CN109884187A - A kind of compressed sensing based supersonic guide-wave field damage detecting method suitable for plate structure - Google Patents
A kind of compressed sensing based supersonic guide-wave field damage detecting method suitable for plate structure Download PDFInfo
- Publication number
- CN109884187A CN109884187A CN201910141759.4A CN201910141759A CN109884187A CN 109884187 A CN109884187 A CN 109884187A CN 201910141759 A CN201910141759 A CN 201910141759A CN 109884187 A CN109884187 A CN 109884187A
- Authority
- CN
- China
- Prior art keywords
- wave field
- source
- damage
- compressed sensing
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
The invention discloses a kind of compressed sensing based supersonic guide-wave field damage detecting method suitable for plate structure, step includes: building SLDV sampling system；It determines space sparse sampling mesh coordinate, sample coordinate is inputted into SLDV sampling system, acquire ultrasonic guided wave signals under health status and containing faulted condition respectively, by two groups of signal subtractions, obtain the difference signal comprising damage scattered information；The position of damage scattering source is estimated at random, obtains hypothesis source coordinate；Compressed sensing equation is established, and solves the excitation function in hypothesis source with base tracking noise reduction algorithm；All-wave field is reconstructed using the excitation function acquired, RMS imaging is carried out to the all-wave field of reconstruct, obtains damage imaging result.Compressed sensing technology is applied to supersonic guide-wave field damage check field by the present invention, wave field reconstruct and damage imaging are carried out using the sparse sampling signal of spatially regular distribution, 90% or more the time of measuring reduction of all-wave field can be will acquire, while being obtained with the full wave field coherence factor that measures close to 0.8 reconstruct wave field.
Description
Technical field
The invention belongs to technical field of nondestructive testing more particularly to a kind of suitable for the compressed sensing based of plate structure
Supersonic guide-wave field damage detecting method.
Background technique
Plate structure as a kind of common structure type, the fields such as aerospace, communications and transportation and petroleum works all
There is very extensive application.Thin-slab structure is during long-term military service by the effect of the factors such as load and environment, it may appear that no
With the structural damage of degree.Therefore the generation that prevention safety accident is not only facilitated to the safety detection of this class formation, can also be with
Avoid unnecessary economic loss.
Currently, be suitable for plate structure conventional lossless detection method mainly have: Magnetic Flux Leakage Inspecting, Ultrasonic C-Scan, infiltration with
And acoustic emission detection etc..Wherein, although Magnetic Flux Leakage Inspecting and Ultrasonic C-Scan detection method are using comparatively extensive, its disadvantage
It is that detection process is time-consuming and laborious, detection efficiency is low；Infiltration hair is succinct convenient, but can only detect surface damage；Acoustic emission detection
More complicated external condition, and the interference vulnerable to noise signal are usually required, signal analysis is difficult.
Supersonic guide-wave can be propagated over long distances along waveguiding structure and decay small, and detection range is big, and damage to different type
Sensitivity is highly suitable for that damages all kinds of in the structures such as large-area sheet, shell, pipeline are detected and assessed, great development prospect.
Traditional ultrasonic guided wave detecting method often realizes the positioning of damage according to the transition time between distributed thinned array, but limited
In spatial resolution, it is difficult to make accurate assessment for features such as scale, the orientations of damage.It is how general using non-contact scanning type laser
Height in plate structure tested region can be obtained by strangling vialog (Scanning Laser Doppler Vibrometer, SLDV)
Spatial resolution guided wave field, and the variation of wave field characteristics caused by damaging is obtained accordingly, can reach to the mesh for damaging accurate assessment
's.However SLDV needs point by point repeatedly measurement to improve signal-to-noise ratio when scanning, it is not only time-consuming that intensive scanning forms mass data, but also
Great challenge is brought to storage, transmission and the signal analysis of data.
It is measured by means of SLDV, seeks efficient data sampling strategy, sparse reconstruct all-wave field, then be to reach efficient evaluations
One of effective means of damage characteristic.Recently, scholar proposes that compressed sensing based method comes sparse reconstruct all-wave field, however
Its method needs spatially stochastical sampling, and commercial SLDV system need additional assemblies to support random measurement, thus realize this method compared with
For difficulty.Herein with uniform sparse sampling strategic complement stochastic sampling strategy, and it will assume that source is set as random distribution, not only
Requirement when being able to satisfy building compressed sensing equation to sensing matrix, moreover it is possible to meet SLDV measure setup requirement, save system
Cost.
Summary of the invention
The present invention according to problems of the prior art, propose it is a kind of suitable for plate structure based on compressed sensing
Supersonic guide-wave field damage detecting method.
The technical solution adopted in the present invention is as follows:
A kind of compressed sensing based supersonic guide-wave field damage detecting method suitable for plate structure, comprising:
Construct SLDV sampling system；
Determine space sparse sampling mesh coordinate, by sample coordinate input SLDV sampling system, respectively health status with
Containing ultrasonic guided wave signals are acquired under faulted condition, by two groups of signal subtractions, the difference signal comprising damage scattered information is obtained；
The position of damage scattering source is estimated at random, obtains hypothesis source coordinate；
Compressed sensing equation is established, and solves the excitation function in hypothesis source with base tracking noise reduction algorithm；
All-wave field is reconstructed using the excitation function acquired, RMS imaging is carried out to the all-wave field of reconstruct, obtains damage imaging knot
Fruit.
Further, SLDV sampling system is constructed, wherein SLDV sampling system includes: computer, scanning type laser Doppler
Vialog (Scanning Laser Doppler Vibrometer, SLDV), arbitrarily signal generating device, power amplifier, PZT
Driving source etc..
Further, it determines space sparse sampling mesh coordinate, sample coordinate is inputted into SLDV sampling system, respectively in health
State, by two groups of signal subtractions, obtains the difference comprising damage scattered information with containing ultrasonic guided wave signals are acquired under faulted condition
Signal, used in sparse sampling grid be equidistant grid.
Further, the step of position of damage scattering source being estimated at random, obtains hypothesis source coordinate are as follows:
A, determination assumes source region, covers the position in there may be source as far as possible；
B, uniform grid is set in the region, grid spacing d is no more than the half of guided wave field minimum wavelength；
C, inside each grid, with grid element center point (x0,y0) on the basis of put at random take a little, generate hypothesis source coordinate (x,
Y):
Wherein random is uniformly random function.
Further, compressed sensing equation is established, and the excitation function for assuming source is solved with base tracking noise reduction algorithm,
Detailed process includes:
A, assume that the excitation function in all hypothesis sources is isotropic, the transmitting square in building hypothesis source to sparseness measuring point
Battle array A ∈ CM×N, wherein M and N respectively indicates sparseness measuring point quantity and assumes source quantity, CM×NIndicate the complex number space of M × N.A
In m row s column element be that the pumping signal in s-th of hypothesis source travels to the transmission function of m-th of measuring point, only considering single mode
When, it indicates are as follows:
Wherein dM, sIt is hypothesis source at a distance from measuring point,To assume the wave on source to driving source direction under mode u
Number, is estimated using dispersion relation known to material；
B, by structure under health status and containing the signal y measured under faulted condition1With y2Subtract each other, obtain difference signal y,
Joint transfer matrix A constructs compressed sensing equation Av=y, tracks Method of Noise by base and solves hypothesis source forcing function v.
Further, all-wave field is reconstructed using the excitation function acquired, detailed process includes:
A, select reconstruction region in surface of test piece, determine coordinate to reconstruction point in this region, building assume source point to
The transfer matrix A ' of reconstruction point calculates the frequency domain wave field W=A ' v to reconstruction point；
B, inverse Fourier transform is done to W, obtains the time domain wavefield of reconstruction point.
To assess quality reconstruction, definition reconstructs wave field and the coherence coefficient of true wavefield is as follows:
Wherein SR, M(f) it indicates to reconstruct wave field at frequency f and measures the cross-spectral density of wave field, SR(f) and SM(f) divide
Wave field Wei not be reconstructed at frequency f and measures the autopower spectral density of wave field.C (f) is being calculated into frequency range (f1,f2) in take mean value
CmeanIndex as evaluation wave field quality reconstruction.
Further, RMS imaging is carried out to the all-wave field of reconstruct, obtains final damage imaging as a result, detailed process includes:
A, RMS imaging indicators are calculated
Wherein rms (P) is the root mean square of reconstruction signal at plate structure surface P point, t1、t2To measure start/stop time, x (t)
For analog signal；xiActually to reconstruct obtained discrete signal, n is signal length.
B, using the rms value of each point as imaging indicators, damage imaging result is obtained.
Beneficial effects of the present invention:
It firstly, the present invention uses uniform sparse sampling strategy, and will assume that source is set as random distribution, be not only able to satisfy
Requirement when constructing compressed sensing equation to sensing matrix, moreover it is possible to meet SLDV examination network input requirements, evade SLDV survey
Amount system, which carries out random measurement, need to increase the limitation of system cost；Secondly, compressed sensing technology is applied to supersonic guide-wave field damage
Hurt detection field, carry out wave field reconstruct and damage imaging using sparseness measuring signal, the time of measuring contracting of all-wave field can be will acquire
More than subtracting 90%, while obtaining with the full wave field coherence factor that measures close to 0.8 reconstruct wave field.
Detailed description of the invention
Fig. 1 is a kind of process of compressed sensing based supersonic guide-wave field damage detecting method suitable for plate structure
Figure；
Fig. 2 is test specimen schematic diagram to be measured；
Fig. 3 is sparseness measuring grid and hypothesis source arrangement schematic diagram；
Fig. 4 is SLDV sampling system schematic diagram；
Fig. 5 is reconstruct wave field figure；
Fig. 6 is the tendency chart that average coherence property coefficient changes with sampling ratio；
Fig. 7 is RMS image；
In figure, 1, computer, 2, SLDV- scanning type laser Doppler vibrometer (Scanning Laser Doppler
Vibrometer, SLDV), 3, signal generator, 4, power amplifier, 5, test specimen to be measured, 6, PZT driving source.Circle is in Fig. 3
Sparseness measuring grid is put as hypothesis source.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, the specific embodiments are only for explaining the present invention, not
For limiting the present invention.
The present invention proposes that a kind of compressed sensing based supersonic guide-wave field suitable for plate structure as shown in Figure 1 is damaged
Detection method, the specific steps are as follows:
Step 1, SLDV sampling system is constructed, as shown in figure 4, the system specifically includes: computer 1, scanning type laser are more
General Le vialog (Scanning Laser Doppler Vibrometer, SLDV) (Scanning Laser Doppler
Vibrometer, SLDV) 2, arbitrarily signal generating device 3, signal power amplifier 4, test specimen 5 and PZT driving source 6, scanning
Formula laser doppler vialog 2 is popped one's head in including ultrasonic laser, and ultrasonic laser is popped one's head in the vibration of test specimen surface measuring point
Speed real-time detection result is transferred on computer 1.
In the present embodiment, the PSV-500 model scanning type laser Doppler vibrometer produced using Polytec company
(Scanning Laser Doppler Vibrometer, SLDV) 2 and sub computers 1；Test specimen 5 to be measured is 1mm thickness aluminium sheet,
As shown in figure 4, having sticked the thin rounded flakes simulation damage that a diameter is 7mm on 5 surface of test specimen to be measured.
Step 2, measured zone is selected in test specimen 5, as shown in Figure 2；Determine sparse sampling grid, what is selected in this example is dilute
Dredge examination network overall length 100mm, total high 100mm, spacing 5mm, as shown in circle in Fig. 3.
It before introducing damage, is sampled using the sampled point that SLDV sampling system sets step 1, pick-up structure is strong
Signal y under health state1。
After introducing damage, signal y of the structure under containing faulted condition is acquired2, and with health signal y1Subtract each other to obtain signal y
=y2-y1, using signal y as the input quantity of compressed sensing equation.
In this example, the time interval of excitation is 10ms, sample frequency 5.12MHz, when sampling a length of 200 μ s.
Step 3, the position of damage scattering source is estimated at random, obtains hypothesis source coordinate, detailed process are as follows:
3.1 determine hypothesis source region, cover the position in there may be source as far as possible, as assumed shown in source region in Fig. 2；
3.2 are arranged uniform grid in the region, and grid spacing d is no more than the half of guided wave field minimum wavelength, this example
Take 2.5mm；
3.3 inside each grid, with grid element center point (x0,y0) on the basis of put at random take a little, generate hypothesis source coordinate
(x, y):
Wherein random is uniformly random function.
It is assumed that source point is specific as shown in point red in Fig. 2.
Defining sampling ratio (Sampling Rate, SR) is measurement points and Nyquist law states when reconstruct wave field
Minimum sampling number ratio multiplied by absolutely.
Step 4 establishes compressed sensing equation, and is solved with base tracking noise reduction algorithm to the excitation function for assuming source, has
Body process is as follows:
4.1 assume that the excitation function in all hypothesis sources uniformly motivates in all directions, building hypothesis source to sparseness measuring point
Transfer matrix A ∈ CM×N, wherein M=441 and N=3321 respectively indicates sparseness measuring point quantity and assumes source quantity, CM×NTable
Show the complex number space of M × N.M row s column element is that the pumping signal in s-th of hypothesis source travels to the transmitting of m-th of measuring point in A
Function is indicated when only considering single mode are as follows:
Wherein dM, sIt is hypothesis source at a distance from measuring point,To assume the wave on source to driving source direction under mode u
Number, is estimated using dispersion relation known to material；
4.2 construct compressed sensing equation Av=y using signal y and transfer matrix A, track Method of Noise by base and solve hypothesis
Source forcing function v.
Step 5, all-wave field is reconstructed using the excitation function acquired, detailed process is as follows:
5.1 select reconstruction region, this example selection reconstruct full surface wave field of aluminium sheet test specimen in surface of test piece.Building assumes source point
To the transfer matrix A ' to reconstruction point, the frequency domain wave field W=A ' v to reconstruction point is calculated；
In selected reconstruction region, determine by interval of 2.5mm to reconstruction point coordinate.In the region, to by surveying entirely
Amount obtains guided wave field, needs at least to acquire 25921 points, according to the measure setup of step 2.3, time of measuring is about 2.1 hours；
And according in step 1 sparseness measuring be arranged, actual samples point quantity be 441 points, sampling ratio SR=441/25921 ×
100%=1.7%, actual measurement time are reduced to 2.1 minutes.
5.2 couples of W do inverse Fourier transform, obtain the time domain wavefield of reconstruction point.
Fig. 5 is the reconstructed residual wave field of 62.5 μ s.Reconstruct the average coherence property coefficient C of wave field and true wavefieldmeanWith SR
The tendency chart of variation is shown in Fig. 6, as can be seen from the figure: when sampling ratio SR is lower than 10%, the average coherence property coefficient of reconstruct
CmeanWith the approximate linear growth of SR, and growth rate is very fast, when sampling ratio reaches 10%, CmeanReach 0.77；And work as SR
At 10% to 40%, CmeanSlow down with the growth rate of SR；When sampling ratio reaches 40% or more, CmeanIt is basically stable at
0.9 or more, speedup is slow.
In conclusion can be obtained average coherence property coefficient C when sampling ratio is only 10%meanClose to 0.8 reconstruct
Wave field, the time of measuring that can will acquire all-wave field at this time accordingly reduce 90%, can greatly improve detection ground efficiency.
Step 6, RMS imaging is carried out to the all-wave field of reconstruct, obtains final damage imaging as a result, detailed process is as follows:
6.1 calculate RMS imaging indicators
Wherein rms (P) is the root mean square of reconstruction signal at plate structure surface P point, t1、t2To measure start/stop time, x (t)
For analog signal；xiActually to reconstruct obtained discrete signal, n is signal length.
6.2, using the rms value of each point as imaging indicators, obtain damage imaging result.
Fig. 7 is finally RMS imaging results figure, wherein figure (a) is that the RMS that reconstruct wave field is calculated is imaged
Figure, figure (b) are the image for scheming (a) after 0.6 times of threshold filtering.By imaging results, can to the center of damage into
Row estimation, estimated coordinates are (199.8,252.7), and apart from actual position (200,250) 2.71mm, error is about wave field most small echo
Long half.
In conclusion this method can reconstruct the higher all-wave field of precision using less measurement point, greatly reduce
The time of measuring of all-wave field detecting；The stochastic sampling strategy in existing method is replaced with the sparse sampling strategy of rule, can guarantee
Commercial SLDV system is easily achieved picking up signal without increasing system cost；Meanwhile using all-wave field technology to reconstructing
All-wave field is handled, and can damage be positioned and be assessed, and position error is about minimum wavelength half.
Above embodiments are merely to illustrate design philosophy and feature of the invention, and its object is to make technology in the art
Personnel can understand the content of the present invention and implement it accordingly, and protection scope of the present invention is not limited to the above embodiments.So it is all according to
It is within the scope of the present invention according to equivalent variations made by disclosed principle, mentality of designing or modification.
Claims (7)
1. a kind of compressed sensing based supersonic guide-wave field damage detecting method suitable for plate structure, which is characterized in that packet
Include following steps: building SLDV sampling system；Space sparse sampling mesh coordinate is determined, by sample coordinate input SLDV sampling system
System acquires ultrasonic guided wave signals under health status and containing faulted condition respectively, and two groups of signal subtractions obtain dissipating comprising damage
Penetrate the difference signal of information；The position of damage scattering source is estimated at random, obtains hypothesis source coordinate；Establish compressed sensing side
Journey, and the excitation function that noise reduction algorithm solves hypothesis source is tracked with base；All-wave field is reconstructed using the excitation function acquired, to reconstruct
All-wave field carry out RMS imaging, obtain damage imaging result.
2. a kind of compressed sensing based supersonic guide-wave field damage check suitable for plate structure according to claim 1
Method, which is characterized in that the SLDV sampling system includes: computer, scanning type laser Doppler vibrometer, arbitrary signal hair
Raw device, power amplifier and PZT driving source.
3. a kind of compressed sensing based supersonic guide-wave field damage check suitable for plate structure according to claim 1
Method, which is characterized in that the space sparse sampling grid is equidistant grid.
4. a kind of compressed sensing based supersonic guide-wave field damage check suitable for plate structure according to claim 1
Method, which is characterized in that the position of described pair of damage scattering source is estimated at random, obtains the detailed process packet of hypothesis source coordinate
It includes:
A, determination assumes source region, covers the position in there may be source as far as possible；
B, uniform grid is set in the region, grid spacing d is no more than the half of guided wave field minimum wavelength；
C, inside each grid, with grid element center point (x0,y0) on the basis of put at random take a little, generate hypothesis source coordinate (x, y):
Wherein random is uniformly random function.
5. a kind of compressed sensing based supersonic guide-wave field damage check suitable for plate structure according to claim 1
Method, which is characterized in that it is described to establish compressed sensing equation, and the excitation function in hypothesis source is solved with base tracking noise reduction algorithm
Detailed process includes:
A, assume that the excitation function in all hypothesis sources is isotropic, the transfer matrix A in building hypothesis source to sparseness measuring point
∈CM×N, wherein M and N respectively indicates sparseness measuring point quantity and assumes source quantity, CM×NIndicate the complex number space of M × N.In A
M row s column element is that the pumping signal in s-th of hypothesis source travels to the transmission function of m-th of measuring point, when only considering single mode,
It indicates are as follows:
Wherein dM, sIt is hypothesis source at a distance from measuring point,To assume the wave number on source to driving source direction under mode u, by
Dispersion relation known to structure to be checked is calculated；
B, by structure under health status and containing the signal y measured under faulted condition1With y2Subtract each other, obtain difference signal y, combines
Transfer matrix A constructs compressed sensing equation Av=y, tracks Method of Noise by base and solves hypothesis source forcing function v.
6. a kind of compressed sensing based supersonic guide-wave field damage check suitable for plate structure according to claim 1
Method, which is characterized in that the process of excitation function that the utilization acquires reconstruct all-wave field includes:
A, reconstruction region is selected in surface of test piece, determines the coordinate to reconstruction point in this region, building assumes source point to wait reconstruct
The transfer matrix A ' of point calculates the frequency domain wave field W=A ' v to reconstruction point；
B, inverse Fourier transform is done to W, obtains the time domain wavefield of reconstruction point；
To assess quality reconstruction, definition reconstructs wave field and the coherence coefficient of true wavefield is as follows:
Wherein SR, M(f) it indicates to reconstruct wave field at frequency f and measures the cross-spectral density of wave field, SR(f) and SM(f) it is respectively
Wave field is reconstructed at frequency f and measures the autopower spectral density of wave field.C (f) is being calculated into frequency range (f1,f2) in take mean value Cmean
Index as evaluation wave field quality reconstruction.
7. a kind of compressed sensing based supersonic guide-wave field damage check suitable for plate structure according to claim 1
Method, which is characterized in that the imaging indicators calculation method of the RMS imaging are as follows:
Wherein rms (P) is the root mean square of reconstruction signal at plate structure surface P point, t1、t2To measure start/stop time, x (t) is to connect
Continuous analog signal；xiActually to reconstruct obtained discrete signal, n is signal length.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910141759.4A CN109884187B (en) | 2019-02-26 | 2019-02-26 | Ultrasonic guided wave field damage detection method based on compressed sensing and applicable to plate-shaped structure |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910141759.4A CN109884187B (en) | 2019-02-26 | 2019-02-26 | Ultrasonic guided wave field damage detection method based on compressed sensing and applicable to plate-shaped structure |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109884187A true CN109884187A (en) | 2019-06-14 |
| CN109884187B CN109884187B (en) | 2021-09-10 |
Family
ID=66929438
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910141759.4A Active CN109884187B (en) | 2019-02-26 | 2019-02-26 | Ultrasonic guided wave field damage detection method based on compressed sensing and applicable to plate-shaped structure |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109884187B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110553156A (en) * | 2019-08-30 | 2019-12-10 | 清华大学 | pipeline ultrasonic guided wave compression sensing health monitoring method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102507739A (en) * | 2011-11-15 | 2012-06-20 | 北京理工大学 | Ultrasonic guided wave defect imaging method for impact damages of carbon fiber composite material |
| CN104502452A (en) * | 2014-12-17 | 2015-04-08 | 江苏大学 | Structural damage assessment method based on ultrasonic guided-wave drive/sensing array |
| CN105651859A (en) * | 2016-01-12 | 2016-06-08 | 杭州浙达精益机电技术股份有限公司 | Ultrasonic guided wave device and method for monitoring corrosion of pipeline |
| CN106770691A (en) * | 2017-01-04 | 2017-05-31 | 天津大学 | A kind of turbine rotor ultrasonic phase array compression method based on compressed sensing |
-
2019
- 2019-02-26 CN CN201910141759.4A patent/CN109884187B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102507739A (en) * | 2011-11-15 | 2012-06-20 | 北京理工大学 | Ultrasonic guided wave defect imaging method for impact damages of carbon fiber composite material |
| CN104502452A (en) * | 2014-12-17 | 2015-04-08 | 江苏大学 | Structural damage assessment method based on ultrasonic guided-wave drive/sensing array |
| CN105651859A (en) * | 2016-01-12 | 2016-06-08 | 杭州浙达精益机电技术股份有限公司 | Ultrasonic guided wave device and method for monitoring corrosion of pipeline |
| CN106770691A (en) * | 2017-01-04 | 2017-05-31 | 天津大学 | A kind of turbine rotor ultrasonic phase array compression method based on compressed sensing |
Non-Patent Citations (2)
| Title |
|---|
| M RADZIEŃSKI等: "Application of RMS for damage detection by guided elastic waves", 《JOURNALOFPHYSICS:CONFERENCESERIES》 * |
| OLIVIER MESNIL等: "Sparse wavefifield reconstruction and source detection using Compressed Sensing", 《ULTRASONICS》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110553156A (en) * | 2019-08-30 | 2019-12-10 | 清华大学 | pipeline ultrasonic guided wave compression sensing health monitoring method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109884187B (en) | 2021-09-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110389170B (en) | Train component crack damage detection method and system based on Lamb wave imaging | |
| Yu et al. | Crack imaging and quantification in aluminum plates with guided wave wavenumber analysis methods | |
| Rossetto et al. | Locating a weak change using diffuse waves: Theoretical approach and inversion procedure | |
| Prado et al. | Lamb mode diversity imaging for non-destructive testing of plate-like structures | |
| Sears et al. | Ultrasonic attenuation measurement by spectral ratios utilizing signal processing techniques | |
| Quaegebeur et al. | Correlation-based imaging technique using ultrasonic transmit–receive array for non-destructive evaluation | |
| Merabet et al. | 2-D and 3-D reconstruction algorithms in the Fourier domain for plane-wave imaging in nondestructive testing | |
| US20150160169A1 (en) | Method and system for multi-path active defect detection, localization and characterization with ultrasonic guided waves | |
| CN112067691B (en) | Multi-frequency ultrasonic tomography method for combining attenuation spectrum of oil-gas-water three-phase medium | |
| Lubeigt et al. | Topological imaging in bounded elastic media | |
| CN110487393A (en) | The unstable state free field restoring method measured using single side acoustic pressure and particle velocity | |
| Yang et al. | A reverse time migration-based multistep angular spectrum approach for ultrasonic imaging of specimens with irregular surfaces | |
| Xu et al. | Minimum variance Lamb wave imaging based on weighted sparse decomposition coefficients in quasi-isotropic composite laminates | |
| Tang et al. | A method based on SVD for detecting the defect using the magnetostrictive guided wave technique | |
| CN108508093A (en) | A kind of detection method and system of workpiece, defect height | |
| Xu et al. | Lamb wave imaging based on multi-frequency sparse decomposition | |
| Ge et al. | High-resolution ultrasonic imaging technology for the damage of concrete structures based on total focusing method | |
| Chady et al. | Neural network models of eddy current multi-frequency system for nondestructive testing | |
| Gao et al. | An accurate measurement method of lamb wave phase velocity based on clustering algorithms | |
| CN109884187A (en) | A kind of compressed sensing based supersonic guide-wave field damage detecting method suitable for plate structure | |
| Levine et al. | Guided wave localization of damage via sparse reconstruction | |
| Petromichelakis et al. | Signal-to-Noise Ratio analysis for time-reversal based imaging techniques in bounded domains | |
| Yang et al. | Passive detection and localization of fatigue cracking in aluminum plates using Green’s function reconstruction from ambient noise | |
| Rao et al. | Detection of defects in highly attenuating materials using ultrasonic least-squares reverse time migration with preconditioned stochastic gradient descent | |
| Yang et al. | Imaging a defect in layered media with different shaped interfaces using reverse time migration without velocity model known a priori |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |