Temperature self-adaptive train brake disc abrasion monitoring method based on ZGV guided wave and related device

Abstract

The invention discloses a ZGV guided wave-based temperature self-adaptive train brake disc abrasion monitoring method and a related device, and the method comprises the steps: exciting an excitation signal which meets a ZGV mode and a thickness resonance mode at the same time to a to-be-detected train brake disc, and collecting a resonance Lamb wave signal formed by the reflection of the excitation signal in the to-be-detected train brake disc; carrying out preprocessing and Fourier transform on the resonance Lamb wave signal in sequence to obtain frequency domain data of the resonance Lamb wave signal; respectively extracting the frequency of the S1-ZGV mode and the frequency of the S1 thickness resonance mode according to the frequency domain data of the resonance Lamb wave signal; and inputting the frequency of the S1-ZGV mode and the frequency of the S1 thickness resonance mode into a preset calibration model associated with the to-be-measured train brake disc, and calculating to obtain a working condition temperature value and a working condition thickness value of the to-be-measured train brake disc, so that high-precision monitoring can be performed on the abrasion state of the train brake disc in real time.

Description

Technical Field

[0001] This invention relates to the field of non-destructive testing technology for equipment, and in particular to a temperature-adaptive train brake disc wear monitoring method and related device based on ZGV guided waves. Background Technology

[0002] With the rapid development of modern rail transit technology, high-speed railway systems have placed more stringent demands on the safety, reliability, and intelligence of train operation. Currently, high-speed EMU train sets generally employ a combined braking strategy of electric and air braking, with the trailer section primarily using air braking, and the two braking methods working in tandem. In air braking systems, disc brakes are widely used due to their fast braking response, controllable braking force, and superior heat dissipation. During braking, the friction between the brake pads and the train's brake disc generates braking force, which is a crucial means of ensuring safe deceleration and stopping of the train in the event of electric brake failure. Therefore, the wear condition of the brake disc has a vital impact on train operation safety. Accurate monitoring of the service condition of the brake disc is an important prerequisite for implementing condition-based maintenance, predictive maintenance, and preventing structural failures.

[0003] Existing methods for monitoring the wear condition of train brake discs mainly include offline manual monitoring and online monitoring technology. Offline manual monitoring relies on manual operation, has low measurement efficiency, and is difficult to achieve real-time monitoring during operation. Online monitoring technology mainly infers the geometric parameters of the brake disc based on ultrasonic non-destructive testing methods. However, monitoring is usually based on a single temperature or ignores the temperature-thickness coupling effect. During the actual service of the brake disc, the material wave velocity changes with temperature, making it impossible for ultrasonic non-destructive testing methods to effectively eliminate the errors caused by temperature disturbances, thus affecting the monitoring accuracy of the wear condition of the train brake disc. Summary of the Invention

[0004] This invention provides a temperature-adaptive train brake disc wear monitoring method and related device based on ZGV guided waves, which solves the technical problem that existing train brake disc wear monitoring technologies ignore the influence of temperature and are difficult to monitor the wear status of train brake discs in real time with high precision.

[0005] This invention provides a temperature-adaptive train brake disc wear monitoring method based on ZGV guided waves, the method comprising:

[0006] An excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode is excited to the brake disc of the train under test, and the resonance Lamb wave signal formed by the reflection of the excitation signal in the brake disc of the train under test is collected.

[0007] The resonant Lamb wave signal is preprocessed and Fourier transformed sequentially to obtain the frequency domain data of the resonant Lamb wave signal;

[0008] Based on the frequency domain data of the resonant Lamb wave signal, the frequencies of the S1-ZGV mode and the S1 thickness resonant mode are extracted respectively.

[0009] The frequencies of the S1-ZGV mode and the S1 thickness resonance mode are input into a preset calibration model associated with the brake disc of the train under test, and the operating temperature and operating thickness values ​​of the brake disc of the train under test are calculated.

[0010] Optionally, the process of determining the excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode includes:

[0011] Obtain the material parameters of the brake disc of the train under test, and construct a standard train brake disc sample associated with the brake disc of the train under test based on the material parameters;

[0012] Based on the sample parameters of the standard train brake disc sample, a corresponding dispersion curve is established;

[0013] Determine the first frequency corresponding to the ZGV point with a slope of 0 from the dispersion curve, and determine the second frequency corresponding to the thickness resonance point with a wavenumber of 0.

[0014] The excitation signal of the brake disc of the train under test is determined by the first frequency and the second frequency.

[0015] Optionally, the process of establishing the preset calibration model includes:

[0016] The elastic modulus of the standard train brake disc sample at different temperatures was obtained, and the temperature-elastic modulus function was obtained by polynomial fitting.

[0017] Construct test train brake disc samples with different elastic moduli and thickness gradients corresponding to the test train brake disc;

[0018] Excitation signals that simultaneously satisfy the ZGV mode and the thickness resonance mode are excited to the measurement train brake disc samples under different elastic moduli and thickness gradients, and the sample resonance Lamb wave signal formed by the reflection of the excitation signal in the measurement train brake disc samples under different elastic moduli and thickness gradients is collected.

[0019] The sample resonance Lamb wave signal is preprocessed and Fourier transformed sequentially to obtain the sample frequency domain data of the sample resonance Lamb wave signal.

[0020] Based on the sample frequency domain data of the sample resonance Lamb wave signal, the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different elastic moduli and thickness gradients are extracted respectively.

[0021] Based on the temperature-elastic modulus function, the frequencies of the S1-ZGV modes and the S1 thickness resonance modes under different elastic moduli and thickness gradients are converted into the frequencies of the S1-ZGV modes and the S1 thickness resonance modes under different temperatures and thickness gradients.

[0022] Based on the frequencies of the S1-ZGV modes and the S1 thickness resonance modes under different temperatures and thickness gradients, a preset calibration model is generated.

[0023] Optionally, the process of establishing a preset calibration model by fitting the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different temperature and thickness gradients includes:

[0024] Based on the frequencies of the S1-ZGV modes under different temperature and thickness gradients, fitting curves of the frequency of the S1-ZGV modes with thickness under different temperature gradients and fitting curves of the frequency of the S1-ZGV modes with temperature under different thickness gradients were obtained.

[0025] Based on the frequencies of the S1 thickness resonance modes under different temperature and thickness gradients, fitting curves of the frequency of the S1 thickness resonance modes as a function of thickness under different temperature gradients and fitting curves of the frequency of the S1 thickness resonance modes as a function of temperature under different thickness gradients are obtained.

[0026] Based on the fitting curves of the frequency of the S1-ZGV mode with thickness under different temperature gradients and the fitting curves of the frequency of the S1-ZGV mode with temperature under different thickness gradients, a two-dimensional fitting surface of the S1-ZGV mode with thickness-temperature is obtained, thereby establishing the fitting equation of the two-dimensional fitting surface of the S1-ZGV mode with thickness-temperature.

[0027] Based on the fitting curves of the frequency of the S1 thickness resonance mode with thickness under different temperature gradients and the fitting curves of the frequency of the S1 thickness resonance mode with temperature under different thickness gradients, a two-dimensional fitting surface of the S1 thickness resonance mode with thickness-temperature is obtained, thereby establishing the fitting equation of the two-dimensional fitting surface of the S1 thickness resonance mode with thickness-temperature.

[0028] Based on the thickness-temperature S1-ZGV mode two-dimensional fitting surface fitting equation and the thickness-temperature S1 thickness resonance mode two-dimensional fitting surface fitting equation, a preset calibration model is obtained.

[0029] Optionally, the step of sequentially preprocessing and Fourier transforming the resonant Lamb wave signal to obtain the frequency domain data of the resonant Lamb wave signal includes:

[0030] The resonant signal portion of the resonant Lamb wave signal is truncated using a Hanning window and pre-processed with zero-padding to obtain a pre-processed signal.

[0031] The preprocessed signal is subjected to a fast Fourier transform to obtain the frequency domain data of the resonant Lamb wave signal.

[0032] The present invention also provides a temperature-adaptive train brake disc wear monitoring system based on ZGV guided waves, the system comprising:

[0033] The excitation unit is used to excite an excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode to the brake disc of the train under test, and to collect the resonance Lamb wave signal formed by the reflection of the excitation signal in the brake disc of the train under test.

[0034] The ZGV frequency domain data processing unit is used to preprocess and Fourier transform the resonant Lamb wave signal sequentially to obtain the frequency domain data of the resonant Lamb wave signal.

[0035] A multimodal frequency extraction unit is used to extract the frequencies of the S1-ZGV mode and the S1 thickness resonant mode based on the frequency domain data of the resonant Lamb wave signal.

[0036] The temperature and thickness calculation unit is used to input the frequency of the S1-ZGV mode and the frequency of the S1 thickness resonance mode into a preset calibration model associated with the brake disc of the train under test, and calculate the working temperature value and working thickness value of the brake disc of the train under test.

[0037] Optionally, the ZGV frequency domain data processing unit includes:

[0038] The preprocessing subunit is used to perform Hanning window truncation and zero-padding expansion preprocessing on the resonant signal portion of the resonant Lamb wave signal to obtain the preprocessed signal.

[0039] The Fourier transform subunit is used to perform a fast Fourier transform on the preprocessed signal to obtain the frequency domain data of the resonant Lamb wave signal.

[0040] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the temperature-adaptive train brake disc wear monitoring method as described above.

[0041] The present invention also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the temperature-adaptive train brake disc wear monitoring method as described above.

[0042] The present invention also provides a computer program product, including a computer program or instructions, which, when executed by a processor, implement the steps of the temperature-adaptive train brake disc wear monitoring method as described above.

[0043] As can be seen from the above technical solutions, the present invention has the following advantages:

[0044] This invention provides a temperature-adaptive train brake disc wear monitoring method and related device based on ZGV guided waves. The method includes: exciting an excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode to the brake disc of the train under test; acquiring the resonance Lamb wave signal formed by the reflection of the excitation signal in the brake disc of the train under test; performing preprocessing and Fourier transform on the resonance Lamb wave signal in sequence to obtain the frequency domain data of the resonance Lamb wave signal; extracting the frequencies of the S1-ZGV mode and the S1 thickness resonance mode from the frequency domain data of the resonance Lamb wave signal; inputting the frequencies of the S1-ZGV mode and the S1 thickness resonance mode into a preset calibration model associated with the brake disc of the train under test, and calculating the working temperature value and working thickness value of the brake disc of the train under test.

[0045] This invention leverages the high sensitivity of ZGV mode and thickness resonance mode to temperature and thickness. It acquires the frequencies of the S1-ZGV mode and S1 thickness resonance mode of the brake disc under test in real time. Based on the frequencies of the S1-ZGV mode and S1 thickness resonance mode, the operating temperature and thickness of the brake disc under test are jointly deduced. This effectively eliminates the error caused by temperature disturbance during the wear monitoring of train brake discs, improves the applicability and stability of the thickness measurement process under different temperature fields, and solves the technical problem that existing train brake disc wear monitoring technologies ignore the influence of temperature and are difficult to monitor the wear state of train brake discs in real time with high precision. Attached Figure Description

[0046] 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.

[0047] Figure 1 A flowchart illustrating the steps of a temperature-adaptive train brake disc wear monitoring method based on ZGV guided waves, provided in this embodiment of the invention.

[0048] Figure 2 This is a schematic diagram of the connection between the train brake disc and the electromagnetic ultrasonic transducer in an experimental simulation provided by an embodiment of the present invention;

[0049] Figure 3 This is a schematic diagram illustrating the mathematical relationship between the temperature and elastic modulus of a train brake disc, provided in an embodiment of the present invention.

[0050] Figure 4 Dispersion curve of a 30mm thick train brake disc provided for an embodiment of the present invention;

[0051] Figure 5 (a) is a time-domain schematic diagram of the excitation signal provided in an embodiment of the present invention; Figure 5 (b) is a frequency domain schematic diagram of the excitation signal provided in an embodiment of the present invention;

[0052] Figure 6 A schematic diagram of the structure of a two-dimensional finite element simulation model of a train brake disc with a thickness of 30mm provided in an embodiment of the present invention;

[0053] Figure 7 (a) is a time-domain diagram of the resonant Lamb wave signal at different temperatures with a thickness of 30 mm provided in an embodiment of the present invention; Figure 7 (b) is a time window of 500°C at different temperatures for a thickness of 30 mm provided in an embodiment of the present invention. -1000 The spectrum of the resonance signal;

[0054] Figure 8 (a) is a time-domain diagram of resonant Lamb wave signals of different thicknesses with an elastic modulus of 215 GPa provided in an embodiment of the present invention; Figure 8 (b) is a time window of 500 for different thicknesses with an elastic modulus of 215 GPa provided in the embodiment of the present invention. -1000 The spectrum of the resonance signal;

[0055] Figure 9 (a) is a schematic diagram of the fitting curve of the S1-ZGV frequency with temperature under different thicknesses provided in the embodiment of the present invention; Figure 9 (b) is a schematic diagram of the fitting curve of the S1 thickness resonance frequency with temperature under different thicknesses provided in the embodiment of the present invention;

[0056] Figure 10 (a) is a schematic diagram of the fitting curve of the S1-ZGV frequency versus thickness at different temperatures provided in an embodiment of the present invention; Figure 10 (b) is a schematic diagram of the fitting curve of the S1-ZGV frequency versus thickness at different temperatures provided in the embodiments of the present invention;

[0057] Figure 11 (a) is a schematic diagram of surface fitting of S1-ZGV frequency with temperature and thickness provided in an embodiment of the present invention; Figure 11(b) is a surface fitting diagram of the S1 thickness resonance frequency with temperature and thickness provided in the embodiment of the present invention;

[0058] Figure 12 (a) is a time-domain diagram of the resonant Lamb wave of a train brake disc with a thickness of 26.3 mm and a temperature of 250 °C provided in an embodiment of the present invention; Figure 12 (b) refers to the train brake disc with a thickness of 26.3 mm and a temperature of 250°C provided in the embodiment of the present invention, within a time window of 500... -1000 The spectrum of the resonance signal;

[0059] Figure 13 This is a schematic diagram of a temperature-adaptive train brake disc wear monitoring system based on ZGV guided waves provided in an embodiment of the present invention. Detailed Implementation

[0060] This invention provides a temperature-adaptive train brake disc wear monitoring method and related device based on ZGV guided waves, which solves the technical problem that existing train brake disc wear monitoring technologies ignore the influence of temperature and are difficult to monitor the wear status of train brake discs in real time with high precision.

[0061] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0062] Please see Figure 1 This invention provides a temperature-adaptive train brake disc wear monitoring method based on ZGV guided waves, the method comprising:

[0063] Step 101: Excite the brake disc of the train under test with an excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode, and collect the resonance Lamb wave signal formed by the reflection of the excitation signal in the brake disc of the train under test.

[0064] It should be noted that, in order to realistically simulate the working state of the train brake disc during train operation, please refer to [link / reference needed]. Figure 2The test bench uses a heating chamber to enclose the train brake disc and heat it to simulate the high-temperature conditions generated by friction during actual braking. The test bench supports both the brake disc and the heating chamber. In actual service, the friction between the brake pads and the brake disc generates temperatures of several hundred degrees Celsius. The material wave velocity of the train brake disc changes with temperature; therefore, temperature interference needs to be considered during the monitoring of train brake disc wear.

[0065] Zero Group Velocity (ZGV) mode and thickness resonance mode are extremely sensitive to the temperature and thickness of the train brake disc. To excite and respond to the resonant Lamb wave signals of the ZGV mode and thickness resonance mode, such as... Figure 2 As shown, an excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode can be excited by an electromagnetic ultrasonic transducer. The excitation signal undergoes multiple refractions and reflections in the brake disc of the train under test, eventually forming a resonant Lamb wave signal.

[0066] In this embodiment, two modal characteristic signals, namely the resonant Lamb wave signal, which are sensitive to both thickness and temperature, can be acquired simultaneously with a single excitation. This provides key input data for the subsequent synchronous inversion of the real-time thickness and temperature of the train brake disc, enabling high-precision, temperature-adaptive online wear monitoring without interfering with train operation.

[0067] In an optional implementation, the process of determining the excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode includes the following steps:

[0068] S11. Obtain the material parameters of the brake disc of the train under test, and construct a standard train brake disc sample associated with the brake disc of the train under test based on the material parameters.

[0069] S12. Based on the sample parameters of the standard train brake disc sample, establish the corresponding dispersion curve;

[0070] S13. Determine the first frequency corresponding to the ZGV point with a slope of 0 from the dispersion curve, and determine the second frequency corresponding to the thickness resonance point with a wavenumber of 0.

[0071] S14. Determine the excitation signal of the brake disc of the train under test through the first frequency and the second frequency.

[0072] The material parameters of the brake disc to be tested include material type, material density, and Poisson's ratio; the sample parameters include material parameters, sample thickness, and elastic modulus.

[0073] In this specific embodiment, based on the material parameters of the train brake disc under test, a flat plate model of a standard train brake disc sample with standard thickness under normal temperature conditions (20℃) is established using the COMSOL Multiphysics software platform; based on the sample parameters of the flat plate model of the standard train brake disc sample, its dispersion curves under each mode are established; the distribution relationship between wavenumber and frequency is obtained by solving the symmetric and antisymmetric guided wave modes of each order.

[0074] The solution to the dispersion curve is based on the Rayleigh–Lamb equation, which can be expressed as:

[0075] For S-mode (symmetric):

[0076]

[0077] For mode A (antisymmetric):

[0078]

[0079] In the formula: H is half the thickness of the flat plate model, K is the wavenumber; P and Q are the propagation constants, and satisfy the following two equations:

[0080]

[0081]

[0082] In the formula: Angular frequency; and These are the longitudinal wave velocity and transverse wave velocity in the flat plate model, respectively, calculated based on material parameters.

[0083] After solving the problem, MATLAB software is used to process and analyze the data. This embodiment mainly focuses on the frequency points of the ZGV mode and the thickness resonance mode. The ZGV mode corresponds to the point with a slope of zero, while the thickness resonance mode appears at the position of zero wavenumber. That is, the first frequency corresponding to the ZGV point with a slope of 0 and the second frequency corresponding to the thickness resonance point with a wavenumber of 0 are determined from the dispersion curve.

[0084] After determining the theoretical value of the excitation frequency from the dispersion curve, the experimental setup was used to analyze and select the appropriate excitation center frequency and period in order to find the best excitation signal and ensure that its spectrum can cover the range of these two frequency points at the same time. The design also takes into account the requirements of bandwidth and energy concentration to achieve effective excitation of S1-ZGV and S1 thickness resonant modes.

[0085] Specifically, in determining the excitation signal, the center frequency of the signal is calculated based on the first and second frequencies. This calculated center frequency can be used as the reference center frequency of the excitation signal, which can be adjusted according to the excitation effect of the mode. Then, the signal period is determined based on the frequency range of the first and second frequencies. The signal period selection requires the signal bandwidth to completely cover the frequency range of the first and second frequencies. Too few periods result in too wide a bandwidth and dispersed energy, while too many periods result in too narrow a bandwidth, which may not be able to cover both frequencies simultaneously. Next, a preset signal waveform is set according to the requirements of the excitation signal. A clean sine pulse can be used as the basic waveform. Finally, the excitation signal is generated based on the center frequency, signal period, and preset signal waveform.

[0086] Furthermore, in practical applications, for train brake discs with the same material parameters, only one excitation signal confirmation is needed when monitoring the wear of the train brake disc.

[0087] Step 102: Perform preprocessing and Fourier transform on the resonant Lamb wave signal in sequence to obtain the frequency domain data of the resonant Lamb wave signal.

[0088] In this embodiment, the resonant Lamb wave signal includes signal data of the S1–ZGV mode and the S1 thickness resonant mode. By performing preprocessing and Fourier transform on the resonant Lamb wave signal in sequence, the frequency domain data of the resonant Lamb wave signal obtained after transformation can clearly and accurately present the independent frequency domain data of the two modes, the S1–ZGV mode and the S1 thickness resonant mode, thus laying a reliable foundation for the subsequent accurate extraction of characteristic frequencies used for calculation.

[0089] In an optional implementation, step 102 may include the following steps:

[0090] S21. Perform Hanning window truncation and zero-padding expansion preprocessing on the resonant signal portion of the resonant Lamb wave signal to obtain the preprocessed signal.

[0091] S22. Perform a fast Fourier transform on the preprocessed signal to obtain the frequency domain data of the resonant Lamb wave signal.

[0092] In this specific embodiment, the stable signal portion (i.e., the resonant signal portion) in the resonant Lamb wave signal is preprocessed by Hanning window truncation and zero-padding to eliminate the initial pulse wave and noise interference while improving the frequency resolution. Then, the preprocessed signal is subjected to Fast Fourier Transform (FFT) to obtain frequency domain data, and the S1-ZGV mode and the S1 thickness resonant mode can be clearly distinguished in the frequency domain.

[0093] Step 103: Based on the frequency domain data of the resonant Lamb wave signal, extract the frequencies of the S1-ZGV mode and the S1 thickness resonant mode respectively.

[0094] In this embodiment, the main peak frequencies of the two modes, S1-ZGV mode and S1 thickness resonance mode, are extracted from the frequency domain data to determine the frequencies of the S1-ZGV mode and the S1 thickness resonance mode.

[0095] Step 104: Input the frequencies of the S1-ZGV mode and the S1 thickness resonance mode into the preset calibration model associated with the brake disc of the train under test, and calculate the working temperature and working thickness values ​​of the brake disc of the train under test.

[0096] It should be noted that the preset calibration model includes the thickness-temperature S1-ZGV mode two-dimensional fitting surface fitting equation and the thickness-temperature S1 thickness resonance mode two-dimensional fitting surface fitting equation. By inputting the frequencies of the S1-ZGV mode and the S1 thickness resonance mode into the preset calibration model, the working temperature value and working thickness value of the brake disc of the train under test can be calculated, providing reliable technical support for the online monitoring of train brake disc wear.

[0097] In one optional implementation, the process of establishing a preset calibration model may include the following steps:

[0098] S31. Obtain the elastic modulus of a standard train brake disc sample at different temperatures, and obtain the temperature-elastic modulus function through polynomial fitting.

[0099] S32. Construct test train brake disc samples with different elastic moduli and thickness gradients corresponding to the brake disc of the train under test;

[0100] S33. Excite the train brake disc sample under different elastic modulus and thickness gradients with excitation signals that simultaneously satisfy the ZGV mode and the thickness resonance mode, and collect the sample resonance Lamb wave signal formed by the reflection of the excitation signal in the train brake disc sample under different elastic modulus and thickness gradients.

[0101] S34. Perform preprocessing and Fourier transform on the sample resonance Lamb wave signal in sequence to obtain the sample frequency domain data of the sample resonance Lamb wave signal.

[0102] S35. Based on the sample frequency domain data of the sample resonance Lamb wave signal, extract the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different elastic moduli and thickness gradients respectively.

[0103] S36. Based on the temperature-elastic modulus function, the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different elastic moduli and thickness gradients are converted into the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different temperatures and thickness gradients.

[0104] S37. Based on the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different temperatures and thickness gradients, a preset calibration model is generated by fitting.

[0105] To effectively eliminate measurement errors caused by temperature disturbances during train brake disc wear monitoring, this invention aims to solve the coupling law among temperature, thickness, and frequency of the train brake disc. Based on this, considering that the elastic modulus of the train brake disc material has a clear correspondence with temperature, and that the ZGV mode and thickness resonance mode are essentially sensitive to the elastic properties (i.e., elastic modulus) and geometric dimensions (i.e., thickness) of the train brake disc, the elastic modulus of a standard train brake disc sample at different temperatures can be obtained in step S31, and the temperature-elastic modulus function can be obtained through polynomial fitting, thereby establishing the mapping relationship between temperature and elastic modulus.

[0106] After obtaining the elastic modulus of a standard train brake disc sample at different temperatures, a polynomial fitting can be used to construct a continuous functional relationship. The polynomial with the highest fit is then selected to determine the temperature-elastic modulus function. By establishing the mapping relationship between temperature and elastic modulus through the temperature-elastic modulus function, the equivalent elastic modulus of the material's local area can be calculated, thereby efficiently estimating the real-time operating temperature of the train brake disc.

[0107] In this specific embodiment, based on the material parameters of the train brake disc under test and different elastic moduli and thickness gradients, multiple two-dimensional finite element simulation models of the train brake disc samples are constructed using COMSOL Multiphysics software. A point source excitation method is used to simulate the self-generating and self-receiving working mode of an actual electromagnetic ultrasonic transducer, thereby achieving the excitation signal and the acquisition of the sample resonance Lamb wave signal. Then, the acquired sample resonance Lamb wave signal is preprocessed and subjected to Fourier transform to obtain the sample frequency domain data. Next, the frequency data of the S1-ZGV mode and the S1 thickness resonance mode under different elastic moduli and thickness gradients are extracted from the sample frequency domain data. Based on the temperature-elastic modulus function, the modal frequencies under different elastic moduli and thickness gradients are converted into modal frequencies under different temperature and thickness gradients. Finally, the modal frequencies under different temperature and thickness gradients are fitted to generate a preset calibration model.

[0108] In an optional implementation, step S37 may include:

[0109] S371. Based on the frequencies of the S1-ZGV modes under different temperature and thickness gradients, fit curves of the frequency of the S1-ZGV modes with thickness under different temperature gradients and fit curves of the frequency of the S1-ZGV modes with temperature under different thickness gradients are obtained.

[0110] S372. Based on the frequency of the S1 thickness resonance mode under different temperature and thickness gradients, fit curves of the frequency of the S1 thickness resonance mode with thickness under different temperature gradients and fit curves of the frequency of the S1 thickness resonance mode with temperature under different thickness gradients are obtained.

[0111] S373. Based on the fitting curves of the frequency of the S1-ZGV mode with thickness under different temperature gradients and the fitting curves of the frequency of the S1-ZGV mode with temperature under different thickness gradients, a two-dimensional fitting surface of the S1-ZGV mode with thickness-temperature is obtained, thereby establishing the fitting equation of the two-dimensional fitting surface of the S1-ZGV mode with thickness-temperature.

[0112] S374. Based on the fitting curves of the frequency of the S1 thickness resonance mode with thickness under different temperature gradients and the fitting curves of the frequency of the S1 thickness resonance mode with temperature under different thickness gradients, a two-dimensional fitting surface of the S1 thickness resonance mode with thickness-temperature is obtained, thereby establishing the fitting equation of the two-dimensional fitting surface of the S1 thickness resonance mode with thickness-temperature.

[0113] S375. Based on the thickness-temperature S1-ZGV mode two-dimensional fitting surface fitting equation and the thickness-temperature S1 thickness resonance mode two-dimensional fitting surface fitting equation, the preset calibration model is obtained.

[0114] Understandably, the S1-ZGV mode and the S1 thickness resonance mode are sensitive to both temperature and thickness. Therefore, under different temperature and thickness gradients, the frequencies of the S1-ZGV mode and the S1 thickness resonance mode will shift.

[0115] In this specific embodiment, the frequency variation patterns of the S1-ZGV mode and the S1 thickness resonance mode under a single variable (fixed temperature variation or fixed thickness) are analyzed, and a series of one-dimensional characteristic curves are obtained through fitting. Subsequently, based on the patterns and data of these one-dimensional curves, a surface fitting algorithm is used for fusion, and finally two continuous two-dimensional surface mathematical equations with thickness and temperature as independent variables are fitted, namely, the thickness-temperature S1 thickness resonance mode two-dimensional fitting surface fitting equation and the temperature-temperature S1 thickness resonance mode two-dimensional fitting surface fitting equation.

[0116] The frequencies of the extracted S1-ZGV modes and the S1 thickness resonance mode are input into the two-dimensional fitting surface equations of the thickness-temperature S1 thickness resonance mode and the temperature-temperature S1 thickness resonance mode, respectively. The operating temperature and operating thickness of the brake disc of the train under test are calculated, thereby realizing the temperature-adaptive measurement of the train brake disc thickness and providing reliable technical support for the high-temperature online diagnosis of train brake disc wear.

[0117] This invention demonstrates broad applicability and strong engineering practical value in wear monitoring, thickness assessment, and high-temperature measurement. It provides a new theoretical basis and technical means for the safety assessment and non-destructive testing of rail transit braking systems, and has significant engineering application prospects and promotion potential.

[0118] To facilitate understanding, this invention also provides a simulation verification example of a temperature-adaptive train brake disc wear monitoring method based on ZGV guided waves.

[0119] This example, based on the COMSOL Multiphysics software platform, constructs a multimodal resonant wave propagation model for inverting the thickness and temperature of a train brake disc. Considering the inherent limitations of three-dimensional full-scale modeling, such as high computational resource consumption and low solution efficiency, this example optimizes the model dimensions by employing a two-dimensional approximation from solid mechanics to improve computational efficiency.

[0120] 1) Establish the mathematical relationship between the temperature and elastic modulus of the train brake disc:

[0121] The train brake disc used in this example is made of 25Cr2MoV material. The material parameters and thickness settings at room temperature (20℃) are as follows: standard thickness 30 mm, density 7850 kg / m³, elastic modulus 215 GPa, and Poisson's ratio 0.3. Since the elastic modulus of the material has a clear correlation with temperature, its specific values ​​are shown in Table 1. To construct a continuous functional relationship, this example filters polynomials from order 0 to 5, ultimately selecting the second-order curve with the highest goodness of fit for fitting, thus obtaining the mathematical expression for the temperature-elastic modulus function between the elastic modulus and temperature, i.e. ,like Figure 3 As shown. The characteristics of resonant Lamb waves in the frequency domain are highly sensitive to changes in material parameters and thickness. Based on this characteristic, the local equivalent elastic modulus of the material can be obtained through inversion, and then the real-time temperature of the corresponding area of ​​the train brake disc can be calculated.

[0122] Table 1. Relationship between temperature (T) and elastic modulus (E) from 20℃ to 600℃

[0123]

[0124] 2) Based on the semi-analytical finite element method, the dispersion curve in the wavenumber-frequency domain is calculated, and the multimodal resonance Lamb wave signal is extracted:

[0125] The dispersion characteristics of a standard train brake disc with a temperature of 20℃ (elastic modulus of 215 GPa) and a thickness of 30 mm were calculated, and the results are as follows: Figure 4As shown. The resonant Lamb wave signal mainly includes the signals of the zero group velocity (ZGV) mode and the thickness resonant mode. In the dispersion curve, the ZGV mode corresponds to the point with a slope of zero, while the thickness resonant mode appears at the position of zero wavenumber. The specific resonant modes used in this example are the S1-ZGV mode and the S1 thickness resonant mode.

[0126] To effectively excite the aforementioned modes, a sinusoidal pulse with a center frequency of 100 kHz and modulated by a 5-cycle Hanning window was selected as the excitation signal. The form of the excitation signal is as follows: Figure 5 As shown in (a) and (b), its design takes into account both bandwidth and energy concentration requirements. It can concentrate the transmitted wave energy around 100kHz while covering the frequency range corresponding to the S1-ZGV mode and the S1 thickness resonance mode, which is beneficial to improving the signal-to-noise ratio and mode recognition accuracy of the detection signal.

[0127] 3) Establish a quantitative relationship between the multimodal resonance Lamb wave and the brake disc thickness and temperature, and construct a regression equation based on the S1-ZGV mode and the S1 thickness resonance mode:

[0128] In this example, a parameter combination with a thickness range of 25mm to 30mm (in 0.5mm increments) and an elastic modulus range of 170GPa to 215GPa (in 5GPa increments) was selected. These parameters were coupled one by one to establish two-dimensional finite element simulation models for multiple train brake disc samples for analysis. The model structure of a 30mm thick train brake disc sample under normal temperature conditions is shown below. Figure 6 As shown, a point source excitation method is used to simulate the self-generating and self-receiving working mode of an actual ultrasonic electromagnetic transducer.

[0129] Set the total simulation time to 1000 in each model. This ensures that the ultrasonic waves from the excitation signal fully generate resonant Lamb waves within the train brake disc and form a stable resonance process. The normal displacement at the receiving point is then extracted as the response signal.

[0130] in, Figure 7 (a) shows the time-domain signal corresponding to the increase in elastic modulus from 170 GPa to 215 GPa when the thickness is fixed at 30 mm. It can be observed that there is a relatively strong initial pulse wave in the initial stage, followed by multiple refractions and reflections of the longitudinal and transverse waves within the brake disc, eventually forming a resonant Lamb wave. This process typically takes about 10 times the length of the excitation signal; therefore, for a 500... The subsequent resonant signal segment is truncated using a Hanning window and preprocessed with zero-padding. Then, a fast Fourier transform is used to obtain the spectrum of the frequency domain data, as shown below. Figure 7 As shown in (b).

[0131] Spectral analysis results show that, under constant thickness, both the S1-ZGV mode and the S1 thickness resonance mode exhibit significant frequency shifts with changes in the elastic modulus (i.e., temperature), and these shifts are highly sensitive. Similarly, when the train brake disc thickness is changed while maintaining a fixed elastic modulus, these two modes also exhibit similar frequency shift characteristics, such as... Figure 8 As shown in (a) and (b), the frequency of the resonant Lamb wave signal exhibits a coupled response characteristic to thickness and temperature. By extracting the frequency domain characteristics of the multimodal resonant Lamb wave, the thickness and temperature parameters of the train brake disc can be simultaneously inverted and calculated.

[0132] based on Figure 3 The established temperature-elastic modulus function mathematical relationship converts the elastic modulus range of 170 GPa–215 GPa into corresponding temperature values. Next, frequency response fitting analyses were performed under single-variable conditions of fixed temperature and fixed thickness, and the fitting curve results are shown below. Figure 9 (a) and (b) and Figure 10 As shown in (a) and (b). From Figure 9 and Figure 10 It can be observed that, regardless of whether the thickness is changed while the temperature is fixed or the temperature is changed while the thickness is fixed, the frequencies of the S1-ZGV mode and the S1 thickness resonance mode both exhibit good monotonic variation characteristics.

[0133] Based on the fitted curves, two-dimensional fitting surfaces for the S1-ZGV modal frequencies and the S1 thickness resonant modal frequencies with respect to the brake disc thickness and temperature were constructed, as follows: Figure 11 As shown in (a) and (b), the corresponding calibration model is constructed. The resulting surface fitting equation is as follows:

[0134] For the S1-ZGV mode, its two-dimensional fitted surface equation is: ;

[0135] For the S1 thickness resonance mode, its two-dimensional fitted surface equation is: In the above formula, H represents the thickness of the train brake disc, and T represents the temperature of the train brake disc.

[0136] From the goodness-of-fit index ( From the perspective of both the S1-ZGV and the root mean square error (RMSE), the fitting accuracy of both modes is high, indicating that the frequency shift characteristics of the multimode resonance wave are strongly correlated with the brake disc thickness and temperature. Therefore, by obtaining the actual frequencies of the S1-ZGV and S1 thickness resonance modes and substituting them into the above fitting equation, the simultaneous calculation of the two physical quantities of brake disc thickness and temperature can be achieved.

[0137] 4) Real-time monitoring of train brake disc wear and temperature using the frequencies of the S1-ZGV mode and the S1 thickness resonance mode, combined with the fitted equation:

[0138] After establishing the calibration model, in order to achieve real-time monitoring of the wear state and temperature of the train brake disc, the frequency values ​​of the S1-ZGV mode and the S1 thickness resonance mode extracted from the actual detected resonance Lamb wave signal can be substituted into the corresponding fitting equations to simultaneously solve for the working thickness and working temperature of the train brake disc.

[0139] To verify the accuracy of this method, a finite element verification model was constructed with a brake disc thickness of 26.3 mm and a temperature of 250℃ (corresponding to an elastic modulus of 201.167 GPa). The time-domain signal received by the probe was extracted and analyzed at 500... Up to 1000 Spectral analysis was performed on the signal segment within the time interval, and the results are as follows: Figure 12 As shown in (a) and (b), under the verification conditions, the extracted S1-ZGV modal frequency is 105.5078 kHz, and the S1 thickness resonance modal frequency is 111.445 kHz. Substituting these two frequency values ​​into the two fitting equations in the calibration model, the thickness H = 26.1 mm and the temperature T = 263.4 ℃ were calculated. Compared with the preset values ​​of the model, the thickness calculation error is 0.2 mm, with a relative error of 0.76%, and the temperature calculation error is 13.4 ℃, with a relative error of 5.36%. The results show that the train brake disc thickness and temperature obtained by this method are in high agreement with the actual values, and have good measurement accuracy and engineering applicability.

[0140] Therefore, the temperature-adaptive train brake disc wear monitoring method based on ZGV guided waves proposed in this invention, based on the frequency domain characteristic fusion of multimodal resonant Lamb waves, can simultaneously achieve highly reliable monitoring of train brake disc thickness and temperature. It features simple operation, sensitive response, and strong robustness, providing an innovative and practical technical means for monitoring the structural health of brake discs in the rail transit field.

[0141] The following describes the temperature-adaptive train brake disc wear monitoring system based on ZGV guided waves provided in the embodiments of this application. The temperature-adaptive train brake disc wear monitoring system based on ZGV guided waves described below can be referred to in correspondence with the temperature-adaptive train brake disc wear monitoring method based on ZGV guided waves described above.

[0142] Please see Figure 13 The present invention also provides a temperature-adaptive train brake disc wear monitoring system based on ZGV guided waves, the system comprising:

[0143] The excitation unit 201 is used to excite an excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode to the brake disc of the train under test, and to collect the resonance Lamb wave signal formed by the reflection of the excitation signal in the brake disc of the train under test.

[0144] ZGV frequency domain data processing unit 202 is used to preprocess and Fourier transform the resonant Lamb wave signal sequentially to obtain the frequency domain data of the resonant Lamb wave signal.

[0145] The multimodal frequency extraction unit 203 is used to extract the frequencies of the S1-ZGV mode and the S1 thickness resonant mode based on the frequency domain data of the resonant Lamb wave signal.

[0146] The temperature and thickness calculation unit 204 is used to input the frequency of the S1-ZGV mode and the frequency of the S1 thickness resonance mode into the preset calibration model associated with the brake disc of the train under test, and calculate the working temperature value and working thickness value of the brake disc of the train under test.

[0147] ZGV frequency domain data processing unit 202 includes:

[0148] The preprocessing subunit is used to perform Hanning window truncation and zero-padding expansion preprocessing on the resonant signal portion of the resonant Lamb wave signal to obtain the preprocessed signal.

[0149] The Fourier transform subunit is used to perform a fast Fourier transform on the preprocessed signal to obtain the frequency domain data of the resonant Lamb wave signal.

[0150] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the above-described temperature-adaptive train brake disc wear monitoring methods.

[0151] The present invention also provides a computer-readable storage medium having a computer program or instructions stored thereon, wherein the computer program or instructions, when executed by a processor, implement the steps of any of the above-mentioned temperature-adaptive train brake disc wear monitoring methods.

[0152] The present invention also provides a computer program product, including a computer program or instructions, wherein when the computer program or instructions are executed by a processor, the steps of any of the above-mentioned temperature-adaptive train brake disc wear monitoring methods are implemented.

[0153] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0154] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0155] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0156] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0157] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0158] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A temperature-adaptive train brake disc wear monitoring method based on ZGV guided waves, characterized in that, The method includes: An excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode is excited to the brake disc of the train under test, and the resonance Lamb wave signal formed by the reflection of the excitation signal in the brake disc of the train under test is collected. The resonant Lamb wave signal is preprocessed and Fourier transformed sequentially to obtain the frequency domain data of the resonant Lamb wave signal; Based on the frequency domain data of the resonant Lamb wave signal, the frequencies of the S1-ZGV mode and the S1 thickness resonant mode are extracted respectively. The frequencies of the S1-ZGV mode and the S1 thickness resonance mode are input into a preset calibration model associated with the brake disc of the train under test, and the operating temperature and operating thickness values ​​of the brake disc of the train under test are calculated.

2. The temperature-adaptive train brake disc wear monitoring method according to claim 1, characterized in that, The process of determining the excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode includes: Obtain the material parameters of the brake disc of the train under test, and construct a standard train brake disc sample associated with the brake disc of the train under test based on the material parameters; Based on the sample parameters of the standard train brake disc sample, a corresponding dispersion curve is established; Determine the first frequency corresponding to the ZGV point with a slope of 0 from the dispersion curve, and determine the second frequency corresponding to the thickness resonance point with a wavenumber of 0. The excitation signal of the brake disc of the train under test is determined by the first frequency and the second frequency.

3. The temperature-adaptive train brake disc wear monitoring method according to claim 2, characterized in that, The process of establishing the preset calibration model includes: The elastic modulus of the standard train brake disc sample at different temperatures was obtained, and the temperature-elastic modulus function was obtained by polynomial fitting. Construct test train brake disc samples with different elastic moduli and thickness gradients corresponding to the test train brake disc; Excitation signals that simultaneously satisfy the ZGV mode and the thickness resonance mode are excited to the measurement train brake disc samples under different elastic moduli and thickness gradients, and the sample resonance Lamb wave signal formed by the reflection of the excitation signal in the measurement train brake disc samples under different elastic moduli and thickness gradients is collected. The sample resonance Lamb wave signal is preprocessed and Fourier transformed sequentially to obtain the sample frequency domain data of the sample resonance Lamb wave signal. Based on the sample frequency domain data of the sample resonance Lamb wave signal, the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different elastic moduli and thickness gradients are extracted respectively. Based on the temperature-elastic modulus function, the frequencies of the S1-ZGV modes and the S1 thickness resonance modes under different elastic moduli and thickness gradients are converted into the frequencies of the S1-ZGV modes and the S1 thickness resonance modes under different temperatures and thickness gradients. Based on the frequencies of the S1-ZGV modes and the S1 thickness resonance modes under different temperatures and thickness gradients, a preset calibration model is generated.

4. The temperature-adaptive train brake disc wear monitoring method according to claim 3, characterized in that, The process of establishing a preset calibration model by fitting the frequencies of the S1-ZGV mode and the S1 thickness resonance mode under different temperature and thickness gradients includes... Based on the frequencies of the S1-ZGV modes under different temperature and thickness gradients, fitting curves of the frequency of the S1-ZGV modes with thickness under different temperature gradients and fitting curves of the frequency of the S1-ZGV modes with temperature under different thickness gradients were obtained. Based on the frequencies of the S1 thickness resonance modes under different temperature and thickness gradients, fitting curves of the frequency of the S1 thickness resonance modes as a function of thickness under different temperature gradients and fitting curves of the frequency of the S1 thickness resonance modes as a function of temperature under different thickness gradients are obtained. Based on the fitting curves of the frequency of the S1-ZGV mode with thickness under different temperature gradients and the fitting curves of the frequency of the S1-ZGV mode with temperature under different thickness gradients, a two-dimensional fitting surface of the S1-ZGV mode with thickness-temperature is obtained, thereby establishing the fitting equation of the two-dimensional fitting surface of the S1-ZGV mode with thickness-temperature. Based on the fitting curves of the frequency of the S1 thickness resonance mode with thickness under different temperature gradients and the fitting curves of the frequency of the S1 thickness resonance mode with temperature under different thickness gradients, a two-dimensional fitting surface of the S1 thickness resonance mode with thickness-temperature is obtained, thereby establishing the fitting equation of the two-dimensional fitting surface of the S1 thickness resonance mode with thickness-temperature. Based on the thickness-temperature S1-ZGV mode two-dimensional fitting surface fitting equation and the thickness-temperature S1 thickness resonance mode two-dimensional fitting surface fitting equation, a preset calibration model is obtained.

5. The temperature-adaptive train brake disc wear monitoring method according to claim 1, characterized in that, The step of sequentially preprocessing and Fourier transforming the resonant Lamb wave signal to obtain its frequency domain data includes: The resonant signal portion of the resonant Lamb wave signal is truncated using a Hanning window and pre-processed with zero-padding to obtain a pre-processed signal. The preprocessed signal is subjected to a fast Fourier transform to obtain the frequency domain data of the resonant Lamb wave signal.

6. A temperature-adaptive train brake disc wear monitoring system based on ZGV guided waves, characterized in that, The system includes: The excitation unit is used to excite an excitation signal that simultaneously satisfies the ZGV mode and the thickness resonance mode to the brake disc of the train under test, and to collect the resonance Lamb wave signal formed by the reflection of the excitation signal in the brake disc of the train under test. The ZGV frequency domain data processing unit is used to preprocess and perform Fourier transform on the resonant Lamb wave signal in sequence to obtain the frequency domain data of the resonant Lamb wave signal. The multimodal frequency extraction unit is used to extract the frequencies of the S1-ZGV modes and the S1 thickness resonant modes respectively based on the frequency domain data of the resonant Lamb wave signal. The temperature and thickness calculation unit is used to input the frequency of the S1-ZGV mode and the frequency of the S1 thickness resonance mode into a preset calibration model associated with the brake disc of the train under test, and calculate the working temperature value and working thickness value of the brake disc of the train under test.

7. The temperature-adaptive train brake disc wear monitoring system according to claim 6, characterized in that, The ZGV frequency domain data processing unit includes: The preprocessing subunit is used to perform Hanning window truncation and zero-padding expansion preprocessing on the resonant signal portion of the resonant Lamb wave signal to obtain the preprocessed signal. The Fourier transform subunit is used to perform a fast Fourier transform on the preprocessed signal to obtain the frequency domain data of the resonant Lamb wave signal.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the temperature-adaptive train brake disc wear monitoring method as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by the processor, they implement the steps of the temperature-adaptive train brake disc wear monitoring method as described in any one of claims 1-5.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by the processor, they implement the steps of the temperature-adaptive train brake disc wear monitoring method as described in any one of claims 1-5.

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