Cast-in-place pile cross-hole CT detection method, system and equipment based on multi-wave integration

Abstract

The invention relates to the technical field of constructional engineering detection, and discloses a cast-in-place pile cross-hole CT detection method, system and equipment based on multi-wave integration, and the method comprises the steps: laying inspection holes, deploying a time-sharing excitation sensor, collecting multi-wave data, fusing the multi-wave data, correcting and compensating, and constructing a joint objective function to invert material parameters. A three-dimensional model is generated, defect space information is extracted, and hidden defect accurate detection is achieved; the system comprises a probe control module, a data acquisition module, a data processing module, a three-dimensional modeling module and a user interaction module. The device comprises an integrated probe device and a three-layer sensing structure from inside to outside. According to the method, anti-interference detection is achieved through multi-wave-type collaborative excitation and layered shielding probe design, and pile body defects are accurately positioned in combination with cross-wave-type data fusion processing and a self-adaptive inversion algorithm; defect space distribution is visually quantified based on dynamic threshold three-dimensional modeling, an integrated system adapts to a complex engineering environment, and the detection precision and efficiency of the cast-in-place pile are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction engineering detection, and in particular to a cast-in-place pile cross-hole CT detection method, system and equipment based on multi-wave integration. Background Art

[0002] Cast-in-place piles are an important foundation structure widely used in construction projects. However, as a critical foundation structure that bears load and transmits stress, their internal quality is directly related to project safety. However, due to complex construction techniques and variable geological conditions, cast-in-place piles are prone to hidden defects such as segregation, voids, and cracks, posing significant challenges to the accuracy and applicability of traditional inspection methods.

[0003] The ultrasonic transmission method, currently widely used in engineering, determines defects based on the propagation characteristics of a single elastic wave in concrete. This method relies heavily on concrete homogeneity and is susceptible to wave velocity distortion due to scattering effects in densely reinforced areas, making it difficult to distinguish between material defects and structural interference signals. For small defects or deep, slowly varying defects, detection sensitivity decreases significantly due to wavefield attenuation and resolution limitations. Furthermore, traditional methods primarily focus on local sections of the pile body and lack a comprehensive assessment of the three-dimensional structure of the pile. This makes it particularly difficult to accurately quantify the spatial distribution characteristics of defects, particularly in the inspection of large-diameter, ultra-deep cast-in-place piles.

[0004] On the other hand, the coupling interference of multiple physical fields under complex working conditions further restricts detection reliability. For example, differences in the mechanical properties of the soil around the pile can cause deviations in the ultrasonic propagation path. Traditional methods fail to account for soil coupling effects, leading to defect location errors. Interference from electromagnetic environmental noise on high-frequency signal acquisition is also not effectively suppressed.

[0005] Therefore, the present invention proposes a cross-hole CT detection method, system and equipment for bored piles based on multi-wave integration to address the deficiencies of the existing technology. Summary of the Invention

[0006] In response to the shortcomings of the existing technology, the present invention provides a cross-hole CT detection method, system and equipment for bored piles based on multi-wave integration, which solves the problems of traditional single-waveform detection methods under complex working conditions, such as difficulty in separating multi-physical field interference, low accuracy in identifying small-scale defects, and insufficient quantification of three-dimensional defect spatial distribution.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a cross-hole CT detection method for bored piles based on multi-wave integration, the method comprising the following steps:

[0008] S1. Arrange multiple inspection holes around the cast-in-place pile according to a preset geometric layout, and deploy integrated probes in the inspection holes. The integrated probes include ultrasonic sensors, electromagnetic wave sensors, and seismic wave sensors that work in a time-sharing manner.

[0009] S2. sequentially exciting the ultrasonic wave, electromagnetic wave, and seismic wave through timing control, and synchronously collecting propagation time and path data of each wave type between inspection holes;

[0010] S3, performing cross-waveform normalization processing on the electromagnetic wave data, performing soil layer coupling correction on the ultrasonic wave velocity based on the seismic wave data, dynamically compensating the corrected wave velocity in combination with the steel bar distribution parameters, and generating wave velocity parameters for multi-physics field fusion;

[0011] S4. Constructing a joint constraint objective function based on the wave velocity parameters of the multi-physics field fusion, and using an adaptive step size optimization algorithm to invert pile material parameters and defect distribution characteristics;

[0012] S5. Generate a three-dimensional structural model of the cast-in-place pile based on the inversion results, and output the spatial position and size information of the defects through isosurface extraction and visual mapping.

[0013] Preferably, the step S1 includes:

[0014] Multiple inspection holes are arranged symmetrically around the cast-in-place pile in the shape of a regular polygon. The radius R and the pile diameter D satisfy R=kD, where k is the proportional coefficient and the spacing between adjacent inspection holes is L. ij By the formula:

[0015]

[0016] Determine, where n is the number of inspection holes;

[0017] The integrated probe comprises an ultrasonic sensor, an electromagnetic wave sensor and a seismic wave sensor which work in time sharing, and an electromagnetic shielding layer is provided between the ultrasonic sensor and the electromagnetic wave sensor.

[0018] Preferably, the step S2 includes:

[0019] Ultrasonic waves, electromagnetic waves and seismic waves are excited in sequence through time-sharing trigger control, and the timing control equation satisfies:

[0020]

[0021] Among them, t ultra (k), t EM (k), t seis (k) is the triggering time of ultrasonic wave, electromagnetic wave and seismic wave at the kth excitation; T is the time base unit; Δt is the delay time of seismic wave triggering;

[0022] Synchronously collect the propagation time t of each wave mode between inspection holes AC And path data, the path data is decomposed into:

[0023]

[0024] Among them, S AE 、S EG 、S GC are the path lengths of AE, EG, and GC segments respectively; V AE 、V EG 、V GC is the wave velocity of the corresponding section.

[0025] Preferably, performing cross-waveform normalization processing on the electromagnetic wave data in step S3 includes:

[0026] The measured electromagnetic wave velocity V EM Mapped to the ultrasonic speed range, the normalized formula is:

[0027]

[0028] Among them, v ultra,min 、V EM,norm is the empirical wave velocity range of electromagnetic waves; v ultra,min 、v ultra,max It is the empirical wave velocity range of ultrasonic waves.

[0029] Preferably, performing soil layer coupling correction on ultrasonic wave velocity based on seismic wave data in step S3 includes:

[0030] According to the seismic wave velocity V seis Dynamically adjust the ultrasonic velocity V ultra , the correction formula is:

[0031]

[0032] Among them, V seis,min 、V seis,max is the empirical velocity range of seismic waves; Φ(x) is the transition function; c1 and c2 are correction coefficients.

[0033] Preferably, the step S3 of dynamically compensating the corrected wave velocity in combination with the steel bar distribution parameters includes:

[0034] According to the proportion of steel bar cross-sectional area Adjust the wave speed, the compensation formula is:

[0035]

[0036] Among them, V d(i) is the wave velocity after dynamic compensation at depth i; β(i) is the stirrup arrangement correction coefficient at depth i; V base is the reference wave velocity; V EM,corr is the normalized electromagnetic wave velocity.

[0037] Preferably, step S4 includes:

[0038] Construct a joint constraint objective function:

[0039]

[0040] Where m = [E, μ, ρ, ∈] T is the material parameter vector, including elastic modulus, shear modulus, density and dielectric constant; d k is the measured data vector of the kth type of waveform; G k (m) is the forward model output of the kth type of wave; w k is the weight coefficient of each waveform data, satisfying λ is the dynamically adjusted regularization coefficient, which is related to the difference in seismic wave velocity;

[0041] The adaptive step size optimization algorithm adjusts the search step size r according to the difference between ultrasonic and seismic wave velocities, satisfying:

[0042]

[0043] Among them, r base is the initial step length; is the average wave velocity, and the convergence condition of the inversion process is that the relative change rate of the objective function in adjacent iterations is less than the preset threshold.

[0044] Preferably, step S5 includes:

[0045] A three-dimensional structural model of the cast-in-place pile is generated based on the inversion results. The voxel attributes of the three-dimensional model are calculated using the Gaussian kernel function:

[0046]

[0047] Where V(x,y,z) is the voxel attribute value at the coordinate (x,y,z) in three-dimensional space; w k is the weight coefficient of the kth sampling point; r k is the spatial coordinate of the kth sampling point; σ k is the standard deviation of the kernel function related to the corrected wave velocity;

[0048] The isosurface threshold τ is determined by statistically correcting the wave velocity distribution, satisfying:

[0049]

[0050] Among them, Vcorr (i) is the corrected wave velocity of the i-th voxel; is the average wave velocity; M is the statistical multiplication coefficient;

[0051] Based on the threshold, an isosurface is extracted and mapped to a three-dimensional space coordinate system, and the spatial position and size information of the defect is output.

[0052] The present invention also provides a cast-in-place pile cross-hole CT detection system based on multi-wave integration, the system comprising the following modules:

[0053] Probe control module: used to control the integrated probe to stimulate ultrasonic waves, electromagnetic waves and seismic waves in a time-sharing manner, and receive return signals;

[0054] Data acquisition module: communicates with the probe control module to synchronously collect the propagation time and path data of each waveform between the inspection holes;

[0055] Data processing module: performs cross-waveform normalization, soil layer coupling correction, and reinforcement dynamic compensation on the collected data to generate wave velocity parameters for multi-physics field fusion, and inverts pile material parameters and defect distribution through adaptive optimization algorithms;

[0056] 3D modeling module: Constructs a 3D structural model of the cast-in-place pile based on the inversion results, extracts isosurfaces and calculates the spatial characteristics of defects;

[0057] User interaction module: Visually outputs 3D defect models, supports parameter configuration and test report generation.

[0058] The present invention also provides a bored pile cross-hole CT detection device based on multi-wave integration. The integrated probe device includes a three-layer sensing structure from the inside to the outside:

[0059] Inner layer: a flexible electromagnetic wave sensor configured to transmit and receive high-frequency electromagnetic wave signals;

[0060] Middle layer: piezoelectric ceramic ultrasonic sensors, arranged around the inner layer, used for directionally exciting ultrasonic waves;

[0061] Outer layer: micro seismic wave sensors, evenly distributed on the outer surface of the probe, used to detect seismic wave vibration signals;

[0062] Electromagnetic shielding layer: It is set between the inner layer and the middle layer and adopts a metal woven mesh structure to isolate the mutual interference between electromagnetic waves and ultrasonic waves.

[0063] The present invention provides a cast-in-place pile cross-hole CT detection method, system and equipment based on multi-wave integration.

[0064] It has the following beneficial effects:

[0065] 1. This invention overcomes the limitations of single-waveform detection by time-sharing the excitation of ultrasonic, electromagnetic, and seismic waves, combined with multi-physics field data fusion. The elastic wave characteristics of ultrasonic waves, the dielectric sensitivity of electromagnetic waves, and the soil penetration of seismic waves complement each other, enabling the simultaneous acquisition of pile mechanical parameters, material dielectric properties, and soil coupling information, significantly improving the dimensionality and reliability of defect detection.

[0066] 2. The probe of this invention utilizes an integrated package of three layers of sensors (inner, middle, and outer) and an electromagnetic shielding layer, effectively isolating the high-frequency electromagnetic field from the mutual interference of ultrasonic vibration signals. This design ensures the independence and purity of multi-waveform signal acquisition, resolving the technical challenge of signal crosstalk between multiple sensors in a single probe.

[0067] 3. This invention generates fused velocity parameters and constructs a joint constraint objective function through a progressive process of cross-waveform normalization, soil layer coupling correction, and rebar dynamic compensation. Combined with an adaptive optimization algorithm, this method achieves high-precision inversion of pile material parameters and defect distribution, overcoming the misjudgment and missed detection issues often associated with traditional methods due to environmental interference.

[0068] 4. This invention uses dynamic thresholding to extract isosurfaces and maps them to a three-dimensional coordinate system, visually displaying the spatial location, shape, and size of defects. This technology transforms abstract velocity data into actionable engineering information, significantly improving the efficiency of interpreting test results and supporting decision-making.

[0069] 5. The collaborative design of the integrated probe and anti-interference cable adapts to complex environments such as mud and dense rebar in bored pile inspection holes. The system supports simultaneous inspection of multiple holes and automated data processing, meeting the needs of rapid inspection of large-diameter and ultra-deep bored piles, significantly improving engineering inspection efficiency and equipment reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 is a flow chart of the method of the present invention;

[0071] Figure 2 This is a system architecture diagram of the present invention;

[0072] Figure 3 This is a schematic diagram of the inspection hole arrangement of the present invention;

[0073] Figure 4 Schematic diagram of the integrated probe structure of the present invention;

[0074] Among them, 10, inspection hole A; 20, inspection hole B; 30, inspection hole C; 40, inspection hole D; 50, cable; 60, electromagnetic wave sensor; 70, ultrasonic sensor; 80, seismic wave sensor. DETAILED DESCRIPTION

[0075] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0076] See also Figure 1 Read Figure 3 The embodiment of the present invention provides a cross-hole CT detection method for bored piles based on multi-wave integration, the method comprising the following steps:

[0077] S1. Arrange multiple inspection holes around the cast-in-place pile according to a preset geometric layout, and deploy integrated probes in the inspection holes. The integrated probes include ultrasonic sensors, electromagnetic wave sensors, and seismic wave sensors that work in a time-sharing manner.

[0078] In this embodiment, the implementation of step S1 specifically includes symmetrical layout of inspection holes and deployment of integrated probes. Through multi-sensor collaborative layout and electromagnetic interference suppression design, basic data acquisition conditions are provided for cross-hole CT inspection. The specific technologies are as follows:

[0079] A number of inspection holes are arranged symmetrically around the cast-in-place pile in the shape of a regular polygon. The inspection holes include inspection hole A10, inspection hole B20, inspection hole C30, and inspection hole D40. The minimum number of holes is 3 (the arrangement of the holes can be varied. Inspection hole B20 can be placed above, to the left, or to the right of inspection hole A10). The following uses a 3-hole model to illustrate the formula. This time, inspection holes A10 and C30 are used as inspection holes, and inspection hole B20 is used as a correction hole. The line AB intersects the pile at points E and G. The cross section is divided perpendicular to the ABC plane along different buried depths i of the soil layer (i = 0, j = 2, 3j, 4j...n j 、)where n j The center of the regular polygon coincides with the axis of the pile. The layout radius R is proportional to the pile diameter D, satisfying R = kD, where the proportional coefficient k is determined according to the soil characteristics around the pile and the detection depth requirements. The number of inspection holes n is selected according to the pile diameter and detection resolution requirements, and satisfies n ≥ 3. The spacing between adjacent inspection holes L ij By formula:

[0080]

[0081] Calculations ensure that the inspection holes are evenly distributed around the pile. This geometric layout ensures that the inspection path between any two inspection holes covers different areas of the pile cross-section, avoiding detection blind spots and providing a spatial basis for multi-wave data cross-validation.

[0082] An integrated probe is deployed vertically in each inspection hole. The probe includes an ultrasonic sensor, an electromagnetic wave sensor, and a seismic wave sensor that work in time-sharing mode. The specific configuration is as follows:

[0083] Ultrasonic sensor: Made of piezoelectric ceramic material, it is arranged in the middle layer of the probe in the form of a ring array. The emission direction is perpendicular to the axis of the probe and is used to transmit ultrasonic pulse signals in a directionally directed manner to adjacent inspection holes.

[0084] Electromagnetic wave sensor: It is arranged in the inner layer of the probe and adopts a broadband antenna structure to support the transmission and reception of high-frequency electromagnetic waves. The working frequency band covers the sensitive area of the dielectric property difference between soil and concrete media.

[0085] Seismic wave sensor: Evenly distributed on the outer surface of the probe in the form of miniature accelerometers, it is used to detect the vibration signal of the soil around the pile. Its omnidirectional sensitivity can capture the multi-angle seismic wave propagation path.

[0086] An electromagnetic shielding layer, made of a woven metal mesh, is installed between the ultrasonic sensor and the electromagnetic wave sensor. This shielding layer covers the entire axial length of the probe, with mesh size less than 1 / 10 of the minimum electromagnetic wave wavelength. This shielding layer blocks electromagnetic interference with the ultrasonic sensor during electromagnetic wave transmission. This design prevents signal crosstalk caused by electromagnetic field coupling within the probe, ensuring independent acquisition of ultrasonic and electromagnetic wave signals.

[0087] The ultrasonic, electromagnetic and seismic wave sensors work alternately through a time-sharing control circuit:

[0088] The ultrasonic sensor is triggered first and enters the sleep state after transmitting the pulse signal;

[0089] The electromagnetic wave sensor starts to emit high-frequency electromagnetic waves after the ultrasonic signal decays to the background noise level;

[0090] The seismic wave sensor continuously monitors the ambient vibration and records the seismic wave propagation data after a preset silent time window.

[0091] The time-sharing working mode is achieved through the collaboration of hardware timers and software trigger logic, ensuring that multi-waveform signals are completely isolated in the time domain.

[0092] The density of the inspection path is determined by the ratio k between the regular polygon radius R and the pile diameter, as well as the number of inspection holes n. As k increases, the inspection path shifts outward from the pile, making it suitable for edge defect detection in large-diameter piles. As n increases, the spacing between adjacent inspection holes decreases, reducing the angle between the inspection paths and improving resolution in local areas. In actual projects, k and n can be dynamically adjusted based on pile size and inspection objectives to optimize the balance between inspection efficiency and accuracy.

[0093] S2. sequentially exciting the ultrasonic wave, electromagnetic wave, and seismic wave through timing control, and synchronously collecting propagation time and path data of each wave type between inspection holes;

[0094] In this embodiment, the implementation of step S2 specifically includes multi-waveform time-sharing excitation control and synchronous acquisition of propagation data, and the independence and resolvability of multi-physics field data are ensured through time isolation and path decomposition technology. The specific technology is as follows:

[0095] Ultrasonic waves, electromagnetic waves, and seismic waves are excited in sequence through the timing control equations, which are defined as follows:

[0096]

[0097] Among them, t ultra (k), t EM (k), t seis (k) is the triggering moment of ultrasonic wave, electromagnetic wave and seismic wave at the kth excitation; T is the time base unit; Δt is the delay time of seismic wave triggering.

[0098] Time base unit T: determines the cycle beat of multi-waveform triggering. Its value matches the sensor response time and signal attenuation characteristics to ensure that the previous waveform signal is fully attenuated before triggering the next waveform.

[0099] Delay time Δt: It is set at the moment of seismic wave triggering to avoid the interference of residual vibration of ultrasonic and electromagnetic waves. The specific value is determined by the wave attenuation experiment.

[0100] Ultrasonic waves and electromagnetic waves are triggered alternately: ultrasonic waves are triggered at even multiples of T, and electromagnetic waves are triggered at odd multiples of T. The two are completely isolated in the time domain.

[0101] Seismic wave delayed triggering: The seismic wave is activated at time Δt after the ultrasonic wave is triggered, taking advantage of the low propagation speed of the seismic wave to avoid aliasing with the high-frequency electromagnetic wave signal at the receiving end.

[0102] The propagation time t of each wave mode is collected synchronously between adjacent inspection holes AC , and analyze the wave velocity distribution through the path decomposition formula:

[0103]

[0104] Among them, S AE 、S EG 、S GC They are the lengths of the three segments of the wave signal path from the transmitting hole (A) to the receiving hole (C):

[0105] AE segment: the soil propagation path from the launch hole to the outer edge of the pile body, reflecting the wave velocity characteristics of the soil around the pile;

[0106] EG segment: propagation path inside the pile, directly related to the uniformity of the pile material;

[0107] GC segment: The soil propagation path from the outer edge of the pile to the receiving hole, used to cross-verify the soil parameters around the pile. AE 、V EG 、V GC The solution is obtained through least squares inversion and provides input for subsequent multi-wave data fusion.

[0108] Trigger signal generation: A time-sharing control circuit is used to generate high-precision trigger pulses, with timing errors controlled at the sub-microsecond level, ensuring that the excitation moment is strictly synchronized with the data acquisition clock.

[0109] Signal acquisition unit: The receiving end is equipped with a multi-channel acquisition card, each channel independently latches the rising edge of the trigger signal and records the waveform arrival time t AC , the time resolution is better than 1μs.

[0110] The total propagation time t AC Decomposing it into three independent paths, we can distinguish the influence of the pile and the soil around the pile on the wave velocity:

[0111] Soil segment (AE, GC): used to correct the interference of soil parameter fluctuations around the pile on the test results;

[0112] Pile body segment (EG): directly reflects the material defects of the pile body and provides core data for 3D inversion.

[0113] S3, performing cross-waveform normalization processing on the electromagnetic wave data, performing soil layer coupling correction on the ultrasonic wave velocity based on the seismic wave data, dynamically compensating the corrected wave velocity in combination with the steel bar distribution parameters, and generating wave velocity parameters for multi-physics field fusion;

[0114] In this embodiment, the implementation of step S3 specifically includes multi-stage processing of electromagnetic wave data normalization, soil layer coupling correction, and steel bar dynamic compensation, and generates a high-confidence wave velocity distribution by fusing multiple physical field parameters:

[0115] The measured electromagnetic wave velocity is mapped to the ultrasonic wave velocity range to eliminate the influence of dimension difference on the fusion analysis. The normalization formula is defined as:

[0116]

[0117] Where: V EM is the measured wave velocity of the electromagnetic wave on the detection path; V EM,min 、V EM,max are the lower and upper limits of the empirical wave velocity of electromagnetic waves in the target medium, which are obtained through historical test data statistics (for example, the typical value range in concrete medium is 0.95×10 8m / s to 1.22×10 8 m / s);

[0118] v ultra,min 、v ultra,max The lower and upper limits of the empirical wave velocity of ultrasound in concrete are determined according to the nominal parameters of the material (for example, the typical value range in normal concrete is 3000m / s to 4500m / s).

[0119] This mapping process linearly scales the electromagnetic wave velocity to the same dimensional range as the ultrasonic wave velocity, providing a unified benchmark for subsequent weighted fusion of multi-wave data.

[0120] The ultrasonic velocity is dynamically adjusted according to the seismic wave velocity to compensate for the attenuation effect of the soil around the pile on ultrasonic propagation. The correction formula is:

[0121]

[0122] Among them, V ultra is the original measurement value of ultrasonic velocity without correction; V seis is the measured velocity of the seismic wave on the detection path; V seis,min 、V seis,max are the lower and upper limits of the empirical velocity of seismic waves in the soil around the pile, which are calibrated by geological survey data (for example, the typical value range in soft clay is 1200 m / s to 1800 m / s); Φ(x) is a transition function used to smooth the influence of seismic velocity changes on the correction coefficient. Its function form can be a Sigmoid function (for example )) or piecewise linear function; c1 and c2 are correction coefficients related to the soil type, determined by calibration tests (for example, typical values for sandy soil are c1 = 0.90 and c2 = 0.26).

[0123] The correction process introduces seismic wave velocity to reflect the mechanical properties of soil and suppresses the deviation of wave velocity solution caused by soil heterogeneity.

[0124] The corrected wave velocity is adjusted according to the steel bar cross-sectional area ratio and arrangement density. The compensation formula is:

[0125]

[0126] Where: V d (i) is the wave velocity after dynamic compensation at depth i; ρ rebar (i) is the proportion of the cross-sectional area of the steel bars at depth i, defined as Obtained from pile design drawings or core drilling data; β(i) is the stirrup arrangement correction factor at depth i, assigned a value based on the ratio of stirrup spacing to diameter (e.g., β = 0.6 for a spacing of 200 mm and a diameter of 10 mm); V baseV is the reference wave velocity without reinforcement interference, which is set according to the nominal parameters of the material (for example, 4000 m / s for normal concrete); EM,corr is the electromagnetic wave velocity after normalization and soil layer correction.

[0127] The model separates material defects and structural interference signals by quantifying the scattering and diffraction effects of the spatial distribution of steel bars on wave velocity.

[0128] S4. Constructing a joint constraint objective function based on the wave velocity parameters of the multi-physics field fusion, and using an adaptive step size optimization algorithm to invert pile material parameters and defect distribution characteristics;

[0129] In this embodiment, the implementation of step S4 specifically includes the construction of a joint constraint objective function and the design of an adaptive step-size optimization algorithm, and the high-precision reconstruction of pile material parameters and defect distribution is achieved through collaborative inversion of multi-waveform data:

[0130] The joint constraint objective function is constructed based on the wave velocity parameters of multi-physics field fusion, and its mathematical expression is defined as:

[0131]

[0132] Where: m = [E, μ, ρ, ∈] T is the material parameter vector, including elastic modulus E, shear modulus μ, density ρ and dielectric constant ∈, which respectively characterize the stiffness, shear resistance, mass distribution and electromagnetic properties of the pile material; d k is the measured data vector of the kth type of wave (ultrasonic, electromagnetic, seismic), and its dimension is consistent with the number of detection paths; G k 9m) is the output of the forward model of the kth wave type, which is obtained by numerically solving the wave equation. Its input is the material parameter m, and the output is the theoretical wave velocity and propagation time; w k is the weight coefficient of each waveform data, satisfying w1+w2+w3=1, determined by historical data calibration or experimental optimization (for example, ultrasonic weight w1=0.4, electromagnetic w2=0.3, seismic w3=0.3); λ is the dynamically adjusted regularization coefficient, defined as Among them, λ0 is the baseline regularization strength; is the average wave speed; is the L1 norm of the spatial gradient of the material parameter, which is used to constrain the smoothness of the inversion result and suppress parameter oscillation caused by noise.

[0133] The adjustment rules of the regularization coefficient λ are as follows:

[0134] Baseline regularization strength λ0: set based on the initial material parameter estimates and the data noise level, preferably determined by pre-inversion tests;

[0135] Wave velocity difference term||V ultra -V seis ||: Calculate the Euclidean norm of the difference between ultrasonic and seismic wave velocities on all detection paths;

[0136] Dynamic adjustment logic: When the wave velocity difference is significant (for example, in the presence of voids or cracks), increase λ to strengthen the regularization constraint and avoid overfitting the local abnormal data; when the difference is small (homogeneous medium), decrease λ to preserve the detailed characteristics of the material parameters.

[0137] The adaptive step-size strategy based on wave velocity difference is used to iteratively solve the minimum value of the objective function. The step-size update formula is:

[0138]

[0139] Where: r base is the initial step size, which is set according to the trace estimation of the Hessian matrix of the objective function. Where H is the Hessian matrix; ||V ultra -V seis || is the Euclidean norm of the difference between ultrasonic and seismic wave velocities, reflecting the degree of medium heterogeneity; is the average wave velocity, which is defined as the arithmetic mean of the two types of wave velocities and is used to normalize the magnitude of the difference.

[0140] This strategy automatically increases the step size to accelerate convergence when the medium is highly inhomogeneous (such as in areas with cracks), and reduces the step size in homogeneous areas to improve parameter estimation accuracy.

[0141] The iteration termination condition is set as the relative change rate of the objective function of two adjacent iterations is less than the preset threshold ∈, that is:

[0142]

[0143] Where: m (t) is the estimated value of the material parameter at the tth iteration; ∈ is set according to the computational efficiency and inversion accuracy requirements. Preferably, the value range is 10 -5 ≤∈≤10 -3 .

[0144] S5. Generate a three-dimensional structural model of the cast-in-place pile based on the inversion results, and output the spatial position and size information of the defect through isosurface extraction and visual mapping;

[0145] In this embodiment, the implementation of step S5 specifically includes the construction of a three-dimensional structural model, calculation of isosurface thresholds, and defect space mapping, and the quantitative expression of the internal defects of the cast-in-place pile is achieved through spatial interpolation of the wave velocity field and statistical feature analysis:

[0146] Based on the material parameter distribution obtained by inversion, a three-dimensional structural model of the cast-in-place pile is generated. The voxel attributes of the model are calculated by weighted interpolation of the Gaussian kernel function, and its mathematical expression is:

[0147]

[0148] Where: V(x,y,z) is the voxel attribute value at the coordinate (x,y,z) in three-dimensional space, representing the equivalent wave velocity at that location; r k is the spatial coordinate of the kth sampling point, which is determined by the layout of the detection hole and the depth of the probe; w k is the weight coefficient of the kth sampling point, defined as Among them, V ultra(k) is the corrected ultrasonic velocity at the kth sampling point; V seis (k) is the corrected seismic wave velocity; σ k is the standard deviation of the Gaussian kernel function, which is related to the corrected wave velocity and is defined as Wherein, α is a proportional factor used to adjust the spatial smoothing range of the kernel function, and is preferably determined through preliminary experiments or empirical values (eg, 0.1≤α≤0.3).

[0149] The isosurface threshold τ is set by statistically correcting the wave velocity distribution to distinguish normal areas from defective areas. The threshold calculation formula is:

[0150]

[0151] Where: V corr (i) is the corrected wave velocity of the i-th voxel, determined by the fused wave velocity parameter generated in step S3; is the average wave velocity of all voxels, calculated as M is the statistical multiplication coefficient, which is set according to the confidence requirements of defect detection. Preferably, the value range is 2≤M≤3, corresponding to the 2σ-3σ confidence interval in statistics; N is the total number of voxels in the three-dimensional model, which is determined by the model resolution (voxel size) and the geometric dimensions of the pile.

[0152] Based on the threshold τ, the isosurface is extracted and the velocity anomaly area is mapped to the three-dimensional space coordinate system. The specific process includes:

[0153] Isosurface generation:

[0154] The Marching-Cubes algorithm is used to traverse the three-dimensional voxel data and identify voxels that satisfy V(x,y,z)<τ;

[0155] Perform 8-vertex interpolation calculations on each voxel to generate an isosurface represented by a triangular mesh. The vertex coordinates are determined by the linear interpolation formula:

[0156]

[0157] Among them, p0 and p1 are the coordinates of adjacent voxel vertices; V0 and V1 are the corresponding vertex attribute values.

[0158] Coordinate transformation:

[0159] Convert the coordinates of the isosurface vertices from the model local coordinate system (with the pile center as the origin) to the project global coordinate system. The conversion parameters include the longitude and latitude, azimuth, and burial depth of the pile center point.

[0160] The coordinate transformation matrix is defined as:

[0161] T=R z (θ)·T offset ;

[0162] Among them, R z (θ) is the rotation matrix around the vertical axis (corresponding to the pile azimuth angle θ); T offset is the translation matrix (corresponding to the coordinates of the center point of the pile).

[0163] Defect parameter calculation:

[0164] Volume calculation: For each connected domain of the isosurface, the defect volume is calculated by voxel accumulation method or triangular mesh integration;

[0165] Equivalent diameter: defined as the diameter of the defect volume V d The same sphere diameter is calculated as

[0166] Spatial position: Calculate the coordinates of the center of gravity of the defect area as its spatial position reference point.

[0167] See also Figure 2 The present invention also provides a cast-in-place pile cross-hole CT detection system based on multi-wave integration, the system comprising the following modules:

[0168] Probe control module: used to control the integrated probe to stimulate ultrasonic waves, electromagnetic waves and seismic waves in a time-sharing manner, and receive return signals;

[0169] This module is responsible for the time-sharing excitation and signal reception control of the integrated probe, and realizes multi-waveform orderly triggering through the collaboration of hardware logic and software.

[0170] Time-sharing trigger control: A programmable timer is used to generate precise trigger pulse sequences to activate ultrasonic sensors, electromagnetic wave sensors, and seismic wave sensors in sequence. The trigger interval is dynamically adjusted according to the signal attenuation characteristics to ensure that the next waveform is started only after the previous waveform signal is completely attenuated.

[0171] Electromagnetic shielding design: A metal braided shielding layer is set between the ultrasonic and electromagnetic wave sensors to block the interference of high-frequency electromagnetic fields on piezoelectric ceramic ultrasonic elements. The shielding effectiveness is achieved by optimizing the mesh density and conductive materials.

[0172] Probe structure configuration: The probe adopts a layered packaging structure. The inner layer is a flexible electromagnetic wave transmitting / receiving antenna, the middle layer is a ring-shaped piezoelectric ultrasonic array, and the outer layer integrates a MEMS seismic accelerometer. The layers are physically separated by an insulating isolation layer.

[0173] Data acquisition module: communicates with the probe control module to synchronously collect the propagation time and path data of each waveform between the inspection holes;

[0174] This module realizes the synchronous acquisition and preprocessing of multi-waveform propagation data to ensure the temporal and spatial consistency of the original data.

[0175] Multi-channel synchronous acquisition: Equipped with a multi-channel high-speed acquisition card, each channel independently latches the rising edge of the trigger signal and records the waveform arrival time with microsecond accuracy. The time base is provided by a high-stable constant temperature crystal oscillator.

[0176] Path data analysis: Based on the geometric relationship of the inspection hole layout, the propagation path is decomposed into the internal segment of the pile and the soil segment around the pile. The length and wave velocity distribution of each segment are calculated based on the probe lifting and lowering positions.

[0177] Signal preprocessing: The original signal is subjected to bandpass filtering, baseline correction and noise suppression. The ultrasonic signal is intercepted using threshold triggering, and the electromagnetic wave signal is intercepted through a time window to eliminate environmental noise.

[0178] Data processing module: performs cross-waveform normalization, soil layer coupling correction, and reinforcement dynamic compensation on the collected data to generate wave velocity parameters for multi-physics field fusion, and inverts pile material parameters and defect distribution through adaptive optimization algorithms;

[0179] This module performs multi-physics data fusion and parameter inversion to generate pile material properties and defect distribution.

[0180] Cross-waveform normalization: Linearly map the electromagnetic wave velocity to the ultrasonic wave velocity range, eliminate dimensional differences, and calibrate the empirical wave velocity range using historical data.

[0181] Soil layer coupling correction: Dynamically adjust the ultrasonic velocity based on the seismic wave velocity to compensate for the impact of soil heterogeneity on sound wave propagation. The correction coefficient is assigned through the soil type lookup table.

[0182] Rebar dynamic compensation: Quantify the attenuation of wave velocity due to the reinforcement scattering effect based on the reinforcement distribution density and arrangement parameters, and generate a corrected fused wave velocity field.

[0183] Adaptive inversion algorithm: Construct a multi-waveform joint constraint objective function, adopt a variable step size optimization strategy to iteratively solve the material parameters, and the convergence condition is determined based on the relative change rate threshold of the objective function.

[0184] 3D modeling module: Constructs a 3D structural model of the cast-in-place pile based on the inversion results, extracts isosurfaces and calculates the spatial characteristics of defects;

[0185] This module converts the inversion results into a three-dimensional visual model, supporting quantitative analysis of defect spatial characteristics.

[0186] Voxel attribute interpolation: The wave velocity of discrete sampling points is spatially interpolated based on the Gaussian kernel function to generate a continuous three-dimensional wave velocity field. The standard deviation of the kernel function is adaptively adjusted according to the local wave velocity gradient.

[0187] Isosurface extraction: The Marching-Cubes algorithm is used to extract abnormal wave velocity areas below the dynamic threshold, generate defect isosurfaces represented by triangular meshes, and eliminate pseudo defects formed by isolated noise points.

[0188] Defect parameter calculation: Calculate the volume, equivalent diameter and center of gravity coordinates of the connected domain of the isosurface. The volume is obtained by voxel accumulation or grid integration method, and the equivalent diameter is converted to the diameter of a sphere with the same volume.

[0189] User interaction module: Visually output 3D defect model, support parameter configuration and test report generation;

[0190] This module provides a visual operation interface and report generation function, supporting human-computer interactive analysis of test results.

[0191] 3D visualization engine: supports model rotation, scaling, cross-section cutting and transparency adjustment. The defect area is mapped with color gradient to show the degree of wave velocity anomaly, and the pile outline wireframe is superimposed to assist positioning.

[0192] Parameter configuration interface: provides an input panel for adjustable parameters such as detection hole layout parameters, wave velocity threshold, inversion algorithm step size, etc., and supports importing and exporting parameter preset templates.

[0193] Test report generation: Built-in standardized report templates automatically fill in key information such as defect location, size, wave velocity anomalies, etc., support 3D model screenshots, data tables and curve charts, and output formats are compatible with PDF and Word.

[0194] See also Figure 4 , a cast-in-place pile cross-hole CT detection equipment based on multi-wave integration, integrated probe equipment, including a three-layer sensing structure from the inside to the outside:

[0195] Inner layer: flexible electromagnetic wave sensor 60, configured to transmit and receive high-frequency electromagnetic wave signals;

[0196] Middle layer: piezoelectric ceramic ultrasonic sensors 70, arranged around the inner layer, for directionally exciting ultrasonic waves;

[0197] Outer layer: micro seismic wave sensors 80, evenly distributed on the outer surface of the probe, used to detect seismic wave vibration signals;

[0198] Electromagnetic shielding layer: It is set between the inner layer and the middle layer and adopts a metal woven mesh structure to isolate the mutual interference of electromagnetic waves and ultrasonic waves;

[0199] The cable 50 is connected to the integrated probe and is used to realize sensor power supply, signal transmission and mechanical support functions.

[0200] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A cross-hole CT detection method for bored piles based on multi-wave integration, characterized in that: The method comprises the following steps: S1. Arrange multiple inspection holes around the cast-in-place pile according to a preset geometric layout, and deploy integrated probes in the inspection holes. The integrated probes include ultrasonic sensors, electromagnetic wave sensors, and seismic wave sensors that work in a time-sharing manner. S2. sequentially exciting the ultrasonic wave, electromagnetic wave, and seismic wave through timing control, and synchronously collecting propagation time and path data of each wave type between inspection holes; S3. Performing cross-waveform normalization processing on the electromagnetic wave data, performing soil layer coupling correction on the ultrasonic wave velocity based on the seismic wave data, dynamically compensating the corrected wave velocity in combination with the steel bar distribution parameters, and generating wave velocity parameters for multi-physics field fusion; S4. Constructing a joint constraint objective function based on the wave velocity parameters of the multi-physics field fusion, and using an adaptive step size optimization algorithm to invert pile material parameters and defect distribution characteristics; S5. Generate a three-dimensional structural model of the cast-in-place pile based on the inversion results, and output the spatial position and size information of the defects through isosurface extraction and visual mapping.

2. The cross-hole CT detection method for bored piles based on multi-wave integration according to claim 1 is characterized in that: The step S1 comprises: Multiple inspection holes are arranged symmetrically around the cast-in-place pile in the shape of a regular polygon. The radius R and the pile diameter D satisfy R=kD, where k is the proportional coefficient and the spacing between adjacent inspection holes is L. ij By the formula: Determine, where n is the number of inspection holes; The integrated probe comprises an ultrasonic sensor, an electromagnetic wave sensor and a seismic wave sensor which work in time sharing, and an electromagnetic shielding layer is provided between the ultrasonic sensor and the electromagnetic wave sensor.

3. The cross-hole CT detection method for bored piles based on multi-wave integration according to claim 1 is characterized in that: The step S2 comprises: Ultrasonic waves, electromagnetic waves and seismic waves are excited in sequence through time-sharing trigger control, and the timing control equation satisfies: Among them, t ultra (k), t EM (k), t seis (k) is the triggering time of ultrasonic wave, electromagnetic wave and seismic wave at the kth excitation; T is the time base unit; Δt is the delay time of seismic wave triggering; Synchronously collect the propagation time t of each wave mode between inspection holes AC And path data, the path data is decomposed into: Among them, S AE 、S EG 、S GC are the path lengths of AE, EG, and GC segments respectively; V AE 、V EG 、V GC is the wave velocity of the corresponding section.

4. The method for cross-hole CT detection of bored piles based on multi-wave integration according to claim 1 is characterized in that: The cross-waveform normalization processing of the electromagnetic wave data in step S3 includes: The measured electromagnetic wave velocity V EM Mapped to the ultrasonic speed range, the normalized formula is: Among them, v ultra,min 、V EM,norm is the empirical wave velocity range of electromagnetic waves; v ultra,min 、v ultra,max It is the empirical wave velocity range of ultrasonic waves.

5. The method for cross-hole CT detection of bored piles based on multi-wave integration according to claim 1 is characterized in that: The step S3 of performing soil layer coupling correction on ultrasonic velocity based on seismic wave data includes: According to the seismic wave velocity V seis Dynamically adjust the ultrasonic velocity V ultra , the correction formula is: Among them, V seis,min 、V seis,max is the empirical velocity range of seismic waves; Φ(x) is the transition function; c1 and c2 are correction coefficients.

6. The method for cross-hole CT detection of bored piles based on multi-wave integration according to claim 1 is characterized in that: The step S3 of dynamically compensating the corrected wave velocity in combination with the steel bar distribution parameters includes: According to the proportion of steel bar cross-sectional area Adjust the wave speed, the compensation formula is: Among them, V d (i) is the wave velocity after dynamic compensation at depth i; β(i) is the stirrup arrangement correction coefficient at depth i; V base is the reference wave velocity; V EM,corr is the normalized electromagnetic wave velocity.

7. The method for cross-hole CT detection of bored piles based on multi-wave integration according to claim 1 is characterized in that: The step S4 comprises: Construct a joint constraint objective function: Where m = [E, μ, ρ, ∈] T is the material parameter vector, including elastic modulus, shear modulus, density and dielectric constant; d k is the measured data vector of the kth type of waveform; G k (m) is the forward model output of the kth type of wave; w k is the weight coefficient of each waveform data, satisfying λ is the dynamically adjusted regularization coefficient, which is related to the difference in seismic wave velocity; The adaptive step size optimization algorithm adjusts the search step size r according to the difference between ultrasonic and seismic wave velocities, satisfying: Among them, r base is the initial step length; is the average wave velocity, and the convergence condition of the inversion process is that the relative change rate of the objective function in adjacent iterations is less than the preset threshold.

8. The method for cross-hole CT detection of bored piles based on multi-wave integration according to claim 1 is characterized in that: The step S5 comprises: A three-dimensional structural model of the cast-in-place pile is generated based on the inversion results. The voxel attributes of the three-dimensional model are calculated using the Gaussian kernel function: Where V(x,y,z) is the voxel attribute value at the coordinate (x,y,z) in three-dimensional space; w k is the weight coefficient of the kth sampling point; r k is the spatial coordinate of the kth sampling point; σ k is the standard deviation of the kernel function related to the corrected wave velocity; The isosurface threshold τ is determined by statistically correcting the wave velocity distribution, satisfying: Among them, V corr (i) is the corrected wave velocity of the i-th voxel; is the average wave velocity; M is the statistical multiplication coefficient; Based on the threshold, an isosurface is extracted and mapped to a three-dimensional space coordinate system, and the spatial position and size information of the defect is output.

9. A cast-in-place pile cross-hole CT detection system based on multi-wave integration, applied to the method according to any one of claims 1 to 8, characterized in that: The system includes the following modules: Probe control module: used to control the integrated probe to stimulate ultrasonic waves, electromagnetic waves and seismic waves in a time-sharing manner, and receive return signals; Data acquisition module: communicates with the probe control module to synchronously collect the propagation time and path data of each waveform between the inspection holes; Data processing module: performs cross-waveform normalization, soil layer coupling correction, and reinforcement dynamic compensation on the collected data to generate wave velocity parameters for multi-physics field fusion, and inverts pile material parameters and defect distribution through adaptive optimization algorithms; 3D modeling module: Constructs a 3D structural model of the cast-in-place pile based on the inversion results, extracts isosurfaces and calculates the spatial characteristics of defects; User interaction module: Visually outputs 3D defect models, supports parameter configuration and test report generation.

10. A bored pile cross-hole CT detection device based on multi-wave integration, an integrated probe device used in the method according to any one of claims 1 to 8, characterized in that: It includes three layers of sensing structure from inside to outside: Inner layer: a flexible electromagnetic wave sensor configured to transmit and receive high-frequency electromagnetic wave signals; Middle layer: piezoelectric ceramic ultrasonic sensors, arranged around the inner layer, used for directionally exciting ultrasonic waves; Outer layer: micro seismic wave sensors, evenly distributed on the outer surface of the probe, used to detect seismic wave vibration signals; Electromagnetic shielding layer: It is set between the inner layer and the middle layer and adopts a metal woven mesh structure to isolate the mutual interference between electromagnetic waves and ultrasonic waves.

Images