A building structure safety detection method and device based on acoustic wave detection and wave field separation

Abstract

The application discloses a kind of based on acoustic wave detection and wave field separation building structure safety detection method and device, it is related to acoustic wave detection and safety detection technical field.The method includes obtaining initial acoustic wave detection data and carrying out acoustic wave travel time analysis, the spatial distribution range of preliminary determination internal abnormal area;For the range, increase observation density and obtain local enhanced detection data;Wave field separation is carried out to data in space domain and time domain, filter out surface wave and oblique incidence interference wave, extract vertical reflection wave data;Based on vertical reflection wave data, three-dimensional acoustic imaging is carried out, and the spatial positioning feature and geometric profile of abnormal area are obtained;Safety evaluation model is combined to carry out safety evaluation to target detection area.The present application can effectively peel off complex interference wave field, improve abnormal body spatial positioning precision and safety evaluation reliability.

Description

Technical Field

[0001] This invention relates to the field of acoustic wave detection and safety inspection technology, and in particular to a method and device for building structure safety inspection based on acoustic wave detection and wave field separation. Background Technology

[0002] With the acceleration of urbanization, the number of high-rise buildings is constantly increasing, making regular and accurate quality and safety inspections of them particularly important. Especially in earthquake-prone areas, after experiencing the impact of natural seismic waves or long-term environmental micro-seismic effects, the internal structural components of high-rise buildings, such as shear walls and load-bearing columns, are prone to hidden damage such as micro-cracks, material deterioration, or voids. In order to quickly assess the safety status of buildings after an earthquake or to conduct routine seismic performance screening, non-destructive testing technologies based on seismic exploration principles, such as acoustic or microseismic detection, are widely used in the safety inspection and quality inspection of modern engineering structures.

[0003] During detection, artificial seismic sources, such as impact devices, are used to generate sound waves on the surface of building components. Detectors are then used to receive wave field signals reflected or scattered by anomalies within the structure. Furthermore, by processing and analyzing this sound wave data and seismic wave signals, the physical state of the building structure's interior is explored and a safety assessment is conducted.

[0004] However, in practical applications of acoustic detection for complex structures in high-rise buildings, the complex internal boundaries of structural components and the potential presence of multiple cracks of varying sizes lead to severe dispersion, multiple reflections, and mode transitions as the acoustic waves propagate through the confined solid medium after the seismic source excites them. This results in the detector receiving signals containing not only vertically reflected waves reflecting the actual location of anomalies within the medium, but also a large number of complex interference wave fields such as non-vertical reflected waves and surface waves.

[0005] This severe scattering effect and multipath interference greatly increases the difficulty of interpreting acoustic signals and assessing seismic damage. Existing detection methods are unable to accurately extract vertical waveform data with high signal-to-noise ratios, resulting in insufficient accuracy in spatial positioning and quantification of internal structural anomalies, and consequently, inadequate reliability of safety assessments.

[0006] Therefore, it is necessary to provide a method and device for building structure safety inspection based on acoustic wave detection and wave field separation to solve the above-mentioned technical problems. Summary of the Invention

[0007] This invention overcomes the shortcomings of the prior art and provides a method and device for building structure safety detection based on acoustic wave detection and wave field separation.

[0008] To achieve the above objectives, the technical solution adopted by this invention is: a building structure safety inspection method based on acoustic wave detection and wave field separation, comprising the following steps:

[0009] Acquire initial acoustic wave detection data, which is a multipath reflection signal formed by the interaction between the acoustic wave excited by the seismic source and the abnormal area inside the target detection area, collected by the receiving array on the surface of the target detection area;

[0010] The initial acoustic wave detection data is analyzed by acoustic wave travel time to preliminarily determine the spatial distribution range of the internal anomaly zone;

[0011] Acquire local enhanced detection data, which is an acoustic signal collected after increasing the observation density of the receiving array for the spatial distribution range;

[0012] The local enhanced detection data is subjected to wave field separation processing in the spatial and temporal domains to filter out surface waves propagating along the detection surface and interference waves incident at an angle, and extract vertical reflected wave data.

[0013] Three-dimensional acoustic imaging is performed based on the extracted vertical reflected wave data to obtain the spatial positioning features and geometric contours of the internal anomaly area.

[0014] Based on the spatial positioning features and geometric contours, and combined with a preset security assessment model, a security assessment is performed on the target detection area.

[0015] In a preferred embodiment of the present invention, the step of acquiring initial acoustic wave detection data and performing acoustic wave travel time analysis to preliminarily determine the spatial distribution range of the internal anomaly region specifically includes:

[0016] Identify key structural features of the target detection area, divide the surface of the target detection area into observation grids based on the key structural features, and deploy multi-channel receiving arrays at the grid nodes;

[0017] An elastic wave is excited by applying excitation using a seismic source, and the multi-channel receiving array synchronously records the wave field signal to obtain the initial acoustic wave detection data;

[0018] Feature extraction is performed on the initial acoustic wave detection data to obtain the travel time and amplitude information of the direct wave and the reflected wave. A velocity cloud field map is established through multi-path wave velocity inversion. Spatial clustering and cross-location analysis are performed on the wave velocity and amplitude anomalies to preliminarily determine the spatial distribution range of the internal anomaly zone.

[0019] In a preferred embodiment of the present invention, the acquisition of local enhanced detection data specifically includes:

[0020] Based on the preliminarily determined spatial distribution range of the internal anomaly zone, the coordinates of the anomaly center, its spatial orientation, and its estimated size are extracted.

[0021] The spatial range is expanded along the spatial direction and vertical direction to construct a densified detection window for local enhanced observation;

[0022] Based on the extracted spatial orientation and estimated size, the array element layout parameters and beam parameters of the phased receiver array are calculated. The array element layout parameters and beam parameters include the array element spacing, array arrangement, beam deflection angle, focusing depth sequence and excitation frequency.

[0023] Based on the calculated array element layout parameters and beam parameters, directional acoustic wave excitation and reception are performed to obtain the locally enhanced detection data.

[0024] In a preferred embodiment of the present invention, before performing wavefield separation processing in the spatial and temporal domains on the locally enhanced detection data, wavefield enhancement processing is further performed on the data. The specific steps are as follows:

[0025] The acoustic velocity was measured in an anomaly-free reference zone within the target detection area and corrected for the ambient temperature to obtain the calibrated velocity wave. ;

[0026] According to the calibration fast wave The direct wave time window is calculated based on the distance between detection points, and a window function is used to extract the signal within the time window from the locally enhanced detection data. ;

[0027] The intercepted signal is time-reversed to generate an inverted signal. The inverted signal is then subjected to a frequency weighting function to enhance the frequency band signal sensitive to anomalies. The transmit power is adjusted in conjunction with the array element delay and a focused extension reconstruction is performed.

[0028] In a preferred embodiment of the present invention, the wavefield separation determination condition for extracting the vertical reflected wave data is as follows:

[0029] Let the instantaneous vibration direction vector of the medium particles during elastic wave propagation be... The wave field propagation direction vector is The normal unit vector of the detection surface is n;

[0030] Calculate the polarization angle between the particle vibration direction and the normal of the detection surface. ;

[0031] Calculate the incident angle between the wave field propagation direction and the normal of the detection surface. ;

[0032] When the separation criteria are met simultaneously <10° and When the angle is less than 5°, the corresponding waveform component is determined to be the vertical reflected wave data.

[0033] In a preferred embodiment of the present invention, the method for wavefield separation of the locally enhanced detection data specifically includes:

[0034] Based on the data acquired by the three-component detectors in the receiving array, the polarization angle is obtained by normalizing the data at each time point t and calculating the instantaneous vibration direction unit vector. ;

[0035] The spatial spectrum of the array data is calculated using the MUSIC algorithm. The main peak direction is located and extracted as the propagation direction vector k of the incident wavefield, and then the incident angle is obtained. ;

[0036] Ray tracing is performed using a 3D mesh model of the structure, and a path-time mapping table is established to record the propagation time window of each ray path. Paths with an angle ≥5° are marked as invalid non-vertical tilted incident wave paths;

[0037] A dynamic weighting function is constructed based on the separation determination criteria. A joint determination is performed at each time point t, if and only if the polarization angle corresponding to that time point is... When the angle is less than 10° and the wave field propagation path at that time point is not marked as an invalid non-vertical tilted incident path, the dynamic weighting function... The value is 1 if it is set to 1, otherwise the value is 0.

[0038] Using the dynamic weight function The original locally enhanced detection data is reconstructed to remove clutter and output an enhanced waveform containing only vertically reflected waves.

[0039] In a preferred embodiment of the present invention, the step of performing three-dimensional acoustic imaging based on the extracted vertical reflected wave data to obtain the spatial positioning features and geometric contours of the internal anomaly region specifically includes:

[0040] By utilizing the extracted vertical reflected wave data and combining it with the regional background wave velocity model, a pre-stack migration imaging algorithm is used to perform wavefield extrapolation in the three-dimensional spatial domain, thereby achieving focusing on the reflection interface of the internal anomalous body.

[0041] Extract the strong amplitude envelope attribute from the focused 3D data volume, and extract the abnormal boundary point cloud data through threshold segmentation;

[0042] Surface reconstruction is performed based on the boundary point cloud data to generate the three-dimensional geometric contour of the internal anomaly area, and its spatial positioning features are extracted. The spatial positioning features include the spatial depth, volume scale and distribution shape of the anomaly area.

[0043] In a preferred embodiment of the present invention, the step of performing a security assessment on the target detection area in conjunction with a preset security assessment model specifically includes:

[0044] Based on the spatial location features and geometric contours of the acquired internal abnormal area, the defect type is determined;

[0045] The geometric contours and defect types are mapped to the finite element analysis model to perform a three-dimensional mechanical model of the building component containing the defect in the target detection area.

[0046] Boundary conditions are applied to the mechanical model to calculate stress distribution and deformation parameters. By comprehensively comparing with the defect-free state, the reduction effect of internal abnormal zones on stiffness and bearing capacity is quantitatively evaluated, and the safety performance level of building components is classified.

[0047] A building structure safety detection device based on acoustic wave detection and wave field separation includes a data acquisition system and a control and data processing system communicatively connected to the data acquisition system.

[0048] The data acquisition system includes: a source component for exciting elastic wave groups in the target detection area, and a multi-channel receiving array for acquiring multipath reflection signals;

[0049] The control and data processing system includes:

[0050] The initial travel time analysis module is used to acquire initial acoustic wave detection data and perform travel time and wave velocity inversion to preliminarily determine the spatial distribution range of the internal anomaly zone.

[0051] An array enhancement control module is used to adjust the observation density and beam parameters of the receiving array for the spatial distribution range, and to control the acquisition of local enhanced detection data.

[0052] The joint wave field separation module is used to perform spatial and temporal wave field separation processing on the local enhanced detection data, filter out surface waves and oblique incident interference waves, and extract vertical reflected wave data.

[0053] The acoustic wave migration imaging module is used to perform three-dimensional migration imaging based on the extracted vertical reflected wave data, and to extract the spatial positioning features and geometric contours of the internal anomalous area.

[0054] The security assessment module is used to perform a security energy assessment of the target detection area by combining a preset security assessment model and the geometric contour.

[0055] In a preferred embodiment of the present invention, the multi-channel receiving array includes: a high-frequency phased array probe array and a three-component detector;

[0056] The seismic source assembly includes: an impact seismic source with adjustable energy and trigger synchronization accuracy;

[0057] The joint wavefield separation module has a built-in time reversal enhancement processing unit and a MUSIC algorithm spatial spectrum estimation unit, which are used to jointly perform wavefield band reshaping, polarization filtering and multipath ray tracing elimination.

[0058] In a preferred embodiment of the present invention,

[0059] This invention addresses the shortcomings of the prior art and has the following beneficial effects:

[0060] (1) This invention provides a method for building structure safety inspection based on acoustic wave detection and wavefield separation. First, a large-scale coarse exploration is performed to quickly locate the approximate spatial range of the internal anomaly zone. Then, the observation density of the receiving array is increased and the beam parameters are optimized for localized intensified detection within this range. Finally, wavefield separation processing combining the spatial and temporal domains is used to accurately filter out surface waves propagating along the detection surface and interference waves incident at an angle from the mixed wavefield, retaining only vertically reflected waves. This process directly removes complex multipath scattering and mode conversion interference from the physical level, making the defect reflection signals that were originally submerged by noise stand out. Compared with the traditional method of directly interpreting the full waveform data, this invention solves the problem of low signal-to-noise ratio caused by dispersion and multiple reflections within a confined structure, providing a high-fidelity data foundation for subsequent imaging and improving the reliability of hidden defect detection and spatial positioning accuracy.

[0061] (2) The wave field separation judgment condition used in this invention combines polarization filtering with ray tracing path verification by simultaneously constraining the polarization angle between the instantaneous vibration direction of the medium particles and the normal of the detection surface, as well as the incident angle between the wave field propagation direction and the normal of the detection surface. This method uses the particle vibration vector recorded by the three-component detector and the wave propagation direction estimated by the phased array spatial spectrum to jointly screen waveform components from both kinematic and dynamic dimensions of the wave. It can accurately identify and eliminate interference waves whose vibration direction deviates from the normal and whose propagation path is not perpendicular, retaining only the perpendicular reflection wave that simultaneously satisfies the two angle thresholds. This separation method with a clear physical mechanism breaks through the limitation of traditional single filtering methods that cannot effectively distinguish interference waves of the same frequency, making the extracted reflection waveform more realistically reflect the spatial position of the abnormal interface.

[0062] (3) In the local enhancement detection stage, this method dynamically calculates the element spacing, array arrangement, beam deflection angle, and focusing depth sequence of the phased array receiver based on the spatial orientation and estimated size of the anomaly area determined in the initial exploration, directly mapping the geometric parameters of the anomaly area to beam control parameters. This enables the detection beam to perform directional deflection scanning along the anomaly area and to focus at different depths. Compared with the fixed observation grid method, this method achieves spatially non-uniform densified observation at the signal acquisition end, ensuring both the low-frequency penetration requirement of deep anomalies and the high-frequency resolution requirement of micro-cracks, reducing spatial aliasing and energy divergence, and making the anomaly information carried by the local enhancement detection data richer and more concentrated.

[0063] (4) Before wavefield separation, this method introduces wavefield enhancement preprocessing based on time reversal and frequency weighting. The direct wave time window is calculated by using the measured background wave velocity in the anomaly-free reference area and after temperature correction. The signal is intercepted and then time-reversed. A frequency weighting function is applied to the reversed signal to enhance the frequency band signal sensitive to anomalous bodies. Then, focusing, extension, and reconstruction are performed in combination with array element delay adjustment. This processing utilizes the adaptive focusing characteristics of time reversal to achieve phase alignment and coherent superposition of the weak scattered wave energy dispersed in multiple receiving channels at the target focal point, effectively enhancing the weak reflection signal generated by concealed damage. At the same time, frequency weighting further highlights the sensitivity of high-frequency components to small defects, providing high signal-to-noise ratio waveform data for subsequent wavefield separation and imaging.

[0064] (5) This method ultimately performs three-dimensional acoustic imaging on the extracted vertical reflected wave data, and directly maps the spatial positioning features and geometric contours of the generated internal anomaly area to the finite element analysis model. It then performs three-dimensional mechanical modeling of the building components with defects, and calculates stress distribution and deformation parameters by applying boundary conditions, quantifying the reduction effect of the anomaly area on stiffness and bearing capacity. This transforms the non-destructive testing results from abstract acoustic property anomalies into a mechanical calculation model with clear physical boundaries, directly translating acoustic impedance differences into structural stress concentration factors and ultimate bearing capacity attenuation. This achieves a substantial leap from geometric detection to mechanical assessment, providing directly applicable quantitative basis for the classification of building structure safety performance levels and repair and reinforcement decisions. Attached Figure Description

[0065] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 This is a flowchart of a building structure safety inspection method based on acoustic wave detection and wave field separation according to the present invention;

[0067] Figure 2 This is a system block diagram of a building structure safety detection device based on acoustic wave detection and wave field separation according to the present invention. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein. Therefore, the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0070] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this application based on the specific circumstances.

[0071] Example 1:

[0072] like Figure 1 As shown, this invention provides a method for building structure safety inspection based on acoustic wave detection and wavefield separation, comprising the following steps:

[0073] S1. Acquire initial acoustic wave detection data. The initial acoustic wave detection data is the multipath reflection signal collected by the receiving array on the surface of the target detection area, which is formed by the interaction between the acoustic wave excited by the seismic source and the abnormal area inside the target detection area.

[0074] S2. Perform acoustic travel time analysis on the initial acoustic wave detection data to preliminarily determine the spatial distribution range of the internal anomaly zone;

[0075] S3. Acquire local enhanced detection data, which is the acoustic signal collected after increasing the observation density of the receiving array for the spatial distribution range;

[0076] S4. Perform wave field separation processing in the spatial and temporal domains on the local enhanced detection data, filter out surface waves propagating along the detection surface and interference waves incident at an angle, and extract vertical reflected wave data.

[0077] S5. Perform three-dimensional acoustic imaging based on the extracted vertical reflected wave data to obtain the spatial positioning features and geometric contours of the internal anomalous area.

[0078] S6. Based on spatial positioning features and geometric contours, and combined with a preset security assessment model, conduct a security assessment of the target detection area.

[0079] The core concept of this invention lies in: first, large-area coarse probing to define the region, then high-density fine-tuning to define the region, and finally achieving high-fidelity imaging through joint wavefield separation. In the actual service environment of complex high-rise buildings, when sound waves are excited using artificial seismic sources, due to the constraints of the building structure boundaries and the inhomogeneity of the internal medium, the sound waves will experience severe dispersion, multiple reflections, and mode conversions during propagation, such as the conversion of volume waves into Rayleigh surface waves. In traditional impact imaging methods or ultrasonic testing, these multipath effects intertwine and overlap with scattered waves, greatly masking the reflected signals carrying true defect interface information.

[0080] To this end, after initially determining the approximate spatial distribution of the anomalous region, this embodiment of the invention strategically deploys a phased array receiver and designs optimal beam parameters to reduce spatial aliasing at the signal acquisition end. In the data processing stage, a wavefield separation technique based on polarization characteristics and path tracing is employed to extract the vertically reflected waves containing crucial depth information from the mixed wavefield. Compared to existing conventional methods, this invention's detection method not only reduces scattering noise and multipath crosstalk but also outputs waveform data with a high signal-to-noise ratio for subsequent 3D imaging. This allows the imaged geometric model to be directly mapped into finite element analysis software for mechanical verification, improving the certainty and reliability of engineering structure safety assessments.

[0081] The following is a detailed explanation of each detection step in the embodiments of the present invention.

[0082] In step S1, the first step in acquiring initial acoustic wave detection data is to scientifically construct an on-site acoustic wave observation system. Specifically, the operator first identifies the key structural features of the target detection area, focusing on beam-column joints prone to stress concentration, opening edges, and curved corners or concave-convex surfaces with abrupt shape changes. Based on these key structural features, a spatial observation grid is divided on the surface of the target detection area.

[0083] In one embodiment, for flat and homogeneous load-bearing walls, the size of the grid cells is usually uniformly set between 0.5m×0.5m and 2m×2m; while for key feature locations such as stress concentration or abrupt shape changes identified above, a non-uniform grid division strategy is adopted to locally reduce the grid size in order to improve the spatial sampling rate.

[0084] Furthermore, multi-channel receiving arrays are deployed at the divided grid nodes. To accurately capture elastic wave signals containing different frequency bands and polarization characteristics, the receiving array preferably uses a three-component broadband detector, such as a seismic detector with a dominant frequency response covering 10Hz to 50kHz. For the seismic source, a standardized artificial seismic source with constant mass and adjustable impact energy, such as a 250g standard steel hammer or an electromagnetic exciter, can be used to ensure the repeatability of the elastic wave energy and the consistency of the wavelet for each excitation.

[0085] It is worth noting that before comprehensively collecting the initial acoustic wave detection data, this embodiment also provides a background wave field pre-inspection method: randomly select 2-4 benchmark detection points without obvious appearance defects from the detection area and conduct pre-tests respectively. By recording waveforms at different offset distances, a reference waveform database of the area under anomaly-free conditions is established, specifically including the normal wave velocity range, typical amplitude attenuation curves, and phase consistency characteristics.

[0086] After the preliminary inspection is completed, the seismic source is used to apply excitation at the predetermined excitation point to generate elastic waves. At this time, a multi-channel receiving array, preferably in conjunction with a synchronous seismic data acquisition instrument with more than 24 channels, performs zero-delay synchronous sampling to fully record the multi-path reflection and scattering signals formed by the interaction between the sound waves excited by the seismic source and the anomalous area inside the target detection area, which is the initial sound wave detection data.

[0087] In step S2, after acquiring the initial acoustic wave detection data, acoustic wave travel time analysis is performed on the data to preliminarily determine the spatial distribution range of the internal anomaly region, specifically including:

[0088] S21. Extract features from the initial acoustic wave detection data recorded by each channel, accurately pick up the first arrival travel time information and amplitude peak of the direct wave and the main reflected wave; combine the spatial coordinates of each detector, use the multi-path wave velocity inversion algorithm, and select the best travel time tomography technique to iteratively reconstruct the wave velocity structure inside the medium, thereby establishing a three-dimensional velocity cloud field map of the entire detection area.

[0089] S22. Based on the reconstructed velocity cloud field map and the extracted wave field dynamics features, wave field anomaly points are selected according to anomaly detection rules; these anomaly detection rules include, but are not limited to:

[0090] Wave velocity anomaly: The calculated local elastic wave propagation velocity is significantly lower than the pre-detected lower limit of normal wave velocity;

[0091] Amplitude anomaly: Calculate the ratio of the amplitude at the test point to the amplitude at the reference point. ,when When the value is less than 0.7, it is determined that there is strong wave energy attenuation and it is marked as a suspected defect signal;

[0092] Phase anomaly: The phase difference of the same wave packet on adjacent detectors exceeds 10%.

[0093] S23. Since single-point anomalies may be caused by surface heterogeneity or poor coupling, this embodiment introduces spatial clustering and cross-location analysis to eliminate artifacts. For example, a spatial search window is set, such as a spherical neighborhood with a radius of 0.3m. When three or more wave velocity / amplitude anomaly points are clustered within this neighborhood, the area is determined to be a valid internal anomaly region. By extracting the envelope of these valid anomaly cluster centers, the spatial distribution range, macroscopic orientation, and estimated length and width dimensions of internal anomaly regions, such as microcrack clusters and cavities, can be preliminarily determined, providing prior information for subsequent localized intensified detection.

[0094] In step S3, based on the spatial distribution range of the internal anomaly region initially identified in step S2, a locally enhanced phased array exploration scheme is generated.

[0095] In specific implementation, the methods for obtaining locally enhanced detection data include:

[0096] S31. Extract the geometric and spatial parameters of the internal anomaly region from the preliminary exploration results, including: anomaly center coordinates, spatial orientation determined based on wave velocity gradient direction. And the estimated major axis, minor axis and depth dimensions.

[0097] S32. Extend outward by 1.2 times along the long axis of the internal anomaly region and by 1.5 times along the short axis to construct a dense detection window for local enhanced observation, ensuring complete recording of diffraction waves generated at the edge of the anomaly and avoiding imaging boundary truncation effects.

[0098] S33. Based on the extracted spatial orientation and estimated dimensions, calculate the element layout parameters and beam parameters of the phased array receiver. These parameters include element spacing, array arrangement, beam deflection angle, focusing depth sequence, and excitation frequency. The specific calculation and configuration methods are as follows:

[0099] Element spacing setting: To effectively suppress spatial aliasing during high-frequency signal acquisition, the element spacing is calculated and constrained. ;in, For wavelength, For transmitting wave speed to the wall, In this embodiment, the excitation frequency is preferably configured to be 0.02 m.

[0100] Array layout design: The layout is flexibly adjusted according to the extracted spatial orientation. When the internal abnormal area extends in a straight line, a linear array is arranged; when the detected structural defect extends in a curve, the array is arranged in a conjugate arc shape.

[0101] Beam deflection angle setting: Set the direction perpendicular to the spatial orientation as the primary scanning direction, i.e. It drives the beam to perform multi-angle dynamic deflection within a range of ±30° in the main scanning direction, for example, by setting a step of 5°, for a total of 13 deflection angles.

[0102] Focusing depth sequence and excitation frequency matching: The focusing depth sequence is set in layers according to the estimated depth size, such as dividing it into multiple focusing points such as 0.2m, 0.4m, 0.6m, etc., according to the depth step. The excitation frequency is dynamically adjusted according to the physical size of the anomaly. For microcracks, high frequency parameters are matched, while for deep anomalies, the frequency is reduced to ensure sufficient wave field penetration.

[0103] S34. Drive each element of the phased array to apply the set delay time, perform dynamic deflection scanning and synchronous reception at multiple angles and depths, thereby acquiring locally enhanced wavefield data that balances high spatial resolution and deep penetration.

[0104] Through the above steps, the geometric parameters of the internal anomaly region are directly mapped to the beam control parameters, realizing a closed-loop detection logic from "what the defect looks like" to "how to scan," significantly improving detection targeting and efficiency. Furthermore, it effectively distinguishes signals from important detection points from other auxiliary signals, enhancing detection accuracy and reliability.

[0105] In step S4, the local enhanced detection data is subjected to wave field separation processing in the spatial and temporal domains to filter out surface waves propagating along the detection surface and interference waves incident at an angle, and extract the vertical reflected wave data.

[0106] The basic principle of elastic wave detection technology lies in using the propagation characteristics of waves to detect anomalies within a structure. When elastic waves, such as sound waves, propagate through a structure, they encounter defects (such as cracks or voids) and undergo reflection and scattering. These reflected and scattered waves carry crucial information such as the location and shape of the defects. However, in actual detection processes, due to the complexity of the structure, the propagation path of elastic waves is often not a single vertical path, but rather involves scattering and reflection in multiple directions, resulting in complex waveform data.

[0107] The presence of non-vertical reflection waveform data not only increases the difficulty of data analysis, but may also obscure the true defect information, leading to misjudgment or omission.

[0108] In specific implementation, the wavefield separation method for locally enhanced detection data includes:

[0109] S41. Perform time-reversal-based wavefield enhancement preprocessing on the locally enhanced detection data. Measure the wave velocity in a defect-free reference area adjacent to the target detection region. The background wave velocity was obtained after calibration with the ambient temperature on site. : T represents the ambient temperature, with a temperature coefficient α = 0.002 / ℃;

[0110] According to background wave velocity Calculate the direct wave time window by combining the detection point spacing L. A window function (such as the Hanning window) is used to extract the signal s(t) within the time window of the probe data and invert it into s(-t), and a frequency weight is applied to the inverted signal: ,in, To enhance the high-frequency wave energy that is more sensitive to concealed damage; subsequently, wavefield focusing, extension, and reconstruction are performed using a phased array receiver, the specific reconstruction method of which is as follows:

[0111] Based on the preset spatial location of the target focal point and the spatial coordinates of each element in the receiving array, combined with the background wave velocity after environmental calibration, the spatial propagation distance and travel time difference of the sound waves received by each element to reach the focal point are calculated, thereby determining the required time delay compensation for each element. To suppress sidelobe energy leakage during the spatial superposition of wave fields, corresponding spatial distribution amplitude weights are assigned to each element according to its relative geometric position in the array. For example, the element weights in the central region of the array are set to the maximum value and then smoothly decrease towards the edge regions. The signals of each element after time reversal and frequency weighting are strictly aligned in the time domain according to the calculated time delay compensation, and multi-channel coherent superposition is performed in combination with the corresponding spatial distribution amplitude weights. Through this multi-channel delay and weighted superposition mechanism, the weak scattered waves of each channel achieve precise phase alignment and physical constructive interference of energy at the set target focal point, thereby outputting a reconstructed high signal-to-noise ratio focused waveform.

[0112] S42. Separate the vertical reflected wave data from the collected data, under the following conditions:

[0113] Vibration direction vector ;

[0114] Propagation direction vector ;

[0115] Determination of perpendicular incidence: Using three-component detector data, the angle between the vibration direction and the normal to the detection surface is calculated. : ,reserve The signal components, i.e., the vertically reflected wave data;

[0116] Where n is the perpendicular direction (normal direction) of the detection surface, and in this embodiment, the three-component detector is installed strictly perpendicular to the detection surface, and n is taken as the Z-axis direction of the detector coordinate system; v is the instantaneous vibration direction vector of the medium particles when the elastic wave propagates, and the vibration signals in three orthogonal directions are recorded by the three-component sensor (X, Y, Z axes). The composite vibration direction vector is: .

[0117] This step specifically includes the following sub-steps:

[0118] S421. Based on the wavefield data acquired by the three-component detector, normalize the vibration signal at each time point t and calculate the instantaneous vibration direction unit vector: ;

[0119] Using the normal to the detection surface n=(0,0,1) as a reference, calculate the angle of the vibration direction point by point: ,reserve The signal with the specified time interval is set to zero, while the rest are set to zero, in order to eliminate signal components whose vibration direction deviates from the normal.

[0120] S422. The incident wave direction k is estimated using the MUSIC algorithm.

[0121] Based on the MUSIC algorithm, spatial spectrum is calculated using sensor array data. : Where EN is the noise subspace and a is the array manifold vector;

[0122] Positioning the incident wave direction angle Extract the main peak direction as the incident wave direction k;

[0123] A 3D mesh of the structure is constructed based on the BIM model. Ray tracing is performed on each possible path, and the angle between the ray propagation direction and the normal is determined. Mark it as an invalid path to verify whether the propagation path is strictly perpendicular and eliminate interference from non-perpendicular oblique incidence.

[0124] S423. Establish a path-time mapping table, record the propagation time window of each ray path (e.g., from the arrival time t1 of the direct wave to the arrival time t2 of the reflected wave), and remove the signal components corresponding to all non-vertical inclined incident paths.

[0125] For each time point t, the weights must be satisfied simultaneously. : ;

[0126] Signal reconstruction is performed, and the output is an enhanced signal containing only vertical elastic waves. : ,in, This is the original signal.

[0127] After the above steps, the polarization filtering and path constraint results are combined to accurately separate non-perpendicularly tilted incident waveform data, retaining only the vertically reflected wave data related to the defect. Furthermore, based on the vertically reflected wave data, the precise location and size of structural defects within the detection area are determined, significantly improving the signal-to-noise ratio and positioning accuracy of defect detection.

[0128] In step S5, three-dimensional acoustic imaging is performed based on the extracted vertical reflected wave data to obtain the spatial positioning features and geometric contours of the internal anomaly area.

[0129] After wavefield separation processing in step S4, high signal-to-noise ratio vertical reflected wave data with surface waves and multipath oblique interference removed are obtained, which provides an ideal data foundation for high-fidelity imaging of the interior of structures.

[0130] In practice, three-dimensional acoustic imaging methods include:

[0131] S51. Using the extracted vertical reflected wave data and the regional background wave velocity model obtained in step S2, a three-dimensional pre-stack time migration or pre-stack depth migration (PSDM) imaging algorithm is used to perform inverse wavefield extrapolation in the spatial domain. By calculating the diffraction trajectory of the reflected wave energy received by each detector in the three-dimensional spatial grid and performing coherent superposition, the reflected energy of internal anomalous bodies (such as crack surfaces and cavity walls) is accurately focused, generating a three-dimensional data volume containing three-dimensional spatial coordinates and amplitude information.

[0132] S52. Perform seismic attribute analysis on the focused 3D data volume, and use Hilbert transform to extract the instantaneous amplitude of the 3D wavefield, i.e., the strong amplitude envelope attribute. Set a dynamic adaptive threshold, for example, take 15% to 25% of the local spatial wavefield energy peak as the cutoff threshold, and extract the spatial grid points above the threshold to form 3D anomaly boundary point cloud data representing the defect boundary.

[0133] S53. Based on the boundary point cloud data, Poisson surface reconstruction or Delaunay triangulation algorithm is used to perform surface fitting and mesh reconstruction to generate the three-dimensional geometric contour of the internal anomaly area. Then, its spatial positioning features are extracted from the geometric contour, specifically including: the spatial depth of the top and bottom of the anomaly area, absolute volume scale, major and minor axis ratio, and distribution morphology parameters such as orientation and tilt angle in three-dimensional space.

[0134] In step S6, a security assessment is performed on the target detection area based on spatial positioning features and geometric contours, combined with a preset security assessment model.

[0135] This step aims to transform the "geometric topography" obtained from geophysical exploration into "safety indicators" in engineering mechanics, achieving a closed loop from non-destructive testing to life assessment. Specifically, it includes:

[0136] S61. Determine the physical property type of the defect based on the polarity characteristics of the reflected wave and the extracted geometric contour. For example, when the reflected wave exhibits strong negative polarity and is accompanied by multiple diffractions, it is determined to be an air-filled "void" or "wide crack"; when it appears as a chaotic group of weak reflections, it is determined to be a concrete "segregation" or "honeycomb" area.

[0137] S62. The generated 3D geometric contour and defect physical attribute types are mapped to the structural finite element analysis model through Boolean operations. That is, in the intact benchmark model of the building component where the target detection area is located, the corresponding area's elements are precisely "removed" or "weakened" to establish a refined 3D mechanical model containing the actual shape of the defects.

[0138] S63. Apply boundary conditions under actual service conditions (such as dead load, live load, and wind and seismic loads) to the defective mechanical model, and calculate its structural response parameters such as stress concentration factor and maximum displacement deformation using a nonlinear finite element solver. Compare the calculation results with the baseline model in a defect-free state to quantitatively assess the reduction effect of the internal anomaly zone on the overall stiffness and ultimate bearing capacity of the component. Finally, based on the reduction factor and referring to the current national building structure appraisal standards, classify the safety performance level of the building component (e.g., into four levels: I, II, III, and IV), and output repair and reinforcement recommendations accordingly.

[0139] The method provided by this invention employs a combination of macroscopic and microscopic spatial non-uniform physical sampling, directly suppressing spatial aliasing and diffraction interference in the high-frequency band at the receiving end. The core wavefield separation algorithm, through dual geometric constraints on the three-dimensional vector of instantaneous particle vibration and the wavefield propagation path, completely eliminates Rayleigh surface wave disturbances and multi-path tilting secondary clutter within the confined boundary at the physical level. The purified vertically reflected acoustic energy thus eliminates divergent arc artifacts in three-dimensional offset imaging, enabling precise focusing of the reflected energy from hidden defect interfaces. Finally, the high-precision defect geometric point cloud is directly mapped onto the structural finite element mesh. The system directly calculates the amplification effect of the defect morphology on the local stress concentration coefficient and the actual attenuation of the component's ultimate bearing capacity through computational power, substantially transforming conventional apparent acoustic detection into computational solid mechanics quantitative analysis with clearly defined physical boundary conditions.

[0140] Example 2:

[0141] Based on the above detection method, this invention also provides a building structure safety detection device based on acoustic wave detection and wavefield separation. For example... Figure 2As shown, the device is highly integrated in terms of hardware architecture and deeply customized in terms of software algorithms, designed to perform detection processes such as steps S1-S6.

[0142] Specifically, the device includes a data acquisition hardware system and a control and data processing system (typically mounted in a high-performance edge computing terminal or mobile workstation) that is connected to the hardware system via a high-speed industrial bus (such as Gigabit Ethernet or fiber optic data cable).

[0143] The data acquisition hardware system includes: a source assembly for exciting a broadband elastic wave group on the surface of the target detection area, preferably comprising an electromagnetic shock source with precisely adjustable energy and trigger synchronization accuracy; and a multi-channel receiving array for acquiring multipath reflection signals. To meet the wavefield separation requirements, the multi-channel receiving array integrates a high-frequency phased array probe array and a high-sensitivity three-component detector, capable of simultaneously recording particle vibration signals in three orthogonal directions in space.

[0144] The control and data processing system is logically configured to include the following functional modules:

[0145] The initial travel time analysis module is used to acquire initial acoustic wave detection data and perform automatic travel time picking and three-dimensional wave velocity inversion to preliminarily determine the spatial distribution range of the internal anomaly zone.

[0146] The array enhancement control module is used to dynamically calculate and adjust the observation density and beam deflection parameters of the receiving array for the locked spatial distribution range, and control the underlying hardware to acquire local enhancement detection data.

[0147] The joint wavefield separation module is the core data cleaning unit of this device, which integrates a time-reversal enhancement processing unit based on FPGA or GPU hardware acceleration and a MUSIC algorithm spatial spectrum estimation unit. This module jointly performs wavefield band reshaping, particle polarization filtering, and multi-path three-dimensional ray tracing removal, outputting clean vertical reflection wave data;

[0148] The acoustic migration imaging module is used for rapid three-dimensional pre-stack migration imaging based on extracted vertical reflected wave data, and to extract high-precision spatial positioning features and geometric contours of internal anomaly areas.

[0149] The safety assessment module is used to seamlessly import the above geometric contours into a preset mechanical model to quantitatively assess and determine the safety performance of the target detection area.

[0150] The detection device of this invention deeply integrates a broadband directional excitation system and a multi-channel receiving array. It synchronously and accurately captures weak scattered wave trains and the trajectories of triaxial orthogonal particles using a high-frequency phased array probe and a three-component geophone. The dedicated hardware computing unit built into the wavefield separation module performs time-reversal focusing reconstruction and eigenvalue decomposition calculations of the spatial spectrum matrix in parallel at the underlying level. This hardware-level decoupling mechanism avoids time delays and phase distortions in the transmission of massive amounts of 3D seismic wave data, outputting pure P-wave reflection signals truncated from transverse and surface wave crosstalk in real time. The back-end evaluation module receives the purified wavefield feature matrix and directly solves for the initial stiffness matrix degradation parameters of the damaged area based on the nonlinear constitutive relationship of concrete. This directly translates the abstract acoustic impedance anomaly characteristics into quantitative mechanical parameters of the shear and bending bearing capacity of building nodes, providing physical data support for full-life-cycle disaster simulation.

[0151] Based on the preferred embodiments of the present invention described above, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for building structure safety inspection based on acoustic wave detection and wavefield separation, characterized in that, Includes the following steps: Acquire initial acoustic wave detection data, which is a multipath reflection signal formed by the interaction between the acoustic wave excited by the seismic source and the abnormal area inside the target detection area, collected by the receiving array on the surface of the target detection area; The initial acoustic wave detection data is analyzed by acoustic wave travel time to preliminarily determine the spatial distribution range of the internal anomaly zone; Acquire local enhanced detection data, which is an acoustic signal collected after increasing the observation density of the receiving array for the spatial distribution range; The local enhanced detection data is subjected to wave field separation processing in the spatial and temporal domains to filter out surface waves propagating along the detection surface and interference waves incident at an angle, and extract vertical reflected wave data. Three-dimensional acoustic imaging is performed based on the extracted vertical reflected wave data to obtain the spatial positioning features and geometric contours of the internal anomaly area. Based on the spatial positioning features and geometric contours, and combined with a preset security assessment model, a security assessment is performed on the target detection area.

2. The method for building structure safety inspection based on acoustic wave detection and wave field separation according to claim 1, characterized in that, The process of acquiring initial acoustic wave detection data and performing acoustic wave travel time analysis to preliminarily determine the spatial distribution range of the internal anomaly region specifically includes: Identify key structural features of the target detection area, divide the surface of the target detection area into observation grids based on the key structural features, and deploy multi-channel receiving arrays at the grid nodes; An elastic wave is excited by applying excitation using a seismic source, and the multi-channel receiving array synchronously records the wave field signal to obtain the initial acoustic wave detection data; Feature extraction is performed on the initial acoustic wave detection data to obtain the travel time and amplitude information of the direct wave and the reflected wave. A velocity cloud field map is established through multi-path wave velocity inversion. Spatial clustering and cross-location analysis are performed on the wave velocity and amplitude anomalies to preliminarily determine the spatial distribution range of the internal anomaly zone.

3. The method for building structure safety inspection based on acoustic wave detection and wavefield separation according to claim 1, characterized in that, The acquisition of locally enhanced detection data specifically includes: Based on the preliminarily determined spatial distribution range of the internal anomaly zone, the coordinates of the anomaly center, its spatial orientation, and its estimated size are extracted. The spatial range is expanded along the spatial direction and vertical direction to construct a densified detection window for local enhanced observation; Based on the extracted spatial orientation and estimated size, the array element layout parameters and beam parameters of the phased receiver array are calculated. The array element layout parameters and beam parameters include the array element spacing, array arrangement, beam deflection angle, focusing depth sequence and excitation frequency. Based on the calculated array element layout parameters and beam parameters, directional acoustic wave excitation and reception are performed to obtain the locally enhanced detection data.

4. The method for building structure safety inspection based on acoustic wave detection and wavefield separation according to claim 1, characterized in that, Before performing wavefield separation processing in the spatial and temporal domains on the locally enhanced detection data, wavefield enhancement processing is also performed on the data. The specific steps are as follows: The acoustic velocity was measured in an anomaly-free reference zone within the target detection area and corrected for the ambient temperature to obtain the calibrated velocity wave. ; According to the calibration fast wave The direct wave time window is calculated based on the distance between detection points, and a window function is used to extract the signal within the time window from the locally enhanced detection data. ; The intercepted signal is time-reversed to generate an inverted signal. The inverted signal is then subjected to a frequency weighting function to enhance the frequency band signal sensitive to anomalies. The transmit power is adjusted in conjunction with the array element delay and a focused extension reconstruction is performed.

5. The method for building structure safety inspection based on acoustic wave detection and wavefield separation according to claim 1, characterized in that, The extracted vertical reflected wave data has the following wavefield separation criteria: Let the instantaneous vibration direction vector of the medium particles during elastic wave propagation be... The wave field propagation direction vector is The normal unit vector of the detection surface is n; Calculate the polarization angle between the particle vibration direction and the normal of the detection surface. ; Calculate the incident angle between the wave field propagation direction and the normal of the detection surface. ; When the separation criteria are met simultaneously <10° and When the angle is less than 5°, the corresponding waveform component is determined to be the vertical reflected wave data.

6. The method for building structure safety inspection based on acoustic wave detection and wave field separation according to claim 5, characterized in that, The method for wavefield separation of the locally enhanced detection data specifically includes: Based on the data acquired by the three-component detectors in the receiving array, the polarization angle is obtained by normalizing the data at each time point t and calculating the instantaneous vibration direction unit vector. ; The spatial spectrum of the array data is calculated using the MUSIC algorithm. The main peak direction is located and extracted as the propagation direction vector k of the incident wavefield, and then the incident angle is obtained. ; Ray tracing is performed using a 3D mesh model of the structure, and a path-time mapping table is established to record the propagation time window of each ray path. Paths with an angle ≥5° are marked as invalid non-vertical tilted incident wave paths; A dynamic weighting function is constructed based on the separation determination criteria. A joint determination is performed at each time point t, if and only if the polarization angle corresponding to that time point is... When the angle is less than 10° and the wave field propagation path at that time point is not marked as an invalid non-vertical tilted incident path, the dynamic weighting function... The value is 1 if it is set to 1, otherwise the value is 0. Using the dynamic weight function The original locally enhanced detection data is reconstructed to remove clutter and output an enhanced waveform containing only vertically reflected waves.

7. The method for building structure safety inspection based on acoustic wave detection and wavefield separation according to claim 1, characterized in that, The step of performing three-dimensional acoustic imaging based on the extracted vertical reflected wave data to obtain the spatial positioning features and geometric contours of the internal anomaly region specifically includes: By utilizing the extracted vertical reflected wave data and combining it with the regional background wave velocity model, a pre-stack migration imaging algorithm is used to perform wavefield extrapolation in the three-dimensional spatial domain, thereby achieving focusing on the reflection interface of the internal anomalous body. Extract the strong amplitude envelope attribute from the focused 3D data volume, and extract the abnormal boundary point cloud data through threshold segmentation; Surface reconstruction is performed based on the boundary point cloud data to generate the three-dimensional geometric contour of the internal anomaly area, and its spatial positioning features are extracted. The spatial positioning features include the spatial depth, volume scale and distribution shape of the anomaly area.

8. A method for building structure safety inspection based on acoustic wave detection and wavefield separation according to claim 1, characterized in that, The security assessment of the target detection area, based on a pre-set security assessment model, specifically includes: Based on the spatial location features and geometric contours of the acquired internal abnormal area, the defect type is determined; The geometric contours and defect types are mapped to the finite element analysis model to perform a three-dimensional mechanical model of the building component containing the defect in the target detection area. Boundary conditions are applied to the mechanical model to calculate stress distribution and deformation parameters. By comprehensively comparing with the defect-free state, the reduction effect of internal abnormal zones on stiffness and bearing capacity is quantitatively evaluated, and the safety performance level of building components is classified.

9. A building structure safety inspection device based on acoustic wave detection and wavefield separation, performing a building structure safety inspection method based on acoustic wave detection and wavefield separation as described in any one of claims 1-8, characterized in that, It includes a data acquisition system and a control and data processing system that is communicatively connected to the data acquisition system; The data acquisition system includes: a source component for exciting elastic wave groups in the target detection area, and a multi-channel receiving array for acquiring multipath reflection signals; The control and data processing system includes: The initial travel time analysis module is used to acquire initial acoustic wave detection data and perform travel time and wave velocity inversion to preliminarily determine the spatial distribution range of the internal anomaly zone. An array enhancement control module is used to adjust the observation density and beam parameters of the receiving array for the spatial distribution range, and to control the acquisition of local enhanced detection data. The joint wave field separation module is used to perform spatial and temporal wave field separation processing on the local enhanced detection data, filter out surface waves and oblique incident interference waves, and extract vertical reflected wave data. The acoustic wave migration imaging module is used to perform three-dimensional migration imaging based on the extracted vertical reflected wave data, and to extract the spatial positioning features and geometric contours of the internal anomalous area. The security assessment module is used to perform a security energy assessment of the target detection area by combining a preset security assessment model and the geometric contour.

10. A building structure safety detection device based on acoustic wave detection and wavefield separation according to claim 9, characterized in that, The multi-channel receiving array includes: a high-frequency phased array probe array and a three-component detector; The seismic source assembly includes: an impact seismic source with adjustable energy and trigger synchronization accuracy; The joint wavefield separation module has a built-in time reversal enhancement processing unit and a MUSIC algorithm spatial spectrum estimation unit, which are used to jointly perform wavefield band reshaping, polarization filtering and multipath ray tracing elimination.

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