Method and device for detecting internal defects of ship laminated plate

Abstract

The invention relates to the technical field of material testing and analysis, in particular to a method and device for detecting internal defects of a ship laminated plate, and the method comprises the steps: obtaining internal damage data of a defect part of the ship laminated plate; determining the defect depth and the defect type of the defect part of the ship laminate based on the internal damage data; based on the defect depth, the defect type and the laying layer of the ship, a prefabricated defect laminated plate is constructed; determining a target frequency band matched with the prefabricated defect laminated plate; wherein the energy corresponding to the target frequency band regularly changes along with the size of the defect; and determining the defect equivalent of the ship laminate based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band. According to the method, various types of defects and the defect equivalent of the ship laminate can be accurately analyzed by acquiring the internal damage data of the defect part of the ship laminate and combining with the constructed target frequency band of the prefabricated defect laminate.

Description

Technical Field

[0001] The invention relates to the technical field of material testing and analysis, and in particular to a method and a device for detecting internal defects of a ship laminate in the technical field of material testing and analysis. Background Art

[0002] The laminate structure of FRP boats is mostly formed by hand lay-up process, which is flexible, adaptable, not limited by size and shape, and is particularly suitable for the production of large-sized and complex-shaped boat structures. However, in the hand lay-up process, the labor intensity of workers is high, the on-site hygiene conditions are poor, the human factors are large, and the quality is difficult to control. FRP laminates are prone to defects such as bubbles, inclusions, and dry spots during the production process, resulting in reduced mechanical properties, posing a threat to the structural integrity and navigation safety of boats.

[0003] In order to avoid hidden dangers caused by invisible internal defects, internal defects need to be detected and evaluated. At present, defect detection methods for composite materials are mainly divided into two categories: destructive testing and non-destructive testing. However, destructive testing methods will damage the samples, so they are generally not suitable for quality control of actual products. In addition, high costs are also a consideration, especially for high-value items such as boats. Among non-destructive testing methods, ultrasonic phased array non-destructive testing technology has become the focus of current research on non-destructive testing of composite materials due to its high reliability and high precision. However, the application of ultrasonic technology in composite material defect detection is mainly focused on judging the presence or absence of defects and the detection of single defects, and cannot compare and quantitatively evaluate the differences in ultrasonic detection signals of multiple defects. Summary of the invention

[0004] The purpose of the present invention is to provide a method and device for detecting internal defects of shipboard laminates. The technical scheme adopted is as follows:

[0005] In a first aspect, an embodiment of the present invention provides a method for detecting internal defects of a ship laminate, the method comprising:

[0006] Obtain internal damage data of defective parts of ship laminates;

[0007] Determining the defect depth and defect type of the defective portion of the boat laminate based on the internal damage data;

[0008] constructing a prefabricated defective laminate based on the defect depth, the defect type and the ply of the boat;

[0009] Determine a target frequency band that matches the prefabricated defective laminate; wherein the energy corresponding to the target frequency band changes regularly with the size of the defect;

[0010] Based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band, the defect equivalent of the ship laminate is determined.

[0011] In a second aspect, an embodiment of the present invention provides a device for detecting internal defects of a ship laminate, the device comprising:

[0012] An acquisition module, used to acquire internal damage data of defective parts of the ship laminate;

[0013] A first determination module, configured to determine a defect depth and a defect type of a defective portion of the ship laminate based on the internal damage data;

[0014] A construction module, configured to construct a prefabricated defective laminate based on the defect depth, the defect type and the ply of the boat;

[0015] The second determination module is used to determine the target frequency band that matches the prefabricated defective laminate; wherein the energy corresponding to the target frequency band changes regularly with the size of the defect;

[0016] The third determination module is used to determine the defect equivalent of the ship laminate based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band.

[0017] According to a third aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0018] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the first aspect or any possible implementation manner described in the first aspect.

[0019] The present invention has the following beneficial effects: by scanning the defective part of the boat laminate, a scanned image is obtained; and based on the scanned image, the defect depth and defect type of the defective part of the boat laminate are determined; in this way, by performing a preliminary analysis on the scanned image of the defective part of the boat laminate, the defect depth and defect type of the defective part can be quickly obtained. Afterwards, the prefabricated defective laminate can be accurately constructed according to the defect depth, the defect type and the ply of the boat; and the target frequency band that matches the prefabricated defective laminate is further determined; wherein the energy corresponding to the target frequency band changes regularly with the size of the defect; finally, by combining the energy of the scanned image in each frequency band with the energy corresponding to the target frequency band, the defect equivalent of the boat laminate can be accurately obtained. In this way, by obtaining the internal damage data of the defective parts of the boat laminates, and then combining time domain, frequency domain, time-frequency domain signal processing, etc., the defect depth and defect type of the defective parts of the boat laminates can be accurately determined. Then, by combining the target frequency band of the constructed prefabricated defective laminates, various types of defects and the defect equivalents of the boat laminates can be accurately analyzed. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is a schematic diagram of the implementation process of a method for detecting internal defects of a ship and boat laminate provided by an embodiment of the present invention;

[0022] Figure 2 is a schematic diagram of scanning results of an ultrasonic phased array detector provided in an embodiment of the present invention;

[0023] Figure 3 is a schematic diagram of an ultrasonic phased array detector provided by an embodiment of the present invention;

[0024] Figure 4 It is another implementation flow diagram of a method for detecting internal defects of a shipboard laminate provided by an embodiment of the present invention;

[0025] Figure 5 Schematic diagram of an application scenario of a method for detecting internal defects of a shipboard laminate provided by an embodiment of the present invention;

[0026] Figure 6 It is another implementation flow diagram of a method for detecting internal defects of a shipboard laminate provided by an embodiment of the present invention;

[0027] Figure 7 It is a schematic diagram of the composition structure of a device for detecting internal defects of a ship and boat laminate provided by an embodiment of the present invention;

[0028] Figure 8 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the method for detecting internal defects of a shipboard laminate according to the present invention, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0030] Among them, in the description of the embodiments of the present invention, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a way to describe the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present invention, "multiple" refers to two or more than two.

[0031] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0032] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0033] In the related art, the laminate structure of FRP boats is mostly formed by hand lay-up process, which is flexible, adaptable, not limited by size and shape, and is particularly suitable for the production of large-sized and complex-shaped boat structures. However, in the hand lay-up process, the labor intensity of workers is high, the on-site sanitary conditions are poor, the human factors are large, and the quality is difficult to control. FRP laminates are prone to defects such as bubbles, inclusions, and dry spots during the production process, resulting in reduced mechanical properties, posing a threat to the structural integrity and navigation safety of boats. In addition, when boats are sailing at high speeds and docking at docks, they often collide or collide due to improper operation. Due to the poor impact resistance of FRP, cracks or delamination damage are easily generated, and most of them occur inside the material and are invisible to the naked eye, posing a greater risk to the safety of the boat structure.

[0034] In order to avoid hidden dangers caused by invisible internal defects, internal defects need to be detected and evaluated. At present, defect detection methods for composite materials are mainly divided into two categories: destructive testing and non-destructive testing. Destructive testing can intuitively show the internal structure and defects of the material, thereby providing accurate and detailed analysis results. In contrast, non-destructive testing technology uses optical, electromagnetic and acoustic principles to detect defects and damage inside the material without compromising the integrity of the material. In addition, non-destructive testing also requires accurate qualitative and quantitative analysis of the detected features in order to evaluate the performance of the material, predict the safety of the structure, and estimate its residual strength and expected life.

[0035] However, destructive testing methods will damage the samples, so they are not suitable for quality control of actual products and are costly. Among the non-destructive testing methods, ultrasonic phased array non-destructive testing technology has become the focus of current research on non-destructive testing of composite materials due to its high reliability and high precision. However, the application of ultrasonic technology in composite material defect detection is mainly focused on judging the presence or absence of defects and the detection of single defects, and it is not possible to compare and quantitatively evaluate the differences in ultrasonic detection signals of multiple defects.

[0036] Based on this, an embodiment of the present invention provides a method for detecting internal defects of a ship laminate, through which the type, depth and size of different defects inside the FRP laminate can be accurately judged.

[0037] The following is a detailed description of a method for detecting internal defects of a shipboard laminate provided by the present invention in conjunction with the accompanying drawings. Figure 1 , which shows a schematic diagram of the implementation process of a method for detecting internal defects of a shipboard laminate provided by an embodiment of the present invention, the method comprising:

[0038] 101, obtaining internal damage data of defective parts of ship laminates.

[0039] Here, the boat can be any type of fiberglass boat, such as a fiberglass yacht, a fiberglass ship or a fiberglass transport ship. The boat laminate can be a fiberglass boat laminate. Figure 2 As shown, the internal damage data of the defective part includes: A-scan signal 24 (undetected), A-scan signal 23 (detected), C-scan image 21 and S-scan image 22. Among them, A-scan signal 24 (undetected) is a radio frequency waveform, A-scan signal 23 (detected) is a video waveform, and C-scan image 21 and S-scan image 22 can be obtained through A-scan signal 23 (detected).

[0040] In some possible implementations, a scanning signal is obtained by performing phased array ultrasonic scanning on the defective part of the ship laminate; for example, Figure 3The portable ultrasonic phased array detector shown in the figure performs phased array ultrasonic scanning on the defective part of the boat laminate to obtain an undetected signal. By performing detection processing on the undetected signal, a first scanning signal can be obtained, that is, Figure 2 The A-scan signal 23 (after detection) shown. Afterwards, the first scanning signal is converted to obtain multiple types of converted signals; for example, by converting the A-scan signal (after detection) into an S-scan signal and a C-scan signal, multiple types of converted signals are obtained. Finally, based on the multiple types of converted signals, multiple types of scanning images of the defective part of the ship laminate are determined; the defective part is scanned by these multiple types of converted signals to obtain multiple types of scanning images, and the multiple types of scanning images and the first scanning signal are used as the internal damage data. In this way, by using an ultrasonic phased array detector to perform phased array ultrasonic scanning on the defective part of the ship laminate, the C-scan image and S-scan image of the defective part can be accurately obtained, so as to analyze the defect area and defect depth of the defective part.

[0041] 102. Determine the defect depth and defect type of the defect location of the ship laminate based on the internal damage data.

[0042] Here, since the S-scan image in the internal damage data is a two-dimensional image of the defective part, it can characterize the internal structure of the defective part. The horizontal axis represents the distance of a straight line scan of the probe on the surface of the defective part, and the vertical axis represents the sound propagation time (distance). The distribution of defects and the depth of defects on any longitudinal section of the defective part under inspection are displayed. Therefore, the defect depth of the defective part of the ship laminate can be obtained through the S-scan image in the internal damage data.

[0043] In some possible implementations, the first scanning image in the internal damage data is obtained; and based on the first scanning image, the defect depth of the defective part of the boat laminate is determined. Here, the first scanning image may be an S-scan image of the defective part; wherein the first scanning image may be obtained by the A-scan signal 23 (after detection). Since the first scanning image in the internal damage data is generated by scanning the defective part of the boat laminate layer by layer and reconstructing and processing the image data obtained by scanning each layer, the first scanning image can be used to obtain information such as the internal structure, internal structural characteristics, defect distribution and size of the defective part. Therefore, through the first scanning image, the defect depth of the defective part of the boat laminate can be accurately analyzed.

[0044] Since the defect types of the defective parts of the shipboard laminate are different, the corresponding spectra are also different. Therefore, the defect type of the defective parts of the shipboard laminate can be determined by the spectrum corresponding to the internal damage data. In some possible implementations, the first frequency domain signal is obtained by performing frequency domain conversion on the undetected signal corresponding to the first scanning signal of the internal damage data; wherein the undetected signal is as follows: Figure 2 As shown in the A-scan signal 24 (undetected), the waveform of the A-scan signal 24 (undetected) is a radio frequency waveform. Then, based on the frequency spectrum corresponding to the first frequency domain signal and the preset relationship table, the defect type of the defective part of the ship laminate is determined; wherein the preset relationship table is used to characterize the correspondence between the frequency spectrum and the defect type.

[0045] Here, a Fourier transform is performed on the undetected signal corresponding to the first scanning signal corresponding to the internal damage data to obtain a first frequency domain signal; then, according to the correspondence between the frequency spectrum and the defect type in the preset relationship table, the defect type corresponding to the frequency spectrum of the first frequency domain signal can be determined, thereby obtaining the defect type of the defective part of the boat laminate.

[0046] 103. Construct a prefabricated defective laminate based on the defect depth, the defect type and the ply of the boat.

[0047] Here, after analyzing the defect depth of the defect location, the defect type and the ply of the boat, the corresponding prefabricated defective laminate can be produced.

[0048] In some possible implementations, a prefabricated defective laminate may be produced by the following process:

[0049] Step 1: Design and manually paste six types of defects: delamination, inclusion, bulging, poor / rich resin, fiber breakage, and dry spots.

[0050] Among them, the manufacturing process of prefabricated defective laminates is as follows: Figure 4 As shown, the following steps are explained:

[0051] 401, designing the plate size and defect size according to the defect depth and the defect type.

[0052] 402, prepare the production materials.

[0053] 403, locate the defect.

[0054] 404, wax the mold surface.

[0055] 405, hand lay-up is performed according to the lay-up of the boat.

[0056] 406, placing defects on the plies.

[0057] Here, if Figure 5 As shown in image 501, the defect is placed.

[0058] 407, completing the subsequent layer pasting.

[0059] like Figure 5 As shown in image 502 in FIG. 1 , the fibers are manually wetted and air bubbles are eliminated to achieve hand lay-up.

[0060] 408, waiting for the ply to solidify.

[0061] like Figure 5 As shown in the image 503 in FIG. 1 , the laminate is waited to solidify so as to facilitate subsequent demoulding of the laminate.

[0062] 409, after the laminate is solidified, the laminate is demoulded.

[0063] 410, on the demoulded laminate, excess material is cut off to obtain a cut laminate.

[0064] 411, the cut plies are surface-grinded to obtain a prefabricated defective laminate.

[0065] 104 , determining a target frequency band to be matched by the prefabricated defective laminate.

[0066] The energy corresponding to the target frequency band changes regularly with the size of the defect; for example, the energy of the target frequency band increases proportionally with the increase of the defect; or, the energy of the target frequency band decreases proportionally with the decrease of the defect.

[0067] In some possible implementations, the above step 104 can be performed by Figure 6 The steps shown achieve:

[0068] 601 , perform phased array ultrasonic scanning on the prefabricated defective laminate to obtain a second scanning signal corresponding to the prefabricated defective laminate.

[0069] Here, an ultrasonic phased array detector is used to perform phased array ultrasonic scanning on the prefabricated defective laminate to obtain an undetected signal corresponding to the prefabricated defective laminate. By performing detection processing on the undetected signal, an A scan signal (after detection), that is, a second scanning signal, can be obtained.

[0070] 602. Perform frequency domain conversion on the undetected signal corresponding to the second scanning signal to obtain a second frequency domain signal.

[0071] Here, the undetected signal corresponding to the second scanning signal is converted into a frequency domain signal through FFT transformation, and the energy of each frequency band of the frequency domain signal is extracted for analysis.

[0072] 603 : Perform energy extraction on the second frequency domain signal to obtain energy of the second frequency domain signal in each frequency band.

[0073] Here, after the second frequency domain signal is obtained, the energy of each frequency band is obtained by calculating the amplitude and frequency of the second frequency domain signal.

[0074] 604 : Determine a target frequency band that changes regularly with the size of the defect based on the energy of the second frequency domain signal in each frequency band.

[0075] Here, after obtaining the energy of the second frequency domain signal in each frequency band, the target frequency band whose energy increases or decreases in proportion to the defect size can be statistically obtained. In this way, by performing frequency domain conversion on the undetected signal corresponding to the second scanning signal, the second frequency domain signal can be obtained, and then the energy of the second frequency domain signal in each frequency band can be analyzed to accurately calculate the target frequency band whose energy can change regularly with the defect size.

[0076] In some possible implementations, assuming that there is a signal X(t) with a period of T, the Fourier sequence of the signal is as shown in formula (1):

[0077]

[0078] Among them, a0, a n , b n is the Fourier series; f n are the harmonic frequencies.

[0079] In ultrasonic testing, the signal is usually regarded as a transient signal of finite time. For the signal X(t) at a certain moment, T tends to infinity, and the Fourier sequence at this time is as shown in formula (2):

[0080]

[0081] By converting the Fourier coefficients into a continuous frequency function X(f), we can obtain formula (3):

[0082]

[0083] Where f is the frequency and X(f) is a complex function. The amplitude-frequency is obtained as shown in formula (4):

[0084]

[0085] In practical applications, continuous signals are sampled and quantized through analog-to-digital converters and converted into discrete signals to facilitate the recording and processing of signal data. At this time, discrete Fourier transform (DFT) is used to perform time-frequency conversion of the signal, as shown in formula (5):

[0086]

[0087] Wherein, X[k] is the complex value of the kth frequency component in the frequency domain, x[n] is the nth sampling point of the time domain signal (i.e., the undetected signal corresponding to the first scanning signal or the undetected signal corresponding to the second scanning signal), N is the total number of sampling points of the signal, and j is an imaginary unit.

[0088] However, in the actual signal processing process, the DFT calculation complexity is large and is not suitable for large-scale data processing. Fast Fourier Transform (FFT) is an efficient and fast algorithm for DFT. The calculation complexity of DFT is O(N 2 ), and FFT reduces the computational complexity to O(NlogN) through a specific algorithm, which greatly reduces the computational complexity.

[0089] In the frequency domain, the spectrum energy can be expressed by the square of the spectrum E as shown in formula (6):

[0090] E=∑|X(k)| 2 (6);

[0091] If you only care about the energy of a specific frequency band, you can sum the frequency points in the band. For example, if the frequency band is from the k1th to the k2th frequency points, then the energy of the frequency band is as shown in formula (7):

[0092]

[0093] In this way, after obtaining the energy of each frequency band, the target frequency band whose energy value changes regularly with the defect size can be quickly and accurately counted.

[0094] 105. Determine the defect equivalent of the ship laminate based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band.

[0095] Here, the internal damage data includes two-dimensional images (eg, C-scan images, S-scan images), etc. After scanning the prefabricated defective laminate, an A-scan signal (ie, a second scanning signal), a C-scan image, and an S-scan image of the prefabricated defective laminate can be obtained.

[0096] By comparing the energy of the internal damage data in each frequency band with the energy corresponding to the target frequency band, the defect equivalent of the ship laminate can be calculated.

[0097] In some possible implementations, the above step 105 may be implemented by the following steps 151 to 153 (not shown):

[0098] 151. Compare the energy of the internal damage data in each frequency band with the energy corresponding to the target frequency band to obtain a first comparison result.

[0099] Here, by performing Fourier transform on the undetected signal corresponding to the first scanning signal of the internal damage data to obtain a first frequency domain signal, and then performing energy extraction on the first frequency domain signal, the energy of the internal damage data in each frequency band can be obtained; the energy of the internal damage data in each frequency band is compared with the energy corresponding to the target frequency band to obtain a first comparison result.

[0100] 152. Determine a defect equivalent of the ship laminate based on the first comparison result.

[0101] Here, by obtaining the mapping relationship between the energy of each frequency band and the defect equivalent, and according to the first comparison result and the mapping relationship, the defect equivalent of the shipboard laminate is calculated. Since the defect equivalents corresponding to the energies of different frequency bands are different, the defect equivalent of the shipboard laminate can be accurately estimated according to the difference between the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band.

[0102] In some possible implementations, whether the determined defect equivalent of the shipboard laminate is accurate can be determined by the following process:

[0103] First, based on the second scan image in the internal damage data, the defect area of ​​the defective part of the ship laminate is determined.

[0104] Here, since the internal damage data includes the second scan image, the second scan image may be obtained by Figure 2 The A-scan signal (after detection) shown in the figure is obtained. For example, the second scan image can be a C-scan image. Among them, C-scan is a cross-sectional imaging method in a two-dimensional plane. The oscilloscope screen of the C-scan instrument represents the projection surface of the inspected workpiece and can draw the horizontal projection position of the defect. Therefore, the defect distribution and area inside the workpiece can be detected through the C-scan image. Therefore, the defect area of ​​the defective part of the boat laminate can be estimated through the C-scan image (i.e., the second scan image).

[0105] Secondly, the defect area is compared with the preset defect areas of various defects of the prefabricated defective laminate to obtain a second comparison result.

[0106] Finally, based on the second comparison result and the preset corresponding relationship, it is judged whether the determined defect equivalent of the boat laminate is accurate.

[0107] Here, the preset corresponding relationship is used to characterize the corresponding relationship between the preset defect area of ​​each type of defect and the energy of each frequency band. When the ultrasonic phased array detector is used to scan the prefabricated defective laminate, the C-scan image and S-scan image of the prefabricated defective laminate can be scanned by transforming the first scanning signal, so that the defect area of ​​the prefabricated defective laminate can be analyzed through the C-scan image, and the energy of the frequency domain signal can be extracted by frequency domain conversion of the undetected signal corresponding to the first scanning signal, and then a mapping relationship can be established between the extracted energy and the preset defect area obtained by analysis; in this way, the mapping relationship between the target frequency band of the prefabricated defective laminate and the preset defect area can be obtained. Based on this, the difference between the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band can be obtained through the first comparison result, and the area difference can be obtained through the second comparison result.

[0108] Since the second scanning image of the prefabricated defective laminate, i.e., the C-scan image of the prefabricated defective laminate, can be obtained after the ultrasonic phased array detector is used to scan the prefabricated defective laminate, the defect area of ​​the prefabricated defective laminate can be quickly estimated. After estimating the defect area of ​​the defective part through the C-scan image, since the energy of the frequency bands corresponding to different defect areas is different, the defect area is matched to the matching frequency band; the preset defect area of ​​the frequency band in the prefabricated defective laminate is further determined; and through the second comparison result between the two defect areas, it can be analyzed whether the determined defect equivalent is accurate.

[0109] In some embodiments, the edgeless active contour model image processing technology can be used to extract the defect area in the C-scan image and compare it with the preset defect area of ​​each defect to verify the accuracy of "determining the defect area through the C-scan image", which can be achieved through the following process:

[0110] The edgeless active contour model is a variant of the snake model, and its energy functional form E(C,φ) is shown in formula (8):

[0111]

[0112] Where C is the contour; φ is the level set function, which is used to implicitly represent the contour; μ, λ1, and λ2 are weight parameters; I(x) is the image intensity; c1 and c2 are the average grayscale values ​​inside and outside the contour, respectively; is the Heaviside function corresponding to the level set function, which is used to distinguish the areas inside and outside the contour.

[0113] In some possible implementations, the process of extracting the defect area in the C-scan image by the edgeless active contour model image processing technology is as follows:

[0114] First, the level set function φ is initialized.

[0115] Secondly, the average grayscale value of the inner area c1 and the outer area c2 of the contour is calculated.

[0116] Again, regarding the scattered initial energy function, the fitting error of the internal region is: |I(x)-c1| 2 , and the fitting error in the outer region: |I(x)-c2| 2 .

[0117] Again, update the level set function φ.

[0118] Again, the new means c1 and c2 are calculated through the updated level set function φ.

[0119] Again, check whether the energy converges. If the energy converges, output the segmentation result; if the energy does not converge, return to the step "update the level set function φ" until the energy converges.

[0120] In this way, after obtaining the defect area of ​​the C-scan image through the above process, the defect area is compared with the preset area to determine whether the two areas are consistent. If they are consistent, it means that the method of determining the defect area through the C-scan image is more accurate.

[0121] In some possible implementations, after scanning the prefabricated defective laminate with an ultrasonic phased array detector, multiple types of scanning images corresponding to the prefabricated defective laminate can be obtained, wherein the multiple types of scanning images include: a two-dimensional scanning image corresponding to the prefabricated defective laminate, such as a C-scan image and an S-scan image. Afterwards, the defect depth of the prefabricated defective laminate can be analyzed through the S-scan image, and the defect area of ​​the prefabricated defective laminate can be analyzed through the C-scan image; in order to verify whether the determined defect depth and defect area are accurate, the following process can be used:

[0122] The undetected signal corresponding to the second scanning signal is further transferred to the time-frequency domain for analysis through Hilbert-Huang transform to verify the accuracy of "determining the defect depth of the defective part of the ship laminate through the second scanning image", which can be achieved through the following process:

[0123] First, a Hilbert-Huang transform is performed on the undetected signal corresponding to the second scanning signal to obtain a time-frequency domain signal.

[0124] Here, the nonlinear and non-stationary signal cannot be directly used for Hilbert-Huang transform. Before that, the signal needs to be decomposed by EMD:

[0125] STEP 1: First, use the original signal S(t) (i.e., the undetected signal corresponding to the second scan signal) to find all the extreme maximum points in the time domain signal, and fit the upper envelope of the maximum value e through the cubic spline interpolation algorithm. upper (t). Similarly, the lower envelope of the minimum value is fitted. lower (t), so that all signal amplitudes are within the range of the two envelopes, and the mean envelope m(t) of the envelope is obtained, as shown in formula (9):

[0126]

[0127] STEP 2: Subtract the mean envelope from the original signal S(t) to obtain h1(t) = s(t) - m(t). Determine whether h1(t) is an IMF component. If not, use h1(t) as the source signal to be analyzed in the next step, replacing S(t). Repeat STEP 1 and STEP 2 until h1(t) meets the IMF condition, as shown in formula (10):

[0128] c1(t)=h1(t) (10);

[0129] STEP 3: C1(t) is the first IMF component of the original signal. Subtract S(t) from C1(t) to obtain the residual component r1(t), as shown in formula (11):

[0130] r1(t)=s(t)-c1(t) (11);

[0131] STEP 4: Use r1(t) as the new original signal and repeat STEP1, STEP2, and STEP3 to get the remaining IMF components, which are recorded as c1(t), c2(t), c3(t), and so on. n (t). The whole process is iterated continuously until the decomposed residual component is a monotonic function or a constant, and then EMD completes the screening process of the original signal S(t).

[0132] Through EMD decomposition, the problem that the original signal (i.e., the undetected signal corresponding to the second scan signal) cannot be directly used for Hilbert transform is solved. By using Hilbert-Huang transform to calculate the instantaneous frequency and amplitude of each IMF component, the signal changes can be analyzed and possible defects can be identified. When reconstructing the signal, the peak value and time point of the echo signal can be observed by analyzing the envelope of the signal, and some IMF components can be selectively reconstructed to reduce the interference of noise on the reconstructed signal.

[0133] Hilbert transform can transform the IMF signal C i (t) is transformed into a real signal in the same domain , as shown in formula (12):

[0134]

[0135] The analytical signal represents each intrinsic mode function as the amplitude envelope and phase function of the signal. The analytical function obtained by the IMF signal and the transformed real signal is as shown in formula (13):

[0136]

[0137] in is the complex carrier signal, c i (t)e jθ(t) is a complex envelope signal.

[0138] Perform Hilbert transform on all IMF components, calculate the absolute value of the analytical signal, obtain the envelope of the ultrasonic signal, and then accumulate and reconstruct all signals. The reconstructed signal s′(t) is shown in formula (14):

[0139]

[0140] By performing Hilbert transform on the reconstructed signal, the time-frequency domain signal can be obtained.

[0141] Secondly, the frequency spectrum corresponding to the time-frequency domain signal is compared with the frequency spectrum corresponding to the second frequency domain signal to obtain a spectrum comparison result.

[0142] Thirdly, based on the spectrum comparison result, it is judged whether the determined defect depth and preset defect area of ​​the prefabricated defective laminate are accurate to obtain a judgment result.

[0143] Finally, based on the judgment result and the multiple types of scanned images corresponding to the prefabricated defective laminate, the defect depth and the preset defect area corresponding to the prefabricated defective laminate are updated.

[0144] Here, after obtaining the reconstructed signal s′(t), the reconstructed signal can be subjected to a Hilbert-Huang transform to obtain a spectrum after the Hilbert-Huang transform, and the spectrum after the Hilbert-Huang transform is compared with the spectrum corresponding to the second frequency domain signal. If the two spectra are consistent, it means that the accuracy of "determining the defect depth and preset defect area of ​​the prefabricated defective laminate through two-dimensional scanning images (for example, the C-scan image and S-scan image of the prefabricated defective laminate)" is high. If the two spectra are inconsistent, the defect depth and preset defect area of ​​the prefabricated defective laminate are re-analyzed according to the comparison results. In this way, by further transferring the undetected signal corresponding to the second scanning signal to the time-frequency domain for analysis through the Hilbert-Huang transform, it is possible to accurately determine whether the determined defect depth and preset defect area of ​​the prefabricated defective laminate are accurate.

[0145] In an embodiment of the present invention, a scanned image is obtained by scanning the defective part of the boat laminate; and based on the scanned image, the defect depth and defect type of the defective part of the boat laminate are determined; in this way, by performing a preliminary analysis on the scanned image of the defective part of the boat laminate, the defect depth and defect type of the defective part can be quickly obtained. Afterwards, a prefabricated defective laminate can be accurately constructed based on the defect depth, the defect type and the ply of the boat; and the target frequency band that matches the prefabricated defective laminate is further determined; wherein the energy corresponding to the target frequency band changes regularly with the size of the defect; finally, by combining the energy of the scanned image in each frequency band with the energy corresponding to the target frequency band, the defect equivalent of the boat laminate can be accurately obtained. In this way, by obtaining the internal damage data of the defective parts of the boat laminates, and then combining time domain, frequency domain, time-frequency domain signal processing, etc., the defect depth and defect type of the defective parts of the boat laminates can be accurately determined. Then, by combining the target frequency band of the constructed prefabricated defective laminates, various types of defects and the defect equivalents of the boat laminates can be accurately analyzed.

[0146] In the embodiment of the present invention, ultrasonic phased array technology is used to carry out nondestructive detection and evaluation of defect type, size, and depth from the time domain, frequency domain, and time-frequency domain in combination with image segmentation technology. The type, depth, and size of the defect can be determined more accurately.

[0147] The embodiment of the present invention provides a device for detecting internal defects of a ship laminate. Figure 7 , which shows a schematic diagram of the composition structure of a device for detecting internal defects of a shipboard laminate provided by an embodiment of the present invention, the device 700 comprises:

[0148] An acquisition module 701 is used to acquire internal damage data of defective parts of a ship laminate;

[0149] A first determination module 702 is used to determine the defect depth and defect type of the defective part of the ship laminate based on the internal damage data;

[0150] A construction module 703 is used to construct a prefabricated defective laminate based on the defect depth, the defect type and the ply of the boat;

[0151] The second determination module 704 is used to determine the target frequency band that matches the prefabricated defective laminate; wherein the energy corresponding to the target frequency band changes regularly with the size of the defect;

[0152] The third determination module 705 is used to determine the defect equivalent of the ship laminate based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band.

[0153] In some possible implementations, the acquisition module 801 is also used to perform phased array ultrasonic scanning on the defective part of the boat laminate to obtain a first scanning signal; convert the first scanning signal to obtain multiple types of converted signals; determine multiple types of scanning images of the defective part of the boat laminate based on the multiple types of converted signals; and use the multiple types of scanning images and the first scanning signal as the internal damage data.

[0154] In some possible implementations, the first determination module 702 is further configured to obtain a first scanning image in the internal damage data; and determine a defect depth of a defective portion of the ship laminate based on the first scanning image.

[0155] In some possible implementations, the first determination module 702 is further used to perform frequency domain conversion on an undetected signal corresponding to a first scanning signal corresponding to the internal damage data to obtain a first frequency domain signal; based on the frequency spectrum corresponding to the first frequency domain signal and a preset relationship table, determine the defect type of the defective part of the ship laminate; wherein the preset relationship table is used to characterize the correspondence between the frequency spectrum and the defect type.

[0156] In some possible implementations, the second determination module 704 is further used to perform phased array ultrasonic scanning on the prefabricated defective laminate to obtain a second scanning signal corresponding to the prefabricated defective laminate; perform frequency domain conversion on an undetected signal corresponding to the second scanning signal to obtain a second frequency domain signal; perform energy extraction on the second frequency domain signal to obtain the energy of the second frequency domain signal in each frequency band; and determine a target frequency band that changes regularly with the size of the defect based on the energy of the second frequency domain signal in each frequency band.

[0157] In some possible implementations, the third determination module 705 is further used to compare the energy of the internal damage data in each frequency band with the energy corresponding to the target frequency band to obtain a first comparison result; and determine the defect equivalent of the ship laminate based on the first comparison result.

[0158] In some possible implementations, the third determination module 705 is further configured to obtain a mapping relationship between energy in each frequency band and a defect equivalent; and determine the defect equivalent of the ship laminate based on the first comparison result and the mapping relationship.

[0159] In some possible implementations, the third determination module 705 is further used to determine the defect area of ​​the defective part of the boat laminate based on the second scanning image in the internal damage data; compare the defect area with the preset defect areas of various defects of the prefabricated defective laminate to obtain a second comparison result; based on the second comparison result and the preset correspondence, determine whether the determined defect equivalent of the boat laminate is accurate; wherein the preset correspondence is used to characterize the correspondence between the preset defect areas of the various defects and the energy of each frequency band.

[0160] In some possible implementations, the first determination module 702 is further used to perform a Hilbert-Huang transform on the undetected signal corresponding to the second scanning signal to obtain a time-frequency domain signal; compare the frequency spectrum corresponding to the time-frequency domain signal with the frequency spectrum corresponding to the second frequency domain signal to obtain a spectrum comparison result; based on the spectrum comparison result, determine whether the determined defect depth and preset defect area of ​​the prefabricated defective laminate are accurate to obtain a determination result; based on the determination result and multiple types of scanning images corresponding to the prefabricated defective laminate, update the defect depth and preset defect area corresponding to the prefabricated defective laminate.

[0161] Optionally, the transmission medium can be a wired link (for example, but not limited to, coaxial cable, optical fiber and digital subscriber line (DSL), etc.) or a wireless link (for example, but not limited to, wireless Fidelity (WIFI), Bluetooth and mobile device network, etc.). It should be noted that: the device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, the method embodiments provided in the above embodiments belong to the same concept. The specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0162] Figure 8 is a schematic diagram of the structure of a computer device provided by an embodiment of the present invention. Figure 8 As shown, the computer device 800 includes: a memory 801, a processor 802, and a computer program 803 stored in the memory 801 and running on the processor 802, wherein when the processor 802 executes the computer program 803, the computer device can execute any of the aforementioned methods for detecting internal defects of ship laminates.

[0163] In addition, an embodiment of the present invention also protects a system, which may include a memory and a processor, wherein an executable program code is stored in the memory, and the processor is used to call and execute the executable program code to perform a method for detecting internal defects of a shipboard laminate provided by an embodiment of the present invention. This embodiment can divide the system into functional modules according to the above method example. For example, it can correspond to each functional module, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic, which is only a logical function division, and there may be other division methods in actual implementation. It should be noted that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here.

[0164] It should be understood that the device provided in this embodiment is used to perform the above-mentioned method for detecting internal defects of a ship laminate, so the same effect as the above-mentioned implementation method can be achieved. In the case of an integrated unit, the device may include a processing module and a storage module. Among them, when the device is applied to a device, the processing module can be used to control and manage the actions of the device. The storage module can be used to support the device to execute mutual program codes, etc. Among them, the processing module can be a processor or a controller, which can implement or execute various exemplary logic boxes, modules and circuits described in conjunction with the disclosure of the present invention. The processor can also be a combination that implements a computing function, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc., and the storage module can be a memory.

[0165] In addition, the device provided in the embodiment of the present invention may be a chip, a component or a module, and the chip may include a connected processor and a memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip may execute a method for detecting internal defects of a ship laminate provided in the above embodiment. This embodiment also provides a computer-readable storage medium, in which a computer program code is stored, and when the computer program code is run on a computer, the computer executes the above-mentioned related method steps to implement a method for detecting internal defects of a ship laminate provided in the above embodiment.

[0166] This embodiment also provides a computer program product. When the computer program product is run on a computer, the computer executes the above-mentioned related steps to implement a method for detecting internal defects of a shipboard laminate provided in the above embodiment. Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here. Through the description of the above implementation mode, the technicians in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In practical applications, the above-mentioned function allocation can be completed by different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by the present invention, it should be understood that the disclosed device and method can be implemented in other ways. For example, the device embodiment described above is only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, which may be electrical, mechanical or other forms.

[0167] It should be noted that the sequence of the above-mentioned embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or may be advantageous. The various embodiments in this specification are described in a progressive manner, and the same and similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments. The above content is only a specific implementation method of the present invention, but the protection scope of the present invention is not limited to this. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered within the protection scope of the present invention.

Claims

1. A method for detecting internal defects of a shipboard laminate, characterized in that: The method for detecting internal defects of boat laminates comprises: Obtain internal damage data of defective parts of ship laminates; Determining the defect depth and defect type of the defective portion of the boat laminate based on the internal damage data; constructing a prefabricated defective laminate based on the defect depth, the defect type and the ply of the boat; Determine a target frequency band that matches the prefabricated defective laminate; wherein the energy corresponding to the target frequency band changes regularly with the size of the defect; Based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band, the defect equivalent of the ship laminate is determined.

2. A method for detecting internal defects of a shipboard laminate according to claim 1, characterized in that: The obtaining of internal damage data of defective parts of the boat laminate comprises: Performing phased array ultrasonic scanning on the defective part of the boat laminate to obtain a first scanning signal; Converting the first scanning signal to obtain multiple types of converted signals; Determining multiple types of scanned images of defective parts of the boat laminate based on the multiple types of converted signals; The multiple types of scan images and the first scan signal are used as the internal damage data.

3. A method for detecting internal defects of shipboard laminates according to claim 1, characterized in that: The step of determining the defect depth of the defective portion of the ship laminate based on the internal damage data comprises: Acquire a first scan image in the internal damage data; Based on the first scanning image, a defect depth of a defective portion of the ship laminate is determined.

4. A method for detecting internal defects of shipboard laminates according to claim 1, characterized in that: Determining the defect type of the defective part of the boat laminate based on the internal damage data includes: Performing frequency domain conversion on an undetected signal corresponding to a first scanning signal of the internal damage data to obtain a first frequency domain signal; Based on the frequency spectrum corresponding to the first frequency domain signal and a preset relationship table, the defect type of the defective part of the ship laminate is determined; wherein the preset relationship table is used to characterize the correspondence between the frequency spectrum and the defect type.

5. The method for detecting internal defects of shipboard laminates according to claim 1, characterized in that: The step of determining a target frequency band that matches the prefabricated defective laminate comprises: Performing phased array ultrasonic scanning on the prefabricated defective laminate to obtain a second scanning signal corresponding to the prefabricated defective laminate; Performing frequency domain conversion on the undetected signal corresponding to the second scanning signal to obtain a second frequency domain signal; Performing energy extraction on the second frequency domain signal to obtain energy of the second frequency domain signal in each frequency band; Based on the energy of the second frequency domain signal in each frequency band, a target frequency band that changes regularly with the size of the defect is determined.

6. The method for detecting internal defects of shipboard laminates according to claim 1, characterized in that: The determining the defect equivalent of the shipboard laminate based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band includes: Compare the energy of the internal damage data in each frequency band with the energy corresponding to the target frequency band to obtain a first comparison result; Based on the first comparison result, a defect equivalent of the ship laminate is determined.

7. A method for detecting internal defects of shipboard laminates according to claim 6, characterized in that: The step of determining the defect equivalent of the ship laminate based on the first comparison result includes: Obtain the mapping relationship between the energy of each frequency band and the defect equivalent; Based on the first comparison result and the mapping relationship, a defect equivalent of the ship laminate is determined.

8. The method for detecting internal defects of shipboard laminates according to claim 1, characterized in that: After determining the defect equivalent of the shipboard laminate based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band, the method further includes: Determining a defect area of ​​a defective portion of the ship laminate based on a second scan image in the internal damage data; Comparing the defect area with preset defect areas of various defects of the prefabricated defective laminate to obtain a second comparison result; Based on the second comparison result and the preset corresponding relationship, it is judged whether the determined defect equivalent of the boat laminate is accurate; wherein the preset corresponding relationship is used to characterize the corresponding relationship between the preset defect area of ​​each type of defect and the energy of each frequency band.

9. A method for detecting internal defects of shipboard laminates according to claim 5, characterized in that: The method further comprises: Performing Hilbert-Huang transform on the undetected signal corresponding to the second scanning signal to obtain a time-frequency domain signal; Comparing the frequency spectrum corresponding to the time-frequency domain signal with the frequency spectrum corresponding to the second frequency domain signal to obtain a spectrum comparison result; Based on the spectrum comparison result, judging whether the determined defect depth and preset defect area of ​​the prefabricated defective laminate are accurate, and obtaining a judgment result; Based on the judgment result and the multiple types of scanned images corresponding to the prefabricated defective laminate, the defect depth and the preset defect area corresponding to the prefabricated defective laminate are updated.

10. A device for detecting internal defects of shipboard laminates, characterized in that: The device comprises: An acquisition module, used to acquire internal damage data of defective parts of the ship laminate; A first determination module, configured to determine a defect depth and a defect type of a defective portion of the ship laminate based on the internal damage data; A construction module, configured to construct a prefabricated defective laminate based on the defect depth, the defect type and the ply of the boat; The second determination module is used to determine the target frequency band that matches the prefabricated defective laminate; wherein the energy corresponding to the target frequency band changes regularly with the size of the defect; The third determination module is used to determine the defect equivalent of the ship laminate based on the energy of the internal damage data in each frequency band and the energy corresponding to the target frequency band.

Images