CN108491777B - Lamb wave space sampling signal fitting method based on Morlet mother wavelet - Google Patents
Lamb wave space sampling signal fitting method based on Morlet mother wavelet Download PDFInfo
- Publication number
- CN108491777B CN108491777B CN201810204278.9A CN201810204278A CN108491777B CN 108491777 B CN108491777 B CN 108491777B CN 201810204278 A CN201810204278 A CN 201810204278A CN 108491777 B CN108491777 B CN 108491777B
- Authority
- CN
- China
- Prior art keywords
- morlet
- lamb wave
- fitting
- wavelet function
- waveform
- 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.)
- Expired - Fee Related
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
- G06F2218/10—Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
- G06F2218/14—Classification; Matching by matching peak patterns
Abstract
The invention discloses a Lamb wave space sampling signal fitting method based on Morlet mother wavelets, and belongs to the technical field of engineering structure health monitoring. The method comprises the steps of firstly setting the center frequency, the sampling frequency and the sampling time of Morlet mother wavelet; then constructing Lamb wave excitation simulation signals according to the number of the wave crests of the excitation signals of the Lamb waves; secondly, calculating the frequency bandwidth parameters of the Morlet mother wavelet according to the correlation coefficients of the Morlet mother wavelet fitting waveform and the Lamb wave excitation simulation signal under different frequency bandwidth parameters; and finally, solving the fitting parameters of the Morlet wavelet function according to the error square sum of the Morlet wavelet function fitting waveform under different scale factors and displacement factors and the Lamb wave space sampling signal, wherein the corresponding Morlet wavelet function fitting waveform is the Morlet wavelet function fitting waveform of the Lamb wave space sampling signal. The invention improves the spatial resolution and the length of the Lamb wave spatial sampling signal, thereby being beneficial to promoting the application of the space-wavenumber domain signal processing method in the field of engineering structure health monitoring.
Description
Technical Field
The invention relates to a Lamb wave space sampling signal fitting method based on Morlet mother wavelets, and belongs to the technical field of engineering structure health monitoring.
Background
The Lamb wave based structural health monitoring method has the advantages of high damage monitoring sensitivity, large monitoring range, online application and offline application, active damage monitoring and passive impact monitoring, monitoring of metal structures and composite material structures and the like. Therefore, the Lamb wave-based structural health monitoring method is widely researched at home and abroad, and is one of the most promising structural health monitoring technologies at present. Generally, a piezoelectric sensor is a main device for realizing Lamb wave excitation and sensing. For the structural health monitoring method based on Lamb waves, the early method mainly identifies and characterizes the damage by analyzing the damage of Lamb waves and the characteristics or mode transformation characteristics of signals in time domain, frequency domain, time-frequency domain, such as the flight time, amplitude, energy, main frequency components and amplitude thereof, time-frequency amplitude, singularity characteristic value and the like of the signals. However, Lamb waves have multi-mode characteristics, that is, Lamb wave signals of multiple modes appear under the same central frequency, Lamb waves of different modes are often mutually interleaved and overlapped in time and distance, analysis is difficult by using a conventional time domain, frequency domain or time-frequency domain signal processing method, and Lamb wave signals of different modes have different propagation characteristics, which causes the error of the above various structural health monitoring imaging methods based on Lamb waves to be increased, and even cause monitoring difficulty. To do this, researchers have attempted to analyze Lamb wave signals in the spatio-wavenumber domain. Many students use a scanning laser doppler vibrometer to collect the spatial fluctuation information of Lamb wave propagation in the structure, which is difficult to perform online monitoring of structural damage. Some scholars use the piezoelectric sensor array to collect Lamb wave spatial fluctuation information for on-line monitoring, and are limited by the size and structure form of the piezoelectric sensor, and the spatial resolution and the length of Lamb wave spatial signals collected in the mode are limited, so that the subsequent spatial-wavenumber domain signal processing method is seriously influenced, and the damage monitoring error is increased.
Disclosure of Invention
In order to solve the problems, the invention provides a Lamb wave space sampling signal fitting method based on Morlet mother wavelets.
The invention adopts the following technical scheme for solving the technical problems:
the method comprises the following steps: initialization settings
①, setting the central frequency of Morlet mother wavelet as c, sampling frequency as d, sampling time as t, and resolution of sampling time as Deltat as 1/d.
② according to the number n of peak of Lamb wave excitation signal, corresponding Lamb wave excitation simulation signal s is constructed by formula (1)1The center frequency of the simulated signal is c1C, sampling frequency d1D, the sampling time t1＝t。
In the formula: c. C1For the central frequency, t, of the Lamb wave excitation simulation signal1The sampling time of the Lamb wave excitation simulation signal is shown, n is the number of wave crests of the Lamb wave excitation simulation signal, and pi is the circumferential rate.
Step two: calculating the bandwidth parameter h of Morlet mother wavelet
① sets the scanning range of the bandwidth parameter h of Morlet mother wavelet as hs and the scanning resolution as Deltah.
② calculating Morlet mother wavelet function waveform f under each frequency bandwidth parameter according to Morlet mother wavelet function (formula (2))1(t), extracting Morlet mother wavelet function waveform f1(t) imaginary part, normalization and left-right turning to obtain Morlet mother wavelet fitting waveform s2。
In the formula: f. of1Is a Morlet mother wavelet function, t is sampling time, pi is a circumferential rate, and h is a bandwidth parameter of Morlet mother waveletThe number, e is a natural constant, i is an imaginary unit, and c is the center frequency of the Morlet mother wavelet.
③ calculating Morlet mother wavelet fitting waveform s according to formula (3)2And Lamb wave excitation simulation signal s1The correlation coefficient r of (1).
In the formula: r is s2And s1Coefficient of correlation, Cov(s)2,s1) Is s is2And s1Of (1) covariance, Var [ s ]2]Is s is2Variance of (1), Var [ s ]1]Is s is1The variance of (c).
④, finally obtaining the correlation coefficient r under each frequency bandwidth parameter, wherein the frequency bandwidth parameter corresponding to the maximum value of the correlation coefficient r is used as the frequency bandwidth parameter h of the Morlet mother wavelet.
Step three: calculating Morlet wavelet function fitting waveform s of Lamb wave space sampling signal3
①, setting the scanning range of the scale factor a of the Morlet wavelet function as and the scanning resolution as delta a, and setting the scanning range of the displacement factor b of the Morlet wavelet function as bs and the scanning resolution as delta b.
②, a scale factor a and a displacement factor b are selected, and the spatial sampling point x at the moment is calculated according to the formula (4).
In the formula: and g is the spatial sampling frequency of the Lamb wave spatial sampling signal.
③ calculating Morlet wavelet function waveform f under current parameters according to Morlet wavelet function (formula (5))2(x) Extracting Morlet wavelet function waveform f2(x) Normalized and left-right turned to obtain Morlet wavelet function fitting waveform s3。
④ calculating Morlet wavelet function fitting waveform s according to formula (6)3And the spatial sampling signal s0The sum of squared errors of k.
k＝∑(s3-s0)2(6)
⑤, finally obtaining the error square sum k under each scale factor a and displacement factor b, wherein the scale factor a and the displacement factor b corresponding to the minimum value of the error square sum k are used as the fitting parameters of the Morlet wavelet function, and the corresponding Morlet wavelet function fitting waveform s is at this time3Namely Lamb wave space sampling signal s0Fitting the waveform with the Morlet wavelet function.
The invention has the following beneficial effects:
1. the spatial resolution of the Lamb wave spatial sampling signal is improved;
2. the length of Lamb wave space sampling signals is increased;
3. the hardware requirement of the space-wavenumber domain signal processing method on the space sampling equipment is reduced;
4. the number of the Lamb wave space sampling sensors is reduced;
5. the damage monitoring error based on the space-wavenumber domain signal processing method is reduced;
6. the method is beneficial to promoting the application of the space-wavenumber domain signal processing method in the field of engineering structure health monitoring.
Drawings
FIG. 1 is an implementation flow of a Lamb wave space sampling signal fitting method based on Morlet mother wavelet;
FIG. 2 is a schematic diagram of a specimen shape, a piezoelectric sensor position, and a two-dimensional rectangular coordinate system in an embodiment;
FIG. 3 is a Lamb wave spatial sampling signal;
FIG. 4 is a Lamb wave excitation simulation signal;
figure 5 is a correlation coefficient for each frequency bandwidth parameter;
FIG. 6 is a Morlet mother wavelet fit waveform;
FIG. 7 is a sum of squares of errors at various scale factors and displacement factors;
fig. 8 is a comparison of a Morlet wavelet function fit waveform with a Lamb wave spatially sampled signal.
Detailed Description
The invention is further described by the following specific embodiments with reference to the attached drawings.
The method comprises the steps of firstly setting the center frequency, the sampling frequency and the sampling time of Morlet mother wavelet; then constructing Lamb wave excitation simulation signals according to the number of the wave crests of the excitation signals of the Lamb waves; secondly, calculating the frequency bandwidth parameters of the Morlet mother wavelet according to the correlation coefficients of the Morlet mother wavelet fitting waveform and the Lamb wave excitation simulation signal under different frequency bandwidth parameters; and finally, solving the fitting parameters of the Morlet wavelet function according to the error square sum of the Morlet wavelet function fitting waveform and the space sampling signal under different scale factors and displacement factors, wherein the corresponding Morlet wavelet function fitting waveform is the Morlet wavelet function fitting waveform of the Lamb wave space sampling signal.
Fig. 1 is an implementation flow of the Lamb wave space sampling signal fitting method based on Morlet mother wavelet of the present invention: setting the central frequency c, the sampling frequency d and the sampling time t of the Morlet mother wavelet; constructing Lamb wave excitation simulation signals s according to the number n of the peaks of the excitation signals of Lamb waves1(ii) a Setting a scanning range hs and an interval delta h of a frequency bandwidth parameter h of Morlet mother wavelet; selecting a scanning value of a frequency bandwidth parameter; calculating Morlet mother wavelet function waveform f1(t); extraction of f1(t) imaginary part, normalization and left-right turning to obtain Morlet mother wavelet fitting waveform s2(ii) a Calculating s2And s1The correlation coefficient r of (a); calculating a correlation coefficient under each frequency bandwidth parameter; selecting a frequency bandwidth parameter corresponding to the maximum value of the correlation coefficient r as a frequency bandwidth parameter h of the Morlet mother wavelet; setting a scanning range as and an interval delta a of a scale factor a of the Morlet wavelet function, and setting a scanning range bs and an interval delta b of a displacement factor b of the Morlet wavelet function; selecting a scanning value of a scale factor and a scanning value of a displacement factor; calculating a spatial sampling point x; calculating Morlet wavelet function waveform f2(x) (ii) a Extraction of f2(x) Normalized and left-right reversed to obtain Morlet wavelet function fitting waveform s3(ii) a Calculating s3And the spatial sampling signal s0The sum of squared errors of k; calculating the sum of squares of errors under each scale factor and each displacement factor; and selecting a scale factor a and a displacement factor b corresponding to the minimum error sum of squares as fitting parameters of a Morlet wavelet function, wherein the corresponding Morlet wavelet function fitting waveform is the Morlet wavelet function fitting waveform of the Lamb wave space sampling signal.
The test pieces of examples are a block of 100cm × 100cm × 0.2cm (length × width × thickness) aluminum alloy. The exciting/sensing element is a PZT-5A type piezoelectric transducer, and the diameter and the thickness of the PZT-5A type piezoelectric transducer are respectively 0.8cm and 0.04 cm. The experimental facility uses a structural health monitoring system developed by a university. A7-array-element linear piezoelectric sensor array is uniformly arranged in the middle position under a test piece and used for acquiring structural Lamb wave space signals, the distance between the central points of two adjacent piezoelectric sensors is 0.9cm, and the distance between the linear piezoelectric sensor array and the lower edge of an aluminum alloy test piece is 20 cm. And a piezoelectric sensor is arranged at a position 30cm away from the central point of the linear piezoelectric sensor array and is used as an excitation element of Lamb waves. A two-dimensional rectangular coordinate system is established on the test piece structure by taking the axis of the linear piezoelectric sensor array as the x axis and the central point of the linear piezoelectric sensor array as the origin, as shown in fig. 2. A20 kHz sine-modulated five-peak narrow-band signal is generated by using a structural health monitoring system and is input to an exciting element. The structural health monitoring system is connected with the linear piezoelectric sensor array to collect Lamb wave signals and Lamb wave space sampling signals s transmitted in the structure0As shown in fig. 3.
The embodiment comprises the following steps:
the method comprises the following steps: initialization settings
①, setting the central frequency c of Morlet mother wavelet to 1Hz, sampling frequency d to 50Hz, sampling time t to [ -70,70], and resolution Δ t to 1/d.
② according to the number of Lamb wave excitation signal peaks (sine modulation five-peak narrow-band signal, n is 5), corresponding Lamb wave excitation simulation signal s is constructed by using formula (1)1The center frequency of the simulated signal is c1C 1Hz, and d1D 50Hz, and t1＝t＝[-70,70]As shown in fig. 4.
In the formula: c. C1For the central frequency, t, of the Lamb wave excitation simulation signal1The sampling time of the Lamb wave excitation simulation signal is shown, n is the number of wave crests of the Lamb wave excitation simulation signal, and pi is the circumferential rate.
Step two: calculating the bandwidth parameter h of Morlet mother wavelet
①, the sweep range of the frequency bandwidth parameter h of Morlet mother wavelet is set as hs ═ 1.5,2.4, and the sweep resolution is set as Δ h ═ 0.0001.
② calculating Morlet mother wavelet function waveform f under each frequency bandwidth parameter according to Morlet mother wavelet function (formula (2))1(t), extracting Morlet mother wavelet function waveform f1(t) imaginary part, normalization and left-right turning to obtain Morlet mother wavelet fitting waveform s2。
In the formula: f. of1The method is a Morlet mother wavelet function, t is sampling time, pi is a circumference ratio, h is a frequency bandwidth parameter of the Morlet mother wavelet, e is a natural constant, i is an imaginary number unit, and c is the central frequency of the Morlet mother wavelet.
③ calculating Morlet mother wavelet fitting waveform s according to formula (3)2And Lamb wave excitation simulation signal s1The correlation coefficient r of (1).
In the formula: r is s2And s1Coefficient of correlation, Cov(s)2,s1) Is s is2And s1Of (1) covariance, Var [ s ]2]Is s is2Variance of (1), Var [ s ]1]Is s is1The variance of (c).
④ the correlation coefficient r under each bandwidth parameter is shown in fig. 5, where the bandwidth parameter (1.9621) corresponding to the maximum value (0.9985) of the correlation coefficient r is 1.9621 as the bandwidth parameter h of the Morlet mother wavelet, and the waveform s of the Morlet mother wavelet fit at this time is shown as2As shown in fig. 6.
Step three: calculating Morlet wavelet function fitting waveform s of Lamb wave space sampling signal3
① sets the sweep range of the scale factor a of the Morlet wavelet function as ═ 10,30 and the sweep resolution Δ a ═ 0.01, the sweep range of the displacement factor b of the Morlet wavelet function bs [ -0.054, 0.054] and the sweep resolution Δ b ═ 0.00009.
②, a scale factor a and a displacement factor b are selected, and the spatial sampling point x at the moment is calculated according to the formula (4).
In the formula: g is the spatial sampling frequency of the Lamb wave spatial sampling signal, and g is 2 pi/delta x.
③ calculating Morlet wavelet function waveform f under current parameters according to Morlet wavelet function (formula (5))2(x) Extracting Morlet wavelet function waveform f2(x) Normalized and left-right turned to obtain Morlet wavelet function fitting waveform s3。
④ calculating Morlet wavelet function fitting waveform s according to formula (6)3And Lamb wave space sampling signal s0The sum of squared errors of k.
k＝∑(s3-s0)2(6)
⑤, the sum of squared errors k under the scale factors a and b is finally obtained, the normalized sum of squared errors k is shown in fig. 7, wherein the scale factor a (20) corresponding to the minimum value of the sum of squared errors k (0.1211)26) and a shift factor b (-0.00882) as fitting parameters of the Morlet wavelet function, when the corresponding Morlet wavelet function fits the waveform s3Namely Lamb wave space sampling signal s0The Morlet wavelet function of (a) is fitted to the waveform as shown in fig. 8. As can be seen from fig. 8, the Morlet wavelet function fitting waveform greatly improves the spatial resolution and length of Lamb wave spatial sampling signals.
While the invention has been particularly shown and described with reference to a preferred embodiment thereof, it will be understood by those skilled in the art that various changes in form and detail may be made without departing from the scope of the invention as set forth in the following claims. The foregoing detailed description has been presented in conjunction with specific embodiments of this invention, but is not intended to limit the invention thereto. Any simple modifications of the above embodiments according to the technical essence of the present invention still fall within the scope of the technical solution of the present invention.
Claims (9)
1. A Lamb wave space sampling signal fitting method based on Morlet mother wavelets is characterized in that the fitting method comprises the following steps:
the method comprises the following steps: initializing and setting to construct Lamb wave excitation simulation signal s1；
Step two: obtaining a frequency bandwidth parameter h of the Morlet mother wavelet according to correlation coefficients of the Morlet mother wavelet fitting waveform and the Lamb wave excitation simulation signal under different frequency bandwidth parameters;
step three: according to the error square sum of the Morlet wavelet function fitting waveform and the Lamb wave space sampling signal under different scale factors and displacement factors, the fitting parameter of the Morlet wavelet function is obtained, and the corresponding Morlet wavelet function fitting waveform is the Morlet wavelet function fitting waveform s of the Lamb wave space sampling signal3；
The third step is specifically as follows:
(1) setting the scanning range of a scale factor a of a Morlet wavelet function as and the scanning resolution as delta a; the scanning range of the displacement factor b of the Morlet wavelet function is bs, and the scanning resolution is delta b;
(2) selecting a scale factor a and a displacement factor b, and calculating a space sampling point x at the moment;
(3) calculating Morlet wavelet function waveform f under current parameters according to Morlet wavelet function2(x) Extracting Morlet wavelet function waveform f2(x) Normalized and left-right turned to obtain Morlet wavelet function fitting waveform s3；
(4) Calculating Morlet wavelet function fitting waveform s3And Lamb wave space sampling signal s0The sum of squared errors of k;
(5) finally obtaining the error square sum k under each scale factor a and each displacement factor b, wherein the scale factor a and the displacement factor b corresponding to the minimum value of the error square sum k are used as the fitting parameters of the Morlet wavelet function, and the corresponding Morlet wavelet function fitting waveform s is obtained at the moment3Namely Lamb wave space sampling signal s0Fitting the waveform with the Morlet wavelet function.
2. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 1,
the first step is specifically as follows:
(1) setting the central frequency of Morlet mother wavelet as c, sampling frequency as d and sampling time as t;
(2) constructing corresponding Lamb wave excitation simulation signals s according to the number n of the peak of the excitation signal of the Lamb wave1。
3. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 2, wherein:
in the formula: c. C1For the central frequency, t, of the Lamb wave excitation simulation signal1Is the sampling time of the Lamb wave excitation simulation signal, n is the number of wave crests of the Lamb wave excitation simulation signal, pi is the circumference ratio, c1＝c，t1＝t。
4. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 1,
the second step is specifically as follows:
(1) setting the scanning range of the frequency bandwidth parameter h of Morlet mother wavelet as hs and the scanning resolution as delta h;
(2) calculating Morlet mother wavelet function waveform f under each frequency bandwidth parameter according to Morlet mother wavelet function1(t), extracting Morlet mother wavelet function waveform f1(t) imaginary part, normalization and left-right turning to obtain Morlet mother wavelet fitting waveform s2；
(3) Calculating Morlet mother wavelet fitting waveform s2And Lamb wave excitation simulation signal s1The correlation coefficient r of (a);
(4) finally, obtaining the correlation coefficient r under each frequency bandwidth parameter, wherein the frequency bandwidth parameter corresponding to the maximum value of the correlation coefficient r is used as the frequency bandwidth parameter h of the Morlet mother wavelet.
5. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 4, wherein:
in the formula: f. of1The method is a Morlet mother wavelet function, t is sampling time, pi is a circumference ratio, h is a frequency bandwidth parameter of the Morlet mother wavelet, e is a natural constant, i is an imaginary number unit, and c is the central frequency of the Morlet mother wavelet.
6. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 4 or 5, wherein:
in the formula: r is s2And s1Coefficient of correlation, Cov(s)2,s1) Is s is2And s1Of (1) covariance, Var [ s ]2]Is s is2Variance of (1), Var [ s ]1]Is s is1The variance of (c).
7. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 1, wherein:
in the formula: x is a spatial sampling point, g is the spatial sampling frequency of the Lamb wave spatial sampling signal, a is a scale factor, and b is a displacement factor.
8. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 1, wherein:
in the formula: f. of2The method is a Morlet wavelet function, pi is a circumference ratio, h is a frequency bandwidth parameter of a Morlet mother wavelet, e is a natural constant, i is an imaginary number unit, c is the central frequency of the Morlet mother wavelet, a is a scale factor, and b is a displacement factor.
9. The Lamb wave spatial sampling signal fitting method based on Morlet mother wavelets according to claim 1, wherein:
sum of squared errors k ═ Σ(s)3-s0)2。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810204278.9A CN108491777B (en) | 2018-03-12 | 2018-03-12 | Lamb wave space sampling signal fitting method based on Morlet mother wavelet |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810204278.9A CN108491777B (en) | 2018-03-12 | 2018-03-12 | Lamb wave space sampling signal fitting method based on Morlet mother wavelet |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108491777A CN108491777A (en) | 2018-09-04 |
| CN108491777B true CN108491777B (en) | 2020-04-17 |
Family
ID=63338834
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810204278.9A Expired - Fee Related CN108491777B (en) | 2018-03-12 | 2018-03-12 | Lamb wave space sampling signal fitting method based on Morlet mother wavelet |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108491777B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110018235B (en) * | 2019-03-12 | 2021-07-13 | 上海大学 | Time domain compensation-based under-sampling Lamb wave number searching method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105372326A (en) * | 2015-10-20 | 2016-03-02 | 南京航空航天大学 | Space-wavenumber filter based on Lamb wave wavenumber scanning |
-
2018
- 2018-03-12 CN CN201810204278.9A patent/CN108491777B/en not_active Expired - Fee Related
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105372326A (en) * | 2015-10-20 | 2016-03-02 | 南京航空航天大学 | Space-wavenumber filter based on Lamb wave wavenumber scanning |
Non-Patent Citations (2)
| Title |
|---|
| Non-contact ultrasonic technique for Lamb wave characterization in composite plates;M.S. Harb等;《Ultrasonics》;20150904;全文 * |
| 基于多频率数据融合的Lamb 波损伤定位研究;杨晓华等;《声学技术》;20170430;第36卷(第2期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108491777A (en) | 2018-09-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yan | A Bayesian approach for damage localization in plate-like structures using Lamb waves | |
| CN106990018B (en) | A kind of prestressed concrete beam Grouted density intelligent identification Method | |
| Flynn et al. | Maximum-likelihood estimation of damage location in guided-wave structural health monitoring | |
| Dai et al. | Structure damage localization with ultrasonic guided waves based on a time–frequency method | |
| Xu et al. | Lamb wave inspection for composite laminates using a combined method of sparse reconstruction and delay-and-sum | |
| CN100523765C (en) | Vibrating detection method for detecting looseness of large-scale generator rotor slot wedge and apparatus therefor | |
| Yu et al. | Advanced signal processing for enhanced damage detection with piezoelectric wafer active sensors | |
| CN106331951A (en) | Harmonic distortion measurement method and system based on continuous logarithmic swept response | |
| CN106255027B (en) | A kind of the sound quality Small Enclosure appraisal procedure and system of non-linear audio system | |
| CN109374740B (en) | Synthetic aperture MUSIC damage positioning method based on array error correction | |
| CN104101651A (en) | Grain size nondestructive evaluation method based on haar wavelet | |
| CN103344709A (en) | Piezoelectric ultrasonic phased array multi-damage imaging method based on linear mapping frequency dispersion compensation | |
| Zhao et al. | Reconstruction of Lamb wave dispersion curves by sparse representation with continuity constraints | |
| Yuan et al. | A single frequency component-based re-estimated MUSIC algorithm for impact localization on complex composite structures | |
| CN109683134A (en) | A kind of high-resolution localization method towards rotation sound source | |
| CN102333052A (en) | Underwater sound signal blind deconvolution method suitable for shallow sea low-frequency conditions | |
| CN110243521A (en) | A kind of sheet stress measurement method and sheet stress measuring system | |
| CN108491777B (en) | Lamb wave space sampling signal fitting method based on Morlet mother wavelet | |
| CN110542723B (en) | Guided wave signal sparse decomposition and damage positioning-based two-stage damage position identification method | |
| CN105717198A (en) | Single frequency and re-estimation MUSIC (multiple signal classification) method for structure-oriented impact locating | |
| Guo et al. | A novel solution for improved performance of Time-frequency concentration | |
| CN103383413A (en) | Real-time harmonic detection method based on direct weight determination method | |
| Li et al. | A novel ultrasonic array signal processing scheme for wind measurement | |
| CN107741263B (en) | Liquid level estimation method based on frequency domain information fusion | |
| Yan et al. | Time-delay estimation of ultrasonic echoes based on the physical model matching |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200417 Termination date: 20210312 |