Guided wave adaptive enhancement time reversal imaging method and system for structural damage of vehicle and computer program product

Abstract

The invention discloses a guided wave self-adaptive enhanced time reversal imaging method and system for vehicle structure damage and a computer program product, and belongs to the technical field of aircraft structure health monitoring. The envelope of the damage scattering signal is calculated through Shannon continuous complex wavelet transform and Hilbert transform, and m wave bands with the maximum peak value are selected as potential damage scattering signal wave bands; the damage factor of each potential wave band is calculated, the wave band with the maximum damage factor is a real damage scattering wave band, other signals are set to be zero, and therefore guided wave self-adaption enhancement is achieved, and the signal-to-noise ratio is increased; on the basis of extraction of a damage scattering wave band, a time reversal focusing imaging method is adopted, imaging results generated when all the sensors serve as excitation are superposed, and the point with the maximum pixel value is the damage position. The implementation process is accurate and efficient, and damage positioning can be achieved through the piezoelectric sensor monitoring network on the main load-bearing structure.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft structural health monitoring, and in particular to a method, system, and computer program product for guided wave adaptive enhanced time reversal imaging of vehicle structural damage. Background Art

[0002] Reusable launch vehicles have wide-range, ultra-high-speed, long-endurance, and reusable service requirements. They typically have thermal protection structures bonded to the outer surface of conventional airframe structures for insulation, resulting in multi-layered, heterogeneous structures. Due to the increasing amount of waste and its derivatives generated by space activities, the thermal protection structures of launch vehicles may be subject to hypervelocity impacts exceeding 3 km / s, posing a serious threat to their safe operation. Therefore, there is an urgent need to monitor the structural health of hypervelocity impact damage to the thermal protection structures of launch vehicles, allowing time for repair of the damage, launching a replacement vehicle, or changing the re-entry trajectory to prevent the damaged thermal protection structures from further exposure to high-temperature airflow, thereby ensuring the safe and reliable operation of the launch vehicle.

[0003] Structural health monitoring technology integrates stress, strain, acceleration, and piezoelectric sensors on or within the structure to acquire structural response signals related to the structural health state. Appropriate signal processing methods are then used to extract signal features related to structural damage. Combined with specific damage diagnosis and prediction methods, this technology enables monitoring of the structural health state and remaining life assessment. This enables condition-based maintenance, rather than scheduled maintenance, thus saving unnecessary maintenance costs. Structural health monitoring based on piezoelectric guided waves is one of the most promising technologies. Piezoelectric sensors are attached to the surface of the monitored structure or embedded within it. When guided waves generated by the piezoelectric sensors propagate through the structure, damage within the structure causes scattering and energy attenuation of the guided wave signals. This allows damage monitoring to be performed based on changes in the guided wave signal's characteristics. Guided wave structural health monitoring technology offers advantages such as high sensitivity, sensitivity to minor damage, a wide monitoring range, and the ability to monitor both online and offline.

[0004] Currently, little research has been conducted on hypervelocity impact damage monitoring of multilayer heterogeneous structures in reusable launch vehicles. Therefore, damage monitoring of thermal protection structures using piezoelectric sensor networks on the primary load-bearing structure is of great research significance. However, due to the significant difference between the high acoustic impedance of the primary load-bearing structure and the low acoustic impedance of the thermal protection structure, which creates a "mirror shielding" effect, the hypervelocity impact damage to the thermal protection structure has a very weak effect on the guided wave, easily obscuring the damage information, making damage monitoring difficult. Summary of the Invention

[0005] The present application aims to provide a method, system and computer program product for guided wave adaptive enhanced time reversal imaging of carrier structure damage, which solves the difficulties in extracting and monitoring damage information.

[0006] To achieve the above objectives, the technical solution of this application is:

[0007] A guided wave adaptive enhanced time reversal imaging method for vehicle structural damage, comprising:

[0008] The waveguide signal in a healthy state is collected as a reference signal, and the waveguide signal in a damaged state is collected as a damage signal. The damage signal is subtracted from the reference signal to obtain the damage scattering signal, and the Shannon continuous complex wavelet transform is used for noise reduction.

[0009] The Hilbert transform is used to calculate the damage scattering signal envelope, the local peak value and its position of the damage scattering signal envelope are found, and multiple bands with the largest peak values are selected as potential damage scattering signal bands;

[0010] Calculate the damage factor of each potential damage scattering signal band respectively. The potential damage scattering signal band with the largest damage factor is the real damage scattering signal band, and the remaining damage scattering signals are set to zero.

[0011] Based on the extraction of damage scattering signal bands, the time-reversal focusing imaging method is used to locate the damage. All imaging results are superimposed, and the point with the maximum pixel value is the damage location.

[0012] Optionally, the selecting of multiple bands with the largest peak values as potential damage scattered signal bands includes: adding windows to the reference signal and the damage signal respectively with the peak value as the center, and the window length is the length of the sinusoidal modulation 5 peak signal.

[0013] Optionally, the damage factor of each potential damage scattering signal band is calculated, the potential damage scattering signal band with the largest damage factor is defined as the real damage scattering signal band, and the remaining damage scattering signals are set to zero, including:

[0014] Define damage factors to quantify the impact of damage on guided wave signals;

[0015] Calculate the damage factor of each window and select the potential damage scattering signal band of the window with the largest damage factor as the most damage-sensitive band;

[0016] After determining the most damage-sensitive band, the potential damage scattering signal band with the largest damage factor is retained as the real damage scattering signal band, and the remaining damage scattering signals are set to zero. Finally, the damage scattering signal band is extracted.

[0017] Optionally, the impairment factor includes a normalized difference signal energy impairment factor, which is expressed as follows:

[0018]

[0019] Among them, DI m is the normalized difference signal energy damage factor of the mth window, H nor and D nor are the normalized reference signal and damage signal, is the normalized reference signal of the mth window, is the normalized damage signal of the mth window, and t represents the time variable.

[0020] Optionally, the extracted damage scattering signal band is represented as follows:

[0021]

[0022] Where S(t) is the damage scattering signal band, The window m with the largest damage factor max The reference signal, The window m with the largest damage factor max The damage signal is t, and t represents the time variable.

[0023] Optionally, the method of extracting the damage scattering signal band, using a time-reversal focusing imaging method to perform damage imaging positioning, and using a rotation excitation method to superimpose all imaging results, with the point with the maximum pixel value being the damage location, includes:

[0024] Step S41: Based on the extracted damage scattering signal band, the monitoring area is divided into p grid units with equal spacing, and j=1;

[0025] Step S42: Assume that the jth grid cell is the damage location;

[0026] Step S43: using a rotation excitation method, calculating the arrival delay of the damage scattered signal of the sensing end of each channel relative to the excitation end under different excitation ends;

[0027] Step S44: each damage scattered signal band is time-reversed after a fixed time length, and then delayed according to the arrival delay before being sent out, so as to generate a focus at the damage location;

[0028] Step S45: Calculate the energy value of the j-th grid cell in the monitoring area according to the time-reversal focusing synthesis result of the damage scattering signal band of each channel;

[0029] Step S46: Determine whether j=p is satisfied. If so, proceed to step S47; if not, j=j+1, and return to step S42;

[0030] Step S47: The energy values of each grid unit in the monitoring area are superimposed as pixel values to generate an image, and the point with the maximum pixel value is the actual damage position.

[0031] Optionally, the time-reversal focusing synthesis result of the damage scattering signal band of each channel is expressed as follows:

[0032]

[0033] Among them, v s (t,x j ,y j ) represents the composite signal at the damage position after time reversal focusing, (x j ,y j ) represents the damage location, t represents the time variable, s i represents the damage scattering signal band of the i-th channel, Δ i represents the arrival delay of the damage scattered signal from the sensing end of the i-th channel relative to the excitation end, k represents the number of sensing ends, τ represents the fixed time length, and t i represents the time variable of the damage scattering signal at the i-th sensor end.

[0034] Optionally, the calculation of the pixel value of the j-th grid unit in the monitoring area includes: calculating the sum of the squares of the synthetic signal moduli of the j-th grid unit according to the time-reversed focusing synthesis results of the damage scattering signals of each channel, obtaining the energy value of the j-th grid unit, and using the energy value as the pixel value of the j-th grid unit.

[0035] A guided wave adaptive enhanced time-reversal imaging system for carrier structure damage comprises: one or more processors; and a storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the guided wave adaptive enhanced time-reversal imaging method for carrier structure damage as described in any one of the above descriptions, and perform adaptive enhanced time-reversal imaging of guided waves according to the guided wave adaptive enhanced time-reversal imaging method for carrier structure damage.

[0036] A computer program product comprises a computer program, which, when executed by a processor, implements the steps of the method for guided wave adaptive enhanced time reversal imaging of vehicle structural damage as described in any one of the above.

[0037] The present application proposes a method, system and computer program product for adaptively enhanced time-reversal imaging of guided waves for damage to a carrier structure. The method monitors damage to the thermal protection structure through a piezoelectric monitoring network on the main load-bearing structure. The method calculates the damage factor of each potential damage scattering signal band, and the band with the maximum damage factor is the actual damage scattering band, while the remaining signals are set to zero, thereby achieving adaptive enhancement of guided waves and improving the signal-to-noise ratio. This solves the problem that the damage of multi-layer heterogeneous structures has a weak effect on guided waves, making it difficult to extract damage information. Based on the extracted damage scattering signal band, a time-reversal focusing imaging method is used to locate damage imaging. The imaging results of each piezoelectric sensor when it is excited are superimposed, and the point with the maximum pixel value is the damage position, thereby achieving accurate positioning of carrier structure damage. The method has broad application prospects in the field of aircraft structural health monitoring.

[0038] In order to make the above features and advantages of the application more obvious and easy to understand, the following embodiments are given and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of the guided wave adaptive enhanced time reversal imaging method for vehicle structural damage proposed in this application.

[0040] Figure 2 This is a flowchart of step S4 of this application.

[0041] Figure 3 Figure (a) is a schematic diagram of a multilayer heterostructure in one embodiment of the present application.

[0042] Figure 3 Figure (b) is a schematic diagram of the layout of sensors in the monitoring area on the multi-layer heterogeneous structure in one embodiment of the present application.

[0043] Figure 4 Figure (a) is a schematic diagram of signal changes before and after damage in one embodiment of the present application.

[0044] Figure 4 Figure (b) is a schematic diagram of scattering signals of different channel damage in one embodiment of the present application.

[0045] Figure 4 Figure (c) is a schematic diagram of the damage scattering signal after denoising using Shannon continuous complex wavelet transform in one embodiment of the present application.

[0046] Figure 5 Figure (a) is a schematic diagram of the damage scattering signal envelope using the time reversal imaging method.

[0047] Figure 5 Figure (b) is a schematic diagram of the damage scattering signal envelope phase modulation using the time reversal imaging method.

[0048] Figure 5 Figure (c) is a schematic diagram of the results of direct synthesis of the damage scattering signal envelope using the time reversal imaging method.

[0049] Figure 5 Figure (d) is a schematic diagram of the damage scattering signal envelope phase synthesis results directly using the time reversal imaging method.

[0050] Figure 5 Figure (e) is a schematic diagram of the damage imaging results directly using the time reversal imaging method.

[0051] Figure 6 Figure (a) is a schematic diagram of the changes in the guided wave signal before and after channel 1-2 is damaged.

[0052] Figure 6 Figure (b) is a schematic diagram of signal amplification in different bands of channels 1-2.

[0053] Figure 6 Figure (c) is a schematic diagram of the damage scattering signal in different bands of channel 1-2.

[0054] Figure 7 Figure (a) is a schematic diagram of the damage scattering signal envelope using the method of the present application.

[0055] Figure 7 Figure (b) is a schematic diagram of the damage scattering signal envelope phase modulation using the method of the present application.

[0056] Figure 7 Figure (c) is a schematic diagram of the results of direct synthesis of the damage scattering signal envelope using the method of the present application.

[0057] Figure 7 Figure (d) is a schematic diagram of the damage scattering signal envelope phase synthesis result using the method of the present application.

[0058] Figure 7 Figure (e) is a schematic diagram of the damage imaging results using the method of the present application.

[0059] Figure 8 Figure (a) is a schematic diagram of the damage imaging results at damage level a when all piezoelectric sensors are excited in turn.

[0060] Figure 8 Figure (b) is a schematic diagram of the damage imaging results at damage level b when all piezoelectric sensors are excited in turn.

[0061] Figure 8 Figure (c) is a schematic diagram of the damage imaging results at damage level c when all piezoelectric sensors are excited in turn.

[0062] In the drawings, like reference numerals refer to the same drawing elements. DETAILED DESCRIPTION

[0063] To make the purpose and technical solutions of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be clearly and completely described below in conjunction with the drawings of the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the described embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0064] The present application provides a method, system and computer program product for guided wave adaptive enhanced time reversal imaging of carrier structural damage, which are used for guided wave adaptive enhanced time reversal imaging of carrier structural damage of multi-layer heterostructure.

[0065] See also Figure 1 , Figure 1 The flowchart of the guided wave adaptive enhanced time reversal imaging method for carrier structure damage proposed in this application is as follows: The guided wave adaptive enhanced time reversal imaging method for carrier structure damage proposed in this application comprises: steps S1 to S4.

[0066] Step S1: collecting a healthy waveguide signal as a reference signal and a damaged waveguide signal as a damage signal. Subtracting the damage signal from the reference signal to obtain a damage scattering signal, and performing denoising using Shannon continuous complex wavelet transform.

[0067] Step S2: Calculate the damage scattering signal envelope using Hilbert transform, find the local peak value and position of the damage scattering signal envelope, and select m bands with the largest peak values as potential damage scattering signal bands;

[0068] Step S3, respectively calculating the damage factor of each potential damage scattering signal band, the potential damage scattering signal band with the largest damage factor is the real damage scattering signal band, and the remaining damage scattering signals are set to zero;

[0069] Step S4: Based on the extracted damage scattering signal band, a time-reversal focusing imaging method is used to perform damage imaging and positioning. All imaging results are superimposed, and the point with the maximum pixel value is the damage position.

[0070] In step S1, see Figure 1In step S1, the waveguide signal in a healthy state is collected as a reference signal, and the waveguide signal in a damaged state is collected as a damage signal. The damage signal is subtracted from the reference signal to obtain a damage scattering signal, and the Shannon continuous complex wavelet transform is used for noise reduction.

[0071] As an example, k piezoelectric sensors are arranged on the inner surface of a multilayer heterostructure serving as the main load-bearing structure. The piezoelectric sensors are excited in turn. Each piezoelectric sensor acts as an excitation end to generate an excitation signal, and the remaining piezoelectric sensors act as sensing ends to receive the excitation signal. This results in a piezoelectric monitoring network consisting of y excitation-sensing channels, where y is expressed as follows:

[0072] y=k 2 .

[0073] Furthermore, holes are punched on the surface of the thermal protection structure of the multi-layer heterostructure to simulate hypervelocity impact damage. Based on the set piezoelectric monitoring network, the guided wave signal of the multi-layer heterostructure in a healthy state is collected as a reference signal, and the guided wave signal of the multi-layer heterostructure in a damaged state is collected as a damage signal. The damage signal is subtracted from the reference signal to obtain the damage scattering signal, and the damage scattering signal is calculated.

[0074] Furthermore, since the damage of multilayer heterostructures has a weak effect on guided waves, the damage scattering signal is basically submerged by noise. Therefore, the Shannon continuous complex wavelet transform is used to extract the frequency component of the guided wave signal with the same center frequency and bandwidth as the damage scattering signal, which plays a role in reducing the noise of the damage scattering signal.

[0075] In step S2, see Figure 1 In step S2, the Hilbert transform is used to calculate the damage scattering signal envelope, the local peak value and position of the damage scattering signal envelope are found, and the m bands with the largest peak values are selected as potential damage scattering signal bands.

[0076] As an example, m is usually set to 2.

[0077] Theoretically, the maximum value of the damage scattering signal envelope corresponds to the flight time of the damage scattering signal. However, since the damage of the multilayer heterostructure has a very weak impact on the guided wave signal, the maximum value of the damage scattering signal envelope may correspond to the flight time of the direct wave of the damage scattering signal, and the second maximum value of the damage scattering signal envelope may correspond to the flight time of the damage scattering signal.

[0078] As an example, the Hilbert transform is used to calculate the envelope of the damage scattering signal, and the local peak value and its position of the damage scattering signal envelope are found. All peak values are sorted in descending order of amplitude, and the m bands with the largest peak amplitude are selected. The reference signal and the damage signal are windowed with the peak value as the center, and the window length is N. N is usually the length of the sinusoidal modulation 5-peak signal. The reference signal is recorded as Hm (t), the damage signal is denoted as D m (t), where m represents the number of different band windows; t = 1, 2, ..., N represents the time variable.

[0079] In step S3, see Figure 1 In step S3, the damage factor of each potential damage scattering signal band is calculated respectively. The potential damage scattering signal band with the largest damage factor is the real damage scattering signal band, and the remaining damage scattering signals are set to zero.

[0080] As an example, step S3 includes: steps S31 to S33.

[0081] Step S31: defining a damage factor to quantify the impact of damage on the guided wave signal;

[0082] Step S32: Calculate the damage factors of m windows and select the window m with the largest damage factor. max The potential damage scattering signal band is taken as the most damage sensitive band;

[0083] Step S33: After determining the most damage-sensitive band, retain the potential damage scattering signal band with the largest damage factor as the real damage scattering signal band, set the remaining damage scattering signals to zero, and finally extract the damage scattering signal band S(t).

[0084] As an example, in step S31, defining the damage factor includes: defining multiple damage factors.

[0085] In one embodiment of the present application, the impairment factor is defined as the normalized difference signal energy impairment factor DI, and the impairment factor calculation formula of the mth window is as follows:

[0086]

[0087] Among them, DI m is the normalized difference signal energy damage factor of the mth window, H nor and D nor are the normalized reference signal and damage signal, is the normalized reference signal of the mth window, is the normalized damage signal of the mth window, and t represents the time variable.

[0088] As an example, in step S32, the window m with the largest damage factor is max It is expressed as follows:

[0089]

[0090] Among them, DI m is the damage factor of the mth window.

[0091] As an example, the damage scattering signal band extracted in step S33 is represented as follows:

[0092]

[0093] Where S(t) is the damage scattering signal band, The window m with the largest damage factor max The reference signal, The window m with the largest damage factor max The damage signal is t, and t represents the time variable.

[0094] In step S4, see Figure 1 In step S4, based on the extraction of the damage scattering signal band, the time-reversal focusing imaging method is used to perform damage imaging and positioning. The alternating excitation method is used to superimpose all imaging results, and the point with the maximum pixel value is the damage location.

[0095] As an example, see Figure 2 , Figure 2 This is a flowchart of step S4, which includes steps S41 to S47.

[0096] Step S41: Based on the extracted damage scattering signal band, the monitoring area is divided into p grid units with equal spacing, and j=1;

[0097] Step S42: Assume that the jth grid unit (x j ,y j ) is the injury location;

[0098] Step S43: Using the alternate excitation method, calculate the arrival delay Δ of the damage scattered signal of the sensing end of each channel relative to the excitation end under different excitation ends. i .

[0099] As an example, when the first piezoelectric sensor is the excitation end, the arrival delay of the damage scattered signal band of each piezoelectric sensor relative to the first piezoelectric sensor is calculated. The arrival delay Δ of the damage scattered signal band of the i-th sensor relative to the excitation sensor is i , which is expressed as follows:

[0100]

[0101] Among them, r i is the distance from the i-th piezoelectric sensor to the damage location; r1 is the distance from the first piezoelectric sensor to the damage location; c g is the group velocity of the guided wave signal propagation.

[0102] Step S44: each damage scattered signal band is time-reversed after taking a fixed time length, and then delayed according to the arrival delay before being sent out to generate a focus at the damage position.

[0103] As an example, when the first piezoelectric sensor is the excitation end, each damage scattering signal band is taken with a fixed time length τ and then time-reversed τ-t1, τ-t2, ..., τ-t k , and then delay Δ1, Δ2, …, Δ k It is emitted later and focuses at the damage site.

[0104] Among them, t k is the time variable of the damage scattering signal at the kth sensing end, that is, the time variable of the damage scattering signal received by the kth piezoelectric sensor, Δ k is the arrival delay of the damage scattered signal band of the kth piezoelectric sensor relative to the exciting piezoelectric sensor.

[0105] Furthermore, after time-reversal focusing, the damage position (x j ,y j ) of the composite signal v s (t,x j ,y j ) is expressed as:

[0106]

[0107] Among them, t represents the time variable, s i represents the damage scattering signal band of the i-th channel; Δ i represents the arrival delay of the damage scattered signal at the sensing end of the i-th channel relative to the excitation end. If (x j ,y j ) is not the damage location, then the amplitude of the synthesized signal is not as large as the amplitude of the signal focused on the actual damage location.

[0108] Step S45: Calculate the pixel value of the j-th grid unit in the monitoring area according to the time-reversal focusing synthesis result of the damage scattering signal band of each channel.

[0109] As an example, according to the time-reversed focusing synthesis results of the damage scattering signals of each channel, the square sum of the synthetic signal modulus of the j-th grid unit is calculated respectively to obtain the energy value of the j-th grid unit, and the energy value is used as the pixel value Sum of the j-th grid unit. j .

[0110] Step S46: Determine whether j=p is satisfied. If so, proceed to step S47; if not, set j=j+1 and return to step S42.

[0111] Step S47: The energy value Sum of each grid cell in the monitoring area j The image is generated by superimposing pixel values, and the point with the maximum pixel value is the actual damage location.

[0112] Since the selection of different piezoelectric sensors as excitations will affect the accuracy of damage location, the damage location accuracy is usually higher when the piezoelectric sensor close to the damage location is used as the excitation. Therefore, to improve the accuracy and reliability of damage location, the pixel values of the imaging results when all piezoelectric sensors are excited in turn are superimposed, and the point with the maximum pixel value is the actual damage location.

[0113] The present application also provides a guided wave adaptive enhanced time reversal imaging system for carrier structure damage, comprising: one or more processors; a storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the guided wave adaptive enhanced time reversal imaging method for carrier structure damage as described above, and perform adaptive enhanced time reversal imaging of the guided wave according to the guided wave adaptive enhanced time reversal imaging method for carrier structure damage.

[0114] The present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the guided wave adaptive enhanced time reversal imaging method for vehicle structural damage as described above.

[0115] In one embodiment of this application, please refer to Figure 3 , Figure 3 Figure (a) is a schematic diagram of the carrier structure in one embodiment of the present application. Figure 3Figure (b) is a schematic diagram of the sensor layout for the monitoring area on the carrier structure in one embodiment of the present application. The carrier structure features a multi-layered, heterogeneous structure, a crucial thermal protection feature for reusable carriers. It primarily consists of an insulating tile thermal protection structure 31, strain isolation pads 32, and a T300 main load-bearing structure 33. Each layer is bonded together with high-temperature-resistant silicone rubber. The insulating tile thermal protection structure 31 measures 250mm x 250mm x 25mm, the strain isolation pads 32 measure 250mm x 250mm x 3mm, and the T300 main load-bearing structure 33 measures 350mm x 350mm x 2mm. An electric drill was used to drill holes in the thermal protection structure to simulate hypervelocity impact damage. The damage location P was at coordinates (-50 mm, 50 mm), and the damage shape was cylindrical. The damage severity gradually increased, from damage level a (diameter 13 mm, depth 15 mm), to damage level b (diameter 19 mm, depth 15 mm), and to damage level c (diameter 19 mm, depth 25 mm). Piezoelectric sensors were placed on the inner surface of the T300 main load-bearing structure 33. Eight piezoelectric sensors, specifically piezoelectric sensor 1 through piezoelectric sensor 8, were evenly distributed around the structure, covering a monitoring area of 250 mm x 250 mm. The piezoelectric sensors were alternately excited, resulting in a piezoelectric monitoring network consisting of 56 excitation-sensing channels. This piezoelectric monitoring network on the T300 main load-bearing structure 33 was used to locate the hole damage location P on the thermal protection structure 31 of the thermal insulation tile. The following analysis uses guided wave monitoring of damage level c as an example.

[0116] Please continue reading Figure 4 , Figure 4 The influence of damage on the guided wave signals of different channels is given when piezoelectric sensor 1 is used as the excitation and piezoelectric sensors 2 to 8 are used as the responses. Figure 4 Figure (a) is a schematic diagram of signal changes before and after damage in one embodiment of the present application. Figure 4 In (a), it can be seen that the signals before and after the damage basically overlap, and the damage has a weak effect on the guided wave; Figure 4 Figure (b) is a schematic diagram of different channel damage scattering signals in one embodiment of the present application. Figure 4 As can be seen from Figure (b), the maximum value of the damage scattering signal is less than 0.4V, and the damage information is basically submerged by the noise. In order to reduce the influence of noise on the damage scattering signal, the Shannon continuous complex wavelet transform is used for noise reduction. Figure 4 Figure (c) is a schematic diagram of the damage scattering signal after denoising using Shannon continuous complex wavelet transform in one embodiment of the present application. Figure 4 In Figure (c), obvious signal wave packets can be seen, and channels 1-2, 1-3, and 1-4 close to the damage are relatively significantly affected by the damage.

[0117] Please continue reading Figure 5 , Figure 5 Schematic diagram of the results of directly using the time-reversal focusing imaging method. Figure 5 Figure (a) is a schematic diagram of the damage scattering signal envelope using the time reversal imaging method; Figure 5 Figure (b) is a schematic diagram of the damage scattering signal envelope phase modulation using the time reversal imaging method; Figure 5 Figure (c) is a schematic diagram of the direct synthesis of the damage scattering signal envelope using the time reversal imaging method; Figure 5 Figure (d) shows the damage scattering signal envelope phase synthesis result using the time-reversal imaging method. The damage scattering signal envelope is phase modulated based on the arrival delays from piezoelectric sensors 2 to 8 to piezoelectric sensor 1. Figure 5 Figure (e) is a schematic diagram of the damage imaging results using the time-reversal focusing imaging method, with a positioning error of 74.8 mm. Figure 5 It can be seen that the amplitude of the damage scattering signal envelope after phase modulation and synthesis is not significantly improved, resulting in the inability to locate the damage.

[0118] Figure 6 Taking channel 1-2 as an example, the reasons why the damage cannot be located are analyzed. Figure 6 Figure (a) shows the change of guided wave signals before and after the 1-2 channel is damaged. Figure 6 As can be seen in Figure (a), the changes in the guided wave signals before and after damage are very weak, and the healthy and damaged signals basically overlap. In order to further observe the impact of damage on the guided wave, three typical bands were selected for amplification to make the maximum amplitude range of the signal consistent. Figure 6 Figure (b) is a schematic diagram of signal amplification in different bands of channel 1-2. Figure 6 As shown in (b), band 11 is the direct signal band, band 12 is the damage influence band obtained by theoretical calculation, and band 13 is the boundary reflection band. Figure 6Figure (c) shows the damage scattering signal at different wavelengths for channel 1-2. Since channel 1-2 does not directly pass through the damage, band 11 is unaffected by the damage, and the signal barely changes before and after the damage. However, due to its maximum original signal amplitude and the influence of noise and system repeatability, the damage scattering signal amplitude is the largest. Therefore, the damage scattering signal in band 11 is not the true damage scattering signal. Band 12 is the true damage-affected band. After amplification, the signal amplitude and phase change before and after the damage can be seen. The corresponding damage scattering signal amplitude is also relatively large, consistent with the influence of damage on waveguides. Band 13 is the boundary reflection signal. Due to its smaller signal amplitude, band 13 is more susceptible to noise and system repeatability. After amplification, the signal waveform changes significantly before and after the damage. However, due to its smaller original signal amplitude, the damage scattering signal amplitude is also small. When using time-reversal imaging algorithms for damage localization, the band corresponding to the maximum damage scattering signal amplitude is defaulted as the damage-affected band, resulting in the inability to locate the damage.

[0119] As an example, Figure 7 The results of extracting the true damage scattering signal from a damage scattering signal containing noise and system repeatability errors using the method of this application are shown. First, the two bands with the largest local peaks in the damage scattering signal envelope are selected as potential damage scattering signal bands. Then, the normalized difference signal energy damage factor is calculated for each potential band. The band with the largest damage factor is the true damage scattering band. Finally, based on the intercepted damage scattering bands, time-reversal focusing imaging is used to perform damage imaging and localization. Figure 7 Figure (a) is a schematic diagram of the damage scattering signal envelope using the method of the present application; Figure 7 Figure (b) is a schematic diagram of the damage scattering signal envelope phase modulation using the method of the present application; Figure 7 Figure (c) is a schematic diagram of the result of direct synthesis of the damage scattering signal envelope using the method of the present application; Figure 7 Figure (d) is a schematic diagram of the damage scattering signal envelope phase synthesis result using the method of the present application. The damage scattering signal envelope is phase modulated according to the arrival delays from piezoelectric sensors 2 to 8 to piezoelectric sensor 1. Figure 7 Figure (e) is a schematic diagram of the damage imaging result using the method of this application, with a positioning error of 4.4 mm. Figure 7As can be seen from Figure (b), channels 1-2, 1-3, and 1-4 are significantly affected by damage and play a dominant role in the damage localization results. The extracted true damage scattering signal envelope can be focused after phase modulation. The amplitude of the synthesized damage scattering signal envelope of all channels after phase modulation is increased by 21.4% compared to the direct synthesis of the signal envelope. The damage can be accurately located, and the error between the damage imaging result and the actual damage boundary is 4.4 mm.

[0120] As an example, Figure 8 The given imaging result is a synthesis of the imaging results when all piezoelectric sensors are stimulated in turn. Figure 8 Figure (a) is a schematic diagram of the damage imaging results under damage level a when all piezoelectric sensors are stimulated in turn. Figure 8 Figure (b) is a schematic diagram of the damage imaging results under damage level b when all piezoelectric sensors are stimulated in turn. Figure 8 Figure (c) is a schematic diagram of the damage imaging results at different damage levels when all piezoelectric sensors are excited in turn. It can be seen from the figure that the imaging results at different damage levels can be accurately located. As the damage degree increases, the damage localization accuracy gradually improves.

[0121] The present application proposes a method, system, and computer program product for adaptively enhanced time-reversal imaging of guided waves for damage to a carrier structure. The method monitors damage to a thermal protection structure through a piezoelectric monitoring network on the main load-bearing structure. The method calculates the damage factor for each potential damage scattering signal band, where the band with the maximum damage factor is the true damage scattering band, and the remaining signals are set to zero. This achieves adaptive enhancement of the guided waves, improves the signal-to-noise ratio, and solves the problem of difficulty in extracting damage information due to the weak effect of carrier structure damage on the guided waves. Based on the extracted damage scattering signal band, a time-reversal focusing imaging method is used for damage imaging and positioning. The imaging results of each piezoelectric sensor when stimulated are superimposed, and the point with the maximum pixel value is the damage position. This achieves accurate positioning of carrier structure damage, and has broad application prospects in the field of aircraft structural health monitoring.

[0122] Although the present application has been disclosed above with reference to the embodiments, they are not intended to limit the present application. Anyone with ordinary knowledge in the technical field may make slight changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be determined by the scope of the appended patent application.

Claims

1. A method for adaptively enhanced time-reversal imaging of vehicle structural damage using guided waves, characterized in that: include, The waveguide signal in a healthy state is collected as a reference signal, and the waveguide signal in a damaged state is collected as a damage signal. The damage signal is subtracted from the reference signal to obtain the damage scattering signal, and the Shannon continuous complex wavelet transform is used for noise reduction. The Hilbert transform is used to calculate the damage scattering signal envelope, the local peak value and its position of the damage scattering signal envelope are found, and multiple bands with the largest peak values are selected as potential damage scattering signal bands; Calculate the damage factor of each potential damage scattering signal band respectively. The potential damage scattering signal band with the largest damage factor is the real damage scattering signal band, and the remaining damage scattering signals are set to zero. Based on the extraction of damage scattering signal bands, the time-reversal focusing imaging method is used to locate the damage. All imaging results are superimposed, and the point with the maximum pixel value is the damage location.

2. The method for guided wave adaptive enhanced time reversal imaging of vehicle structural damage according to claim 1, characterized in that: The selecting of multiple bands with the largest peak values as potential damage scattered signal bands includes: adding windows to the reference signal and the damage signal respectively with the peak values as the center, and the window length is the length of the sinusoidal modulation 5 peak value signal.

3. The guided wave adaptive enhanced time reversal imaging method for vehicle structural damage according to claim 2, characterized in that: The damage factor of each potential damage scattering signal band is calculated, the potential damage scattering signal band with the largest damage factor is defined as the real damage scattering signal band, and the remaining damage scattering signals are set to zero, including: Define damage factors to quantify the impact of damage on guided wave signals; Calculate the damage factor of each window and select the potential damage scattering signal band of the window with the largest damage factor as the most damage-sensitive band; After determining the most damage-sensitive band, the potential damage scattering signal band with the largest damage factor is retained as the real damage scattering signal band, and the remaining damage scattering signals are set to zero. Finally, the damage scattering signal band is extracted.

4. The method for guided wave adaptive enhanced time reversal imaging of vehicle structural damage according to claim 3, wherein: The damage factor includes the normalized difference signal energy damage factor, which is expressed as follows: Among them, DI m is the normalized difference signal energy damage factor of the mth window, H nor and D nor are the normalized reference signal and damage signal, is the normalized reference signal of the mth window, is the normalized damage signal of the mth window, and t represents the time variable.

5. The method for guided wave adaptive enhanced time reversal imaging of vehicle structural damage according to claim 3, wherein: The extracted damage scattering signal band is expressed as follows: Where S(t) is the damage scattering signal band, The window m with the largest damage factor max The reference signal, The window m with the largest damage factor max The damage signal is t, and t represents the time variable.

6. The method for guided wave adaptive enhanced time reversal imaging of vehicle structural damage according to claim 1, wherein: The method is based on extracting the damage scattering signal band, adopting the time-reversal focusing imaging method to perform damage imaging positioning, adopting the alternating excitation method to superimpose all imaging results, and the point with the maximum pixel value is the damage position, including: Step S41: Based on the extracted damage scattering signal band, the monitoring area is divided into p grid units with equal spacing, and j=1; Step S42: Assume that the jth grid cell is the damage location; Step S43: using a rotation excitation method, calculating the arrival delay of the damage scattered signal of the sensing end of each channel relative to the excitation end under different excitation ends; Step S44: each damage scattered signal band is time-reversed after a fixed time length, and then delayed according to the arrival delay before being sent out, so as to generate a focus at the damage location; Step S45: Calculate the energy value of the j-th grid cell in the monitoring area according to the time-reversal focusing synthesis result of the damage scattering signal band of each channel; Step S46: Determine whether j=p is satisfied. If so, proceed to step S47; if not, j=j+1, and return to step S42; Step S47: The energy values of each grid unit in the monitoring area are superimposed as pixel values to generate an image, and the point with the maximum pixel value is the actual damage position.

7. The method for guided wave adaptive enhanced time reversal imaging of vehicle structural damage according to claim 6, characterized in that: The time-reversal focusing synthesis results of the damage scattering signal bands of each channel are shown as follows: Among them, v s (t,x j ,y j ) represents the composite signal at the damage position after time reversal focusing, t represents the time variable, (x j ,y j ) represents the damage location, s i represents the damage scattering signal band of the i-th channel, Δ i represents the arrival delay of the damage scattered signal from the sensing end of the i-th channel relative to the excitation end, k represents the number of sensing ends, τ represents the fixed time length, and t i represents the time variable of the damage scattering signal at the i-th sensor end.

8. The method for guided wave adaptive enhanced time reversal imaging of vehicle structural damage according to claim 7, characterized in that: The pixel value of the j-th grid cell in the monitoring area is calculated, including: calculating the square sum of the synthetic signal modulus values of the j-th grid cell according to the time reversal focusing synthesis results of the damage scattering signals of each channel, obtaining the energy value of the j-th grid cell, and using the energy value as the pixel value of the j-th grid cell.

9. A guided wave adaptive enhanced time reversal imaging system for vehicle structural damage, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the method for adaptively enhanced time-reversal imaging of guided waves for vehicle structural damage according to any one of claims 1 to 8, and perform adaptively enhanced time-reversal imaging of guided waves according to the method for adaptively enhanced time-reversal imaging of guided waves for vehicle structural damage.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of the guided wave adaptive enhanced time reversal imaging method for vehicle structure damage according to any one of claims 1 to 8.

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