A method and device for detecting damage to the bonding interface of a wind turbine blade, and a storage medium

Abstract

The present invention belongs to the technical field of damage detection, in particular to a method and device for detecting damage to the bonded interface of a wind turbine blade and a storage medium. The method for detecting damage to the bonded interface of a wind turbine blade includes: S1. A pulsed excitation ultrasonic probe generates ultrasonic waves, and the ultrasonic waves act on the wind turbine blade; S2. The ultrasonic probe receives the echo signal of the wind turbine blade; S3. After filtering and amplifying the echo signal, the filtered and amplified echo signal is processed to obtain sub-harmonics; S4. Fourier transform is performed on the sub-harmonics, and imaging is performed on the transformed sub-harmonics; S5. The bonded interface damage is detected by using the imaging signal. The present invention has the advantages of fast detection speed, high reliability, and being unaffected by the nonlinear interference of experimental instruments, and is sensitive to minor damage and has little impact on testing equipment.

Description

Technical Field

[0001] The present invention belongs to the technical field of damage detection, and particularly relates to a method and device for detecting damage to the bonding interface of a wind turbine blade, and a storage medium. Background Art

[0002] Wind power generation is an important part of renewable energy. In order to improve the structural stiffness of wind turbine blades, prevent local buckling, and enhance the load-bearing capacity of the entire blade, sandwich structures are usually used in the leading edge, trailing edge, shear ribs, and other parts of wind turbine blades. Therefore, the sandwich composite structure is one of the key materials in wind turbine blades.

[0003] The sandwich structure usually consists of upper and lower skins (surface layers) with high strength and thin thickness, and a relatively thick and light core material. Due to the complexity inside the sandwich structure, improper connection operations may lead to phenomena such as debonding, wrinkling, internal cracking of the skin, or inclusion of the core material between the skin and the core during use or processing. Among them, the debonding defect between the core layer and the skin is the most common defect in sandwich composites.

[0004] To connect the upper and lower skins and the core material, sandwich panels usually adopt a bonding process, and adhesive bonding is the most commonly used connection method. However, in the complex service environment of the blade, the debonding of the adhesive layer will cause serious separation between the skin and the core material, thereby reducing the load-bearing capacity of the sandwich composite. Due to the complexity inside the sandwich structure, manual judgment of debonding defects is often unreliable because debonding defects usually present as small areas, non-continuity, and strong concealment. Therefore, it is crucial to detect defects as early as possible and perform repairs to avoid more serious failure problems.

[0005] Detecting the damage that occurs at the bonding interface of the sandwich composite structure can timely detect the defects in the interface adhesive layer. Common detection methods in the prior art include ultrasonic detection, X-ray detection, etc. The X-ray detection method uses the difference in the intensity of the transmitted rays in a local area and the surrounding area to judge whether the contact layer is good, but it has the disadvantages of a bulky host, difficult placement, and serious radiation. The ultrasonic detection method mainly uses the linear characteristics such as reflection, scattering, and mode conversion of ultrasonic waves when passing through damage, and can well detect larger damages such as cracks and corrosion, but it is difficult to detect tiny damages.

[0006] The invention patent with Chinese Patent Publication No. CN107655979A discloses a non-destructive testing method for the trailing edge bonding area of a wind turbine blade, which includes the following steps: First, measure the width of the adhesive in the trailing edge bonding area. Use a trailing edge scanning tooling, place a pair of probes on the upper and lower sides of the trailing edge bonding area of the blade, gradually increase the gain of the ultrasonic flaw detector until the signal height reaches 80% of the full screen; move the two probes coaxially and synchronously; when the position where the signal height drops by 12 dB, this position is the edge position of the trailing edge bonding area of the wind turbine blade; then, detect the defects in the adhesive layer of the trailing edge bonding area, move the two probes coaxially and synchronously, and control the scanning speed within 150 mm / s; when the position where the signal height drops by 12 dB, this position is the defective area of the adhesive layer in the trailing edge bonding area of the wind turbine blade. This non-destructive testing method uses the transmission method for detection and can achieve 100% non-destructive testing of the trailing edge bonding area of non-parallel wind turbine blades.

[0007] However, the above-mentioned existing technology uses traditional ultrasonic methods for detection, and it is impossible to detect minor damages (such as damages at the 100 nm level) at the bonding interface, and the detection sensitivity is limited. Summary of the Invention

[0008] To solve the technical problems existing in the above-mentioned existing technology, the present invention provides a method and device for detecting damages at the bonding interface of wind turbine blades and a storage medium.

[0009] To achieve the above purpose, the technical solution of the present invention is as follows:

[0010] In the first aspect, the present invention provides a method for detecting damages at the bonding interface of wind turbine blades, including:

[0011] S1. Pulse-excite an ultrasonic probe to generate ultrasonic waves, and the ultrasonic waves act on the wind turbine blade;

[0012] S2. The ultrasonic probe receives the echo signal of the wind turbine blade;

[0013] S3. After filtering and amplifying the echo signal, process the filtered and amplified echo signal to obtain sub-harmonics;

[0014] S4. Perform Fourier transform on the sub-harmonics and image the transformed sub-harmonics;

[0015] S5. Use the imaging signal to detect damages at the bonding interface.

[0016] Further, the center frequency of the ultrasonic probe is 10 MHz - 20 MHz.

[0017] Further, the filtering in step S3 is: filtering out frequencies above 20 MHz.

[0018] Further, in step S3, the echo signal after filtering and amplification is processed to obtain a sub-harmonic. The specific method is as follows:

[0019] Let be the sub-harmonic envelope signal, be the measured ultrasonic echo signal. Using the measured ultrasonic echo signal, the ultrasonic echo signal with a certain value of the conditional probability density function;

[0020] Using the conditional probability density function and the prior probability distribution of the sub-harmonic envelope signal to obtain the probability density function of the sub-harmonic envelope signal ;

[0021] Based on the probability density function of the sub-harmonic envelope signal to obtain the maximum a posteriori estimate value of the sub-harmonic envelope signal ;

[0022] Use the fundamental frequency echo to estimate the autocorrelation function of the sub-harmonic echo;

[0023] Use the autocorrelation function of the sub-harmonic echo to reconstruct the sub-harmonic signal.

[0024] Furthermore, the ultrasonic echo signal with a certain value of the conditional probability density function is:

[0025]

[0026] where is the standard deviation of the noise , is the probability normalization constant, C is n the identity matrix of order, whose diagonal elements are composed of the discretized sub-harmonic carrier signal, n represents the number of samples per unit time, represents the transpose of.

[0027] Furthermore, h the prior probability distribution of is:

[0028]

[0029] where is the probability normalization constant, is h the mean value of, is h the covariance matrix of, is the matrix The inverse matrix of is the transpose of

[0030] Furthermore, h the probability density function of

[0031]

[0032] Furthermore, based on h the probability density function of h the maximum a posteriori estimate value of

[0033] is obtained as follows: h Take the derivative of the logarithm in the probability density function of h and set the derivative formula to zero to obtain

[0034] .

[0035] Furthermore, using the fundamental frequency echo, estimate the autocorrelation function of the subharmonic echo, specifically including:

[0036] Calculate the empirical autocorrelation function of the fundamental frequency echo according to the fundamental frequency echo envelope signal;

[0037] Perform Gaussian function fitting on the empirical autocorrelation function of the fundamental frequency echo to obtain the smoothed autocorrelation function model of the fundamental frequency echo;

[0038] Calculate the standard deviation of the autocorrelation function of the subharmonic echo to obtain the autocorrelation function of the subharmonic echo.

[0039] Furthermore, set the fundamental frequency echo envelope signal as , and the empirical autocorrelation function of the fundamental frequency echo is:

[0040]

[0041] where represents the time lag, , and represents the empirical autocorrelation function of the fundamental frequency echo envelope signal , represents the fundamental frequency echo envelope signal at time

[0042] Furthermore, the smoothed autocorrelation function model of the fundamental frequency echo is:

[0043]

[0044] is the fitted Gaussian standard deviation, represents the Gaussian form of the empirical autocorrelation function of the fundamental frequency echo envelope signal .

[0045] Furthermore, the standard deviation of the autocorrelation function of the subharmonic echo is:

[0046]

[0047] Furthermore, the autocorrelation function of the subharmonic echo is:

[0048]

[0049] The smoothed autocorrelation function model of the subharmonic is:

[0050]

[0051] where represents the signal sampling points , each data group formed of the autocorrelation function of the subharmonic echo, represents the smoothed autocorrelation function of the subharmonic.

[0052] Furthermore, using the autocorrelation function of the subharmonic echo to reconstruct the subharmonic signal, the specific method is:

[0053] Construct a diagonal matrix P , based on the diagonal matrix P , the autocorrelation function of the subharmonic echo, and h the maximum a posteriori estimate value to reconstruct the subharmonic signal.

[0054] Furthermore, the diagonal matrix P is:

[0055]

[0056] where P is a 100x100 matrix, the first 50 elements of its diagonal elements are: 0.1, 0.12, 0.14,..., 1; the last 50 elements of its diagonal elements are: 0.985, 0.97, 0.955,..., 0.25; the matrix P All elements except the first 50 elements and the last 50 elements of the diagonal elements are zero.

[0057] Furthermore, the construction method of the diagonal matrix P is:

[0058] Obtain sub - harmonic amplitude distribution data: Through experiments, measure the peak amplitudes of sub - harmonic signals at different propagation distances;

[0059] Curve fitting: Use polynomials to fit the amplitude - distance data;

[0060] Normalization: Normalize the maximum value of the fitted curve to 1;

[0061] Distance - time conversion: According to the sound speed, convert the propagation distance to time and map the time to the signal sampling point sequence number n , , where, is the sampling frequency;

[0062] Construct a diagonal matrix : The matrix dimension is N×N, where N is the number of signal sampling points; the values of the diagonal elements of the diagonal matrix are the normalized values of the peak amplitudes corresponding to the signal sampling point sequence number n, and the elements other than the diagonal elements are all zero.

[0063] Furthermore, the reconstructed sub - harmonic signal is:

[0064] .

[0065] In a second aspect, the present invention also provides a device for detecting damage to the bonded interface of a wind turbine blade, including an ultrasonic probe and a flaw detector. The flaw detector includes a host computer, a main control chip, a pulse emission circuit, a pulse reception circuit, an operational amplifier circuit, and an acquisition circuit; the pulse emission circuit and the pulse reception circuit are both communicatively connected to the ultrasonic probe; the ultrasonic probe is disposed on the surface of the object to be tested;

[0066] The host computer is communicatively connected to the main control chip. The main control chip controls the pulse emission circuit to emit pulses, thereby exciting the ultrasonic probe to generate ultrasonic waves; the echo signals received by the ultrasonic probe are sequentially returned to the main control chip through the pulse reception circuit, the operational amplifier circuit, and the acquisition circuit;

[0067] The main control chip processes the echo signals using the above - mentioned method for detecting damage to the bonded interface of a wind turbine blade to obtain a sub - harmonic signal imaging diagram, and the host computer is used to display the sub - harmonic signal imaging diagram.

[0068] In a third aspect, the present invention also provides a computer - readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the above - mentioned method for detecting damage to the bonded interface of a wind turbine blade.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] The present invention extracts sub-harmonic signals from ultrasonic signals and uses the sub-harmonic signals to detect the damage of the bonding interface, which has the advantages of fast detection speed, high reliability, and being not affected by the non-linear interference of experimental instruments. Moreover, it is sensitive to slight damage and has little influence on the testing equipment.

[0071] In addition, the amplitude of the sub-harmonic signal obtained by the present invention is not easily submerged by noise, thereby improving the detection ability under noise interference. Description of the Drawings

[0072] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art.

[0073] Figure 1 It is the block diagram of the device connection in the embodiment of the present invention.

[0074] Description of the Reference Numerals in the Drawings:

[0075] 1. Leading edge of the wind turbine blade, 2. Substrate of the wind turbine blade, 3. Core of the wind turbine blade, 4. Trailing edge of the wind turbine blade, 5. Ultrasonic probe, 6. Wind turbine blade. Detailed Embodiments

[0076] The following will clearly describe the technical solutions of the present invention in conjunction with the drawings. Obviously, the described embodiments are not all the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0077] It should be noted that, unless otherwise specifically stated, the relative arrangements of the components and steps described in these embodiments and the numerical expressions should not be construed as limiting the scope of the present invention.

[0078] The following description of the exemplary embodiments is merely illustrative and in no way restricts the present invention and its application or use. The techniques, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail here, but when applicable, these techniques, methods, and devices should be regarded as part of this specification.

[0079] It should be noted that the terms used herein are only for describing the specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless otherwise clearly specified in the context, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "include" and / or "comprise" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or their combinations.

[0080] For the convenience of description, in the present invention, if the words "upper", "lower", "left", and "right" appear, they only indicate consistency with the upper, lower, left, and right directions of the accompanying drawings themselves, and do not limit the structure. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0081] Term Explanation Section: Terms such as "installation", "connection", "connection", and "fixation" in the present invention should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection, an electrical connection, a direct connection, or an indirect connection through an intermediate medium, and it can be an internal connection between two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0082] Embodiment 1

[0083] This embodiment provides a method for detecting damage to the bonding interface of a wind turbine blade, including:

[0084] S1. A pulsed excitation ultrasonic probe generates ultrasonic waves, and the ultrasonic waves act on the wind turbine blade;

[0085] S2. The ultrasonic probe receives the echo signal of the wind turbine blade;

[0086] S3. After filtering and amplifying the echo signal, the filtered and amplified echo signal is processed to obtain sub-harmonics to improve the signal-to-noise ratio of the echo signal;

[0087] S4. Perform Fourier transform on the sub-harmonics and image the transformed sub-harmonics;

[0088] S5. Use the imaging signal to detect damage to the bonding interface.

[0089] Under the action of ultrasonic excitation (with a fundamental frequency of ), if there are defects (such as cracks, delaminations, debondings, etc.) at the bonding interface of the wind turbine blade, it will cause significant nonlinear effects when ultrasonic waves propagate through the defects, transferring from the fundamental frequency to the sub-harmonic frequency and thus exciting and radiating Sub-harmonic signals. The sub-harmonic resonance method has the advantages of fast detection speed, high reliability, and being unaffected by the non-linearity interference of experimental instruments. Sub-harmonic ultrasonic resonance can avoid the interference of some non-destructive phenomena such as the inherent non-linearity of materials; in addition, the amplitude of the sub-harmonic obtained by this method is not easily submerged by noise, thus improving the detection ability under noise interference. Therefore, in this embodiment, the damage of the adhesive interface of the wind turbine blade is detected based on the sub-harmonic signal, and the detection accuracy is high.

[0090] Among them, the center frequency of the ultrasonic probe is 10 MHz - 20 MHz, preferably 15 MHz.

[0091] The filtering in step S3 is: filtering out the frequencies above 20 MHz, specifically using a 20 MHz low-pass filter. After filtering, the echo signal is amplified by an operational amplifier circuit.

[0092] In step S3, the echo signal after filtering and amplification is processed to obtain sub-harmonics. The specific method is:

[0093] Let be the sub-harmonic envelope signal, be the measured ultrasonic echo signal, be the noise in the measured ultrasonic echo signal, then there is:

[0094]

[0095] Among them, the matrix C is a diagonal matrix, and its diagonal elements are composed of the discretized sub-harmonic carrier signal, that is, the sampling frequency = 100 MHz, the sampling interval is 0.1 s, the initial phase is 0, then:

[0096]

[0097] = 5 MHz, which is the sub-harmonic center frequency; represents the diagonal element in the matrix , represents the sampling time.

[0098] According to the sampling time series (t1 = 0, t2 = 10, t3 = 20,... t n , in microseconds, n represents the total number of sampling points of the signal) to generate a discrete sub-harmonic carrier signal, place the carrier samples on the diagonal to form a diagonal matrix C , and the other elements of the diagonal matrix C except the diagonal are 0:

[0099]

[0100] 、 、 All are dimensional vectors, C is order matrix, where represents the number of time samplings. In this embodiment, = 100, that is, 100 samplings per second.

[0101] Then, using the measured ultrasonic echo signal, the ultrasonic echo signal with a certain h value conditional probability density function:

[0102]

[0103] where, is the standard deviation of the noise , is the probability normalization constant, C is n order identity matrix, whose diagonal terms are harmonic signals, n represents the number of samplings per unit time, represents the transpose of the matrix, represents transpose of.

[0104] Using the conditional probability density function and h prior probability distribution of, the h probability density function of is obtained;

[0105] h The prior probability distribution of is:

[0106]

[0107] where, is the probability normalization constant, is the average value of h, is the covariance matrix of h, is the matrix inverse matrix of, represents the matrix inverse matrix of, is transpose of.

[0108] Using Bayes' formula, when the ultrasonic echo signal h with the subharmonic envelope signal is known, h the probability density function of is:

[0109]

[0110] Based on h the probability density function, the maximum a posteriori (MAP) estimate of h is obtained;

[0111] When the matrices C , , and are known or determined in preprocessing, the estimator that maximizes the posterior probability h is called the maximum a posteriori (MAP) estimate. To maximize the h probability density function, by taking the derivative of the logarithm in the probability density function formula of h with respect to h and setting it to zero, the MAP estimate of h is obtained:

[0112] .

[0113] Using the distance of the sound source and the fundamental frequency echo amplitude characteristics of the subharmonic components, the MAP estimator of the subharmonic envelope can be effectively constructed. C is a diagonal matrix representing a sampled cosine wave with the subharmonic as the center frequency and an initial phase of 0. To stably estimate , the fundamental frequency echo is used instead of the subharmonic echo because the signal-to-noise ratio of the subharmonic echo is low. is defined as the autocorrelation coefficient (ACF) of the subharmonic echo.

[0114] The amplitude of the fundamental wave echo signal is much larger than that of the harmonic echo. To stably estimate , first, the smoothed ACF of the fundamental frequency echo envelope is determined by fitting a Gaussian function to the observed ACF, and its standard deviation is doubled to determine the ACF of the accurate subharmonic echo signal envelope. Since the ACF is normalized so that the maximum value equals 1, the obtained ACF should be multiplied by the standard deviation of its subharmonic echo envelope to construct . The specific operation is as follows:

[0115] According to the fundamental frequency echo (frequency = 10 MHz) envelope signal , the empirical autocorrelation function of the fundamental frequency echo is calculated as:

[0116]

[0117] represents the time lag amount, , , are the signal sampling points; Indicates the fundamental frequency echo envelope signal of the empirical autocorrelation function Indicates the fundamental frequency echo envelope signal at time

[0118] Perform Gaussian function fitting on the empirical autocorrelation function of the fundamental frequency echo to obtain the smoothed autocorrelation function model of the fundamental frequency echo:

[0119]

[0120] is the fitted Gaussian standard deviation, reflecting the time correlation of the fundamental wave envelope; Indicates the fundamental frequency echo envelope signal of the Gaussian form of the empirical autocorrelation function

[0121] The frequency of the sub-harmonic is 1 / 2 of the fundamental wave, and its bandwidth is also reduced by half. Therefore, the time resolution of the second harmonic is lower and the correlation time is longer.

[0122] Calculate the standard deviation of the autocorrelation function of the sub-harmonic echo to obtain the autocorrelation function of the sub-harmonic echo.

[0123] The standard deviation of the autocorrelation function of the sub-harmonic echo is:

[0124]

[0125] For each pair of sampling times, calculate the time difference, then the autocorrelation function of the sub-harmonic echo is:

[0126]

[0127] The smoothed autocorrelation function model of the sub-harmonic is:

[0128]

[0129] where represents the signal sampling point , each data group constituted by is the autocorrelation function of the sub-harmonic echo,

[0130] Use the stable estimation of the high signal-to-noise ratio of the fundamental frequency echo to avoid the ACF distortion caused by directly using the low signal-to-noise ratio harmonic signal and achieve the purpose of noise suppression. In addition. By Gaussian fitting and standard deviation adjustment, the broadband width characteristics of the sub-harmonic are retained to maintain high resolution.

[0131] Use the above method to construct a matrix When the echo signal propagates, it is affected by the distance, resulting in a certain degree of attenuation of the amplitude of the echo signal. Construct a diagonal matrix P to represent the generation and attenuation characteristics of the subharmonic components.

[0132] Therefore, using the autocorrelation function of the subharmonic echo, the subharmonic signal is reconstructed. The specific method is as follows:

[0133] Construct a diagonal matrix P , based on the diagonal matrix P , the autocorrelation function of the subharmonic echo, and h the maximum a posteriori estimate value, the subharmonic signal is reconstructed.

[0134] Among them, the diagonal matrix P is:

[0135]

[0136] Among them, P is a 100x100 matrix. The first 50 elements of its diagonal elements are: 0.1, 0.12, 0.14,..., 1; the last 50 elements of its diagonal elements are: 0.985, 0.97, 0.955,..., 0.25; the elements of the matrix P except for the first 50 elements and the last 50 elements of the diagonal elements are all zero.

[0137] The construction method of the diagonal matrix P is:

[0138] Obtain the subharmonic amplitude distribution data: Through experiments, measure the peak amplitude of the subharmonic signal at different propagation distances; the amplitude will first increase and then decrease with the propagation distance, showing non-linear characteristics;

[0139] Curve fitting: Use a polynomial to fit the amplitude-distance data; in this embodiment, a cubic polynomial is used for fitting because the cubic polynomial can better fit the non-linear trend of the amplitude first rising and then falling. In addition, the cubic polynomial is more stable than the high-order polynomial and can avoid overfitting. The form of the fitting equation is:

[0140]

[0141] Among them, is the propagation distance, represents the peak amplitude, a , b , c , d represent the coefficients of the polynomial after fitting.

[0142] Normalization processing: Normalize the maximum value of the fitted curve to 1; keep it consistent with the covariance matrix The scale consistency is expressed as:

[0143] .

[0144] denotes the value after normalization, denotes the maximum value in.

[0145] Distance - time conversion: According to the speed of sound , the propagation distance is converted into time, , where t is the round - trip time; The time is mapped to the signal sampling point number , , where, is the sampling frequency.

[0146] Construct a diagonal matrix : The matrix dimension is N×N, where N is the number of signal sampling points; The diagonal elements of the diagonal matrix are the values of the signal sampling point number corresponding to the value after normalization , and the elements other than the diagonal elements are all zero; Each diagonal element value represents the amplitude weight of the sub - harmonic at the corresponding time point.

[0147] The reconstructed sub - harmonic signal is:

[0148] .

[0149] The sub - harmonic resonance method provided by this embodiment has the advantages of fast detection speed, high reliability, and being unaffected by the nonlinear interference of experimental instruments, so it has broad application prospects. The sub - harmonic resonance method has the advantages of being sensitive to slight damage and having less influence on testing equipment.

[0150] Sub - harmonic ultrasonic resonance can avoid the interference of some non - destructive phenomena such as the inherent nonlinearity of materials; On the other hand, the sub - harmonic amplitude obtained by this method is not easily submerged by noise, thereby improving the detection ability under noise interference.

[0151] Embodiment 2

[0152] This embodiment provides a device for detecting the damage of the bonding interface of a wind turbine blade. As Figure 1 shown, it includes an ultrasonic probe 5 and a flaw detector. The flaw detector includes a host computer, a main control chip, a pulse emission circuit, a pulse reception circuit, an operational amplifier circuit, and an acquisition circuit; The pulse emission circuit and the pulse reception circuit are both communicatively connected to the ultrasonic probe 5; The ultrasonic probe 5 is disposed on the surface of the object to be measured;

[0153] In this embodiment, the object to be measured is a wind turbine blade 6, which includes a wind turbine blade leading edge 1 and a wind turbine blade trailing edge 4. The wind turbine blade leading edge 1, the wind turbine blade trailing edge 4, and the shear rib part all adopt a sandwich structure in the form of a wind turbine blade base material 2, which includes an internal wind turbine blade core 3 and an external wind turbine blade skin.

[0154] The host computer is communicatively connected to the main control chip, and the main control chip controls the pulse emission circuit to emit pulses, thereby exciting the ultrasonic probe 5 to generate ultrasonic waves; the echo signals received by the ultrasonic probe 5 are sequentially returned to the main control chip through the pulse receiving circuit, the operational amplifier circuit, and the acquisition circuit;

[0155] The main control chip processes the echo signals using the above-mentioned adhesive interface damage detection method to obtain a sub-harmonic signal imaging diagram, and the host computer is used to display the sub-harmonic signal imaging diagram.

[0156] In addition, the adhesive interface damage detection device further includes a data storage module, which is connected to the host computer and is used to store data such as the generated images.

[0157] During detection, the ultrasonic probe 5 is adsorbed on the wind turbine blade 6, and the flaw detector is held manually. The host computer selects the type of excitation pulse (sine, sharp wave, square wave, etc.), and further the pulse emission circuit generates a high-voltage (maximum voltage about 100V) pulse with a frequency of 10MHz to excite the ultrasonic probe 5 to generate ultrasonic waves and act on the wind turbine blade; the ultrasonic probe 5 receives the echo signals, which are received and filtered by the pulse receiving circuit. Among them, the filter of the receiving circuit is a 20MHz low-pass filter to filter out the echo signals with frequencies above 20MHz; further, the echo signals are amplified by the operational amplifier circuit and collected and processed in the main control chip FPGA. The main control chip FPGA processes the signals through signal processing techniques of Bayesian inference and fundamental wave echo information to improve the signal-to-noise ratio of the echo signals.

[0158] Further, by simply performing band-pass filtering (4MHz - 6MHz) on the signals processed by Bayesian inference and fundamental wave echo information, sub-harmonics (frequency of 5MHz) can be extracted, and further ultrasonic sub-harmonic imaging is performed after Fourier transform. On the host computer, the time-domain waveform diagram of the received original echo signals, the time-domain waveform diagram of the echo signals processed by the signal processing techniques of Bayesian inference and fundamental wave echo information, the amplitude diagram after Fourier transform, and the imaging diagram are displayed.

[0159] Embodiment Three

[0160] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the wind turbine blade adhesive interface damage detection method provided in Embodiment One.

[0161] The above specific embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the examples, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A method for detecting damage to the bonding interface of a wind turbine blade, characterized in that, Including: S1. A pulsed excitation ultrasonic probe generates ultrasonic waves, and the ultrasonic waves act on the wind turbine blade; S2. The ultrasonic probe receives the echo signal of the wind turbine blade; S3. After filtering and amplifying the echo signal, the filtered and amplified echo signal is processed to obtain sub-harmonics; S4. Perform Fourier transform on the sub-harmonics, and image the transformed sub-harmonics; S5. Use the imaging signal to detect the damage of the bonding interface; In step S3, the filtered and amplified echo signal is processed to obtain sub-harmonics. The specific method is: Let be the subharmonic envelope signal, and be the measured ultrasonic echo signal. Using the measured ultrasonic echo signal, the conditional probability density function of the ultrasonic echo signal with a certain value is obtained; ​ Using the conditional probability density function and the prior probability distribution of the subharmonic envelope signal to obtain the probability density function of the subharmonic envelope signal ; Based on the probability density function of the sub-harmonic envelope signal obtain the maximum a posteriori estimate of the sub-harmonic envelope signal ; Use the fundamental frequency echo to estimate the autocorrelation function of the sub-harmonic echo; Use the autocorrelation function of the sub-harmonic echo to reconstruct the sub-harmonic signal.

2. The method for detecting damage to the bonding interface of a wind turbine blade according to claim 1, wherein The center frequency of the ultrasonic probe is 10 MHz - 20 MHz.

3. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 1, wherein, The filtering in step S3 is: filtering out frequencies above 20 MHz.

4. The method for detecting damage to the bonding interface of a wind turbine blade according to claim 1, wherein Ultrasonic echo signal With a certain The conditional probability density function with a value is: wherein, is the standard deviation of the noise , is a constant for probability normalization C is n an identity matrix of order n whose diagonal elements are composed of discretized subharmonic carrier signals denotes the transpose of 5. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 4, characterized in that, h The prior probability distribution is as follows: wherein, is a constant for probability normalization, is h the average value of is h the covariance matrix of is the inverse matrix of the matrix is transpose of 6. The method for detecting damage to the bonding interface of a wind turbine blade according to claim 5, characterized in that, h The probability density function is as follows: 。 7. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 6, wherein Based on h , the maximum a posteriori estimate of h is obtained, specifically as follows: Taking the derivative of the logarithm in the probability density function of h and setting the resulting formula to zero, we obtain the maximum a posteriori estimate of h : 。 8. The method for detecting damage to the bonding interface of a wind turbine blade according to claim 7, characterized in that, Using the fundamental frequency echo to estimate the autocorrelation function of the sub-harmonic echo specifically includes: According to the fundamental frequency echo envelope signal, calculate the empirical autocorrelation function of the fundamental frequency echo; Perform Gaussian function fitting on the empirical autocorrelation function of the fundamental frequency echo to obtain a smooth autocorrelation function model of the fundamental frequency echo; Calculate the standard deviation of the autocorrelation function of the sub-harmonic echo to obtain the autocorrelation function of the sub-harmonic echo.

9. The method for detecting damage to the bonding interface of a wind turbine blade according to claim 8, wherein, Set the fundamental frequency echo envelope signal as , and the empirical autocorrelation function of the fundamental frequency echo is:[[]] represents the time lag amount, , , is the signal sampling point; represents the empirical autocorrelation function of the fundamental frequency echo envelope signal , represents the fundamental frequency echo envelope signal at the moment.

10. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 9, characterized in that, The smooth autocorrelation function model of the fundamental frequency echo is: is the fitted Gaussian standard deviation, represents the Gaussian form of the empirical autocorrelation function of the fundamental frequency echo envelope signal .

11. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 10, characterized in that, Standard deviation of the autocorrelation function of the subharmonic echo is as follows: 。 12. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 11, characterized in that, The autocorrelation function of the sub-harmonic echo is: The smooth autocorrelation function model of the sub-harmonic is: Among them, represents the signal sampling points , each data group formed the autocorrelation function of the subharmonic echo, represents the smoothed autocorrelation function of the subharmonic.

13. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 12, wherein Using the autocorrelation function of the sub-harmonic echo to reconstruct the sub-harmonic signal. The specific method is: Construct a diagonal matrix P , based on the diagonal matrix P , the autocorrelation function of the subharmonic echo, and h the maximum a posteriori estimate value, reconstruct the subharmonic signal.

14. The method for detecting damage at the bonding interface of a wind turbine blade according to claim 13, wherein Diagonal matrix P The construction method is as follows: Obtain the sub-harmonic amplitude distribution data: Through experiments, measure the peak amplitudes of the sub-harmonic signals at different propagation distances; Curve fitting: Use polynomials to fit the amplitude-distance data; Normalization processing: Normalize the maximum value of the fitted curve to 1; Distance - time conversion: According to the speed of sound, the propagation distance is converted into time, and the time is corresponding to the signal sampling point serial number n , , where is the sampling frequency; Construct a diagonal matrix P: The matrix dimension is N×N, where N is the number of signal sampling points; the values of the diagonal elements of the diagonal matrix P are the normalized values of the peak amplitudes corresponding to the signal sampling point serial number n, and the elements other than the diagonal elements are all zero.

15. The method for detecting damage to the adhesive interface of a wind turbine blade according to claim 13, characterized in that Reconstructed subharmonic signal is as follows: 。 16. A device for detecting damage to the bonding interface of a wind turbine blade, comprising an ultrasonic probe and a flaw detector, characterized in that, The flaw detector includes a host computer, a main control chip, a pulse emission circuit, a pulse reception circuit, an operational amplifier circuit, and an acquisition circuit; the pulse emission circuit and the pulse reception circuit are both communicatively connected to the ultrasonic probe; the ultrasonic probe is disposed on the surface of the object to be measured; The host computer is communicatively connected to the main control chip. The main control chip controls the pulse emission circuit to emit pulses, thereby exciting the ultrasonic probe to generate ultrasonic waves; the echo signal received by the ultrasonic probe sequentially returns to the main control chip through the pulse reception circuit, the operational amplifier circuit, and the acquisition circuit; The main control chip processes the echo signal by using the method for detecting the damage of the bonding interface of the wind turbine blade according to any one of claims 1 - 15 to obtain a sub-harmonic signal imaging diagram, and the host computer is used to display the sub-harmonic signal imaging diagram.

17. A computer-readable storage medium, characterized in that, A computer program is stored on the storage medium, and when the computer program is executed by a processor, the method for detecting the damage of the bonding interface of the wind turbine blade according to any one of claims 1 - 15 is implemented.

Images