Friction wear acoustic emission detection method based on shear wave sensor

Abstract

The invention provides a frictional wear acoustic emission detection method based on a shear wave sensor, which comprises the following steps: determining the frequency response range of the shear wave sensor and designing the shear wave sensor according to the requirements of the material characteristics of a friction pair, different working condition scenes and monitoring precision; a designed shear wave sensor is installed on one side of a non-contact surface of a friction pair in a self-transmitting and self-receiving mode, and a frictional wear monitoring system is built by combining with the shear wave sensor; shear wave acoustic emission signals and mechanical signals collected in a frictional wear monitoring system are synchronously stored, collected data are analyzed by adopting a method of combining time domain analysis, frequency domain analysis and time-frequency analysis, a corresponding relation between signal characteristics and frictional wear states is established, and accurate identification of shear damage is realized. According to the invention, the in-situ, real-time and high-precision monitoring of the shear damage in the friction wear process is realized by optimizing the type of the sensor and building a friction wear monitoring system.

Description

Technical Field

[0001] This invention relates to the technical field of friction and wear monitoring, and in particular to a sensor-based method for detecting friction and wear acoustic emission. Background Technology

[0002] In modern industry, the efficient operation of machinery plays a decisive role in production efficiency and product quality. Friction and wear are unavoidable phenomena in the operation of machinery and are one of the main causes of mechanical system failure. Long-term friction and wear significantly reduce the performance and service life of machinery, causing huge economic losses in the industrial sector. Statistics show that friction consumes approximately one-third of the world's energy resources, and wear causes about 80% of mechanical parts to fail annually. Therefore, there is an urgent need for accurate and effective monitoring methods to achieve early identification and warning of friction and wear conditions.

[0003] The friction and wear process is essentially a shearing action and material removal process between contact surfaces, with energy release mainly in the form of shear waves. From a mechanical perspective, the core of friction and wear is the shear stress generated by the relative sliding between two contact surfaces. When the shear stress exceeds the shear strength of the material, it will trigger shear fracture and shedding of the surface material. The elastic waves released in this process are mainly in the form of shear waves.

[0004] Traditional methods for detecting friction and wear, such as vision- and optical inspection, weight measurement, and surface profile measurement, suffer from limitations such as strong hysteresis, reliance on indirect parameters, or offline measurement, failing to meet the demands of modern industry for high-precision, real-time measurement. Acoustic emission (AE) technology, as a dynamic non-destructive testing method, can achieve real-time monitoring and assessment of friction and wear conditions by capturing transient elastic stress waves released during deformation and fracture within or on the surface of materials during friction and wear. However, most existing AE sensors are resonant or broadband sensors based on the piezoelectric effect, and their sensitivity direction is typically longitudinal waves perpendicular to the sensor mounting surface. Since the particle vibration direction of longitudinal waves is consistent with the wave propagation direction, they are sensitive to large-area uniform wear parallel to the wave propagation direction, but lack effective monitoring capabilities for shear damage commonly present during friction and wear processes, such as surface scratches, localized stick-slip, and shear cracks, as well as the shear wave signals released by such damage.

[0005] Shear waves propagate in solids and are more sensitive to shear-related defects. Compared to longitudinal waves, the particle vibration direction of shear waves is perpendicular to the wave propagation direction, giving them a significant advantage in detecting shear damage perpendicular to the propagation direction. When shear waves encounter shear damage such as surface scratches or localized stick-slip, the physical properties of the material in the damaged area, such as shear modulus and density, change significantly. This leads to marked changes in the propagation speed, direction, reflection, and transmission characteristics of the shear waves, forming distinctive acoustic emission signals that can accurately reflect the location, type, and severity of the damage. However, currently, there is no solution for applying shear wave sensors to triboelectric acoustic emission monitoring. There is a lack of technical means to analyze the acoustic emission signals of shear waves generated during triboelectric processes, making it difficult to fully utilize the advantages of shear waves in wear monitoring and failing to meet the actual needs of high-precision wear monitoring in industrial equipment. Summary of the Invention

[0006] To address the technical problems of existing technologies being insensitive to shear damage and having low monitoring accuracy during friction and wear processes, this invention proposes a friction and wear acoustic emission detection method based on a shear wave sensor. By optimizing the sensor type and building a friction and wear monitoring system, in-situ, real-time, and high-precision monitoring of shear damage during friction and wear processes can be achieved.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows: a method for detecting triboelectric acoustic emission based on a shear wave sensor, comprising the following steps:

[0008] S1. Based on the material properties of the friction pair, different working conditions, and the requirements for monitoring accuracy, determine the frequency response range of the shear wave sensor and design the shear wave sensor.

[0009] S2. Install the designed shear wave sensor on the non-contact side of the friction pair in a self-generating and self-receiving mode, and build a friction and wear monitoring system in conjunction with the force sensor.

[0010] S3. The shear wave acoustic emission signal and mechanical signal collected by the friction and wear monitoring system are saved synchronously. The collected data are analyzed by combining time domain, frequency domain and time-frequency analysis methods to establish the correspondence between signal characteristics and friction and wear state, so as to achieve accurate identification of shear damage.

[0011] Preferably, the method for determining the frequency response range of the shear wave sensor is as follows: a friction pair-sensor coupled simulation model is established using finite element simulation software, and key parameters such as the elastic modulus, Poisson's ratio, and density of the friction pair material are input. The propagation attenuation characteristics of shear waves and longitudinal waves within the friction pair at the same frequency and their response sensitivity to shear damage are simulated. The results show that the response effect of shear waves to shear damage is significantly better than that of longitudinal waves.

[0012] By adjusting the frequency of the point excitation source in the friction pair-sensor coupling simulation model and comparing the simulation results of shear waves at different frequencies, the differences in response to shear damage at different frequencies are clarified. By comparing the amplitude intensity, time-domain response characteristics and peak arrival time of the shear wave signal at different frequencies, the differences in response sensitivity of shear waves at different frequencies to shear damage are quantified, and the optimal frequency response range of the shear wave sensor is finally determined.

[0013] Preferably, the optimal frequency response range is approximately 0-5MHz;

[0014] Aluminum-tungsten steel was selected as the friction pair, aluminum plate was selected as the wear test piece, and custom tungsten steel needles were used as the mating friction parts. The point contact friction in mechanical parts was simulated by the reciprocating friction between the tungsten steel needles and the aluminum plate.

[0015] Based on the selected friction pair parameters, a simulation model of shear wave acoustic emission was established using finite element simulation software: a rectangular model was established, a point excitation source was set on one side of the aluminum plate to excite pulse waves in the shear direction, and a long receiving line segment was set at the center of the other side to arrange boundary probes to simulate shear wave sensors and collect the propagating shear wave response and the corresponding longitudinal wave response.

[0016] The shear wave sensor is fabricated using an adhesive bonding process. The shear wave piezoelectric ceramic sheet is oriented and bonded to the non-contact side of the friction pair using epoxy adhesive or ion-based thinning adhesive. Before bonding, the contact surface is treated with an organic cleaning solution. The lead wires of the shear wave sensor are shielded coaxial cables. One end of the coaxial cable is positively soldered to the piezoelectric ceramic sheet electrode, and the negative end is bonded to an aluminum plate with conductive epoxy adhesive. Alternatively, the positive and negative ends can be soldered to one side of the shear wave sensor using a flanged electrode type piezoelectric ceramic sheet. The other end of the coaxial cable is connected to the signal acquisition device.

[0017] Preferably, when the frequency is below 500kHz, the attenuation of the shear wave is minimal when it propagates inside the aluminum plate-friction pair, the signal amplitude is stable and the peak value is clear, and the pulse width is moderate; when the frequency is above 500kHz, although the peak response of the shear wave is prominently instantaneous, the propagation attenuation is significant, and the installation process requires high precision in terms of the flatness of the shear sensor and the accuracy of the contact surface treatment.

[0018] Preferably, the friction and wear monitoring system includes a sensor module, a testing device module, and an acoustic emission signal acquisition module. The acoustic emission signal acquisition module includes a digital oscilloscope and a data acquisition card, with the digital oscilloscope and data acquisition card connected to a computer's data acquisition system. The sensor module includes a shear wave sensor and a force sensor, wherein the shear wave sensor is arranged in a self-emitting and self-receiving mode, and the output terminal of the shear wave sensor is connected to the signal input terminal of the digital oscilloscope. The force sensor is installed on the fixed end of the friction pair and is connected to the input terminal of the data acquisition card through a voltage transmitter. The testing device module includes a friction and wear testing machine, on which the friction pair is placed.

[0019] The force sensor is a piezoelectric force sensor; the friction pair is fixed to the robotic arm of the friction and wear testing machine via a connector.

[0020] Preferably, the piezoelectric ceramic sheet of the shear wave sensor is attached to the center of the non-friction surface of the aluminum plate, and the output end of the shear wave sensor is connected to a digital oscilloscope via a coaxial cable to acquire the shear wave acoustic emission signal in real time; the force sensor is installed on the fixed end of the friction and wear testing machine, the axis of the force sensor is perpendicular to the friction surface, and the output end of the force sensor is connected to a data acquisition card via a voltage transmitter to acquire the normal pressure signal in real time.

[0021] The tungsten steel needle is fixed to the loading arm of the testing machine via a connector, and the aluminum plate is fixed to the worktable. The contact pressure between the tip of the tungsten steel needle and the aluminum plate is adjusted, and the parameters of the initial load and sliding stroke are set. The sampling rate of the digital oscilloscope and the data acquisition card are set to be consistent.

[0022] Preferably, the method for analyzing the collected data includes: preprocessing the collected shear wave acoustic emission signal by filtering and denoising using a high-pass filter, extracting the time-domain features of peak value, root mean square value, and pulse width, and preliminarily evaluating the signal reception effect by comparing the differences in time-domain parameters between the background noise and the collected shear wave acoustic emission signal.

[0023] The preprocessed shear wave acoustic emission signal is converted into a frequency domain spectrum by Fourier transform. The peak distribution and energy ratio of the shear wave emission signal in the characteristic frequency band are analyzed to identify the main frequency characteristics of the signal. Time-frequency decomposition is performed to generate a time-frequency two-dimensional spectrum to observe the spatiotemporal distribution characteristics of the energy concentration area and locate the key frequencies and time nodes of signal attenuation or loss.

[0024] The normal pressure signal is filtered using the same filtering strategy as the shear wave acoustic emission signal to remove noise interference and extract key features such as average pressure, fluctuation amplitude, and pressure change rate. The normal pressure signal and the shear wave acoustic emission signal are precisely synchronized by time axis alignment, and the correlation response law between the two is established.

[0025] Preferably, through multi-condition friction and wear experiments, shear wave acoustic emission signals and normal pressure signals under different wear conditions are collected simultaneously. After filtering, the features of the two types of signals are extracted. Combined with the observation of the surface morphology of the friction pair, the feature thresholds and feature combination rules corresponding to different wear conditions are clarified through correlation analysis, and a one-to-one correspondence between signal features and friction and wear conditions is established.

[0026] Preferably, in actual testing, shear wave sensors are arranged in the non-contact area of ​​the friction pair in a self-generating and self-receiving manner to simultaneously collect shear wave acoustic emission signals and normal pressure signals. After the same filtering and feature extraction, the real-time feature values ​​are matched with the stored established correspondence. Combining the feature change trend and the correlation response law, the current friction and wear state is determined in real time. When the feature value exceeds the damage threshold and typical shear damage characteristics appear, shear damage such as stick-slip slip, micro-protrusion shear fracture, and subsurface shear crack initiation is identified, and the degree of damage and development trend are judged.

[0027] Preferably, the different wear states include light wear, moderate wear, heavy wear, and wear involving adhesion / abrasive particles / fretting;

[0028] The aforementioned characteristic thresholds and characteristic combination rules include: mild wear corresponds to low amplitude, low fluctuation acoustic emission characteristics and stable pressure characteristics; severe adhesive wear corresponds to a sharp increase in acoustic emission peak value, increased pulse width and a dramatic increase in pressure fluctuation amplitude.

[0029] Compared with existing technologies, the beneficial effects of this invention are as follows: By analyzing the nature of the friction and wear process and the propagation characteristics of shear waves, this invention selects shear wave sensors for in-situ detection of friction and wear acoustic emission. By constructing a friction and wear monitoring system including a sensor module, a test device module, and a signal acquisition module, it achieves synchronous acquisition of shear wave acoustic emission signals and mechanical signals during the friction and wear process. By optimizing the selection and arrangement of sensors, constructing a friction and wear monitoring system, and establishing the correspondence between shear wave signal characteristics and friction and wear states, this invention fills the application gap of shear wave sensors in the field of friction and wear acoustic emission monitoring. It fully leverages the high sensitivity of shear waves to shear-type damage, achieving in-situ, real-time, and high-precision monitoring during the friction and wear process. This provides reliable technical support for predictive maintenance of industrial equipment, reduces equipment failure losses caused by friction and wear, and promotes the development of friction and wear monitoring technology towards precision and intelligence, resulting in significant economic and social benefits. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of the shear wave acoustic emission simulation model in an embodiment of the present invention.

[0032] Figure 2 The following are acceleration response and comparison diagrams at low frequency in embodiments of the present invention; wherein, a is the acceleration response diagram in the X direction, b is the acceleration response diagram in the Y direction, and c is a comparison diagram of acceleration response in the X and Y directions.

[0033] Figure 3 The following are acceleration response and comparison diagrams at medium frequency in embodiments of the present invention; wherein, a is the acceleration response diagram in the X direction, b is the acceleration response diagram in the Y direction, and c is a comparison diagram of acceleration response in the X and Y directions.

[0034] Figure 4 The figures shown are high-frequency acceleration response and comparison diagrams in the embodiments of the present invention; wherein, a is the acceleration response diagram in the X direction, b is the acceleration response diagram in the Y direction, and c is a comparison diagram of the acceleration responses in the X and Y directions.

[0035] Figure 5 This is a schematic diagram of the overall connection of the friction and wear monitoring system in an embodiment of the present invention.

[0036] Figure 6 This is a schematic diagram of the shear wave sensor installation structure in an embodiment of the present invention.

[0037] Figure 7 This is a schematic diagram of the friction pair installation in an embodiment of the present invention.

[0038] Figure 8 The diagram shows the background noise signal and the filtering result in an embodiment of the present invention. In the diagram, a is the background signal spectrum at 0-400kHz, b is the spectrum at 0-10kHz, c is the spectrum at 0-1kHz, and d is the time-domain signal and spectrum obtained after filtering.

[0039] Figure 9 This is a diagram showing the signal processing results when the program multiplier is 30% in an embodiment of the present invention.

[0040] Figure 10 This is a diagram showing the signal processing results when the program multiplier is 60% in an embodiment of the present invention.

[0041] Figure 11This is a diagram showing the signal processing results when the program multiplier is 90% in an embodiment of the present invention. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] like Figure 1 As shown, a friction and wear acoustic emission detection method based on a shear wave sensor is proposed. First, based on the material characteristics of the friction pair and the operating conditions, the optimal frequency response range of the shear wave sensor is determined through finite element simulation. The shear wave sensor is then fabricated and installed. The sensor is placed on the non-contact side of the friction pair. A friction and wear monitoring system, including a sensor module, an experimental device module, and an acoustic emission signal acquisition module, is built in conjunction with a force sensor to conduct friction and wear experiments. The acquired shear wave acoustic emission signals and mechanical signals are simultaneously saved. Through a multi-dimensional analytical method combining time-domain, frequency-domain, and time-frequency analysis, the correspondence between signal characteristics and friction and wear states is established, enabling accurate identification of shear-type damage. This invention fully leverages the high sensitivity of shear waves to shear-type damage such as friction and wear, achieving in-situ, real-time, and high-precision monitoring. This provides reliable support for predictive maintenance of industrial equipment and promotes the development of friction and wear monitoring technology towards precision and intelligence.

[0044] S1. Based on the material properties of the friction pair, different working conditions, and the requirements for monitoring accuracy, determine the frequency response range of the shear wave sensor and design the shear wave sensor.

[0045] A coupled simulation model of the friction pair and sensor was established using finite element method (FEM) simulation software. Key parameters such as the elastic modulus, Poisson's ratio, and density of the friction pair material (e.g., steel, aluminum alloy) were input. The propagation attenuation characteristics of shear waves and longitudinal waves at different frequencies within the friction pair and their response sensitivity to shear damage were simulated. The results showed that shear waves significantly outperformed longitudinal waves in responding to shear damage, making shear waves more suitable for friction and wear detection. Shear waves were observed through acceleration in the X-direction in the finite element simulation, while longitudinal waves were observed through acceleration in the Y-direction. Different friction pair materials exhibited different frequency responses. By adjusting the frequency of the point excitation source in the simulation model and comparing simulations of shear waves at different frequencies, the differences in response to shear damage at different frequencies were clarified. X-direction acceleration (corresponding to the shear wave response) and Y-direction acceleration (corresponding to the longitudinal wave response) were collected. By comparing the amplitude intensity, time-domain response characteristics, and peak arrival time of the two types of signals, the difference in response sensitivity between longitudinal waves and shear waves to shear damage was quantified. Based on the simulation results, the optimal frequency response range of the shear wave sensor was finally determined, specifically approximately 0-5 MHz.

[0046] In this embodiment, aluminum-tungsten carbide was used as the friction pair for the experiment. The specific specifications are as follows: A commonly used industrial 6061 aluminum alloy plate (aluminum plate) was selected as the wear test piece, with dimensions of 70mm × 40mm × 10mm. Its elastic modulus is 69 GPa, Poisson's ratio is 0.33, density is 2700 kg / m³, and hardness is 100 HB. The mating friction component is a custom-made tungsten carbide needle with a tip curvature radius of 5mm. Its elastic modulus is 530 GPa, Poisson's ratio is 0.22, density is 14.8 g / cm³, and hardness is 550 HB. The experiment simulates typical point contact friction in mechanical parts through the reciprocating friction between the tungsten carbide needle and the aluminum plate.

[0047] Based on the friction pair parameters selected in the experiment, a simulation model of shear wave acoustic emission was established using finite element simulation software, such as... Figure 1 As shown, a rectangular model with dimensions of 20 mm × 12 mm was established. A point excitation source was set on one side of the aluminum plate to generate a shear-direction pulse wave. A 12 mm long receiving line segment was set at the center of the other side to arrange a boundary probe to simulate a shear wave sensor, collecting the X-direction acceleration (corresponding to the shear wave response) and Y-direction acceleration (corresponding to the longitudinal wave response) propagating to this region. By comparing the amplitude intensity, time-domain response characteristics, and peak arrival time of the two types of signals, the difference in the response sensitivity of longitudinal waves and shear waves to shear-type damage was quantified. Figure 1 The rectangles on both sides are the perfect matching layers, which reduce the interference of boundary reflections on signal feature extraction.

[0048] The simulation experiment simulated the acceleration response in the X and Y directions at three different frequencies (low, medium, and high) within the 0-10MHz range. The simulation results are as follows: Figure 2, 3 As shown in Figure 4, where Figure 2 -a is the X-direction acceleration response at low frequencies. Figure 2 -b represents the acceleration response in the Y direction at low frequencies. Figure 2 -c is a comparison of the acceleration response in the X and Y directions at low frequencies; Figure 3 -a is the X-direction acceleration response at mid-frequency. Figure 3 -b is the Y-direction acceleration response plot at mid-frequency. Figure 3 -c is a comparison of the acceleration response in the X and Y directions at mid-frequency. Figure 4 -a is the X-direction acceleration response diagram at high frequencies. Figure 4 -b represents the acceleration response in the Y direction at high frequencies. Figure 4 -c is a comparison of the acceleration response in the X and Y directions at high frequencies.

[0049] Simulation results show that the amplitudes of the lateral acceleration components at the three different frequencies are all much higher than those of the longitudinal components, with the lateral acceleration amplitudes reaching 1 to 2 orders of magnitude higher than those of the longitudinal components. This further demonstrates that the sensitivity of the shear wave response to shear-type damage is much higher than that of the longitudinal wave response, and this difference in sensitivity remains stable over a wide frequency range, providing a basis for experiments using shear wave sensors to detect friction and wear.

[0050] Further analysis of the propagation characteristics and response features of shear waves at different frequencies leads to the conclusion that: at low frequencies (below 5MHz), the shear wave exhibits minimal attenuation when propagating within the aluminum alloy plate, i.e., the aluminum plate friction pair. The signal amplitude is stable, the peak value is clear, and the pulse width is moderate, facilitating subsequent extraction of time-domain features such as peak value and kurtosis. At medium and high frequencies (above 5MHz), although the peak response of the shear wave is highly instantaneous, the propagation attenuation is significant. Furthermore, it places extremely high demands on the installation process, such as the flatness of the sensor bonding and the precision of the contact surface treatment. In actual working conditions, it is difficult to ensure the consistency of signal transmission, and signal distortion is prone to occur.

[0051] The shear wave sensor is fabricated using an adhesive bonding process. Specifically, the shear wave piezoelectric ceramic sheet is oriented and bonded to the non-contact side of the friction pair using epoxy adhesive or ion-based thinning adhesive. Before bonding, the contact surface is treated with an organic cleaning solution to ensure it is free of impurities, preventing any interference with the sensor's normal operation. The shear wave piezoelectric ceramic sheet receives shear-like elastic wave signals generated during friction and wear, converting them into electrical signals. The shear wave sensor's lead wires use shielded coaxial cables. One end is positively soldered to the piezoelectric ceramic sheet electrode, and the negative end is bonded to an aluminum plate using conductive epoxy adhesive. Alternatively, a flanged electrode type piezoelectric ceramic sheet can be used, with both positive and negative terminals soldered to one side of the shear wave sensor. The positions of the positive and negative terminals differ between the two methods. The other end of the coaxial cable connects to the signal acquisition equipment to achieve stable transmission of the shear wave signal. Shear wave piezoelectric ceramic sheets are available in different frequency models; the appropriate frequency model should be selected based on the required frequency (low, medium, or high frequency).

[0052] S2. Install the shear wave sensor designed in step S1 on the non-contact side of the friction pair in a self-generating and self-receiving mode, and build a friction and wear monitoring system in conjunction with the force sensor.

[0053] like Figure 5 As shown, the friction and wear monitoring system includes a sensor module, a test device module, and an acoustic emission signal acquisition module. The specific configurations of each module are as follows:

[0054] The sensor module includes a shear wave sensor and a force sensor. The shear wave sensor is arranged in a self-emitting and self-receiving mode, attached to the non-contact side of the friction pair with epoxy resin. The output of the shear wave sensor is connected to the signal input of a digital oscilloscope. This self-emitting and self-receiving arrangement, where the sensor is attached to the non-contact area of ​​the friction pair (opposite to the rubbed area), facilitates better reception of the acoustic emission signals generated by friction and wear. The force sensor is a piezoelectric force sensor, installed at the fixed end of the friction pair, and connected to the input of a data acquisition card via a voltage transmitter to collect the normal pressure during the friction process in real time.

[0055] The testing device module includes a friction and wear testing machine, equipped with a speed loading unit, a stroke adjustment unit, etc., to simulate the friction and wear process under different working conditions. The friction pair needs to be placed on the friction and wear testing machine for testing. The friction and wear testing machine is the driving device, driving the movement of the friction pair. The friction pair is the executing component of the experiment, and the experiment is mainly conducted on the friction pair. The speed and stroke can be adjusted by regulating the parameters on the friction and wear testing machine. The robotic arm is a key component of the friction and wear testing machine, and it is used in conjunction with the connecting parts to move the friction pair to conduct the friction and wear experiment. The connecting parts are used to fix the friction pair to the friction and wear testing machine.

[0056] The acoustic emission signal acquisition module is based on a digital oscilloscope and mainly acquires shear wave acoustic emission signals; the force signal is mainly acquired by connecting a voltage transmitter to a data acquisition card, and its sampling rate is consistent with that of the digital oscilloscope.

[0057] Based on the simulation results, a low-frequency shear wave sensor was selected for the friction and wear experiment, and a friction and wear monitoring system was built, such as... Figure 5 As shown, the connections and parameter settings for each module are as follows: Attach the piezoelectric ceramic sheet of the shear wave sensor to the center of the non-friction surface of the aluminum plate, as shown. Figure 6 As shown; its output end is connected to a digital oscilloscope via a coaxial cable to acquire shear wave signals in real time; the force sensor is installed on the fixed end of the friction and wear testing machine, with its axis perpendicular to the friction surface, and its output end is connected to a data acquisition card via a voltage transmitter to acquire normal pressure signals in real time.

[0058] The tungsten carbide needle is fixed to the loading arm of the testing machine via a connector, and the aluminum alloy plate is fixed to the worktable. Figure 7 As shown, the contact pressure between the tungsten carbide needle tip and the aluminum plate is adjusted by turning the screw, and parameters such as the initial load and sliding stroke are set to ensure stable contact during the friction process. The sampling rates of the digital oscilloscope and the data acquisition card are set to be consistent to ensure time synchronization. The digital oscilloscope and the data acquisition card are connected to the computer's data acquisition system to acquire the shear wave acoustic emission signal and normal mechanical signal during the experiment in real time.

[0059] S3. The shear wave acoustic emission signal and mechanical signal collected by the friction and wear monitoring system are saved synchronously. The collected data are analyzed by combining time domain, frequency domain and time-frequency analysis methods to establish the correspondence between signal characteristics and friction and wear state, so as to achieve accurate identification of shear damage.

[0060] Signal analysis methods should proceed sequentially from three levels: time domain, frequency domain, and time-frequency analysis. First, the acquired raw shear wave acoustic emission signal undergoes filtering and noise reduction preprocessing. A high-pass filter is used to remove background noise, extracting time-domain features such as peak value, root mean square value, and pulse width. By comparing the differences in time-domain parameters between the background noise and the shear wave acoustic emission signal acquired in the experiment, the signal reception effect is preliminarily evaluated. This helps distinguish friction and wear signals from background noise signals, improving signal discernibility. Next, Fourier transform is used to convert the preprocessed time-domain signal into a frequency-domain spectrum. The peak distribution and energy proportion of the shear wave emission signal in characteristic frequency bands are analyzed to identify the main frequency characteristics of the signal. Finally, time-frequency decomposition is performed to generate a two-dimensional time-frequency spectrum. By observing the spatiotemporal distribution characteristics of energy concentration areas, key frequencies and time points of signal attenuation or loss are located, providing data support for subsequent analysis of the causes of signal reception differences.

[0061] Simultaneously, synchronization and collaborative verification are performed using the acquired force sensor signals: The normal pressure signal is filtered using the same filtering strategy as the shear wave acoustic emission signal to remove noise interference, extracting key features such as average pressure, fluctuation amplitude, and pressure change rate; precise synchronization of the pressure signal and shear wave signal is achieved through time axis alignment, establishing their correlation response law. Consistent fluctuations are observed; for example, when pressure fluctuations are small, the AE (acoustic emission) signal should have a low peak value, regular pulse width, and low frequency of occurrence, corresponding to a stable wear stage; when the pressure change rate suddenly increases or the fluctuation amplitude increases instantaneously, the corresponding AE signal will show a large sudden peak value and a significant increase in pulse width.

[0062] Before the experiment, background noise signals were collected to eliminate environmental interference. Under a frictionless, stationary state, with the sensor installation position and signal acquisition equipment parameters consistent with subsequent experiments, three sets of background noise signals were continuously collected, each set for 30 seconds. The collected signals were then subjected to FFT transformation and spectral analysis. The spectral analysis results are as follows: Figure 8 As shown, the analysis is performed using a method of gradually narrowing down the frequency band: where Figure 8 -a is the background signal spectrum from 0 to 400 kHz. The background signal has multiple sharp spikes, but the amplitudes are all less than 10, which should be environmental noise. There is a DC component noise with an amplitude greater than 10 near 0. Figure 8 -b is the spectrum diagram at 0-10kHz, which shows that there is a DC component noise with an amplitude of about 60 in the 0-1kHz frequency band; Figure 8 -c represents the spectrum from 0 to 1 kHz. It can be seen that the noise amplitude is relatively large in the 0-0.4 kHz frequency band. After filtering, with a cutoff frequency set to 0.4 kHz, the resulting time-domain signal and spectrum are shown below. Figure 8 As shown in -d, it can be seen that the amplitude of the background time-domain signal is significantly reduced after filtering, with the amplitude range decreasing from [-500, 500] to [-100, 100]. The spectrum is also reduced, with the amplitude range all below 15, making it distinguishable from the subsequent experimental signals. The background signal used for comparison is as follows. Figure 8 -d is shown.

[0063] The formal experiment employed a single-variable method, fixing other operating parameters and conducting comparative experiments by varying the sliding speed. During the formal experiment, an aluminum plate was coated with grease, and a robotic arm drove a tungsten carbide needle to reciprocate and rub the aluminum plate. The speed was controlled by adjusting parameters on the friction and wear testing machine (sliding speed 0.5 m / s, with the actual operating conditions controlled at 30%, 60%, and 90%). For each sliding speed condition, shear wave acoustic emission signals and normal pressure signals from the force sensor were simultaneously acquired. Each set of conditions was run for 100 cycles before stopping, and this process was repeated three times consecutively. After each run, the system was allowed to stand for 10 minutes before starting the next set of conditions to avoid the accumulation of frictional heat affecting signal accuracy. All acquired signals were structured and stored according to the naming convention of "sliding speed - number of experiments," with raw signals and background noise signals categorized and archived to provide a standardized data foundation for subsequent signal analysis.

[0064] After filtering the acquired time-domain signal, an FFT transform is performed, and the result is as follows: Figure 9 , Figure 10 , Figure 11 As shown, where Figure 9 This is the signal when the program's multiplier is controlled at 30%. Figure 10 This is the signal when the program's multiplier is controlled at 60%. Figure 11 It is a signal that the program's multiplier is controlled at 90%.

[0065] Experimental results show that as the slip velocity increases, although the overall acoustic emission (AE) activity (possibly in amplitude or energy) may increase or remain the same, the main peak of the spectrum shifts to lower frequencies. This may indicate that the adhesive release time in the slip-release phase becomes longer, providing preliminary evidence for the stick-slip mechanism. It also confirms the feasibility of using shear wave sensors for tribological wear detection, providing a basis for subsequent experiments.

[0066] Through multi-condition friction and wear experiments, shear wave acoustic emission signals and normal pressure signals under different wear states (light / moderate / heavy wear, adhesive / abrasive / fretting wear, etc.) were collected simultaneously. After filtering, the characteristics of the two types of signals (such as peak value, energy, center frequency, and pulse width of the AE signal, and average pressure, fluctuation amplitude, and rate of change of the pressure signal) were extracted. Combined with the observation of the surface morphology of the friction pair, the characteristic thresholds and characteristic combination rules corresponding to different wear states were clarified through correlation analysis (such as light wear corresponding to low amplitude and low fluctuation AE characteristics + stable pressure characteristics, and heavy adhesive wear corresponding to a sudden increase in AE peak value, increased pulse width + dramatic increase in pressure fluctuation amplitude), and a one-to-one correspondence between signal characteristics and friction and wear states was established.

[0067] In subsequent actual testing, shear wave sensors are arranged in the non-contact area of ​​the friction pair in a self-generating and self-receiving manner to simultaneously collect shear wave AE signals and pressure signals. After filtering and feature extraction using the same process, the real-time feature values ​​are matched with the established corresponding relationship library. Combining the feature change trend and correlation response law, the current friction and wear state is determined in real time. When the feature value exceeds the damage threshold and typical characteristics of shear damage appear (such as sudden high-amplitude pulses of AE signal, pressure change rate rising in step with AE pulse), shear damage such as stick-slip slip, micro-protrusion shear fracture, and subsurface shear crack initiation can be accurately identified, and the degree and development trend of damage can be judged.

[0068] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for detecting triboelectric acoustic emission based on a shear wave sensor, characterized in that, The steps are as follows: S1. Based on the material properties of the friction pair, different working conditions, and the requirements for monitoring accuracy, determine the frequency response range of the shear wave sensor and design the shear wave sensor. S2. Install the designed shear wave sensor on the non-contact side of the friction pair in a self-generating and self-receiving mode, and build a friction and wear monitoring system in conjunction with the force sensor. S3. The shear wave acoustic emission signal and mechanical signal collected by the friction and wear monitoring system are saved synchronously. The collected data are analyzed by combining time domain, frequency domain and time-frequency analysis methods to establish the correspondence between signal characteristics and friction and wear state, so as to achieve accurate identification of shear damage.

2. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 1, characterized in that, The method for determining the frequency response range of the shear wave sensor is as follows: a friction pair-sensor coupled simulation model is established using finite element simulation software. Key parameters such as the elastic modulus, Poisson's ratio, and density of the friction pair material are input. The propagation attenuation characteristics of shear waves and longitudinal waves within the friction pair at the same frequency and their response sensitivity to shear damage are simulated. The results show that the response effect of shear waves to shear damage is significantly better than that of longitudinal waves. By adjusting the frequency of the point excitation source in the friction pair-sensor coupling simulation model and comparing the simulation results of shear waves at different frequencies, the differences in response to shear damage at different frequencies are clarified. By comparing the amplitude intensity, time-domain response characteristics and peak arrival time of the shear wave signal at different frequencies, the differences in response sensitivity of shear waves at different frequencies to shear damage are quantified, and the optimal frequency response range of the shear wave sensor is finally determined.

3. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 2, characterized in that, The optimal frequency response range is approximately 0-5MHz; Aluminum-tungsten steel was selected as the friction pair, aluminum plate was selected as the wear test piece, and custom tungsten steel needles were used as the mating friction parts. The point contact friction in mechanical parts was simulated by the reciprocating friction between the tungsten steel needles and the aluminum plate. Based on the selected friction pair parameters, a simulation model of shear wave acoustic emission was established using finite element simulation software: a rectangular model was established, a point excitation source was set on one side of the aluminum plate to excite pulse waves in the shear direction, and a long receiving line segment was set at the center of the other side to arrange boundary probes to simulate shear wave sensors and collect the propagating shear wave response and the corresponding longitudinal wave response. The shear wave sensor is fabricated using an adhesive bonding process. The shear wave piezoelectric ceramic sheet is oriented and bonded to the non-contact side of the friction pair using epoxy adhesive or ion-based thinning adhesive. Before bonding, the contact surface is treated with an organic cleaning solution. The lead wires of the shear wave sensor are shielded coaxial cables. One end of the coaxial cable is positively soldered to the piezoelectric ceramic sheet electrode, and the negative end is bonded to an aluminum plate with conductive epoxy adhesive. Alternatively, the positive and negative ends can be soldered to one side of the shear wave sensor using a flanged electrode type piezoelectric ceramic sheet. The other end of the coaxial cable is connected to the signal acquisition device.

4. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 3, characterized in that, At frequencies below 500kHz, the attenuation of the shear wave is minimal when propagating inside the aluminum plate-friction pair, the signal amplitude is stable and the peak value is clear, and the pulse width is moderate. At frequencies above 500kHz, although the peak response of the shear wave is transient, the propagation attenuation is significant, and the installation process requires high precision in terms of the flatness of the shear sensor and the accuracy of the contact surface treatment.

5. The triboelectric acoustic emission detection method based on a shear wave sensor according to any one of claims 1-4, characterized in that, The friction and wear monitoring system includes a sensor module, a testing device module, and an acoustic emission signal acquisition module. The acoustic emission signal acquisition module includes a digital oscilloscope and a data acquisition card, with the digital oscilloscope and data acquisition card connected to a computer's data acquisition system. The sensor module includes a shear wave sensor and a force sensor. The shear wave sensor is arranged in a self-emitting and self-receiving mode, and its output is connected to the signal input of the digital oscilloscope. The force sensor is mounted on the fixed end of the friction pair and is connected to the input of the data acquisition card via a voltage transmitter. The testing device module includes a friction and wear testing machine, on which the friction pair is placed. The force sensor is a piezoelectric force sensor; the friction pair is fixed to the robotic arm of the friction and wear testing machine via a connector.

6. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 5, characterized in that, The piezoelectric ceramic sheet of the shear wave sensor is attached to the center of the non-friction surface of the aluminum plate. The output end of the shear wave sensor is connected to a digital oscilloscope via a coaxial cable to acquire the shear wave acoustic emission signal in real time. The force sensor is installed on the fixed end of the friction and wear testing machine. The axis of the force sensor is perpendicular to the friction surface. The output end of the force sensor is connected to a data acquisition card via a voltage transmitter to acquire the normal pressure signal in real time. The tungsten steel needle is fixed to the loading arm of the testing machine via a connector, and the aluminum plate is fixed to the worktable. The contact pressure between the tip of the tungsten steel needle and the aluminum plate is adjusted, and the parameters of the initial load and sliding stroke are set. The sampling rate of the digital oscilloscope and the data acquisition card are set to be consistent.

7. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 6, characterized in that, The method for analyzing the collected data includes: preprocessing the collected shear wave acoustic emission signal by filtering and denoising using a high-pass filter, extracting the time-domain features of peak value, root mean square value, and pulse width, and preliminarily evaluating the signal reception effect by comparing the differences in time-domain parameters between the background noise and the collected shear wave acoustic emission signal. The preprocessed shear wave acoustic emission signal is converted into a frequency domain spectrum by Fourier transform. The peak distribution and energy ratio of the shear wave emission signal in the characteristic frequency band are analyzed to identify the main frequency characteristics of the signal. Time-frequency decomposition is performed to generate a time-frequency two-dimensional spectrum to observe the spatiotemporal distribution characteristics of the energy concentration area and locate the key frequencies and time nodes of signal attenuation or loss. The normal pressure signal is filtered using the same filtering strategy as the shear wave acoustic emission signal to remove noise interference and extract key features such as average pressure, fluctuation amplitude, and pressure change rate. The normal pressure signal and the shear wave acoustic emission signal are precisely synchronized by time axis alignment, and the correlation response law between the two is established.

8. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 5 or 6, characterized in that, Through multi-condition friction and wear experiments, shear wave acoustic emission signals and normal pressure signals under different wear conditions were collected simultaneously. After filtering, the features of the two types of signals were extracted. Combined with the observation of the surface morphology of the friction pair, the feature thresholds and feature combination rules corresponding to different wear conditions were clarified through correlation analysis, and a one-to-one correspondence between signal features and friction and wear conditions was established.

9. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 8, characterized in that, In actual testing, shear wave sensors are arranged in the non-contact area of ​​the friction pair in a self-generating and self-receiving manner. Shear wave acoustic emission signals and normal pressure signals are collected simultaneously. After the same filtering and feature extraction, the real-time feature values ​​are matched with the stored established correspondence. Combining the feature change trend and the correlation response law, the current friction and wear state is determined in real time. When the feature value exceeds the damage threshold and typical shear damage characteristics appear, shear damage such as stick-slip slip, micro-protrusion shear fracture, and subsurface shear crack initiation is identified, and the degree of damage and development trend are judged.

10. The triboelectric acoustic emission detection method based on a shear wave sensor according to claim 9, characterized in that, The different wear states include light wear, moderate wear, heavy wear, and wear caused by adhesion / abrasive particles / fretting. The aforementioned characteristic thresholds and characteristic combination rules include: mild wear corresponds to low amplitude, low fluctuation acoustic emission characteristics and stable pressure characteristics; severe adhesive wear corresponds to a sharp increase in acoustic emission peak value, increased pulse width and a dramatic increase in pressure fluctuation amplitude.

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