A landing gear damage identification method based on FSDP images

Abstract

The application discloses a landing gear damage identification method based on FSDP images, relates to the technical field of structural health monitoring and nondestructive testing, and aims to solve the problem that the existing whole-image identification method is prone to missing detection when the outer ring feature of an early closed crack of a landing gear is not obvious; the method collects a response signal of a landing gear component to be measured under ultrasonic excitation, generates an FSDP image and extracts a frequency spectrum feature; damage-sensitive spectrum evidence, central weak texture evidence and outer ring obvious damage evidence are determined respectively; when the spectrum evidence and the central evidence both meet early abnormal conditions and the outer ring evidence does not meet obvious damage conditions, an early closed crack risk result is output; the method can avoid that the outer ring health feature covers the central weak anomaly, and improves the reliability of early damage identification of the landing gear.

Description

Technical Field

[0001] This application relates to the fields of structural health monitoring and non-destructive testing technology, and in particular, to a landing gear damage identification method based on FSDP images. Background Technology

[0002] During takeoff, taxiing, and landing, the landing gear of a drone is subjected to repeated impact loads. This makes the connection parts, support rods, and irregular transition parts of the landing gear more prone to fatigue cracks, closed cracks, or localized structural damage. If these damages are not detected in the early stages, the cracks may continue to propagate under the impact of subsequent takeoff and landing, thus affecting the safety of the drone's taxiing, landing, and mission execution. To improve the timeliness of landing gear structural condition monitoring, existing technologies typically use ultrasonic testing, nonlinear ultrasonic testing, image feature extraction, and deep learning models to identify the presence, location, and degree of damage to landing gear structural components.

[0003] Spectral Symmetric Dot Pattern (FSDP) can convert the frequency domain information of an ultrasonic response signal into a two-dimensional image with symmetrical texture, thus allowing the spectral changes in a one-dimensional ultrasonic signal to be presented in the form of image texture. Existing recognition methods based on FSDP images typically first perform frequency domain transformation on the response signal, then generate an FSDP image, and input the entire FSDP image into a recognition model, which automatically extracts image features and outputs the damage recognition results. For structural components with obvious cracks, the central and outer regions of the FSDP image usually show significant changes, so the whole-image recognition model can easily complete the classification work.

[0004] However, for early-closing cracks in the landing gear, crack contact nonlinearity may first cause a weak enhancement in the harmonic neighborhood or sideband neighborhood, and in the central region of the FSDP image, it manifests as local point density changes, light gray texture diffusion, or an increase in short radial texture; at this time, the outer line spacing of the FSDP image may still be close to a healthy state. If existing methods directly output conclusions based on the overall classification results of the entire FSDP image, the health features of the outer region can easily mask the weak anomalies in the central region, causing the system to misjudge early closed cracks as having no damage. Therefore, it is necessary to provide a landing gear damage identification method that can comprehensively utilize the logical relationship between weak spectral anomalies, weak central texture, and obvious damage states in the outer region. Summary of the Invention

[0005] This application provides a landing gear damage identification method based on FSDP images. Its purpose is to avoid the identification model or whole-image judgment process directly outputting the conclusion of no damage when the early closed crack of the landing gear has not yet formed an obvious change in the outer ring line spacing, thereby improving the reliability of the early damage identification of the landing gear; the specific content of the technical solution is as follows.

[0006] On one hand, a landing gear damage identification method based on FSDP images is provided. The method includes: acquiring the response signal generated by the landing gear component under test under ultrasonic excitation; generating an FSDP image based on the response signal and acquiring the spectral features corresponding to the response signal; determining damage-sensitive spectral evidence based on the spectral features, and simultaneously determining central weak texture evidence based on the central region of the FSDP image and determining outer ring obvious damage evidence based on the outer ring region of the FSDP image; when both the damage-sensitive spectral evidence and the central weak texture evidence satisfy the early anomaly condition, and the outer ring obvious damage evidence does not satisfy the obvious damage condition, the early closed crack risk result is output.

[0007] In one possible implementation, the landing gear damage identification device acquires the response signal generated by the landing gear component under ultrasonic excitation in the following way: the landing gear damage identification device first acquires the detection configuration corresponding to the target measurement point of the landing gear component under test; Then, the landing gear damage identification device, according to the detection configuration, controls the excitation sensor to apply ultrasonic excitation to the landing gear component under test; next, the landing gear damage identification device uses the receiving sensor to collect the response signal corresponding to the target measurement point; wherein, the detection configuration includes ultrasonic excitation parameters, sampling parameters and FSDP generation parameters.

[0008] In one possible implementation, the landing gear damage identification device generates an FSDP image based on the response signal and obtains the spectral features corresponding to the response signal in the following manner: the landing gear damage identification device first performs frequency domain transformation on the response signal to obtain spectral data; then, the landing gear damage identification device generates an FSDP image based on the amplitude sequence in the spectral data; next, the landing gear damage identification device extracts at least one frequency band feature from the high-frequency carrier neighborhood, harmonic neighborhood, and sideband neighborhood from the spectral data, and uses the extracted frequency band feature as the spectral feature corresponding to the response signal.

[0009] In one possible implementation, the step of determining damage-sensitive spectral evidence based on the spectral features includes: The local enhancement amount of the harmonic neighborhood or the sideband neighborhood relative to its corresponding local background is obtained; the low-frequency disturbance amount corresponding to the low-frequency modulation main peak is obtained; if the local enhancement amount reaches the weak spectral anomaly threshold and the low-frequency disturbance amount does not reach the overall low-frequency disturbance threshold, it can be determined that the damage-sensitive spectral evidence satisfies the early anomaly condition.

[0010] In one possible implementation, the step of generating the FSDP image based on the amplitude sequence in the spectral data includes: The amplitude sequence is logarithmically processed to obtain a logarithmic amplitude sequence. Based on the logarithmic amplitude sequence, the frequency hysteresis coefficient, the mirror symmetry plane rotation angle, and the deflection angle gain, the radius and deflection angle of the frequency sampling point in polar coordinates are determined. The FSDP image is generated based on the radius and the deflection angle.

[0011] In one possible implementation, the landing gear damage identification device determines weak central texture evidence based on the central region of an FSDP image using the following method: The device first determines the central region according to the polar coordinate radius of the FSDP image; then, it extracts central texture indicators from the central region; finally, it determines weak central texture evidence based on these indicators. The central texture indicators include at least one of point density, grayscale dispersion, and the number of radial short lines.

[0012] In one possible implementation, the landing gear damage identification device determines weak texture evidence in the center based on a center texture index in the following way: the landing gear damage identification device compares the center texture index with a corresponding weak texture threshold in the center; if the center texture index reaches the corresponding weak texture threshold in the center, then the landing gear damage identification device can determine that there is a weak texture anomaly in the center region, and can determine that the weak texture evidence in the center meets the early anomaly conditions.

[0013] In one possible implementation, the step of determining evidence of significant damage in the outer ring based on the outer ring region of the FSDP image includes: The outer region is determined according to the polar coordinate radius of the FSDP image; the outer line spacing index is extracted from the outer region; and evidence of obvious damage to the outer circle is determined based on the outer line spacing index; wherein, the outer line spacing index includes at least one of the following: the change in the line spacing between adjacent radial lines and the change in the continuity of radial lines.

[0014] In one possible implementation, the step of determining evidence of obvious damage to the outer ring based on the outer ring spacing index includes: comparing the outer ring spacing index with a corresponding obvious damage threshold for the outer ring. If the outer ring spacing index reaches the corresponding outer ring obvious damage threshold, it can be determined that the evidence of obvious damage to the outer ring meets the obvious damage condition; if the outer ring spacing index does not reach the corresponding outer ring obvious damage threshold, it can be determined that the evidence of obvious damage to the outer ring does not meet the obvious damage condition.

[0015] In one possible implementation, after outputting the early closed crack risk result, the method further includes: re-acquiring a resampled response signal at the same target measurement point on the landing gear component under test; re-determining the damage-sensitive spectral evidence, the central weak texture evidence, and the outer ring obvious damage evidence based on the resampled response signal; if, after resampling, the damage-sensitive spectral evidence and the central weak texture evidence still meet the early anomaly condition, and the outer ring obvious damage evidence still does not meet the obvious damage condition, then the early closed crack confirmation result is output; if, after resampling, the damage-sensitive spectral evidence or the central weak texture evidence does not meet the early anomaly condition, then an occasional interference result is output.

[0016] The landing gear damage identification method based on FSDP images provided in this application does not output the damage status solely based on the classification results of the entire FSDP image. Instead, it obtains damage-sensitive spectral evidence, weak texture evidence in the center, and obvious damage evidence in the outer ring from the spectral characteristics of the response signal, the central region, and the outer ring region of the FSDP image, respectively. Furthermore, it outputs an early closure crack risk result only when both the damage-sensitive spectral evidence and the weak texture evidence in the center indicate early abnormalities, while the obvious damage evidence in the outer ring does not yet indicate significant damage. This avoids directly outputting a conclusion of no damage when the outer ring region is still close to a healthy state, which is beneficial for identifying early closure cracks.

[0017] Furthermore, this embodiment does not perform simple weighting on the spectral features, center texture features, and outer ring spacing features. Instead, it first determines whether there is evidence of obvious damage to the outer ring. If there is no evidence of obvious damage to the outer ring, the identification device further combines damage-sensitive spectral evidence and weak center texture evidence to determine whether there is a risk of early closure cracks in the landing gear component under test. In this way, this method can avoid the whole image recognition model being dominated by the health features of the outer ring area, thereby improving the stability of the landing gear damage identification results. Attached Figure Description

[0018] To illustrate the technical solutions in the embodiments of this application more clearly, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of an implementation environment provided in an embodiment of this application; Figure 2 This is a flowchart of a landing gear damage identification method based on FSDP images provided in an embodiment of this application; Figure 3 This is a schematic diagram of an FSDP image generation process provided in an embodiment of this application; Figure 4 This is a schematic diagram of a three-evidence logical determination process provided in an embodiment of this application; Figure 5 This is a schematic diagram of a resampling verification process provided in an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0021] It is understood that the terms “first,” “second,” etc., used in this application can be used to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms; these terms are merely used to distinguish one concept from another.

[0022] In the embodiments of this application, the FSDP image refers to an image generated based on a spectral symmetric dot matrix pattern; damage-sensitive spectral evidence is used to characterize weak spectral anomalies in the response signal associated with early damage; weak texture evidence in the center is used to characterize weak texture anomalies in the central region of the FSDP image; and obvious damage evidence in the outer ring is used to characterize obvious line spacing anomalies in the outer ring region of the FSDP image. The purpose of early closed crack risk results is to indicate the current detection status, which matches the evidence combination corresponding to early closed cracks, and it can serve as the basis for triggering resampling, manual review, or further non-destructive testing.

[0023] Figure 1 This is a schematic diagram illustrating the implementation environment of a landing gear damage identification method based on FSDP images provided in this application embodiment; as follows: Figure 1As shown, this implementation environment includes the landing gear component under test, an excitation sensor, a receiving sensor, and a landing gear damage identification device; the excitation sensor is used to apply ultrasonic excitation to the landing gear component under test. The receiving sensor is used to collect the response signal generated by the landing gear component under ultrasonic excitation; the landing gear damage identification device is used to receive and process this response signal and output the corresponding damage identification result.

[0024] Optionally, the landing gear component to be tested is a support rod, connecting transition component, T-shaped component, or other metal structural component that bears the impact load of takeoff and landing in the UAV landing gear; the landing gear damage identification device can be a computer, detection terminal, embedded detection device, or server; the specific type of landing gear damage identification device is not limited in the embodiments of this application.

[0025] Figure 2 This is a flowchart of a landing gear damage identification method based on FSDP images provided in an embodiment of this application; see also Figure 2 This method includes the following steps: S201, The landing gear damage identification equipment performs the task of acquiring the detection configuration corresponding to the target measurement points of the landing gear component to be tested; The target measurement point refers to the signal acquisition location set on the landing gear component to be tested; the detection configuration includes ultrasonic excitation parameters, sampling parameters, and FSDP generation parameters; the ultrasonic excitation parameters may include: Excitation frequency, excitation amplitude, and excitation duration are all possible parameters; sampling parameters may include at least one of sampling frequency, number of sampling points, and sampling time window; FSDP generation parameters may include at least one of frequency hysteresis coefficient, mirror symmetry plane rotation angle, and deflection angle gain.

[0026] Optionally, the landing gear damage identification device can obtain the detection configuration from a local configuration file, a detection database, or user input information; for the same type of landing gear component to be tested, the corresponding detection configuration can be pre-set; for different target measurement points, different FSDP generation parameters and threshold parameters can also be set separately to adapt to the signal propagation path of different measurement points.

[0027] S202. The landing gear damage identification equipment controls the excitation sensor according to the detection configuration to apply ultrasonic excitation to the landing gear component under test, and uses the receiving sensor to collect the response signal corresponding to the target measurement point; In one possible implementation, the excitation sensor is a piezoelectric ceramic sensor, and the receiving sensor is a piezoelectric sensor, an accelerometer, or other sensor capable of receiving ultrasonic responses. The landing gear damage identification device sends an excitation control signal to the excitation sensor, causing the excitation sensor to operate according to the ultrasonic excitation parameters. The receiving sensor collects the response signal generated by the landing gear component under test under ultrasonic excitation and sends this response signal to the landing gear damage identification device.

[0028] It should be noted that the response signal can be a time-domain signal obtained from a single acquisition, or a time-domain signal obtained after multiple acquisitions, through averaging, filtering, or truncation; this application does not limit this.

[0029] In one possible implementation, ultrasonic excitation can be a single-frequency high-frequency excitation or a composite excitation including a low-frequency modulation signal and a high-frequency carrier signal. When using a single-frequency high-frequency excitation, the spectral characteristics will include the high-frequency carrier neighborhood and the harmonic neighborhood. When using a composite excitation, the spectral characteristics will additionally include the sideband neighborhood and the low-frequency modulation peak.

[0030] S203, The landing gear damage identification equipment performs frequency domain conversion on the response signal to obtain spectrum data; Optionally, the landing gear damage identification device performs a Fourier transform on the response signal to obtain a frequency domain signal. In this way, the landing gear damage identification device generates spectral data based on the amplitude of the frequency domain signal. This spectral data includes multiple frequency sampling points and the amplitude corresponding to each frequency sampling point. The landing gear damage identification device then generates an FSDP image based on this spectral data and extracts damage-sensitive spectral evidence from this spectral data.

[0031] S204. The landing gear damage identification device generates an FSDP image based on the amplitude sequence in the spectrum data; See Figure 3 In one possible implementation, the landing gear damage identification device performs logarithmic processing on the amplitude sequence in the spectral data to obtain a logarithmic amplitude sequence; based on the maximum and minimum values ​​in the logarithmic amplitude sequence and the logarithmic amplitude of each frequency sampling point, it calculates the radius of each frequency sampling point in polar coordinates; based on the logarithmic amplitude sequence, frequency hysteresis coefficient, mirror symmetry plane rotation angle, and deflection angle gain, it calculates the deflection angle of each frequency sampling point in polar coordinates; and based on the radius and deflection angle corresponding to each frequency sampling point, it generates an FSDP image in the polar coordinate plane.

[0032] For example, the complex value of the k-th frequency sampling point after the Fourier transform of the response signal is X(k), and the logarithmic magnitude A(k) can be expressed by equation (1): A(k)=log(|X(k)|+ε) (1) Where A(k) is the logarithmic magnitude of the k-th frequency sampling point, X(k) is the complex value of the k-th frequency sampling point after the Fourier transform of the response signal, and ε is a positive number to prevent abnormalities in logarithmic or denominator operations; the radius r(k) of the k-th frequency sampling point in polar coordinates can be represented by equation (2): r(k)=[A(k)-Amin] / [Amax-Amin+ε](2), where r(k) is the radius of the k-th frequency sampling point in polar coordinates, Amin is the minimum value in the logarithmic amplitude sequence, and Amax is the maximum value in the logarithmic amplitude sequence.

[0033] The counterclockwise deflection angle θ1(k) and clockwise deflection angle θ2(k) of the k-th frequency sampling point relative to the mirror symmetry plane can be expressed by equations (3) and (4), respectively: θ1(k)=θ0+{[A(k+l)-Amin] / [Amax-Amin+ε]}·g(3); θ2(k)=θ0-{[A(k+l)-Amin] / [Amax-Amin+ε]}·g (4); Where θ1(k) is the counterclockwise deflection angle of the kth frequency sampling point, θ2(k) is the clockwise deflection angle of the kth frequency sampling point, θ0 is the rotation angle of the mirror symmetry plane, l is the frequency lag coefficient, and g is the deflection angle gain.

[0034] Optionally, the FSDP image may include a single-cycle FSDP image or a full-cycle FSDP image obtained by periodizing the single-cycle FSDP image. In order to facilitate the subsequent extraction of the central and outer regions of the FSDP image, the landing gear damage identification device may perform periodic processing on the single-cycle FSDP image and convert it into a centrally symmetrical full-cycle FSDP image.

[0035] S205. The landing gear damage identification device extracts spectral features from the spectral data and determines damage-sensitive spectral evidence based on these features; In one possible implementation, the landing gear damage identification device extracts at least one frequency band feature from the high-frequency carrier neighborhood, harmonic neighborhood, and sideband neighborhood of the spectrum data as spectrum features; the high-frequency carrier neighborhood can be determined based on the high-frequency excitation frequency fh in the ultrasonic excitation parameters; the harmonic neighborhood can be determined based on integer multiples of the high-frequency excitation frequency fh; and the sideband neighborhood can be determined based on the sum or difference frequency position between the high-frequency excitation frequency fh and the low-frequency modulation frequency fl.

[0036] For example, when using composite excitation, the harmonic neighborhood can include frequency points within a preset bandwidth around 2fh, and the sideband neighborhood can include frequency points within a preset bandwidth around fh+fl, fh-fl, 2fh+fl, and 2fh-fl; the preset bandwidth can be determined based on the sampling frequency, frequency resolution, and structural response characteristics of the object being detected.

[0037] The landing gear damage identification device obtains the local enhancement amount of the harmonic neighborhood or sideband neighborhood relative to the corresponding local background; the local enhancement amount Es can be expressed by Equation (5): Es=(At-Ab) / (Ab+ε) (5); Where Es is the local enhancement amount, At is the target amplitude in the harmonic neighborhood or sideband neighborhood, and Ab is the corresponding local background amplitude; the target amplitude can be the peak amplitude, average amplitude, or integral amplitude in the target neighborhood; the local background amplitude can be the average amplitude, median amplitude, or smoothed amplitude of the adjacent frequency band outside the target neighborhood.

[0038] The landing gear damage identification device also acquires the low-frequency disturbance corresponding to the low-frequency modulation peak. The low-frequency disturbance El can be expressed by equation (6): El=(Al-Alb) / (Alb+ε) (6); Wherein, El is the low-frequency disturbance, Al is the amplitude of the low-frequency modulation main peak, and Alb is the amplitude of the low-frequency background. The purpose of the low-frequency disturbance is to determine whether the anomaly in the current response signal is caused by the overall excitation disturbance.

[0039] When the local enhancement Es reaches the weak spectral anomaly threshold, and the low-frequency disturbance El does not reach the overall low-frequency disturbance threshold, the landing gear damage identification device can determine that the damage-sensitive spectral evidence meets the early anomaly conditions. In this way, the landing gear damage identification device can consider that the response signal contains spectral evidence related to early closed cracks when weak enhancement occurs in the high-frequency harmonic neighborhood or sideband neighborhood, but the overall low-frequency disturbance does not increase synchronously.

[0040] S206. The landing gear damage identification device determines weak texture evidence in the center based on the central region of the FSDP image. In one possible implementation, the landing gear damage identification device determines the central region based on the polar coordinate radius of the FSDP image. Specifically, the landing gear damage identification device can identify the region with the polar coordinate center as the center and a normalized radius r less than or equal to the center radius threshold Rc as the central region. Alternatively, the landing gear damage identification device can also identify the inner circle region of a preset proportion in the FSDP image as the central region.

[0041] The landing gear damage identification device extracts the central texture index from the central area; the central texture index includes at least one of the following: point density, gray level dispersion, and radial short line number; among which, the point density Dc can be represented by the formula (7): Dc=Nc / Sc (7); where Dc is the central point density, Nc is the number of foreground points in the central area, and Sc is the area of ​​the central area; Landing gear damage identification equipment can use methods such as grayscale threshold segmentation, edge detection, or binarization to obtain the foreground point from the central area.

[0042] Gray-scale dispersion can be determined based on the variance, standard deviation, or gray-scale difference range of pixel gray-scale values ​​within the central region; the number of radial short lines can be obtained by counting the number of texture segments with lengths less than a preset length threshold along multiple radial directions of the central region after edge extraction.

[0043] The landing gear damage identification device compares the central texture index with the corresponding central weak texture threshold. When the central texture index reaches the corresponding central weak texture threshold, the landing gear damage identification device can determine that the central weak texture evidence meets the early anomaly condition. When the central texture index includes multiple indices such as point density, gray-level dispersion, and the number of radial short lines, the landing gear damage identification device obtains the central weak texture threshold corresponding to each index and compares them separately. As long as at least one central texture index reaches its corresponding threshold, the central weak texture evidence is determined to meet the early anomaly condition. In this way, when the central region of the FSDP image shows local densification, light gray texture diffusion, or an increase in short radial textures, the landing gear damage identification device can capture the central weak texture evidence corresponding to the early closed crack.

[0044] S207. Landing gear damage identification equipment uses the outer ring area of ​​FSDP images to determine obvious evidence of damage to the outer ring. In one possible implementation, the landing gear damage identification device determines the outer ring region based on the polar coordinate radius of the FSDP image. Specifically, the landing gear damage identification device can identify the annular region with a normalized radius r greater than or equal to the outer ring radius threshold Ro as the outer ring region; or, the landing gear damage identification device can also identify the outer ring region with a preset proportion in the FSDP image as the outer ring region.

[0045] The landing gear damage identification device extracts the outer ring line spacing index from the outer ring area; the outer ring line spacing index includes at least one of the line spacing change of adjacent radial lines and the continuous change of radial lines; the line spacing change Lo can be expressed by formula (8): Lo=[1 / (m-1)]·Σ(j=1tom-1)|dj-dj0|(8) Where Lo is the change in the outer circle line spacing, dj is the spacing between the j-th pair of adjacent radial lines in the current FSDP image, dj0 is the corresponding line spacing in the health baseline FSDP image, and m is the number of radial lines; if a health baseline FSDP image for a single component is not established, then dj0 can be the average of the corresponding line spacing in the same type of health sample set.

[0046] The variation in radial line continuity can be determined based on the number of break points, continuous length, or missing line proportion of the radial line. The landing gear damage identification device compares the outer ring spacing index with the corresponding outer ring significant damage threshold. If the outer ring spacing index reaches the corresponding outer ring significant damage threshold, the landing gear damage identification device determines that the evidence of significant damage to the outer ring meets the significant damage condition. If the outer ring spacing index does not reach the corresponding outer ring significant damage threshold, the landing gear damage identification device determines that the evidence of significant damage to the outer ring does not meet the significant damage condition.

[0047] S208. The landing gear damage identification device determines the detection results of the landing gear component under test based on damage-sensitive spectrum evidence, weak texture evidence in the center, and obvious damage evidence in the outer ring. See Figure 4 In one possible implementation, when both the damage-sensitive spectral evidence and the central weak texture evidence meet the early anomaly condition, and the outer ring obvious damage evidence does not meet the obvious damage condition, the landing gear damage identification device outputs an early closed crack risk result. This judgment indicates that: a damage-sensitive spectral weak anomaly has appeared in the response signal, and a weak texture anomaly has also appeared in the central region of the FSDP image, but the outer ring region has not yet formed an obvious line spacing change. At this critical juncture, the landing gear damage identification device does not directly regard the fact that the outer ring region is close to a healthy state as evidence of no damage, but rather determines the current state as an early closed crack risk state.

[0048] When the evidence of obvious damage to the outer ring meets the conditions for obvious damage, the landing gear damage identification device outputs the obvious damage identification result; the obvious damage identification result may include at least one of the following: damage existence result, damage location result, and damage scale result.

[0049] If the damage-sensitive spectral evidence does not meet the early anomaly condition, the weak texture evidence in the center does not meet the early anomaly condition, and the obvious damage evidence in the outer ring does not meet the obvious damage condition, the landing gear damage identification device can output a result without anomalies.

[0050] S209. After outputting the early closed crack risk result, the landing gear damage identification equipment triggers resampling processing; join Figure 5 In one possible implementation, the landing gear damage identification device re-collects the resampled response signal at the same target measurement point on the landing gear component under test; during resampling, the sensor position and ultrasonic excitation parameters can be kept unchanged to reduce the impact of changes in measurement point or excitation.

[0051] The landing gear damage identification device re-determines the damage-sensitive spectral evidence, central weak texture evidence, and outer ring obvious damage evidence based on the resampled response signal. If, after resampling, the damage-sensitive spectral evidence and central weak texture evidence still meet the early anomaly conditions, and the outer ring obvious damage evidence still does not meet the obvious damage conditions, the landing gear damage identification device outputs an early closed crack confirmation result. If, after resampling, the damage-sensitive spectral evidence or central weak texture evidence does not meet the early anomaly conditions, the landing gear damage identification device outputs an occasional interference result.

[0052] Optionally, the landing gear damage identification device can perform one or multiple resampling operations. In the case of multiple resampling operations, the landing gear damage identification device evaluates each resampling result. If the resampling results that meet a preset ratio satisfy the following conditions: If both the damage-sensitive spectrum evidence and the central weak texture evidence meet the early anomaly conditions, and the outer ring obvious damage evidence does not meet the obvious damage conditions, then the landing gear damage identification device will output an early closed crack confirmation result; if the preset ratio is not reached, then the landing gear damage identification device will output an occasional interference result or a result pending re-inspection.

[0053] S210, The landing gear damage identification device outputs the identification results; Optionally, the identification results may include the type of detection conclusion, the target measurement point identification, evidence of damage-sensitive spectrum, evidence of weak texture in the center, evidence of obvious damage in the outer ring, and recommended treatment actions; the type of detection conclusion may include no abnormal results, early closed crack risk results, early closed crack confirmation results, occasional interference results, results pending re-inspection, or obvious damage identification results; recommended treatment actions may include continued monitoring, resampling, manual verification, or maintenance inspection.

[0054] In one possible implementation, the thresholds for weak spectral anomalies, low-frequency overall disturbances, weak central texture, and significant outer ring damage can be predetermined based on a healthy sample set, an early damage sample set, and a significant damage sample set. The healthy sample set includes response signals and FSDP images collected from the landing gear component under test, or similar landing gear components, in a healthy state. The early damage sample set includes response signals and FSDP images collected under known early cracks, closed cracks, or minor fatigue damage conditions. The significant damage sample set includes response signals and FSDP images collected under known significant cracks or larger-scale damage conditions.

[0055] For example, for any indicator Q, the healthy mean μQ and healthy standard deviation σQ can be calculated based on the healthy sample set. μQ + λ1σQ can be determined as the early abnormality threshold, and μQ + λ2σQ can be determined as the significant damage threshold, where λ1 and λ2 are preset coefficients, and λ2 is greater than λ1. Alternatively, the early abnormality threshold can be determined based on the lower limit value of the corresponding indicator in the early damage sample set, and the significant damage threshold can be determined based on the lower limit value of the corresponding indicator in the significant damage sample set. The embodiments of this application do not limit the method of threshold calibration, as long as it can be used to distinguish between healthy state, early abnormal state, and significant damage state.

[0056] With the threshold calibration method described above, the landing gear damage identification equipment can convert early abnormal conditions and obvious damage conditions into an executable index comparison process, thereby avoiding the judgment of damage status based solely on subjective observation results.

[0057] In one example, after the landing gear damage identification device collects the response signal of the target measurement point, it first calculates the local enhancement amount Es in the harmonic neighborhood and the low-frequency disturbance amount El corresponding to the low-frequency modulation main peak. If the local enhancement amount Es reaches the weak spectral anomaly threshold and the low-frequency disturbance amount El does not reach the overall low-frequency disturbance threshold, then the landing gear damage identification device determines that the damage-sensitive spectral evidence meets the early anomaly conditions. At the same time, the landing gear damage identification device extracts the point density Dc from the central region of the FSDP image; if the point density Dc reaches the central weak texture threshold, then the landing gear damage identification device determines that the central weak texture evidence meets the early anomaly condition.

[0058] The landing gear damage identification equipment further calculates the change in outer ring spacing, Lo. If Lo does not reach the threshold for obvious damage to the outer ring, it means that no obvious damage characteristics have formed in the outer ring area. At this critical juncture, the landing gear damage identification equipment will not output a result of no abnormality, but will output a result of early closed crack risk and trigger resampling. If the same conditions are still met after resampling, then an early closed crack confirmation result will be output. If the spectral evidence or central evidence disappears after resampling, then an occasional interference result will be output.

[0059] Therefore, the embodiments of this application do not simply weight different features, but rather use the logical relationship of "weak spectral anomaly established, weak central texture established, and obvious outer ring damage not established" to identify the risk of early closed cracks. In this logic, the absence of evidence of obvious outer ring damage is not directly equivalent to a healthy state, but together with spectral evidence and central evidence, it constitutes the conditions for judging the risk of early closed cracks.

[0060] This application embodiment can also provide a landing gear damage identification device based on FSDP images. The device includes: a signal acquisition module, which is used to acquire the response signal generated by the landing gear component under test under ultrasonic excitation; an image generation module, which is used to generate an FSDP image based on the response signal and acquire the spectral features corresponding to the response signal; and a spectral evidence determination module, which is used to determine damage-sensitive spectral evidence based on the spectral features. The central evidence determination module is used to determine weak texture evidence in the center based on the central region of the FSDP image; the outer ring evidence determination module is used to determine obvious damage evidence in the outer ring based on the outer ring region of the FSDP image; the result output module is used to output an early closed crack risk result when both the damage-sensitive spectral evidence and the weak texture evidence in the center meet the early anomaly condition, and the obvious damage evidence in the outer ring does not meet the obvious damage condition.

[0061] This application also provides an electronic device; the electronic device includes a processor and a memory, wherein the memory stores a computer program; the processor is used to load and execute the computer program to implement the landing gear damage identification method based on FSDP images as described in any of the above method embodiments.

[0062] This application also provides a computer-readable storage medium; the computer-readable storage medium stores a computer program; the computer program is loaded and executed by a processor to implement the landing gear damage identification method based on FSDP images described in any of the above method embodiments.

[0063] The above embodiments are merely used to illustrate possible implementations of this application and are not intended to limit the scope of protection of this application; any modifications, equivalent substitutions or improvements made to this application within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A landing gear damage identification method based on FSDP images, characterized in that, The method includes: acquiring the response signal generated by the landing gear component under test under ultrasonic excitation; generating an FSDP image based on the response signal and acquiring the spectral features corresponding to the response signal; determining damage-sensitive spectral evidence based on the spectral features, determining central weak texture evidence based on the central region of the FSDP image, and determining outer ring obvious damage evidence based on the outer ring region of the FSDP image. If both the damage-sensitive spectral evidence and the central weak texture evidence meet the early anomaly condition, and the outer ring obvious damage evidence does not meet the obvious damage condition, the early closed crack risk result is output.

2. The method according to claim 1, characterized in that, The step of acquiring the response signal generated by the landing gear component under ultrasonic excitation includes: acquiring the detection configuration corresponding to the target measurement point of the landing gear component under test; and controlling the excitation sensor to apply ultrasonic excitation to the landing gear component under test according to the detection configuration. The response signal corresponding to the target measurement point is acquired by receiving a sensor; wherein, the detection configuration includes ultrasonic excitation parameters, sampling parameters and FSDP generation parameters.

3. The method according to claim 1, characterized in that, The step of generating an FSDP image based on the response signal and obtaining the spectral features corresponding to the response signal includes: performing frequency domain transformation on the response signal to obtain spectral data; generating the FSDP image based on the amplitude sequence in the spectral data; and extracting at least one of high-frequency carrier neighborhood features, harmonic neighborhood features, and sideband neighborhood features from the spectral data as the spectral features.

4. The method according to claim 3, characterized in that, The step of determining the damage-sensitive spectral evidence based on the spectral characteristics includes: obtaining the local enhancement amount of the harmonic neighborhood or the sideband neighborhood relative to the corresponding local background; and obtaining the low-frequency disturbance amount corresponding to the low-frequency modulation peak. If the local enhancement reaches the weak spectral anomaly threshold and the low-frequency perturbation does not reach the overall low-frequency perturbation threshold, the damage-sensitive spectral evidence is determined to meet the early anomaly condition.

5. The method according to claim 3, characterized in that, The step of generating the FSDP image based on the amplitude sequence in the spectrum data includes: performing logarithmic processing on the amplitude sequence to obtain a logarithmic amplitude sequence; Based on the logarithmic amplitude sequence, frequency lag coefficient, mirror symmetry plane rotation angle, and deflection angle gain, the radius and deflection angle of the frequency sampling point in polar coordinates are determined; the FSDP image is generated based on the radius and the deflection angle.

6. The method according to claim 1, characterized in that, The step of determining weak texture evidence in the center based on the central region of the FSDP image includes: determining the central region according to the polar coordinate radius of the FSDP image; extracting a central texture index from the central region; and determining the weak texture evidence in the center based on the central texture index; wherein the central texture index includes at least one of point density, grayscale dispersion, and number of radial short lines.

7. The method according to claim 6, characterized in that, The step of determining the weak texture evidence based on the central texture index includes: obtaining a weak texture threshold corresponding to each of the central texture indices; comparing each of the central texture indices with its corresponding weak texture threshold; and determining that a weak texture anomaly exists in the central region when at least one of the central texture indices reaches its corresponding weak texture threshold, and determining that the weak texture evidence satisfies the early anomaly condition.

8. The method according to claim 1, characterized in that, The step of determining evidence of significant damage to the outer ring based on the outer ring region of the FSDP image includes: determining the outer ring region according to the polar coordinate radius of the FSDP image; extracting the outer ring line spacing index from the outer ring region; and determining the evidence of significant damage to the outer ring based on the outer ring line spacing index. Among them, the outer ring line status index includes at least one of the following: the change in the line spacing between adjacent radial lines and the change in the continuity of radial lines.

9. The method according to claim 8, characterized in that, The step of determining evidence of obvious damage to the outer ring based on the outer ring spacing index includes: comparing the outer ring spacing index with the corresponding obvious damage threshold of the outer ring. If the outer ring spacing index reaches the corresponding outer ring significant damage threshold, the evidence of significant damage to the outer ring is determined to meet the significant damage condition; if the outer ring spacing index does not reach the corresponding outer ring significant damage threshold, the evidence of significant damage to the outer ring is determined not to meet the significant damage condition.

10. The method according to any one of claims 1 to 9, characterized in that, After outputting the early closed crack risk result, the method further includes: re-acquiring a resampled response signal at the same target measurement point on the landing gear component under test; re-determining the damage-sensitive spectrum evidence, the central weak texture evidence, and the outer ring obvious damage evidence based on the resampled response signal; after resampling, if the damage-sensitive spectrum evidence and the central weak texture evidence still meet the early anomaly conditions, and the outer ring obvious damage evidence still does not meet the obvious damage conditions, then outputting the early closed crack confirmation result; if the damage-sensitive spectrum evidence or the central weak texture evidence does not meet the early anomaly conditions after resampling, outputting the occasional interference result.

Images