CN111693609B - An Ultrasonic Detection Method for Small Defects Based on Scattered Wave Interference Theory - Google Patents

Abstract

The invention discloses an ultrasonic detection method for micro-defects based on scattered wave interference theory, which comprises the following steps: (1) using the finite element simulation method to obtain the mechanism of the interference technology to identify micro-defects; (2) implementing the micro-defect interference mechanism based on the simulation. Acquisition of ultrasonic scanning signals and acquisition and identification of micro-defect feature information; (3) Making micro-defect test blocks to verify the ability of interferometry to identify micro-defects; (4) Optimizing the process parameters for interferometry detection of micro-defects. The invention extracts the micro-defect information through advanced signal analysis technology, realizes the rapid identification of the micro-defect, and solves the identification problem of the micro-defect.

Description

A method for ultrasonic detection of tiny defects based on scattered wave interference theory

Technical Field

The invention belongs to the technical field of ultrasonic nondestructive testing, and more specifically relates to a method for ultrasonically detecting tiny defects based on scattered wave interference theory.

Background Art

Powder high-temperature alloy is the preferred material for key hot-end components of advanced aero-engines. It is mainly used to manufacture high-temperature load-bearing rotating components at the hot end of engines, such as turbine disks, compressor disks, drum shafts, and turbine disk high-pressure baffles. Due to the particularity of powder metallurgy, defects such as inclusions, heat-induced pores, and original grain boundaries often exist in the organization of powder high-temperature alloy. With the development of powder metallurgy processing technology, the powder high-temperature alloys currently produced are very dense and have very low pore content. However, due to the particularity of the powder high-temperature alloy manufacturing process, the presence of non-metallic inclusions is inevitable. The powder disks used in the engine have very high requirements for internal micro-inclusions, and usually do not allow defects larger than 400μm. Some aero-engine manufacturing companies have requirements for inclusion sizes as high as 169μm. With the improvement of material requirements, the defect size that needs to be detected is getting smaller and smaller, and some powder high-temperature alloy materials even require the detection of 50μm inclusions. As for the currently known detection capabilities, the minimum detectable defect size is Ф0.4mm. When the defect size is less than 0.4mm, the defect echo amplitude will be very low, even lower than the noise amplitude. Therefore, it is impossible to obtain tiny defect information through the defect wave. When the defect size is less than 0.4mm, the defect has little effect on the bottom wave amplitude. Therefore, it is difficult to obtain tiny defect information through changes in the bottom wave amplitude.

Therefore, how to provide a method for ultrasonic detection of tiny defects based on scattered wave interference theory is an urgent problem that technicians in this field need to solve.

Summary of the invention

In view of this, the present invention provides a method for ultrasonic detection of tiny defects based on scattered wave interference theory, which extracts tiny defect information through advanced signal analysis technology, realizes rapid identification of tiny defects, and solves the problem of identifying tiny defects.

In order to achieve the above object, the present invention adopts the following technical solution:

A method for ultrasonic detection of tiny defects based on scattered wave interference theory comprises the following steps:

(1) The mechanism of identifying small defects by interference technology is obtained by using finite element simulation method;

(2) Acquisition of ultrasonic scanning signals and acquisition and identification of micro-defect feature information are realized based on the micro-defect interference mechanism obtained by simulation;

(3) Produce a micro-defect test block to verify the ability of the interferometry method to identify micro-defects;

(4) Optimize the process parameters for interferometry detection of tiny defects.

Preferably, in the step (1), during the finite element simulation process, a comparison between the transient stress diagram and the time domain waveform diagram obtained after the ultrasonic wave passes through a tiny defect and the transient stress diagram and the time domain waveform diagram without passing through the defect shows that, after the incident wave and the diffracted wave interfere with each other, a new interference wave train is generated at the tail of the incident wave. This interference wave train contains defect information and is used to identify tiny defects.

Preferably, in step (2), the completely acquired ultrasonic bottom wave train including the interference wave train is unfolded, the gate frame selects the newly generated interference wave train, and the entire scanning area is imaged using amplitude imaging and depth imaging methods, so that tiny defects can be identified in one scan.

Preferably, in step (3), the micro-defect test block is a cylindrical aviation aluminum alloy micro-defect test block with a thickness of 5 mm to 80 mm and an end face diameter of 10 to 80 mm.

Preferably, the material composition of the cylindrical aviation aluminum alloy micro-defect test block is silicon Si: 0.4%; iron Fe: 0.40%; copper Cu: 1.7%; manganese Mn: 0.30%; magnesium Mg: 3.0%; chromium Cr: 0.4%; zinc Zn: 4.8%; titanium Ti: 0.30%; aluminum Al: balance 88.7%.

Preferably, the bottom end surface of the cylindrical aviation aluminum alloy micro-defect test block contains four flat-bottom hole defects of Ф0.1mm, Ф0.2mm, Ф0.3mm, and Ф0.4mm, with a hole depth of 1.6mm and a burial depth of 5mm to 80mm.

Preferably, in step (4), the detection probe selected for the process parameters of interferometric detection of tiny defects is an ultrasonic water immersion focusing probe with a frequency of 5Mhz to 15Mhz, a chip size range of 12.7mm to 25.4mm in diameter, and a focal length of 15mm to 330mm in water.

Preferably, in step (4), the process parameters for detecting tiny defects by interference method are a scanning step of 0.2 mm and a scanning speed of 20 mm/s.

The beneficial effects of the present invention are:

The present invention conducts research on the characteristics of waves passing through tiny defects, and extracts tiny defect information through advanced signal analysis technology, thereby achieving rapid identification of tiny defects and solving the problem of identifying tiny defects.

The interference technology used in this method has the advantages of being fast and highly sensitive, that is, only one comprehensive scan is required to collect the bottom wave or penetration wave in the entire wave train, perform time and frequency analysis, and obtain the presence or absence of tiny defects and plane position information, thereby solving the problem of fast identification of defects, especially tiny defects.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

Figure 1 is a transient stress diagram of a 0.1 mm defect.

Figure 2 is a transient stress diagram of a 0.2 mm defect.

FIG3 is a transient stress diagram when there is no defect.

FIG4 is a time domain waveform diagram of a 0.1 mm defect.

FIG5 is a time domain waveform diagram of a 0.2 mm defect.

FIG. 6 is a time domain waveform diagram when there is no defect.

FIG. 7 is a top view of a test block with minute defects.

FIG8 is a side view of a test block with minor defects.

FIG9 is an interference wave train diagram.

FIG. 10 is a diagram showing the imaging result of interference wave train scanning.

FIG11 is a waveform diagram of the excitation signal.

FIG12( a ) is a cross-sectional view with the cross-sectional view 0.1 mm (y=39.9 mm) from the upper surface.

FIG12( b ) is a cross-sectional view where the cross-sectional view is 0.1 mm (y=0.1 mm) away from the lower surface.

Figure 12(c) is a cross-sectional view at a distance of 0.1 mm (y=12.5 mm) from the upper surface of the defect.

Figure 13(a) is the transient stress diagram of defect-free comparison specimen No. 4.

Figure 13(b) is the time domain waveform of defect-free comparison block No. 4.

Figure 14(a1) is the transient stress diagram of specimen No. 1 at the one-dimensional section y=39.9 mm.

FIG14( b1 ) is a time domain waveform diagram of test piece No. 1 at the one-dimensional section line y=39.9 mm.

Figure 14(a2) is the transient stress diagram of specimen No. 1 at the one-dimensional section y=0.1mm.

FIG14( b2 ) is a time domain waveform diagram of test piece No. 1 at the one-dimensional section line y=0.1 mm.

Figure 14(a3) is the transient stress diagram of specimen No. 1 at the one-dimensional section y=12.5mm.

FIG14( b3 ) is a time domain waveform diagram of test piece No. 1 at the one-dimensional section line y=12.5 mm.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

The present invention provides a method for ultrasonic detection of tiny defects based on scattered wave interference theory, comprising the following steps:

(1) The finite element simulation method is used to obtain the mechanism of interferometric technology to identify small defects. The specific method used is:

Simulation of incident and scattered waves at tiny defects to study interference

The propagation of ultrasonic waves in aluminum alloy thick plates was simulated using COMSOL Multiphysics software. A simple two-dimensional model of the workpiece was established. Tiny defects of different sizes were simulated in the model to study the laws and phenomena of ultrasonic waves propagating in defects. The physical field was set to solid mechanics, and the transient state of ultrasonic waves was studied. After geometric modeling of the simulation model, modules were assigned to each part with different material properties. In the material library, the entire test block was assigned to 7075 aluminum alloy material, and the preset tiny defects were assigned air properties. The parameter information of each material is shown in Table 1.

Table 1 Material parameter information

本发明实验激励源为5MHz，在铝合金中波长大概为1.26mm。选择的最大网格尺寸为1/10波长，即0.126mm。网格形状为三角形网格。对物理模型的初始条件和边界条件进行设定，加载后进行求解。先在铝合金厚板上侧施加一个5MHz的正弦波激励信号，激励声源被定义为线声源使晶片振动产生超声波作为激励源。超声波激励信号为式

The excitation source of the experiment of the present invention is 5MHz, and the wavelength in aluminum alloy is about 1.26mm. The maximum grid size selected is 1/10 wavelength, that is, 0.126mm. The grid shape is a triangular grid. The initial conditions and boundary conditions of the physical model are set, and the solution is performed after loading. First, a 5MHz sinusoidal wave excitation signal is applied to the upper side of the aluminum alloy thick plate. The excitation sound source is defined as a line sound source to make the chip vibrate to generate ultrasonic waves as the excitation source. The ultrasonic excitation signal is

The waveform of the excitation signal is shown in FIG11 .

The boundary of the physical simulation model (except the connection between the probe and the aluminum alloy thick plate) is set as a "low reflection boundary" to reduce the interference of other external factors on the results of the sound wave propagation law. In order to simulate the process of ultrasonic excitation of the ultrasonic probe, a linear segmentation operation is performed on the upper surface of the test block to cut out a line segment with a length of 5mm directly above the preset defect, and excitation is set at this line segment to simulate the probe emission excitation. Considering the running memory and storage size of the simulation model and the time for the sound wave to go back and forth in the workpiece is 40mm/6300m/s*2＝12.7μs, the solution time is set to 15μs.

In order to study the influence of defect size, burial depth, and defect type on ultrasonic testing, six groups of simulation experiments were conducted. The test blocks and defect information of each group of experiments are shown in Table 2.

Table 2 Defect information

serial number Defect Type Buried depth(mm) Defect size (mm) Test block size (mm) 1 Long strip pores 30 φ0.1*2 φ20*40 2 Long strip pores 30 φ0.2*2 φ20*40 3 Long strip pores 30 φ0.3*2 φ20*40 4 No defects φ20*40 5 Long strip pores 3 φ0.1*2 φ20*40 6 Flat bottom hole 38 φ0.1*2 φ20*40 7 Slag inclusion 30 φ0.1*0.1 φ20*40

In the process of processing the experimental results, the ultrasonic time domain signal waveform was solved at three different positions of the test block, and three one-dimensional cross-sections were set. The first one was 0.1 mm from the upper surface of the test block to simulate the receiving position of the ultrasonic reflection method. The second one was 0.1 mm from the bottom of the test block to simulate the receiving position of the ultrasonic transmission method. The third one was 0.5 mm from the upper end of the defect to observe the waveform changes of the ultrasonic reflection echo just passing through the micro-defect. The three one-dimensional cross-sections are shown in Figures 12(a), 12(b) and 12(c).

1) Take the transient stress change diagram of the defect-free comparison block No. 4 and the defect waveform diagram at y = 12.5 mm as reference, as shown in Figure 13 (a) and Figure 13 (b):

2) The transient stress diagram and time domain waveform diagram of test block No. 1 were solved at the one-dimensional sections y=39.9mm, y=0.1mm, and y=12.5m, and the results are shown in Figures 14(a1), 14(b1), 14(a2), 14(b2), 14(a3), and 14(b3), respectively.

According to the dynamic stress diagram and time domain waveform diagram in Figure 3, at the upper part of the defect at y=12.5mm, the four most obvious red and green strips represent the energy intensity, which corresponds to the four peaks and troughs of the time domain waveform diagram, and the strip closest to the upper end of the defect corresponds to the second peak of the time domain waveform. We refer to the wave train including this peak and its afterward as the coda wave. It can be clearly seen from the transient stress diagram that when passing through a small defect, the tail of the entire bottom wave is scattered at the upper end of the defect, generating a new scattered wave, and the energy intensity of the bottom wave coda wave also changes. This change is the interference of a bottom wave and a scattered wave on the surface of a small defect. The defect information can be obtained by studying the interference of this bottom wave and the scattered wave on the surface of a small defect.

During the finite element simulation process, the transient stress diagram and time domain waveform diagram obtained after the ultrasonic wave passes through a tiny defect are compared with the transient stress diagram and time domain waveform diagram without passing through the defect. It shows that a new interference wave train is generated after the incident wave and the diffraction wave interfere with each other. The interference wave train diagram is shown in Figure 9 and is located at the tail of the incident wave. This interference wave train contains defect information. This interference wave is located at the tail of the incident wave, resulting in a slight difference in amplitude and depth time between the interference wave train at the tail of the bottom wave that passes through a tiny defect and the normal bottom wave tail wave train without defects. For this slight difference in the interference wave at the tail of the bottom wave, imaging is performed using the ultrasonic C-scan imaging method to identify tiny defects.

During the finite element simulation process, the four red and green bars in the transient stress diagram represent the energy intensity of this area. The brighter the color (the closer the color is to red and green), the greater the energy intensity represented, and the larger the waveform amplitude on the corresponding time domain waveform diagram. The darkest color is the peak and trough. The darker the color (the closer the color is to dark blue), the lower the energy is, and the corresponding time domain waveform amplitude is very low, close to 0. The entire area contained in this peak and trough is a complete bottom wave. The primary bottom wave is the wave formed by the reflection of the incident wave (the wave that enters the interior of the test block after the initial excitation applied above the test block is called the incident wave) at the bottom of the test block for the first time. As can be seen from the stress diagram in Figure 14 (a3), the primary bottom wave propagates upward from the bottom surface. When it passes through the small defect (white thin strip) and is about to leave the small defect, a new wave is generated at the tail of the primary bottom wave. This is the diffraction phenomenon of the wave. The diffraction of the wave refers to the phenomenon that the wave changes its propagation direction when it encounters an obstacle or discontinuity in the medium. This phenomenon is very obvious when the size of the obstacle is very small. According to Huygens' principle, this wave is a diffraction wave generated by the tip of the small defect as the new wave source. This diffraction wave propagates around with the tip as the center of the circle. As shown in the stress diagram in Figure 14 (a3), the side lobes generated around the tip of the small defect are diffraction waves. In the corresponding time domain waveform diagram in Figure 14 (b3), the small wave generated at the tail of the bottom wave is the diffraction wave. According to Huygens' principle, the diffraction wave has two The first characteristic of the diffraction wave is that its vibration frequency is consistent with the original mother wave (the primary bottom wave in this paper), and the second is that it propagates in all directions. When a part of the diffracted wave propagates upward to the surface in the same direction as the primary bottom wave, the two basic conditions of interference are met. The interference will cause the two waves to superimpose, so that the vibration of certain areas is strengthened or weakened. Since there is a certain time difference between the primary incident wave and the diffracted wave when they propagate upward to the surface, the tail of the ultrasonic bottom wave and the diffracted wave interfere with each other and superimpose to form a new interference wave. The interference wave corresponds to the bottom one of the four red and green stripes in the stress diagram of Figure 13 (a3). It can be seen that the bottom red and green stripe is broken and a new short stripe is generated. The color is lighter than the bottom wave stripe, indicating that the energy is lower than the bottom wave. The new small fluctuation generated at the tail of the bottom wave seen in the time domain waveform diagram is this interference wave train. Therefore, this interference wave train must contain defect information and can be used to identify tiny defects. There are two methods to identify small defects using interference wave trains. The first is to check whether a new interference wave train is formed at the tail of the bottom wave. If a new interference wave train exists, it means that there is a small defect inside the test block, which is dominant. The second is to judge whether there is a defect inside the test block and the characteristics of the defect based on the influence of the interference effect of the diffraction wave and the bottom wave on the primary bottom wave. This influence can be divided into two aspects. The first is the change in the amplitude of the wave train at the tail of the bottom wave, and the second is the change in the time domain of the wave train at the tail of the bottom wave. This influence is invisible and requires software to analyze and process the data to obtain the result.

(2) Acquisition of ultrasonic scanning signals and acquisition and identification of micro-defect feature information are realized based on the micro-defect interference mechanism obtained by simulation;

Ultrasonic scanning complete signal acquisition adopts ultrasonic water immersion c scanning technology. According to the ultrasonic simulation process, the incident wave should enter the workpiece vertically from the upper end face of the workpiece, so the small defect test block is placed horizontally. The probe is located above the upper end face of the small defect test block, and the end face scanning method is adopted. The probe is selected as a water immersion focused longitudinal wave straight probe. Probe selection:

式中n是透镜与耦合介质波速比，

在实际检测过程中，实际焦距F'为：F'＝F-L(c₃/c₂-1)式中，L为工件中焦点至工件表面的距离，c₂是水的声速，c₃是试块材料介质声速，由于我们制作的小缺陷试块是平底孔试块，缺陷都在试块底部，所以公式中L就是试块的厚度，由于聚焦探头的特性，实际焦距F'要覆盖微小缺陷，即实际焦距要大于水层厚度加试块厚度，我们制作的小缺陷试块厚度范围是5mm～80mm，经过上述公式计算，探头焦距的选择范围在15mm～330mm。Selection of probe focal length, the relationship between the focal length F of the focusing probe and the curvature radius r of the acoustic lens is:

Where n is the wave velocity ratio between the lens and the coupling medium,

In the actual detection process, the actual focal length F' is: F'=FL(c ₃ /c ₂ -1) where L is the distance from the focus in the workpiece to the surface of the workpiece, c ₂ is the sound velocity of water, and c ₃ is the sound velocity of the test block material medium. Since the small defect test block we made is a flat-bottom hole test block, the defects are all at the bottom of the test block, so L in the formula is the thickness of the test block. Due to the characteristics of the focusing probe, the actual focal length F' must cover tiny defects, that is, the actual focal length must be greater than the water layer thickness plus the test block thickness. The thickness range of the small defect test block we made is 5mm~80mm. After calculation with the above formula, the selection range of the probe focal length is 15mm~330mm.

In step (2), pure water is used as a coupling agent to unfold the completely collected ultrasonic bottom wave train containing the interference wave train, and the gate frame selects the newly generated interference wave train, that is, the tail position of the bottom wave is framed, and the entire scanning area is imaged using the amplitude imaging method and the depth imaging method, so as to identify tiny defects in one scan. The acquisition and processing of ultrasonic signals adopts the ultrasonic C-scanning, a very mature non-destructive testing signal acquisition and imaging technology. The ultrasonic C-scanning technology is used to completely acquire the ultrasonic waveform data of the entire test block scanning area. The characteristic is that the ultrasonic C-scanning data acquisition is point acquisition, that is, the entire scanning area is replaced by a large number of acquisition points. As the probe moves, the ultrasonic data of each point is collected. Each point is evenly distributed and has the same interval. Each point contains the complete ultrasonic train information of the position, and the adjacent points are combined together to contain the complete ultrasonic information of the fixed area. The amplitude imaging method selects the interference wave train at the tail of the bottom wave of all the acquisition points in the entire scanning area. The system will automatically identify the highest amplitude point of the interference wave train selected in each acquisition point, and record this highest amplitude. The color depth is used instead of the amplitude size to form an image. The color with high amplitude is bright, and the color with low amplitude is dark. When the medium is uniform, the color depth of the area will be close to the same. When there are small defects, the amplitude of the interference wave train at the tail of the bottom wave will be different from other defect-free areas due to the interference effect, resulting in the color of the area being different from the normal area. The entire scanning area is imaged by the probe, and tiny defects can be scanned and identified at one time. The signal acquisition process of depth imaging is the same as that of amplitude imaging, but the signal processing method is slightly different. The term depth in depth imaging refers to the distance that the ultrasonic wave propagates when it propagates from the upper surface to the bottom surface, that is, the sound path. Since the sound velocity of ultrasonic waves in the same homogeneous medium is fixed, time can be used to characterize the sound. This is the principle of the time domain waveform diagram. The horizontal axis represents the propagation time and the vertical axis represents the energy intensity. Since the sound velocity of ultrasonic waves is fixed when they propagate in a homogeneous medium, when there are no tiny defects at all acquisition points, the energy at the specified depth, that is, at the specified propagation time point, should be consistent. When there are tiny defects, the interference effect on the wave train at the tail of the bottom wave causes the sound path of the wave to change, that is, there is a defect. There is a difference in ultrasonic depth information between the defective collection point and the defect-free collection point, so imaging can be performed based on the difference in depth information. The specific operation method is to intercept the band containing the interference tail wave of all collection points of the same time length, divide this band equally at a certain time interval, take the highest point of each equally divided small band and record it, and use the color depth to represent the maximum amplitude of this equally divided small band of all collection points. The interference effect of the diffraction wave of the tiny defect and the bottom wave makes the ultrasonic energy at a fixed depth position different from the ultrasonic energy at the same depth position of the defect-free test block (that is, there is a difference in the waveform amplitude at the same time node). The image with the color depth representing the amplitude will show the tiny defects inside the test block.

(3) Produce a micro-defect test block to verify the ability of the interferometry method to identify micro-defects;

(4) Optimize the process parameters for interferometry detection of tiny defects.

In another embodiment, the scanning equipment used in the actual detection process of the present invention is an ultrasonic water immersion C scanning system.

In another embodiment, in step (3), the micro-defect test block is a cylindrical aviation aluminum alloy micro-defect test block, see Figures 7-8, with a thickness of 5 mm to 80 mm and an end face diameter of 10 to 80 mm.

In another embodiment, the material composition of the cylindrical aviation aluminum alloy micro-defect test block is silicon Si: 0.4%; iron Fe: 0.40%; copper Cu: 1.7%; manganese Mn: 0.30%; magnesium Mg: 3.0%; chromium Cr: 0.4%; zinc Zn: 4.8%; titanium Ti: 0.30%; aluminum Al: balance 88.7%.

In another embodiment, the bottom end surface of the cylindrical aviation aluminum alloy micro-defect test block contains four flat-bottom hole defects of 0.1mm, 0.2mm, 0.3mm, and 0.4mm, with a hole depth of 1.6mm and a buried depth of 5mm to 80mm. The entire scanning area is imaged using the amplitude imaging method and the depth imaging method, and the four micro-defects of different sizes contained in the test block are scanned and identified at one time. The interference wave train scanning imaging result is shown in Figure 10.

The transient stress diagram obtained after the ultrasonic wave passes through a Ф0.1mm defect is shown in Figure 1, and the transient stress diagram without defects is shown in Figure 3; the time domain waveform diagram obtained after the ultrasonic wave passes through a Ф0.1mm defect is shown in Figure 4, and the time domain waveform diagram without defects is shown in Figure 6.

The transient stress diagram obtained after the ultrasonic wave passes through a Ф0.2mm defect is shown in Figure 2, and the transient stress diagram without defects is shown in Figure 3; the time domain waveform diagram obtained after the ultrasonic wave passes through a Ф0.2mm defect is shown in Figure 5, and the time domain waveform diagram without defects is shown in Figure 6.

In another embodiment, in step (4), the detection probe selected for the process parameters of the interference method for detecting tiny defects is an ultrasonic water immersion focusing probe with a frequency of 5Mhz to 15Mhz, a chip size range of 12.7mm to 25.4mm in diameter, and a focal length of 15mm to 330mm in water. The selection of probe frequency, the advantages of a high-frequency probe are small pulse width, high resolution, good sound beam directivity, concentrated energy, and strong ability to detect small defects, while the disadvantages are large attenuation, large near field area, and low signal-to-noise ratio. The advantages and disadvantages of a low-frequency probe are exactly opposite to those of a high-frequency probe. In the process of selecting a probe, for small defects and workpieces with small thickness, a higher frequency should be selected, and for thick workpieces and high-attenuation materials, a low-frequency probe should be selected. The selection of probe frequency in this method should also follow the above principles.

Selection of probe chip size: the larger the chip size, the smaller the half diffusion angle will be, the more concentrated the ultrasonic energy will be, and the greater the ultrasonic energy will be. The energy for discovering long-distance defects is conducive to defect detection. At the same time, the larger the chip size, the larger the near-field area, which is not conducive to close-range defect detection. Therefore, when using this method for detection, for the detection of high-attenuation thick workpieces, a large chip size should be selected, and for low-attenuation thin workpieces, a small chip size should be selected.

When the focusing probe is detecting the workpiece, the actual focal length F' will become smaller. Therefore, the actual focal length in the workpiece is calculated according to the following formula: F' = FL ( _c2 / _c3-1 ). In the formula, L is the distance from the focus of the workpiece to the surface of the workpiece, _c1 is the sound speed of water, and _c2 is the wave speed of the workpiece. In order to make the scanning distance cover the entire workpiece, the actual focal length of the probe is generally close to the thickness of the workpiece, so that the energy of the bottom wave is maximized and the interference effect is more obvious. In water immersion focusing detection, the water layer thickness (the distance between the probe and the upper surface of the workpiece) will also affect the detection effect. The water layer thickness calculation formula is H = F- _Lc2 / _c1 .

The flatness of the upper and lower surfaces of the workpiece has a great influence on the bottom wave, and this method uses the interference wave train at the tail of the bottom wave to form an image. In order to avoid the flatness of the workpiece affecting the interference wave train, the workpiece should be kept flat and level.

The specific implementation steps are as follows (taking the detection of 0.1mm flat bottom holes with a burial depth of 80mm as an example): Place the 80mm thick aluminum alloy small defect test block flatly in the water tank of the ultrasonic water immersion system, select and install the appropriate probe according to the material and thickness of the workpiece, the probe selected is 10Mhz frequency, 15 inches (381mm) focal length in water, and 0.75 inches (19.05mm) chip size. Add water to the water layer thickness calculated according to the water layer thickness formula (water layer thickness is 45mm), turn on the ultrasonic pulse transmitter and receiver, select the appropriate transmission voltage (400v) and excitation frequency (10Mhz), and adjust the transmission voltage according to the signal-to-noise ratio of the noise of the bottom wave interference tail wave height, try to make the bottom wave interference tail wave higher, and at the same time, do not make the noise too high. The automatic scanning step is set to 8 as the minimum 0.2mm, and the scanning speed is the minimum 30mm/s. In order to ensure that the scanning range covers the entire test block, the scanning range is set to 80mm*80mm. After the scan is completed, the amplitude imaging method and the depth imaging method are used to select the bottom wave and tail wave for imaging.

In another embodiment, in step (4), the process parameters selected for the interference method for detecting tiny defects are a scanning step of 0.2 mm and a scanning speed of 20 mm/s.

In another embodiment, the detection probe selected is an ultrasonic water immersion focusing probe with a frequency of 10Mhz, a chip size of 19.05mm in diameter, and a focal length of 304.8mm in water. The scanning step is set to 0.2mm and the scanning speed is 20mm/s.

The present invention conducts research on the characteristics of waves passing through tiny defects, and extracts tiny defect information through advanced signal analysis technology, thereby achieving rapid identification of tiny defects and solving the problem of identifying tiny defects.

The interference technology used in this method has the advantages of being fast and highly sensitive, that is, only one comprehensive scan is required to collect the bottom wave or penetration wave in the entire wave train, perform time and frequency analysis, and obtain the presence or absence of tiny defects and plane position information, thereby solving the problem of fast identification of defects, especially tiny defects.

The present invention can solve the problems of long detection cycle and high detection cost in the current powder disc detection, break through the bottleneck that restricts the development and production of powder disc models due to problems of detection capability and detection efficiency, and improve detection efficiency and shorten production cycle under the premise of providing sufficient detection accuracy; by comparing the detection capability with the traditional partition focusing detection technology, the superiority and reliability of the new generation of detection technology are verified, and the transformation of powder disc micro-inclusion defect detection from traditional methods to new detection technologies is further accelerated, thereby improving the overall detection level of aircraft engines; through process and method research, a practical solution is provided for the rapid detection of powder discs, and process specifications that can be used for actual powder disc detection are established to meet the detection requirements of aircraft engines for quality control.

In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims (6)

1. A scattered wave interference theory-based micro defect ultrasonic detection method is characterized by comprising the following steps:

(1) Utilizing a finite element simulation method to obtain an interference technology to identify a tiny defect mechanism;

in the step (1), in the finite element simulation process, comparison between a transient stress image and a time domain waveform image obtained after ultrasonic waves pass through a micro defect and a transient stress image and a time domain waveform image which do not pass through the defect shows that a new interference wave train is generated after the interference action of incident waves and diffraction waves, and the new interference wave train is positioned at the tail part of the incident waves and contains defect information for identifying the micro defect;

(2) Obtaining ultrasonic scanning signals and obtaining and identifying the characteristic information of the micro defects according to the micro defect interference mechanism obtained by simulation;

in the step (2), the fully acquired ultrasonic bottom wave array containing the interference wave array is unfolded, a gate frame is used for selecting the newly generated interference wave array, and an amplitude imaging method and a depth imaging method are used for imaging the whole scanning area, so that the micro defects are identified through one-time scanning;

(3) Manufacturing a micro defect test block for verifying the capability of identifying micro defects by an interferometry;

(4) The process parameters for interferometry detection of small defects are optimized.

2. The ultrasonic detection method of the micro defects based on the scattered wave interference theory of claim 1, wherein in the step (3), the micro defect test block is a cylindrical aviation aluminum alloy micro defect test block, the thickness is 5 mm-80 mm, and the end face diameter is 10-80 mm.

3. The ultrasonic detection method of the micro defects based on the scattered wave interference theory according to claim 2, wherein the material composition of the cylindrical aviation aluminum alloy micro defect test block is as follows: 0.4%; 0.40% of Fe; copper Cu:1.7%; manganese Mn:0.30%; magnesium Mg:3.0%; chromium Cr:0.4%; zinc Zn:4.8%; titanium Ti:0.30%; aluminum Al: the balance 88.7%.

4. The ultrasonic detection method for the micro defects based on the scattered wave interference theory is characterized in that the bottom end face of the cylindrical aviation aluminum alloy micro defect test block comprises 4 flat-bottom hole defects with the diameter of phi 0.1mm, the diameter of phi 0.2mm, the diameter of phi 0.3mm and the diameter of phi 0.4mm, the hole depth is 1.6mm, and the burial depth is 5 mm-80 mm.

5. The ultrasonic detection method of the micro defects based on the scattered wave interference theory of claim 1, wherein in the step (4), the detection probes selected as the process parameters for detecting the micro defects by an interference method are ultrasonic water immersion focusing probes with the frequency of 5-15 Mhz, the wafer size range of 12.7-25.4 mm in diameter and the in-water focal distance of 15-330 mm.

6. The ultrasonic detection method of the micro defects based on the scattered wave interference theory of claim 5, wherein in the step (4), the scanning step adopted by the process parameters for detecting the micro defects by an interference method is 0.2mm, and the scanning speed is 20mm/s.

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