Method and system for detecting interlayer peel strength of PTFE (Polytetrafluoroethylene) membrane material

Abstract

The invention relates to the technical field of PTFE detection, and particularly discloses a method and a system for detecting interlayer peel strength of a PTFE membrane material, and the method comprises the following steps: acquiring an ultrasonic wave A scanning data sequence and local membrane material tension information; performing filtering processing according to the ultrasonic A scanning data sequence to obtain an ultrasonic signal; the ultrasonic compensation amount is calculated according to the local membrane material tension information, and the ultrasonic signal is compensated according to the ultrasonic compensation amount; according to the compensated ultrasonic signal, extracting a strength characteristic parameter related to the interlayer peeling strength; based on a preset quantitative relationship, quantifying the strength characteristic parameters into interlayer peel strength distribution data of the to-be-detected region; the method solves the problem that structural noise generated by a glass fiber base cloth woven structure is aliasing with a peel strength characteristic signal, and the problem that ultrasonic signal comparability is reduced due to the fact that an acoustic elastic effect is introduced by non-uniformity of tension of a membrane material in an in-service state.

Description

Technical Field

[0001] The present application relates to the field of PTFE detection technology, and more specifically, to a method and system for detecting the interlayer peeling strength of PTFE membrane materials. Background Art

[0002] PTFE membranes are widely used in the roof structures of large public buildings such as stadiums and airport terminals due to their light weight, good light transmittance and strong self-cleaning properties. Non-destructive testing technologies such as ultrasonic testing have become the mainstream method for evaluating the interlayer peel strength of PTFE membranes, supporting predictive maintenance and structural safety monitoring, and promoting the construction industry to develop in the direction of efficient, non-destructive health assessment.

[0003] However, ultrasonic testing faces severe challenges in quantitatively evaluating interlayer peel strength. The periodic weaving structure of the glass fiber base cloth causes the thickness and acoustic properties of the PTFE membrane to show regular changes at the microscopic scale, generating a strong structural noise signal. This noise is mixed with the weak acoustic characteristic signal representing the peel strength, making it difficult to effectively separate. At the same time, the tension unevenness of the PTFE membrane in service introduces the acoustic elastic effect. The difference in tension at different locations causes changes in the sound velocity and reflection characteristics, which reduces the comparability of the ultrasonic signal. The combined effect of these interfering factors hinders the stable extraction of characteristic parameters related to peel strength from the echo signal, making it impossible to achieve a reliable quantitative assessment and early warning of the health status of the entire membrane surface.

[0004] There is currently no effective technical solution to the above problems. Summary of the Invention

[0005] The purpose of this application is to provide a method and system for detecting the peel strength between layers of PTFE membrane materials, so as to solve the problem of the overlapping of the structural noise generated by the glass fiber base cloth woven structure and the peel strength characteristic signal, and the problem of the uneven tension of the membrane material in service introducing the acoustic elastic effect, which leads to the reduction of the comparability of the ultrasonic signal, thereby achieving the effect of quantitatively evaluating the peel strength between layers of PTFE membrane materials.

[0006] In a first aspect, the present application provides a method for detecting the peel strength between layers of a PTFE membrane material, for quantitatively evaluating the peel strength between layers of a membrane material in an in-service PTFE membrane structure, the method comprising the following steps: S1. Acquire an ultrasonic A-scan data sequence of a region to be measured in a PTFE membrane and local membrane tension information of the region to be measured, wherein the ultrasonic A-scan data sequence covers at least several weaving cycles of the glass fiber base cloth; S2. Filtering the periodic spatial frequency components generated by the glass fiber base cloth woven structure according to the ultrasonic A-scan data sequence to obtain an ultrasonic signal; S3. Based on a pre-established tension-ultrasonic parameter correlation relationship, an ultrasonic compensation amount is calculated according to the local film material tension information, and the ultrasonic signal is compensated according to the ultrasonic compensation amount; S4. extracting strength characteristic parameters related to interlayer peeling strength based on the compensated ultrasonic signal; S5. Based on a preset quantitative relationship, quantify the strength characteristic parameter into interlayer peeling strength distribution data of the area to be measured.

[0007] The method for detecting the interlayer peeling strength of PTFE membrane materials, wherein step S1 comprises: S11, scanning the area to be measured along a preset scanning path using an ultrasonic probe to obtain the ultrasonic A-scan data sequence, and simultaneously collecting the vibration frequency using a laser displacement sensor; S12. Mapping the vibration frequency to the local film material tension information according to a preset mapping relationship.

[0008] The method for detecting the interlayer peeling strength of PTFE membrane materials, wherein step S2 comprises: S21, converting the ultrasonic A-scan data sequence into spatial domain data, and converting the spatial domain data into a spatial frequency spectrum; S22, analyzing the spatial frequency spectrum to identify characteristic positions and bandwidths of periodic noise caused by the woven structure of the glass fiber base cloth; S23, constructing a spatial domain filter based on the characteristic position and bandwidth, and using the spatial domain filter to attenuate or eliminate periodic frequency components related to the woven structure of the glass fiber base cloth in the spatial frequency spectrum to obtain a filtered spatial frequency spectrum; S24. Inversely convert the filtered frequency spectrum into the ultrasonic signal.

[0009] The method for detecting the interlayer peeling strength of PTFE membrane materials, wherein step S22 comprises: S221. Identify periodic components of the spatial frequency spectrum to obtain periodic frequency components with significant energy in the spatial frequency spectrum; S222. Based on the preset spatial frequency characteristics of the glass fiber base cloth woven structure, compare and screen the periodic frequency components with significant energy to determine the periodic frequency components in the spatial frequency spectrum that are consistent with the glass fiber base cloth woven structure; S223 , extracting the center frequency and frequency range of the periodic frequency component consistent with the woven structure of the glass fiber base cloth as the characteristic position and the bandwidth, respectively.

[0010] The method for detecting the interlayer peeling strength of PTFE membrane materials, wherein the strength characteristic parameters include one or more of the amplitude attenuation rate of the reflected echo at the interface between the PTFE coating and the base fabric, the echo waveform broadening, the energy distribution change, and the ratio of the target frequency components.

[0011] The method for detecting the interlayer peel strength of PTFE membrane materials, wherein the strength characteristic parameters include the amplitude attenuation rate of the echo reflected from the interface between the PTFE coating and the base fabric, the echo waveform broadening, the energy distribution change, and the ratio of the target frequency components, step S4 includes: S41, identifying and isolating the reflected echo from the interface between the PTFE coating and the base fabric from the compensated ultrasonic signal; S42, calculating the ratio of the amplitude of the reflected echo to a preset reference amplitude to obtain the amplitude attenuation rate; S43, calculating the waveform duration or characteristic width of the reflected echo according to the waveform of the isolated reflected echo to obtain the echo waveform broadening; S44, performing frequency domain conversion on the reflected echo, and analyzing energy distribution of different frequency segments in the frequency domain conversion result to obtain the energy distribution change; S45. Calculating the energy ratio between the target frequency components in the frequency domain conversion result to obtain the ratio of the target frequency components; S46. Taking the amplitude attenuation rate, the echo waveform broadening, the energy distribution change, and the ratio of the target frequency component as the intensity characteristic parameters.

[0012] The method for detecting the interlayer peeling strength of PTFE membrane materials, wherein step S41 comprises: S411, determining an expected arrival time range of the reflected echo at the interface between the PTFE coating and the base fabric based on the thickness information of the PTFE coating and the propagation speed of the ultrasonic wave in the PTFE coating; S412: Within the expected arrival time range, identify the echo signal with the maximum amplitude in the compensated ultrasonic signal, use the echo signal as the echo reflected from the interface between the PTFE coating and the base fabric, and isolate the echo signal.

[0013] The method for detecting interlayer peel strength of PTFE membrane materials, wherein the quantitative relationship includes a nonlinear mapping function, and the nonlinear mapping function is a pre-established transformation function of weighted characteristic parameters and interlayer peel strength, and step S5 includes: S51. Weighting different parameters of the intensity characteristic parameters of different measurement points in the area to be measured based on preset parameter weights to obtain weighted characteristic parameters of the different measurement points in the area to be measured; S52, mapping the weighted characteristic parameter to interlayer peeling strength based on the nonlinear mapping function; S53 , generating interlayer peeling strength distribution data of the area to be measured according to the interlayer peeling strengths at different measuring points in the area to be measured.

[0014] The method for detecting the interlayer peeling strength of PTFE membrane materials, wherein step S53 comprises: S531, generating a continuous interlayer peeling strength field of the area to be measured based on the interlayer peeling strengths of different measuring points in the area to be measured using a spatial interpolation method; S532 : Generate an interlayer peeling strength distribution diagram of the area to be measured as the interlayer peeling strength distribution data according to the continuous interlayer peeling strength field.

[0015] In a second aspect, the present application further provides a PTFE membrane interlayer peeling strength detection system for quantitatively evaluating the interlayer peeling strength of a PTFE membrane structure in service, the system comprising: an acquisition module, configured to acquire an ultrasonic A-scan data sequence of a region to be measured in the PTFE membrane material and local membrane material tension information of the region to be measured, wherein the ultrasonic A-scan data sequence covers at least several weaving cycles of the glass fiber base cloth; an ultrasonic extraction module for filtering the periodic spatial frequency components generated by the glass fiber base cloth woven structure according to the ultrasonic A-scan data sequence to obtain an ultrasonic signal; an ultrasonic compensation module, configured to calculate an ultrasonic compensation amount according to the local film material tension information based on a pre-established tension-ultrasonic parameter correlation relationship, and compensate the ultrasonic signal according to the ultrasonic compensation amount; A feature extraction module is used to extract strength feature parameters related to interlayer peeling strength based on the compensated ultrasonic signal; The quantification module is used to quantify the strength characteristic parameters into interlayer peeling strength distribution data of the area to be measured based on a preset quantization relationship.

[0016] From the above, it can be seen that the present application provides a method and system for detecting the peel strength between layers of PTFE membrane materials. The method of the present application combines the structural noise filtering processing of the ultrasonic A-scan data sequence with the acoustic elastic effect compensation of the local membrane tension information in a series manner, thereby solving the problem of the overlapping of the structural noise generated by the glass fiber base cloth woven structure and the peel strength characteristic signal, as well as the problem of the acoustic elastic effect introduced by the uneven tension of the membrane material in the service state, resulting in a reduction in the comparability of the ultrasonic signal, thereby achieving the effect of quantitatively evaluating the peel strength between layers of PTFE membrane materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Flowchart of the method for detecting the interlayer peel strength of PTFE membrane provided in an embodiment of the present application.

[0018] Figure 2 This is a schematic diagram of the structure of the PTFE membrane interlayer peeling strength detection system provided in an embodiment of the present application.

[0019] Reference numerals: 201, acquisition module; 202, ultrasonic extraction module; 203, ultrasonic compensation module; 204, feature extraction module; 205, quantification module. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of the present application.

[0021] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0022] First, please refer to Figure 1 Some embodiments of the present application provide a method for detecting the peel strength between layers of a PTFE membrane material, for quantitatively evaluating the peel strength between layers of a PTFE membrane material in an in-service PTFE membrane structure. The method comprises the following steps: S1. Acquire an ultrasonic A-scan data sequence of a region to be measured in a PTFE membrane and local membrane tension information of the region to be measured, wherein the ultrasonic A-scan data sequence covers at least several weaving cycles of the glass fiber base cloth; S2. Filtering the periodic spatial frequency components generated by the glass fiber base cloth woven structure according to the ultrasonic A-scan data sequence to obtain an ultrasonic signal; S3. Based on the pre-established tension-ultrasonic parameter correlation relationship, the ultrasonic compensation amount is calculated according to the local membrane material tension information, and the ultrasonic signal is compensated according to the ultrasonic compensation amount; S4. extracting strength characteristic parameters related to interlayer peeling strength based on the compensated ultrasonic signal; S5. Based on a preset quantitative relationship, the intensity characteristic parameter is quantified into interlayer peeling strength distribution data of the area to be measured.

[0023] Specifically, the ultrasonic A-scan data sequence refers to a series of ultrasonic time-domain waveform data collected along a specific path. Each waveform records the change in the signal intensity of the ultrasonic wave propagating inside the material and reflected echoes from different interfaces over time. It is used to obtain the acoustic information inside the membrane material, especially the reflected echoes at the interface between the PTFE coating and the base fabric. These echoes contain information for evaluating the interlayer peel strength.

[0024] More specifically, local membrane tension information refers to the tensile stress or strain data experienced by the membrane within the measured area, reflecting the stress state at different locations on the membrane. This information can be acquired using non-contact or contact sensors. For example, a laser displacement sensor can measure the membrane's vibration frequency and map it to tension. This information can be used to characterize the nonuniformity of membrane tension during operation, providing a data foundation for subsequent compensation of the acoustoelastic effect and ensuring the comparability of ultrasonic signals.

[0025] More specifically, the weave period of the glass fiber fabric refers to the size or spatial spacing of the repetitive structural units formed during the weaving process. This can be determined based on microstructural analysis of the membrane material, image processing, or prior material characterization. This serves to guide the acquisition range of the ultrasonic A-scan data sequence for subsequent filtering. The periodic spatial frequency component refers to the spatially periodic frequency component in the ultrasonic A-scan data sequence, caused by the weave structure of the glass fiber fabric.

[0026] More specifically, the tension-ultrasonic parameter correlation relationship refers to the quantitative correspondence between the tension exerted on the membrane material and the characteristic parameters of ultrasonic propagation in the membrane material (such as sound velocity, echo amplitude or transit time, etc.). It can be based on applying tension loads of different gradients to the membrane sample in a controlled environment, performing ultrasonic testing at the same time, measuring the corresponding ultrasonic propagation parameters, and then establishing a mathematical model or lookup table through data fitting, regression analysis or machine learning methods. It is used to calculate the deviation of the ultrasonic signal caused by tension changes based on the actual measured local membrane tension information, and then compensate for it to eliminate the influence of tension unevenness on the test results.

[0027] More specifically, the intensity characteristic parameter refers to a quantitative indicator extracted from the compensated ultrasonic signal that can reflect the peel strength between the interface layer of the PTFE coating and the base fabric. It is a bridge connecting the ultrasonic signal and the peel strength.

[0028] Specifically, the method of the present application first obtains the ultrasonic A-scan data sequence and the corresponding local membrane material tension information of the area to be measured. The ultrasonic A-scan data sequence contains the time domain waveform of the ultrasonic wave propagating inside the membrane material and reflected from the interface between the PTFE coating and the base fabric. These waveforms are the basis for analyzing the interlayer peeling strength. At the same time, the local membrane material tension information is obtained, which provides a data basis for the subsequent solution of the acoustic elastic effect caused by the tension unevenness of the membrane material in service. The acquisition range of the ultrasonic A-scan data sequence covers at least several weaving cycles of the glass fiber base fabric, ensuring that the data contains periodic information, which provides a prerequisite for the subsequent identification and removal of structural noise. Subsequently, based on the acquired ultrasonic A-scan data sequence, the periodic spatial frequency components generated by the weaving structure of the glass fiber base fabric are filtered. This processing step can strip these structural noises from the original signal, so that the obtained ultrasonic signal has a higher signal-to-noise ratio, wherein the acoustic characteristic signals related to the interlayer peeling strength are no longer masked by the structural noise, thereby improving the accuracy of subsequent feature extraction. Next, based on a pre-established tension-ultrasonic parameter correlation, the local membrane tension information is used to calculate an ultrasonic compensation value. This compensation is then used to compensate the ultrasonic signal after removing structure-induced noise. This compensation process eliminates the effects of tension nonuniformity on ultrasonic signal propagation characteristics (such as sound velocity and reflection characteristics), making ultrasonic signals at different measurement points under different tension conditions comparable and thus reflecting the true interlayer peel strength. After obtaining the compensated ultrasonic signal, intensity characteristic parameters related to interlayer peel strength are extracted. Due to the improved purity and comparability of the input signal, the extracted intensity characteristic parameters are less susceptible to external interference and can therefore characterize the interlayer peel state of the membrane material. Finally, based on a pre-defined quantization relationship, the extracted intensity characteristic parameters are quantified into interlayer peel strength distribution data for the measured area. This quantification process converts the intensity characteristic parameters into specific interlayer peel strength values ​​and presents them as distribution data, allowing users to understand the peel strength status of the entire measured area, thereby supporting predictive maintenance and structural safety monitoring. The entire process, through step-by-step processing and correction, ensures the accuracy of the final assessment results.

[0029] Through the above scheme, the method of this application improves the signal-to-noise ratio by filtering the periodic spatial frequency components. At the same time, by introducing local membrane tension information and performing ultrasonic compensation, it solves the problem of reduced ultrasonic signal comparability caused by the acoustic elastic effect introduced by the uneven membrane tension in the service state, thus ensuring the accuracy and comparability of data at different measurement points. As a result, the method of this application can extract characteristic parameters related to peel strength from the ultrasonic signal and quantify them into interlayer peel strength distribution data, thereby achieving quantitative assessment and early warning of the health status of the entire membrane surface.

[0030] The method of the present application combines the structural noise filtering processing of the ultrasonic A-scan data sequence with the acoustic elastic effect compensation of the local membrane tension information in a series manner, thereby solving the problem of the overlapping of the structural noise generated by the glass fiber base cloth woven structure and the peel strength characteristic signal, as well as the problem of the acoustic elastic effect introduced by the uneven tension of the membrane material in the service state, which leads to a reduction in the comparability of the ultrasonic signal, thereby achieving the effect of quantitatively evaluating the peel strength between PTFE membrane layers.

[0031] In some preferred embodiments, step S1 includes: S11, scanning the area to be measured along a preset scanning path using an ultrasonic probe to obtain an ultrasonic A-scan data sequence, and simultaneously collecting vibration frequency using a laser displacement sensor; S12. Map the vibration frequency to local membrane material tension information according to a preset mapping relationship.

[0032] Specifically, the process of obtaining the ultrasonic A-scan data sequence in step S11 can be carried out in combination with an adaptive flexible coupling interface or constant contact pressure control, wherein the adaptive flexible coupling interface refers to a flexible material or structure that can automatically adjust its own shape according to changes in the surface shape and roughness of the PTFE membrane material to maintain close contact with the membrane surface. It can be achieved by using a liquid-filled bag, a gel pad, a flexible rubber probe or a multi-joint robotic arm in combination with a flexible probe; constant contact pressure control refers to a technology that ensures that a preset and stable contact pressure is always maintained between the ultrasonic probe and the surface of the PTFE membrane material through a mechanical or electronic feedback system. It can be achieved by using a spring loading mechanism, a pneumatic / hydraulic drive system combined with pressure sensor feedback control or a force sensor and servo motor linkage control; adopting an adaptive flexible coupling interface or constant contact pressure control can ensure stable contact between the ultrasonic probe and the surface of the PTFE membrane material.

[0033] More specifically, the preset mapping relationship refers to a mathematical function or lookup table established through experimental calibration, theoretical modeling or data-driven methods, which is used to associate the vibration frequency of the membrane material with the local membrane material tension value. It can be implemented using polynomial fitting, neural network models, finite element simulation results or nonlinear regression models constructed based on a large amount of experimental data.

[0034] Specifically, when acquiring ultrasonic A-scan data sequences, the ultrasonic probe, combined with an adaptive flexible coupling interface or constant contact pressure control, scans the test area along a pre-set scanning path. This combination ensures stable and consistent acoustic coupling between the probe and the PTFE membrane surface, effectively avoiding contact instability caused by uneven or curved membrane surfaces. This ensures the accuracy and comparability of the acquired ultrasonic A-scan data sequences, providing high-quality raw data for subsequent signal processing and intensity feature parameter extraction. Simultaneously, during the scanning process, a laser displacement sensor simultaneously acquires the membrane's vibration frequency. The laser displacement sensor accurately measures the membrane's vibration response under specific excitations in a non-contact manner. This vibration frequency is physically correlated with the membrane's local tension. This approach avoids the potential damage or interference to the membrane caused by traditional contact tension measurement and allows for accurate raw vibration data to be acquired. Subsequently, based on a pre-set mapping relationship, the acquired vibration frequency is converted into local membrane tension information, resulting in a local tension value that precisely corresponds to the ultrasonic A-scan data sequence.

[0035] By stably acquiring ultrasonic signals and precise local tension information, the method of the present application can more accurately compensate for the acoustic-elastic effect, thereby effectively eliminating the influence of tension unevenness on the propagation characteristics of the ultrasonic signal, so that the intensity characteristic parameters extracted from the compensated ultrasonic signal can more accurately reflect the interlayer peeling strength, thereby improving the reliability of the entire PTFE membrane interlayer peeling strength detection method and the accuracy of quantitative evaluation.

[0036] In some preferred embodiments, step S2 includes: S21, converting the ultrasonic A-scan data sequence into spatial domain data, and converting the spatial domain data into a spatial frequency spectrum; S22. Analyze the spatial frequency spectrum to identify the characteristic position and bandwidth of the periodic noise caused by the woven structure of the glass fiber base cloth; S23. Constructing a spatial domain filter based on the characteristic position and bandwidth, and using the spatial domain filter to attenuate or eliminate periodic frequency components related to the woven structure of the glass fiber base cloth in the spatial frequency spectrum to obtain a filtered spatial frequency spectrum; S24. Inversely convert the filtered frequency spectrum into an ultrasonic signal.

[0037] Specifically, the characteristic location and bandwidth of periodic noise refer to the specific frequency point or frequency range occupied by the periodic noise generated by the glass fiber base fabric woven structure in the spatial frequency spectrum. This can be determined through spectral analysis of the spatial frequency spectrum, such as peak detection, energy threshold setting, or pattern recognition algorithms. A spatial domain filter is a mathematical tool or algorithm used to attenuate or eliminate specific frequency components in the spatial frequency spectrum. It can adopt notch filters, band-stop filters, Gaussian filters, Butterworth filters, etc., and its parameters are set according to the identified noise characteristic location and bandwidth.

[0038] Specifically, the above steps elaborate on how to filter the ultrasonic A-scan data sequence in step S2 to remove the periodic structural noise generated by the woven structure of the glass fiber base cloth, thereby effectively solving the problem of the difficulty in separating the high intensity structural noise and the low intensity characteristic signal, and laying the foundation for the subsequent accurate extraction of characteristic parameters related to interlayer peeling strength. Step S21 converts the ultrasonic A-scan data sequence into spatial domain data, and converts the spatial domain data into a spatial frequency spectrum based on a two-dimensional Fourier transform. In the time domain or spatial domain of the original ultrasonic A-scan data sequence, the noise generated by the periodic woven structure of the glass fiber base cloth is often mixed with the effective signal, making it difficult to directly separate. Through the two-dimensional Fourier transform, these periodic noise components can be represented as specific, concentrated frequency peaks in the frequency domain, making the identification and location of the noise clear and feasible. Step S22 analyzes the spatial frequency spectrum to identify the characteristic position and bandwidth of the periodic noise caused by the woven structure of the glass fiber base cloth, which is the core of ensuring the accuracy and effectiveness of the filtering. In the frequency spectrum, the periodic structural noise of the glass fiber base cloth will exhibit specific frequency characteristics. Through detailed analysis of the frequency spectrum, the center frequency (characteristic location) and frequency range (bandwidth) of these noise components can be determined. This highly accurate identification process avoids the loss of effective signals that may result from non-targeted filtering, ensuring that only the target noise is processed. Step S23, by designing and applying filters based on the noise's characteristics (location and bandwidth), can specifically suppress or eliminate the noise components in the frequency spectrum while retaining as much effective signal related to interlayer peel strength as possible, thereby obtaining a low-noise frequency spectrum that significantly removes structure-borne noise. Step S24, inverse Fourier transforming the filtered frequency spectrum into an ultrasonic signal, produces an ultrasonic signal that has removed or significantly attenuated the structural noise of the glass fiber base fabric weave. This low-noise ultrasonic signal provides high-quality data input for the subsequent steps to accurately extract the strength characteristic parameters related to interlayer peel strength, thereby improving the reliability and accuracy of the entire detection method.

[0039] Through the above-mentioned processing, the method of the present application effectively removes the periodic structural noise generated by the glass fiber base cloth woven structure in the PTFE membrane material, significantly reduces the aliasing between the structural noise and the acoustic characteristic signal characterizing the peel strength, and makes the extraction of characteristic parameters related to the peel strength from the ultrasonic echo signal more stable and accurate, thereby improving the accuracy of the interlayer peel strength evaluation of the PTFE membrane material.

[0040] In some preferred embodiments, step S22 includes: S221, identifying periodic components of the spatial frequency spectrum to obtain periodic frequency components with significant energy in the spatial frequency spectrum; S222. Based on the preset spatial frequency characteristics of the glass fiber base cloth woven structure, compare and screen periodic frequency components with significant energy to determine periodic frequency components in the spatial frequency spectrum that are consistent with the glass fiber base cloth woven structure; S223. Extract the center frequency and frequency range of the periodic frequency component that matches the woven structure of the glass fiber base cloth as the characteristic position and bandwidth, respectively.

[0041] Specifically, periodic component identification refers to identifying frequency components with repetitive or regular patterns from the spatial frequency spectrum. This can be achieved by performing peak detection on the frequency spectrum and identifying frequency points where energy is concentrated and has obvious periodicity, or by using methods such as autocorrelation analysis and wavelet transform to reveal the periodic characteristics of the signal. A periodic frequency component with significant energy refers to the energy intensity of the periodic frequency component in the spatial frequency spectrum, and its value is higher than a preset threshold or significantly higher than the background noise level. An absolute energy threshold can be set based on experience, or a relative threshold can be determined through statistical analysis for identification to ensure that the identified periodic component is sufficient to constitute interference with the target signal. The preset spatial frequency characteristics of the glass fiber base cloth woven structure refer to the specific frequency pattern or range of the glass fiber base cloth woven structure in the spatial frequency spectrum obtained through theoretical analysis, experimental measurement or historical data accumulation before actual detection. The frequency range can be determined based on the half-height width of the spectrum, the energy concentration or the preset spectrum shape model.

[0042] Specifically, the purpose of step S221 is to preliminarily screen out all periodic signals with sufficient energy that may constitute interference from the complex frequency spectrum. By focusing on components with high energy intensity, background noise or random fluctuations with low energy and little impact on subsequent analysis can be effectively excluded, thereby limiting the analysis scope to signals that are most likely to contain structural noise. After preliminarily screening out all periodic components with high energy intensity, step S222 introduces key prior knowledge, namely the preset spatial frequency characteristics of the glass fiber base cloth woven structure. In this stage, by comparing and screening the identified periodic frequency components with these preset characteristics, those frequency components that are periodic but not derived from the glass fiber base cloth woven structure can be excluded, thereby accurately locking and determining the periodic noise components that are actually generated by the glass fiber base cloth woven structure, greatly improving the accuracy and specificity of noise identification, avoiding misjudging other irrelevant periodic signals as structural noise, and ensuring the targetedness of subsequent filtering. Step S223 extracts the center frequency and frequency range of these components as the characteristic position and bandwidth respectively. These parameters are the basis for constructing spatial domain filters, which accurately define the position and width of the noise components that need to be attenuated or eliminated in the frequency spectrum.

[0043] Through the above processing, the method of the present application can accurately identify the characteristic position and bandwidth of the periodic noise caused by the glass fiber base cloth woven structure in the spatial frequency spectrum, effectively solving the problem that in practical applications, the spatial frequency spectrum may contain multiple periodic components and it is difficult to distinguish the noise actually coming from the glass fiber base cloth woven structure. This method avoids misjudging other irrelevant periodic components as target structure noise by introducing the preset spatial frequency characteristics of the glass fiber base cloth woven structure for comparison and screening, thereby ensuring that the filter constructed subsequently can accurately attenuate or eliminate the target structure noise, significantly improving the purity of the ultrasonic signal after removing the structural noise, and ensuring the accuracy of the subsequent intensity characteristic parameter extraction, thereby improving the reliability of the quantitative evaluation of the interlayer peeling strength of the PTFE membrane material.

[0044] In some preferred embodiments, the process of establishing the tension-ultrasonic parameter correlation relationship includes: A1. Under a controlled environment, apply a preset gradient of tension to the PTFE membrane sample and perform ultrasonic testing on the PTFE membrane sample to obtain the ultrasonic signal propagation parameters under different tension loads. A2. Establish a tension-ultrasonic parameter correlation relationship based on different tension loads and corresponding ultrasonic signal propagation parameters.

[0045] Specifically, a controlled environment refers to precisely controlling external conditions, such as temperature, humidity, and air pressure, to ensure that these environmental factors do not interfere with the ultrasonic propagation characteristics during the experiment, thereby enabling the acquired data to accurately reflect the intrinsic relationship between tension and ultrasonic parameters. A preset gradient tension load refers to a force applied to a membrane sample according to a pre-set, gradually changing sequence of tension values, used to simulate the behavior of the membrane under different stress states, thereby fully capturing the changing patterns of ultrasonic signal propagation parameters under various tensions. The tension-ultrasonic parameter correlation can be implemented using mathematical function models, polynomial fitting, lookup tables, neural network models, or machine learning algorithms.

[0046] Specifically, under these controlled conditions, a series of preset, gradually varying tensile loads are applied to the PTFE membrane sample. By applying gradient tension, the various stress states that the membrane may encounter in actual applications can be systematically simulated, thereby comprehensively capturing the variations in ultrasonic signal propagation parameters under varying tensions. While applying varying tensile loads, the membrane sample is ultrasonically inspected, and corresponding ultrasonic signal propagation parameters, such as sound velocity, interface reflection echo amplitude, or transit time, are acquired. These parameters are selected because they are sensitive to the stress state within the membrane and can directly reflect the effect of tension on ultrasonic propagation characteristics, providing critical raw data for establishing subsequent correlations. Subsequently, based on these ultrasonic signal propagation parameters acquired under varying tensile loads, a quantitative correlation between tension and ultrasonic parameters is established. This established correlation enables the system to accurately predict or calculate the deviation of the ultrasonic signal caused by tension changes based on local membrane tension information during actual inspections, thereby determining the required ultrasonic compensation. Through the accurate correlation relationship established by this scheme, the method of the present application can accurately calculate the ultrasonic compensation amount and effectively correct the deviation caused by tension in the ultrasonic signal, so that the compensated ultrasonic signal can more realistically reflect the interlayer peeling strength of the membrane material, thereby overcoming the problems in the existing technology of reduced comparability of ultrasonic signals and difficulty in stably extracting characteristic parameters due to tension unevenness, laying a solid foundation for the subsequent extraction of strength characteristic parameters and accurate evaluation of interlayer peeling strength.

[0047] More specifically, since the tension-ultrasonic parameter correlation relationship is obtained under a controlled environment, step S3 can further introduce environmental information to establish the tension-ultrasonic parameter correlation relationship, so that the tension applied to the membrane material is actually a quantitative correspondence between the environmental information and the tension and the characteristic parameters of ultrasonic wave propagation in the membrane material, so that step S3 can be transformed into: based on the pre-established tension-ultrasonic parameter correlation relationship, the ultrasonic compensation amount is calculated according to the local membrane material tension information and the current environmental information, and the ultrasonic signal is compensated according to the ultrasonic compensation amount.

[0048] In some preferred embodiments, the intensity characteristic parameters include one or more of the amplitude attenuation rate of the echo reflected from the interface between the PTFE coating and the base fabric, echo waveform broadening, energy distribution change, and ratio of target frequency components.

[0049] Specifically, the target frequency component is a frequency component related to the peeling strength between the interface layer of the PTFE coating and the base fabric.

[0050] More specifically, the amplitude attenuation rate refers to the degree of energy loss in the ultrasonic echo reflected at the interface between the PTFE coating and the base fabric. Echo waveform broadening refers to the increase in the duration or characteristic width of the reflected echo signal in the time domain, which can be characterized by the half-width (FWHM) of the echo signal, the envelope duration, or the waveform width under a preset threshold. Energy distribution change refers to the change in the energy proportion or spectral shape of the reflected echo signal in different frequency bands, which can be quantified using parameters such as the center of gravity of the spectrum, the root mean square frequency, the energy ratio of a preset frequency band, or the spectrum entropy. The ratio of target frequency components refers to the relative relationship in energy or amplitude between frequency components associated with the peel strength between the interface layers of the PTFE coating and the base fabric, and can be calculated using the energy ratio or amplitude ratio between two or more characteristic frequency peaks associated with peeling.

[0051] Specifically, in actual testing, the periodic weaving structure of the glass fiber base cloth will generate structural noise, and the uneven tension of the membrane material will introduce the acoustic elastic effect. These factors make it challenging to stably extract the characteristic parameters related to peeling strength from the echo signal. This solution first removes the structural noise by filtering the ultrasonic signal and compensates the signal according to the local membrane tension information, thereby eliminating the main interference factors. On this basis, the intensity characteristic parameters can be extracted. The amplitude attenuation rate reflects the energy loss caused by poor interface bonding; the broadening of the echo waveform reveals the ultrasonic diffusion caused by interface defects; the change in energy distribution reveals the microscopic mechanism of interface damage, such as the sensitivity of specific frequency components to peeling; the ratio of target frequency components enhances the recognition ability and reduces the interference of irrelevant frequency components by focusing on the frequency components associated with peeling strength. The combined use of these parameters can capture the changes in ultrasonic signals caused by peeling between PTFE membrane layers from multiple angles, providing a basis for evaluation.

[0052] In some preferred embodiments, the intensity characteristic parameters include the amplitude attenuation rate of the echo reflected from the interface between the PTFE coating and the base fabric, the echo waveform broadening, the energy distribution change, and the ratio of the target frequency components. Step S4 includes: S41, identifying and isolating the reflected echo from the interface between the PTFE coating and the base fabric from the compensated ultrasonic signal; S42, calculating the ratio of the amplitude of the reflected echo to the preset reference amplitude to obtain the amplitude attenuation rate; S43. Calculate the waveform duration or characteristic width of the reflected echo according to the waveform of the isolated reflected echo to obtain the echo waveform broadening; S44, performing frequency domain conversion on the reflected echo, and analyzing energy distribution of different frequency segments in the frequency domain conversion result to obtain energy distribution changes; S45. Calculate the energy ratio between the target frequency components in the frequency domain conversion result to obtain the ratio of the target frequency components; S46. The amplitude attenuation rate, the echo waveform broadening, the energy distribution change, and the ratio of the target frequency components are used as intensity characteristic parameters.

[0053] Specifically, after acquiring an ultrasonic A-scan data sequence and removing the noise from the periodic spatial frequency components generated by the glass fiber base fabric's woven structure, the ultrasonic signal is compensated based on local membrane tension information. This results in a pure and calibrated ultrasonic signal, laying the foundation for accurate feature parameter extraction. First, the reflected echo from the PTFE coating-base fabric interface is identified and isolated from the compensated ultrasonic signal. This step serves as the starting point for all subsequent parameter calculations, ensuring that the data source for analysis is directly related to interfacial debonding. Next, by calculating the ratio of the amplitude of the isolated reflected echo to a preset reference amplitude, the degree of ultrasonic energy loss or attenuation at the interface is quantified. The amplitude attenuation rate directly reflects the tightness of the interfacial bond; poorer bonding generally results in greater attenuation, providing a quantifiable indicator of debonding strength. Furthermore, the waveform duration or characteristic width of the isolated reflected echo is calculated based on its waveform. This captures waveform distortion caused by debonding or defects during ultrasonic propagation at the interface. Waveform broadening may indicate scattering or multipath propagation of the ultrasonic wave at an inhomogeneous interface, and this waveform variation provides another dimension of information about the degree of debonding. Furthermore, by performing frequency domain conversion on the reflected echo and analyzing the energy distribution of different frequency bands in the frequency domain conversion results, the effect of interface peeling on the ultrasonic frequency components can be revealed. Peeling or defects may cause the attenuation or enhancement of certain frequency components, thereby causing changes in the energy distribution. This characteristic change in the frequency domain is a sensitive indicator for assessing the health of the interface. On this basis, calculating the energy ratio between the target frequency components in the frequency domain conversion results can more focusedly extract features that are highly correlated with the degree of peeling. This ratio analysis can effectively amplify the specific frequency response caused by peeling and provide a more targeted quantitative indicator. Ultimately, the amplitude attenuation rate, echo waveform broadening, energy distribution change and the ratio of the target frequency components are combined as intensity characteristic parameters to form a multi-dimensional evaluation system. This comprehensive parameter set can comprehensively reflect the peeling condition between PTFE membrane layers from different angles, improve the accuracy and robustness of the evaluation, and avoid the limitations that may exist in a single parameter.

[0054] In some preferred embodiments, step S41 includes: S411, determining an expected arrival time range of the reflected echo at the interface between the PTFE coating and the base fabric based on the thickness information of the PTFE coating and the propagation speed of the ultrasonic wave in the PTFE coating; S412. Within the expected arrival time range, identify the echo signal with the maximum amplitude in the compensated ultrasonic signal, regard the echo signal as the echo reflected from the interface between the PTFE coating and the base fabric, and isolate it.

[0055] Specifically, the thickness information of the PTFE coating is the geometric dimension data of the coating part of the PTFE membrane material, which can be obtained from the manufacturing specifications of the membrane material, or measured on-site by non-contact measuring equipment, or inversely calculated by combining the transit time of the ultrasonic wave itself in the coating with the known sound speed. The propagation speed of ultrasonic waves in the PTFE coating is an inherent physical parameter of the propagation of ultrasonic waves in the PTFE material, and its value depends on the density, elastic modulus and other properties of the PTFE material. The speed can be calibrated in advance by measuring the ultrasonic transit time of a standard PTFE sample, or obtained by consulting the relevant material acoustic database. The expected arrival time range is a time interval calculated based on the thickness information of the PTFE coating and the propagation speed of ultrasonic waves in the PTFE coating, indicating the time window in which the reflected echo from the interface between the PTFE coating and the base fabric may appear. The determination of this range is usually based on the theoretical time for the round-trip propagation of ultrasonic waves, and a certain margin is taken into account to cope with minor deviations in actual measurements. Isolation refers to extracting the identified target echo signal from the complete ultrasonic signal to make it independent of other non-target signals. This can be achieved through a variety of signal processing techniques, such as applying a time window function to intercept the target echo, or copying the target echo data into a new data structure for subsequent independent analysis and calculation.

[0056] Specifically, step S411 uses the known physical properties of the PTFE coating to predict the time of appearance of the target echo. By combining information about the PTFE coating's thickness and the propagation speed of ultrasound within the PTFE coating, it calculates the theoretical time required for the ultrasound to originate from the probe, pass through the PTFE coating, reflect at the interface between the PTFE coating and the base fabric, and return to the probe. Based on this theoretical time, a reasonable expected arrival time range with minimal error is set. This predictive mechanism significantly narrows the search space for the target echo, effectively eliminating interference from other irrelevant or interfering echoes on the time axis, laying the foundation for subsequent accurate identification. Within this precise time window, step S412 further locates the target echo by identifying the echo with the maximum amplitude within the compensated ultrasonic signal. At the interface between the PTFE coating and the base fabric, a significant reflected echo is typically generated due to differences in acoustic impedance. By searching for the echo with the largest amplitude within the determined expected arrival time range, the reflected signal that best represents the state of the interface can be effectively captured. This method can identify the strongest acoustic response at that interface, even in the presence of minor delamination or defects. Once the maximum amplitude echo signal is identified, it is isolated. This isolation ensures that the subsequent calculation of intensity characteristic parameters is based only on the target signal directly related to the interlayer peeling strength, thus avoiding interference from other noise or non-target echoes on the evaluation results.

[0057] Through the above processing, the method of the present application can accurately identify and effectively isolate the reflected echo from the interface between the PTFE coating and the base fabric. Even when the internal structure of the membrane material is complex, there are other interfering signals or weak effective echoes, it can ensure the accurate capture of the target echo, avoid the interference of non-target signals on the subsequent calculation of intensity characteristic parameters, and significantly improve the accuracy of intensity characteristic parameters such as amplitude attenuation rate, echo waveform broadening, energy distribution change, and target frequency component ratio.

[0058] In some preferred embodiments, the quantitative relationship includes a nonlinear mapping function, which is a pre-established transformation function of the weighted characteristic parameter and the interlayer peeling strength. Step S5 includes: S51. Based on preset parameter weights, weight different parameters of the intensity characteristic parameters of different measurement points in the area to be measured to obtain weighted characteristic parameters of the different measurement points in the area to be measured; S52, mapping the weighted characteristic parameter to interlayer peeling strength based on a nonlinear mapping function; S53 , generating interlayer peeling strength distribution data of the area to be measured according to the interlayer peeling strengths at different measuring points in the area to be measured.

[0059] Specifically, a nonlinear mapping function refers to a mathematical function that can capture the complex nonlinear relationship between input and output, which can be implemented using nonlinear models such as polynomial functions, exponential functions, logarithmic functions, neural network models, or support vector machines.

[0060] Specifically, step S51 weights the various strength characteristic parameters obtained at different measurement points according to preset parameter weights to obtain weighted characteristic parameters. This weighted characteristic parameter can more comprehensively and accurately reflect the actual peeling state of the film material, providing a more representative input for subsequent quantification. Subsequently, step S52 uses a pre-established nonlinear mapping function to map these weighted characteristic parameters into specific interlayer peel strength values, effectively resolving the complex nonlinear relationship that may exist between the strength characteristic parameters and the interlayer peel strength. The nonlinear model can more accurately capture this complex relationship, avoiding the errors caused by traditional linear quantification and significantly improving the accuracy and reliability of the quantification results. Step S53 integrates the interlayer peel strength data obtained at different measurement points in the test area to generate interlayer peel strength distribution data for the entire test area.

[0061] Through the above processing, the method of the present application can optimize the combination of different types of strength characteristic parameters by introducing parameter weights, so that it can more accurately reflect the interlayer peeling state of the film material. By adopting a nonlinear mapping function, it can accurately capture the complex relationship between the strength characteristic parameters and the actual interlayer peeling strength, avoiding the errors caused by traditional linear quantification.

[0062] In some preferred embodiments, step S53 includes: S531, generating a continuous interlayer peeling strength field of the area to be measured based on the interlayer peeling strengths of different measuring points in the area to be measured using a spatial interpolation method; S532 : Generate an interlayer peeling strength distribution diagram of the area to be measured as interlayer peeling strength distribution data according to the continuous interlayer peeling strength field.

[0063] Specifically, the spatial interpolation method refers to a geographic spatial data processing technology that estimates the values ​​of unknown points based on the values ​​of known discrete points. It can be implemented using the inverse distance weighted method, Kriging method, spline interpolation method, or natural neighbor interpolation method. The continuous interlayer peeling strength field refers to a mathematical model or data representation in which the interlayer peeling strength in the area to be measured presents a continuous change in space, in which the strength value of any point can be estimated or calculated. It can be represented in the form of grid data, raster data, or contour data. The interlayer peeling strength distribution map refers to a graphical presentation of the continuous interlayer peeling strength field, which intuitively displays the spatial distribution characteristics of the interlayer peeling strength in the area to be measured. It can be generated in the form of a heat map, contour map, or color-coded map.

[0064] Specifically, step S531 generates a continuous interlayer peel strength field for the test area based on the interlayer peel strength at different measurement points within the test area using a spatial interpolation method. This spatial interpolation method allows for a reasonable estimation and infilling of strength values ​​for unmeasured areas based on limited discrete measurement point data, thereby overcoming the potential for discontinuous and incomplete information from relying solely on discrete data and providing a comprehensive, seamless understanding of the interlayer peel strength across the entire test area. The continuous interlayer peel strength field generated in this manner provides a solid foundation for subsequent analysis and visualization. Building on this foundation, step S532 uses the continuous intensity field as input to create a precise and intuitive distribution map, clearly demonstrating the interlayer peel strength trends and distribution characteristics across different regions of the membrane surface. This visualization significantly improves the efficiency and accuracy of data interpretation, enabling maintenance personnel to quickly identify potential weak areas or peeling risk points. This approach, combined with the previous step of acquiring precise discrete data, transforms previously discrete and difficult-to-assess comprehensive data into a continuous, intuitive, and easily understood holistic view through spatial interpolation and visualization, thereby enhancing the ability to reliably and quantitatively assess membrane health and provide early warnings.

[0065] Second, please refer to Figure 2 Some embodiments of the present application further provide a PTFE membrane interlayer peeling strength detection system for quantitatively evaluating the interlayer peeling strength of an in-service PTFE membrane structure. The system comprises: An acquisition module 201 is configured to acquire an ultrasonic A-scan data sequence of a region to be measured in the PTFE membrane and local membrane tension information of the region to be measured, wherein the ultrasonic A-scan data sequence covers at least several weaving cycles of the glass fiber base cloth; Ultrasonic extraction module 202, configured to filter the periodic spatial frequency components generated by the glass fiber base cloth woven structure according to the ultrasonic A-scan data sequence to obtain an ultrasonic signal; The ultrasonic compensation module 203 is configured to calculate an ultrasonic compensation amount based on the pre-established tension-ultrasonic parameter correlation relationship and the local film material tension information, and compensate the ultrasonic signal according to the ultrasonic compensation amount; A feature extraction module 204 is used to extract strength feature parameters related to interlayer peeling strength based on the compensated ultrasonic signal; The quantification module 205 is configured to quantify the intensity characteristic parameters into interlayer peeling intensity distribution data of the area to be measured based on a preset quantization relationship.

[0066] The system of the present application combines the structural noise filtering processing of the ultrasonic A-scan data sequence with the acoustic elastic effect compensation of the local membrane tension information in a series manner, thereby solving the problem of the overlapping of the structural noise generated by the glass fiber base cloth woven structure and the peel strength characteristic signal, as well as the problem of the acoustic elastic effect introduced by the uneven tension of the membrane material in the service state, which leads to a reduction in the comparability of the ultrasonic signal, thereby achieving the effect of quantitative evaluation of the peel strength between PTFE membrane layers.

[0067] In addition, the units described as separate components may or may not be physically separate, and 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0068] Furthermore, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0069] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0070] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for testing the peel strength between layers of PTFE membranes, used for quantitatively evaluating the peel strength between layers of membranes in an in-service PTFE membrane structure, characterized in that: The method comprises the following steps: S1. Acquire an ultrasonic A-scan data sequence of a region to be measured in a PTFE membrane and local membrane tension information of the region to be measured, wherein the ultrasonic A-scan data sequence covers at least several weaving cycles of the glass fiber base cloth; S2. Filtering the periodic spatial frequency components generated by the glass fiber base cloth woven structure according to the ultrasonic A-scan data sequence to obtain an ultrasonic signal; S3. Based on a pre-established tension-ultrasonic parameter correlation relationship, calculate an ultrasonic compensation amount according to the local film material tension information, and compensate the ultrasonic signal according to the ultrasonic compensation amount; S4. extracting strength characteristic parameters related to interlayer peeling strength based on the compensated ultrasonic signal; S5. Based on a preset quantitative relationship, quantify the strength characteristic parameter into interlayer peeling strength distribution data of the area to be measured.

2. The PTFE membrane interlayer peeling strength detection method according to claim 1, wherein Step S1 includes: S11, scanning the area to be measured along a preset scanning path using an ultrasonic probe to obtain the ultrasonic A-scan data sequence, and simultaneously collecting the vibration frequency using a laser displacement sensor; S12. Mapping the vibration frequency to the local film material tension information according to a preset mapping relationship.

3. The PTFE membrane interlayer peeling strength detection method according to claim 1, wherein Step S2 includes: S21, converting the ultrasonic A-scan data sequence into spatial domain data, and converting the spatial domain data into a spatial frequency spectrum; S22, analyzing the spatial frequency spectrum to identify characteristic positions and bandwidths of periodic noise caused by the woven structure of the glass fiber base cloth; S23, constructing a spatial domain filter based on the characteristic position and bandwidth, and using the spatial domain filter to attenuate or eliminate periodic frequency components related to the woven structure of the glass fiber base cloth in the spatial frequency spectrum to obtain a filtered spatial frequency spectrum; S24. Inversely convert the filtered frequency spectrum into the ultrasonic signal.

4. The PTFE membrane interlayer peeling strength detection method according to claim 3, wherein: Step S22 includes: S221. Identify periodic components of the spatial frequency spectrum to obtain periodic frequency components with significant energy in the spatial frequency spectrum; S222. Based on the preset spatial frequency characteristics of the glass fiber base cloth woven structure, compare and screen the periodic frequency components with significant energy to determine the periodic frequency components in the spatial frequency spectrum that are consistent with the glass fiber base cloth woven structure; S223 , extracting the center frequency and frequency range of the periodic frequency component consistent with the woven structure of the glass fiber base cloth as the characteristic position and the bandwidth, respectively.

5. The method for detecting the peeling strength between layers of PTFE membrane material according to claim 1, wherein: The intensity characteristic parameters include one or more of the amplitude attenuation rate of the echo reflected from the interface between the PTFE coating and the base fabric, echo waveform broadening, energy distribution change, and ratio of target frequency components.

6. The method for detecting the interlayer peeling strength of PTFE membranes according to claim 5, wherein: The intensity characteristic parameters include the amplitude attenuation rate of the echo reflected from the interface between the PTFE coating and the base fabric, the echo waveform broadening, the energy distribution change, and the ratio of the target frequency components. Step S4 includes: S41, identifying and isolating the reflected echo from the interface between the PTFE coating and the base fabric from the compensated ultrasonic signal; S42, calculating the ratio of the amplitude of the reflected echo to a preset reference amplitude to obtain the amplitude attenuation rate; S43, calculating the waveform duration or characteristic width of the reflected echo according to the waveform of the isolated reflected echo to obtain the echo waveform broadening; S44, performing frequency domain conversion on the reflected echo, and analyzing energy distribution of different frequency segments in the frequency domain conversion result to obtain the energy distribution change; S45. Calculating the energy ratio between the target frequency components in the frequency domain conversion result to obtain the ratio of the target frequency components; S46. Taking the amplitude attenuation rate, the echo waveform broadening, the energy distribution change, and the ratio of the target frequency component as the intensity characteristic parameters.

7. The method for detecting the interlayer peeling strength of a PTFE membrane according to claim 6, wherein: Step S41 includes: S411, determining an expected arrival time range of the reflected echo at the interface between the PTFE coating and the base fabric based on the thickness information of the PTFE coating and the propagation speed of the ultrasonic wave in the PTFE coating; S412: Within the expected arrival time range, identify the echo signal with the maximum amplitude in the compensated ultrasonic signal, use the echo signal as the echo reflected from the interface between the PTFE coating and the base fabric, and isolate the echo signal.

8. The method for detecting the interlayer peeling strength of PTFE membranes according to claim 1, wherein: The quantitative relationship includes a nonlinear mapping function, which is a pre-established transformation function of the weighted characteristic parameter and the interlayer peeling strength. Step S5 includes: S51. Weighting different parameters of the intensity characteristic parameters of different measurement points in the area to be measured based on preset parameter weights to obtain weighted characteristic parameters of the different measurement points in the area to be measured; S52, mapping the weighted characteristic parameter to interlayer peeling strength based on the nonlinear mapping function; S53 , generating interlayer peeling strength distribution data of the area to be measured according to the interlayer peeling strengths at different measuring points in the area to be measured.

9. The method for detecting the interlayer peeling strength of PTFE membranes according to claim 8, wherein: Step S53 includes: S531, generating a continuous interlayer peeling strength field of the area to be measured based on the interlayer peeling strengths of different measuring points in the area to be measured using a spatial interpolation method; S532 : Generate an interlayer peeling strength distribution diagram of the area to be measured as the interlayer peeling strength distribution data according to the continuous interlayer peeling strength field.

10. A PTFE membrane interlayer peeling strength detection system for quantitatively evaluating the interlayer peeling strength of an in-service PTFE membrane structure, characterized in that: The system comprises: an acquisition module, configured to acquire an ultrasonic A-scan data sequence of a region to be measured in the PTFE membrane material and local membrane material tension information of the region to be measured, wherein the ultrasonic A-scan data sequence covers at least several weaving cycles of the glass fiber base cloth; an ultrasonic extraction module for filtering the periodic spatial frequency components generated by the glass fiber base cloth woven structure according to the ultrasonic A-scan data sequence to obtain an ultrasonic signal; an ultrasonic compensation module, configured to calculate an ultrasonic compensation amount according to the local film material tension information based on a pre-established tension-ultrasonic parameter correlation relationship, and compensate the ultrasonic signal according to the ultrasonic compensation amount; A feature extraction module is used to extract strength feature parameters related to interlayer peeling strength based on the compensated ultrasonic signal; The quantification module is used to quantify the strength characteristic parameters into interlayer peeling strength distribution data of the area to be measured based on a preset quantization relationship.

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