CN116482231A - Ultrasonic imaging method for internal defects of material with high signal-to-noise ratio - Google Patents
Ultrasonic imaging method for internal defects of material with high signal-to-noise ratio Download PDFInfo
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Abstract
The invention discloses a high signal-to-noise ratio ultrasonic imaging method for internal defects of materials, which is characterized in that the spatial coherence of signals received by all channels in full matrix data is utilized, the delay rule of an algorithm is corrected by combining with the configuration characteristics of a curved surface of a PBX, the high signal-to-noise ratio imaging of the defects of cracks of different orientations of the curved surface configuration PBX is realized, and the quality of a reconstructed image is compared and evaluated. Compared with the traditional linear synthetic focusing imaging, the algorithm provided by the invention improves the signal-to-noise ratio of the ultrasonic reconstruction image of the crack defect of the particle-filled composite material PBX by more than 10dB, obviously improves the detection capability of the crack defect, and simultaneously gives consideration to imaging efficiency.
Description
Technical Field
The invention relates to the technical field of inspection and detection, in particular to a high signal-to-noise ratio ultrasonic imaging method for internal defects of materials.
Background
The particle-filled composite material is a two-phase or multi-phase composite material composed of a particulate material and a high polymer reinforced matrix. The particle filling composite material has remarkable improvement and lifting effects on mechanical properties (such as toughness and tensile strength), and is widely applied in the fields of aerospace, chemical petroleum, construction and the like. The polymer bonded explosive (Polymer Bonded eXplosives, PBX) is a typical particle filled composite material which is formed by pressing an elementary explosive crystal body with high filling (more than 90 percent) and a small amount of binder, has high mechanical property and good processing and forming properties, and is widely applied to domestic and foreign weaponry. Under the action of environmental factors, the PBX can generate macroscopic cracks, so that the mechanical property of the explosive component is degraded and the explosive sensitivity is improved, and the safety and the reliability of the system are affected. Therefore, the establishment of an accurate and effective method for detecting and imaging the internal cracks of the PBX is important for revealing the fracture mechanical behavior rule of the PBX and evaluating the structural integrity of the PBX.
Ultrasonic phased array detection and imaging methods present unique advantages and potential in the detection of internal defects. But the characteristics of materials of the PBX component show low sound velocity, strong attenuation and the like on ultrasonic waves, so that the signal-to-noise ratio of defect echoes is lower, and the ultrasonic imaging quality is further affected. In addition, the curved nature of the PBX components presents challenges for high signal-to-noise imaging of internal defects. Full focus (Total Focusing Method, TFM) imaging algorithms based on the principle of linear Delay And add Sum (DAS) And their derivatives have been demonstrated to enable high signal-to-noise imaging And quantitative evaluation of internal defects. For example, vector TFM is used to characterize the direction of the crack, and multimode TFM is used to enhance the ability of defect characterization. In addition, zhang Haiyan et al propose a TFM array imaging method for acoustic beam directivity function correction, which achieves high signal-to-noise ratio imaging of fold defects in carbon fiber reinforced composites. Experiments prove that aiming at a complex-configuration workpiece of a particle filling composite material such as a PBX, a signal processing algorithm based on a DAS principle has very limited effect on noise and clutter signals, the deformation of a reconstructed defect form can be caused by a curved surface configuration, and serious background noise exists in an image due to the strong attenuation characteristic of an internal particle filling structure to ultrasonic waves, so that the identification and quantitative detection of internal defects are influenced.
Unlike imaging algorithms employing the DAS principle, time-lapse combination-multiply-add (Delay Multiply And Sum, DMAS) nonlinear beamforming algorithms exploit the spatial coherence of the radio frequency received signal to improve the signal-to-noise ratio, exhibiting excellent performance in terms of noise and clutter signal suppression. Matrone et al have studied the use of DMAS in medical ultrasound imaging and combined with techniques such as synthetic aperture imaging, plane wave imaging, and multiline transmission imaging to further enhance the performance of DMAS. Luo et al apply DMAS to ultrasonic plane wave composite imaging of wedge-shaped two-layer medium, and detect the internal defect of steel rail, thus realizing high signal-to-noise ratio imaging of defect. Teng et al applied DMAS to post-processing imaging of full matrix data (Full Matrix Capture, FMC) to improve imaging quality for ultrasonic phased array detection. Yu et al detect the defects of the manual prefabricated transverse through holes of the planar PBX material by utilizing a DMAS algorithm and combining a pseudo-color imaging technology, and obtain an imaging result with high signal-to-noise ratio. The Baseband DMAS (Baseband-DMAS, BB-DMAS) nonlinear beam forming algorithm is provided, so that aliasing of frequency spectrum components and high computational complexity caused by combination and multiplication of radio frequency signals are avoided. The algorithm demodulates the radio frequency receiving signals, uses baseband signal spatial coherence to replace pairing multiplication of radio frequency signals, and can remarkably reduce the calculation load of an imaging algorithm while obtaining high signal-to-noise ratio ultrasonic images. The characteristics enable BB-DMAS to have great application potential in the aspect of high signal-to-noise ratio ultrasonic imaging of the internal defects of the particle filling composite material.
Disclosure of Invention
Aiming at the problem of detecting internal defects of a PBX of a curved surface configuration and particle filling composite material, the invention combines a BB-DMAS nonlinear beam forming method with a synthetic focusing imaging principle, provides a material internal defect high signal-to-noise ratio ultrasonic imaging method, is realized according to a Baseband nonlinear synthetic focusing (Baseband-Nonlinear Synthetic Focusing, BB-NSF) imaging algorithm model, realizes effective suppression of noise and clutter in a received signal through spatial coherence of full matrix data, corrects a delay rule of an algorithm by combining configuration characteristics of a detection test block, and uses a flexible transducer array to carry out ultrasonic imaging on cracks of the PBX test block with different thickness, thereby obtaining a high-quality ultrasonic image. And further simulation analysis of the influence rule of the position of the flexible transducer on the imaging results of the PBX cracks with different orientations, obtaining key factors influencing crack defect detection in signals, and finally quantitatively evaluating the imaging quality.
The invention realizes the above purpose through the following technical scheme:
an ultrasonic imaging method with high signal-to-noise ratio for internal defects of materials comprises the following steps:
step 1, processing the received FMC original signal by using a denoising method, processing the received FMC original signal, and using Hilbert transform to filter the signal s i (t) (i=1, 2,3, …, N) into its in-phase and quadrature components;
step 2, calculating the delay time of the transmitting-receiving group signal based on the virtual focus point (x, z), and extracting the baseband signal amplitude of the corresponding receiving signal at the position; under the condition of keeping the phase unchanged, the amplitude is root-scaled p times, and then the scaled values are coherently summed to generate a new amplitude A (x, z);
step 3, the p-th power of the amplitude is taken to recover the dimension, and the pixel intensity of the virtual focus point (x, z) of the final image can be obtained by calculating the modulus of two components in the Hilbert transform.
Step 4, for a curved surface test block with radius R, the angles corresponding to each array element and the z coordinate axis are as follows:
according to the parameter equation of the circle, the x-axis and z-axis coordinates of the array element of the flexible transducer can be expressed as x 'respectively' m ＝Rsinθ m And z' m ＝R(1-cosθ m )；
And 5, for the curved surface contour of the tested block, the flight time after delay correction can be rewritten as follows:
substituting the formula (5) into the formula (1) to obtain the BB-NSF imaging algorithm of the curved surface component.
The time domain received signal is demodulated into an in-phase component and a quadrature component by Hilbert transform, and the modulus and phase components are:
wherein H [. Cndot.]Representing Hilbert transform, I i (t) and Q i (t) represents in-phase and quadrature components, respectively; x is X i (t) is the modulus of two components in the Hilbert transform, f i (t) is the corresponding phase;
for a focal point P (x, z) of the imaging region, the ultrasonic wave is emitted from the t-th element through the focal point, and the flight time received by the r-th element is:
where i represents the ith received signal in the FMC data, (z) t ,x t ) And (z) r ,x r ) The coordinate positions of the transmitting array element and the receiving array element are respectively shown in the specification, and the subscript relationship is r=mod (i, M) and t=1+ (i-r)/M; c L Is the velocity of the longitudinal wave propagating in the test block by the ultrasound.
In step 3, the signal amplitude corresponding to each transmitting-receiving group flight time is extracted and scaled into p times of rootCarrying out coherent summation on the scaled channel amplitudes, and then carrying out p-th power recovery signal dimension; therefore, the BB-NSF algorithm based on FMC data is:
wherein I (x, z) is the intensity of any pixel point of the ultrasonic image, and the coefficient p represents the signal space coherence between the received signals in the FMC data.
In the step 3, the coefficient p is an integer or a non-integer, and along with the increase of the p value, more signal coherence is introduced in the BB-NSF imaging process, so that the method has a better clutter suppression effect on ultrasonic imaging.
Typically, the coefficient p value is set to 2.
The invention has the beneficial effects that:
1) By combining BB-NSF algorithm, the imaging characteristics of the flexible transducer on cracks with different orientations of the PBX test piece with different thickness are different, and the characteristics of the crack tip, the crack root and the shape can be completely presented for the defects of large orientation angle and 15mm of embedded depth;
2) Experiments show that the BB-NSF algorithm with curved surface correction can improve the signal-to-noise ratio of an ultrasonic reconstruction image of the particle filled composite material PBX crack defect by more than 10dB by utilizing the spatial coherence of signals received by each channel in the full matrix data, thereby remarkably improving the detection capability of the crack defect and simultaneously taking the imaging efficiency into consideration;
3) The selection of the p value can directly influence the signal-to-noise ratio improvement degree and imaging efficiency of the BB-NSF algorithm, and the corrected BB-NSF algorithm improves the signal-to-noise ratio of a far-field position, improves the image detection capability of far-field defects and reduces the possibility of false detection or omission.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly explain the practical drawings required in the embodiments or the prior art description, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of BB-NSF algorithm of the present invention;
FIG. 2 is a schematic diagram of a synthetic focus imaging of the present invention;
FIG. 3 is a schematic diagram of the delay time calculation of the post-processing imaging algorithm of the curved surface workpiece;
FIG. 4 is a schematic illustration of a geometric model of crack defects of a particle composite PBX of the present invention;
FIG. 5 is a simulated imaging of defects A, B and C of the flexible transducer of the present invention at different inspection positions;
FIG. 6 (a) TFM image, (b) root mean square of pixel peak values of BB-NSF image defect region and pixel intensity in background noise region; (c) SNR indicator of TFM and BB-NSF defects;
FIG. 7 is a schematic illustration of an experimental PBX test block with an artificial pre-crack defect;
fig. 8T =5, r=8 time domain signal: (a) defect A, (B) defect B, (C) defect C detection location;
fig. 9 undelayed modified (a) TFM; after the delay correction, (b) TFM, (c) F-DMAS, (d) imaging result of BB-NSF algorithm on defect A; (e) Imaging results of BB-NSF on defects A, B and C after delay correction.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, based on the examples herein, which are within the scope of the invention as defined by the claims, will be within the scope of the invention as defined by the claims.
In any embodiment, as shown in fig. 1-3, the method for ultrasonic imaging of the internal defect of the material with high signal to noise ratio comprises the following implementation steps:
according to the ultrasonic phased array FMC data acquisition principle, assuming that a one-dimensional linear phased array transducer is provided with M array elements, by sequentially and independently exciting the array elements to transmit ultrasonic signals and simultaneously receiving echo signals by all the array elements, the echo matrix data of N=M×M can be obtained. Fig. 1 is a schematic diagram of a BB-NSF algorithm according to the present invention, in which a zero-phase bandpass filter and a wavelet denoising method are first used to process a received FMC original signal before an imaging algorithm, so as to reduce the influence of low-frequency and high-frequency noise components and phase distortion caused by the filter on an imaging result. The filtered signal s is then transformed by Hilbert transform i (t) (i=1, 2,3, …, N) into its in-phase and quadrature components. According to the TFM synthetic focusing imaging algorithm principle, the delay time of the transmitting-receiving group signal is calculated based on the virtual focusing point (x, z), and the baseband signal amplitude of the corresponding receiving signal at the position is extracted. The amplitude is root scaled p times while keeping the phase unchanged, and then the scaled values are coherently summed to generate a new amplitude a (x, z). Finally, the amplitude is raised to the power of p to restore the dimension, and the pixel intensity of the virtual focus point (x, z) of the final image can be obtained by calculating the modulus of two components in the Hilbert transform.
The time domain received signal is demodulated into an in-phase component and a quadrature component by hilbert transform, and its modulus and phase components can be expressed as:
wherein H [. Cndot.]Representing Hilbert transform, I i (t) and Q i (t) represents in-phase and quadrature components, respectively. X is X i (t) is the modulus of two components in the Hilbert transform, f i And (t) is the corresponding phase. As shown in fig. 2, for a focal point P (x, z) of an imaging region, ultrasonic waves are emitted from the t-th element through the focal point, and a time of flight received by the r-th element can be expressed as:
where i represents the ith received signal in the FMC data, (z) t ,x t ) And (z) r ,x r ) The coordinate positions of the transmitting array element and the receiving array element are respectively indicated by the subscripts r=mod (i, M) and t=1+ (i-r)/M. c L Is the velocity of the longitudinal wave propagating in the test block by the ultrasound.
Extracting the signal amplitude corresponding to each transmitting-receiving group flight time and scaling it into p times of rootAnd carrying out coherent summation on the scaled channel amplitudes, and then carrying out p-th power recovery signal dimension. Thus, the BB-NSF algorithm based on FMC data can be written as:
where I (x, z) is the intensity of any pixel point of the ultrasound image, the coefficient p may be expressed as the signal space coherence between the received signals in the FMC data, and p is not limited to an integer. With the increase of the p value, more signal coherence is introduced in the BB-NSF imaging process, so that the method has a better clutter suppression effect on ultrasonic imaging. Without loss of generality, the present invention sets the p value to 2.
Different from the imaging algorithm of the planar workpiece, when the flexible ultrasonic array is directly coupled to the surface of the curved workpiece, the geometric position coordinates of each array element can be changed, and the time for receiving ultrasonic waves by the space pixel point can be changed, so that the delay rule needs to be corrected to realize accurate mapping and image reconstruction of the imaging space. Fig. 3 is a schematic diagram of ultrasonic signal flight times of a flexible transducer array of a curved workpiece. The established two-dimensional rectangular coordinate system Oxz is arranged at the center of the flexible transducer array, the x-axis is along the tangential direction of the surface profile of the tested block to the right, and the z-axis and the normal direction of the surface profile of the tested block point to the tested area.
If the length of the array is not stretched or compressed when the flexible array is coupled to the contoured surface, the effective detection arc length of the transducer may be represented as l= (M-1) d, where d is the array element spacing and M is the number of array elements. For a curved surface test block with radius R, the angle corresponding to each array element and the z coordinate axis can be expressed as:
according to the parameter equation of the circle, the x-axis and z-axis coordinates of the array element of the flexible transducer can be expressed as x 'respectively' m ＝Rsinθ m And z' m ＝R(1-cosθ m ). Considering the curved surface profile of the tested block, the flight time after delay correction can be rewritten as follows:
substituting the formula (5) into the formula (1) to obtain the BB-NSF imaging algorithm of the curved surface component.
In any embodiment, as shown in fig. 4-6, a high signal-to-noise ratio ultrasonic imaging method for internal defects of a material according to the invention comprises the following steps:
establishing a particle composite material PBX workpiece model with unequal thickness curved surfaces and containing cracks with different orientations shown in fig. 4 in CIVA software, wherein the outer surface radius R 1 50mm, inner face radius R 2 The thickness of the material is 40mm, and the thickness of the material at different positions is 6.23-26.23 mm. The content of binder in the pellet composite was set to 5% and the content of pellets was 95%. The particle composite model was reduced to a density of 1.895g/cm 3 An isotropic material having a longitudinal wave sound velocity of 3010m/s. Three open bottom groove defects A, B and C with orientations of 60 degrees, 30 degrees and 0 degrees respectively, with a defect length of 5mm and a defect width of 0.5mm, were created on the particle composite model, and the orientations were defined as the angles of the cracks and the normal line of the profile of the test block at the root. The 16-array element flexible linear array transducer is directly coupled with the outline of the tested model and acquires FMC dataThe sampling frequency was set to 33.3MHz. The center frequency of the flexible transducer is 2.5MHz, the width and length of the array elements are 3.5mm and 6mm respectively, and the center distance of the array elements is 1.5mm.
Fig. 5 shows the BB-NSF imaging simulation results of the flexible transducer at different positions, and it can be seen that the proposed algorithm can effectively detect defect a with 60 ° orientation and about 11mm burial depth. As the flexible transducer moves from left to right, the crack surface has significant echo amplitude intensity when the transducer centerline has not yet crossed the center of the defect a, the defect shape feature can be fully represented, and the defect type can be effectively identified (see fig. 5 a-b). As the transducer centerline gradually crosses the defect location, the crack root and crack tip remain clearly resolved, but the crack profile information begins to appear partially missing until it completely disappears (see fig. 5 c-d). Therefore, for the detection of the crack defects of the curved-surface PBX component, when the center line of the transducer and the outline of the crack defect form a certain angle and the center of the transducer is positioned at the root position of the crack defect, the information of the outline of the bottom surfaces of the defect and the test block is complete, and the imaging effect is optimal. Fig. 5e-f show the imaging results of defect B and defect C, wherein the crack orientation is small, the signals received by the transducer array elements are almost all reflected echo signals of the crack tips, the crack profile echo signals are weak, the crack profile information is lost, and the crack tip information is preserved and presented.
To objectively evaluate the improvement in performance of BB-NSF over conventional TFM in terms of imaging noise suppression, simulated FMC data was used to compare different imaging algorithms to obtain the signal-to-noise ratio of defect imaging, using SNR = 20lg [ i ] max /RMS(I b )],(I max To define the pixel peak intensity of the defect region, RMS (I b ) Root mean square for pixel intensity in a defect-free background noise region) index. As shown in fig. 6a and 6b, the present invention proposes that BB-NSF significantly enhances the pixel peak intensity I of the defective region compared to TFM max Root mean square RMS (I) of pixel intensities in a defect-free background noise region b ) Only a slight increase occurs. As shown in FIG. 6c, the signal-to-noise ratio of the traditional TFM imaging is in the range of 34 dB-52 dB, and the invention provides that the signal-to-noise ratio of BB-NSF is 76 dB-114 dB, which is lack ofThe signal to noise ratio of the notch A, B, C is improved by about 42dB, 69dB and 61dB respectively, the improvement effect is obvious, and the advantages of the BB-NSF algorithm in the aspect of clutter suppression and image signal to noise ratio improvement are embodied.
In one embodiment, as shown in fig. 7-9, a method for ultrasonic imaging of internal defects of a material with high signal-to-noise ratio according to the present invention, the implementation process and the analysis of the result include:
the PBX test block with the artificial pre-crack defect is selected as a detection object, the external dimension and the defect position are the same as those of the CIVA simulation model, and the experimental schematic diagram is shown in fig. 7. The PBX test piece is formed by isostatic pressing of 95% HMX crystals and 5% adhesive, the inner and outer molded surfaces of the test piece and the artificial pre-fabricated crack defect are obtained through machining, and the calibrated sound velocity of the test piece is 3010m/s. In the experiment, flexible PMUT is bent and tightly adhered to the surface of a PBX test piece, and vaseline is selected as a coupling agent.
The ultrasonic imaging system adopted in the experiment consists of a piezoelectric micromechanical ultrasonic transducer (Piezoelectric Miccomachined Ultrasonic Transducer, PMUT) array, a lower computer FMC data acquisition module based on FPGA and an upper computer PC. The FPGA data acquisition module can support 64 transmitting/receiving parallel channels at maximum, and is excited by 1 period of sine signals in the experiment, and the excitation voltage is 20V. The flexible transducer collects FMC data at different detection positions through the FPGA and uploads the FMC data to the upper computer, and then the FMC data is subjected to post-processing through the algorithm provided by the invention to obtain a defect reconstruction image. The FMC data acquisition system parameter configuration and each defect tip depth location are shown in table 1.
TABLE 1 Experimental parameters and crack depth
| Transducer parameters | Value of | Defect crack tip burial depth/mm | Value of |
| Number of array elements | 16 | Defect A | 16 |
| Array element center distance/mm | 1.5 | Defect B | 23 |
| Center frequency/MHz | 2.5 | Defect C | 24 |
The defect A, B and the defect C are taken to correspond to a typical time domain signal in FMC data for analysis, and the 6 th array element transmits the ultrasonic signal received by the 8 th array element as shown in figure 8. From this, structural and electrical noise of large amplitude can be observed, which is due to the complex echo signal composition caused by acoustic scattering by the particle composite material. In addition, the extracted signals also find the originating waves with large amplitude, so that the signals can be predicted to have serious background noise in a defect-free area when being used for imaging, and meanwhile, near-field blind areas exist in a near-surface area of a detection test block, and serious interference is easily caused to defect judgment.
And selecting a proper detection position according to the CIVA simulation result, and collecting FMC data of the tested PBX test block for post-processing imaging. Fig. 9 (a) shows a TFM imaging result without surface delay correction, and it can be seen that not only the image has serious background noise, but also the crack defect a and the bottom contour of the tested block are severely distorted, and the shape and the true position of the defect cannot be determined. In contrast, after the curved surface delay correction is introduced, the bottom surface contour and defect information of the tested block are presented, but serious background noise still exists in the image, and misjudgment is easy to cause (see fig. 9 b). Fig. 9c-d are respectively the F-DMAS with curved surface delay correction introduced and the BB-NSF proposed by the present invention, it can be seen that the signal-to-noise ratio of the near field region and the defect region is significantly improved, because the nonlinear operation is performed on the full matrix data, the coherent signal (defect echo) is enhanced and the incoherent signal (noise) is weakened, so the pixel intensity of the defect position is increased, the pixel intensity of the non-defect position is reduced, and the overall signal-to-noise ratio is significantly improved. And respectively reconstructing 3 crack defect images by adopting a BB-NSF algorithm of curved surface delay correction according to the curved surface profile characteristics of the measured object to obtain a full field diagram as shown in fig. 9 e. The shape and position characteristics of the defect A and the bottom surface and side wall contours of the tested block can be obtained from the imaging result, the background noise of BB-NSF images of the defects B and C is obviously reduced, the strength of crack tip signals of the defects B and C is improved, and the rule has better consistency with the simulation result of FIG. 5.
The SNR and the calculation time for the results of the different algorithms for imaging the defects a, B and C are shown in table 2. Compared with a classical TFM, the TFM imaging algorithm based on directivity correction and coherence factor improves SNR of defects A, B and C by-3.65 dB and-6.85 dB on average, and the operation time consumed by calculating one frame of image is respectively increased by 0.2s and 0.03s; the F-DMAS imaging algorithm can remarkably improve the SNR indexes of defects A, B and C, and improves the SNR indexes by 10.64dB on average, so that the position information of the defects can be clearly observed, but the F-DMAS algorithm has huge time consumption for obtaining a frame of image, about 142.79s is needed, and the real-time detection requirement is limited. In contrast, the BB-NSF provided by the invention can realize the dynamic adjustment of the signal-to-noise ratio of an imaging result by setting the signal space coherence coefficient p between the received signals in the FMC data. When p=1, the SNR index of each defect is equivalent to that of the TFM, the SNR of the defect is improved along with the increase of the p value, the SNR index of the same level as that of the F-DMAS can be obtained when p=2, meanwhile, the operation time only needs 0.41s, the defect that the calculation load of the F-DMAS imaging algorithm is large is obviously improved, and compared with the classical TFM imaging algorithm, the time consumption is only increased by 0.12s. Therefore, the BB-NSF algorithm also shows remarkable advantages in terms of calculation efficiency while achieving a high signal-to-noise ratio.
Furthermore, as can be seen from table 2, for any algorithm, as the depth of detection of defect A, B, C increases, the trend of signal-to-noise reduction is obvious, especially as low as 5.02dB (defect C) for TFM imaging without optimization of the algorithm, where the defect signal is completely submerged by background noise. This is mainly due to the strong attenuation properties of the PBX material, and the echo signal of a far field defect may be buried in electrical noise or structural noise, resulting in false detection or omission of the defect. Under the condition of improving the signal-to-noise ratio of the full-field image, the BB-NSF algorithm provided by the invention improves the signal-to-noise ratio of the defect C with a deeper detection position to 15.64dB, inhibits the influence of background noise, realizes effective identification of defect information, shows that the algorithm improves the image detection capability of far-field defects to a certain extent, and reduces the possibility of false detection or omission.
Table 2 performance index based on experimental data imaging algorithm
Aiming at the problem of high signal-to-noise ratio imaging of crack defects of a particle filled composite material, the invention provides a post-processing imaging algorithm of baseband nonlinear synthetic focusing (BB-NSF), and ultrasonic imaging is carried out on cracks of a non-uniform thickness curved surface PBX test block by using a flexible transducer array, so that high-quality ultrasonic images are obtained, and the obtained effects comprise:
1) By combining BB-NSF algorithm, the imaging characteristics of the flexible transducer on cracks with different orientations of the PBX test piece with different thickness are different, and the characteristics of the crack tip, the crack root and the shape can be completely presented for the defects of large orientation angle and 15mm of embedded depth;
2) Experiments show that the BB-NSF algorithm with curved surface correction can improve the signal-to-noise ratio of an ultrasonic reconstruction image of the particle filled composite material PBX crack defect by more than 10dB by utilizing the spatial coherence of signals received by each channel in the full matrix data, thereby remarkably improving the detection capability of the crack defect and simultaneously taking the imaging efficiency into consideration;
3) The selection of the p value can directly influence the signal-to-noise ratio improvement degree and imaging efficiency of the BB-NSF algorithm, and the corrected BB-NSF algorithm improves the signal-to-noise ratio of a far-field position, improves the image detection capability of far-field defects and reduces the possibility of false detection or omission.
Further experiments have found that the method of the invention is suitable for homogeneous and heterogeneous materials, and especially has the best detection effect on internal defects (cracks, inclusions, pores, layering and the like) of metal or metal matrix composites, two-phase or multi-phase composites (such as particle filled composites).
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims. In addition, the specific features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various possible combinations are not described further. Moreover, any combination of the various embodiments of the invention can be made without departing from the spirit of the invention, which should also be considered as disclosed herein.
Claims (5)
1. The high signal-to-noise ratio ultrasonic imaging method for the internal defects of the material is characterized by comprising the following steps of:
step 1, processing the received FMC original signal by using a denoising method, processing the received FMC original signal, and using Hilbert transform to filter the signal s i (t) (i=1, 2,3, …, N) into its in-phase and quadrature components;
step 2, calculating the delay time of the transmitting-receiving group signal based on the virtual focus point (x, z), and extracting the baseband signal amplitude of the corresponding receiving signal at the position; under the condition of keeping the phase unchanged, the amplitude is root-scaled p times, and then the scaled values are coherently summed to generate a new amplitude A (x, z);
step 3, the p-th power of the amplitude is obtained to restore the dimension, and the pixel intensity of the virtual focus point (x, z) of the final image can be obtained by calculating the modulus of two components in the Hilbert transform;
step 4, for a curved surface test block with radius R, the angles corresponding to each array element and the z coordinate axis are as follows:
according to the parameter equation of the circle, the x-axis and z-axis coordinates of the array element of the flexible transducer can be expressed as x 'respectively' m ＝R sinθ m And z' m ＝R(1-cosθ m )；
And 5, for the curved surface contour of the tested block, the flight time after delay correction can be rewritten as follows:
substituting the formula (5) into the formula (1) to obtain the BB-NSF imaging algorithm of the curved surface component.
2. The method of claim 1, wherein in step 1, the time domain received signal is demodulated into an in-phase component and a quadrature component by hilbert transform, and the modulus and the phase component are:
wherein H [. Cndot.]Representing Hilbert transform, I i (t) and Q i (t) is the same asPhase and quadrature components; x is X i (t) is the modulus of two components in the Hilbert transform, f i (t) is the corresponding phase;
for a focal point P (x, z) of the imaging region, the ultrasonic wave is emitted from the t-th element through the focal point, and the flight time received by the r-th element is:
where i represents the ith received signal in the FMC data, (z) t ,x t ) And (z) r ,x r ) The coordinate positions of the transmitting array element and the receiving array element are respectively shown in the specification, and the subscript relationship is r=mod (i, M) and t=1+ (i-r)/M; c L Is the velocity of the longitudinal wave propagating in the test block by the ultrasound.
3. The method of claim 1, wherein in step 3, signal amplitudes corresponding to the time of flight of each transmit-receive set are extracted and scaled to p times by using a rootCarrying out coherent summation on the scaled channel amplitudes, and then carrying out p-th power recovery signal dimension; therefore, the BB-NSF algorithm based on FMC data is:
wherein I (x, z) is the intensity of any pixel point of the ultrasonic image, and the coefficient p represents the signal space coherence between the received signals in the FMC data.
4. The method of claim 3, wherein in the step 3, the coefficient p is an integer or a non-integer, and as the p value increases, more signal coherence is introduced in the BB-NSF imaging process, so that the method has a better clutter suppression effect on ultrasonic imaging.
5. A method of high signal to noise ratio ultrasonic imaging of internal defects in a material according to claim 3, wherein the value of the coefficient p in step 3 is set to 2.
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| CN117503203A (en) * | 2024-01-03 | 2024-02-06 | 之江实验室 | Phase aberration correction method and system for ultrasonic ring array imaging |
| CN117503203B (en) * | 2024-01-03 | 2024-03-22 | 之江实验室 | Phase aberration correction method and system for ultrasonic ring array imaging |
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