A CFRP defect detection method and system based on bidirectional scanning line laser thermal imaging

Abstract

The application discloses a CFRP defect detection method and system based on bidirectional scanning line laser thermal imaging, uses a line laser to perform bidirectional scanning on a material surface, collects temperature distribution of the material surface in a scanning process, and obtains an infrared image sequence; in the collected infrared image sequence, a local area at a rear side of a laser spot is selected as a cutting window, the cutting window is combined according to a spatial corresponding position to obtain a composite image of one-way scanning, a reference window is selected from the composite image, the composite image is corrected according to the spatial distribution of the line laser power density in the reference window, and a defect image of single scanning is obtained; and the defect images obtained by the forward and reverse scanning are superimposed to obtain an infrared image containing internal defect information of the material. The laser background noise interference is effectively reduced, the positioning of the defects is more accurate, and the image quality is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of infrared thermal imaging nondestructive testing, and particularly relates to a CFRP (Carbon fibre reinforced polymer) defect detection method and system based on bidirectional scanning line laser thermal imaging. BACKGROUND

[0002] Carbon fibre reinforced polymer (CFRP) is a structural material with carbon fiber as reinforcing material and resin, ceramic, metal, etc. as matrix material. Resin-based carbon fiber composite material is one of the most commonly used composite materials, and its share in the carbon fiber composite material consumer market is as high as 80%. In recent years, CFRP has been widely used in high-tech fields and engineering structures due to its excellent physical and mechanical properties such as small density, high strength, corrosion resistance, and fatigue resistance. However, during production and use, CFRP often produces defects such as delamination, delamination, cracks, bubbles, inclusions, erosion, improper curing, core deformation, matrix cracking, etc. In addition, surface scratches, surface cracks, impact damage, water ingress, penetration, core crushing, etc. may also occur during use. Their occurrence and existence not only reduce the physical and mechanical properties of the material, but also further reduce the integrity and load-bearing capacity of the structure.

[0003] Laser thermal imaging is a leading nondestructive testing method for CFRP material defects. Among them, line laser thermal imaging uses line laser as excitation source to locally heat the irradiated area of the material surface for a short time, and then collects the temperature distribution of the overall surface of the material through an infrared thermal imager and performs corresponding data processing, so as to analyze the internal defect information of the material. Compared with traditional infrared thermal imaging technology, using laser as excitation source has the advantages of high energy concentration, high thermal density, accurate directionality, and controllable heating pattern shape, etc., and can detect surface cracks and subsurface matrix cracking and interlaminar cracks in materials, such as a metal micro-crack three-dimensional characterization system and method based on reflective laser thermal imaging, and another automatic calculation method for CFRP infrared thermal imaging delamination defect area. However, due to the uneven power density distribution of laser, the background noise caused by itself often covers the defect information of the material. How to effectively overcome the interference of laser background noise and extract high-quality CFRP internal defect information image is of great significance to the application of line laser thermal imaging technology in the field of composite materials such as CFRP. SUMMARY

[0004] The technical problems to be solved by the present application are to provide a CFRP defect detection method and system based on bidirectional scanning line laser thermal imaging, to solve the technical problems of strong laser background noise in line laser scanning infrared images and difficult defect image reconstruction, and to better detect internal defect information of CFRP.

[0005] The present application adopts the following technical solutions:

[0006] A CFRP defect detection method based on bidirectional scanning line laser thermal imaging, comprising the following steps:

[0007] S1, using a line laser to perform bidirectional scanning on the surface of the material, collecting the temperature distribution of the material surface during the scanning process, and obtaining an infrared image sequence;

[0008] S2, in the infrared image sequence collected in step S1, selecting a local area behind the laser spot as a cutting window, and combining the cutting window according to the spatial corresponding position to obtain a synthesized image of one-way scanning;

[0009] S3, selecting a reference window from the synthesized image obtained in step S2, and correcting the synthesized image according to the spatial distribution of the line laser power density in the reference window to obtain a defect image of single scanning;

[0010] S4, superimposing the defect images obtained by scanning forward and backward in step S3 to obtain an infrared image containing internal defect information of the material.

[0011] Specifically, in step S1, the temperature information of the scanning area is extracted to obtain a forward scanning infrared image sequence f index (x, y, n), which represents the temperature of a pixel point with pixel coordinates (x, y) in the nth image; (x, y) is the pixel coordinates in the X direction and the Y direction, x∈(0, L-1), y∈(0, W-1), n is the image number, and the value range is 0~(N-1);

[0012] The pixel with the highest temperature in the image is regarded as the center of the line laser spot, and the spot center coordinates of the nth image are denoted as (c x , c y ) n ;

[0013] The material surface is heated by reverse scanning to obtain a reverse scanning infrared image sequence f′ index (x, y, n).

[0014] Further, the image size L×W of the scanning area and the image number N satisfy the following conditions:

[0015]

[0016]

[0017] Specifically, step S2 is as follows:

[0018] Determine the size of the capture window as L cut ×W, L cut W represents the number of pixels along the X-axis of the window, and W represents the number of pixels along the Y-axis.

[0019] Select the i-th frame image f index Using (x, y, n = i) as a reference image, the temperature distribution curve f along the centerline of the specimen in the X direction is plotted. index (x, y = W / 2, n = i), the initial surface temperature of the material is denoted as T0; the distance between the termination position of the cropping window and the center of the light spot is denoted as the offset distance d, and the termination pixel coordinates x of the cropping window in the X direction of the nth frame image are calculated based on the offset distance d and the cropping window size. n According to 0≤x n -5+1<x n The range of values ​​for n is determined by ≤L-1 and 0≤n≤N-1;

[0020] Take a blank image with a pixel size of L×N, and fill the blank image with the values ​​stored in the cropping window according to the pixel coordinates to obtain the composite image A. pos The infrared sequence obtained by scanning in reverse along the X-axis is truncated and synthesized to obtain the synthesized image A during the reverse scan. neg .

[0021] Furthermore, the number of pixels L along the X-axis of the window cut for:

[0022]

[0023] Here, round indicates rounding the calculation result up.

[0024] Furthermore, the offset distance d is:

[0025] d = x tmax -x i

[0026] Where, x tmax x is the x-coordinate of the pixel with the highest temperature in the image. i The x-coordinate of the terminal pixel of the cropping window in the X direction of the i-th frame image.

[0027] Specifically, step S3 is as follows:

[0028] Based on the synthesized image A negThe non-defect area of the image surface is preliminarily judged, if the intercepted window of the kth image covers the non-defect area, the corresponding window is used as the reference window K;

[0029] The temperature difference distribution of the non-defect area is obtained by selecting a Gaussian surface to fit the image, and the pixel coordinates (x, y) in the reference window K are brought into the Gaussian surface expression g(x, y) to obtain a correction matrix I, the matrix size is L cut x W, the values stored in the correction matrix I are the distribution of the surface temperature change of the normal area under the laser heating, the intercepted window obtained in step S2 is subtracted from the correction matrix in sequence, and the remaining values are the surface temperature changes caused by the defects, a blank image with LxN pixels is taken, the values stored in the corrected intercepted window are filled into the blank image according to the pixel coordinates, and then normalized to obtain the infrared image M of the defect in the forward scanning pos , the infrared image M of the defect in the reverse laser scanning is calculated neg .

[0030] Further, the correction matrix I is:

[0031]

[0032] Wherein, x k is the terminal pixel horizontal coordinate of the intercepted window of the kth image in the X direction, g is the Gaussian surface expression, L cut is the number of pixels of the window along the X axis, and W is the number of pixels along the Y axis.

[0033] Further, the intercepted window t index (x, y, n) of the n th image before correction is represented as:

[0034]

[0035] The intercepted window Q index (x, y, n) of the n th image after correction is: index (x, y, n) = t n (x, y, n) - I; x n is the terminal pixel coordinate of the intercepted window of the n th image in the X direction, and W is the number of pixels along the Y axis.

[0036] In a second aspect, the embodiments of the present application provide a CFRP defect detection system based on bidirectional scanning line laser thermal imaging, comprising:

[0037] A scanning module uses a line laser to perform bidirectional scanning on the surface of the material, collects the temperature distribution of the surface of the material in the scanning process, and obtains an infrared image sequence;

[0038] The combination module selects a local area behind the laser spot in the infrared image sequence collected by the scanning module as a cutting window, and combines the cutting window to obtain a synthetic image of one-way scanning according to a corresponding position in space;

[0039] The correction module selects a reference window from the synthetic image obtained by the combination module, and corrects the synthetic image according to the spatial distribution of the linear laser power density in the reference window to obtain a defect image of single scanning.

[0040] The detection module superimposes the defect images obtained by the correction module through forward and reverse scanning to obtain an infrared image containing internal defect information of the material.

[0041] Compared with the prior art, the present application has at least the following beneficial effects:

[0042] A CFRP defect detection method based on bidirectional scanning line laser thermal imaging, which selects a rear area of laser scanning as a cutting window, the surface of the specimen in this area enters a cooling state, the temperature difference between the defect and the normal area is large, and the quality of the obtained synthetic defect image is good; the area directly irradiated by the laser with large temperature change is avoided, and the influence of large differences in laser power density distribution on the detection effect is reduced, thereby effectively reducing the interference of laser background noise; in addition, a correction matrix is obtained by fitting the temperature distribution of the normal area of the material surface using a Gaussian surface, and the temperature change of the material surface caused only by the defect is extracted using the correction matrix; finally, the infrared images obtained through forward and reverse scanning are superimposed, so that the positioning of the defect is more accurate, and the image quality is improved.

[0043] Further, the infrared image sequence is numbered to facilitate correct splicing of the cutting window. Scanning and heating in two directions of the material surface can effectively reduce the shape error caused by one-way heat transfer during one-way scanning.

[0044] Further, according to the position of the laser spot, only the area of the material that is heated by laser scanning is selected, the redundant part in the infrared image sequence is removed, and the data calculation amount is reduced.

[0045] Further, when the cutting window is too close to the laser spot, the defect information is easily covered by the laser background noise due to the excessively high temperature; when the cutting window is too far from the laser spot, the temperature change caused by the defect is not obvious due to the excessively low temperature. According to the temperature distribution curve, the termination pixel coordinate x n of the nth image cutting window in the X direction is determined, which can ensure that the cutting window is in an area with high signal-to-noise ratio of defect information. Splicing these cutting windows with high signal-to-noise ratio according to the corresponding positions can preliminarily extract the defect information.

[0046] Further, the number of pixels L of the window along the X axis is determined according to the size and number of imagescut , can ensure that the subsequent interception window splicing according to the spatial position, adjacent interception window will not have gap, also will not have too much overlap.

[0047] Further, the interception window in each frame of infrared image keeps the same offset distance d with the laser spot, ensures the same heating condition of each interception window, and facilitates calculation of the temperature change caused only by the defect in the subsequent step.

[0048] Further, in the synthesis image A neg , the defect-free area of the image surface is preliminarily judged, and the Gaussian surface is used to fit the temperature distribution of the defect-free area as a correction matrix I. Since the experimental conditions are completely the same in one experiment, the temperature distribution difference between the defect-free area and the defect area is basically caused by the defect, and the correction matrix obtained from the defect-free area is used to correct the interception window, which can well retain the surface temperature change caused by the defect.

[0049] Further, the interception window of the normal area is selected to fit the correction matrix, so that the correction matrix is consistent with the heating and cooling conditions of the interception window, and the correction matrix is applicable to all interception windows. Since the power density of the laser generally presents an elliptical Gaussian distribution, the Gaussian surface function can well fit the temperature distribution of the defect-free area, reducing the fitting error.

[0050] Further, the interception window t index (x,y,n) selected in each frame of image before correction has the same size and the same heating and cooling conditions. In this way, the temperature distribution difference between the interception windows is caused by the internal defect, effectively retaining the defect information.

[0051] It can be understood that the beneficial effects of the above-mentioned second aspect can be referred to the related description in the above-mentioned first aspect, which will not be described here.

[0052] In summary, the CFRP defect detection method proposed in the present application superimposes the scanning results in the forward and reverse directions, reducing the detection error caused by one-way heat transfer. The cooling area selected at a suitable distance from the laser spot as the interception window can improve the signal-to-noise ratio of the defect information. The normal area of the material itself is used to fit the correction matrix, effectively extracting the temperature distribution caused only by the defect. The present application can reduce the interference of the laser background noise in the infrared image, effectively extract the defect information in the infrared image sequence, and avoid the defect shape error caused by one-way scanning.

[0053] The technical solutions of the present application will be further described in detail below with reference to the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 For the infrared image sequence and image number;

[0055] Figure 2 For the size and position of the intercept window;

[0056] Figure 3 For the detection flow chart and schematic diagram of bidirectional scanning line laser thermography;

[0057] Figure 4 For the schematic diagram of line laser scanning thermography nondestructive testing system;

[0058] Figure 5 For the 50th frame of the material surface infrared image collected;

[0059] Figure 6 For the scanning synthesized image, (a) is the forward scanning synthesized image, and (b) is the reverse scanning synthesized image;

[0060] Figure 7 For the corrected scanning image, (a) is the corrected forward scanning image, and (b) is the reverse scanning image;

[0061] Figure 8 For the defect distribution image, (a) is the actual internal defect distribution, and (b) is the superimposed infrared image;

[0062] Figure 9 For the schematic diagram of the time domain superposition method and the method of the present application, (a) is the time domain superposition method, and (b) is the method of the present application. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0064] In the description of the present application, it should be understood that the terms “include” and “contain” indicate the existence of described features, whole, steps, operations, elements and / or components, but do not exclude the existence or addition of one or more other features, whole, steps, operations, elements, components and / or sets thereof.

[0065] It should also be understood that the terms used in the present application specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, the singular forms “a”, “an” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0066] It should also be further understood that the term "and / or" when used in the specification and in the following claims, is intended to mean that one or more of the listed items can be present, and that the alternatives are to be taken in all possible combinations, and that the phrase is intended to be construed to cover all of the possible combinations. In addition, the character " / " in the present application generally represents an "or" relationship between the objects before and after it.

[0067] It should be understood that, although the terms first, second, third, etc. can be used in the embodiments of the present application to describe various ranges, etc., these ranges should not be limited to these terms. These terms are only used to distinguish one range from another. For example, a first range can also be referred to as a second range, and similarly, a second range can also be referred to as a first range, without departing from the scope of the embodiments of the present application.

[0068] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined" or "if (a stated condition or event) is detected" can be interpreted to mean "when it is determined" or "in response to determining" or "when (the stated condition or event) is detected" or "in response to detecting (the stated condition or event)".

[0069] Various structural diagrams according to the disclosed embodiments of the present application are shown in the accompanying drawings. These diagrams are not drawn to scale, in which certain details are exaggerated for the purpose of clarity, and certain details can be omitted. The shapes and relative sizes of the various regions, layers, and their relative positions shown in the drawings are merely exemplary, and in actuality, they can deviate due to manufacturing tolerances or technical limitations, and a person skilled in the art can additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0070] The present application provides a CFRP defect detection method based on bidirectional scanning line laser thermal imaging. First, a line laser is used to perform bidirectional scanning on the material surface, and an infrared thermal imager is used to collect the temperature distribution of the material surface during scanning. Second, in the collected infrared image sequence, a local area behind the laser spot is selected as a cutting window, and these cutting windows are combined according to the spatial corresponding positions to obtain a synthesized image of one-way scanning. Third, a reference window is selected from the synthesized image, and the synthesized image is corrected according to the spatial distribution of the line laser power density in the reference window to obtain a defect image of single scanning. Finally, the defect images obtained by forward and reverse scanning are superimposed to obtain an infrared image containing internal defect information of the material.

[0071] Please refer toFigure 3 The application discloses a CFRP defect detection method based on bidirectional scanning line laser thermal imaging, and comprises the following steps.

[0072] S1, bidirectional line laser scanning thermal imaging

[0073] Please refer to Figure 1 , the line laser is used for forward scanning and heating on the surface of the carbon fiber composite material along the X direction, and in the process, an infrared thermal imager is used for recording the temperature distribution change of the material surface in real time. Temperature information of the scanning area is extracted to obtain an infrared image sequence f index (x, y, n) of the forward scanning, wherein the temperature of a pixel point with pixel coordinates (x, y) in the nth image is represented, (x, y) is pixel coordinates in the X direction and the Y direction, wherein x belongs to (0, L-1), y belongs to (0, W-1), n is an image number, and the value range is 0-(N-1).

[0074] The pixel with the highest temperature in the image is regarded as the center of the line laser spot, and the center coordinates of the spot in the nth image are marked as (c x , cy) n .

[0075] The image size LxW of the scanning area and the image number N and the laser spot center satisfy the following conditions:

[0076]

[0077]

[0078] After waiting for the test piece to be fully cooled, the other test conditions are kept unchanged, the material surface is reversely scanned and heated, and an infrared image sequence f' index (x, y, n) of the reverse scanning is obtained.

[0079] S2, determination of the intercept window and synthesis of the infrared image

[0080] S201, the size of the intercept window is determined.

[0081] In order to obtain the complete infrared image of the test piece surface, the size of the intercept window is L cut xW, L cut is the number of pixels of the window along the X axis, and W is the number of pixels along the Y axis. Since the scanning speed of the laser is constant, the time interval of the shooting is also constant, and L cut is calculated according to the number of pixels moved by the laser in the adjacent two images, and the specific calculation is as follows:

[0082]

[0083] Wherein, round represents rounding up the calculation result.

[0084] S202. Determine the position of the capture window;

[0085] like Figure 2 As shown, select the i-th frame image f index (x, y, n = i) serves as a reference image, which should be kept at a sufficient distance from the boundary; plot the temperature distribution curve f along the centerline of the specimen in the X direction. index (x, y = W / 2, n = i), where the horizontal axis in the figure represents the pixel coordinate x, and the vertical axis represents the surface temperature of the specimen. The highest temperature T is reached at the center of the light spot in the figure. max The x-coordinate is x tmax The initial temperature of the material surface is denoted as T0.

[0086] Calculate the cutoff temperature T i as follows:

[0087] T i =λ(T) max -T0)+T0

[0088] Where λ∈(0,1) is the temperature attenuation coefficient. When λ is too large, the interception window is too close to the center of the light spot, resulting in excessive noise. When λ is too small, the average temperature of the interception window is too low, which is detrimental to detection. The value of λ needs to be selected and calculated based on the specific physical characteristics of the substrate. Since the interception window is located behind the light spot, the cutoff temperature T in this area is read. i The corresponding x-coordinate i x i This represents the ending x-coordinate of the cropping window in the i-th frame of the image.

[0089] The distance between the end position of the capture window and the center of the spot is denoted as the offset distance d.

[0090] d = x tmax -x i

[0091] During forward scanning, the window for capturing the nth frame image is t. pos (x, y, n) represents the pixel coordinates, where (x, y) are the pixel coordinates and their values ​​range from (x, y, n) to (x, y, n). n -L cut +1, 0)~(x n , W-1), calculate the ending pixel coordinates x of the cropping window in the X direction of the nth frame image based on the offset distance d and the cropping window size. n .

[0092] x n =n×L cut -d

[0093] The value t stored in the nth frame image capture window index(x, y, n) represents the difference between the surface temperature of the material at coordinates (x, y) and the initial temperature.

[0094] t index (x, y, n) = f index (x, y, n) - T0

[0095] wherein, f index (x, y, n) represents the temperature of the pixel point with pixel coordinates (x, y) in the nth frame of image, T0 is the initial temperature of the surface of the material.

[0096] Since the intercept window is located at the rear side of the laser spot, not all intercept windows of the frames of images are within the image range. According to 0≤x n -5 + 1 < x n ≤ L - 1 and 0≤n≤N-1, the value range of n is calculated.

[0097] S203, a blank image with pixels of LxN is taken, the values stored in the intercept window are filled into the blank image according to the pixel coordinates, and a composite image A pos As shown in Figure 6 (a).

[0098] Similarly, the intercept and composite processing are performed on the infrared sequence obtained by the reverse scanning along the X axis, and the composite image during the reverse scanning is A neg As shown in Figure 6 (b).

[0099] S3, correction and superposition of infrared images

[0100] S301, according to the composite image A neg The defect-free area of the image surface can be preliminarily judged. Generally, the defect area accounts for a small proportion in the material to be detected. If the intercept window of the kth frame of image covers a defect-free area, the window can be used as a reference window K.

[0101] S302, since the power density of the line laser generally obeys Gaussian distribution, a suitable Gaussian surface is selected to fit the image to obtain the temperature difference distribution of the defect-free area.

[0102] The expression of the Gaussian surface is:

[0103]

[0104] wherein, g(x, y) represents the temperature difference value of the point with coordinates (x, y), the least square method is used to bring the temperature difference value t index (x, y, k) and the pixel point coordinates (x, y) into Gaussian fitting to obtain the fitting coefficients A, μ x , σ x , μy , sigma y .

[0105] Then the pixel coordinate (x, y) in the reference window K is brought into the Gaussian surface expression g(x, y) to obtain a correction matrix I, the matrix size is L cut ×W; the value stored in the correction matrix I is the distribution of the surface temperature change of the test piece under the laser heating in the normal area.

[0106]

[0107] The intercept window obtained in step S2 is sequentially subtracted from the correction matrix, and the remaining value is the surface temperature change caused by the existence of the defect.

[0108] The intercept window t index (x, y, n) of the n-th frame image before correction is represented as

[0109]

[0110] The intercept window Q index (x, y, n) of the n-th frame image after correction is represented as index (x, y, n)-I.

[0111] A blank image with L×N pixels is taken, the value stored in the intercept window after correction is filled into the blank image according to the pixel coordinate, and then normalized to obtain the infrared image M of the defect during forward scanning pos As shown in Figure 7 (a).

[0112] Similarly, the infrared image M of the defect during reverse laser scanning is calculated neg As shown in Figure 7 (b).

[0113] S4, the images of forward and reverse scanning are superimposed to obtain the infrared image E containing the internal defect information of the material E=0.5(M pos +M neg ).

[0114] In another embodiment of the present application, a CFRP defect detection system based on bidirectional scanning line laser thermal imaging is provided, which can be used to realize the CFRP defect detection method based on bidirectional scanning line laser thermal imaging. Specifically, the CFRP defect detection system based on bidirectional scanning line laser thermal imaging comprises a scanning module, a combination module, a correction module and a detection module.

[0115] The scanning module uses a line laser to perform bidirectional scanning on the surface of the material, collects the temperature distribution of the surface of the material during scanning, and obtains an infrared image sequence.

[0116] The combination module selects a local area behind the laser spot as a cutting window in the infrared image sequence collected by the scanning module, and combines the cutting window according to the spatial corresponding position to obtain a synthetic image of one-way scanning.

[0117] The correction module selects a reference window from the synthetic image obtained by the combination module, corrects the synthetic image according to the spatial distribution of the linear laser power density in the reference window, and obtains a defect image of single scanning.

[0118] The detection module superimposes the defect images obtained by the correction module through forward and reverse scanning to obtain an infrared image containing internal defect information of the material.

[0119] In another embodiment of the present application, a terminal device is provided, which includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to realize the corresponding method flow or corresponding function. The processor in the embodiment of the present application can be used for the operation of the CFRP defect detection method based on bidirectional scanning line laser thermal imaging, including:

[0120] The material surface is scanned bidirectionally by using a line laser, the temperature distribution of the material surface in the scanning process is collected, an infrared image sequence is obtained, a local area behind the laser spot is selected as a cutting window in the collected infrared image sequence, the cutting window is combined according to the spatial corresponding position to obtain a synthetic image of one-way scanning, a reference window is selected from the synthetic image, the synthetic image is corrected according to the spatial distribution of the linear laser power density in the reference window, a defect image of single scanning is obtained, and the defect images obtained by forward and reverse scanning are superimposed to obtain an infrared image containing internal defect information of the material.

[0121] In another embodiment of the present application, the present application also provides a storage medium, specifically a computer readable storage medium (Memory), which is a memory device in the terminal device, used for storing programs and data. It can be understood that the computer readable storage medium herein can include the built-in storage medium in the terminal device, and of course can also include the expansion storage medium supported by the terminal device. The computer readable storage medium provides a storage space, which stores the operating system of the terminal. Moreover, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and the instructions can be one or more computer programs (including program codes). It should be noted that the computer readable storage medium herein can be a high-speed RAM memory, or a non-volatile memory such as at least one disk memory.

[0122] The one or more instructions stored in the computer readable storage medium can be loaded and executed by the processor to realize the corresponding steps of the CFRP defect detection method based on the bidirectional scanning line laser thermal imaging in the above-mentioned embodiments; the one or more instructions in the computer readable storage medium are loaded and executed by the processor as follows:

[0123] The material surface is scanned bidirectionally using a line laser, the temperature distribution of the material surface in the scanning process is collected, and an infrared image sequence is obtained; in the collected infrared image sequence, a local area behind the laser spot is selected as a clipping window, and the clipping window is combined according to the spatial corresponding positions to obtain a composite image of unidirectional scanning; a reference window is selected from the composite image, and the composite image is corrected according to the spatial distribution of the line laser power density in the reference window to obtain a defect image of single scanning; the defect images obtained by the forward and reverse scanning are superimposed to obtain an infrared image containing internal defect information of the material.

[0124] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0125] The line laser scanning thermal imaging nondestructive testing system is as follows Figure 4As shown, the laser scanning galvanometer is used to realize the bidirectional scanning heating of the laser on the material surface, and in this process, the infrared thermal imager is used to record the temperature distribution change of the material surface in real time. In order to exclude the interference of external noise and verify the effectiveness of the detection method proposed in the application, in an embodiment of the application, COMSOL multi-physics is used to simulate the scanning heating process of the laser on the material surface, and random noise is added to simulate the environmental interference in the experiment. Finite element simulation belongs to the commonly used research method of infrared thermal imaging, and does not belong to the content involved in the application, which will not be described here.

[0126] In the embodiment of the application, the line laser presents an elliptical Gaussian distribution, the major axis of the line laser is 30 mm, the minor axis is 0.6 mm, and the laser power is 2 W.

[0127] The size of the collected scanning area is 150 mm*26 mm, the line laser scanning speed is 2 mm / s, the scanning time is 0-75 s, the acquisition speed is 2 Fps, and large-size workpiece detection can be realized through path planning of the galvanometer and image splicing. The temperature information of the scanning area is extracted to obtain the infrared image sequence f index (x,y,n) of the forward scanning and the infrared image sequence f' index (x,y,n) of the reverse scanning. (x,y) is the pixel coordinate of the X direction and the Y direction, the value range is (0,0)-(750,130), and n is the image number, the value range is 0-150. Figure 5 The original gray-scale image of the 50th frame of forward laser scanning is shown.

[0128] The size L cut of the intercept window is determined according to the image size. In order to obtain the complete infrared image of the test piece surface, the length L cut of the intercept window in the X direction is calculated according to the number of pixels moved by the laser in the adjacent two frames of images.

[0129]

[0130] Secondly, as shown in the reference image, the temperature distribution of the test piece surface along the X axis is determined according to the 50th frame of image. Figure 5 The temperature at the center of the light spot reaches the maximum value T max =366.6K, the abscissa is x tmax =250, and the initial temperature of the material surface is T0=293.15K.

[0131] When the intercept window is outside the inflection point of the curve, the image becomes relatively smooth, and the reference curve is similar to the Gaussian curve, and λ=0.317 is selected according to the experience value for calculation; the cut-off temperature value T i is calculated as follows:

[0132] Ti = λ(T max - T0) + T0 = 316.43 K

[0133] The coordinate point closest to the temperature is (230, 316.6).

[0134] The offset distance d = 250 - 230 = 20 is calculated.

[0135] The nth frame image interception window in forward scanning is represented by t index (x, y, n), where (x, y) is the pixel coordinate, and the value range is (x n -5 + 1, 0) ~ (x n , 130). The terminal pixel coordinate x n in the X direction of the interception window is calculated according to the offset distance d and the interception window size.

[0136] x n = n x 5 - 20

[0137] In the nth frame image interception window, the value stored in the pixel coordinate (x, y) is the difference between the material surface temperature and the initial temperature.

[0138] t index (x, y, n) = f index (x, y, n) - 293.15 K

[0139] According to 0 ≤ x n -5 + 1 < x n ≤ 750 and 0 ≤ n ≤ 150, it can be calculated that the value range of n is 5 ~ 150.

[0140] Subsequently, a blank image with a pixel of 751 x 131 is taken. According to the above formula, only the interception windows from the 5th frame to the 150th frame are within the material range. The information stored in the interception window is filled into the corresponding position of the image according to the pixel number, and the synthesized image A pos in forward scanning is obtained. In order to compare with the subsequent processed image, A pos is normalized and displayed to obtain the infrared image as shown in Figure 6 (a).

[0141] In reverse laser scanning, the same image interception and synthesis processing is performed to obtain the synthesized image A neg in reverse scanning as shown in Figure 6 (b).

[0142] According to the synthesized image A neg , it can be preliminarily judged that the interception window of the 15th frame image is completely included in the defect-free area, and the window is used as the reference window K.

[0143] The temperature difference distribution of the defect-free region is obtained by fitting the image with a proper Gaussian surface. The expression of the Gaussian surface is:

[0144]

[0145] The temperature difference value t index (x,y,k) in the reference window K is brought into the Gaussian fitting with the pixel coordinates (x,y) to obtain the fitting parameters A=18.5, μ x =55.05, σ x =30.6i, μ y =65.0, σ y =30.74.

[0146] The pixel coordinates (x,y) in the reference window K are brought into the expression of the Gaussian surface g(x,y) to obtain the correction matrix I.

[0147] The difference between the intercept window obtained in step S2 and the correction matrix is obtained to obtain the corrected intercept window Q inaex (x,y,n) of the nth frame of image t index (x,y,n)-I.

[0148] A blank image with pixels of LxN is taken, the values stored in the corrected intercept window are filled into the blank image according to the pixel coordinates, and then normalized to obtain the infrared image M pos of the defect during forward scanning, as shown in Figure 7 (a).

[0149] Similarly, the infrared image M neg of the defect during reverse laser scanning is calculated, as shown in Figure 7 (b).

[0150] Finally, the images obtained by forward and reverse scanning are superimposed to obtain the infrared image E=0.5(M pos +M neg ) containing the internal defect information of the material, and the result of the bidirectional scanning line laser thermography is shown in Figure 8 (b).

[0151] The CFRP material in this embodiment is set to have a thickness of 4 mm, and the defects are located inside the material at a distance of 1 mm from the surface, and the specific sizes are shown in Figure 8 (a). A suitable threshold value is selected to calculate the area of the defect and the position of the defect, and the results are shown in Table 1.

[0152] Table 1: Comparison of detection results and actual results

[0153]

[0154] The method of using the whole surface temperature time domain superposition method commonly used for the collected thermal imaging data is compared with the method proposed in this case, and the results are shown in Table 2. Figure 9 The signal-to-noise ratio is calculated by dividing the average temperature of the defect area by the average temperature of the whole surface, and the results are shown in Table 2.

[0155] Table 2: Signal-to-noise ratio of the method in this case and the time domain superposition method

[0156]

[0157] It can be seen that the defect shape extracted by the method is more clear, and the signal-to-noise ratio is improved by an average of 250%. The method can well overcome the background noise caused by uneven distribution of laser power density, has low calculation complexity, high defect restoration degree, and is suitable for detecting near-surface defects such as delamination and debonding of carbon fiber composite materials.

[0158] In summary, the CFRP defect detection method and system based on bidirectional scanning line laser thermal imaging of the application uses a bidirectional scanning method to avoid errors caused by one-way heat transfer and improve the detection accuracy of the defect shape. The use of the interception window to intercept the effective area in each frame of image can well overcome the background noise caused by uneven distribution of laser power density. The normal area of the material surface is used to construct a correction matrix to extract the temperature distribution caused only by the defect, and the signal-to-noise ratio of the defect information is improved.

[0159] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The above integrated unit can be realized in the form of hardware or software. In addition, the specific names of each functional unit and module are only for easy distinction, and do not limit the protection scope of the application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0160] In the above embodiments, the description of each embodiment has its own emphasis, and the parts not described or recorded in a certain embodiment can be referred to the related description of other embodiments.

[0161] Those skilled in the art can understand that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized in electronic hardware or in combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0162] In the embodiments provided by the present application, it should be understood that the disclosed apparatus / terminal and method can be implemented in other ways. For example, the apparatus / terminal embodiments described above are merely schematic. The division of the modules or units is merely a logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed coupling or direct coupling or communication connection between the units can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or in other forms.

[0163] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e. they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0164] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically independently, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0165] The integrated module / unit, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the computer-readable medium can include or exclude contents according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0166] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The flow or multiple flows and / or blocks Figure 1 The apparatus that implements the functions specified in one or more flows or blocks.

[0167] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction apparatus, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The flow or multiple flows and / or blocks Figure 1 The apparatus that implements the functions specified in one or more flows or blocks.

[0168] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable data processing devices to generate a computer implemented process, so that the instructions executed on the computer or other programmable data processing devices provide a process for implementing the flowchart Figure 1 one flow or multiple flows and / or blocks Figure 1 Figure 1 one block or multiple blocks.

[0169] The above is only to illustrate the technical idea of the present application, and cannot limit the protection scope of the present application. Any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the claims of the present application.

Claims

1. A CFRP defect detection method based on bidirectional scanning line laser thermography, characterized by, Includes the following steps: S1. Use a line laser to perform bidirectional scanning on the material surface, collect the temperature distribution on the material surface during the scanning process, and obtain an infrared image sequence; S2. In the infrared image sequence acquired in step S1, a local area behind the laser spot is selected as a cropping window. The cropping windows are combined according to their spatially corresponding positions to obtain a unidirectional scan composite image, specifically: The size of the intercept window is determined as , is the number of pixels along the X-axis direction of the window, is the number of pixels along the Y-axis direction. Select the first frame image As a reference image, draw the temperature distribution curve on the center line of the test piece X direction , the initial temperature of the material surface is recorded as ; The distance between the termination position of the intercepted window and the center of the light spot is recorded as the offset distance d , according to the offset distance d And the size of the intercepted window, the termination pixel coordinate of the first frame image interception window in the X direction is calculated , according to And Determine the value range of n ; Take a pixel as The blank image is filled with the values ​​stored in the cropping window according to pixel coordinates to obtain the composite image. The infrared sequence obtained by scanning in reverse along the X-axis is truncated and synthesized to obtain the synthesized image during the reverse scan. Offset distance d for: wherein, is the horizontal coordinate of the pixel with the highest temperature value in the image, is the horizontal coordinate of the pixel with the highest temperature value in the image, is the horizontal coordinate of the pixel with the highest temperature value in the image, S3. Select a reference window from the synthesized image obtained in step S2, and correct the synthesized image according to the spatial distribution of the linear laser power density in the reference window to obtain the defect image of a single scan, specifically: According to the synthetic image A preliminary judgment is made on the defect-free area of the image surface. If the first If the area covered by the window of the frame image is a defect-free area, the corresponding window is used as the reference window ; The temperature difference distribution of the non-defect area is obtained by selecting a Gaussian surface to fit the image, and then the reference window The pixel coordinates The Gaussian surface expression is brought in The correction matrix is obtained The matrix size is The correction matrix The values stored in the correction matrix are the distribution of the surface temperature change of the normal area under laser heating, the intercepted window obtained in step S2 is subtracted from the correction matrix in sequence, and the remaining values are the surface temperature changes caused by the defects, a blank image with one pixel of is taken, the values stored in the corrected intercepted window are filled into the blank image according to the pixel coordinates, and then normalized to obtain the infrared image of the defect during forward scanning The infrared image of the defect during reverse laser scanning is calculated ; S4. Superimpose the defect images obtained from the two scans in step S3 (forward and reverse) to obtain an infrared image containing information about internal defects in the material.

2. The CFRP defect detection method based on bidirectional scanning line laser thermography according to claim 1, characterized in that, In step S1, the temperature information of the scanning region is extracted to obtain an infrared image sequence of forward scanning , represents the temperature of a pixel point with pixel coordinates in the i-th frame image; , , are pixel coordinates in the X direction and the Y direction, , is an image number, and the value range is 0 ; The pixel with the highest temperature in the image is regarded as the center of the line laser spot, and the coordinates of the center of the line laser spot are recorded as The coordinates of the center of the spot of the frame image are recorded as ; a reverse scanning heating is performed on the surface of the material to obtain a sequence of infrared images of the reverse scanning .

3. The CFRP defect detection method based on bidirectional scanning line laser thermography according to claim 2, characterized in that, Image size of the scanned area and the number of images with the center of the laser spot satisfying the following conditions: 。 4. The method for CFRP defect detection based on bidirectional scanning line laser thermography according to claim 1, characterized in that, Number of pixels of the window along the X-axis direction is: wherein denotes rounding up the result of the calculation.

5. The bidirectional scanning line laser thermography based CFRP defect detection method according to claim 1, characterized in that, correction matrix is: wherein, is the first is the termination pixel abscissa of the frame image capture window in the X direction, is the Gaussian surface expression, is the number of pixels of the window along the X axis, is the number of pixels along the Y axis.

6. The bidirectional scanning line laser thermography based CFRP defect detection method according to claim 1, characterized in that, Before the amendment, Article 15 of the Patent Law Frame image capture window The matrix is represented as: modified frame image clipping window ; for the the termination pixel coordinate of the frame image clipping window in the X direction, is the number of pixels along the Y axis direction.

7. A CFRP defect detection system based on bidirectional scanning line laser thermography, characterized by, include: The scanning module uses a line laser to perform bidirectional scanning of the material surface, acquiring the temperature distribution of the material surface during the scanning process, and obtaining an infrared image sequence. The combination module selects a local area behind the laser spot as a cropping window from the infrared image sequence acquired by the scanning module, and combines the cropping windows according to their spatially corresponding positions to obtain a unidirectional scan composite image, specifically: The size of the intercept window is determined as , is the number of pixels along the X-axis direction of the window, is the number of pixels along the Y-axis direction. Select the first Frame image As a reference image, the temperature distribution curve on the center line of the specimen X direction is drawn The initial temperature of the material surface is recorded as ; The distance between the termination position of the capture window and the center of the light spot is denoted as the offset distance. d According to the offset distance d And calculate the first [window size]. The ending pixel coordinates of the frame image capture window in the X direction ,according to as well as Sure n The range of values ​​for ; Take a blank image with pixel , fill the values stored in the intercept window into the blank image according to the pixel coordinates, and get the composite image . For the infrared sequence obtained by reverse scanning along the X axis, the intercept and synthesis processing is performed to obtain the composite image during reverse scanning as , and the offset distance d is: wherein, is the horizontal coordinate of the pixel with the highest temperature value in the image, is the horizontal coordinate of the pixel with the highest temperature value in the image, is the horizontal coordinate of the pixel with the highest temperature value in the image, The correction module selects a reference window from the composite image obtained by the combination module, and corrects the composite image according to the spatial distribution of the linear laser power density in the reference window to obtain the defect image of a single scan, specifically: According to the synthetic image If the preliminary judgment is that the defect-free region of the image surface is the first region, the first region is used as the reference window If the preliminary judgment is that the defect-free region of the image surface is the first region, the first region is used as the reference window If the preliminary judgment is that the defect-free region of the image surface is the first region, the first region is used as the reference window The temperature difference distribution of the defect-free area is obtained by selecting a Gaussian surface to fit the image, and then a reference window The pixel coordinates The Gaussian surface expression is brought in The correction matrix is obtained The matrix size is The correction matrix The values stored in the correction matrix are the distribution of the surface temperature change of the normal area under laser heating, the intercepted window obtained by the combination module is sequentially subtracted from the correction matrix, and the remaining values are the surface temperature changes caused by the defects, and a blank image with a pixel of The values stored in the corrected intercepted window are filled into the blank image according to the pixel coordinates, and then normalized to obtain the infrared image of the defect during forward scanning The infrared image of the defect during reverse laser scanning is calculated ; The detection module superimposes the defect images obtained from the two scans by the correction module to obtain an infrared image containing information about internal defects in the material.

Images