Micro-damage tomography method based on nonlinear ultrasonic static component damage index

Abstract

The invention provides a micro-damage tomography method based on a nonlinear ultrasonic static component damage index, and particularly relates to the technical field of material monitoring. The method specifically comprises the following steps: S1, arranging sensors on the surface of a to-be-detected component; s2, setting a signal excitation end and a signal receiving end; s3, signal emission is carried out on the signal excitation end, a receiving signal of the signal receiving end is collected, and error preprocessing is carried out on the collected signal; s4, carrying out fast Fourier transform analysis and obtaining a static component energy value; s5, calculating a nonlinear damage index; s6, based on a detection grid formed by a circular array or an orthogonal scanning type array, a nonlinear damage index is used as a parameter to be embedded into an RAPID ellipse positioning algorithm, pixel values of the detection grid in an imaging area are calculated and filled, and a micro-damage tomographic image is generated. According to the method, millimeter-level positioning imaging of microcracks, layering defects and the like in the to-be-monitored structure can be realized by combining the nonlinear damage index with the RAPID ellipse chromatography algorithm.

Description

Technical Field

[0001] This invention relates to the field of materials monitoring technology, specifically to a micro-damage tomography method based on the nonlinear ultrasonic static component damage index. Background Technology

[0002] Materials are prone to structural defects such as microcracks, fatigue damage, and delamination under long-term service or extreme conditions (e.g., high temperature, high load, strong radiation). If these defects are not detected and identified in a timely manner, they may lead to catastrophic failures and cause significant damage to personnel and equipment. Therefore, developing highly sensitive and reliable non-destructive testing technologies is of great significance for ensuring the safe operation of critical structures.

[0003] Ultrasonic nondestructive testing (UDT) has become an important technical means in the field of structural health monitoring due to its advantages such as non-invasiveness, high resolution, and strong penetration. However, existing mainstream linear ultrasonic testing methods mainly rely on the elastic response of materials, and have weak ability to identify microscale damage (such as early cracks or interface degradation), which is prone to false positives or false negatives. Traditional nonlinear ultrasonic testing methods, such as those based on the second harmonic coefficient (... While traditional ultrasonic imaging can reflect nonlinear damage, it suffers from severe signal attenuation and poor imaging stability in high-attenuation materials (such as carbon fiber composites), limiting its practical engineering applications. In recent years, static component (SC) signals, as a direct product of nonlinear acoustic response, have attracted widespread attention. Damage regions such as cracks and interface fissures accumulate local low-frequency strain under ultrasonic excitation, resulting in an enhancement of the static component in the signal. Compared to harmonic components, the static component has a lower frequency, stronger penetration ability, and better attenuation resistance, making it particularly suitable for micro-damage detection in high-attenuation systems such as composite materials and complex components.

[0004] In industrial nondestructive testing image reconstruction, the imaging algorithm and sensor array layout directly determine the imaging quality and detection resolution. Existing systems mostly employ the RAPID algorithm for elliptic probabilistic image reconstruction. This algorithm utilizes the time difference of sound wave propagation (TOF) to construct an elliptic trajectory model between the transmitter and receiver pairs, achieving defect probability mapping. However, the traditional RAPID algorithm primarily relies on linear signal amplitude as a damage indicator, failing to fully extract nonlinear response features and exhibiting insufficient sensitivity in multipath interference or complex structural scenarios, easily leading to blurred images or misjudgments. Furthermore, the acoustic wave amplitude upon which existing elliptic localization algorithms are based is typically significantly affected by material anisotropy, sound attenuation, and structural noise, resulting in a low signal-to-noise ratio, unclear image boundaries, and difficulty in achieving accurate spatial reconstruction of early, subtle damage.

[0005] Therefore, there is an urgent need for a new ultrasonic nondestructive testing method that can combine nonlinear acoustic parameters, adapt to high-attenuation materials, and improve spatial imaging accuracy, so as to break through the technical bottleneck of existing linear ultrasound or traditional RAPID image algorithms in micro-damage detection. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, this invention provides a micro-damage tomography method based on the nonlinear ultrasound static component damage index, the specific technical solution of which is as follows: A micro-damage tomography method for nonlinear ultrasound static component damage index, specifically including the following steps: S1. Select either a circular array or an orthogonal scanning array to deploy sensors on the surface of the component to be measured; S2. Set the signal excitation end and signal receiving end; S3. Transmit signals to the signal excitation end and collect the received signals from the signal receiving end. Transmit the received signals to the oscilloscope through an amplifier. The oscilloscope collects the signals and uploads them to the PC data processing terminal. The collected signals are then subjected to error preprocessing. S4. Perform Fast Fourier Transform analysis on the signal after error preprocessing in S3 and obtain the energy value of the static component; S5. Calculate the nonlinear damage index ; S6. Based on the detection grid formed by a circular array or orthogonal scanning array, the nonlinear damage index is... The RAPID elliptical localization algorithm is embedded as a parameter to calculate and fill the detection grid in the imaging area, generating a micro-damage tomographic image.

[0007] Preferably, in S1, the circular array is formed by arranging the sensors according to a diameter of... The circular array is arranged in a circular structure, and the number of array elements in the circular array is... indivual; The orthogonal scanning array uses one face of the component under test as the scanning area and places two sensors at two adjacent corners of the scanning area. Wherein, the diameter of the circular array satisfy The spacing between the two sensors in the orthogonal scanning array satisfy ;wavelength , The phase velocity is the frequency of the signal excitation terminal. This is the transmission frequency of the signal excitation terminal.

[0008] Preferably, in S2, the center frequency of both the signal excitation end and the signal receiving end sensor is 500kHz; the transmission signal of the signal excitation end adopts a narrowband pulse modulated by a Hanning window and the transmission frequency is 200kHz to 500kHz.

[0009] Preferably, in S3, signal transmission and signal acquisition specifically include: S3.1. When using the circular array deployment, the signal acquisition process specifically includes the following sub-steps: S3.1.1 Sequentially arrange the circular array... Each sensor serves as a signal excitation terminal, and the remaining... Each sensor serves as a signal receiver. S3.1.2 Use a signal generator and an attenuator to sequentially transmit low-amplitude and high-amplitude excitation signals to each sensor, while simultaneously acquiring the signals received by the remaining sensors; wherein, when each sensor is used as a signal excitation end, the signals received by the remaining sensors are repeatedly acquired no less than five times; S3.1.3 Uploads several received signals obtained in S3.1.2 to the PC data processing terminal and calculates the average value of the repeatedly acquired signals, thereby completing the preprocessing of random errors in the measurement results; S3.2 When the orthogonal scanning array is deployed, the signal acquisition process specifically includes the following sub-steps: S3.2.1 The signal excitation end is set at one corner of the scanning area, and the signal receiving end is set at the other corner of the scanning area along the X-axis. S3.2.2 Using a signal generator and an attenuator, low-amplitude and high-amplitude excitation signals are emitted to the signal excitation end respectively to excite it, while the signal at the signal receiving end is collected to complete the scanning of a sound path; S3.2.3 Simultaneously move the signal excitation end and the signal receiving end along the Y-axis direction, with a movement step of 5mm for each scan. Repeat S3.2.2 to complete the scan of the Y-axis direction of the scan area respectively; among them, the signal needs to be collected no less than five times when scanning each acoustic path; S3.2.4 Move the signal excitation end back to the initial position, and move the signal receiving end to the corner diagonally opposite its initial position; S3.2.5 Using a signal generator and an attenuator, low-amplitude and high-amplitude excitation signals are emitted to the signal excitation end respectively to excite it, while the signal at the signal receiving end is collected to complete the scanning of one acoustic path; S3.2.6 Simultaneously move the signal excitation end and the signal receiving end along the X-axis direction, with a movement step of 5mm for each scan. Repeat S3.2.5 to complete the scan of the X-axis direction of the scan area; among them, the signal needs to be collected no less than five times when scanning each acoustic path; S3.2.7 Uploads several received signals obtained in S3.2.3 and S3.2.6 to the PC data processing terminal and calculates the average value of the signals repeatedly collected for each sound path, thereby completing the preprocessing of random errors in the measurement results of all sound paths.

[0010] Preferably, the voltage amplitude range of the low-amplitude excitation signal is 10–30V; and the voltage amplitude range of the high-amplitude excitation signal is 50–80V.

[0011] Preferably, a Fast Fourier Transform analysis is performed on the average value of the acquired signal after error preprocessing according to S3.1.3 or S3.2.7, and the spectral amplitude within the zero-band of integration (0–500 Hz) is used to calculate the... and ; in, The static component energy under low-amplitude excitation signal excitation; This refers to the static component energy under high-amplitude excitation signal.

[0012] More preferably, in S5, the nonlinear damage index The calculation formula is as follows: ; in, This is the amplification factor of the transmitted signal amplitude at the signal excitation end, which is the ratio of the high and low amplitudes of the incident wave at the signal excitation end. .

[0013] Further preferably, in S6, the detection grid formed by the circular array or orthogonal scanning array is a two-dimensional spatial grid, and each pixel in the two-dimensional spatial grid corresponds to a spatial location in the component under test; the nonlinear damage index is... Embedded in the RAPID elliptic localization algorithm, the comprehensive nonlinear response intensity of each pixel in the two-dimensional spatial grid is calculated. This enables visualization and spatial reconstruction of the location and extent of potential damage within the structure under test, generating a micro-damage tomographic image. In this image, different shades of color represent the probability of damage at each spatial location. Specifically: Scenario 1: The dark blue to light green area corresponds to low... The value indicates that the material in this region is in good condition, with no nonlinear response detected, and is therefore inferred to be in a non-destructive state. Scenario 2: The yellow to red area corresponds to high The value indicates that the nonlinearity of the response in this region is significantly enhanced under high amplitude excitation, which is inferred to be due to debonding, microcracks or fatigue damage. Specifically, when the imaging area exhibits a strip-shaped distribution with an aspect ratio ≥ 4:1, it is inferred that there is a crack propagation path or fatigue damage along its length direction; when the imaging area exhibits a circular or elliptical patch-shaped distribution, it is inferred that there is a debonding defect.

[0014] More preferably, the PC data processing terminal includes a MATLAB signal processing module, a fast Fourier transform analysis module, a parameter extraction module, and a wireless communication module; the signal excitation end, signal receiving end, signal generator, attenuator, amplifier, and oscilloscope are all electrically connected to the PC data processing terminal.

[0015] The beneficial effects of this invention are: This invention proposes a nonlinear damage index based on static components. The micro-damage detection method combines the RAPID elliptical tomography algorithm, amplifies the damage signal by high and low excitation amplitude modulation, and optimizes the imaging algorithm by combining circular array or orthogonal scanning to achieve high sensitivity, high efficiency and accurate spatial positioning of micro-damage. Compared with traditional nonlinear second harmonic detection methods, in terms of detection sensitivity, The index effectively avoids the dependence of the second harmonic method on phase matching by extracting the static nonlinear response, and the sensitivity of the nonlinear damage index calculated by the static component is 1.5 times that of the damage index obtained by the corresponding second harmonic method, thus achieving stable identification of micro-damage. Especially in the field of nondestructive testing of composite materials, the nonlinear damage index obtained by static component calculation The imaging performance is significantly superior to the traditional second harmonic method. Its core breakthrough lies in the improved signal fidelity brought about by the low attenuation characteristics, thereby maintaining stable signal strength and achieving a signal-to-noise ratio of ≥8dB even with 20dB background noise. However, in anisotropic materials such as carbon fiber reinforced polymers, the second harmonic method suffers from rapid energy dissipation due to dispersion effects during sound wave propagation (the measured attenuation coefficient reaches 23.7dB / m at 5MHz), which severely restricts the ability to detect deep defects and large-area inspections. However, by extracting the steady-state response of the fundamental wave and the nonlinear interaction with the material through the static component, its attenuation coefficient is only linearly related to the frequency (measured at 7.2dB / m in the same frequency band), which greatly improves the signal penetration depth and propagation distance, supporting deep defect detection and scanning of larger areas. Attached Figure Description

[0016] The accompanying drawings constituting this invention are provided to further understand this application and do not constitute an undue limitation of this application.

[0017] Figure 1 A flowchart of the method provided for this invention; Figure 2 This is a layout diagram of a circular array of sensors. Figure 3 This is a diagram showing the sensor layout and scanning path for an orthogonal scanning array. Figure 4 This is a schematic diagram of a circular array used in Example 1; where (a) is a diagram showing the location of the sensors; and (b) is a diagram showing the numbering of each sensor. Figure 5 The tomographic images of micro-damage generated in Example 1 are shown below; (a) is a tomographic image of a 10×10mm debonding defect in the specimen; and (b) is a tomographic image of a 3×3mm debonding defect in the specimen. Figure 6 Tomographic images of a 10×10mm debonding defect in a specimen obtained using the conventional second harmonic method; Figure 7 This is a schematic diagram of the orthogonal scanning area in Example 2; Figure 8 The micro-damage tomographic image generated in Example 2. Detailed Implementation

[0018] The specific implementation of the micro-damage tomography method based on the nonlinear ultrasonic static component damage index provided by the present invention will be further described with reference to the accompanying drawings and embodiments.

[0019] like Figure 1 As shown, the micro-damage tomography method based on the nonlinear ultrasound static component damage index specifically includes the following steps: S1. Select either a circular array or an orthogonal scanning array to deploy sensors on the surface of the component to be measured; Preferably, in S1, the circular array is formed by arranging the sensors according to a diameter of... The circular array is arranged in a circular structure, and the number of array elements in the circular array is... One, such as Figure 2 As shown; The orthogonal scanning array uses one face of the component under test as the scanning area and places two sensors at two adjacent corners of the scanning area. Wherein, the diameter of the circular array satisfy The spacing between the two sensors in the orthogonal scanning array satisfy ;wavelength , The phase velocity is the frequency of the signal excitation terminal. This is the transmission frequency of the signal excitation terminal.

[0020] It is worth noting that the sensors in the circular array use piezoelectric elements, while the sensors in the orthogonal scanning array use ultrasonic probes.

[0021] S2. Set the signal excitation end and signal receiving end; Preferably, in S2, the center frequency of both the signal excitation end and the signal receiving end sensor is 500kHz; the transmission signal of the signal excitation end adopts a narrowband pulse modulated by a Hanning window and the transmission frequency is 200kHz to 500kHz.

[0022] S3. Transmit signals to the signal excitation end and collect the received signals from the signal receiving end. Transmit the received signals to the oscilloscope through an amplifier. The oscilloscope collects the signals and uploads them to the PC data processing terminal. The collected signals are then subjected to error preprocessing. Preferably, in S3, using different arrays for signal transmission and signal acquisition specifically includes: S3.1. When using the circular array deployment, the signal acquisition process specifically includes the following sub-steps: S3.1.1 Sequentially arrange the circular array... Each sensor serves as a signal excitation terminal, and the remaining... Each sensor serves as a signal receiver. S3.1.2 Use a signal generator and an attenuator to sequentially transmit low-amplitude and high-amplitude excitation signals to each sensor, while simultaneously acquiring the signals received by the remaining sensors; wherein, when each sensor is used as a signal excitation end, the signals received by the remaining sensors are repeatedly acquired no less than five times; S3.1.3 Uploads several received signals obtained in S3.1.2 to the PC data processing terminal and calculates the average value of the repeatedly acquired signals, thereby completing the preprocessing of random errors in the measurement results; S3.2 When the orthogonal scanning array is deployed, the signal acquisition process specifically includes the following sub-steps: S3.2.1 The signal excitation end is set at one corner of the scanning area, and the signal receiving end is set at the other corner of the scanning area along the X-axis. S3.2.2 Using a signal generator and an attenuator, low-amplitude and high-amplitude excitation signals are emitted to the signal excitation end respectively to excite it, while the signal at the signal receiving end is collected to complete the scanning of a sound path; S3.2.3 Simultaneously move the signal excitation end and the signal receiving end along the Y-axis direction, with a movement step of 5mm for each scan. Repeat S3.2.2 to complete the scan of the Y-axis direction of the scan area respectively; among them, the signal needs to be collected no less than five times when scanning each acoustic path; S3.2.4 Move the signal excitation end back to the initial position, and move the signal receiving end to the corner diagonally opposite its initial position; S3.2.5 Using a signal generator and an attenuator, low-amplitude and high-amplitude excitation signals are emitted to the signal excitation end respectively to excite it, while the signal at the signal receiving end is collected to complete the scanning of one acoustic path; S3.2.6 Simultaneously move the signal excitation end and signal receiving end along the X-axis direction, with a movement step of 5mm for each scan. Repeat S3.2.5 to complete the scan of the X-axis direction of the scan area. For each acoustic path scan, the signal must be collected at least five times. The specific scan path is as follows: Figure 3 As shown; S3.2.7 Uploads several received signals obtained in S3.2.3 and S3.2.6 to the PC data processing terminal and calculates the average value of the signals repeatedly collected for each sound path, thereby completing the preprocessing of random errors in the measurement results of all sound paths.

[0023] Preferably, the voltage amplitude range of the low-amplitude excitation signal is 10–30V; and the voltage amplitude range of the high-amplitude excitation signal is 50–80V.

[0024] S4. Perform Fast Fourier Transform analysis on the signal after error preprocessing in S3 and obtain the energy value of the static component; Preferably, a Fast Fourier Transform analysis is performed on the average value of the acquired signal after error preprocessing according to S3.1.3 or S3.2.7, and the spectral amplitude within the zero-band of integration (0–500 Hz) is used to calculate the... and ; in, The static component energy under low-amplitude excitation signal excitation; This refers to the static component energy under high-amplitude excitation signal.

[0025] S5. Calculate the nonlinear damage index ; More preferably, in S5, the nonlinear damage index The calculation formula is as follows: ; in, This is the amplification factor of the transmitted signal amplitude at the signal excitation end, which is the ratio of the high and low amplitudes of the incident wave at the signal excitation end. .

[0026] S6. Based on the detection grid formed by a circular array or orthogonal scanning array, the nonlinear damage index is... The RAPID elliptical localization algorithm is embedded as a parameter to calculate and fill the detection grid in the imaging area, generating a micro-damage tomographic image.

[0027] Specifically, the detection grid formed by a circular array or orthogonal scanning array is a two-dimensional spatial grid, where each pixel corresponds to a spatial location in the component under test; the circular array uses a directly defined polar coordinate grid. Generate a detection grid; an orthogonal scanning array of sensors is arranged along the Cartesian coordinate axes to form a Cartesian grid. Further generate a detection grid; and apply the nonlinear damage index. Embedded in the RAPID elliptic localization algorithm, the comprehensive nonlinear response intensity of each pixel in the two-dimensional spatial grid is calculated. This enables visualization and spatial reconstruction of the location and extent of potential damage within the structure under test, generating a micro-damage tomographic image. In this image, different shades of color represent the probability of damage at each spatial location. Specifically: Scenario 1: The dark blue to light green area corresponds to low... The value indicates that the material in this region is in good condition, with no nonlinear response detected, and is therefore inferred to be in a non-destructive state. Scenario 2: The yellow to red area corresponds to high The value indicates that the nonlinearity of the response in this region is significantly enhanced under high amplitude excitation, which is inferred to be due to debonding, microcracks or fatigue damage. Specifically, when the imaging area exhibits a strip-shaped distribution with an aspect ratio ≥ 4:1, it is inferred that there is a crack propagation path or fatigue damage along its length direction; when the imaging area exhibits a circular or elliptical patch-shaped distribution, it is inferred that there is a debonding defect.

[0028] Specifically, if the imaging area is distributed in a circular or elliptical patch pattern, with an aspect ratio of less than 2:1, clear boundaries, and isolated distribution, it is usually inferred to be a debonding, interface separation, or local unbonded defect. If the imaging area shows a short strip or thin line distribution, the aspect ratio is generally between 2:1 and 4:1, and it exhibits an asymmetrical, locally prominent high-response area, it is inferred to be the initiation area of ​​early microcracks. If the imaging area is distributed in a band or elongated strip shape, with an aspect ratio greater than or equal to 4:1, and is continuously distributed along its length, it is inferred to be a fatigue cumulative damage zone or a crack propagation path.

[0029] More preferably, the PC data processing terminal includes a MATLAB signal processing module, a fast Fourier transform analysis module, a parameter extraction module, and a wireless communication module; the signal excitation end, signal receiving end, signal generator, attenuator, amplifier, and oscilloscope are all electrically connected to the PC data processing terminal.

[0030] To better understand the micro-damage tomography method provided by this invention, specific embodiments are described below.

[0031] Example 1: In this embodiment, a total of 12 piezoelectric elements are used in a circular array, and each piezoelectric element is numbered sequentially from 1 to 12, as follows: Figure 4 As shown in (a) and (b), two metal component bonding specimens were selected as the specimen bodies. The upper and lower bonding layers of each specimen body were made of Al7075-T6 aluminum alloy, with dimensions of 200×200×2mm. The intermediate bonding layer used IXChemistry-28206 two-component liquid industrial adhesive. A polytetrafluoroethylene (PTFE) sheet was placed inside the intermediate bonding layer between the bonding layer and the bonded layers to simulate debonding defects (two square debonding defects, one 10×10mm and the other 3×3mm, were placed in the intermediate bonding layer of the two specimen bodies for comparative analysis). A rectangular coordinate system was established with the center of the bonded component as the origin. In this embodiment, the center coordinates of the debonding defects were (20, 30). The excitation signal at the signal excitation end was a sinusoidal pulse signal with a period of 10, a center frequency of 300kHz, and modulated by a Hanning window, with a circular array diameter of 150mm.

[0032] During testing, a low-amplitude excitation signal (output level set to 40%) was first used to complete the full array signal acquisition process sequentially: using piezoelectric element 1 as the signal excitation end, the received signals of piezoelectric elements 2 to 12 (excluding element 1) were acquired; then, using piezoelectric element 2 as the signal excitation end, the received signals of piezoelectric elements 1 (excluding element 2) and piezoelectric elements 3 to 12 (excluding element 2) were acquired; and so on, until all signals were acquired using the 12 piezoelectric elements as signal excitation ends in sequence. A total of 132 sets of response data under the low-amplitude excitation signal condition were obtained in a single acquisition.

[0033] Next, repeat the above steps, repeatedly acquiring data in the same excitation-reception order, but replacing the low-amplitude excitation signal with a high-amplitude excitation signal (output level set to 80%). A total of 132 sets of response data under the high-amplitude excitation signal condition were obtained in a single acquisition.

[0034] To reduce random errors in the measurement results, each piezoelectric element was used as a signal excitation end. When collecting signals from the remaining signal receiving end, the data was collected 5 times and the average value was taken. This resulted in 660 sets of signal data under low amplitude and 660 sets of signal data under high amplitude excitation conditions. After averaging, 132×2 sets of signal data were generated, paired under high and low amplitude excitation conditions, for use in subsequent defect detection and location analysis calculations.

[0035] Specifically, Figure 5Figure 5(a) shows the damage tomography results of a 10×10mm debonding defect; Figure 5(b) shows the damage tomography results of a 3×3mm debonding defect. The elliptical shapes in the figures indicate the locations of the debonding defects detected using the method provided in this invention, while the red boxes represent the actual locations of the debonding defects. There is a certain error between the detected location and the actual location of the debonding defects, but the high-response areas in both figures are concentrated near the actual defect locations, and the relative location errors of the experimental results are both less than 4.18%, which is lower than the industry-accepted 5% error threshold. Therefore, the nonlinear damage index proposed in this invention is suitable for this study. It has good defect localization capability, thus proving that the imaging method provided by the present invention has a certain degree of accuracy and reliability in the quantitative detection and localization of small debonding defects.

[0036] To better compare with traditional tomographic results, a tomographic image of a 3×3mm debonding defect obtained using the traditional second harmonic method is also included. Figure 6 As shown. Because the amplitude of the second harmonic of ultrasonic guided waves is relatively weak, it is difficult to extract and is easily affected by noise, attenuation, and system nonlinearity. The calculated nonlinear parameters of the second harmonic in each path are unstable, resulting in artifacts in the images obtained by traditional methods that are difficult to eliminate, and the images cannot distinguish the specific location of the damage. The imaging method provided by this invention effectively solves the above problems.

[0037] Example 2: In this embodiment, the ultrasonic probe is arranged in an orthogonal scanning array. A schematic diagram of the bonded damaged sample, scanning area, and scanning path direction is shown below. Figure 7 As shown (where the blue dashed line represents the scanned area and the red area simulates damage).

[0038] In this embodiment, the specimen used is a 16-layer quasi-isotropic carbon fiber reinforced composite material plate, with the layup sequence as follows: The composite board has a layer thickness of 0.14 mm per layer and a total thickness of 2.24 mm. Delamination damage was assessed by inserting a 0.05 mm thick polytetrafluoroethylene (PTFE) film between selected layers during the layup bonding process. The scanning area was a 200 × 200 mm rectangular region, with a 200 mm gap between the signal excitation and reception ends. Each scanning step was 5 mm. The excitation signal used was a sinusoidal pulse signal modulated by a Hanning window with a period of 10 and a center frequency of 200 kHz. The experiment involved scanning according to the set step size and calculating the damage index for localization imaging. The results are as follows: Figure 8As shown, the actual shape and location of the delamination damage have been clearly identified. The high-brightness red and orange areas in the image clearly indicate large-area debonding defects within the material. The detection data for these areas show good consistency with the actual dissection results, verifying the reliability of the detection method. It is worth noting that the light blue and green areas generated during the scanning process are actually artifacts caused by the superposition of multiple scanning paths. These interference signals can be effectively eliminated by setting appropriate threshold parameters, thereby ensuring the accuracy of the detection results. In other words, this method can clearly display the damage condition and location within the component being monitored.

[0039] In this invention, terms such as "upper," "lower," "bottom," and "top" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are merely used to facilitate the description of the structural relationships of the various components or elements of this invention and do not specifically refer to any particular component or element in this invention, nor should they be construed as limiting the invention. Terms such as "connected" and "linked" should be interpreted broadly, indicating a fixed connection, an integral connection, or a detachable connection; a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can determine the specific meaning of the above terms in this invention based on the specific circumstances, and they should not be construed as limiting the invention.

[0040] Of course, the above description is not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A micro-damage tomography method based on the nonlinear ultrasonic static component damage index, characterized in that, Specifically, the following steps are included: S1. Select either a circular array or an orthogonal scanning array to deploy sensors on the surface of the component to be measured; S2. Set the signal excitation end and signal receiving end; S3. Transmit signals to the signal excitation end and collect the received signals from the signal receiving end. Transmit the received signals to the oscilloscope through an amplifier. The oscilloscope collects the signals and uploads them to the PC data processing terminal. The collected signals are then subjected to error preprocessing. S4. Perform Fast Fourier Transform analysis on the signal after error preprocessing in S3 and obtain the energy value of the static component; S5. Calculate the nonlinear damage index ; S6. Based on the detection grid formed by a circular array or orthogonal scanning array, the nonlinear damage index is... The RAPID elliptical localization algorithm is embedded as a parameter to calculate and fill the pixel values ​​of the detection grid in the imaging area, generating a micro-damage tomographic image.

2. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 1, characterized in that, In S1, the circular array is formed by arranging the sensors according to a diameter of... The circular array is arranged in a circular structure, and the number of array elements in the circular array is... indivual; The orthogonal scanning array uses one face of the component under test as the scanning area and places two sensors at two adjacent corners of the scanning area. Wherein, the diameter of the circular array satisfy The spacing between the two sensors in the orthogonal scanning array satisfy ;wavelength , The phase velocity is the frequency of the signal excitation terminal. This is the transmission frequency of the signal excitation terminal.

3. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 2, characterized in that, In S2, the center frequency of both the signal excitation end and the signal receiving end sensor is 500kHz; The transmitted signal at the signal excitation terminal is a narrowband pulse modulated by a Hanning window and the transmission frequency is 200kHz to 500kHz.

4. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 3, characterized in that, In S3, signal transmission and signal acquisition specifically include: S3.

1. When using the circular array deployment, the signal acquisition process specifically includes the following sub-steps: S3.1.1 Sequentially arrange the circular array... Each sensor serves as a signal excitation terminal, and the remaining... Each sensor serves as a signal receiver. S3.1.2 Use a signal generator and an attenuator to sequentially transmit low-amplitude and high-amplitude excitation signals to each sensor, while simultaneously acquiring the signals received by the remaining sensors; wherein, when each sensor is used as a signal excitation end, the signals received by the remaining sensors are repeatedly acquired no less than five times; S3.1.3 Uploads several received signals obtained in S3.1.2 to the PC data processing terminal and calculates the average value of the repeatedly acquired signals, thereby completing the preprocessing of random errors in the measurement results; S3.2 When the orthogonal scanning array is deployed, the signal acquisition process specifically includes the following sub-steps: S3.2.1 The signal excitation end is set at one corner of the scanning area, and the signal receiving end is set at the other corner of the scanning area along the X-axis. S3.2.2 Using a signal generator and an attenuator, low-amplitude and high-amplitude excitation signals are emitted to the signal excitation end respectively to excite it, while the signal at the signal receiving end is collected to complete the scanning of a sound path; S3.2.3 Simultaneously move the signal excitation end and the signal receiving end along the Y-axis direction, with a movement step of 5mm for each scan. Repeat S3.2.2 to complete the scan of the Y-axis direction of the scan area respectively; among them, the signal needs to be collected no less than five times when scanning each acoustic path; S3.2.4 Move the signal excitation end back to the initial position, and move the signal receiving end to the corner diagonally opposite its initial position; S3.2.5 Using a signal generator and an attenuator, low-amplitude and high-amplitude excitation signals are emitted to the signal excitation end respectively to excite it, while the signal at the signal receiving end is collected to complete the scanning of one acoustic path; S3.2.6 Simultaneously move the signal excitation end and the signal receiving end along the X-axis direction, with a movement step of 5mm for each scan. Repeat S3.2.5 to complete the scan of the X-axis direction of the scan area; among them, the signal needs to be collected no less than five times when scanning each acoustic path; S3.2.7 Uploads several received signals obtained in S3.2.3 and S3.2.6 to the PC data processing terminal and calculates the average value of the signals repeatedly collected for each sound path, thereby completing the preprocessing of random errors in the measurement results of all sound paths.

5. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 4, characterized in that, The voltage amplitude range of the low-amplitude excitation signal is 10–30V; the voltage amplitude range of the high-amplitude excitation signal is 50–80V.

6. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 4, characterized in that, In S4, a Fast Fourier Transform analysis is performed on the average value of the acquired signal after error preprocessing in S3.1.3 or S3.2.7, and the spectral amplitude within the zero-band of integration (0–500 Hz) is used to calculate the... and ; in, The static component energy under low-amplitude excitation signal excitation; This refers to the static component energy under high-amplitude excitation signal.

7. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 6, characterized in that, In S5, the nonlinear damage index The calculation formula is as follows: ； in, This is the amplification factor of the transmitted signal amplitude at the signal excitation end, which is the ratio of the high and low amplitudes of the incident wave at the signal excitation end. .

8. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 7, characterized in that, In S6, the detection grid formed by a circular array or an orthogonal scanning array is a two-dimensional spatial grid, and each pixel in the two-dimensional spatial grid corresponds to a spatial position in the component to be measured. Nonlinear damage index Embedded in the RAPID elliptic localization algorithm, the comprehensive nonlinear response intensity of each pixel in the two-dimensional spatial grid is calculated. This enables visualization and spatial reconstruction of the location and extent of potential damage within the structure under test, generating a micro-damage tomographic image. In this image, different shades of color represent the probability of damage at each spatial location. Specifically: Scenario 1: The dark blue to light green area corresponds to low... The value indicates that the material in this region is in good condition, with no nonlinear response detected, and is therefore inferred to be in a non-destructive state. Scenario 2: The yellow to red area corresponds to high The value indicates that the nonlinearity of the response in this region is significantly enhanced under high amplitude excitation, which is inferred to be due to debonding, microcracks or fatigue damage. Specifically, when the imaging area exhibits a strip-shaped distribution with an aspect ratio ≥ 4:1, it is inferred that there is a crack propagation path or fatigue damage along its length direction; when the imaging area exhibits a circular or elliptical patch-shaped distribution, it is inferred that there is a debonding defect.

9. The micro-damage tomography method based on the nonlinear ultrasonic static component damage index according to claim 5, characterized in that, The PC data processing terminal includes a MATLAB signal processing module, a fast Fourier transform analysis module, a parameter extraction module, and a wireless communication module. The signal excitation terminal, signal receiving terminal, signal generator, attenuator, amplifier, and oscilloscope are all electrically connected to the PC data processing terminal.

Images