Quantitative detection method for micro defects using low-frequency ultrasonic multi-resolution scanning imaging

Abstract

A quantitative detection method for micro defects using low-frequency ultrasonic multi-resolution scanning imaging, comprising: decomposing a collected encoded ultrasonic A-scan signal by means of split-spectrum analysis into sub-signals with different center frequencies fi, performing amplitude imaging on the sub-signals of the same center frequency fi, identifying defect sizes di measured at half-maximum amplitude in images, and performing linear fitting on the defect sizes di and the center frequencies fi on the basis of a directivity function of an acoustic field, wherein the defect size di corresponding to a fit line slope k=-0.01 is a quantitative defect size. The detection effect no less than three times that of high-frequency ultrasound can be realized by using low-frequency ultrasound.

Description

Quantitative detection method of tiny defects using low-frequency ultrasonic multi-resolution scanning imaging Technical Field

[0001] The invention relates to a method for quantitatively detecting tiny defects using low-frequency ultrasonic multi-resolution scanning imaging, and belongs to the technical field of ultrasonic non-destructive testing. Background Art

[0002] The manufacturing process of high-performance components is influenced by a combination of factors, including material properties, process parameters, and the surrounding environment. Microscopic defects such as pores, cracks, and lack of fusion often form within the components. These defects create significant stress concentrations around them, weakening the component's tensile strength, impact resistance, and fatigue resistance. Therefore, quantitative nondestructive testing of microscopic defects is crucial to ensuring key component performance indicators.

[0003] Ultrasonic testing has the advantages of automated scanning, real-time imaging, simple equipment, and harmlessness to the human body, and has been widely used in various fields. For example, Chabot et al. in France used phased array ultrasonic technology to conduct testing research on aluminum alloy specimens manufactured by laser molten deposition. This technology can detect artificial prefabricated pore-type defects with a diameter of Φ0.6 to 1.0 mm. However, due to the limitations of the low frequency (10 MHz) and large aperture (38.4 mm) of the phased array probe, it is difficult to accurately quantify defects below Φ0.6 mm. Zhang Chi et al. used a water-immersion point focusing probe with a center frequency of 20 MHz and a focal column diameter of 0.44 mm to perform ultrasonic C-scan testing on titanium alloy defects. The results showed that the detection rate of defects smaller than 0.40 mm was low and the quantitative error was large. The study pointed out that when the defect size is smaller than the focal column diameter, the reflected echo energy is significantly reduced, seriously affecting the detection and size quantification accuracy of the defect. Traditional phased array ultrasonic testing (Phased Array Ultrasonic Testing) and ultrasonic C-scan testing (Ultrasonic C-scan Testing) can improve the lateral resolution of scanning imaging to a certain extent by increasing the probe aperture, increasing the probe frequency, and reducing the focal length. This improves the detection capability and quantification accuracy of small defects. However, it is still impossible to quantify small defects smaller than the resolution. At the same time, it also introduces new problems such as reduced signal-to-noise ratio, insufficient detection depth, and difficulty in quantifying defects far from the focal point.

[0004] Summary of the Invention

[0005] To address the problems existing in the prior art, the present invention provides a low-frequency ultrasonic multi-resolution scanning imaging quantitative detection method for tiny defects. This method addresses the conflicting issues of lateral resolution and detection depth in conventional ultrasonic C-scan imaging. It overcomes the limitations of phased array ultrasonic imaging, which hinder quantification of defects hundreds of microns in size due to the low probe frequency and large aperture size. Furthermore, it overcomes the relatively expensive, complex, limited detection depth, and engineering-related challenges of equipment such as ultrasonic microscopes. This method boasts a wider range of applicability, is simple to implement in engineering, and can be applied to all ultrasonic scanning imaging detection technologies, offering significant economic and social benefits.

[0006] The technical solution adopted by the present invention to solve the technical problem is: a quantitative detection method for small defects using low-frequency ultrasonic multi-resolution scanning imaging, which includes the following steps:

[0007] (1) Calibrate the ultrasonic detector, low-frequency ultrasonic probe, and step encoder, perform coded scanning on the object to be inspected, and collect M groups of position-coded ultrasonic A-type echo signals x(t);

[0008] (2) Perform fast Fourier transform on the collected signal x(t) to obtain its amplitude spectrum A(f), and identify the effective frequency band corresponding to half the amplitude of A(f) [f l ,f u ], the effective frequency band is divided into N center frequencies f i The filter band, i is a natural number from 1 to N;

[0009] (3) Using split spectrum analysis with the center frequency f i Bandpass filter the signal x(t) and decompose it into N signals with different center frequencies f i sub-signal y i (t), filter bandwidth b i According to the sub-signal energy E i The total energy E of the sum signal x(t) satisfies 10log(E / E i )<The conditions of signal-to-noise ratio are determined;

[0010] (4) Set the center frequency of the M coding positions to be the same as f i sub-signal y i (t) Perform amplitude imaging to obtain N multi-resolution scanning images Im with different frequency characteristics i ;

[0011] (5) Scan the image Im for each resolution i Identify the defect size d measured at half the amplitude in sequence i , and draw N ultrasound scan images Im i Detected defect size d i Follow f i Change curve;

[0012] (6) Derivation of the directivity function D of the ultrasonic probe based on the acoustic reciprocity principle c , directivity function D c The numerical simulation method is used to determine the formula (1):

[0013] Where: D is the probe size, unit is mm, λ is the wavelength of the sound wave in the material, unit is mm, θ is the sound wave diffusion angle, unit is radian;

[0014] (7) When the speed of sound of the object being tested is v and the depth of the object being tested is A, determine D c The beam width corresponding to half of the maximum amplitude is the ultrasonic scanning image Im of each resolution i Detected defect size d i , according to λf=v, the defect size d is obtained i With the center frequency f i Quantitative relationship:

[0015] (9) Substitute the known ultrasonic probe size D and the component sound velocity v into formula (2), and calculate the defect size d detected in step (5) i Follow f i Perform linear fitting based on the changing pattern to determine the unknown parameter A in formula (2);

[0016] (9) Determine the resolution frequency f corresponding to the slope k = -0.01 based on the fitting curve k , if the bandwidth [f k ,f u ]The updated split spectrum analysis sub-signal energy E i Meet 10lg(E / E i )<SNR condition, by resolving frequency f k Determine the new bandwidth b, draw a new scan image Im and regain the quantitative size d of the defect k ;

[0017] If the resolution frequency f k Not in the effective frequency band or 101g(E / E i )<The condition of signal-to-noise ratio is not met, the fitting curve is extrapolated to the frequency f and the derivative is obtained, and the detection defect size d corresponding to the slope k=-0.01 k It is the quantitative size of the defect.

[0018] The present invention provides a method for quantitatively detecting tiny defects using low-frequency ultrasonic multi-resolution scanning imaging. This method utilizes only a conventional low-frequency ultrasonic probe for coded scanning detection, combined with split-spectrum analysis to generate multi-resolution scanned images. The defect size within each resolution scanned image is then detected. Based on the ultrasonic probe's directivity function, the sizes of all detected defects can be accurately quantified. This method simultaneously improves the signal-to-noise ratio, detection depth, and lateral resolution of tiny defects, achieving a quantitative detection effect three times that of high-frequency ultrasound using low-frequency ultrasound. This method overcomes the limitations of the "-6dB method," which requires a probe resolution smaller than the defect size, and the "equivalent method," which requires a large number of comparison test blocks. It also overcomes the limitations of high-frequency focused probes, such as high attenuation, low signal-to-noise ratio, and insufficient detection depth. Furthermore, it is not limited by the size and shape of the ultrasonic probe or the scanning imaging method, and possesses strong engineering applicability. This approach overcomes the difficulty of balancing resolution and detection depth in traditional ultrasonic C-scan imaging testing, as well as the limitations of phased array ultrasonic imaging testing, which suffer from the difficulty of quantifying defects hundreds of microns due to the low probe frequency and large aperture size. It also addresses the relatively expensive, complex, limited detection depth, and engineering challenges of ultrasonic microscopes. This approach offers a wider range of applications, is simple to implement in engineering, and can be extended to all ultrasonic scanning imaging testing technologies, bringing significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] FIG1 is a schematic diagram of an ultrasonic C-scan detection system.

[0020] FIG2 is a position-coded ultrasonic A-type echo signal x(t) collected by the ultrasonic detection system.

[0021] FIG3 is the amplitude spectrum A(f) of the ultrasonic A-type echo signal x(t).

[0022] Figure 4 is a multi-resolution low-frequency ultrasound scanning imaging image Im i :(a) Center frequency is f1;(b) Center frequency is f2;(c) Center frequency is f 12 ; (d) The center frequency is f 13 .

[0023] Figure 5 shows the detection size d of a nominal Φ200μm defect i Follow f i Change curve.

[0024] Figure 6 shows the multi-resolution low-frequency ultrasonic C-scan imaging detection results of different defects: (a) Φ800μm defect; (b) Φ200μm defect.

[0025] Figure 7 shows the defect size d of a Φ300μm defect detected by multi-resolution ultrasonic C-scan imaging. i Follow f i Change curve.

[0026] Figure 1: 1. 3D printed nickel-based high-temperature alloy specimen, 2. Low-frequency ultrasonic probe, 3. XYZ three-dimensional stepping encoder, 4. Ultrasonic detector, 5. Computer with signal processing software. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0028] FIG1 is a schematic diagram of an ultrasonic C-scan detection system, which includes a 3D printed nickel-based high-temperature alloy sample 1, an ultrasonic detector 4, a low-frequency ultrasonic probe 2, an XYZ three-dimensional stepping encoder 3, and a computer 5 with signal processing software. The detection method adopts the following detection steps:

[0029] (1) Calibrate the ultrasonic detector, low-frequency ultrasonic probe, and step encoder, perform coded scanning on the object to be inspected, and collect M groups of position-coded ultrasonic A-type echo signals x(t);

[0030] (2) Perform fast Fourier transform on the collected signal x(t) to obtain its amplitude spectrum A(f), and identify the effective frequency band corresponding to half the amplitude of A(f) [f l ,f u ], the effective frequency band is divided into N center frequencies f i The filter band, i is a natural number from 1 to N;

[0031] (3) Using split spectrum analysis with the center frequency f i Bandpass filter the signal x(t) and decompose it into N signals with different center frequencies f i sub-signal y i (t), filter bandwidth b i According to the sub-signal energy E i The total energy E of the sum signal x(t) satisfies 10log(E / E i )<The conditions of signal-to-noise ratio are determined;

[0032] (4) Set the center frequency of the M coding positions to the same value f i sub-signal y i (t) Perform amplitude imaging to obtain N multi-resolution scanning images Im with different frequency characteristics i ;

[0033] (5) Scan the image Im for each resolution i Identify the defect size d measured at half the amplitude in sequencei , and draw N ultrasound scan images Im i Detected defect size d i Follow f i Change curve;

[0034] (6) Derivation of the directivity function D of the ultrasonic probe based on the acoustic reciprocity principle c , directivity function D c It can also be measured by numerical simulation, such as formula (1), where D is the probe size, unit is mm, λ is the wavelength of the sound wave in the material, unit is mm, and θ is the sound wave diffusion angle, unit is radian; D c =function(D,λ,θ) (1)

[0035] (7) When the speed of sound of the object being tested is v and the depth of the object being tested is A, determine D c The beam width corresponding to half of the maximum amplitude is the ultrasonic scanning image Im of each resolution i Detected defect size d i , according to λf=v, the defect size d is derived i With the center frequency f i Quantitative relationship of d i =function(D,f i ,v,A) (2)

[0036] (10) Substitute the known ultrasonic probe size D and the component sound velocity v into formula (2), and calculate the defect size d detected in step (5) i Follow f i Perform linear fitting based on the changing pattern to determine the unknown parameter A in formula (2);

[0037] (9) Determine the resolution frequency f corresponding to the slope k = -0.01 based on the fitting curve k , if the bandwidth [f k ,f u ]The updated split spectrum analysis sub-signal energy E i Meet 10lg(E / E i )<SNR condition, by resolving frequency f k Determine the new bandwidth b, draw a new scan image Im and regain the quantitative size d of the defect k ;

[0038] (10) If the resolution frequency f is determined k Not in the effective frequency band or 101g(E / E i )<The condition of signal-to-noise ratio is not met, the fitting curve is extrapolated to the frequency f and the derivative is obtained, and the detection defect size d corresponding to the slope k=-0.01k It is the quantitative size of the defect.

[0039] Example 1

[0040] The ultrasonic C-scan detection system used in this embodiment includes a 3D-printed nickel-based superalloy specimen 1, a low-frequency ultrasonic probe 2 (a water-immersion point-focused probe with a nominal frequency of 20 MHz), an XYZ three-dimensional stepping encoder 3, an ultrasonic detector 4, and a computer 5 with signal processing software, as shown in FIG1 . The 3D-printed nickel-based superalloy specimen is a specimen containing pore-type defects with nominal diameters of Φ100 μm, Φ200 μm, Φ300 μm, Φ400 μm, Φ500 μm, Φ600 μm, Φ700 μm, and Φ800 μm. The detection steps used are as follows:

[0041] (1) The ultrasonic detector, the water-immersion point-focused probe with a nominal frequency of 20 MHz, and the XYZ three-dimensional stepping encoder were calibrated to perform encoding scanning on the 3D-printed nickel-based high-temperature alloy sample to be inspected. The ultrasonic detection system was used to collect 86 × 86 sets of position-encoded ultrasonic A-type echo signals x(t), as shown in Figure 2.

[0042] (2) Perform fast Fourier transform on the signal x(t) collected in step (1) to obtain its amplitude spectrum A(f), as shown in Figure 3. The center frequency of the water immersion point focusing probe is determined to be 19.5 MHz. The effective frequency band corresponding to half the amplitude of A(f) [8.2 MHz, 33.6 MHz] is identified and divided into 13 center frequencies f i =[9MHz, 11MHz, …, 31MHz, 33MHz] filter band, i is a natural number from 1 to 13.

[0043] (3) Using split spectrum analysis with the center frequency f i Bandpass filter the x(t) signal to obtain 13 signals with different center frequencies f i sub-signal y i (t), filter bandwidth b i According to the sub-signal energy E i The total energy of the sum signal x(t) (E = 2.52 mJ) satisfies 10log (E / E i ) < SNR (9.89dB). For example, when center frequency f2 = 11MHz, b2 = 4.1MHz; when center frequency f7 = 21MHz, b7 = 2.1MHz.

[0044] (4) The center frequency of 86×86 coding positions is the same as f i sub-signal y i (t) Perform amplitude imaging to obtain 13 scanning images Im with different frequency characteristics and multiple resolutions i , see Figure 4.

[0045] (5) Scan the image Im for each resolution i Identify the defect size d measured at half the amplitude in sequence i , and draw 13 ultrasound scan images Im i Detected defect size d i Follow f i The change curve of the Φ200μm defect is shown in Figure 5.

[0046] (6) Analyze the directivity function D of the point-focused probe based on the principle of acoustic reciprocity c , as shown in formula (1), where D is the probe size, unit is mm, λ is the wavelength of the sound wave in the object under test, unit is mm, and θ is the sound wave diffusion angle, unit is radian;

[0047] (7) When the speed of sound of the object being tested is v and the depth of the object being tested is A, determine D c The beam width corresponding to half of the maximum amplitude is the ultrasonic scanning image Im of each resolution i Detected defect size d i , according to λf=v, the defect size d is derived i With the center frequency f i The quantitative formula (2);

[0048] (8) Substitute the known ultrasonic probe size D = 6 mm and the sound velocity v = 5720 m / s of the object under test into formulas (2) and (3), and calculate the defect size d detected in step (5). i Follow f i The changing curve is fitted, and the fitting curve of the Φ200μm defect is shown in Figure 5. The unknown parameter in formula (2) is A=53.41mm.

[0049] (9) Determine the resolution frequency f corresponding to k = -0.01 based on the fitting curve k =27.2MHz. Take [27.2MHz, 33.6MHz] as the new split spectrum analysis bandwidth b, and the energy of the column spectrum analysis sub-signal within the bandwidth E i 0.31mJ satisfies 10lg(E / E i ) <9.89dB, and ultrasonic C-scan images with a new resolution were obtained to quantify the defect size. The results are shown in Figure 6. The quantitative result of the Φ800μm defect size is 832μm, and the quantitative result of the Φ200μm defect size is 212μm.

[0050] (10) The actual diameter of each defect was quantified using a laser confocal microscope, resulting in sizes of 196 μm and 774 μm for the Φ200 μm and Φ800 μm defects, respectively. The relative error between the detected size and the actual size of the Φ200 μm defect was 8.1%. The relative error between the detected size and the actual size of the Φ800 μm defect was 7.5%. This demonstrates that multi-resolution low-frequency ultrasonic C-scan imaging technology can accurately quantify the sizes of all detected defects.

[0051] Application Extensions

[0052] (11) A low-frequency ultrasonic probe 2 (a water-immersion point-focused probe with a nominal frequency of 15 MHz) was used to detect a Φ300 μm defect, and the defect size d was plotted using multi-resolution low-frequency ultrasonic C-scan imaging. i Follow f i The change curve is shown in Figure 7. Based on the fitting curve, the corresponding resolution frequency f when k = -0.01 is determined k =31.5MHz. Resolution frequency f k If it is not in the effective frequency band, then f k The corresponding extrapolated defect size d k =314μm, the actual diameter of the Φ300μm defect measured using a laser confocal microscope is Φ287μm, and the relative error of defect quantification is less than 9.5%.

Claims

1. A quantitative detection method for multi-resolution scanning imaging of micro-defects by low-frequency ultrasound, characterized in that, The method comprises the following steps: (1) Calibrate an ultrasonic detector, a low-frequency ultrasonic probe, and a stepping encoder, perform coded scanning on the object to be inspected, and collect M groups of ultrasonic A-mode echo signals x(t) with position codes; (2) Perform a fast Fourier transform on the acquired signal x(t) to obtain its amplitude spectrum A(f), and identify the effective frequency band [f l , f u corresponding to half of the amplitude height of A(f). Divide the effective frequency band equally into N filtering bands with center frequencies f i , where i is a natural number from 1 to N; (3) Split-spectrum analysis is adopted with the center frequency f i Band-pass filtering is performed on the signal x(t) and decomposed into N sub-signals y i with different center frequencies f i (t), and the filtering bandwidth b i is determined according to the condition that the energy E i of the sub-signal and the total energy E of the signal x(t) satisfy 10lg(E / E i ) < signal-to-noise ratio; (4) Center the frequencies of the M coded positions at f i of the sub-signal y i (t) for amplitude imaging to obtain N scanned images Im i with different frequency characteristics and multi-resolution; (5) For each resolution scanned image Im i Successively identify the defect size d measured at half the amplitude i , and plot N ultrasonic scanned images Im i The detected defect size d i versus f i variation curve; (6)Derive the directivity function D of the ultrasonic probe according to the acoustic reciprocity principle c , the directivity function D c is measured by numerical simulation and is given by formula (1): where: D is the probe size in mm, λ is the wavelength of the sound wave in the material in mm, and θ is the sound wave diffusion angle in radians; At the position with the sound velocity v of the object to be inspected and the inspected depth A, determine D c The beam width corresponding to half of the maximum amplitude is the ultrasonic scanning image Im with each resolution i The defect size d to be detected i , according to λf = v, obtain the defect size d to be detected i And the center frequency f i Quantitative relationship of (8) Substitute the known ultrasonic probe size D and the sound velocity v of the component into formula (2), and for the defect size d detected in step (5) i varying with f i perform a linear fitting on the variation law to determine the unknown parameter A in formula (2); (9) Determine the resolution frequency f corresponding to the slope k = -0.01 based on the fitting curve k , if the bandwidth [f k ,f u ] The updated split spectrum analysis sub-signal energy E i Meet 10lg(E / E i )<SNR condition, by resolving frequency f k Determine the new bandwidth b, draw a new scan image Im and regain the quantitative size d of the defect k ; If the resolution frequency f k is not within the effective frequency band or the condition of 10lg(E / E i ) < signal-to-noise ratio is not satisfied, extrapolate the fitting curve with respect to the frequency f and take the derivative. The detection defect size d corresponding to the slope k = -0.01 k is the quantitative size of the defect.

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