Stone structure building detection method based on concrete ultrasonic fault detection scanner

Abstract

The invention relates to the technical field of stone structure ultrasonic detection, in particular to a stone structure building detection method based on a concrete ultrasonic fault detection scanner, and the method comprises the steps: obtaining the initial signal intensity when an ultrasonic signal is transmitted by using the ultrasonic fault detection scanner; obtaining an ultrasonic reflection signal after the ultrasonic signal is reflected at each reflection point under each scanning layer, the intensity of the reflection signal after reflection, and the signal propagation duration; the method comprises the following steps of: obtaining a signal propagation time difference, a signal intensity difference, a signal difference index, a signal disorder degree, a defect evaluation coefficient, a seam recognition degree and a seam correction coefficient of each reflection point under each scanning layer, correcting the intensity of a reflection signal, performing three-dimensional reconstruction on a constructed tomography graph, and detecting internal defects of a stone structure building. According to the method, the interference of the reflection points on the splicing seams during stone splicing is reduced, the accuracy of detecting the internal defects of the stone structure building is improved, and the stability detection of the stone structure building is improved.

Description

Technical Field

[0001] The present application relates to the technical field of ultrasonic detection of stone structures, and in particular to a method for detecting stone structure buildings based on a concrete ultrasonic tomography detection scanner. Background Art

[0002] Stone structure buildings refer to buildings or structures that use natural stone as the main material. As time goes by, many ancient stone buildings will show varying degrees of damage and aging, so the stability of ancient stone buildings is tested. Ultrasonic tomography scanner is a multifunctional ultrasonic matrix non-destructive testing instrument that uses pulse echo technology and synthetic aperture focusing technology to achieve detection functions. It can detect defects such as cavities, cracks and gaps inside the stone.

[0003] However, stone structure buildings are often obtained by stacking and splicing multiple stones. Therefore, they are affected by the flatness of the stone surface and the inevitable gaps between the stones, which interfere with the judgment of the internal structure of the stone. This leads to low accuracy in detecting crack defects in stone structure buildings, affecting the stability detection of stone structure buildings. Summary of the invention

[0004] In order to solve the above technical problems, a stone structure building detection method based on a concrete ultrasonic tomography detection scanner is provided to solve the existing problems.

[0005] The solution to the technical problem of this application is to provide a stone structure building detection method based on a concrete ultrasonic tomography detection scanner, comprising the following steps: An ultrasonic tomography scanner is used to obtain the initial signal strength of the ultrasonic signal when it is emitted, and the ultrasonic reflection signal after the ultrasonic signal is reflected at each reflection point under each scanning layer, the reflection signal strength after reflection, and the signal propagation time; The signal propagation time difference of each reflection point under each scanning layer is obtained by the deviation of the signal propagation time length of each reflection point under each scanning layer; the deviation of the signal intensity of the ultrasonic reflection signal of each reflection point under each scanning layer in the frequency domain is analyzed to determine the signal intensity difference of each reflection point under each scanning layer; the signal propagation time difference and the signal intensity difference are combined to obtain the signal difference index of each reflection point under each scanning layer; According to the difference between the initial signal intensity after the ultrasonic signal is emitted and the reflected signal intensity after the reflection at each reflection point, as well as the complexity of the ultrasonic reflection signal, the signal disorder degree of each reflection point under each scanning layer is determined, and the signal difference index is integrated to obtain the defect assessment coefficient of each reflection point under each scanning layer; Based on the defect assessment coefficient, all reflection points are divided into potential defect points and normal reflection points; the distribution of the potential defect points under each scanning layer and the other potential defect points in its local range, as well as the similarity of the ultrasonic reflection signals, are analyzed to determine the seam recognition degree of the potential defect points under each scanning layer, wherein the seam recognition degree of the normal reflection point is a preset value; Based on the seam recognition degree and the defect assessment coefficient, the gap correction coefficient of each reflection point under each scanning layer is obtained, the reflection signal intensity of each reflection point under each scanning layer is corrected, and each frame of the corrected two-dimensional tomography image is constructed. All frames of the two-dimensional tomography images are three-dimensionally reconstructed to detect internal defects of stone structure buildings.

[0006] Preferably, obtaining the signal propagation time difference of each reflection point under each scanning layer includes: A threshold segmentation algorithm is used to obtain a segmentation threshold of the signal propagation time of all reflection points under each scanning layer, which is recorded as a first segmentation threshold; the average of the signal propagation time of all reflection points under each scanning layer whose signal propagation time is less than the first segmentation threshold is used as the basic propagation time of each scanning layer; The difference between the signal propagation time length of each reflection point under each scanning layer and the basic propagation time length is used as the signal propagation time difference of each reflection point under each scanning layer.

[0007] Preferably, determining the signal strength difference of each reflection point under each scanning layer includes: By using frequency domain analysis, the spectrum of the ultrasonic reflection signal of each reflection point under each scanning layer is obtained, and the signal amplitude of the fundamental wave in the spectrum is obtained; A threshold segmentation algorithm is used to obtain a segmentation threshold of the signal amplitude corresponding to all reflection points under each scanning layer, which is recorded as a second segmentation threshold; the average of the signal amplitudes corresponding to all reflection points under each scanning layer whose signal amplitudes are less than the second segmentation threshold is taken as the basic signal strength of each scanning layer; The difference between the signal amplitude and the signal basic intensity at each reflection point under each scanning layer is used as the signal intensity difference at each reflection point under each scanning layer.

[0008] Preferably, the signal difference index of each reflection point under each scanning layer is the sum of the signal propagation time difference and the signal intensity difference.

[0009] Preferably, the step of determining the signal disorder degree of each reflection point under each scanning layer includes: Perform curve fitting on the ultrasonic reflection signals of each reflection point under each scanning layer to obtain the goodness of fit of the fitting curve; The difference between the initial signal strength and the signal amplitude is recorded as energy attenuation; The signal disorder degree is the inverse of the product of the energy attenuation and the goodness of fit.

[0010] Preferably, the defect assessment coefficient is the sum of the signal disorder degree and the signal difference index.

[0011] Preferably, the step of distinguishing all reflection points into potential defect points and normal reflection points includes: The defect assessment coefficients of all reflection points under each scanning layer are threshold segmented, which is recorded as a third segmentation threshold; reflection points whose defect assessment coefficients are greater than the third segmentation threshold are recorded as potential defect points, otherwise, they are recorded as normal reflection points.

[0012] Preferably, determining the seam recognition degree of each potential defect point under each scanning layer includes: Selecting multiple potential defect points closest to any potential defect point under each scanning layer to form a local defect set of any potential defect point; Performing linear fitting on the position coordinates of all potential defect points in the local defect set, recording the fitting straight line as a gap distribution line; recording the average of the distances from all potential defect points in the local defect set to the gap distribution line as the average distance; The cumulative sum of the similarities of the ultrasonic reflection signals between any potential defect point and all the potential defect points in the local defect set is calculated, and the ratio of the cumulative sum to the average distance is used as the seam recognition degree of any potential defect point.

[0013] Preferably, the gap correction coefficient is a normalized result of the ratio of the defect assessment coefficient to the seam recognition degree.

[0014] Preferably, the step of correcting the reflected signal intensity of each reflection point under each scanning layer, constructing each frame of the corrected two-dimensional tomographic scan image, and three-dimensionally reconstructing all frames of the two-dimensional tomographic scan images includes: The product of the reflection signal intensity of each reflection point under each scanning layer and the gap correction coefficient is recorded as the corrected signal intensity of each reflection point under each scanning layer; the corrected signal intensity of all reflection points under each scanning layer is imaged to construct a corrected two-dimensional tomographic scan image of each frame; and the corrected two-dimensional tomographic scan images of all frames are three-dimensionally reconstructed.

[0015] This application has at least the following beneficial effects: The present application obtains the signal propagation time difference and signal strength difference of each reflection point under each scanning layer through the signal propagation time of each reflection point under each scanning layer and the offset of the signal strength of the ultrasonic reflection signal in the frequency domain; obtains the signal difference index of each reflection point under each scanning layer, which has the beneficial effect of taking into account the difference in signal propagation time and signal strength of different reflection points, so as to reflect the signal difference between the reflection point at the gap defect and the normal reflection point in the stone, and further explains the possible situation that the reflection point is a gap defect; determines the signal disorder degree of each reflection point under each scanning layer; and fuses the signal difference index to obtain the defect evaluation coefficient of each reflection point under each scanning layer, which has the beneficial effect of taking into account the attenuation of the ultrasonic signal at different reflection points in the stone, and the noise in the ultrasonic reflection signal of different reflection points, so as to explain that the corresponding reflection point is affected by the complexity of the signal propagation path and the unevenness of the internal defect surface, so as to reflect that the corresponding reflection point is a gap defect. The invention discloses a method for reconstructing the three-dimensional tomography images of all frames, and ... BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The stone structure building detection method based on concrete ultrasonic tomography detection scanner of the present application is further described in detail below with reference to the accompanying drawings.

[0017] Figure 1 A flowchart of the steps of a stone structure building detection method based on a concrete ultrasonic tomography detection scanner provided in an embodiment of the present application; Figure 2 A flowchart of the steps of a method for obtaining a signal difference index of each reflection point under each scanning layer provided in an embodiment of the present application; Figure 3 A flowchart of the steps of the method for obtaining the gap correction coefficient provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the stone structure building detection method based on the concrete ultrasonic tomography detection scanner proposed in the present application is further described in detail below in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0019] 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 application belongs.

[0020] See also Figure 1 , which shows a flowchart of a method for detecting a stone structure building based on a concrete ultrasonic tomography detection scanner provided by an embodiment of the present application, the method comprising the following steps: Step 1: Use an ultrasonic tomography scanner to obtain the initial signal strength when the ultrasonic signal is emitted, obtain the ultrasonic reflection signal after the ultrasonic signal is reflected at each reflection point under each scanning layer, the reflection signal strength after reflection, and the signal propagation time.

[0021] As time goes by, many ancient stone buildings will show varying degrees of damage and aging, so the stability detection of ancient stone buildings has become an important measure for cultural relics protection. Ultrasonic tomography is used to perform non-destructive detection of internal defects of stone buildings. The internal defects mainly include cracks, cavities and weathering. When using ultrasonic tomography to detect internal defects of stone buildings, the same-side direct wave method is generally used, that is, the transmitter and receiver are on the same side of the building.

[0022] The probe in the ultrasonic tomography scanner consists of a 4×12 dry-point transducer array and a control unit. The transducer is a signal transmitting and receiving device that can emit periodic pulses. It uses pulse echo technology and synthetic aperture focusing technology to achieve detection functions, and can detect inclusions, cavities, cracks, cracks and other defects inside the stone. Among them, the ultrasonic tomography scanner supports panoramic B scanning, panoramic C scanning and panoramic D scanning modes.

[0023] When performing non-destructive testing on stone structures using an ultrasonic tomography scanner, the stone components must be kept dry. Therefore, outdoor stone structures should be tested on sunny days with air humidity below 25%, and there should be no precipitation in the three days before the test.

[0024] Therefore, an A1040 MIRA ultrasonic tomography scanner is used to perform a panoramic B scan on the stone structure building. The stone structure building is a three-dimensional structure, which corresponds to the X-axis, Y-axis and Z-axis. The panoramic B scan refers to the scanner moving and scanning along the side of the building corresponding to the Y-axis in the three-dimensional structure, and each moving position is recorded as each scanning layer. Under each scanning layer, the signal transmitting device of the A1040 MIRA ultrasonic tomography scanner transmits ultrasonic pulse signals of different angles to the inside of the stone, and signal reflections are generated inside the stone due to medium transformation at different positions, and the signal is received by the signal receiving device. The different positions where signal reflections are generated inside the stone under each scanning layer are recorded as reflection points. The synthetic focusing technology is used to obtain the ultrasonic reflection signals and signal propagation time of each reflection point under each scanning layer. The initial signal strength when the ultrasonic wave is emitted is obtained from the signal transmitting device of the ultrasonic tomography scanner, and the reflected signal strength after the signal receiving device receives the ultrasonic wave reflections from each reflection point under each scanning layer. It should be noted that the signal propagation time refers to the interval time between the ultrasonic signal emitted by the signal transmitting end of the ultrasonic tomography scanner and the ultrasonic signal received by the signal receiving end.

[0025] In this embodiment, the operating frequency of the A1040 MIRA ultrasonic tomography scanner is 100KHz. As other implementation modes, the implementer can set it according to the actual situation. Among them, the process of performing panoramic B scanning by the A1040 MIRA ultrasonic tomography scanner is a well-known technology and will not be repeated here.

[0026] At this point, the ultrasonic reflection signal and signal propagation time of each reflection point under each scanning layer, as well as the initial signal strength when the ultrasonic wave is emitted and the reflection signal strength after the ultrasonic wave is reflected at each reflection point under each scanning layer are obtained.

[0027] Step 2, obtaining the signal propagation time difference of each reflection point under each scanning layer through the offset of the signal propagation time length of each reflection point under each scanning layer; analyzing the offset of the signal intensity of the ultrasonic reflection signal of each reflection point under each scanning layer in the frequency domain, and determining the signal intensity difference of each reflection point under each scanning layer; fusing the signal propagation time difference and the signal intensity difference to obtain the signal difference index of each reflection point under each scanning layer.

[0028] When using an ultrasonic tomography scanner for detection, if there is a medium transition from stone to air, or from stone to other materials inside the stone structure, part of the ultrasonic signal will be diffracted and propagated through the defect, while part of the signal will be directly transmitted to the defect, causing the signal to be scattered and reflected.

[0029] At each scanning layer, when scanning the defective points inside the stone, due to the diffraction of the ultrasonic signal, or a part of the ultrasonic pulse signal directly passes through the pores, the propagation speed of the ultrasonic signal in the air is slow, and the signal attenuation is small, resulting in a longer propagation time and less signal attenuation at the reflection point at the defect compared to the normal reflection point; secondly, due to the uneven surface of the internal defect of the stone structure and the complex signal propagation path, the signal receiving device receives more signal noise; based on the above analysis, the signal difference index is determined, and the step flow chart of the method for obtaining the signal difference index of each reflection point at each scanning layer provided in the embodiment of the present application is as follows Figure 2 shown.

[0030] First, the signal propagation time difference is determined by the difference in signal propagation time of all reflection points under each scanning layer, which is: A threshold segmentation algorithm is used to obtain a segmentation threshold of the signal propagation time of all reflection points under each scanning layer, which is recorded as the first segmentation threshold; In this embodiment, the maximum inter-class variance method is used to obtain the segmentation threshold, wherein the maximum inter-class variance method is a well-known technology and will not be described in detail here.

[0031] The average of the signal propagation durations of all reflection points whose signal propagation durations are less than the first segmentation threshold in each scanning layer is used as the basic propagation duration of each scanning layer; The difference between the signal propagation time length of each reflection point under each scanning layer and the basic propagation time length is used as the signal propagation time difference of each reflection point under each scanning layer; In this embodiment, the absolute value of the difference between the signal propagation time length of each reflection point under each scanning layer and the basic propagation time length is used as the signal propagation time difference of each reflection point under each scanning layer.

[0032] It should be noted that if the reflection point is located at a defect in the stone, there will be gaps or cracks at the defect. The signal at the reflection point will be diffracted or directly projected at the defect, causing the signal to propagate in the air for a longer time. The greater the time difference in signal propagation, the more likely it is that the stone structure building has defects at the reflection point.

[0033] Furthermore, the signal strength difference is determined by the difference in signal strength attenuation of the ultrasonic reflection signals at all reflection points under each scanning layer, specifically: By using frequency domain analysis, the spectrum of the ultrasonic reflection signal of each reflection point under each scanning layer is obtained, and the signal amplitude of the fundamental wave in the spectrum is obtained; In this embodiment, discrete Fourier transform is used to obtain the spectrum diagram, wherein discrete Fourier transform is a well-known technology and will not be described in detail here.

[0034] A threshold segmentation algorithm is used to obtain a segmentation threshold of the signal amplitude corresponding to all reflection points under each scanning layer, which is recorded as a second segmentation threshold; Taking the average of the signal amplitudes corresponding to all reflection points whose signal amplitudes are less than the second segmentation threshold in each scanning layer as the basic signal strength of each scanning layer; The difference between the signal amplitude corresponding to each reflection point under each scanning layer and the signal basic strength is recorded as the signal strength difference of each reflection point under each scanning layer; In this embodiment, the absolute value of the difference between the signal amplitude corresponding to each reflection point under each scanning layer and the signal basic intensity is recorded as the signal intensity difference of each reflection point under each scanning layer.

[0035] It should be noted that if the reflection point is located at a defect in the stone, there will be a gap or crack at the defect. In this case, the ultrasonic reflection signal at the reflection point will be diffracted or directly projected at the defect, resulting in a smaller signal attenuation. The greater the difference in signal intensity, the more likely it is that the stone structure building will have a gap or crack defect at the reflection point.

[0036] Further, based on the signal propagation time difference and the signal strength difference, a signal difference index is determined, specifically: The sum of the signal propagation time difference and the signal strength difference is used as the signal difference index of each reflection point under each scanning layer; It should be noted that the larger the obtained signal difference index is, the greater the possibility that defects occur at the position of the corresponding reflection point in the stone structure building.

[0037] At this point, the signal difference index of each reflection point under each scanning layer is obtained.

[0038] Step 3: Determine the signal disorder of each reflection point under each scanning layer according to the difference between the initial signal strength after the ultrasonic signal is emitted and the reflected signal strength after reflection at each reflection point, as well as the complexity of the ultrasonic reflection signal; and fuse the signal difference index to obtain the defect assessment coefficient of each reflection point under each scanning layer.

[0039] Furthermore, the difference between the initial signal strength during ultrasonic emission and the signal strength of the ultrasonic reflection signal, as well as the trend change of signal attenuation, are analyzed to determine the signal disorder, specifically: Perform curve fitting on the ultrasonic reflection signals of each reflection point under each scanning layer to obtain the goodness of fit of the fitting curve; In this embodiment, the least square method is used for curve fitting, wherein the least square method and the extreme of goodness of fit are well-known technologies and will not be described in detail here.

[0040] The difference between the initial signal strength and the signal amplitude is recorded as energy attenuation; In this embodiment, the difference between the initial signal strength and the signal amplitude is recorded as the energy attenuation.

[0041] The reciprocal of the product of the energy attenuation and the goodness of fit is used as the signal disorder of each reflection point under each scanning layer; It should be noted that since the ultrasonic pulse signal will inevitably attenuate when propagating inside a stone structure building, the energy attenuation cannot be zero. The smaller the obtained energy attenuation, the smaller the signal attenuation, indicating that the signal propagates in the air for a longer time, reflecting that the corresponding reflection point is more likely to have a defect; secondly, for the reflection point located at the defect inside the stone structure building, due to the complexity of the signal propagation path and the uneven surface of the internal defect, more noise points appear in the received signal, resulting in greater difficulty in fitting the received signal, and the smaller the goodness of fit; the greater the obtained signal disorder, the more likely the corresponding reflection point is located at the gap defect inside the stone structure building.

[0042] Further, based on the signal disorder degree and the signal difference index, a defect assessment coefficient is determined, specifically: The sum of the signal disorder degree and the signal difference index is used as the defect assessment coefficient of each reflection point under each scanning layer; It should be noted that since the defects in the stone are often scattered inside the stone structure building, for the reflection points corresponding to the non-defective parts, the attenuation degree and propagation time of the ultrasonic signal are roughly the same, and the obtained signal difference index is small. Secondly, the stone texture at the non-defective parts is relatively uniform, so the propagation of the ultrasonic pulse signal is basically consistent, so that the received signal has fewer noise points and the signal disorder is smaller. The smaller the obtained defect assessment coefficient, the less likely it is that the corresponding reflection point is located at the gap or crack defect inside the stone structure building, and the more likely it is to be a normal reflection point. Conversely, the more likely it is that the corresponding reflection point is located at the gap or crack defect inside the stone structure building, and the more likely it is to be a reflection point at the defect.

[0043] At this point, the defect assessment coefficient of each reflection point under each scanning layer is obtained.

[0044] Step 4: Based on the defect assessment coefficient, all reflection points are divided into potential defect points and normal reflection points; the distribution of the potential defect points under each scanning layer and the other potential defect points in its local range, as well as the similarity of the ultrasonic reflection signals, are analyzed to determine the seam recognition degree of the potential defect points under each scanning layer, wherein the seam recognition degree of the normal reflection point is a preset value.

[0045] In stone structural buildings, in addition to the defects of cracks and gaps inside the stone caused by mechanical bearing, weathering and aging, there are also joints formed at the joints when multiple stones are stacked. These joints are formed due to the stacking and splicing of stones, which can easily interfere with the identification and detection of crack defects in stone structural buildings.

[0046] In stone structure buildings, the quality of stone is often required to be high. Therefore, the difference between joints and crack defect joints is that for normal joints, the distribution of joints is often relatively regular, that is, if there are joints, their distribution basically presents horizontal and vertical distribution characteristics. For crack defect joints, their cause is often due to uneven stress or weathering inside the stone, so the distribution direction of crack defect joints is relatively random.

[0047] Due to the requirements for the overall beauty and durability of stone structure buildings, the stone surface of stone structure buildings is relatively smooth. At the same time, the width of the joints in the stone stacking is basically the same. Therefore, for different reflection points on the joints, the similarity of the corresponding ultrasonic reflection signals is relatively high. For crack defect seams, due to the different causes of internal defects in the stone, the surface of the crack defect seams is uneven and the size of the crack defect seams is uneven. Therefore, the similarity of the corresponding ultrasonic reflection signals for different reflection points on the same crack defect seams is relatively low.

[0048] Based on the above analysis, the potential defect points are obtained through the defect assessment coefficient, specifically: Performing threshold segmentation on the defect assessment coefficients of all reflection points under each scanning layer, recorded as a third segmentation threshold; Recording the reflection points whose defect assessment coefficient is greater than the third segmentation threshold as potential defect points, and vice versa, as normal reflection points; In this embodiment, the defect assessment coefficients of all reflection points under each scanning layer are threshold segmented by a cross-validation method, wherein cross-validation is a well-known technique and will not be described in detail herein.

[0049] Selecting multiple potential defect points closest to any potential defect point under each scanning layer to form a local defect set of any potential defect point; In this embodiment, 25 potential defect points closest to any potential defect point under each scanning layer are selected to form a local defect set of any potential defect point. As other implementation methods, the implementer can set them according to actual conditions.

[0050] Performing linear fitting on the position coordinates of all potential defect points in the local defect set, and recording the fitting straight line as a gap distribution line; In this embodiment, the least square method is used for linear fitting, wherein the least square method is a well-known technology and will not be described in detail here.

[0051] It should be noted that the local defect set can be regarded as a set of reflection points on a joint or crack defect, and the gap distribution line reflects the gap distribution of potential reflection points.

[0052] Further, according to the similarity between the ultrasonic reflection signals between any potential defect point and the potential defect points in the local defect set, and the distance between the potential defect point and the gap distribution line, the seam recognition degree is calculated, specifically: The average value of the distances from all potential defect points in the local defect set to the gap distribution line is recorded as the average distance; In this embodiment, the average value of the Euclidean distances from all potential defect points in the local defect set to the gap distribution line is recorded as the average distance.

[0053] Calculate the cumulative sum of the similarities of the ultrasonic reflection signals between any potential defect point and all potential defect points in the local defect set, and use the ratio of the cumulative sum to the average distance as the seam recognition degree of any potential defect point under each scanning layer, wherein the seam recognition degree of the normal reflection point is a preset value; In this embodiment, the preset value is 25. If any potential defect point is a reflection point on the joint seam, theoretically, the similarity of the ultrasonic reflection signal between any potential defect point and all potential defect points in its local defect set is 1. If there is a high similarity, the cumulative sum is 25. Secondly, all potential defect points in the local defect set are reflection points on the joint seam, and the distance to the gap distribution line is 0. Therefore, the maximum seam recognition degree is 25, which means that for the potential defect point, it is a reflection point of the joint seam and does not belong to a crack defect seam. Therefore, for a normal reflection point, it does not belong to a crack defect seam either. Therefore, the seam recognition degree of a normal reflection point is 25.

[0054] In this embodiment, the degree of similarity is measured by calculating the cosine similarity, that is, calculating the cumulative sum of the cosine similarities of the ultrasonic reflection signals between any potential defect point and all the potential defect points in its local defect set, wherein the calculation of the cosine similarity is a well-known technology and will not be repeated here. As other implementation methods, the implementer may adopt other methods of the prior art, such as the Pearson correlation coefficient, etc., and this embodiment does not impose any special restrictions on this.

[0055] In this embodiment, the calculation method of the seam recognition degree of any potential defect point in each scanning layer is:

[0056] in, For the Scan layer The seam identification of potential defect points, For the Scan layer The average distance between all potential defect points in the local defect set of potential defect points and the gap distribution line is the average distance. For the Scan layer The ultrasonic reflection signal of a potential defect point For the first scanning layer The local defect set of potential defect points The ultrasonic reflection signal of a potential defect point For the Scan layer The number of all potential defect points in the local defect set of potential defect points, Indicates the calculation of similarity. In order to preset a value greater than 0 and avoid the denominator being 0, in this embodiment, the value of is 1. As for other implementation methods, the implementer can set it according to the actual situation.

[0057] It should be noted that if The first potential defect point is a reflection point on the joint, and all potential defect points in the local defect set of the potential defect point are regularly distributed, so the average distance is smaller; at the same time, since the surface of the stone joint is flat and uniform in size, the first potential defect point is uniform in size. The similarity of the ultrasonic reflection signal between a potential defect point and other potential defect points in its local defect set is generally high. The larger the cumulative sum is, the greater the seam recognition degree is, which means that the corresponding potential defect point is more likely to be a reflection point on the splicing seam.

[0058] At this point, the seam recognition degree of each reflection point under each scanning layer is obtained.

[0059] Step 5, based on the seam recognition degree and the defect assessment coefficient, obtain the gap correction coefficient of each reflection point under each scanning layer, correct the reflection signal intensity of each reflection point under each scanning layer, construct each frame of the corrected two-dimensional tomography image, reconstruct all frames of the two-dimensional tomography images in three dimensions, and detect internal defects of the stone structure building.

[0060] Furthermore, in order to reduce the interference of the potential defect points on the joint seam under each scanning layer on the reflection points on the crack defect seam, the gap correction coefficient is determined based on the defect assessment coefficient and the seam recognition degree, specifically: The normalized result of the ratio of the defect assessment coefficient to the seam recognition degree is used as the gap correction coefficient of each reflection point under each scanning layer; In this embodiment, the sigmoid function is used for normalization processing, wherein the sigmoid function is a well-known technology and will not be described in detail here. As other implementation methods, the implementer may adopt other methods of the prior art, such as the tanh function, etc. This embodiment does not impose any special restrictions on this.

[0061] It should be noted that if there is a joint or crack gap at the reflection point, the defect assessment coefficient of the reflection point is large, indicating that there may be a gap defect of the stone here; in order to distinguish the gap defects caused by the joint, the reflection points of the joint are often more regularly distributed in space, and the resulting joint recognition is higher. Therefore, the gap correction coefficient is smaller, indicating that the reflection point is more likely to be a reflection point on the joint, and the original data needs to be reduced; and for the reflection points on the crack defect seam, the spatial distribution of the local reflection points is quite different, and the difference in the received signals of different reflection points is quite different, the joint recognition is smaller, and the gap correction coefficient is larger, indicating that the reflection point is more likely to be a reflection point on the crack defect seam; the step flow chart of the method for obtaining the gap correction coefficient provided in the embodiment of the present application is as follows Figure 3 shown.

[0062] Further, based on the gap correction coefficient, the reflected signal intensity of each reflection point is corrected, and then three-dimensional reconstruction is performed, specifically: The product of the reflection signal intensity of each reflection point under each scanning layer and the gap correction coefficient is recorded as the corrected signal intensity of each reflection point under each scanning layer; Ultrasonic imaging technology is used to image the corrected signal intensity of all reflection points under each scanning layer to construct a corrected two-dimensional tomographic scan image for each frame; It should be noted that ultrasonic imaging technology is a well-known technology and will not be described in detail here.

[0063] The three-dimensional structural image of the stone structure building is obtained by three-dimensionally reconstructing the two-dimensional tomographic scan images after all frames are corrected by three-dimensional imaging software; Preferably, in this embodiment, Introview Concrete 3D software is used for three-dimensional reconstruction, wherein Introview Concrete 3D software is a well-known technology and will not be described in detail here. As other implementation methods, the implementer can adopt other methods of the prior art, such as idealViwer 3D software, etc. This embodiment does not impose any special restrictions on this.

[0064] It should be noted that the higher the correction signal intensity, the brighter the color in the corresponding two-dimensional tomography image; secondly, the smaller the gap correction coefficient of the reflection point on the splicing seam, the smaller the correction of the reflection signal intensity, and the larger the gap correction coefficient of the reflection point on the crack defect seam, the greater the adjustment of the reflection signal intensity, thereby realizing the identification of crack defect seams inside the stone while reducing the interference of the splicing seam.

[0065] According to the three-dimensional structural image of the stone structure building, the defects inside the stone structure building are intuitively displayed, and the stone structure at the location where the crack defects exist in the stone structure building is reinforced to ensure the structural stability of the building.

[0066] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0067] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the present application. It should be pointed out that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application without departing from the content of the technical solution of the present application, shall fall within the protection scope of the technical solution of the present application.

Claims

1. A stone structure building detection method based on a concrete ultrasonic tomography detection scanner, characterized in that: The method comprises the following steps: An ultrasonic tomography scanner is used to obtain the initial signal strength of the ultrasonic signal when it is emitted, and the ultrasonic reflection signal after the ultrasonic signal is reflected at each reflection point under each scanning layer, the reflection signal strength after reflection, and the signal propagation time; The signal propagation time difference of each reflection point under each scanning layer is obtained by the deviation of the signal propagation time length of each reflection point under each scanning layer; the deviation of the signal intensity of the ultrasonic reflection signal of each reflection point under each scanning layer in the frequency domain is analyzed to determine the signal intensity difference of each reflection point under each scanning layer; the signal propagation time difference and the signal intensity difference are combined to obtain the signal difference index of each reflection point under each scanning layer; According to the difference between the initial signal intensity after the ultrasonic signal is emitted and the reflected signal intensity after the reflection at each reflection point, as well as the complexity of the ultrasonic reflection signal, the signal disorder degree of each reflection point under each scanning layer is determined, and the signal difference index is integrated to obtain the defect assessment coefficient of each reflection point under each scanning layer; Based on the defect assessment coefficient, all reflection points are divided into potential defect points and normal reflection points; the distribution of the potential defect points under each scanning layer and the other potential defect points in its local range, as well as the similarity of the ultrasonic reflection signals, are analyzed to determine the seam recognition degree of the potential defect points under each scanning layer, wherein the seam recognition degree of the normal reflection point is a preset value; Based on the seam recognition degree and the defect assessment coefficient, the gap correction coefficient of each reflection point under each scanning layer is obtained, the reflection signal intensity of each reflection point under each scanning layer is corrected, and each frame of the corrected two-dimensional tomography image is constructed. All frames of the two-dimensional tomography images are three-dimensionally reconstructed to detect internal defects of stone structure buildings.

2. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 1 is characterized in that: The obtaining of the signal propagation time difference of each reflection point under each scanning layer includes: A threshold segmentation algorithm is used to obtain a segmentation threshold of the signal propagation time of all reflection points under each scanning layer, which is recorded as a first segmentation threshold; the average of the signal propagation time of all reflection points under each scanning layer whose signal propagation time is less than the first segmentation threshold is used as the basic propagation time of each scanning layer; The difference between the signal propagation time length of each reflection point under each scanning layer and the basic propagation time length is used as the signal propagation time difference of each reflection point under each scanning layer.

3. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 1 is characterized in that: Determining the signal strength difference of each reflection point under each scanning layer includes: By using frequency domain analysis, the spectrum of the ultrasonic reflection signal of each reflection point under each scanning layer is obtained, and the signal amplitude of the fundamental wave in the spectrum is obtained; A threshold segmentation algorithm is used to obtain a segmentation threshold of the signal amplitude corresponding to all reflection points under each scanning layer, which is recorded as a second segmentation threshold; the average of the signal amplitudes corresponding to all reflection points under each scanning layer whose signal amplitudes are less than the second segmentation threshold is taken as the basic signal strength of each scanning layer; The difference between the signal amplitude and the signal basic intensity at each reflection point under each scanning layer is used as the signal intensity difference at each reflection point under each scanning layer.

4. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 1 is characterized in that: The signal difference index of each reflection point under each scanning layer is the sum of the signal propagation time difference and the signal intensity difference.

5. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 3 is characterized in that: Determining the signal disorder degree of each reflection point under each scanning layer includes: Perform curve fitting on the ultrasonic reflection signals of each reflection point under each scanning layer to obtain the goodness of fit of the fitting curve; The difference between the initial signal strength and the signal amplitude is recorded as energy attenuation; The signal disorder degree is the inverse of the product of the energy attenuation and the goodness of fit.

6. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 1, characterized in that: The defect assessment coefficient is the sum of the signal disorder degree and the signal difference index.

7. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 1, characterized in that: The method of distinguishing all reflection points into potential defect points and normal reflection points includes: The defect assessment coefficients of all reflection points under each scanning layer are threshold segmented, which is recorded as a third segmentation threshold; reflection points whose defect assessment coefficients are greater than the third segmentation threshold are recorded as potential defect points, otherwise, they are recorded as normal reflection points.

8. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 1, characterized in that: Determining the seam recognition degree of each potential defect point under each scanning layer includes: Selecting multiple potential defect points closest to any potential defect point under each scanning layer to form a local defect set of any potential defect point; Performing linear fitting on the position coordinates of all potential defect points in the local defect set, recording the fitting straight line as a gap distribution line; recording the average of the distances from all potential defect points in the local defect set to the gap distribution line as the average distance; The cumulative sum of the similarities of the ultrasonic reflection signals between any potential defect point and all the potential defect points in the local defect set is calculated, and the ratio of the cumulative sum to the average distance is used as the seam recognition degree of any potential defect point.

9. The stone structure building detection method based on concrete ultrasonic tomography detection scanner as claimed in claim 1, characterized in that: The gap correction coefficient is a normalized result of the ratio of the defect assessment coefficient to the seam recognition degree.

10. The stone structure building detection method based on concrete ultrasonic tomography detection scanner according to claim 1, characterized in that: The reflected signal intensity of each reflection point under each scanning layer is corrected, each frame of the corrected two-dimensional tomographic scan image is constructed, and all frames of the two-dimensional tomographic scan image are three-dimensionally reconstructed, including: The product of the reflection signal intensity of each reflection point under each scanning layer and the gap correction coefficient is recorded as the corrected signal intensity of each reflection point under each scanning layer; the corrected signal intensity of all reflection points under each scanning layer is imaged to construct a corrected two-dimensional tomographic scan image of each frame; and the corrected two-dimensional tomographic scan images of all frames are three-dimensionally reconstructed.

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