CN110702785A - Method and device for time-frequency domain modal decomposition and defect positioning of frequency dispersion Lamb wave polynomial - Google Patents
Method and device for time-frequency domain modal decomposition and defect positioning of frequency dispersion Lamb wave polynomial Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/041—Analysing solids on the surface of the material, e.g. using Lamb, Rayleigh or shear waves
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/07—Analysing solids by measuring propagation velocity or propagation time of acoustic waves
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/36—Detecting the response signal, e.g. electronic circuits specially adapted therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
Abstract
The invention discloses a method and a device for time-frequency domain modal decomposition and defect positioning of a frequency dispersion Lamb wave polynomial, wherein the method comprises the following steps: mounting Lamb wave transmitting and receiving transducers on a flat plate to be tested; the transmitting transducer is connected with an ultrasonic excitation signal to send out Lamb waves; receiving Lamb waves by a receiving transducer, and obtaining detection data through amplification, filtering and sampling; analyzing the time-frequency distribution characteristics of Lamb waves of different modes according to a Lamb wave frequency dispersion curve; performing polynomial time-frequency domain modulation and scaling transformation on the basis functions to construct a polynomial time-frequency domain basis function set; decomposing the detection data in the basis function set to obtain matched basis functions, and reconstructing signals; tracing the matched basis functions to obtain the mode of lamb waves, extracting the instantaneous frequency of the basis functions and obtaining travel time data; and calculating the defect distance according to the group velocity of the corresponding mode. The method can effectively decompose the multi-mode Lamb waves and provide high-precision defect positioning.
Description
Technical Field
The invention relates to the technical field of nondestructive testing, in particular to a method and a device for time-frequency domain modal decomposition and defect positioning of a frequency dispersion Lamb wave polynomial.
Background
Flat plate members are widely used in modern industry. However, structural damage often occurs, seriously threatening the proper functioning and production of the instrument. For example, the corrosive effect will result in a thinner wall thickness of the tank floor, which in the severe cases may cause oil leakage, thereby causing a hazard. Ultrasonic guided waves provide an effective method of detecting structural health. Guided waves are mechanical waves that can propagate long distances along a particular structure with less energy loss. Lamb waves can be present in a plate member, whose vibrations cover the entire plate thickness range, and can be used to detect defects in and on the surface of the plate. Lamb waves can be generated by electromagnetic ultrasonic or piezoelectric transducers, and will be reflected and transmitted when Lamb waves encounter discontinuities in the propagation path. The received reflected Lamb wave therefore contains the health of its propagation path. Therefore, by extracting the features of the received Lamb wave, a defect can be detected.
However, Lamb waves have the characteristics of frequency dispersion and multimode, and influence on signal feature extraction. The dispersion characteristic of Lamb waves means that the wave velocity of Lamb waves is not constant and varies with frequency and plate thickness. Since the frequency of the excitation signal has a certain bandwidth, a pure single-frequency Lamb wave cannot be generated. Lamb waves with different frequencies have different wave speeds, so that wave packets of Lamb wave signals are widened in the time domain, and the problem of time domain overlapping of the signals is brought. The multimode property of Lamb waves means that Lamb has many modes, and even under the same excitation condition, multiple modes can be generated simultaneously, and the modes propagate along a flat plate, so that the problem of mode overlapping is brought, and the extraction of useful information is interfered.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, an object of the present invention is to provide a method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial, which can effectively decompose a multimode Lamb wave and provide high-precision defect localization.
The invention also aims to provide a device for time-frequency domain modal decomposition and defect location of the frequency dispersion Lamb wave polynomial.
In order to achieve the above object, an embodiment of the present invention provides a method for time-frequency domain modal decomposition and defect location of a dispersive Lamb wave polynomial, including:
s1, obtaining a flat plate to be tested, and arranging a Lamb wave transmitting electromagnetic ultrasonic transducer and a Lamb wave receiving electromagnetic ultrasonic transducer on the flat plate to be tested;
s2, applying an ultrasonic excitation signal in the Lamb wave transmitting electromagnetic ultrasonic transducer to send out a Lamb wave signal;
s3, receiving the Lamb wave signals through the Lamb wave receiving electromagnetic ultrasonic transducer, and amplifying, filtering and sampling the Lamb wave signals to obtain detection data;
s4, obtaining group velocities of Lamb waves in different modes within the frequency range of the ultrasonic excitation signal according to the Lamb wave signal, and calculating time-frequency distribution characteristics of the Lamb waves in different modes according to the Lamb wave signal;
s5, fitting the time-frequency distribution characteristics into a polynomial time-frequency relation through a least square method;
s6, obtaining a Gaussian function, modulating the Gaussian function through the polynomial time-frequency relationship, and performing scaling transformation on the debugged Gaussian function to generate a polynomial time-frequency domain basis function set;
s7, decomposing the detection data in the polynomial time-frequency domain basis function set to obtain basis functions matched with the detection data, performing signal reconstruction by using the basis functions matched with the detection data, and calculating a reconstruction error;
s8, judging whether the reconstruction error is smaller than a preset error value, if so, executing S8, otherwise, executing S7, and decomposing again;
s9, processing the basis functions matched with the detection data to obtain different modes of Lamb waves in the detection data, extracting the instantaneous frequency of the basis functions matched with the detection data, and obtaining travel time data of the Lamb waves in the detection data in different modes according to the instantaneous frequency;
and S10, calculating the distance between the defect position and the Lamb wave receiving electromagnetic ultrasonic transducer according to travel time data of different modes and group velocities corresponding to the modes.
According to the method for time-frequency domain modal decomposition and defect positioning of the frequency dispersion Lamb wave polynomial, the Lamb wave transmitting and receiving transducers are arranged on a flat plate to be detected; the transmitting transducer is connected with an excitation signal passing through the power amplifier; receiving Lamb waves by a receiving transducer, and obtaining detection data through amplification, filtering and sampling; analyzing the time-frequency distribution characteristics of Lamb waves in different modes according to the Lamb wave frequency dispersion curve; performing polynomial time-frequency domain modulation and scaling transformation on the basis functions to construct a polynomial time-frequency domain basis function set; decomposing the detection data in the basis function set to obtain matched basis functions, and performing signal reconstruction; tracing the matched basis functions to obtain the mode of Lamb waves, extracting the instantaneous frequency of the basis functions and obtaining travel time data; and calculating the defect distance according to the group velocity of the corresponding mode. The method can effectively decompose the multi-mode Lamb waves and provide high-precision defect positioning.
In addition, the method for time-frequency domain modal decomposition and defect location of frequency-dispersed Lamb wave polynomial according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the present invention, the ultrasonic excitation signal is a sine narrowband signal modulated by a hanning window, and the expression of the ultrasonic excitation signal is:
wherein, H (t)Is a step function, N is the number of cycles, t is the time, fCIs the center frequency of the ultrasonic excitation signal.
Further, in one embodiment of the present invention, the Lamb wave transmitting electromagnetic ultrasonic transducer and the Lamb wave receiving electromagnetic ultrasonic transducer include a permanent magnet and a close-wound spiral coil, the permanent magnet being placed above the close-wound spiral coil.
Further, in an embodiment of the present invention, the expression of the polynomial time-frequency relationship is:
wherein, ckIs a polynomial coefficient, n is the degree of the polynomial, t is time, and M is the number of the fitted polynomial time-frequency relationship.
Further, in one embodiment of the present invention, the gaussian function is:
wherein e is a natural base number, and t is time.
Further, in an embodiment of the present invention, the polynomial time-frequency domain basis function set expression is:
wherein j is an imaginary unit, s is a coefficient of expansion, and e is a natural base number.
Further, in an embodiment of the present invention, the decomposition of the detection data in the set of polynomial time-frequency-domain basis functions is performed by a matching pursuit algorithm.
Further, in an embodiment of the present invention, the reconstruction error is:
wherein y (t) is the detection data, αnAnd (3) decomposing the detection data on the polynomial time-frequency domain basis function set to obtain a projection coefficient, wherein P is the iteration number of the decomposition process.
Further, in an embodiment of the present invention, travel time data of different modes are multiplied by group velocities corresponding to the modes, so as to obtain a distance between a defect position and the Lamb wave receiving electromagnetic ultrasonic transducer.
In order to achieve the above object, an embodiment of the present invention provides a device for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial, including:
the device comprises a setting module, a detection module and a control module, wherein the setting module is used for obtaining a flat plate to be detected, and a Lamb wave transmitting electromagnetic ultrasonic transducer and a Lamb wave receiving electromagnetic ultrasonic transducer are arranged on the flat plate to be detected;
the excitation module is used for applying an ultrasonic excitation signal in the Lamb wave transmitting electromagnetic ultrasonic transducer to send out a Lamb wave signal;
the acquisition module is used for receiving the Lamb wave signals through the Lamb wave receiving electromagnetic ultrasonic transducer, and amplifying, filtering and sampling the Lamb wave signals to obtain detection data;
the computing module is used for obtaining group velocities of Lamb waves in different modes in the frequency range of the ultrasonic excitation signal according to the Lamb wave signal and computing time-frequency distribution characteristics of the Lamb waves in different modes according to the Lamb wave signal;
the fitting module is used for fitting the time-frequency distribution characteristics into a polynomial time-frequency relation through a least square method;
the generating module is used for acquiring a Gaussian function, modulating the Gaussian function through the polynomial time-frequency relationship, and performing scaling transformation on the debugged Gaussian function to generate a polynomial time-frequency domain basis function set;
the decomposition module is used for decomposing the detection data in the polynomial time-frequency domain basis function set to obtain a basis function matched with the detection data, performing signal reconstruction by using the basis function matched with the detection data, and calculating a reconstruction error;
the judging module is used for judging whether the reconstruction error is smaller than a preset error value, if so, executing the processing module, and if not, executing the decomposition module to decompose again;
the processing module is used for processing the basis functions matched with the detection data to obtain different modes of Lamb waves in the detection data, extracting the instantaneous frequency of the basis functions matched with the detection data, and obtaining travel time data of the different modes of Lamb waves in the detection data according to the instantaneous frequency;
and the positioning module is used for calculating the distance between the defect position and the Lamb wave receiving electromagnetic ultrasonic transducer according to the travel time data of different modes and the group velocity corresponding to the modes.
According to the device for time-frequency domain modal decomposition and defect positioning of the frequency dispersion Lamb wave polynomial, the Lamb wave transmitting and receiving transducer is arranged on the flat plate to be detected; the transmitting transducer is connected with an excitation signal passing through the power amplifier; receiving Lamb waves by a receiving transducer, and obtaining detection data through amplification, filtering and sampling; analyzing the time-frequency distribution characteristics of Lamb waves in different modes according to the Lamb wave frequency dispersion curve; performing polynomial time-frequency domain modulation and scaling transformation on the basis functions to construct a polynomial time-frequency domain basis function set; decomposing the detection data in the basis function set to obtain matched basis functions, and performing signal reconstruction; tracing the matched basis functions to obtain the mode of Lamb waves, extracting the instantaneous frequency of the basis functions and obtaining travel time data; and calculating the defect distance according to the group velocity of the corresponding mode. The device can effectively decompose the multimode Lamb waves and provide high-precision defect positioning.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flowchart of a method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial according to an embodiment of the present invention;
FIG. 2 is a time-frequency domain mode decomposition and defect location method for a dispersive Lamb wave polynomial according to another embodiment of the present invention;
FIG. 3 is a diagram of Lamb wave detection signal waveforms and reconstructed signal waveforms according to one embodiment of the invention;
FIG. 4 is a plot of time-of-flight extraction for the symmetric mode and anti-symmetric mode of Lamb wave fundamental according to one embodiment of the present invention;
fig. 5 is a schematic structural diagram of a device for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial according to an embodiment of the invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes a method and an apparatus for time-frequency domain modal decomposition and defect localization of a frequency-dispersive Lamb wave polynomial according to an embodiment of the present invention with reference to the accompanying drawings.
First, a time-frequency domain modal decomposition and defect localization method of a frequency-dispersion Lamb wave polynomial proposed according to an embodiment of the present invention will be described with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial according to an embodiment of the present invention.
As shown in fig. 1 and fig. 2, the method for time-frequency domain modal decomposition and defect localization of frequency-dispersed Lamb wave polynomial includes the following steps:
step S1, obtaining a flat plate to be tested, and arranging a Lamb wave transmitting electromagnetic ultrasonic transducer and a Lamb wave receiving electromagnetic ultrasonic transducer on the flat plate to be tested.
In an embodiment of the present invention, the Lamb wave transmitting electromagnetic ultrasonic transducer and the Lamb wave receiving electromagnetic ultrasonic transducer include a permanent magnet and a close-wound spiral coil, and the permanent magnet is placed above the close-wound spiral coil to provide a bias magnetic field.
Step S2, an ultrasonic excitation signal is applied in the Lamb wave transmitting electromagnetic ultrasonic transducer to emit a Lamb wave signal.
Further, in one embodiment of the present invention, the ultrasonic excitation signal is a hanning window modulated sinusoidal narrowband signal centered at frequency fCBandwidth of 2 Δ fBThe signal expression is:
wherein H (t) is a step function, N is the number of cycles, t is the time, fCIs the center frequency of the ultrasonic excitation signal.
And step S3, receiving the Lamb wave signals through the Lamb wave receiving electromagnetic ultrasonic transducer, and amplifying, filtering and sampling the Lamb wave signals to obtain detection data.
It can be understood that Lamb wave signals are received by the Lamb wave receiving electromagnetic ultrasonic transducer, amplified and filtered by the signal conditioning circuit, and then the detection data is obtained by sampling.
Wherein, as an example, the magnification is 2000 times, the filtering adopts a high-order band-pass filter, and the sampling frequency is 2 MHz.
Step S4, obtaining group velocities of Lamb waves in different modes in the frequency range of the ultrasonic excitation signal according to the Lamb wave signals, and calculating time-frequency distribution characteristics of the Lamb waves in different modes according to the Lamb wave signals.
It can be understood that the group velocities of Lamb waves of different modes in the frequency range of the ultrasonic excitation signal are obtained according to the Lamb wave dispersion curve of the Lamb wave signal, and the time-frequency distribution characteristics (t) of the Lamb waves of different modes after propagating for different distances are calculated according to the Lamb wave dispersion curvei,fi) Wherein, tiAs discrete time coordinates, fiAre discrete frequency coordinates.
And step S5, fitting the time-frequency distribution characteristics to a polynomial time-frequency relation by a least square method.
Further, in an embodiment of the present invention, the expression of the polynomial time-frequency relationship is:
wherein, ckIs a polynomial coefficient, n is the degree of the polynomial, t is time, and M is the number of the fitted polynomial time-frequency relationship.
And step S6, acquiring a Gaussian function, modulating the Gaussian function through a polynomial time-frequency relation, and performing scaling transformation on the debugged Gaussian function to generate a polynomial time-frequency domain basis function set.
It can be understood that polynomial time-frequency domain modulation and scaling transformation are performed on the gaussian function to construct a polynomial time-frequency domain basis function set.
As an example, in the embodiment of the present invention, the gaussian function expression is adopted as:
wherein e is a natural base number, and t is time.
Modulating a Gaussian function g (t) according to the fitted polynomial time-frequency relation, and performing scaling transformation to obtain a basis function set:
wherein j is an imaginary unit, s is a coefficient of expansion, and e is a natural base number.
And step S7, decomposing the detection data in the polynomial time-frequency domain basis function set to obtain basis functions matched with the detection data, performing signal reconstruction by using the basis functions matched with the detection data, and calculating a reconstruction error.
And decomposing the detection data obtained in the step S3 in a polynomial time-frequency domain basis function set, obtaining a basis function matched with the detection data in the basis function set, reconstructing signals according to the obtained matched basis function, and comparing the reconstructed signals with the original Lamb wave signals to obtain reconstruction errors.
As one example, in one embodiment of the invention, the decomposition process may be accomplished using a matching pursuit algorithm.
Step S8, determining whether the reconstruction error is smaller than a preset error value, if yes, executing S8, otherwise, executing S7, and decomposing again.
In one embodiment of the present invention, the reconstruction error is expressed as:
it can be understood that, it is determined whether the reconstruction error is smaller than the preset error value, that is:
wherein y is detection data and alphanAnd (3) detecting a projection coefficient obtained by decomposing the data on the basis function, wherein P is the iteration number of the decomposition process, and epsilon is a preset error value.
If the reconstruction error is not less than the preset error value, S7 is executed, and the matched basis functions are obtained by decomposing again in the polynomial time-frequency domain basis function set until the reconstruction error is less than the preset error value.
Step S9, processing the basis functions matched with the detection data to obtain different modes of Lamb waves in the detection data, extracting the instantaneous frequency of the basis functions matched with the detection data, and obtaining travel time data of the different modes of Lamb waves in the detection data according to the instantaneous frequency.
When the reconstruction error is smaller than the preset error value, tracing the source of the matched basis function to obtain the mode of the Lamb wave, extracting the instantaneous frequency of the matched basis function, and obtaining travel time data corresponding to the central frequency of the Lamb wave.
In the embodiment of the invention, the modes of the obtained Lamb wave are a fundamental wave symmetric mode and a fundamental wave antisymmetric mode.
And step S10, calculating the distance between the defect position and the Lamb wave receiving electromagnetic ultrasonic transducer according to the travel time data of different modes and the group velocity corresponding to the modes.
And calculating the defect position according to the travel time data of different modes of the Lamb wave obtained in the step S9 and the group velocity corresponding to the different modes.
In an embodiment of the invention, the decomposed modes are extracted when the user walks, the travel time data is the time difference between the direct wave and the reflected wave of the same mode, and the travel time of each mode is multiplied by the corresponding group velocity, so that the distance between the defect and the receiving transducer can be obtained.
Fig. 3 is a diagram of Lamb wave detection signal waveforms and reconstructed signal waveforms according to one embodiment of the invention. As shown in fig. 3, the contour and amplitude of the reconstructed signal keep high consistency with the original detection signal. FIG. 4 is a time-lapse extraction chart of symmetric mode and anti-symmetric mode of Lamb wave fundamental wave according to an embodiment of the present invention. As shown in fig. 4, the travel time between the direct wave and the reflected wave in the fundamental symmetric mode is 51.15us, and the travel time between the direct wave and the reflected wave in the fundamental antisymmetric mode is 89.1 us. Further, according to the group velocities of the two modes, the defect distance calculated from the fundamental symmetric mode was 270.6mm, and the defect distance calculated from the fundamental anti-symmetric mode was 265.1 mm. The actual defect distance was 261.7 mm. Therefore, the error between the calculated distance and the actual distance is very small, and the high-precision defect positioning is realized by the scattered Lamb wave polynomial time-frequency domain adaptive mode decomposition and defect positioning method.
According to the method for the time-frequency domain modal decomposition and defect positioning of the frequency dispersion Lamb wave polynomial, which is provided by the embodiment of the invention, Lamb wave transmitting and receiving transducers are arranged on a flat plate to be detected; the transmitting transducer is connected with an excitation signal passing through the power amplifier; receiving Lamb waves by a receiving transducer, and obtaining detection data through amplification, filtering and sampling; analyzing the time-frequency distribution characteristics of Lamb waves in different modes according to the Lamb wave frequency dispersion curve; performing polynomial time-frequency domain modulation and scaling transformation on the basis functions to construct a polynomial time-frequency domain basis function set; decomposing the detection data in the basis function set to obtain matched basis functions, and performing signal reconstruction; tracing the matched basis functions to obtain the mode of Lamb waves, extracting the instantaneous frequency of the basis functions and obtaining travel time data; and calculating the defect distance according to the group velocity of the corresponding mode. The method can effectively decompose the multi-mode Lamb waves and provide high-precision defect positioning.
Next, a time-frequency domain modal decomposition and defect localization apparatus of a frequency-dispersive Lamb wave polynomial according to an embodiment of the present invention will be described with reference to the accompanying drawings.
Fig. 5 is a schematic structural diagram of a device for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial according to an embodiment of the invention.
As shown in fig. 5, the apparatus for time-frequency domain modal decomposition and defect localization of dispersive Lamb wave polynomial includes: the device comprises a setting module 100, an excitation module 200, an acquisition module 300, a calculation module 400, a fitting module 500, a generation module 600, a decomposition module 700, a judgment module 800, a processing module 900 and a positioning module 1000.
The setting module 100 is configured to obtain a flat plate to be tested, and set a Lamb wave transmitting electromagnetic ultrasonic transducer and a Lamb wave receiving electromagnetic ultrasonic transducer on the flat plate to be tested.
And the excitation module 200 is used for applying an ultrasonic excitation signal in the Lamb wave transmitting electromagnetic ultrasonic transducer to emit a Lamb wave signal.
The acquisition module 300 is configured to receive Lamb wave signals through a Lamb wave receiving electromagnetic ultrasonic transducer, and amplify, filter and sample the Lamb wave signals to obtain detection data.
The calculating module 400 is configured to obtain group velocities of Lamb waves of different modes within the frequency range of the ultrasonic excitation signal according to the Lamb wave signal, and calculate a time-frequency distribution characteristic of the Lamb waves of the different modes according to the Lamb wave signal.
The fitting module 500 is configured to fit the time-frequency distribution characteristics to a polynomial time-frequency relationship by a least square method.
The generating module 600 is configured to obtain a gaussian function, modulate the gaussian function according to a polynomial time-frequency relationship, and perform scaling transformation on the debugged gaussian function to generate a polynomial time-frequency domain basis function set.
And the decomposition module 700 is configured to decompose the detection data in the polynomial time-frequency domain basis function set to obtain a basis function matched with the detection data, perform signal reconstruction by using the basis function matched with the detection data, and calculate a reconstruction error.
The determining module 800 is configured to determine whether the reconstruction error is smaller than a preset error value, if so, execute the processing module, and if not, execute the decomposition module to decompose again.
The processing module 900 is configured to process the basis functions matched with the detection data to obtain different modes of Lamb waves in the detection data, extract instantaneous frequencies of the basis functions matched with the detection data, and obtain travel time data of the different modes of Lamb waves in the detection data according to the instantaneous frequencies.
And the positioning module 1000 is configured to calculate a distance between the defect position and the Lamb wave receiving electromagnetic ultrasonic transducer according to travel time data of different modes and group velocities corresponding to the modes.
It should be noted that the explanation of the embodiments of the time-frequency domain mode decomposition and defect location method for the dispersive Lamb wave polynomial is also applicable to the apparatus of the embodiments, and is not repeated here.
According to the device for the time-frequency domain modal decomposition and defect positioning of the frequency dispersion Lamb wave polynomial, which is provided by the embodiment of the invention, Lamb wave transmitting and receiving transducers are arranged on a flat plate to be detected; the transmitting transducer is connected with an excitation signal passing through the power amplifier; receiving Lamb waves by a receiving transducer, and obtaining detection data through amplification, filtering and sampling; analyzing the time-frequency distribution characteristics of Lamb waves in different modes according to the Lamb wave frequency dispersion curve; performing polynomial time-frequency domain modulation and scaling transformation on the basis functions to construct a polynomial time-frequency domain basis function set; decomposing the detection data in the basis function set to obtain matched basis functions, and performing signal reconstruction; tracing the matched basis functions to obtain the mode of Lamb waves, extracting the instantaneous frequency of the basis functions and obtaining travel time data; and calculating the defect distance according to the group velocity of the corresponding mode. The device can effectively decompose the multimode Lamb waves and provide high-precision defect positioning.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A method for time-frequency domain modal decomposition and defect positioning of a frequency dispersion Lamb wave polynomial is characterized by comprising the following steps:
s1, obtaining a flat plate to be tested, and arranging a Lamb wave transmitting electromagnetic ultrasonic transducer and a Lamb wave receiving electromagnetic ultrasonic transducer on the flat plate to be tested;
s2, applying an ultrasonic excitation signal in the Lamb wave transmitting electromagnetic ultrasonic transducer to send out a Lamb wave signal;
s3, receiving the Lamb wave signals through the Lamb wave receiving electromagnetic ultrasonic transducer, and amplifying, filtering and sampling the Lamb wave signals to obtain detection data;
s4, obtaining group velocities of Lamb waves in different modes within the frequency range of the ultrasonic excitation signal according to the Lamb wave signal, and calculating time-frequency distribution characteristics of the Lamb waves in different modes according to the Lamb wave signal;
s5, fitting the time-frequency distribution characteristics into a polynomial time-frequency relation through a least square method;
s6, obtaining a Gaussian function, modulating the Gaussian function through the polynomial time-frequency relationship, and performing scaling transformation on the debugged Gaussian function to generate a polynomial time-frequency domain basis function set;
s7, decomposing the detection data in the polynomial time-frequency domain basis function set to obtain basis functions matched with the detection data, performing signal reconstruction by using the basis functions matched with the detection data, and calculating a reconstruction error;
s8, judging whether the reconstruction error is smaller than a preset error value, if so, executing S8, otherwise, executing S7, and decomposing again;
s9, processing the basis functions matched with the detection data to obtain different modes of Lamb waves in the detection data, extracting the instantaneous frequency of the basis functions matched with the detection data, and obtaining travel time data of the Lamb waves in the detection data in different modes according to the instantaneous frequency;
and S10, calculating the distance between the defect position and the Lamb wave receiving electromagnetic ultrasonic transducer according to travel time data of different modes and group velocities corresponding to the modes.
2. The method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial according to claim 1, wherein the ultrasonic excitation signal is a sine narrow-band signal modulated by a hanning window, and the expression of the ultrasonic excitation signal is as follows:
wherein H (t) is a step function, N is the number of cycles, t is the time, fCIs the center frequency of the ultrasonic excitation signal.
3. The method for time-frequency domain modal decomposition and defect localization of frequency-dispersed Lamb wave polynomials of claim 1,
the Lamb wave transmitting electromagnetic ultrasonic transducer and the Lamb wave receiving electromagnetic ultrasonic transducer comprise permanent magnets and close-wound spiral coils, and the permanent magnets are placed above the close-wound spiral coils.
4. The method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial of claim 1, wherein the polynomial time-frequency relationship has the expression:
wherein, ckIs a polynomial coefficient, n is the degree of the polynomial, t is time, and M is the number of the fitted polynomial time-frequency relationship.
5. The method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial according to claim 1, wherein the gaussian function is:
wherein e is a natural base number, and t is time.
6. The method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial of claim 1, wherein the polynomial set of time-frequency domain basis functions is expressed as:
wherein j is an imaginary unit, s is a coefficient of expansion, and e is a natural base number.
7. The method for time-frequency domain modal decomposition and defect localization of frequency-dispersed Lamb wave polynomials of claim 1,
and completing the decomposition of the detection data in the polynomial time-frequency domain basis function set through a matching pursuit algorithm.
8. The method for time-frequency domain modal decomposition and defect localization of a dispersive Lamb wave polynomial according to claim 1, wherein the reconstruction error is:
wherein y (t) is the detection data, αnAnd (3) decomposing the detection data on the polynomial time-frequency domain basis function set to obtain a projection coefficient, wherein P is the iteration number of the decomposition process.
9. The method for time-frequency domain modal decomposition and defect localization of frequency-dispersed Lamb wave polynomials of claim 1,
and multiplying the travel time data of different modes by the group velocity corresponding to the modes to obtain the distance between the defect position and the Lamb wave receiving electromagnetic ultrasonic transducer.
10. A device for time-frequency domain modal decomposition and defect location of a dispersive Lamb wave polynomial is characterized by comprising:
the device comprises a setting module, a detection module and a control module, wherein the setting module is used for obtaining a flat plate to be detected, and a Lamb wave transmitting electromagnetic ultrasonic transducer and a Lamb wave receiving electromagnetic ultrasonic transducer are arranged on the flat plate to be detected;
the excitation module is used for applying an ultrasonic excitation signal in the Lamb wave transmitting electromagnetic ultrasonic transducer to send out a Lamb wave signal;
the acquisition module is used for receiving the Lamb wave signals through the Lamb wave receiving electromagnetic ultrasonic transducer, and amplifying, filtering and sampling the Lamb wave signals to obtain detection data;
the computing module is used for obtaining group velocities of Lamb waves in different modes in the frequency range of the ultrasonic excitation signal according to the Lamb wave signal and computing time-frequency distribution characteristics of the Lamb waves in different modes according to the Lamb wave signal;
the fitting module is used for fitting the time-frequency distribution characteristics into a polynomial time-frequency relation through a least square method;
the generating module is used for acquiring a Gaussian function, modulating the Gaussian function through the polynomial time-frequency relationship, and performing scaling transformation on the debugged Gaussian function to generate a polynomial time-frequency domain basis function set;
the decomposition module is used for decomposing the detection data in the polynomial time-frequency domain basis function set to obtain a basis function matched with the detection data, performing signal reconstruction by using the basis function matched with the detection data, and calculating a reconstruction error;
the judging module is used for judging whether the reconstruction error is smaller than a preset error value, if so, executing the processing module, and if not, executing the decomposition module to decompose again;
the processing module is used for processing the basis functions matched with the detection data to obtain different modes of Lamb waves in the detection data, extracting the instantaneous frequency of the basis functions matched with the detection data, and obtaining travel time data of the different modes of Lamb waves in the detection data according to the instantaneous frequency;
and the positioning module is used for calculating the distance between the defect position and the Lamb wave receiving electromagnetic ultrasonic transducer according to the travel time data of different modes and the group velocity corresponding to the modes.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110333285A (en) * | 2019-07-04 | 2019-10-15 | 大连海洋大学 | Ultrasonic Lamb waves Defect signal recognition method based on variation mode decomposition |
| CN111337574A (en) * | 2020-04-09 | 2020-06-26 | 上海工程技术大学 | Topological imaging method and device based on ultrasonic lamb wave plate type ballastless track cracks |
| CN111812207A (en) * | 2020-07-21 | 2020-10-23 | 大连理工大学 | Non-reference damage diagnosis imaging method based on ultrasonic guided wave conversion mode extraction |
| CN113533510A (en) * | 2021-06-29 | 2021-10-22 | 北京交通大学 | Method and device for identifying fatigue microcracks of steel rail |
| CN113686959A (en) * | 2021-09-15 | 2021-11-23 | 中国科学院声学研究所 | Imaging method and device based on ultrasonic lamb wave defect detection |
| CN114994175A (en) * | 2022-05-18 | 2022-09-02 | 国营芜湖机械厂 | Space coupling ultrasonic stress detection device and method for modal decomposition double-spectrum analysis |
| CN115017640A (en) * | 2022-05-23 | 2022-09-06 | 哈尔滨工业大学 | Comb-shaped piezoelectric transducer structure optimization design method based on time-space domain hybrid analysis |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05275761A (en) * | 1991-06-05 | 1993-10-22 | Acoustic Imaging Technol Corp | Piezoelectric ceramic-epoxy composite and manufacture thereof |
| CN102128881A (en) * | 2010-12-22 | 2011-07-20 | 南京邮电大学 | Method for monitoring Lamb wave engineering structural damage by utilizing signal decomposition |
| US8548750B1 (en) * | 2007-11-30 | 2013-10-01 | Intellectual Assests LLC | Path classification and estimation method and system for prognosticating asset life |
| WO2013032450A3 (en) * | 2011-08-30 | 2014-03-20 | Georgia Tech Research Corporation | Weld analysis using laser generated narrowband lamb waves |
| CN103698748A (en) * | 2013-12-16 | 2014-04-02 | 南京航空航天大学 | 2D-MUSIC (Two Dimensional-Multiple Signal Classification) impact locating method based on signal wave speed and attenuation compensation in composite material |
| CN103954697A (en) * | 2014-05-20 | 2014-07-30 | 南京信息工程大学 | Fractional differentiation-based lamb wave denoising method |
| CN106596737A (en) * | 2016-11-29 | 2017-04-26 | 大连理工大学 | Lamb wave structure-based multi-mode signal separation method |
| US20170168021A1 (en) * | 2015-12-15 | 2017-06-15 | University Of South Carolina | Structural health monitoring method and system |
| CN107727734A (en) * | 2017-08-24 | 2018-02-23 | 中国人民解放军空军勤务学院 | Method for compensating signal based on fitting of a polynomial and linear piezoelectric sensor array |
| CN107807176A (en) * | 2017-10-12 | 2018-03-16 | 南京航空航天大学 | A kind of frequency dispersion Lamb wave signal resolution Enhancement Method |
| CN108459087A (en) * | 2018-04-25 | 2018-08-28 | 大连理工大学 | A kind of multi-modal Lamb wave modal separation method applied to harden structure damage check |
| CN108921113A (en) * | 2018-07-10 | 2018-11-30 | 南京信息工程大学 | Multi-mode Lamb wave signal separating method based on fractional order differential |
| EP3415640A1 (en) * | 2017-06-16 | 2018-12-19 | Foundation For Research And Technology Hellas | Detecting nucleic acids in impure samples with an acoustic wave sensor |
| CN109212040A (en) * | 2018-08-24 | 2019-01-15 | 清华大学 | The extracting method when analysis of Lamb wave time-frequency crestal line is walked |
| CN109856252A (en) * | 2019-02-01 | 2019-06-07 | 南京信息工程大学 | A kind of multi-mode Lamb wave separation method based on dispersion compensation and blind separation |
| CN110045014A (en) * | 2019-03-11 | 2019-07-23 | 西安交通大学 | Lamb wave frequency dispersion removing method and its system based on Bayesian learning |
-
2019
- 2019-09-24 CN CN201910906037.3A patent/CN110702785B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05275761A (en) * | 1991-06-05 | 1993-10-22 | Acoustic Imaging Technol Corp | Piezoelectric ceramic-epoxy composite and manufacture thereof |
| US8548750B1 (en) * | 2007-11-30 | 2013-10-01 | Intellectual Assests LLC | Path classification and estimation method and system for prognosticating asset life |
| CN102128881A (en) * | 2010-12-22 | 2011-07-20 | 南京邮电大学 | Method for monitoring Lamb wave engineering structural damage by utilizing signal decomposition |
| WO2013032450A3 (en) * | 2011-08-30 | 2014-03-20 | Georgia Tech Research Corporation | Weld analysis using laser generated narrowband lamb waves |
| CN103698748A (en) * | 2013-12-16 | 2014-04-02 | 南京航空航天大学 | 2D-MUSIC (Two Dimensional-Multiple Signal Classification) impact locating method based on signal wave speed and attenuation compensation in composite material |
| CN103954697A (en) * | 2014-05-20 | 2014-07-30 | 南京信息工程大学 | Fractional differentiation-based lamb wave denoising method |
| US20170168021A1 (en) * | 2015-12-15 | 2017-06-15 | University Of South Carolina | Structural health monitoring method and system |
| CN106596737A (en) * | 2016-11-29 | 2017-04-26 | 大连理工大学 | Lamb wave structure-based multi-mode signal separation method |
| EP3415640A1 (en) * | 2017-06-16 | 2018-12-19 | Foundation For Research And Technology Hellas | Detecting nucleic acids in impure samples with an acoustic wave sensor |
| CN107727734A (en) * | 2017-08-24 | 2018-02-23 | 中国人民解放军空军勤务学院 | Method for compensating signal based on fitting of a polynomial and linear piezoelectric sensor array |
| CN107807176A (en) * | 2017-10-12 | 2018-03-16 | 南京航空航天大学 | A kind of frequency dispersion Lamb wave signal resolution Enhancement Method |
| CN108459087A (en) * | 2018-04-25 | 2018-08-28 | 大连理工大学 | A kind of multi-modal Lamb wave modal separation method applied to harden structure damage check |
| CN108921113A (en) * | 2018-07-10 | 2018-11-30 | 南京信息工程大学 | Multi-mode Lamb wave signal separating method based on fractional order differential |
| CN109212040A (en) * | 2018-08-24 | 2019-01-15 | 清华大学 | The extracting method when analysis of Lamb wave time-frequency crestal line is walked |
| CN109856252A (en) * | 2019-02-01 | 2019-06-07 | 南京信息工程大学 | A kind of multi-mode Lamb wave separation method based on dispersion compensation and blind separation |
| CN110045014A (en) * | 2019-03-11 | 2019-07-23 | 西安交通大学 | Lamb wave frequency dispersion removing method and its system based on Bayesian learning |
Non-Patent Citations (2)
| Title |
|---|
| ZHE WANG 等: "Multimodal Lamb Wave Identification Using Combination of Instantaneous Frequency with EMD", 《2019 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE》 * |
| 倪龙 等: "基于频散补偿和分数阶微分的多模式兰姆波分离", 《物理学报》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110333285A (en) * | 2019-07-04 | 2019-10-15 | 大连海洋大学 | Ultrasonic Lamb waves Defect signal recognition method based on variation mode decomposition |
| CN110333285B (en) * | 2019-07-04 | 2021-07-27 | 大连海洋大学 | Ultrasonic lamb wave defect signal identification method based on variational modal decomposition |
| CN111337574A (en) * | 2020-04-09 | 2020-06-26 | 上海工程技术大学 | Topological imaging method and device based on ultrasonic lamb wave plate type ballastless track cracks |
| CN111337574B (en) * | 2020-04-09 | 2023-04-18 | 上海工程技术大学 | Topological imaging method and device based on ultrasonic lamb wave plate type ballastless track cracks |
| CN111812207A (en) * | 2020-07-21 | 2020-10-23 | 大连理工大学 | Non-reference damage diagnosis imaging method based on ultrasonic guided wave conversion mode extraction |
| CN113533510A (en) * | 2021-06-29 | 2021-10-22 | 北京交通大学 | Method and device for identifying fatigue microcracks of steel rail |
| CN113533510B (en) * | 2021-06-29 | 2023-12-08 | 北京交通大学 | Rail fatigue micro-crack identification method and device |
| CN113686959A (en) * | 2021-09-15 | 2021-11-23 | 中国科学院声学研究所 | Imaging method and device based on ultrasonic lamb wave defect detection |
| CN114994175A (en) * | 2022-05-18 | 2022-09-02 | 国营芜湖机械厂 | Space coupling ultrasonic stress detection device and method for modal decomposition double-spectrum analysis |
| CN114994175B (en) * | 2022-05-18 | 2023-01-17 | 国营芜湖机械厂 | Space coupling ultrasonic stress detection device and method for modal decomposition double-spectrum analysis |
| CN115017640A (en) * | 2022-05-23 | 2022-09-06 | 哈尔滨工业大学 | Comb-shaped piezoelectric transducer structure optimization design method based on time-space domain hybrid analysis |
| CN115017640B (en) * | 2022-05-23 | 2023-04-18 | 哈尔滨工业大学 | Comb-shaped piezoelectric transducer structure optimization design method based on time-space domain hybrid analysis |
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