Reflection and transmission dual-mode ultrasonic tomography method and system based on multi-frequency fusion

Abstract

The invention provides a reflection and transmission dual-mode ultrasonic tomography method and system based on multi-frequency fusion, and the method comprises the steps: sequentially exciting low-frequency ultrasound for each ultrasonic sensor, and enabling each ultrasonic sensor to carry out reflection and projection dual-mode tomography at an initial frequency, constructing a low-frequency coefficient matrix and a low-frequency ultrasonic image based on the reflection signals and the transmission signals received by the ultrasonic sensors; based on the low-frequency ultrasonic image, determining a target frequency capable of enabling a sound wave of each ultrasonic sensor to penetrate through each ultrasonic imaging path; sequentially exciting high-frequency ultrasound for each ultrasonic sensor, and constructing a high-frequency coefficient matrix on the basis of a reflected signal and a transmitted signal received by each ultrasonic sensor; and fusing the low-frequency coefficient matrix and the high-frequency coefficient matrix to obtain a fusion coefficient matrix, and performing image reconstruction based on the fusion coefficient matrix to obtain a multi-frequency fused two-phase distribution diagram. According to the invention, the imaging effect of working conditions of multiple bubbles and bubble groups is improved, and the imaging precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of liquid metal-bubble two-phase flow imaging, and in particular to a reflection-transmission dual-mode ultrasonic tomography method and system based on multi-frequency fusion. Background Art

[0002] Existing ultrasonic tomography technologies typically include single-mode imaging and dual-mode imaging. Single-mode imaging typically includes reflection imaging and transmission imaging. However, single-mode imaging can produce many artifacts under certain fluid distributions. When bubbles approach the ultrasonic sensor, the ultrasonic sensor cannot receive the ideal reflected signal. Dual-mode imaging, on the other hand, is typically based on a single frequency and is subject to the dual constraints of the measurement container and resolution. To obtain a resolvable transmission signal amplitude during measurement, an appropriate frequency is selected based on a certain measurement depth requirement. The greater the depth, the lower the frequency needs to be. However, the lower the frequency, the lower the resolution. Furthermore, the presence of bubbles in the cross section can enhance the attenuation of the ultrasonic signal, reducing the imaging effect. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a reflection-transmission dual-modal ultrasonic tomography method and system based on multi-frequency fusion, which can flexibly adapt to working conditions such as different cross-sectional gas content, improve the imaging effect of working conditions with multiple bubbles and bubble groups, and improve the imaging accuracy.

[0004] In order to achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows: In a first aspect, an embodiment of the present invention provides a reflection-transmission dual-modal ultrasound tomography method based on multi-frequency fusion, which is applied to a reflection-transmission dual-modal ultrasound tomography system based on multi-frequency fusion. The reflection-transmission dual-modal ultrasound tomography system based on multi-frequency fusion includes multiple ultrasonic sensors. The reflection-transmission dual-modal ultrasound tomography method based on multi-frequency fusion includes: Each ultrasonic sensor is sequentially excited with low-frequency ultrasound, causing each ultrasonic sensor to perform reflection-projection dual-modal tomography at an initial frequency, and a low-frequency coefficient matrix and a low-frequency ultrasonic image are constructed based on the reflected signal and the transmitted signal received by each ultrasonic sensor; wherein the initial frequency is a frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path when the cross-sectional gas content of the channel to be detected is the predicted highest cross-sectional gas content; determining, based on the low-frequency ultrasonic image, a target frequency capable of enabling the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path; Exciting high-frequency ultrasound in sequence on each of the ultrasonic sensors so that each of the ultrasonic sensors performs reflection-projection dual-modal tomography at the target frequency, and constructing a high-frequency coefficient matrix based on the reflection signal and the transmission signal received by each of the ultrasonic sensors; The low-frequency coefficient matrix and the high-frequency coefficient matrix are fused to obtain a fusion coefficient matrix, and an image is reconstructed based on the fusion coefficient matrix to obtain a two-phase distribution map of multi-frequency fusion.

[0005] Furthermore, an embodiment of the present invention provides a first possible implementation of the first aspect, wherein the step of constructing a low-frequency coefficient matrix and a low-frequency ultrasonic image based on the reflection signal and the transmission signal received by each ultrasonic sensor includes: Reconstructing the low-frequency coefficient matrix and the initial low-frequency ultrasonic image using a dual-mode fusion reconstruction algorithm based on the reflected signals and the transmitted signals received by each ultrasonic sensor; Denoising is performed on the initial low-frequency ultrasonic image, and bubble sealing is performed on the denoised initial low-frequency ultrasonic image to restore the bubble image to be complete, thereby obtaining the low-frequency ultrasonic image.

[0006] Furthermore, an embodiment of the present invention provides a second possible implementation of the first aspect, wherein the step of determining, based on the low-frequency ultrasonic image, a target frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path includes: determining, based on the low-frequency ultrasonic image, a frequency corresponding to a maximum ultrasonic attenuation on an ultrasonic path of each ultrasonic sensor, and selecting a lowest frequency from the frequencies corresponding to the maximum ultrasonic attenuation of each ultrasonic path; Obtaining a set frequency corresponding to a set minimum resolvable bubble radius that can be detected by the ultrasonic sensor; The minimum value between the lowest frequency and the set frequency is used as the target frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path.

[0007] Furthermore, an embodiment of the present invention provides a third possible implementation of the first aspect, wherein the step of determining, based on the low-frequency ultrasonic image, the frequency corresponding to the maximum ultrasonic attenuation on the ultrasonic path of each ultrasonic sensor includes: Acquire the bubble length and the liquid metal length on each of the ultrasonic paths from the low-frequency ultrasonic image; The frequency corresponding to when the attenuated sound pressure amplitude on each ultrasonic path is greater than the ambient noise is determined based on the bubble length and the liquid metal length on each ultrasonic path.

[0008] Furthermore, an embodiment of the present invention provides a fourth possible implementation of the first aspect, wherein the step of constructing a high-frequency coefficient matrix based on the reflected signal and the transmitted signal received by each of the ultrasonic sensors includes: The high-frequency coefficient matrix is ​​reconstructed using a dual-mode fusion reconstruction algorithm based on the reflected signal and the transmitted signal received by each ultrasonic sensor.

[0009] Furthermore, an embodiment of the present invention provides a fifth possible implementation of the first aspect, wherein the step of fusing the low-frequency coefficient matrix with the high-frequency coefficient matrix to obtain a fused coefficient matrix includes: The low-frequency coefficient matrix and the high-frequency coefficient matrix are adaptively fused using an adaptive gradient weight distribution algorithm to obtain the fused coefficient matrix.

[0010] Furthermore, an embodiment of the present invention provides a sixth possible implementation of the first aspect, wherein the step of performing image reconstruction based on the fusion coefficient matrix to obtain a multi-frequency fused two-phase distribution map includes: Reconstructing an initial fused image based on the fusion coefficient matrix; The initial fused image is subjected to denoising processing, and the denoised initial fused image is subjected to bubble sealing processing to restore the bubble image to be complete, thereby obtaining the multi-frequency fused two-phase distribution map.

[0011] Furthermore, an embodiment of the present invention provides a seventh possible implementation of the first aspect, wherein the excitation signal of the ultrasonic sensor is a pulsed step frequency modulation signal; In the steps of sequentially exciting low-frequency ultrasound for each ultrasonic sensor and sequentially exciting high-frequency ultrasound for each ultrasonic sensor, the excitation time interval of each ultrasonic sensor is ; Wherein, the cross section of the channel to be detected is circular, is the cross-sectional diameter of the channel to be detected, is the speed of sound in liquid metal, is the speed of sound in air, is the cross-sectional air content.

[0012] In a second aspect, an embodiment of the present invention further provides a reflection-transmission dual-modality ultrasound tomography system based on multi-frequency fusion, comprising: a controller and a plurality of ultrasonic sensors, wherein the controller comprises a processor and a storage device; The storage device stores a computer program, which, when executed by the processor, executes the method according to any one of the first aspects.

[0013] Furthermore, an embodiment of the present invention provides a first possible implementation of the second aspect, wherein a plurality of the ultrasonic sensors are evenly arranged on the outer surface of the channel to be detected, the cross-section of the channel to be detected is an axially symmetrical figure, and the plurality of the ultrasonic sensors are distributed axially symmetrically relative to the cross-section of the channel to be detected.

[0014] An embodiment of the present invention provides a reflection-transmission dual-modal ultrasonic tomography method and system based on multi-frequency fusion, which is applied to a reflection-transmission dual-modal ultrasonic tomography system based on multi-frequency fusion. The reflection-transmission dual-modal ultrasonic tomography system based on multi-frequency fusion includes multiple ultrasonic sensors. The reflection-transmission dual-modal ultrasonic tomography method based on multi-frequency fusion includes: sequentially stimulating low-frequency ultrasound on each ultrasonic sensor, so that each ultrasonic sensor performs reflection-projection dual-modal tomography at an initial frequency, and constructing a low-frequency coefficient matrix and a low-frequency ultrasonic image based on the reflection signal and transmission signal received by each ultrasonic sensor; wherein the initial frequency is the frequency to be detected. The cross-sectional gas content of the measuring channel is the frequency at which the sound waves of each ultrasonic sensor can penetrate each ultrasonic imaging path when the predicted highest cross-sectional gas content is obtained; the target frequency at which the sound waves of each ultrasonic sensor can penetrate each ultrasonic imaging path is determined based on the low-frequency ultrasonic image; high-frequency ultrasound is sequentially excited on each ultrasonic sensor to make each ultrasonic sensor perform reflection-projection dual-modal tomography at the target frequency, and a high-frequency coefficient matrix is ​​constructed based on the reflected signal and the transmitted signal received by each ultrasonic sensor; the low-frequency coefficient matrix is ​​fused with the high-frequency coefficient matrix to obtain a fusion coefficient matrix, and an image is reconstructed based on the fusion coefficient matrix to obtain a two-phase distribution diagram of multi-frequency fusion. The present invention first sequentially excites each ultrasonic sensor with low-frequency ultrasound to perform reflection-projection dual-modal tomography imaging, and determines the target frequency of subsequent high-frequency imaging based on the low-frequency ultrasonic image obtained by low-frequency imaging, so as to adopt adaptive frequency for high-frequency imaging, thereby ensuring that high-frequency sound waves can penetrate the channel to be detected. By adaptively fusing the low-frequency coefficient matrix with the high-frequency coefficient matrix, the final multi-frequency fused two-phase distribution diagram can meet the minimum resolution requirement, and can flexibly adapt to working conditions such as bubble measurement domains of different sizes and gas content of different cross sections, thereby improving the imaging effect of working conditions with multiple bubbles and bubble groups and improving imaging accuracy.

[0015] Other features and advantages of the embodiments of the present invention will be described in the following description, or some features and advantages can be inferred or determined without doubt from the description, or can be learned by implementing the above-mentioned technologies of the embodiments of the present invention.

[0016] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 A flow chart of a reflection-transmission dual-modality ultrasonic tomography method based on multi-frequency fusion provided by an embodiment of the present invention is shown; Figure 2 A flow chart of ultrasonic tomography of a two-phase flow consisting of liquid metal and bubbles provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0020] Existing ultrasonic tomography technologies generally include single-mode imaging and dual-mode imaging. Single-mode imaging generally uses reflection imaging and transmission imaging.

[0021] The basic principles of dual-modality imaging are as follows: When sound waves propagate to the interface between two different media, they will be reflected, transmitted or diffracted due to the difference in acoustic properties. Based on the geometric approximation of fan-shaped waves, when the incident wavelength is When the distance is much smaller than the characteristic size of the obstacle, the diffraction effect of the sound wave can be ignored. The strength of the diffraction effect can be expressed by the product of the wave number and the characteristic size of the obstacle: (1) in, is the wave number of the sound wave; are the frequency, speed, and wavelength of the sound wave respectively; It is the characteristic size of the obstacle to sound propagation, such as the characteristic size of a sphere is its radius.

[0022] Acoustic Diffraction Effect and Dimensionless Wave Number Parameters There is a significant correlation: The smaller the value, the stronger the diffraction effect, and vice versa, it shows a negative correlation trend. Specifically: (1) When (the characteristic scale of the sphere is equivalent to the wavelength), part of the sound wave produces diffraction phenomenon; (2) when (Rayleigh scattering region), the sound wave produces a significant diffraction effect, and its propagation path is almost not disturbed by the sphere; (3) When the acoustic wave propagates in a straight line (geometric acoustic zone), a clear acoustic shadow area is formed behind the obstacle. In ultrasonic testing based on reflection and transmission modes, different The value is used to judge the minimum. Generally, in the liquid metal-air system, it is believed that when =10, the sound waves will not diffract around the bubble.

[0023] Based on this theory, the minimum bubble size that can be detected by this embodiment is limited by the center frequency of the ultrasonic probe. =10, when a 4MHz ultrasonic probe is selected, the minimum discernible bubble radius in liquid metal lead and bismuth at 400℃ is approximately: (2) The strength of the reflection and transmission effects on the interface is determined by the acoustic impedance Z: (3) in, is the medium density, is the speed of sound in the medium.

[0024] Commonly used transmission coefficients and reflection coefficient The transmission coefficient is the ratio of the sound pressure of the transmitted and reflected sound waves to the original sound pressure. When the sound wave propagates from medium 1 to medium 2 and no diffraction occurs, the transmission coefficient is and reflection coefficient It can be expressed as (4) (5) in, is the acoustic impedance in medium 1, is the acoustic impedance in medium 2.

[0025] At room temperature, the acoustic impedance of air is approximately , while the acoustic impedance in liquid metal is often Order of magnitude, such as the acoustic impedance of gallium is , resulting in a reflectivity of up to 99% when incident vertically on the liquid metal-air interface.

[0026] On this basis, ultrasonic transmission imaging achieves tomographic imaging by comparing the signal amplitude difference between the background field and the measurement field. Ultrasonic reflection imaging uses the time elapsed from the transmitter to the receiver to deduce the reflected interface position for imaging.

[0027] Reflection method: (6) in,d t-r is the axial distance between the boundary point of the discrete phase medium and the ultrasonic transducer probe, TOF t-r is the transit time corresponding to the distance between the discrete phase medium boundary points, c w is the sound velocity of the continuous phase medium in the measured field.

[0028] Transmission method: (7) Where, P 0 is the amplitude of the ultrasonic wave before it enters the medium, P is the amplitude of the ultrasonic wave after traveling a distance of 1, is a function of the ultrasonic attenuation coefficient at any point on the sound path, dl It is a microelement on the sound path.

[0029] After taking the logarithm of both sides, let , then formula (7) is transformed into (8) For the cross section of the liquid-solid two-phase flow pipeline, the circular field is divided according to the appropriate two-dimensional segmentation rule, and the ultrasonic attenuation coefficient in each segmentation unit is considered to be a constant, thus obtaining a discrete relationship between the projection data and the ultrasonic amplitude attenuation. Indicates the j The ultrasonic attenuation coefficient of each subdivision unit is l ii Indicates the i The sound wave ray i The acoustic path length in each subdivision unit. Then the discrete form of equation (6) can be expressed as the following linear equations: (9) make , , , then formula (9) is transformed into (10) Where A is the acoustic path coefficient matrix, which transforms the discrete image reconstruction problem into the problem of estimating the attenuation coefficient vector x from the given projection data Y.

[0030] The aforementioned single reflection mode imaging can better provide information about the bubble boundary and better depict the overall bubble profile. Compared to single reflection mode, single transmission mode provides more information about the bubble center area and can be used to distinguish the two-phase flow behavior within the bubble cluster. For example, the gaps between multiple bubbles filled with liquid metal are difficult to distinguish in single reflection mode. However, both transmission mode and reflection mode have their own shortcomings and can produce many artifacts in certain fluid distributions. For example, when bubbles are close to the sensor, the sensor cannot receive the ideal reflection signal, resulting in poor imaging results.

[0031] Traditional reflection-transmission dual-modality imaging methods, however, are typically based on a single frequency and are subject to the dual constraints of the measurement volume and resolution, requiring a compromise between the two. During measurement, to obtain a resolvable transmission signal amplitude, the appropriate frequency is selected based on the desired measurement depth. The greater the depth, the lower the frequency required. However, lower frequencies also reduce resolution. Furthermore, the presence of bubbles in the cross-section can enhance ultrasonic signal attenuation. This also results in poor imaging quality and an inability to accurately restore the original appearance. Furthermore, the fixed scanning frequency is pre-selected, resulting in low imaging accuracy.

[0032] To improve the above problems, an embodiment of the present invention provides a reflection-transmission dual-modal ultrasound tomography method and system based on multi-frequency fusion. The embodiment of the present invention is introduced in detail below.

[0033] This embodiment provides a reflection-transmission dual-modality ultrasound tomography method based on multi-frequency fusion. This method can be applied to a reflection-transmission dual-modality ultrasound tomography system based on multi-frequency fusion. The reflection-transmission dual-modality ultrasound tomography system based on multi-frequency fusion includes a controller and multiple ultrasonic sensors. Figure 1 The flowchart of the reflection-transmission dual-modality ultrasound tomography method based on multi-frequency fusion is shown, and the method mainly includes the following steps: Step S102 , sequentially stimulating low-frequency ultrasound on each ultrasonic sensor so that each ultrasonic sensor performs reflection-projection dual-modal tomography at an initial frequency, and constructing a low-frequency coefficient matrix and a low-frequency ultrasonic image based on the reflection signal and transmission signal received by each ultrasonic sensor; The above-mentioned ultrasonic sensor can be, for example, an ultrasonic probe, and multiple ultrasonic sensors are evenly arranged on the outer surface of the cross section of the channel to be detected. The cross section of the channel to be detected is an axisymmetric figure, such as a circular, square or rectangular axisymmetric figure, and the multiple ultrasonic sensors are distributed axisymmetrically relative to the cross section of the channel to be detected, so that the ultrasonic sensor can receive the transmission signal of the sensor on the symmetrical side.

[0034] The above-mentioned initial frequency is the frequency at which the sound waves of each ultrasonic sensor can penetrate each ultrasonic imaging path when the cross-sectional gas content of the channel to be detected is the predicted highest cross-sectional gas content; the above-mentioned predicted highest cross-sectional gas content is the expected highest cross-sectional gas content under all test conditions of the channel to be detected. For example, the maximum cross-sectional gas content obtained by measurement can be selected from the historical imaging data of the channel to be detected. For experiments in which the range of cross-sectional gas content can be controlled or predicted, the predicted highest cross-sectional gas content can also be used, which is recorded as the predicted highest cross-sectional gas content. The frequency corresponding to the amplitude of the attenuated sound pressure received by the ultrasonic sensor at the predicted highest cross-sectional gas content is higher than the amplitude of the ambient noise is determined as the initial frequency to ensure that the ultrasonic sensor can penetrate the ultrasonic imaging path at the current cross-sectional gas content during low-frequency imaging.

[0035] In one embodiment, the excitation signal of the ultrasonic sensor is a pulsed step frequency modulation signal; the pulsed step signal can be expressed as: (11) in, is the low-frequency signal amplitude, is the high frequency signal amplitude, f 1 is the initial frequency used to excite low-frequency ultrasound, f 2 is the target frequency used to excite high-frequency ultrasound, and is the phase, is the total time of exciting low-frequency ultrasound (i.e. low-frequency scanning), ~ The time period is the time required to construct a low-frequency coefficient matrix and a low-frequency ultrasound image based on the reflection signal and the transmission signal, and to determine a target frequency for high-frequency imaging based on the low-frequency ultrasound image; and The total time required to excite high-frequency ultrasound is the same as the total time required to excite low-frequency ultrasound. - = ,Right now .

[0036] To ensure phase continuity, the phases of the low-frequency ultrasound and the high-frequency ultrasound must meet the following requirements: (12) When stimulating low-frequency ultrasound, for a sensor array composed of multiple ultrasonic sensors, multiple ultrasonic sensors are stimulated in sequence, and a dual-mode fusion reconstruction algorithm such as a hybrid binary reconstruction algorithm or a linear reconstruction algorithm is used to construct a dual-modal coefficient matrix based on the reflected and transmitted signals received by each ultrasonic sensor to obtain a low-frequency coefficient matrix and a low-frequency ultrasonic image.

[0037] Step S104, determining a target frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path based on the low-frequency ultrasonic image; The bubble length and liquid metal length on each ultrasonic path are determined based on the low-frequency ultrasonic image. The frequency corresponding to the maximum ultrasonic attenuation allowed on each ultrasonic imaging path is calculated based on the bubble length and liquid metal length on each ultrasonic path. The minimum frequency value is selected from the frequencies corresponding to the maximum ultrasonic attenuation allowed on each ultrasonic path and recorded as the minimum frequency. The target frequency in high-frequency imaging that can enable the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path is determined based on the minimum frequency and the set frequency corresponding to the required highest resolution.

[0038] Step S106 , sequentially stimulating each ultrasonic sensor with high-frequency ultrasound to enable each ultrasonic sensor to perform reflection-projection dual-modal tomography at a target frequency, and constructing a high-frequency coefficient matrix based on the reflected signal and the transmitted signal received by each ultrasonic sensor; For the sensor array composed of each ultrasonic wave, a pulsed step frequency modulation signal is used to sequentially excite multiple high-frequency ultrasonic waves. A hybrid binary reconstruction algorithm is used to construct a dual-modal coefficient matrix based on the reflected signal and the transmitted signal to obtain a high-frequency coefficient matrix.

[0039] Step S108 , fusing the low-frequency coefficient matrix and the high-frequency coefficient matrix to obtain a fusion coefficient matrix, and reconstructing the image based on the fusion coefficient matrix to obtain a two-phase distribution map of multi-frequency fusion.

[0040] A fusion algorithm is used to fuse the low-frequency coefficient matrix obtained from low-frequency imaging with the high-frequency coefficient matrix obtained from high-frequency imaging to obtain a fused coefficient matrix. The fusion algorithm can be one or more of weighted fusion, multi-scale fusion, and adaptive fusion. A hybrid binary reconstruction algorithm is used to reconstruct the fused coefficient matrix into a fused image. The fused image is then denoised and bubble-sealed to restore the bubble image to its original state, resulting in a two-phase distribution map of multi-frequency fusion.

[0041] The above-mentioned reflection-transmission dual-modal ultrasonic tomography method based on multi-frequency fusion provided in this embodiment first sequentially excites low-frequency ultrasound on each ultrasonic sensor to perform reflection-projection dual-modal tomography, and determines the target frequency of subsequent high-frequency imaging based on the low-frequency ultrasonic image obtained by low-frequency imaging, so as to use adaptive frequency for high-frequency imaging, thereby ensuring that high-frequency sound waves can penetrate the channel to be detected. By adaptively fusing the low-frequency coefficient matrix with the high-frequency coefficient matrix, the final multi-frequency fused two-phase distribution map can meet the minimum resolution requirement, and can flexibly adapt to working conditions such as bubble measurement domains of different sizes and gas content of different cross sections, thereby improving the imaging effect of working conditions with multiple bubbles and bubble groups and improving imaging accuracy.

[0042] In one implementation, this embodiment provides a specific implementation of constructing a low-frequency coefficient matrix and a low-frequency ultrasound image based on the reflection signal and transmission signal received by each ultrasound sensor: Based on the reflected signals and transmitted signals received by each ultrasonic sensor, a dual-mode fusion reconstruction algorithm is used to reconstruct the low-frequency coefficient matrix and the initial low-frequency ultrasonic image; The initial low-frequency ultrasonic image is subjected to denoising processing, and a bubble sealing processing is performed on the denoised initial low-frequency ultrasonic image to restore the bubble image to be complete, thereby obtaining a low-frequency ultrasonic image.

[0043] For a sensor array consisting of N ultrasonic transducers, a total of N×N time-varying ultrasonic signals are received. The measurement field is divided into different pixel blocks according to a two-dimensional partitioning method, and all non-repeating sound wave paths are marked. Based on the reflected and transmitted signals received by each ultrasonic sensor, a dual-mode fusion reconstruction algorithm (such as a hybrid binary reconstruction algorithm or a linear reconstruction algorithm) is used to construct a dual-modal coefficient matrix, denoted as the low-frequency coefficient matrix. The low-frequency coefficient matrix is ​​the weight distribution of the dual-mode reconstructed image, and the initial low-frequency ultrasonic image is obtained.

[0044] For example, assuming that there are 24 ultrasonic sensors, the calculation formula for the low-frequency coefficient matrix is: (13) (14) in, is the weight distribution of the dual-mode reconstructed image (i.e., the initial low-frequency ultrasound image), m and n represent the node coordinates of the two-dimensional division, and the transmission signal matrix and reflected signal matrix Obtained through the reflection signal and transmission signal received by each ultrasonic sensor, is the number of echoes received by the ultrasonic sensor Tx, is the ratio of the attenuation signal amplitude of particles passing through the Tx-Ry ultrasonic path to the background value, The value of is between 0 and 1. is the threshold for signal binarization, is the sensitivity matrix, is the unit network weight, is the arc projection unit weight.

[0045] The construction process of the sensitivity matrix is: Read signal matrix : If x=y, go to the next step; If x≠y and , proceed to the next step; If x≠y and , read the reflected signal , based on all TOF data received by the self-transmitting and self-receiving ultrasonic sensor, the minimum value is searched to determine the particle system outer contour positioning arc, the arc radius is: (15) The distance between the ultrasonic sensor and the detection area is greater than For any node of Set to 1.

[0046] All arcs are weighted cumulatively. The unit grid weight is the triangle rule adopted by the transmission reconstruction method. 1, to balance the weight influence of the TOF arc received by the ultrasonic sensor itself during superposition, the arc projection unit weight Set to , and are the effective transmission signal number and reflection signal number, respectively.

[0047] The initial low-frequency ultrasound image is subjected to binary segmentation processing, and a filtering algorithm (such as a Gaussian filtering algorithm or other filtering algorithms) is used to perform image denoising. Then, a bubble closing process is performed, and a closing operation is performed based on an elliptical kernel, first dilating and then corroding to fill the internal gaps of the bubble contour, connect adjacent contours, and close the bubble edges, thereby restoring the bubble image to its entirety.

[0048] In one embodiment, this embodiment provides an implementation for determining a target frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path based on a low-frequency ultrasonic image. Specifically, the implementation may refer to the following steps: Step (1): determining the frequency corresponding to the maximum ultrasonic attenuation on the ultrasonic path of each ultrasonic sensor based on the low-frequency ultrasonic image, and selecting the lowest frequency from the frequencies corresponding to the maximum ultrasonic attenuation of each ultrasonic path; On each ultrasonic path corresponding to the low-frequency ultrasonic imaging, the highest frequency corresponding to the maximum ultrasonic attenuation allowed on each ultrasonic path is calculated, and the lowest frequency is selected from all ultrasonic paths.

[0049] In a specific embodiment, the bubble length and liquid metal length on each ultrasonic path are obtained from the low-frequency ultrasonic image; based on the bubble length and liquid metal length on each ultrasonic path, the frequency corresponding to when the attenuated sound pressure amplitude on each ultrasonic path is greater than the ambient noise is determined.

[0050] The attenuation coefficients for different frequencies are calculated as follows: Different prediction models can be selected for calculations of different liquid metals, such as the ultrasonic attenuation coefficient below 5 MHz in lead-bismuth liquid metals. It can be predicted using the following formula: (16) in, is the dynamic viscosity, is the density, is the speed of sound, is the frequency of the i-th ultrasonic path. Ultrasonic attenuation coefficient of air It can be predicted using the following formula: (17) in, is the air temperature, is the reference temperature (25°C), is the air pressure, It is standard atmospheric pressure (101.325kPa).

[0051] Based on the low-frequency ultrasound image obtained in the above steps, OpenCV is called to obtain the bubble length on each ultrasound path i. and liquid metal length In the processed low-frequency ultrasonic image, the grayscale of the bubble edge and interior is 0, while the grayscale of the liquid metal is 255. and liquid metal length This can be done by counting the number of pixels below a grayscale threshold (such as 127). Get, that is: (18) in, is the total number of pixels on ultrasound path i, is the pipe diameter.

[0052] At the new frequency Under the condition of ultrasonic path i, the attenuated sound pressure amplitude received by the receiving probe is (19) Select the sound pressure amplitude after attenuation For any appropriate value higher than the ambient noise, the above formulas (16-19) can be combined to calculate the frequency corresponding to the maximum ultrasonic attenuation on each ultrasonic path. Select the lowest frequency from the frequencies corresponding to the maximum ultrasonic attenuation of each ultrasonic path , to ensure that the sound wave signal emitted during high-frequency imaging can penetrate all ultrasonic paths.

[0053] Step (2): Obtain a set frequency corresponding to a set minimum resolvable bubble radius that can be detected by the ultrasonic sensor; The required minimum resolvable bubble radius is determined, and the set frequency corresponding to the set minimum resolvable bubble radius is calculated based on the above formula (1) to improve the resolution so that bubbles of different sizes in the channel to be detected can be imaged.

[0054] Step (3): The minimum value between the lowest frequency and the set frequency is used as the target frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path.

[0055] Combined with the requirement for the highest resolution, the appropriate ultrasound frequency (i.e., target frequency) is determined for high-frequency imaging. The calculation formula is: (20) In one embodiment, this embodiment provides a specific implementation method for constructing a high-frequency coefficient matrix based on the reflected signals and transmitted signals received by each ultrasonic sensor: a dual-mode fusion reconstruction algorithm is used to reconstruct the high-frequency coefficient matrix based on the reflected signals and transmitted signals received by each ultrasonic sensor.

[0056] According to the reflected and transmitted signals received by each ultrasonic sensor during high-frequency imaging, a dual-mode fusion reconstruction algorithm is used to construct a dual-mode coefficient matrix, which is recorded as the high-frequency coefficient matrix. That is, the high-frequency coefficient matrix can be calculated using the above formulas (13) to (14).

[0057] In one implementation, this embodiment provides a specific implementation method for fusing a low-frequency coefficient matrix with a high-frequency coefficient matrix to obtain a fused coefficient matrix: an adaptive gradient weight allocation algorithm is used to adaptively fuse the low-frequency coefficient matrix with the high-frequency coefficient matrix to obtain a fused coefficient matrix.

[0058] The channel to be measured is segmented, and the low-frequency coefficient matrix and the high-frequency coefficient matrix are dynamically gradient-weighted fused using an adaptive gradient weight distribution method to obtain a fused coefficient matrix.

[0059] Taking the rectangular partitioning method as an example, the space to be measured is divided into horizontal and vertical Pixels, use the Sobel operator to calculate the horizontal gradient and vertical gradient , and calculate the gradient magnitude: (twenty one) Then, dynamic weight allocation is performed according to the ratio of the low-frequency gradient amplitude to the high-frequency gradient amplitude at a grid.

[0060] (twenty two) To avoid calculation errors, Take the minimum value, such as , is the low-frequency gradient amplitude, is the high-frequency gradient amplitude, is the weight of the low-frequency coefficient matrix, is the weight of the high-frequency coefficient matrix.

[0061] Perform pixel fusion: Perform dynamic gradient weighted fusion on the images corresponding to the low-frequency coefficient matrix and the high-frequency coefficient matrix to calculate the fusion coefficient matrix : (twenty three) in, is the low-frequency coefficient matrix, is the high frequency coefficient matrix.

[0062] In one embodiment, this embodiment provides a specific implementation method for obtaining a two-phase distribution map of multi-frequency fusion by image reconstruction based on a fusion coefficient matrix: reconstructing an initial fusion image based on the fusion coefficient matrix; denoising the initial fusion image, and performing bubble sealing processing on the denoised initial fusion image to restore the bubble image to its original state, thereby obtaining a two-phase distribution map of multi-frequency fusion.

[0063] Fusion coefficient matrix To fusion image weight distribution, dual-mode fusion reconstruction algorithm is used through fusion coefficient matrix Imaging is performed to obtain an initial fused image; the initial fused image is subjected to binary segmentation processing, and a filtering algorithm (such as a Gaussian filtering algorithm or other filtering algorithms) is used to perform image denoising processing, and then a bubble closing process is performed. A closing operation is performed based on an elliptical kernel, first dilating and then corroding to fill the internal gaps of the bubble contour, connect adjacent contours, close the bubble edges, and finally obtain a multi-frequency fused two-phase distribution map.

[0064] In one embodiment, in order to prevent the acoustic signal excited by the previous probe from interfering with the acoustic signal excited by the next probe, the time interval between exciting two adjacent ultrasonic sensors needs to be predetermined when exciting each sensor in sequence.

[0065] In the steps of sequentially exciting low-frequency ultrasound on each ultrasonic sensor and sequentially exciting high-frequency ultrasound on each ultrasonic sensor, the excitation time interval of each ultrasonic sensor is: (twenty four) Among them, the cross section of the channel to be detected is circular, is the cross-sectional diameter of the channel to be detected, is the speed of sound in liquid metal, is the speed of sound in air, is the cross-sectional air void fraction, is the number of ultrasonic sensors.

[0066] For reflection imaging, the maximum distance (i.e., diameter) of the system echo signal should not interfere with the system when no bubbles are present. For transmission imaging, this interval should be greater than the time it takes for the sensor to receive a single transmission signal. Due to the significant difference in sound speed between air and liquid metal, the cross-sectional gas fraction should be considered when considering the transmission method. Therefore, the excitation time interval for each ultrasonic sensor is the maximum of the time required to receive the feedback signal for both the reflection and transmission methods.

[0067] For example, for a circular pipe with a diameter of 50mm, 24 ultrasonic probes are evenly arranged on the circumference of the outer side of the circular pipe cross section. The working fluid is a lead-bismuth-air system with a temperature of 400°C (the sound velocity of lead-bismuth is about 1700m / s, and the sound velocity of air is about 520m / s). The total measurement time determined by the reflection method is 1.4ms. Under extremely high gas content conditions (gas content greater than 60%), the measurement time restricted by the transmission principle will become dominant. This situation is very rare in the reactor field. Therefore, for the case where bubbles are dispersed phase, the total time of exciting low-frequency ultrasound is It can be determined by the following formula: (25) The above-mentioned reflection-transmission dual-modal ultrasonic tomography method based on multi-frequency fusion provided in this embodiment, by adopting multi-frequency ultrasonic imaging, not only ensures that discrete bubbles of minimum resolution size can be captured, but also improves the imaging effect of working conditions with multiple bubbles and bubble groups. Moreover, the dual-modal imaging provided in this embodiment does not simply fuse the low-frequency imaging results with the high-frequency imaging results, but uses the low-frequency imaging results to determine the frequency of the next high-frequency imaging, ensuring that the high-frequency sound waves can penetrate the entire field to be measured and ensure that the minimum resolution requirements are met as much as possible, thereby improving the imaging accuracy and being applicable to the fusion of more frequencies, such as adding an intermediate frequency to form a three-frequency fused reflection-transmission dual-modal ultrasonic tomography, and performing reflection-transmission dual-modal ultrasonic tomography at the intermediate frequency f3 to obtain the coefficient matrix V mid ( m,n );Will V low ( m,n ), V mid ( m,n )and V high ( m,n ) fusion to obtain the fusion coefficient matrix V fused ( m,n ) and reconstruct the multi-frequency fusion image.

[0068] Based on the above embodiment, this embodiment provides an example of applying the above multi-frequency fusion-based reflection-transmission dual-mode ultrasonic tomography method to perform ultrasonic tomography on a two-phase flow consisting of liquid metal and bubbles, see Figure 2 The flowchart of ultrasonic tomography of a two-phase flow consisting of liquid metal and bubbles is shown. The specific steps can be referred to as follows: Step 201: Determine the initial frequency of low-frequency imaging based on the predicted highest cross-section gas fraction. f 1. Determine the set frequency based on the set highest resolution f 0; Under the predicted highest cross-sectional air fraction, the frequency corresponding to the amplitude of the attenuated sound pressure received by the ultrasonic sensor being higher than the amplitude of the ambient noise is determined as the initial frequency.

[0069] The required minimum resolvable bubble radius is determined based on the set maximum resolution, and the set frequency corresponding to the set minimum resolvable bubble radius is calculated based on the above formula (1).

[0070] Step 202 , sequentially excite low-frequency ultrasound on each ultrasonic sensor, perform reflection-projection dual-modal tomography at the initial frequency, and obtain a low-frequency coefficient matrix and an initial low-frequency ultrasound image; Step 203 , performing binarization and bubble sealing processing on the initial low-frequency ultrasonic image to obtain a low-frequency ultrasonic image (i.e., a low-frequency two-phase distribution map); The initial low-frequency ultrasound image is binarized and the interior of the bubbles is sealed to obtain a low-frequency ultrasound image. Specifically, a Python script is used to call OpenCV for optimal binarization segmentation. Gaussian filtering is used to remove noise. A closing operation is performed based on an elliptical kernel, first dilating and then eroding to fill gaps in the contour, connect adjacent contours, and close the edges.

[0071] Step 204: Calculate the frequency that enables the sound waves of each ultrasonic sensor to just penetrate each ultrasonic imaging path based on the attenuation effect, and select the lowest frequency from the frequencies corresponding to the maximum ultrasonic attenuation of each ultrasonic path. ; Step 205: Modulate the frequency to the target frequency (i.e., the new frequency) through the step frequency modulation signal. ; Step 206, at the target frequency Perform reflection-projection dual-modal tomography to obtain a high-frequency coefficient matrix; Step 207 , adaptively fusing the low-frequency coefficient matrix and the high-frequency coefficient matrix to obtain a fusion coefficient matrix and reconstructing a multi-frequency fusion image; Step 208 : Binarization and bubble sealing processing are performed on the multi-frequency fusion image to obtain a multi-frequency fusion two-phase distribution map.

[0072] The multi-frequency fusion method provided in this embodiment improves existing dual-modal imaging methods to enhance imaging accuracy. Its adaptive frequency design allows for flexible adaptation to various measurement domain sizes and cross-sectional gas content. This method is applicable to all liquid metal-gas systems, not just the lead-bismuth-air system described above. The method is also applicable to any symmetrically arranged ultrasonic tomography system, not just circular pipes but also rectangular channels.

[0073] Corresponding to the reflection-transmission dual-modal ultrasound tomography method based on multi-frequency fusion provided in the above embodiment, an embodiment of the present invention provides a reflection-transmission dual-modal ultrasound tomography system based on multi-frequency fusion, comprising: a controller and multiple ultrasonic sensors, the controller comprising a processor and a storage device; the storage device storing a computer program, which, when executed by the processor, executes the reflection-transmission dual-modal ultrasound tomography method based on multi-frequency fusion provided in the above embodiment.

[0074] In one embodiment, the plurality of ultrasonic sensors are evenly arranged on the outer surface of the channel to be detected, the cross section of the channel to be detected is an axisymmetric figure, and the plurality of ultrasonic sensors are distributed axisymmetrically relative to the cross section of the channel to be detected.

[0075] The system provided in this embodiment has the same implementation principle and technical effects as those of the aforementioned embodiments. For the sake of brief description, for matters not mentioned in the system embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0076] An embodiment of the present invention provides a computer-readable medium, wherein the computer-readable medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method described in the above embodiment.

[0077] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process of the system described above can refer to the corresponding process in the aforementioned embodiment and will not be repeated here.

[0078] In addition, in the description of the embodiments of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0079] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0080] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0081] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A reflection-transmission dual-modality ultrasound tomography method based on multi-frequency fusion, characterized in that: The invention is applied to a reflection-transmission dual-modal ultrasonic tomography system based on multi-frequency fusion, wherein the reflection-transmission dual-modal ultrasonic tomography system based on multi-frequency fusion includes a plurality of ultrasonic sensors, and the reflection-transmission dual-modal ultrasonic tomography method based on multi-frequency fusion includes: Each ultrasonic sensor is sequentially excited with low-frequency ultrasound, causing each ultrasonic sensor to perform reflection-projection dual-modal tomography at an initial frequency, and a low-frequency coefficient matrix and a low-frequency ultrasonic image are constructed based on the reflected signal and the transmitted signal received by each ultrasonic sensor; wherein the initial frequency is a frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path when the cross-sectional gas content of the channel to be detected is the predicted highest cross-sectional gas content; determining, based on the low-frequency ultrasonic image, a target frequency capable of enabling the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path; Exciting high-frequency ultrasound in sequence on each of the ultrasonic sensors so that each of the ultrasonic sensors performs reflection-projection dual-modal tomography at the target frequency, and constructing a high-frequency coefficient matrix based on the reflection signal and the transmission signal received by each of the ultrasonic sensors; The low-frequency coefficient matrix and the high-frequency coefficient matrix are fused to obtain a fusion coefficient matrix, and an image is reconstructed based on the fusion coefficient matrix to obtain a two-phase distribution map of multi-frequency fusion.

2. The method according to claim 1, characterized in that The step of constructing a low-frequency coefficient matrix and a low-frequency ultrasonic image based on the reflected signals and the transmitted signals received by each ultrasonic sensor includes: Reconstructing the low-frequency coefficient matrix and the initial low-frequency ultrasonic image using a dual-mode fusion reconstruction algorithm based on the reflected signals and the transmitted signals received by each ultrasonic sensor; Denoising is performed on the initial low-frequency ultrasonic image, and bubble sealing is performed on the denoised initial low-frequency ultrasonic image to restore the bubble image to be complete, thereby obtaining the low-frequency ultrasonic image.

3. The method according to claim 1, characterized in that The step of determining, based on the low-frequency ultrasonic image, a target frequency capable of enabling the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path comprises: determining, based on the low-frequency ultrasonic image, a frequency corresponding to a maximum ultrasonic attenuation on an ultrasonic path of each ultrasonic sensor, and selecting a lowest frequency from the frequencies corresponding to the maximum ultrasonic attenuation of each ultrasonic path; Obtaining a set frequency corresponding to a set minimum resolvable bubble radius that can be detected by the ultrasonic sensor; The minimum value between the lowest frequency and the set frequency is used as the target frequency that enables the sound waves of each ultrasonic sensor to penetrate each ultrasonic imaging path.

4. The method according to claim 3, characterized in that The step of determining the frequency corresponding to the maximum ultrasonic attenuation on the ultrasonic path of each ultrasonic sensor based on the low-frequency ultrasonic image includes: Acquire the bubble length and the liquid metal length on each of the ultrasonic paths from the low-frequency ultrasonic image; The frequency corresponding to when the attenuated sound pressure amplitude on each ultrasonic path is greater than the ambient noise is determined based on the bubble length and the liquid metal length on each ultrasonic path.

5. The method according to claim 1, wherein The step of constructing a high-frequency coefficient matrix based on the reflected signal and the transmitted signal received by each ultrasonic sensor includes: The high-frequency coefficient matrix is ​​reconstructed using a dual-mode fusion reconstruction algorithm based on the reflected signal and the transmitted signal received by each ultrasonic sensor.

6. The method according to claim 1, characterized in that The step of fusing the low-frequency coefficient matrix with the high-frequency coefficient matrix to obtain a fused coefficient matrix includes: The low-frequency coefficient matrix and the high-frequency coefficient matrix are adaptively fused using an adaptive gradient weight distribution algorithm to obtain the fused coefficient matrix.

7. The method according to claim 1, characterized in that The step of performing image reconstruction based on the fusion coefficient matrix to obtain a two-phase distribution map of multi-frequency fusion includes: Reconstructing an initial fused image based on the fusion coefficient matrix; The initial fused image is subjected to denoising processing, and the denoised initial fused image is subjected to bubble sealing processing to restore the bubble image to be complete, thereby obtaining the multi-frequency fused two-phase distribution map.

8. The method according to claim 1, characterized in that The excitation signal of the ultrasonic sensor is a pulsed step frequency modulation signal; In the steps of sequentially exciting low-frequency ultrasound for each ultrasonic sensor and sequentially exciting high-frequency ultrasound for each ultrasonic sensor, the excitation time interval of each ultrasonic sensor is ; Wherein, the cross section of the channel to be detected is circular, is the cross-sectional diameter of the channel to be detected, is the speed of sound in liquid metal, is the speed of sound in air, is the cross-sectional air content.

9. A reflection-transmission dual-modality ultrasound tomography system based on multi-frequency fusion, characterized in that: include: a controller and a plurality of ultrasonic sensors, the controller comprising a processor and a memory device; The storage device stores a computer program, which, when executed by the processor, performs the method according to any one of claims 1 to 8.

10. The system according to claim 9, characterized in that The plurality of ultrasonic sensors are evenly arranged on the outer surface of the channel to be detected, the cross section of the channel to be detected is an axisymmetric figure, and the plurality of ultrasonic sensors are distributed in an axisymmetric manner relative to the cross section of the channel to be detected.

Images