Ultrasonic flaw detection method and system for precast concrete assembly connection joint

Abstract

This application provides an ultrasonic flaw detection method and system for precast concrete assembly connection nodes. The method involves performing ultrasonic simulation in three-dimensional space using the coordinate information of each internal component and acoustic constraints to generate acoustic paths unobstructed by the internal components. Based on the geometric layout of these acoustic paths, intelligent ultrasonic sensors are deployed within the precast concrete structure to be inspected. The propagation time of the first wave in each acoustic path is determined from waveform information of different acoustic paths. Ultrasonic tomography is then performed using the acoustic paths and the corresponding propagation times for each path to reconstruct a three-dimensional sound velocity distribution field within the precast concrete structure. Internal defect areas within the precast concrete structure are identified based on this three-dimensional sound velocity distribution field and a preset non-destructive sound velocity threshold. Using this method, model distortion caused by acoustic path obstruction in acoustic velocity tomography can be reduced.

Description

Technical Field

[0001] This application relates to the field of ultrasonic flaw detection technology, and more specifically, to an ultrasonic flaw detection method and system for precast concrete assembly connection nodes. Background Technology

[0002] Ultrasonic testing refers to the use of piezoelectric transducers to excite high-frequency mechanical waves, which propagate in a medium and are received by reflection or transmission signals based on differences in acoustic characteristics. Through a series of physical testing processes, such as time-frequency domain analysis and defect feature interpretation, the invisible geometric structure and state information inside the material are transformed into visualized defect distribution data. This enables non-destructive diagnosis of the tested object from its surface morphology to its internal quality, ultimately providing a quantitative spatial defect information basis for structural integrity assessment, safety early warning, and life prediction.

[0003] Ultrasonic testing of precast concrete assembly joints involves using array-type ultrasonic transducers to excite directional sound beams that propagate through a multi-layered heterogeneous concrete and prestressed steel composite medium according to wave mechanics principles. Based on the scattering, diffraction, and attenuation signal characteristics generated by the abrupt change in acoustic impedance at the interface, a series of non-destructive testing procedures, including full-matrix data acquisition and synthetic aperture focusing imaging, are employed. Traditional ultrasonic testing methods for precast concrete joints often rely on operator experience for local measurement point placement and single-path analysis, making it difficult to effectively avoid the shielding effect of internal steel mesh and metal sleeves on the ultrasonic sound path. For example, traditional methods may fail to predict the spatial orientation of the steel reinforcement, causing the ultrasonic beam to be completely blocked by the reinforcement in the propagation path. The acoustic time data acquired along this blocked path cannot actually reflect the medium state of the intended testing area, but is misjudged as a low-velocity anomaly zone during subsequent sound field reconstruction. This ultimately forms false voids or anomaly bands in the reconstructed model that are unrelated to the actual defect distribution, leading to shielding distortion in the three-dimensional sound velocity field. Therefore, reducing model distortion caused by acoustic path shielding in acoustic velocity tomography has become a challenge for the industry. Summary of the Invention

[0004] This application provides an ultrasonic flaw detection method and system for precast concrete assembly connection nodes, which can reduce model distortion caused by acoustic path obstruction in acoustic velocity tomography.

[0005] In a first aspect, this application provides an ultrasonic flaw detection method for precast concrete assembly connection nodes, comprising the following steps: A three-dimensional building information model of the precast concrete structure to be inspected is obtained, wherein the three-dimensional building information model includes the coordinate information of each internal component in three-dimensional space; By combining the coordinate information with acoustic constraints, ultrasonic simulation is performed in the three-dimensional space to generate an acoustic path that is not obstructed by internal components. Based on the geometric layout of the acoustic path, intelligent ultrasonic sensors are deployed in the precast concrete structure to be tested, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested. When the propagating sound of the first wave in each sound path is determined from the waveform information, ultrasonic tomography is performed through the acoustic path and the propagating sound time corresponding to each sound path to reconstruct the three-dimensional sound velocity distribution field inside the precast concrete structure to be tested. Based on the three-dimensional sound velocity distribution field and a preset non-destructive sound velocity threshold, the internal defect area in the precast concrete structure to be detected is identified.

[0006] In some embodiments, the ultrasonic simulation performed in the three-dimensional space using the coordinate information combined with acoustic constraints to generate an acoustic path not obstructed by internal components specifically includes: A three-dimensional spatial obstacle model of the internal components is established based on the coordinate information; A set of candidate sensor points is deployed on the node detection surface, and then the acoustic path search space is determined by combining acoustic constraints. Using the three-dimensional spatial obstacle model as a constraint, the line-of-sight propagation feasibility of generating all candidate sound paths in the sound path search space is determined. Based on all feasible acoustic paths for direct line-of-sight propagation, an acoustic path that is not obstructed by internal components is generated.

[0007] In some embodiments, deploying intelligent ultrasonic sensors in the precast concrete structure to be tested based on the geometric layout of the acoustic path, and then acquiring waveform information of different acoustic paths in the precast concrete structure to be tested, specifically includes: Based on the geometric layout of the acoustic path, the installation positions of the smart ultrasonic sensors are located and marked on the surface of the node entities. Deploy smart ultrasonic sensors at marked locations and ensure acoustic coupling between the sensors and the concrete surface; The intelligent ultrasonic sensor is controlled to emit and receive ultrasonic waves sequentially according to the acoustic path sequence, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested.

[0008] In some embodiments, determining the propagating sound of the first wave in each sound path from the waveform information specifically includes: The waveform information is preprocessed to enhance the characteristics of the first wave signal; Identify the first wave arrival point of each acoustic path from the preprocessed waveform information; The propagation time of the first wave in each sound path is calculated based on the arrival point of the first wave.

[0009] In some embodiments, ultrasonic tomography is performed through the acoustic path and the propagation time corresponding to each acoustic path to reconstruct the three-dimensional sound velocity distribution field inside the precast concrete structure to be tested. Specifically, this includes: A three-dimensional discretized mesh model of the interior of the precast concrete structure to be tested is established based on the acoustic path. A linear equation system for sound velocity tomography is constructed based on the three-dimensional discretized mesh model and the propagation time of sound. Solve the linear equation system of the sonic velocity tomography to reconstruct the three-dimensional sonic velocity distribution field inside the precast concrete structure to be inspected.

[0010] In some embodiments, identifying internal defect regions in the precast concrete structure to be inspected based on the three-dimensional sound velocity distribution field combined with a preset non-destructive sound velocity threshold specifically includes: Based on the preset non-destructive sound velocity threshold for ultrasonic testing of sound concrete samples. The sound velocity values ​​of each voxel in the three-dimensional sound velocity distribution field are compared with the lossless sound velocity threshold for defects. Based on the comparison results, identify the internal defect areas in the precast concrete structure to be inspected.

[0011] In some embodiments, the internal components refer to key components in precast concrete assembly connection nodes that bear the structural force transmission function, including longitudinal reinforcing bars, transverse stirrups, grouting sleeves, and grout-anchored corrugated pipes.

[0012] Secondly, this application provides an ultrasonic flaw detection system for precast concrete assembly connection nodes, comprising: The acquisition module is used to acquire a three-dimensional building information model of the precast concrete structure to be inspected, wherein the three-dimensional building information model includes the coordinate information of each internal component in three-dimensional space; The processing module is used to perform ultrasonic simulation in the three-dimensional space by combining the coordinate information with acoustic constraints, thereby generating an acoustic path that is not obstructed by internal components. The processing module is also used to deploy intelligent ultrasonic sensors in the precast concrete structure to be tested based on the geometric layout of the acoustic path, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested. The processing module is also used to determine the propagation time of the first wave in each sound path from the waveform information, and to perform ultrasonic tomography through the acoustic path and the propagation time corresponding to each sound path, thereby reconstructing the three-dimensional sound velocity distribution field inside the precast concrete structure to be detected. The execution module is used to identify internal defect areas in the precast concrete structure to be inspected based on the three-dimensional sound velocity distribution field combined with a preset non-destructive sound velocity threshold.

[0013] Thirdly, this application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described ultrasonic flaw detection method for precast concrete assembly connection nodes.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described ultrasonic flaw detection method for precast concrete assembly connection nodes.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The ultrasonic flaw detection method and system for precast concrete assembly connection nodes provided in this application firstly, based on the coordinate information of internal components in the three-dimensional building information model and combined with acoustic constraints, performs ultrasonic simulation in three-dimensional space to generate an acoustic path that is not obstructed by internal components. This process can simulate the propagation path of ultrasonic waves in the digital model in advance, and actively avoid internal components such as steel bars and sleeves that have a strong shielding or interference effect on sound waves through spatial geometric relationships and acoustic principles, thus constructing a theoretically unobstructed acoustic path framework for subsequent data acquisition. This process ensures the effectiveness and reliability of the acquired waveform information from the source, providing a clean data foundation for subsequent high-precision tomographic imaging. Subsequently, waveform information is acquired based on the geometric layout of the acoustic path, and the first wave in each acoustic path is determined. By combining the propagation time of the acoustic path with the propagation time, sound velocity tomography simulation is performed to reconstruct the three-dimensional sound velocity distribution field inside the precast concrete structure to be inspected. This process uses the acoustic path network as a known and optimal physical constraint for tomographic inversion, ensuring that each acoustic path data involved in the reconstruction represents the real and unobstructed propagation path of ultrasound in the concrete medium. This allows the inversion algorithm to accurately reflect the real distribution of sound velocity in the medium based on the difference in acoustic time, rather than false anomalies caused by path occlusion. By introducing a spatially validated effective acoustic path, this process provides a reliable physical kernel for tomographic imaging, enabling the reconstructed three-dimensional sound velocity field to accurately map internal defects, rather than artifacts caused by acoustic path occlusion. In summary, this scheme can reduce model distortion caused by acoustic path occlusion in sound velocity tomography. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating an ultrasonic testing method for precast concrete assembly connection nodes according to some embodiments of this application. Figure 2 This is a schematic diagram illustrating the process of deploying a smart ultrasonic sensor according to some embodiments of this application; Figure 3 This is a schematic diagram illustrating the process of defect comparison according to some embodiments of this application; Figure 4 This is a structural schematic diagram of an ultrasonic flaw detection system for precast concrete assembly connection nodes, as shown in some embodiments of this application. Figure 5 This is an internal structural diagram of a computer device for implementing an ultrasonic flaw detection method for precast concrete assembly connection nodes, according to some embodiments of this application. Detailed Implementation

[0017] To better understand the technical solutions in this embodiment, the technical solutions in this embodiment will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0018] refer to Figure 1 The figure is a flowchart illustrating an ultrasonic testing method for precast concrete assembly connection nodes according to some embodiments of this application. The ultrasonic testing method for precast concrete assembly connection nodes mainly includes the following steps: In step 101, a three-dimensional building information model of the precast concrete structure to be detected is obtained, wherein the three-dimensional building information model includes the coordinate information of each internal component in three-dimensional space.

[0019] In practice, a 3D building information model of the precast concrete structure to be inspected can be loaded into a professional Building Information Modeling (BIM) software platform (such as Autodesk Revit). Then, all internal components within the target node range are automatically identified and selected. Next, the coordinates of the minimum outer box corner point or the coordinates of the axis key point of each internal component in the global coordinate system are parsed. Finally, the coordinates of the minimum outer box corner point are transformed through the transformation matrix to obtain the standardized coordinate information of each internal component in the local coordinate system, which serves as the coordinate information of each internal component in 3D space.

[0020] It should be noted that the three-dimensional building information model refers to a digital model constructed based on building information modeling technology, containing complete geometric information and engineering attributes; the internal components refer to the key components in the precast concrete assembly connection nodes that bear the structural force transmission function, including longitudinal reinforcing bars, transverse stirrups, grouting sleeves, and grout-anchored corrugated pipes; the coordinate information refers to the precise position data of component feature points in three-dimensional space calculated by the BIM software geometry engine, expressed with millimeter-level precision; the coordinate transformation matrix refers to a 4×4 homogeneous transformation matrix used for coordinate system transformation, containing translation and rotation parameters to ensure that the coordinates of all components have a unified local reference benchmark.

[0021] In step 102, ultrasonic simulation is performed in the three-dimensional space using the coordinate information and acoustic constraints to generate an acoustic path that is not obstructed by internal components.

[0022] In some embodiments, the generation of an acoustic path not obstructed by internal components by performing ultrasonic simulation in the three-dimensional space using the coordinate information and acoustic constraints can be achieved through the following steps: A three-dimensional spatial obstacle model of the internal components is established based on the coordinate information; A set of candidate sensor points is deployed on the node detection surface, and then the acoustic path search space is determined by combining acoustic constraints. Using the three-dimensional spatial obstacle model as a constraint, the line-of-sight propagation feasibility of generating all candidate sound paths in the sound path search space is determined. Based on all feasible acoustic paths for direct line-of-sight propagation, an acoustic path that is not obstructed by internal components is generated.

[0023] In specific implementation, the three-dimensional spatial obstacle model of the internal components based on the coordinate information can be established in the following way: First, the coordinate information and geometric dimensions of each internal component are used as input data to generate an accurate triangular mesh surface model for each component. For the steel reinforcement component, a cylindrical meshing algorithm is used to discretize its surface into continuous triangular patches. For the grouting sleeve component, a closed triangular mesh is constructed according to its actual geometric contour. Then, the triangular mesh models of all internal components are combined and spliced ​​in three-dimensional space to form a complete and unified three-dimensional spatial obstacle model. The accuracy of the triangular mesh is controlled by a preset mesh size parameter to ensure that it can accurately represent the geometry of the component and meet the computational efficiency requirements of subsequent ray tracing calculations.

[0024] It should be noted that the three-dimensional spatial obstacle model mentioned in this application refers to a digital model used to characterize the precise geometric contours and distribution positions of all steel bars, sleeves and other components inside the precast concrete node in three-dimensional space. Its function is to provide a geometric basis for spatial occlusion judgment for ultrasonic simulation, and to ensure that the generated ultrasonic wave propagation path can effectively avoid all internal obstacles.

[0025] In practice, the following method can be used to determine the acoustic path search space by deploying a set of candidate sensor points on the node detection surface and combining it with acoustic constraints: First, select two opposite and flat concrete surfaces on the node entity as the detection working surfaces, and generate uniformly distributed sensor candidate point coordinates on each working surface according to a preset grid spacing; then, according to the effective propagation distance range of ultrasonic waves defined in the acoustic constraints, eliminate candidate point pairs that are too close or too far apart. The upper limit of the effective propagation distance is determined by the attenuation characteristics of ultrasonic waves in concrete, and the lower limit is determined by the minimum detection blind zone of the ultrasonic flaw detector; at the same time, according to the beam angle requirements defined in the acoustic constraints, further screen out candidate point pairs whose propagation path and the normal of the detection surface are within a preset range, and finally form an acoustic path search space that satisfies all acoustic constraints.

[0026] It should be noted that the acoustic path search space mentioned in this application refers to a finite set of acoustic paths selected from all possible sensor arrangement schemes through acoustic constraints. Its function is to limit the optimization range of ultrasonic simulation, significantly reduce computational complexity and improve acoustic path planning efficiency while ensuring detection effectiveness.

[0027] In specific implementation, the line-of-sight propagation feasibility of generating all candidate sound paths in the sound path search space, constrained by the three-dimensional spatial obstacle model, can be achieved in the following way: First, extract the start and end coordinates of each candidate sound path from the sound path search space to construct a three-dimensional spatial line segment from the transmitting point to the receiving point; then, use a ray-triangle intersection detection algorithm based on computer graphics to determine whether the line segment intersects with any triangular facet in the three-dimensional spatial obstacle model; when the line segment has no intersection with any triangular facet, the candidate sound path is determined to satisfy the line-of-sight propagation feasibility; when the line segment intersects with any triangular facet, the candidate sound path is determined not to satisfy the line-of-sight propagation feasibility; finally, generate a corresponding feasibility marker for each candidate sound path in the sound path search space to form a complete feasibility evaluation result.

[0028] It should be noted that the feasibility of direct propagation described in this application refers to a binary state attribute used to determine whether ultrasonic waves can propagate in a straight line between a specific emission point and a receiving point without being blocked by internal components. Its function is to quickly screen out effective sound wave propagation paths from a large number of candidate acoustic paths, providing a basis for constructing reliable acoustic paths.

[0029] In specific implementation, generating acoustic paths that are not obstructed by internal components based on all feasible line-of-sight propagation acoustic paths can be achieved in the following way: First, select acoustic paths marked as feasible for line-of-sight propagation from all candidate acoustic paths to form an initial acoustic path set; then, use a graph theory-based network optimization algorithm to select the optimal acoustic path subset from the initial acoustic path set, with the premise of covering the key areas of the nodes and the objective of minimizing the number of acoustic paths; wherein, the coverage of the key areas of the nodes is evaluated by calculating the spatial distribution uniformity of the acoustic beams in the detection area; finally, organize the optimized acoustic path subset and its spatial geometry information into a structured acoustic path, where each acoustic path in the network is ensured to be unobstructed by any internal components and together constitutes complete detection coverage of the internal space of the nodes; wherein each acoustic path includes corresponding acoustic path endpoints (i.e., transmitter and receiver points).

[0030] It should be noted that the acoustic path described in this application refers to a structured detection scheme consisting of multiple optimized ultrasonic propagation paths and their spatial topological relationships. Its function is to guide the precise deployment and collaborative operation of intelligent ultrasonic sensors on the node surface, ensuring complete and unobstructed ultrasonic detection coverage of the internal space of the node.

[0031] In step 103, intelligent ultrasonic sensors are deployed in the precast concrete structure to be tested based on the geometric layout of the acoustic path, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested.

[0032] In some embodiments, reference Figure 2 As shown in the figure, this is a schematic flowchart illustrating the deployment of intelligent ultrasonic sensors according to some embodiments of this application. The deployment of intelligent ultrasonic sensors in the precast concrete structure to be inspected, based on the geometric layout of the acoustic paths, and the subsequent acquisition of waveform information from different acoustic paths within the precast concrete structure, can be achieved through the following steps: First, in 1031, based on the geometric layout of the acoustic path, the installation position of the smart ultrasonic sensor is located and marked on the surface of the node entity; First, in 1032, smart ultrasonic sensors are deployed at marked locations, and acoustic coupling between the sensors and the concrete surface is ensured. First, in 1033, the intelligent ultrasonic sensor is controlled to emit and receive ultrasonic waves sequentially according to the acoustic path sequence, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested.

[0033] In specific implementation, based on the geometric layout of the acoustic path, the installation positions of the intelligent ultrasonic sensors can be located and marked on the surface of the node entity in the following way: First, extract the three-dimensional coordinate data of all acoustic path endpoints (i.e., transmitter and receiver points) from the acoustic path, and convert the coordinates in the model coordinate system to the global measurement coordinate system of the construction site through coordinate transformation; then, use a total station or real-time dynamic differential global navigation satellite system measurement equipment to accurately measure and locate the nodes on the surface of the node entity according to the converted coordinates, and clearly mark each measurement point position with marking paint or positioning patches; finally, number each marked position, and the number is consistent with the acoustic path endpoint number in the acoustic path, forming a correspondence between the position marking and the network layout.

[0034] In practice, a smart ultrasonic sensor is deployed at the marked location, and the acoustic coupling between the sensor and the concrete surface is ensured by the following method: First, the concrete surface at the marked location is ground to remove laitance and impurities, ensuring the surface flatness meets the coupling requirements; then, a layer of acoustic coupling agent is evenly applied to the treated concrete surface, which can be selected from yellow glycerin, cellulose paste, or a special ultrasonic coupling gel; next, the radiating surface of the smart ultrasonic sensor is pressed onto the coupling agent, and air bubbles between the interfaces are eliminated by rotation and movement, while observing the coupling status monitoring indicator light built into the sensor. When the indicator light shows a good state, the sensor is fixed in position using a magnetic base or vacuum adsorption device.

[0035] In practice, controlling the intelligent ultrasonic sensors to sequentially emit and receive ultrasonic waves according to the acoustic path sequence, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested, can be achieved in the following way: First, based on the sequence of all acoustic paths, a control command set containing the transmitting sensor number, receiving sensor number, and acquisition parameters is generated; then, excitation commands are sent to the designated transmitting sensors in sequence through the wireless communication network to generate ultrasonic pulses with preset waveform parameters, and synchronous acquisition commands are sent to all receiving sensors paired with the transmitting sensor; the receiving sensors amplify and convert the acquired analog voltage signals into digital waveform data, and automatically add timestamps, acoustic path numbers, and sensor identification information; finally, the complete waveform information is used as the waveform information of different acoustic paths in the precast concrete structure to be tested.

[0036] It should be noted that the waveform information of the acoustic path mentioned in this application refers to the original voltage signal sequence that contains the characteristics of the entire process of ultrasonic wave propagation in concrete, which is acquired by an intelligent ultrasonic sensor. Its function is to fully record the physical characteristics of ultrasonic wave such as energy attenuation and frequency change on a specific propagation path, so as to provide a data basis for the subsequent extraction of sound wave propagation parameters.

[0037] In step 104, when the propagation time of the first wave in each acoustic path is determined from the waveform information, ultrasonic tomography is performed through the acoustic path and the propagation time corresponding to each acoustic path to reconstruct the three-dimensional sound velocity distribution field inside the precast concrete structure to be tested.

[0038] In some embodiments, the following steps are used to determine the propagating sound of the first wave in each sound path from the waveform information: The waveform information is preprocessed to enhance the characteristics of the first wave signal; Identify the first wave arrival point of each acoustic path from the preprocessed waveform information; The propagation time of the first wave in each sound path is calculated based on the arrival point of the first wave.

[0039] In specific implementation, the waveform information is preprocessed to enhance the characteristics of the first wave signal, which can be achieved in the following way: First, a digital bandpass filter is applied to the waveform information. The passband frequency range of the bandpass filter is set according to the typical frequency response characteristics of ultrasound in concrete to retain the main frequency components of the first wave signal while suppressing high-frequency noise and power frequency interference. Then, the filtered waveform signal is normalized by dividing the signal amplitude by its maximum absolute value to eliminate the signal amplitude variation caused by the difference in coupling conditions. Finally, the normalized signal is further smoothed by using the moving average method or wavelet denoising algorithm to enhance the prominence of the first wave signal and improve the signal-to-noise ratio.

[0040] In specific implementation, identifying the first arrival point of each acoustic path from the preprocessed waveform information can be achieved in the following way: First, calculate the envelope of the preprocessed waveform information by performing a Hilbert transform on the signal and taking the modulus value; then, find the first peak point exceeding a preset threshold on the envelope, the threshold being dynamically adjusted according to the average noise level of the signal; simultaneously, use the Akaike information criterion to assist in the judgment, determining the precise location of the first arrival point by calculating the change in the information criterion value of the signal segment; finally, cross-validate the first arrival points obtained by the envelope method and the Akaike information criterion method, and when the difference between the time points obtained by the two methods is within the allowable range, take the average of the two as the first arrival point of the corresponding acoustic path.

[0041] It should be noted that the first arrival point mentioned in this application refers to the precise time and location at which the ultrasonic signal first arrives at the receiving sensor after propagating from the transmitting sensor through the concrete medium. Its function is to mark the arrival time of the ultrasonic wave along the shortest path, providing a key time reference point for accurately calculating the sound wave propagation time.

[0042] In specific implementation, the propagation time of the first wave in each acoustic path can be calculated based on the arrival point of the first wave in the following manner: First, the ultrasonic emission time reference corresponding to each acoustic path is recorded. The time reference is recorded synchronously by the central control unit when sending the excitation command. Then, the difference between the identified arrival time of the first wave and the emission time reference is calculated to obtain the propagation time of the ultrasonic wave in the concrete. Finally, the multiple propagation time values ​​obtained from multiple acquisitions of the same acoustic path are statistically analyzed. After removing outliers with obvious deviations, the average value is taken as the propagation time of the first wave in that acoustic path.

[0043] It should be noted that the propagation time of sound mentioned in this application refers to the time taken for ultrasonic waves to propagate along the shortest path between the transmitting and receiving sensors. Its function is to quantify the propagation speed characteristics of sound waves in concrete media, serving as the most direct and reliable input observation data for reconstructing the sound velocity distribution field inside the medium.

[0044] In some embodiments, the three-dimensional sound velocity distribution field inside the precast concrete structure to be inspected can be reconstructed by performing ultrasonic tomography through the acoustic path and the propagation time corresponding to each acoustic path using the following steps: A three-dimensional discretized mesh model of the interior of the precast concrete structure to be tested is established based on the acoustic path. A linear equation system for sound velocity tomography is constructed based on the three-dimensional discretized mesh model and the propagation time of sound. Solve the linear equation system of the sonic velocity tomography to reconstruct the three-dimensional sonic velocity distribution field inside the precast concrete structure to be inspected.

[0045] In specific implementation, the establishment of a three-dimensional discretized mesh model of the precast concrete structure to be inspected based on the acoustic path can be achieved in the following way: First, the geometric boundary of the node region is determined according to the spatial coordinates of all acoustic path endpoints in the acoustic path, and a minimum cuboid bounding box containing all acoustic paths is established as the mesh generation region; then, the region is spatially divided using regular hexahedral elements, and the continuous three-dimensional space is discretized into several cubic voxels, wherein the voxel size is set in a balanced manner according to the detection accuracy requirements and computing resources; finally, the correspondence between voxel index and spatial position is established, and a unique identifier and spatial coordinates are assigned to each voxel to complete the establishment of the three-dimensional discretized mesh model.

[0046] In specific implementation, the linear equation system for sound velocity tomography, constructed based on the three-dimensional discretized grid model and the propagation time of sound, can be implemented in the following manner: First, for each sound path, a three-dimensional line segment voxel traversal method based on the Bresenham algorithm is used to determine all voxels traversed by the sound path and their corresponding traversal lengths; then, the traversal lengths of each sound path in each voxel are arranged in voxel index order to form the row vector corresponding to the sound path, and the row vectors of all sound paths are combined to form the sound path length matrix; next, the propagation time of the first wave in each sound path is converted into sound slowness data, i.e., the reciprocal of the propagation time, and the sound slowness data of all sound paths are combined to form the observation vector; finally, a linear equation system is established with the sound path length matrix as the coefficient matrix, the voxel sound slowness as the unknown vector, and the observed sound slowness as the right-hand vector.

[0047] It should be noted that the linear equation system of acoustic velocity tomography described in this application refers to a mathematical model that describes the quantitative relationship between the propagation time of ultrasonic waves and the distribution of sound velocity in the medium. Its function is to transform the physical problem of sound wave propagation into a computable mathematical problem, providing a mathematical solution framework for reconstructing the internal sound velocity field through numerical methods.

[0048] In specific implementation, solving the linear equation system of the sound velocity tomography and then reconstructing the three-dimensional sound velocity distribution field inside the precast concrete structure to be detected can be achieved in the following way: First, algebraic reconstruction technology is used as an iterative solution algorithm to initialize the sound slowness value of all voxels as an initial estimate based on the typical sound velocity of concrete; then, the iterative calculation process begins: for each iteration, each sound path is processed in sequence, and the difference between the theoretical and measured sound slowness under the current sound slowness field is calculated. Based on this difference, the sound slowness values ​​of all relevant voxels are updated according to the proportion of the sound path's travel length in each voxel; after completing one round of processing of all sound paths, the next round of iteration is performed; finally, the iteration termination condition is set. When the root mean square error between the theoretical calculation value and the measured value is less than a preset threshold or the maximum number of iterations is reached, the iteration stops. At this time, the reciprocal of the sound slowness value of each voxel is the reconstructed sound velocity value. These sound velocity values ​​are organized according to the spatial position of the voxels to form a three-dimensional sound velocity distribution field.

[0049] It should be noted that the three-dimensional sound velocity distribution field mentioned in this application refers to a three-dimensional data set that reflects the distribution of sound velocity values ​​at various spatial points inside a node, obtained by reconstructing sound velocity tomography. Its function is to convert discrete sound path measurement data into a continuous spatial sound velocity distribution, and to intuitively present the quality status and defect characteristics inside the concrete.

[0050] In step 105, the internal defect areas in the precast concrete structure to be detected are identified based on the three-dimensional sound velocity distribution field combined with a preset non-destructive sound velocity threshold.

[0051] In some embodiments, identifying internal defect regions in the precast concrete structure to be inspected based on the three-dimensional sound velocity distribution field combined with a preset non-destructive sound velocity threshold can be achieved by the following steps: Based on the preset non-destructive sound velocity threshold for ultrasonic testing of sound concrete samples. The sound velocity values ​​of each voxel in the three-dimensional sound velocity distribution field are compared with the lossless sound velocity threshold for defects. Based on the comparison results, identify the internal defect areas in the precast concrete structure to be inspected.

[0052] In specific implementation, the non-destructive sound velocity threshold for ultrasonic testing based on sound concrete samples can be achieved in the following way: First, prepare sound concrete samples with the same mix proportion and curing conditions as the precast concrete structure to be tested. Use the same intelligent ultrasonic sensor as in the previous steps to perform comprehensive ultrasonic testing on the sound concrete samples to obtain a large number of sound velocity data samples. Then, perform statistical analysis on the sound velocity data samples to calculate the average value and standard deviation of the sound velocity values. Preferably, the statistical principle under the assumption of normal distribution can be adopted, and the value obtained by subtracting a certain number of times the standard deviation from the average value can be set as the non-destructive sound velocity threshold, wherein the multiple of the standard deviation is determined according to the confidence level required for the test.

[0053] It should be noted that the non-destructive sound velocity threshold mentioned in this application refers to the critical sound velocity value determined based on the acoustic properties of sound concrete for judging whether there are internal defects. Its function is to provide an objective and quantitative standard for defect judgment, and to realize the automatic identification and location of quality defects such as voids and looseness inside the node.

[0054] For specific implementation, refer to Figure 3 As shown in the figure, this is a schematic diagram of the defect comparison process in some embodiments of this application. The defect comparison between the sound velocity values ​​of each voxel in the three-dimensional sound velocity distribution field and the lossless sound velocity threshold can be achieved in the following way: First, establish a correspondence table between the spatial index and the sound velocity value of each voxel in the three-dimensional sound velocity distribution field; then, traverse each voxel in the correspondence table and compare its sound velocity value with the preset lossless sound velocity threshold one by one. When the sound velocity value of a voxel is lower than the lossless sound velocity threshold, mark the voxel as a defect candidate voxel and record its spatial coordinates and sound velocity deviation value in the defect candidate list; finally, generate a defect comparison result map containing the spatial positions and sound velocity values ​​of all defect candidate voxels as the defect comparison result. The defect comparison result map intuitively displays the distribution of the sound velocity anomaly area in the form of a three-dimensional data field.

[0055] In practice, the identification of internal defect regions in the precast concrete structure to be inspected based on the comparison results can be achieved in the following way: First, based on the defect candidate voxel set obtained from the defect comparison results, the connected component labeling algorithm in 3D image processing is used to cluster spatially adjacent defect candidate voxels into independent connected regions by checking the 26-neighbor connectivity of each defect candidate voxel; then, morphological analysis is performed on each connected region to calculate its volume, centroid coordinates, circumscribed cube size and other geometric parameters, and pseudo-defect regions with volumes smaller than a preset noise threshold are removed; finally, each remaining connected region is defined as an independent internal defect region.

[0056] In another aspect, in some embodiments, this application provides an ultrasonic flaw detection system for precast concrete assembly connection nodes, referencing... Figure 4 The figure is a structural schematic diagram of an ultrasonic flaw detection system for precast concrete assembly connection nodes according to some embodiments of this application. The ultrasonic flaw detection system 200 for precast concrete assembly connection nodes includes: an acquisition module 201, a processing module 202, and an execution module 203, which are described below: The acquisition module 201 in this application is mainly used to acquire a three-dimensional building information model of the precast concrete structure to be inspected, wherein the three-dimensional building information model includes the coordinate information of each internal component in three-dimensional space. Processing module 202, in this application, is mainly used to perform ultrasonic simulation in the three-dimensional space by combining the coordinate information with acoustic constraints, thereby generating an acoustic path that is not blocked by internal components; In addition, the processing module 202 in this application is also used to deploy intelligent ultrasonic sensors in the precast concrete structure to be tested based on the geometric layout of the acoustic path, so as to collect waveform information of different acoustic paths in the precast concrete structure to be tested. In addition, the processing module 202 in this application is also used to determine the propagation sound time of the first wave in each sound path from the waveform information, and to perform ultrasonic tomography through the acoustic path and the propagation sound time corresponding to each sound path, thereby reconstructing the three-dimensional sound velocity distribution field inside the precast concrete structure to be detected. The execution module 203 in this application is mainly used to identify the internal defect area in the precast concrete structure to be detected based on the three-dimensional sound velocity distribution field combined with the preset non-destructive sound velocity threshold.

[0057] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described ultrasonic flaw detection method for precast concrete assembly connection nodes.

[0058] In some embodiments, reference Figure 5 This figure is an internal structural diagram of a computer device for implementing an ultrasonic testing method for precast concrete assembly connection nodes according to some embodiments of this application. The ultrasonic testing method for precast concrete assembly connection nodes in the above embodiments can be implemented through... Figure 5 The computer device shown is used to implement this, and the computer device 300 includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0059] The processor 301 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more devices used to control the execution of the ultrasonic testing method for precast concrete assembly connection nodes in this application.

[0060] The communication bus 302 is used to transmit information between the aforementioned components.

[0061] Memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CDROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 303 may exist independently and be connected to processor 301 via communication bus 302. Memory 303 may also be integrated with processor 301.

[0062] The memory 303 stores program code for executing the solution of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. In the above embodiment, the ultrasonic flaw detection method for precast concrete assembly connection nodes can be implemented by the processor 301 and one or more software modules in the program code in the memory 303.

[0063] Communication interface 304 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0064] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core processor or a multi-core processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0065] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device may be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0066] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described ultrasonic flaw detection method for precast concrete assembly connection nodes.

[0067] In summary, the ultrasonic flaw detection method and system for precast concrete assembly connection nodes disclosed in this application obtains a three-dimensional building information model of the precast concrete structure to be inspected, wherein the three-dimensional building information model includes the coordinate information of each internal component in three-dimensional space; ultrasonic simulation is performed in the three-dimensional space using the coordinate information and acoustic constraints to generate acoustic paths that are not obstructed by internal components; intelligent ultrasonic sensors are deployed in the precast concrete structure to be inspected based on the geometric layout of the acoustic paths to collect waveform information of different acoustic paths in the precast concrete structure to be inspected; the propagation time of the first wave in each acoustic path is determined from the waveform information, and ultrasonic tomography is performed using the acoustic paths and the propagation time corresponding to each acoustic path to reconstruct the three-dimensional sound velocity distribution field inside the precast concrete structure to be inspected; internal defect areas in the precast concrete structure to be inspected are identified based on the three-dimensional sound velocity distribution field and a preset non-destructive sound velocity threshold; this can reduce model distortion caused by acoustic path obstruction in acoustic velocity tomography.

[0068] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0069] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for ultrasonic inspection of precast concrete fabricated connection joints, characterized in that, Includes the following steps: A three-dimensional building information model of the precast concrete structure to be inspected is obtained, wherein the three-dimensional building information model includes the coordinate information of each internal component in three-dimensional space; By combining the coordinate information with acoustic constraints, ultrasonic simulation is performed in the three-dimensional space to generate an acoustic path that is not obstructed by internal components. Based on the geometric layout of the acoustic path, intelligent ultrasonic sensors are deployed in the precast concrete structure to be tested, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested. When the propagating sound of the first wave in each sound path is determined from the waveform information, ultrasonic tomography is performed through the acoustic path and the propagating sound time corresponding to each sound path to reconstruct the three-dimensional sound velocity distribution field inside the precast concrete structure to be tested. Based on the three-dimensional sound velocity distribution field and a preset non-destructive sound velocity threshold, the internal defect area in the precast concrete structure to be detected is identified.

2. The method of claim 1, wherein, By combining the coordinate information with acoustic constraints, ultrasonic simulation is performed in the three-dimensional space to generate an acoustic path that is not obstructed by internal components. Specifically, this includes: A three-dimensional spatial obstacle model of the internal components is established based on the coordinate information; A set of candidate sensor points is deployed on the node detection surface, and then the acoustic path search space is determined by combining acoustic constraints. Using the three-dimensional spatial obstacle model as a constraint, the line-of-sight propagation feasibility of generating all candidate sound paths in the sound path search space is determined. Based on all feasible acoustic paths for direct line-of-sight propagation, an acoustic path that is not obstructed by internal components is generated.

3. The method of claim 1, wherein, Based on the geometric layout of the acoustic path, intelligent ultrasonic sensors are deployed in the precast concrete structure to be tested, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested. Specifically, this includes: Based on the geometric layout of the acoustic path, the installation positions of the smart ultrasonic sensors are located and marked on the surface of the node entities. Deploy smart ultrasonic sensors at marked locations and ensure acoustic coupling between the sensors and the concrete surface; The intelligent ultrasonic sensor is controlled to emit and receive ultrasonic waves sequentially according to the acoustic path sequence, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested.

4. The method of claim 1, wherein, Determining the propagation of the first wave in each sound path from the waveform information specifically includes: The waveform information is preprocessed to enhance the characteristics of the first wave signal; Identify the first wave arrival point of each acoustic path from the preprocessed waveform information; The propagation time of the first wave in each sound path is calculated based on the arrival point of the first wave.

5. The method as described in claim 1, characterized in that, Ultrasonic tomography is performed through the acoustic path and the propagation time corresponding to each acoustic path to reconstruct the three-dimensional sound velocity distribution field inside the precast concrete structure to be tested. Specifically, this includes: A three-dimensional discretized mesh model of the interior of the precast concrete structure to be tested is established based on the acoustic path. A linear equation system for sound velocity tomography is constructed based on the three-dimensional discretized mesh model and the propagation time of sound. Solve the linear equation system of the sonic velocity tomography to reconstruct the three-dimensional sonic velocity distribution field inside the precast concrete structure to be inspected.

6. The method as described in claim 1, characterized in that, Identifying internal defect regions in the precast concrete structure to be inspected based on the three-dimensional sound velocity distribution field combined with a preset non-destructive sound velocity threshold specifically includes: Based on the preset non-destructive sound velocity threshold for ultrasonic testing of sound concrete samples. The sound velocity values ​​of each voxel in the three-dimensional sound velocity distribution field are compared with the lossless sound velocity threshold for defects. Based on the comparison results, identify the internal defect areas in the precast concrete structure to be inspected.

7. The method as described in claim 1, characterized in that, The internal components refer to the key components in the precast concrete assembly connection nodes that bear the structural force transmission function, including longitudinal reinforcing bars, transverse stirrups, grouting sleeves, and grout-anchored corrugated pipes.

8. An ultrasonic flaw detection system for precast concrete assembly joints, characterized in that, include: The acquisition module is used to acquire a three-dimensional building information model of the precast concrete structure to be inspected, wherein the three-dimensional building information model includes the coordinate information of each internal component in three-dimensional space; The processing module is used to perform ultrasonic simulation in the three-dimensional space by combining the coordinate information with acoustic constraints, thereby generating an acoustic path that is not obstructed by internal components. The processing module is also used to deploy intelligent ultrasonic sensors in the precast concrete structure to be tested based on the geometric layout of the acoustic path, thereby acquiring waveform information of different acoustic paths in the precast concrete structure to be tested. The processing module is also used to determine the propagation time of the first wave in each sound path from the waveform information, and to perform ultrasonic tomography through the acoustic path and the propagation time corresponding to each sound path, thereby reconstructing the three-dimensional sound velocity distribution field inside the precast concrete structure to be detected. The execution module is used to identify internal defect areas in the precast concrete structure to be inspected based on the three-dimensional sound velocity distribution field combined with a preset non-destructive sound velocity threshold.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the ultrasonic flaw detection method for precast concrete assembly connection nodes as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the ultrasonic flaw detection method for precast concrete assembly connection nodes as described in any one of claims 1 to 7.

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