Artifact improvement and noise suppression method for aircraft horizontal tail large shaft defect imaging

Abstract

The invention relates to an artifact improvement and noise suppression method for aircraft horizontal tail large shaft defect imaging, and belongs to the technical field of ultrasonic detection. Comprising the following steps: selecting a proper detection position, and establishing a polar coordinate system; dividing uniform grids; calculating a sound wave propagation distance, and delaying superposition beam forming; traversing all focus points; a beamforming method is improved. The method solves the problems that a traditional delay superposition beam forming method is simple in waveform superposition synthesis mode, incoherent noise mixed in echo signals cannot be effectively distinguished and eliminated, imaging is easily interfered by noise, imaging robustness is not high, and imaging artifacts caused by ultrasonic side lobes cannot be improved. On the basis of a minimum variance adaptive beam forming method, a minimum variance-signal-to-noise ratio coefficient composite adaptive beam forming method is improved and provided; by adding Gaussian strong noise into echo signals to simulate an interference environment, the method has a noise environment imaging effect and a best artifact suppression effect.

Description

Technical Field

[0001] The invention relates to a method for improving artifacts and suppressing noise in imaging defects of a horizontal tail shaft, and belongs to the technical field of ultrasonic detection. Background Art

[0002] The aircraft horizontal tail shaft is the transmission shaft of the aircraft's horizontal tail stabilizer. The fixed end of the shaft is connected to the aircraft fuselage, and the aircraft's horizontal tail is suspended on two force-bearing fulcrums: the fixed end and the suspension end of the horizontal tail shaft. Therefore, the aircraft horizontal tail shaft is an important load-bearing component connecting the aircraft's horizontal tail and the aircraft fuselage. The forces it bears are mainly bending stress and torsional stress transmitted through the aircraft's horizontal tail. If the horizontal tail shaft has defects such as holes or seams due to process errors during the casting process or due to stress fatigue during flight, the risk of shaft breakage will be greatly increased, causing the aircraft's horizontal tail to lose balance uncontrollably. This hidden danger seriously affects the flight safety of the aircraft. Therefore, factory inspection, regular inspection, maintenance and repair of the horizontal tail shaft are of great strategic significance to ensure aircraft safety.

[0003] The ultrasonic method generates ultrasonic waves by exciting the sound field inside the workpiece. When the sound waves encounter the internal defects of the test piece, they will be reflected back to generate defect echoes. By processing the defect echoes, information such as the size and location of the internal defects of the test piece can be obtained. Limited by the curved shape of the horizontal tail shaft, the traditional single-element transmitting and single-element receiving ultrasonic method has low detection accuracy and cannot accurately detect the size and location of defects inside the shaft. Therefore, based on the single-transmitting and single-receiving ultrasonic method, the phased array ultrasonic detection method came into being.

[0004] Ultrasonic phased arrays are divided into two types: rigid phased arrays and flexible phased arrays. Rigid phased arrays cannot be bent and are difficult to perfectly fit the curved surface of the shaft, while flexible phased arrays have good bendability and high fit. Therefore, based on the comparison of the advantages and disadvantages of these two phased arrays and the actual detection environment, the flexible phased array ultrasonic defect detection solution for the horizontal tail shaft is selected. Since the automation level, detection efficiency and noise resistance of the horizontal tail shaft defect detection are required to be high in actual industry, it is necessary to optimize the design of its defect detection and imaging methods to achieve imaging artifact improvement and noise suppression.

[0005] In the actual detection and imaging process of flexible ultrasonic phased array, the imaging quality will be affected by many factors. First, the sidelobe artifacts caused by the side lobes of the ultrasonic beam at the defect point to be detected will greatly reduce the contrast and resolution of the imaging at the defect point during actual detection, thereby reducing the imaging quality; second, the actual factory and industrial detection environment is generally harsh, with a large amount of electromagnetic interference, radiation and other electrical noise, and the working principle of the flexible phased array receiving element is to convert the received ultrasonic signal into an electrical signal waveform for reception. Therefore, in the ultrasonic echo reception process, it is easy to be interfered by electrical noise, which introduces a large amount of incoherent noise into the echo waveform of each phased array element channel, resulting in a large number of noise points in the overall imaging area during the final imaging, which seriously affects the global contrast and resolution of the imaging. Therefore, it is necessary to improve and suppress the artifacts and incoherent noise that may appear in the flexible phased array imaging.

[0006] Therefore, it is urgent to propose an artifact improvement and noise suppression method for aircraft horizontal tail axis defect imaging to solve the above technical problems. Summary of the invention

[0007] In order to solve the above problems, an artifact improvement and noise suppression method for imaging defects of the aircraft horizontal tail shaft is provided. A brief overview of the present invention is given below to provide a basic understanding of certain aspects of the present invention. It should be understood that this overview is not an exhaustive overview of the present invention. It is not intended to determine the key or important parts of the present invention, nor is it intended to limit the scope of the present invention.

[0008] The technical solution of the present invention:

[0009] The method for improving artifacts and suppressing noise for imaging defects of a large axis of a horizontal tail of an aircraft includes the following steps:

[0010] Step 1: Select a suitable detection position and establish a polar coordinate system;

[0011] Step 2: Divide the grid into uniform grids;

[0012] Step 3: Calculate the sound wave propagation distance and perform delay-addition beam synthesis;

[0013] Step 4: Traverse all focus points;

[0014] Step 5: Improve the beamforming method.

[0015] Preferably: in step 1, according to the actual curved surface structure of the horizontal tail shaft, the ports at both ends of the shaft body of the horizontal tail shaft are narrow, and the probe cannot be inserted into the internal cavity to fit the inner surface for scanning and inspection, so the fitting detection position of the probe is selected on the outer surface of the outer diameter of the horizontal tail shaft;

[0016] A polar coordinate system is established for the imaging region with the center of the horizontal tail major axis as the pole and the ray passing through the pole at the center of the imaging region as the polar axis.

[0017] Preferably: in step 2, the imaging focus points of a uniform grid are obtained by uniformly dividing the polar axis and the polar angle; that is, according to step 1, the center of the main axis is selected as the pole, the center line extending outward from this point is used as the polar axis, and then the angle is measured around this center line. Next, in step 2, the imaging focus points of a uniform grid are obtained by uniformly dividing the polar axis and the polar angle. This is actually to create a grid in a polar coordinate system, and each grid point represents a specific combination of polar diameter and polar angle. In this step, there is no need to directly explore the internal cavity, and a uniformly distributed exploration and detection can be performed on the outer surface of the outer diameter of the horizontal tail main axis.

[0018] Preferably: in step three, the sound wave propagation distance between the imaging focal point and the transmitting and receiving array elements is calculated, and the beam synthesis amplitude at the corresponding imaging focal point is obtained by delay superposition; that is, according to the principle of sound wave propagation, the sound wave goes from the transmitting array element to the imaging focal point, and then returns from the imaging focal point to the receiving array element, and the total propagation distance = sound wave propagation speed × time / 2; by calculating the sound wave propagation time from each array element to the imaging focal point, and time delaying the echo signal of each array element, and then superimposing the signals of all array elements, the beam synthesis amplitude at the focal point is obtained, and the wave direction window function can also be introduced as an optimization factor in the delay superposition algorithm to improve the imaging quality.

[0019] Preferably: in step 4, all imaging focal points are traversed and calculated, and a fast full-focus imaging algorithm is used to finally obtain a defect imaging image.

[0020] Preferred: In step five, in order to solve the problems of imaging artifacts and imaging noise that may occur when using the traditional delay and superposition (DAS) beam synthesis method in the flexible phased array fast full focusing imaging algorithm, an improved minimum variance (MV) adaptive beam synthesis method is proposed based on the minimum variance (MV) adaptive beam synthesis method, which has better artifact improvement and noise suppression effects, thereby ensuring the high robustness and high-quality imaging of the fast full focusing algorithm during the defect detection of the aircraft horizontal tail shaft.

[0021] Preferably, the echo signal-to-noise ratio coefficient (SNRF) is the ratio of the echo signal mean to the echo signal standard deviation, which represents the ratio of the intensity of the desired imaging signal to the incoherent random noise signal in the ultrasonic echo signal. In the fast full-focus imaging mode, the calculation formula of the echo signal signal-to-noise ratio coefficient of the flexible phased array array is as follows:

[0022]

[0023] In the formula, N e is the number of array elements of the flexible phased array sparse excitation, Nr is the number of array elements of the flexible phased array sparse reception, x i (k) is the ultrasonic echo signal of the i-th array channel after the corresponding delay compensation processing at the k-th sampling time point, is the average value of all ultrasonic echo signals at the kth sampling time point;

[0024] The final output of the MV-SNRF composite adaptive beamforming method is:

[0025] y MV-SNRF (k) = SNRF (k) × y MV (k) (2)

[0026] Among them, SNRF(k) is the signal-to-noise ratio coefficient of the echo channel signal, y MV (k) is the output of the echo signal after MV adaptive beamforming.

[0027] The present invention has the following beneficial effects:

[0028] The present invention solves the problem that the traditional delayed-addition beamforming method cannot effectively distinguish and eliminate the mixed incoherent noise in the echo signal due to its simple waveform addition synthesis mode, the imaging is easily interfered by noise, the imaging robustness is not high, and the imaging artifacts caused by the ultrasonic side lobe cannot be improved; the present invention improves and proposes a minimum variance-signal-to-noise ratio coefficient composite adaptive beamforming method on the basis of the minimum variance adaptive beamforming method; by adding Gaussian strong noise to the echo signal to simulate the interference environment, it is verified by comparing with the traditional method that the minimum variance-signal-to-noise ratio coefficient composite adaptive beamforming method proposed by the present invention has better imaging effect in a noisy environment and the best artifact suppression effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of defect imaging in a curved surface structure.

[0030] Figure 2 This is the principle block diagram of the minimum variance-SNR coefficient composite adaptive beamforming method.

[0031] Figure 3 This is a comparison chart of the imaging artifact improvement effects of different beamforming methods;

[0032] (a) Delay-and-sum beamforming method;

[0033] (b) Minimum variance adaptive beamforming method;

[0034] (c) Minimum variance-SNR coefficient composite adaptive beamforming method.

[0035] Figure 4This is a comparison chart of the imaging noise suppression effects of different beamforming methods;

[0036] (a) Delay-and-sum beamforming method;

[0037] (b) Minimum variance adaptive beamforming method;

[0038] (c) Minimum variance-SNR coefficient composite adaptive beamforming method. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is described below by the specific embodiments shown in the accompanying drawings. However, it should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0040] Specific implementation method 1: Combination Figure 1-4 The present embodiment is described. The method for improving artifacts and suppressing noise for imaging defects of a large horizontal tail shaft of an aircraft in the present embodiment comprises the following steps:

[0041] Step 1: Select a suitable detection position and establish a polar coordinate system;

[0042] The detection surface of the traditional linear array hard probe element is a rectangular plane, so the rectangular coordinate system is generally used for modeling and calculation of the imaging algorithm; while the detection surface of the flexible phased array element is a circular arc surface when it fits the horizontal tail axis. If the rectangular coordinate system is continued to be used for calculation and imaging, there will be many inconveniences; therefore, the polar coordinates are established for the imaging area with the center of the axis as the pole O, and the ray that vertically divides the imaging area into two and passes through the pole as the polar axis, and the imaging points are evenly divided in the polar axis and polar angle directions, and the transmitting elements of the flexible phased array are stimulated to transmit ultrasonic waves, and the receiving elements of the flexible phased array are gated to receive echoes, and finally the imaging algorithm is used to focus the imaging operation on each imaging point that has been divided in advance;

[0043] Step 2: Divide the grid into uniform grids;

[0044] like Figure 1 As shown, the ultrasonic wave propagation distances among the grid intersection point P (i.e., the imaging focus point P), the transmitting array element of the flexible phased array, and the receiving array element are calculated by evenly dividing the polar axis and polar angle of the imaging area inside the horizontal tail shaft ring; the transmitting array element of the flexible phased array transmits ultrasonic waves from the outer surface of the outer diameter along the radial direction to the imaging area to be measured. If there is a hole-shaped or slit-shaped defect at the imaging point P, the ultrasonic wave is reflected at the defect, and then received by the receiving array element to obtain echo signal data;

[0045] Step 3: Calculate the sound wave propagation distance and perform delay-addition beam synthesis;

[0046] The delay time from the transmission to the reception of the ultrasonic signal at the focal point is calculated by combining the previously calculated sound wave propagation distance between the imaging point and the transmitting and receiving array elements with the sound velocity of the ultrasonic wave propagating in the workpiece material to be tested. All the echo data received by the array element are compensated for the delay at the corresponding imaging point and then superimposed to obtain the beam synthesis amplitude at the corresponding imaging point.

[0047] Step 4: Traverse all focus points;

[0048] Traverse and calculate all imaging points to finally obtain the defect imaging map;

[0049] The present invention is used for flexible phased array defect detection of aircraft horizontal tail shafts. During actual defect detection, the flexible phased array is attached to the outer surface of the shaft and slid circumferentially, so that internal defects of the shaft can be imaged frame by frame, and the internal health status of the horizontal tail shaft can be conveniently and intuitively judged from the images.

[0050] Step 5: Improve the beamforming method and adopt the minimum variance-SNR coefficient composite adaptive beamforming method;

[0051] The minimum variance beamforming method can minimize the output signal power of the flexible phased array, that is, minimize the incoherent noise power, while ensuring that the desired imaging signal passes losslessly. However, the MV beamforming method has limited ability to improve the imaging quality under high-intensity noise and is not very robust.

[0052] The present invention proposes a minimum variance-signal-to-noise ratio coefficient composite adaptive beamforming method, which uses the signal-to-noise ratio of the echo channel signal as a weight to perform secondary composite weighting on the minimum variance adaptive beamforming output; the echo signal-to-noise ratio coefficient (SNRF) is the ratio of the echo signal mean to the echo signal standard deviation, which represents the ratio of the intensity of the desired imaging signal to the incoherent random noise signal in the ultrasonic echo signal. In the fast full-focus imaging mode, the calculation formula of the echo signal signal-to-noise ratio coefficient of the flexible phased array array is as follows:

[0053]

[0054] In the formula, N e is the number of array elements of the flexible phased array sparse excitation, N r is the number of array elements of the flexible phased array sparse reception, x i (k) is the ultrasonic echo signal of the i-th array channel after the corresponding delay compensation processing at the k-th sampling time point, is the average value of all ultrasonic echo signals at the kth sampling time point;

[0055] The final output of the MV-SNRF composite adaptive beamforming method is:

[0056] y MV-SNRF (k) = SNRF (k) × y MV (k) (2)

[0057] Among them, SNRF(k) is the signal-to-noise ratio coefficient of the echo channel signal, y MV (k) is the output of the echo signal after MV adaptive beam synthesis;

[0058] The principle block diagram of the MV-SNRF composite adaptive beamforming method is as follows: Figure 2 As shown in the algorithm block diagram, the low signal-to-noise ratio echo signal x containing a large amount of random noise i (k), firstly, the MV adaptive beamforming method is used to perform the first step of noise filtering, filtering out part of the noise and obtaining the output signal y with improved signal-to-noise ratio MV (k), and then the second step of noise reduction processing is performed by the SNRF beam synthesis method, and finally the output signal y with high signal-to-noise ratio is obtained. MV-SNRF (k), due to the lossless nature of the MV algorithm through the imaging signal, the output signal y MV The imaging amplitude information at the defect point in (k) is retained to the maximum extent;

[0059] As for the sidelobe artifacts generated during ultrasound imaging, the single MV adaptive beamforming method has a very limited effect on suppressing the artifacts. The MV-SNRF composite adaptive beamforming method performs a secondary composite weighted suppression of the imaging artifacts with the SNRF factor as the weight based on the primary suppression of the artifacts by the MV adaptive beamforming method, thereby further maximizing the improvement of the sidelobe imaging artifacts.

[0060] Step 6 of the present invention verifies the effect of improving imaging artifacts and suppressing noise:

[0061] In order to verify that the MV-SNRF composite adaptive beamforming method has better imaging artifact improvement effect than the traditional DAS beamforming and MV adaptive beamforming methods, the multi-element full-focus imaging mode with the highest imaging API value and the number of sub-aperture elements M=16 is used to excite the ultrasonic beam and receive the echo. The defects in the imaging area are set to six point defects. The three beamforming methods of DAS, MV, and MV-SNRF are used to perform the beamforming calculation of the echo signal. The final imaging grayscale contrast is as follows: Figure 3 As shown;

[0062] By comparison, it can be found that due to the influence of the ultrasonic beam sidelobe, the traditional DAS beamforming method produces a large number of imaging artifacts near the defect point, which seriously affects the imaging quality and reduces the defect imaging contrast; while the adaptive beamforming method greatly improves the sidelobe imaging artifacts near the defect point, significantly reduces the imaging API parameter value, and improves the defect imaging quality and contrast, while ensuring that all imaging points can be clearly distinguished; and among the two adaptive beamforming methods, the MV-SNRF composite adaptive beamforming method has the lowest imaging API value, almost no artifacts in the imaging area, the best imaging contrast and imaging quality at the defect point, and has the best imaging artifact removal effect;

[0063] In order to compare and verify the imaging effects of the traditional DAS beamforming method and the MV and MV-SNRF adaptive beamforming methods when the echo signal is aliased with strong background noise interference, Gaussian white noise is added to all echo waveforms. In order to reproduce the extreme interference environment that may exist during field detection as much as possible, thereby reflecting the effectiveness and robustness of the adaptive beamforming method under extreme imaging conditions, the signal-to-noise ratio of the added Gaussian random white noise interference signal is set to -30dB;

[0064] from Figure 4 It can be seen from the results that after adding -30dB Gaussian noise to all echo signal channels, the imaging image of the traditional DAS beamforming method is full of noise points, and the imaging amplitudes of the three defect points (depth 35-40mm) located in the far field are submerged in the noise points and difficult to clearly distinguish; the MV adaptive beamforming method retains the imaging amplitude information at all defect points relatively well, and has a certain inhibitory effect on imaging noise, but the inhibitory ability is limited, and there are still obvious noise points in the final imaging image; compared with the DAS and MV beamforming methods, the MV-SNRF composite adaptive beamforming method has better defect point imaging contrast; that is, from the comparison in the figure, it can be concluded that the MV-SNRF composite adaptive beamforming method proposed in the present invention ensures that there are no obvious noise points in the final imaging image, while also retaining the imaging amplitude information at most defect points, and can clearly distinguish all defect points, with the highest imaging contrast and the best imaging quality.

[0065] It should be noted that in the above embodiments, as long as the technical solutions are not contradictory, they can be arranged and combined, and those skilled in the art can exhaust all possibilities based on the mathematical knowledge of arrangement and combination. Therefore, the present invention will no longer describe the technical solutions after arrangement and combination one by one, but it should be understood that the technical solutions after arrangement and combination have been disclosed by the present invention.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. Artifact improvement and noise suppression method for imaging defects of aircraft horizontal tail shaft, Features: The following steps are involved: Step 1: Select a suitable detection position and establish a polar coordinate system; Step 2: Divide the grid into uniform grids; Step 3: Calculate the sound wave propagation distance and perform delay-addition beam synthesis; Step 4: Traverse all focus points; Step 5: Improve the beamforming method.

2. The method for improving artifacts and suppressing noise for imaging defects of aircraft horizontal tail shafts according to claim 1, Features: In step 1, according to the curved surface structure of the horizontal tail shaft, the fitting detection position of the probe is selected on the outer surface of the outer diameter of the horizontal tail shaft; A polar coordinate system is established for the imaging region with the center of the horizontal tail major axis as the pole and the ray passing through the pole at the center of the imaging region as the polar axis.

3. The method for improving artifacts and suppressing noise for imaging defects of aircraft horizontal tail shafts according to claim 2, Features: In step 2, a uniform grid of imaging focal points is obtained by uniformly dividing the polar axis and polar angle.

4. The method for improving artifacts and suppressing noise for imaging defects of a large horizontal tail axis of an aircraft according to claim 3, Features: In step three, the sound wave propagation distance between the imaging focal point and the transmitting and receiving array elements is calculated, and the beam synthesis amplitude at the corresponding imaging focal point is obtained by delay superposition.

5. The method for improving artifacts and suppressing noise for imaging defects of aircraft horizontal tail shafts according to claim 4, Features: In step 4, by traversing and calculating all imaging focus points, a fast full-focus imaging algorithm is used to finally obtain the defect imaging image.

6. The method for improving artifacts and suppressing noise for imaging defects of a large horizontal tail axis of an aircraft according to claim 5, Features: In step five, based on the minimum variance adaptive beamforming method, an improved minimum variance-SNR coefficient composite adaptive beamforming method is proposed.

7. The method for improving artifacts and suppressing noise for imaging defects of aircraft horizontal tail shafts according to claim 6, Features: The echo signal-to-noise ratio coefficient is the ratio of the echo signal mean to the echo signal standard deviation, which represents the ratio of the intensity of the desired imaging signal to the incoherent random noise signal in the ultrasonic echo signal. In the fast full-focus imaging mode, the calculation formula of the echo signal signal-to-noise ratio coefficient of the flexible phased array array is as follows: In the formula, N e is the number of array elements of the flexible phased array sparse excitation, N r is the number of array elements of the flexible phased array sparse reception, x i (k) is the ultrasonic echo signal of the i-th array channel after the corresponding delay compensation processing at the k-th sampling time point, is the average value of all ultrasonic echo signals at the kth sampling time point; The final output of the MV-SNRF composite adaptive beamforming method is: y MV-SNRF (k)=SNRF(k)×y MV (k) (2) Among them, SNRF(k) is the signal-to-noise ratio coefficient of the echo channel signal, y MV (k) is the output of the echo signal after MV adaptive beamforming.

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