performance of various materials, such as metals, polymers, and ceramics. This experimental method can not only evaluate the friction properties of materials but also study their friction and wear mechanisms. However, when conducting friction tests using current friction and wear testing machines, both the wear amount and wear track detection require manual transfer to the corresponding measuring instruments after the machine is stopped. This process is cumbersome and time-consuming, and it cannot characterize the entire friction and wear state in real time. Therefore, a method is needed that can characterize the friction and wear state in real time to assess the material's condition during friction testing.

[0004] Patent document CN112461933A (application number: CN202011284723.0) discloses a method for detecting acoustic emission characteristic signals of weld crack propagation. This method includes the following steps: preparing a compact tensile specimen; performing a tensile test on the compact tensile specimen and detecting the vibration of the tensile testing machine and the friction acoustic emission characteristic signals during the tensile process to obtain the interference characteristic signal curve in the acoustic emission test of weld crack propagation; preparing the compact tensile specimen; setting the signal acquisition threshold value of the acoustic emission detection software based on the interference signal characteristic curve of the compact tensile specimen; performing a tensile test on the compact tensile specimen and detecting the acoustic emission characteristic signals of the pre-existing crack source propagation during the tensile process to obtain the characteristic curve of the acoustic emission signal of weld crack propagation; after the tensile test, subjecting the compact tensile specimen to fatigue fracture; and determining the crack propagation characteristic morphology of the fracture surface of the compact tensile specimen. However, this patent cannot solve the existing technical problems and cannot meet the needs of this invention. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the purpose of this invention is to provide a friction and wear detection device, characterization method and system based on acoustic emission signals.

[0006] The friction and wear detection device based on acoustic emission signals provided by the present invention includes an acoustic emission fixture for a pin-disc friction and wear testing machine and an acoustic emission signal acquisition and measurement experimental platform;

[0007] The acoustic emission fixture includes a fixing rod, a signal connector, an acoustic emission sensor, a locking nut, and a pin sample;

[0008] The fixed rod is connected to the friction testing machine through a threaded locking mechanism, and a hole is drilled in the middle of the fixed rod for connecting the signal line of the acoustic emission sensor to the acoustic emission sensor;

[0009] A pre-sized annular boss is left at one end of the locking nut for positioning the acoustic emission sensor. The diameter of the hole in the annular boss is larger than the diameter of the signal connector but smaller than the diameter of the acoustic emission sensor.

[0010] The pin sample is fixed to the fixing rod by a locking nut. The upper bottom surface of the pin sample is in contact with the lower bottom surface of the acoustic emission sensor. Coupling agent is applied between the pin sample and the emission sensor.

[0011] The acoustic emission signal acquisition and measurement experimental platform includes an acoustic emission sensor, a signal amplifier, and an acoustic emission signal acquisition board;

[0012] The acoustic emission sensor is connected to a signal amplifier, and the collected signal is amplified by the signal amplifier and then transmitted to the acoustic emission signal acquisition board.

[0013] The acoustic emission acquisition board connects to a signal amplifier via a BNC connector at the front end to receive the amplified signal, and connects to a PC via a USB interface at the back end for developing and setting up the acquisition program.

[0014] Preferably, the acoustic emission sensor is a narrowband miniature sensor;

[0015] The signal amplifier selects different amplification factors according to different operating conditions to obtain data with a suitable signal-to-noise ratio and a maximum value not exceeding the range of the acquisition card.

[0016] The friction and wear characterization method based on acoustic emission signals provided by the present invention performs the following steps:

[0017] Step 1: Fix the acoustic emission sensor fixture with the pin sample on it onto the friction testing machine and make it contact the disc of the friction testing machine. Set the experimental parameters, start the experiment, and start the acoustic emission acquisition program.

[0018] Step 2: Segment and store the acquired raw acoustic emission signal, and process it in real time to calculate the root mean square value and amplitude spectrum;

[0019] Step 3: Observe the friction and wear state of the material based on the root mean square signal and amplitude spectrum displayed on the acquisition interface;

[0020] Step 4: Plot the root mean square curve to compare and obtain the material friction and wear under different working conditions.

[0021] Preferably, the friction speed is adjusted by adjusting the distance between the contact surface and the center of the disk or the angular velocity of the disk rotation, and different experimental conditions, including load and disk rotation angular velocity, are set on the friction testing machine to simulate real working conditions.

[0022] After the experiment begins, the acoustic emission signal acquisition program is started simultaneously. In the friction experiment, the acoustic emission sensor acquires the ultra-high frequency stress wave pulse signal generated by the change in stress distribution in the contact area when the two surfaces of the pin and the disc are in contact and move together. The signal acquired by the acoustic emission sensor is converted into an electrical signal by the signal amplifier and the acoustic emission signal acquisition board and displayed in real time on the acquisition interface.

[0023] Preferably, step 2 includes:

[0024] The acquired signals are segmented and stored as raw data. Specifically, a clock is set inside the program to store a data file at preset intervals.

[0025] In real-time data processing, a producer-consumer model is adopted to ensure the real-time performance of data processing. Data is collected at the producer level and analyzed and stored at the consumer level. Data processing includes the extraction of root mean square signal and amplitude spectrum.

[0026] Preferably, step 3 includes:

[0027] The amplitude spectrum of the original acoustic emission signal is extracted by windowing and performing short-time Fourier transform. This spectrum is used to observe the stability of the friction process in the friction and wear experiment. By observing the dominant frequency when the friction and wear experiment is stable, the friction and wear amount under different working conditions is evaluated.

[0028] The acoustic emission signal has a sampling frequency of 1MHz, which is a high-frequency signal. A high-pass filter is designed to preprocess the signal. The filtered signal x... i Calculate the root mean square (RMS) value, which represents the amount of friction and wear in this stage. The calculation formula is as follows:

[0029]

[0030] Among them, X rms To calculate the root mean square value, the data length is 0.1s, which means 100,000 points are selected for calculation, i.e., n = 100,000, 0 ≤ i ≤ n;

[0031] The processed root mean square (RMS) signal is displayed in real time on the acquisition interface, and the processed data is stored in the same table. After the experiment, the RMS change curve of the acoustic emission signal throughout the entire process is plotted using a plotting tool. The entire signal is observed, and the part with a larger RMS value amplitude is the stage where the friction and wear are more severe.

[0032] The friction and wear characterization system based on acoustic emission signals provided by the present invention includes the following modules:

[0033] Module M1: Fix the acoustic emission sensor fixture with the pin sample on it onto the friction testing machine and make it contact the disc of the friction testing machine. Set the experimental parameters, start the experiment, and start the acoustic emission acquisition program.

[0034] Module M2: The acquired raw acoustic emission signal is segmented and stored, and processed in real time to calculate the root mean square value and amplitude spectrum;

[0035] Module M3: Observes the friction and wear state of the material based on the root mean square signal and amplitude spectrum displayed on the acquisition interface;

[0036] Module M4: Plots root mean square curves to compare and obtain the material friction and wear under different working conditions.

[0037] Preferably, the friction speed is adjusted by adjusting the distance between the contact surface and the center of the disk or the angular velocity of the disk rotation, and different experimental conditions, including load and disk rotation angular velocity, are set on the friction testing machine to simulate real working conditions.

[0038] After the experiment begins, the acoustic emission signal acquisition program is started simultaneously. In the friction experiment, the acoustic emission sensor acquires the ultra-high frequency stress wave pulse signal generated by the change in stress distribution in the contact area when the two surfaces of the pin and the disc are in contact and move together. The signal acquired by the acoustic emission sensor is converted into an electrical signal by the signal amplifier and the acoustic emission signal acquisition board and displayed in real time on the acquisition interface.

[0039] Preferably, the module M2 includes:

[0040] The acquired signals are segmented and stored as raw data. Specifically, a clock is set inside the program to store a data file at preset intervals.

[0041] In real-time data processing, a producer-consumer model is adopted to ensure the real-time performance of data processing. Data is collected at the producer level and analyzed and stored at the consumer level. Data processing includes the extraction of root mean square signal and amplitude spectrum.

[0042] Preferably, the module M3 includes:

[0043] The amplitude spectrum of the original acoustic emission signal is extracted by windowing and performing short-time Fourier transform. This spectrum is used to observe the stability of the friction process in the friction and wear experiment. By observing the dominant frequency when the friction and wear experiment is stable, the friction and wear amount under different working conditions is evaluated.

[0044] The acoustic emission signal has a sampling frequency of 1MHz, which is a high-frequency signal. A high-pass filter is designed to preprocess the signal. The filtered signal x... i Calculate the root mean square (RMS) value, which represents the amount of friction and wear in this stage. The calculation formula is as follows:

[0045]

[0046] Among them, X rms To calculate the root mean square value, the data length is 0.1s, which means 100,000 points are selected for calculation, i.e., n = 100,000, 0 ≤ i ≤ n;

[0047] The processed root mean square (RMS) signal is displayed in real time on the acquisition interface, and the processed data is stored in the same table. After the experiment, the RMS change curve of the acoustic emission signal throughout the entire process is plotted using a plotting tool. The entire signal is observed, and the part with a larger RMS value amplitude is the stage where the friction and wear are more severe.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] (1) The friction and wear characterization method based on acoustic emission signal proposed in this invention is applicable to most friction experiments and can meet the observation of material friction and wear state at different time points in the same set of experiments. This characterization method does not require disassembling the experimental disk for measurement, which greatly saves the measurement time of friction and wear.

[0050] (2) The friction and wear characterization method proposed in this invention monitors and analyzes the acoustic emission signal on the sample surface, and reflects the changes of the sample surface in the friction and wear process in real time, thereby accurately characterizing the friction and wear performance of the sample. This method uses the amplitude spectrum and root mean square value of the acoustic emission signal to characterize the friction and wear amount of the material in the friction experiment. It does not require disassembling the sample and has the advantages of non-contact testing and real-time monitoring.

[0051] (3) The present invention provides an acoustic emission sensor fixture that can tightly attach the sensor to the sample surface, thereby improving the accuracy and stability of signal acquisition. The fixture has a simple structure, is easy to manufacture, and can be directly installed and used on a pin-disc friction and wear testing machine. Attached Figure Description

[0052] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0053] Figure 1 This is a schematic flowchart of a friction and wear characterization method based on acoustic emission signals provided by the present invention.

[0054] Figure 2This is a schematic diagram of the acoustic emission signal acquisition and processing flow in this invention;

[0055] Figure 3 This is a schematic diagram of a pin-disc friction and wear experiment according to an example of the present invention;

[0056] Figure 4 This is a schematic diagram of the acoustic emission sensor fixture provided by the present invention. Detailed Implementation

[0057] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0058] Example 1:

[0059] like Figure 3 and Figure 4 This invention proposes a friction and wear detection device based on acoustic emission signals, which solves the problem that when using current friction and wear testing machines for friction testing, both the wear amount and wear track detection require stopping the machine and manually transferring the data to the corresponding measuring instrument for observation. This process is very cumbersome and time-consuming, and it is impossible to characterize the entire friction and wear state in real time. This invention effectively improves the detection efficiency of material friction and wear.

[0060] The friction and wear detection device based on acoustic emission signals includes an acoustic emission fixture for a pin-disc friction and wear testing machine, comprising a fixing rod, a signal connector, an acoustic emission sensor, a locking nut, and a pin sample.

[0061] The fixed rod is connected to the friction testing machine through a threaded locking mechanism. A hole is drilled in the middle of the fixed rod for connecting the acoustic emission sensor signal line to the acoustic emission sensor. An annular boss is left at one end of the locking nut for positioning the acoustic emission sensor. The diameter of the hole of the annular boss is required to be larger than the diameter of the signal connector and smaller than the diameter of the acoustic emission sensor to ensure that the acoustic emission sensor will not move upward when a load is applied.

[0062] The upper bottom surface of the pin sample contacts the lower bottom surface of the acoustic emission sensor, with coupling agent applied in between to ensure complete contact between the surfaces.

[0063] The pin sample is fixed to the fixed rod by a lock nut, which also ensures that the pin sample is in close contact with the acoustic emission sensor.

[0064] The friction and wear detection device based on acoustic emission signals also includes an acoustic emission signal acquisition and measurement experimental platform, which includes an acoustic emission sensor, a signal amplifier, and an acoustic emission signal acquisition board.

[0065] To ensure the above-mentioned acoustic emission fixture assembly requirements, the acoustic emission sensor must be a narrow-band small sensor.

[0066] The signal amplifier has three amplification levels: 20dB, 40dB, and 60dB. The appropriate amplification factor can be selected according to different operating conditions to obtain data with a suitable signal-to-noise ratio that does not exceed the range of the data acquisition card.

[0067] The front end of the acoustic emission acquisition board connects to the amplified signal via a BNC connector, while the back end connects to a PC via a USB interface for developing and configuring the acquisition program.

[0068] like Figure 1 This invention provides a method for characterizing friction and wear based on acoustic emission signals, comprising the following steps:

[0069] The acoustic emission sensor fixture with pins is installed on the friction testing machine and contacts the disc. The friction speed is adjusted by adjusting the distance between the contact surface and the center of the disc or the rotational angular velocity of the disc. Different experimental conditions such as load and disc rotational angular velocity are set on the friction testing machine to simulate real working conditions. After the experiment starts, the acoustic emission signal acquisition program is started simultaneously.

[0070] In the friction experiment, an acoustic emission sensor collects ultra-high frequency stress wave pulse signals generated by the change in stress distribution in the contact area when the two surfaces of the pin and disc move into contact. The acoustic emission sensor converts these signals into electrical signals through an amplifier and a data acquisition card, which are then displayed in real time on the acquisition interface.

[0071] Some friction and wear experiments require long-term operation to simulate wear under actual use conditions. However, acoustic emission signals are high-frequency signals. In this invention, the sampling rate of the acoustic emission signal is 1MHz. A large amount of data will be generated during the acquisition process, which places high demands on signal storage and processing.

[0072] This invention proposes a solution for signal storage and processing: segmented storage of raw data and real-time processing of feature variables. Figure 2 An internal clock is set to store a data file every 60 seconds, with each file being approximately 5GB in size. A producer-consumer model is used to ensure real-time data processing. The producer acquires data, while the consumer analyzes and stores it. Data processing includes the extraction of the root mean square signal and amplitude spectrum.

[0073] The amplitude spectrum of the original acoustic emission signal is extracted by windowing and performing short-time Fourier transform. This spectrum is used to observe the stability of the friction process in the friction and wear experiment. By observing the dominant frequency when the friction and wear experiment is stable, the friction and wear amount under different working conditions is evaluated.

[0074] The acoustic emission signal is sampled at a frequency of 1MHz, which is a high-frequency signal. A high-pass filter is designed to preprocess the signal and reduce low-frequency noise interference. The root mean square (RMS) value of the filtered signal is calculated, and the magnitude of the RMS value is used to characterize the amount of friction and wear at this stage. The calculation formula is as follows:

[0075]

[0076] Among them, X rms To calculate the root mean square value, the data length is 0.1s, which means 100,000 points are selected for calculation, i.e., n = 100,000, 0 ≤ i ≤ n.

[0077] The processed root-mean-square (RMS) signal is also displayed in real time on the acquisition interface, and the processed data is stored in the same table. After the experiment, the RMS variation curve of the acoustic emission signal throughout the entire process can be plotted using graphing tools. By observing the entire signal, the part with the larger RMS value indicates the stage of most severe friction and wear. By analyzing the RMS variation curves of the acoustic emission signal under different working conditions, the amount of material wear in the friction and wear experiment can be compared.

[0078] The method and apparatus provided by this invention can be widely used in the testing and research of material friction and wear properties, and have potential industrial application prospects.

[0079] Example 2:

[0080] The present invention also provides a friction and wear characterization system based on acoustic emission signals. The friction and wear characterization system based on acoustic emission signals can be implemented by executing the process steps of the friction and wear characterization method based on acoustic emission signals. That is, those skilled in the art can understand the friction and wear characterization method based on acoustic emission signals as a preferred embodiment of the friction and wear characterization system based on acoustic emission signals.

[0081] The friction and wear characterization system based on acoustic emission signals provided by the present invention includes the following modules:

[0082] Module M1: Fix the acoustic emission sensor fixture with the pin sample on it onto the friction testing machine and make it contact the disc of the friction testing machine. Set the experimental parameters, start the experiment, and start the acoustic emission acquisition program.

[0083] Module M2: The acquired raw acoustic emission signal is segmented and stored, and processed in real time to calculate the root mean square value and amplitude spectrum;

[0084] Module M3: Observes the friction and wear state of the material based on the root mean square signal and amplitude spectrum displayed on the acquisition interface;

[0085] Module M4: Plots root mean square curves to compare and obtain the material friction and wear under different working conditions.

[0086] Preferably, the friction speed is adjusted by adjusting the distance between the contact surface and the center of the disk or the angular velocity of the disk rotation, and different experimental conditions, including load and disk rotation angular velocity, are set on the friction testing machine to simulate real working conditions.

[0087] After the experiment begins, the acoustic emission signal acquisition program is started simultaneously. In the friction experiment, the acoustic emission sensor acquires the ultra-high frequency stress wave pulse signal generated by the change in stress distribution in the contact area when the two surfaces of the pin and the disc are in contact and move together. The signal acquired by the acoustic emission sensor is converted into an electrical signal by the signal amplifier and the acoustic emission signal acquisition board and displayed in real time on the acquisition interface.

[0088] Preferably, the module M2 includes:

[0089] The acquired signals are segmented and stored as raw data. Specifically, a clock is set inside the program to store a data file at preset intervals.

[0090] In real-time data processing, a producer-consumer model is adopted to ensure the real-time performance of data processing. Data is collected at the producer level and analyzed and stored at the consumer level. Data processing includes the extraction of root mean square signal and amplitude spectrum.

[0091] Preferably, the module M3 includes:

[0092] The amplitude spectrum of the original acoustic emission signal is extracted by windowing and performing short-time Fourier transform. This spectrum is used to observe the stability of the friction process in the friction and wear experiment. By observing the dominant frequency when the friction and wear experiment is stable, the friction and wear amount under different working conditions is evaluated.

[0093] The acoustic emission signal has a sampling frequency of 1MHz, which is a high-frequency signal. A high-pass filter is designed to preprocess the signal. The filtered signal x... i Calculate the root mean square (RMS) value, which represents the amount of friction and wear in this stage. The calculation formula is as follows:

[0094]

[0095] Among them, X rms To calculate the root mean square value, the data length is 0.1s, which means 100,000 points are selected for calculation, i.e., n = 100,000, 0 ≤ i ≤ n;

[0096] The processed root mean square (RMS) signal is displayed in real time on the acquisition interface, and the processed data is stored in the same table. After the experiment, the RMS change curve of the acoustic emission signal throughout the entire process is plotted using a plotting tool. The entire signal is observed, and the part with a larger RMS value amplitude is the stage where the friction and wear are more severe.

[0097] In the description of this application, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0098] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0099] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for characterizing friction and wear based on acoustic emission signals, characterized in that, The friction and wear detection device based on acoustic emission signals is used. The device includes an acoustic emission fixture for a pin-disc friction and wear testing machine and an acoustic emission signal acquisition and measurement experimental platform. The acoustic emission fixture includes a fixing rod, a signal connector, an acoustic emission sensor, a locking nut, and a pin sample; The fixed rod is connected to the friction testing machine through a threaded locking mechanism, and a hole is drilled in the middle of the fixed rod for connecting the signal line of the acoustic emission sensor to the acoustic emission sensor; A pre-sized annular boss is left at one end of the locking nut for positioning the acoustic emission sensor. The diameter of the hole in the annular boss is larger than the diameter of the signal connector but smaller than the diameter of the acoustic emission sensor. The pin sample is fixed to the fixing rod by a locking nut. The upper bottom surface of the pin sample is in contact with the lower bottom surface of the acoustic emission sensor. Coupling agent is applied between the pin sample and the emission sensor. The acoustic emission signal acquisition and measurement experimental platform includes an acoustic emission sensor, a signal amplifier, and an acoustic emission signal acquisition board; The acoustic emission sensor is connected to a signal amplifier, and the collected signal is amplified by the signal amplifier and then transmitted to the acoustic emission signal acquisition board. The acoustic emission acquisition board connects to a signal amplifier via a BNC connector at the front end to receive the amplified signal, and connects to a PC via a USB interface at the back end for developing and setting up the acquisition program. The acoustic emission sensor is a narrowband small sensor; The signal amplifier selects different amplification factors according to different operating conditions to obtain data with a suitable signal-to-noise ratio and a maximum value not exceeding the range of the acquisition card. The method performs the following steps: Step 1: Fix the acoustic emission sensor fixture with the pin sample on it onto the friction testing machine and make it contact the disc of the friction testing machine. Set the experimental parameters, start the experiment, and start the acoustic emission acquisition program. Step 2: Segment and store the acquired raw acoustic emission signal, and process it in real time to calculate the root mean square value and amplitude spectrum; Step 3: Observe the friction and wear state of the material based on the root mean square signal and amplitude spectrum displayed on the acquisition interface; Step 4: Plot the root mean square curve to compare and obtain the material friction and wear under different working conditions.

2. The method for characterizing friction and wear based on acoustic emission signals according to claim 1, characterized in that, The friction speed is adjusted by adjusting the distance between the contact surface and the center of the disk or the angular velocity of the disk rotation, and different experimental conditions, including load, are set on the friction testing machine to simulate real working conditions. After the experiment begins, the acoustic emission signal acquisition program is started simultaneously. In the friction experiment, the acoustic emission sensor acquires the ultra-high frequency stress wave pulse signal generated by the change in stress distribution in the contact area when the two surfaces of the pin and the disc are in contact and move together. The signal acquired by the acoustic emission sensor is converted into an electrical signal by the signal amplifier and the acoustic emission signal acquisition board and displayed in real time on the acquisition interface.

3. The method for characterizing friction and wear based on acoustic emission signals according to claim 1, characterized in that, Step 2 includes: The acquired signals are segmented and stored as raw data. Specifically, a clock is set inside the program to store a data file at preset intervals. In real-time data processing, a producer-consumer model is adopted to ensure the real-time performance of data processing. Data is collected at the producer level and analyzed and stored at the consumer level. Data processing includes the extraction of root mean square signal and amplitude spectrum.

4. The method for characterizing friction and wear based on acoustic emission signals according to claim 1, characterized in that, Step 3 includes: The amplitude spectrum of the original acoustic emission signal is extracted by windowing and performing short-time Fourier transform. This spectrum is used to observe the stability of the friction process in the friction and wear experiment. By observing the dominant frequency when the friction and wear experiment is stable, the friction and wear amount under different working conditions is evaluated. The acoustic emission signal has a sampling frequency of 1MHz, which is a high-frequency signal. A high-pass filter is designed to preprocess the signal. Calculate the root mean square (RMS) value, which represents the amount of friction and wear in this stage. The calculation formula is as follows: in, To calculate the root mean square value, the data length is 0.1s, which means 100,000 points are selected for calculation, i.e., n=100,000, 0≤i≤n; The processed root mean square (RMS) signal is displayed in real time on the acquisition interface, and the processed data is stored in the same table. After the experiment, the RMS change curve of the acoustic emission signal throughout the entire process is plotted using a plotting tool. The entire signal is observed, and the part with a larger RMS value amplitude is the stage where the friction and wear are more severe.

5. A friction and wear characterization system based on acoustic emission signals, characterized in that, The friction and wear detection device based on acoustic emission signals is used. The device includes an acoustic emission fixture for a pin-disc friction and wear testing machine and an acoustic emission signal acquisition and measurement experimental platform. The acoustic emission fixture includes a fixing rod, a signal connector, an acoustic emission sensor, a locking nut, and a pin sample; The fixed rod is connected to the friction testing machine through a threaded locking mechanism, and a hole is drilled in the middle of the fixed rod for connecting the signal line of the acoustic emission sensor to the acoustic emission sensor; A pre-sized annular boss is left at one end of the locking nut for positioning the acoustic emission sensor. The diameter of the hole in the annular boss is larger than the diameter of the signal connector but smaller than the diameter of the acoustic emission sensor. The pin sample is fixed to the fixing rod by a locking nut. The upper bottom surface of the pin sample is in contact with the lower bottom surface of the acoustic emission sensor. Coupling agent is applied between the pin sample and the emission sensor. The acoustic emission signal acquisition and measurement experimental platform includes an acoustic emission sensor, a signal amplifier, and an acoustic emission signal acquisition board; The acoustic emission sensor is connected to a signal amplifier, and the collected signal is amplified by the signal amplifier and then transmitted to the acoustic emission signal acquisition board. The acoustic emission acquisition board connects to a signal amplifier via a BNC connector at the front end to receive the amplified signal, and connects to a PC via a USB interface at the back end for developing and setting up the acquisition program. The acoustic emission sensor is a narrowband small sensor; The signal amplifier selects different amplification factors according to different operating conditions to obtain data with a suitable signal-to-noise ratio and a maximum value not exceeding the range of the acquisition card. The system includes the following modules: Module M1: Fix the acoustic emission sensor fixture with the pin sample on it onto the friction testing machine and make it contact the disc of the friction testing machine. Set the experimental parameters, start the experiment, and start the acoustic emission acquisition program. Module M2: The acquired raw acoustic emission signal is segmented and stored, and processed in real time to calculate the root mean square value and amplitude spectrum; Module M3: Observes the friction and wear state of the material based on the root mean square signal and amplitude spectrum displayed on the acquisition interface; Module M4: Plots root mean square curves to compare and obtain the material friction and wear under different working conditions.

6. The method for characterizing friction and wear based on acoustic emission signals according to claim 5, characterized in that, The friction speed is adjusted by adjusting the distance between the contact surface and the center of the disk or the angular velocity of the disk rotation, and different experimental conditions, including load and disk rotation angular velocity, are set on the friction testing machine to simulate real working conditions. After the experiment begins, the acoustic emission signal acquisition program is started simultaneously. In the friction experiment, the acoustic emission sensor acquires the ultra-high frequency stress wave pulse signal generated by the change in stress distribution in the contact area when the two surfaces of the pin and the disc are in contact and move together. The signal acquired by the acoustic emission sensor is converted into an electrical signal by the signal amplifier and the acoustic emission signal acquisition board and displayed in real time on the acquisition interface.

7. The tribological wear characterization system based on acoustic emission signals according to claim 5, characterized in that, The module M2 includes: The acquired signals are segmented and stored as raw data. Specifically, a clock is set inside the program to store a data file at preset intervals. In real-time data processing, a producer-consumer model is adopted to ensure the real-time performance of data processing. Data is collected at the producer level and analyzed and stored at the consumer level. Data processing includes the extraction of root mean square signal and amplitude spectrum.

8. The tribological wear characterization system based on acoustic emission signals according to claim 5, characterized in that, The module M3 includes: The amplitude spectrum of the original acoustic emission signal is extracted by windowing and performing short-time Fourier transform. This spectrum is used to observe the stability of the friction process in the friction and wear experiment. By observing the dominant frequency when the friction and wear experiment is stable, the friction and wear amount under different working conditions is evaluated. The acoustic emission signal has a sampling frequency of 1MHz, which is a high-frequency signal. A high-pass filter is designed to preprocess the signal. Calculate the root mean square (RMS) value, which represents the amount of friction and wear in this stage. The calculation formula is as follows: in, To calculate the root mean square value, the data length is 0.1s, which means 100,000 points are selected for calculation, i.e., n=100,000, 0≤i≤n; The processed root mean square (RMS) signal is displayed in real time on the acquisition interface, and the processed data is stored in the same table. After the experiment, the RMS change curve of the acoustic emission signal throughout the entire process is plotted using a plotting tool. The entire signal is observed, and the part with a larger RMS value amplitude is the stage where the friction and wear are more severe.

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