Shield tunnel ultra-wideband elastic wave anti-interference grouting detection method and system

Abstract

This invention belongs to the field of non-destructive testing technology for shield tunnel engineering. It proposes an ultra-wideband elastic wave anti-interference grouting detection method and system for shield tunnels. The method involves obtaining the apparent velocity range, grout mass velocity model, reference spectrum, and classification threshold through calibration; emitting linearly swept frequency elastic waves from an excitation source to acquire the original spatiotemporal wavefield signal; initial filtering via a two-dimensional mask in the f-k domain, followed by morphological component analysis to remove interference from the tunnel segment structure and reconstruct the target reflected wavefield; extracting at least three wavefield characteristic parameters; calculating the grout layer thickness; and combining the threshold to determine the grouting state, outputting a grouting quality evaluation. This method can suppress structural scattering interference and achieve the detection of grouting defects behind the tunnel wall.

Description

Technical Field

[0001] This invention belongs to the field of non-destructive testing technology for shield tunnel engineering, specifically relating to a method and system for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels. Background Technology

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In shield tunneling, grouting behind the tunnel lining segments is a core procedure for controlling ground settlement and ensuring the stability and waterproofing of the tunnel structure. This process is carried out entirely underground in a concealed environment, making it prone to quality defects such as incomplete grouting, voids behind the tunnel lining, or groundwater intrusion. If these defects are not detected and repaired promptly through secondary grouting, they will pose a significant threat to the long-term safe operation of the tunnel.

[0004] Through long-term engineering practice, the inventors and those skilled in the art have discovered two major technical bottlenecks in the quality inspection of grouting behind shield tunnel walls: First, electromagnetic wave detection methods such as ground-penetrating radar are affected by the strong shielding effect of the dense steel mesh inside the tunnel segments, making it difficult for electromagnetic waves to effectively penetrate to the back side of the segments, resulting in a detection blind zone. Second, traditional impact elastic wave methods (such as the impact echo method) mainly excite low-frequency narrow-band signals, while shield tunnel segments have a large number of joints, assembly bolt holes, and hand holes, which will cause complex waveform scattering, diffraction, and mode conversion, forming strong structural interference noise. Traditional narrow-band elastic waves are prone to superposition with the above-mentioned interference echoes, resulting in extremely low accuracy in identifying the thickness of the grouting body and the boundary of defects behind the wall. There is an inherent contradiction between insufficient high-frequency resolution and poor low-frequency anti-interference ability, which easily leads to misjudgment. Summary of the Invention

[0005] To address the technical challenges of simultaneously achieving both high penetration and high resolution in narrow-band elastic waves, as well as severe structural noise interference from shield tunnel segment joints, this invention provides a method and system for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels. By employing ultra-wideband frequency sweep excitation technology and a multi-dimensional domain joint anti-interference filtering algorithm, it achieves high-precision and intelligent anti-interference evaluation of the grouting quality behind the shield tunnel wall.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels.

[0007] A method for detecting ultra-wideband elastic wave interference in grouting for shield tunnels includes the following steps: Combining the deployed elastic wave detection array, which includes an ultra-wideband excitation source and a multi-channel high-frequency broadband receiving sensor, the effective longitudinal body wave apparent velocity range, grouting mass velocity model, reference spectrum, and classification threshold are obtained based on calibration operations. The ultra-wideband excitation source is controlled to emit a linear sweep frequency elastic wave signal, and the original spatiotemporal wave field signal is acquired by a multi-channel high-frequency broadband receiving sensor. The original spatiotemporal wavefield signal is transformed by frequency-wavenumber domain. A two-dimensional filter mask is constructed using the effective longitudinal volume wave apparent velocity range. Interference suppression is performed through the two-dimensional filter mask to obtain the initial filter field. Morphological component analysis was performed on the initial filtered field to remove structural interference texture components and reconstruct the target reflected wave field. At least three characteristic parameters are extracted from the target reflected wave field, including propagation time difference, quality factor, phase deflection angle, high-frequency energy attenuation rate, reflection energy ratio, and transmission energy ratio. Combined with the grouting body group velocity model, the thickness of the grouting layer is calculated using the characteristic parameters, and the state of the grouting body is determined based on the characteristic parameters and the classification threshold. By binding the detection point information and the reference spectrum correlation calibration information, the grouting quality evaluation results are generated.

[0008] In one implementation of the first aspect of the present invention, the linear sweep frequency elastic wave signal is a magnetostrictive sweep frequency excitation output signal, and the linear sweep frequency elastic wave signal includes a low-frequency component for deep exploration and a high-frequency component for high-resolution detection of local defects. The original spatiotemporal wavefield signal is subjected to a two-dimensional Fourier transform to obtain the frequency-wavenumber domain wavefield. The apparent propagation speed is calculated based on the frequency and wavenumber of each wavefield component in the frequency-wavenumber domain wavefield. A two-dimensional filter mask is used to attenuate or zero out the surface waves and structural scattered waves of the tube segments whose propagation apparent velocity is not within the effective longitudinal volume wave apparent velocity range, and the initial filter field is obtained by inverse transformation.

[0009] As a further limitation of the first aspect of the present invention, the initial filtered field is decomposed into smooth volume wave components and texture components. Based on the spatial position, propagation direction, propagation apparent speed and arrival time of the texture components, the structural interference texture components are identified, the structural interference texture components are removed, and the smooth volume wave components and the abnormal texture components of non-structural interference are retained to reconstruct the target reflected wave field.

[0010] In one implementation of the first aspect of the present invention, the process of extracting the quality factor includes: The test point spectrum and reference spectrum of the target reflected wave field are obtained. The spectral logarithm of the test point spectrum and the reference spectrum is calculated. The relative frequency of the spectral logarithm is linearly fitted. The quality factor of the test area is calculated based on the slope obtained from the fitting. The normalized quality factor index is obtained by combining the quality factor of the grouting compaction calibration area.

[0011] In one implementation of the first aspect of the present invention, the process of extracting the phase deflection angle includes: Two sets of analytical signals are obtained by performing Hilbert transform on the target reflection signal and the reference signal of the grouting compaction calibration area. The instantaneous phase of the target signal and the instantaneous phase of the reference signal are obtained from the two sets of analytical signals. The phase difference is obtained by performing phase expansion and period normalization on the two sets of instantaneous phases. The phase difference is used as the phase deflection angle.

[0012] In one implementation of the first aspect of the present invention, the process of extracting the high-frequency energy attenuation rate includes: The high-frequency energy of the target reflected wave and the reference signal of the grouting compaction calibration area within the preset high-frequency band are obtained respectively. The high-frequency energy attenuation rate is calculated based on the high-frequency energy of the target and the reference energy of the reference area.

[0013] In one implementation of the first aspect of the present invention, the process of calculating the thickness of the grouting layer includes: The propagation time difference between the reflected waves at the interface between the pipe segment and the grouting layer and the reflected waves at the interface between the grouting layer and the formation is obtained. The velocity of the grouting group at the center frequency output by the grouting group velocity model is read. Combined with the propagation angle of the elastic wave inside the grouting layer, the thickness of the grouting layer is calculated.

[0014] In one implementation of the first aspect of the present invention, determining the state of the grouting body based on a classification threshold includes: If the phase deflection angle falls within the preset angle range and the normalized quality factor is lower than the first threshold within the classification threshold, it is determined to be an air void. If the phase deflection angle does not fall within the preset angle range and the high-frequency energy attenuation rate is higher than the second threshold within the classification threshold, it is determined to be a water-containing defect. If the reflected energy ratio is lower than the third threshold within the classification threshold and the transmitted energy ratio is higher than the fourth threshold within the classification threshold, it is determined to be a grouting compaction. If the judgment results of multiple characteristic parameters conflict with each other, it is determined to be a suspected anomaly.

[0015] In one implementation of the first aspect of the present invention, generating grouting quality evaluation results includes: The spatial coordinates, grout layer thickness, grout body state, and characteristic parameters of each detection point are bound together. Spatial interpolation is then performed on the bound data to generate a three-dimensional unfolded diagram of the grout layer of the shield tunnel, outputting the defect center location, defect range, and suggested review location.

[0016] Secondly, the present invention provides a shield tunnel ultra-wideband elastic wave anti-interference grouting detection system.

[0017] A shield tunnel ultra-wideband elastic wave anti-interference grouting detection system includes: The calibration acquisition unit is configured to: combine the deployed elastic wave detection array, which includes an ultra-wideband excitation source and a multi-channel high-frequency broadband receiving sensor, to acquire the effective longitudinal body wave apparent velocity range, grouting body group velocity model, reference spectrum, and classification threshold based on calibration operations; The wave field acquisition unit is configured to control an ultra-wideband excitation source to emit a linear sweep frequency elastic wave signal, and acquire the original spatiotemporal wave field signal through a multi-channel high-frequency broadband receiving sensor. The frequency domain filtering unit is configured to: perform frequency-wavenumber domain transformation on the original spatiotemporal wavefield signal, construct a two-dimensional filtering mask using the effective longitudinal volume wave apparent velocity range, perform interference suppression through the two-dimensional filtering mask, and obtain the initial filtered field. The wavefield reconstruction unit is configured to perform morphological component analysis on the initial filtered field, remove structural interference texture components, and reconstruct the target reflected wavefield. The parameter analysis unit is configured to: extract at least three characteristic parameters from the target reflected wave field, including propagation time difference, quality factor, phase deflection angle, high-frequency energy attenuation rate, reflection energy ratio, and transmission energy ratio; combine the grouting body group velocity model; use the characteristic parameters to calculate the grouting layer thickness; and determine the grouting body state based on the characteristic parameters and classification threshold. The evaluation generation unit is configured to generate grouting quality evaluation results by binding detection point information and reference spectrum correlation calibration information.

[0018] Compared with the prior art, the beneficial effects of the present invention are: This invention addresses the waveform scattering interference caused by steel reinforcement shielding of tunnel segments, segment joints, and bolt holes. Traditional elastic wave detection methods struggle to balance penetration and defect identification resolution. By deploying and calibrating an elastic wave detection array, various calibration parameters required for subsequent processing are obtained. This invention transmits linearly swept-frequency elastic wave signals to acquire the original spatiotemporal wavefield signal. Frequency-wavenumber domain transformation is performed to construct a two-dimensional filter mask for initial interference suppression. Morphological component analysis is then used to remove structural interference texture components, reconstructing the target reflected wavefield. This reduces the impact of clutter from the tunnel segment structure on the effective reflected signal.

[0019] This invention extracts multiple feature parameters from the target reflected wave field, calculates the grout layer thickness using a grout mass velocity model, and then determines the grout state based on classification thresholds. This approach changes the previous method of relying solely on a single signal indicator for evaluation, and can distinguish between various conditions such as air voids, water-bearing defects, grout compaction, and suspected anomalies. Furthermore, this invention binds detection point information with calibration information to generate grout quality evaluation results, outputting grout layer thickness and defect-related evaluation information. This provides data support for assessing the grouting quality behind shield tunnel segments, facilitating staff understanding the actual grouting situation behind the tunnel wall, and assisting in subsequent review and handling.

[0020] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0021] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0022] Figure 1 A flowchart of a shield tunnel ultra-wideband elastic wave anti-interference grouting detection method provided as an exemplary embodiment of the present invention; Figure 2 A schematic diagram of the anti-interference mechanism for multi-channel elastic wave array detection and wave field propagation is provided as an exemplary embodiment of the present invention; Figure 3 This is a schematic diagram of a shield tunnel ultra-wideband elastic wave anti-interference grouting detection system provided as an exemplary embodiment of the present invention. Detailed Implementation

[0023] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0025] This implementation proposes a method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels, such as... Figure 1 As shown, it includes the following steps: Step S1: Deploy the tunnel elastic wave detection array.

[0026] An elastic wave detection array is deployed on the inner surface of the shield tunnel segments. The detection array includes an ultra-wideband excitation source and a multi-channel high-frequency broadband receiving sensor.

[0027] In this implementation, the ultra-wideband excitation source is a magnetostrictive linear sweep frequency exciter. The frequency range of the linear sweep frequency elastic wave signal is 1kHz to 100kHz. The 1kHz to 20kHz frequency band is used for deep detection of segments and grouting layers, and the 20kHz to 100kHz frequency band is used for high-resolution detection of local defects in the grouting layer.

[0028] Step S2: Transmit signal to acquire raw wavefield data.

[0029] An ultra-wideband excitation source is controlled to emit ultra-wideband swept-frequency elastic wave signals into the tunnel lining segments. Simultaneously, a multi-channel high-frequency broadband receiving sensor is used to acquire the original elastic wave field signals, which include tunnel lining structure noise, grouting layer reflected waves, and ground transmitted waves, forming the original spatiotemporal wave field matrix. ,in, For the first The spatial location of each receiving channel For the first Each sampling time.

[0030] Ultra-wideband swept frequency elastic wave signal Represented as: (1); in, Let be the excitation envelope function. The starting frequency, = - For the sweep bandwidth, For the termination frequency, For the duration of the frequency sweep, This is the initial phase.

[0031] Step S3: Preprocess the wave field signal by filtering in the fk domain.

[0032] Performing a two-dimensional Fourier transform on the original spatiotemporal wavefield signal yields... f - k The wave field is generated, and a two-dimensional filtering mask is constructed based on the frequency, wave number, and apparent propagation velocity. The surface waves of the tube segments and the scattered waves from the structure that are outside the effective longitudinal volume wave apparent velocity range are attenuated or zeroed. The filtered wave field is then inversely transformed to the spatiotemporal domain, and decomposed into smooth volume wave components and texture components through morphological component analysis. The structural interference texture components that match the spatial position and propagation characteristics of the tube segment joints, bolt holes, or hand holes are removed, while the smooth volume wave components and the abnormal texture components of non-structural interference are retained. The target reflected wave field is then reconstructed.

[0033] More specifically, multi-dimensional joint anti-interference separation is performed on the acquired raw elastic wave field signal, using a method based on... f - k A joint filtering algorithm combining frequency-wavenumber domain and morphological component analysis is used to suppress and eliminate scattered interference waves generated by segment joints and bolt holes, thereby extracting pure grouting layer reflection signals.

[0034] f - k The frequency-wavenumber domain is calculated according to the following formula: (2); in, The complex wave field after frequency-wavenumber domain (fk domain) transformation is the result of two-dimensional Fourier transform in space and time. This represents the total number of receiving sensor channels; Represents the total number of sampling points in a single channel; Represents the receiving channel number; Represents the sampling time sequence number; Representing the The spatial coordinates of the receiving sensor; Representing the Each sampling time; represent Position sensor in The amplitude of the elastic wave signal collected at any time; For space wavenumber, For frequency; The propagation apparent speed of wave field components that are not equal to zero. for: (3); Based on the effective longitudinal body wave apparent velocity range obtained from the calibration Constructing a two-dimensional filter mask When the apparent velocity of a wavefield component falls within the effective longitudinal volume wave apparent velocity range, it is retained; when a wavefield component corresponds to a segment surface wave, joint scattering wave, or bolt hole scattering wave, it is attenuated or zeroed; a smooth transition band is set between the effective wave region and the interference wave region. Filtered wavefield. for: (4); right Perform a two-dimensional inverse Fourier transform to obtain the initial filtered spacetime wave field. .

[0035] Step S4: Morphological analysis to eliminate structural interference.

[0036] Morphological component analysis was used to filter the initial spatiotemporal wave field. Represented as smooth volume wave components Texture components and residual components The sum is: (5); By solving And satisfy Obtain the sparsity coefficient of the smooth component. and texture component sparsity coefficient ,in This is a dictionary of smooth components used to represent reflected waves from continuous interfaces. This is a dictionary of texture components used to represent locally scattered waves. These are the weighting coefficients. This is the allowable value for residuals. It is the L2 norm. It is an L1 norm.

[0037] Based on the known spatial locations of segment joints, bolt holes, and handholes, as well as the propagation direction, apparent velocity, arrival time, and spatial repeatability of texture components, the texture components are classified. Only structural interference texture components that match the segment structure location and possess surface propagation or low apparent velocity characteristics are removed, while smooth volume wave components and anomalous texture components that do not meet the structural interference criteria are retained. The target reflected wavefield is then reconstructed. : (6); in, The sparsity coefficient of the abnormal texture retained after removing structural interference.

[0038] Step S5: Extract multiple types of wavefield feature parameters.

[0039] At least three characteristic parameters are extracted from the target reflected wave field: propagation time difference, quality factor, phase deflection angle, high-frequency energy attenuation rate, reflection energy ratio, and transmission energy ratio. The quality factor is obtained by fitting the spectral ratio between the spectrum of the target reflected wave at the test point and the reference spectrum of the grouting compaction calibration area. The phase deflection angle is determined by the phase difference obtained by the Hilbert transform between the target reflected signal at the test point and the reference signal. The high-frequency energy attenuation rate is determined by the energy ratio between the target reflected wave at the test point and the reference signal in the frequency band of 20kHz to 100kHz.

[0040] More specifically, the spectrum of the point to be measured is extracted within the time window of the target reflected wave. Reference spectrum of grouting compaction calibration area Establish the spectrum ratio relationship: (7); in, Represents the fitting constant term. This represents the propagation time of the elastic wave within the grouting layer.

[0041] A linear fit is performed on the logarithm of the spectrum and the frequency. When the slope of the fit is... At that time, the quality factor of the area to be tested for: (8); Define the normalized quality factor index: (9); in, This is the quality factor for the grouting compaction calibration zone.

[0042] Target reflection signal at the test point Perform Hilbert transform to construct analytic signal : (10); The instantaneous phase is obtained according to formula (10). The instantaneous phase of the reference signal is obtained using the same method. Within the target reflected wave time window, the phase difference after phase expansion and period normalization is calculated and used as the phase deflection angle. , This represents the Hilbert transform.

[0043] High-frequency energy at the test point: (11); High-frequency energy in the reference region: (12); High-frequency energy decay rate: (13); The ratio of the energy of the reflected wave to the energy of the incident reference wave is called the reflected energy ratio. The ratio of the energy of the transmitted wave from the target to the energy of the incident reference wave is called the transmission energy ratio. .

[0044] Step S6: Calculate the thickness to identify defects in the grouting layer.

[0045] The thickness of the grouting layer is calculated based on the propagation time difference of the reflected wave from the target and the velocity model of the grouting mass: (14); in, For the grouting body at the center frequency Group velocity at that location, This refers to the time difference between the reflected wave at the interface between the tunnel lining segment and the grouting layer, and the reflected wave at the interface between the grouting layer and the formation. The propagation angle of the elastic wave in the grouting layer is given by the group velocity model, which is obtained by fitting calibration data.

[0046] The first to fourth thresholds are determined based on calibration specimens, known field conditions, borehole verification data, or historical test samples. When the phase deflection angle is between 160° and 200° and the normalized quality factor is below the first threshold, it is determined to be air void; when the phase deflection angle is not between 160° and 200° and the high-frequency energy attenuation rate is greater than the second threshold, it is determined to be a water-bearing defect or water sac; when the reflection energy ratio is below the third threshold and the transmission energy ratio is above the fourth threshold, it is determined to be grouting compaction; when different indicators conflict, it is determined to be a suspected anomaly, and repeated testing or borehole verification is performed. The grouting mass velocity model and each preset threshold are determined using calibration specimens with known grouting conditions, known field conditions, borehole verification data, or historical test samples.

[0047] Step S7: Output the detection results in 3D mapping.

[0048] The spatial coordinates, grout layer thickness, defect type, defect confidence level, and characteristic parameters of each detection point are bound together. A three-dimensional unfolded map of the grout layer of the shield tunnel is generated by spatial interpolation, and the defect center location, defect range, and suggested review location are output.

[0049] Figure 2 The diagram illustrates the detection mechanism and anti-interference mechanism of a multi-channel elastic wave array. Along the tunnel axis, an ultra-wideband excitation source and a multi-channel receiving sensor array are arranged on the inner surface of the shield segment layer in the tunnel arch of the inner layer of the tunnel. The elastic waves excited by the ultra-wideband excitation source propagate to the outside of the shield segment layer, passing through the segment-grouting layer interface and entering the back wall grouting layer. Some elastic waves are reflected when they encounter cavities and defects inside the back wall grouting layer, while others pass through the grouting layer-soil interface and are incident on the original stratum. Reflected waves generated by karst caves in the original stratum can be received. The multi-channel receiving sensor array receives various types of reflected waves. This detection architecture can collect various wave field signals including those from the segment structure, grouting layer defects, and stratum anomalies, providing the original wave field data basis for subsequent joint anti-interference processing of fk domain and morphological component analysis and separation and extraction of effective reflection signals from the grouting layer.

[0050] More specifically, the following on-site implementation examples are provided: In actual shield tunnel testing projects, an elastic wave detection array is attached to the inner surface of the segment to be tested. To eliminate high-frequency signal attenuation caused by poor contact, a special high-frequency acoustic coupling agent is applied to the bottom of the sensor, and a vacuum suction cup is used to ensure constant pressure coupling between the multi-channel sensor array and the segment surface.

[0051] Before testing, a known grouting compaction area was selected as a reference area. When conditions permit, specimens with known thickness, air voids, and water-containing defects were further used for calibration to obtain the longitudinal wave velocity of the pipe segment, the model of the grout group velocity as a function of frequency, the effective longitudinal body wave apparent velocity range, and the reference spectrum, quality factor, phase, and energy index of different grouting states.

[0052] The magnetostrictive sweep frequency exciter is activated to generate a linear frequency modulated elastic wave with a smooth transition from 1kHz to 100kHz within a predetermined sweep time. The multi-channel receiving array uses a unified clock to synchronously record the complete wave field signal, with a sampling frequency preferably between 1MHz and 5MHz, and synchronously saves the spatial coordinates, sampling time, and signal data of each channel.

[0053] After performing time zero-point correction, channel consistency correction, and pulse compression on each channel signal, the spatiotemporal wavefield is converted to... f - k In the domain, the reflected waves from the grouting layer in the longitudinal depth have a higher apparent velocity, while the diffracted waves from the joints and surface waves propagating along the surface of the pipe segment have a lower apparent velocity. Based on the effective longitudinal volume wave apparent velocity range obtained by calibration, a two-dimensional filter mask is constructed to attenuate or zero the low apparent velocity interference area, and a smooth transition band is set at the filter boundary.

[0054] The initial filtered field is inversely transformed to the spatiotemporal domain, and morphological component analysis is performed using a smooth component dictionary and a texture component dictionary. Iteration stops when the change in reconstruction error between two adjacent iterations is lower than a preset termination value, or when the number of iterations reaches a preset maximum. For local energy clusters in the texture component, their spatial center position, propagation direction, apparent velocity, and arrival time are calculated respectively. Only local energy clusters that match the positions of pipe joints, bolt holes, or handholes and conform to surface propagation characteristics are discarded as structural interference. The remaining anomalous texture components are used together with the smoothed volume wave components for target reflection wavefield reconstruction.

[0055] The reflection events at the interface between the segment and the grouting layer, the reflection events at the interface between the grouting layer and the formation, and the transmission events are determined from the reconstructed target reflection wave field. The thickness of the grouting layer is calculated based on the propagation time difference between the two interface reflection events and the calibration group velocity.

[0056] Within the target reflection wave time window, the spectral ratio between the test point and the dense reference area is calculated. The quality factor is obtained through linear regression, and the normalized quality factor index is calculated. The phase deflection angles of the test signal and the reference signal are obtained using Hilbert transform. The high-frequency energy attenuation rate, reflection energy ratio, and transmission energy ratio in the 20kHz to 100kHz frequency band are calculated respectively.

[0057] The first to fourth thresholds are determined by known state samples. These can be feature cutoff values ​​that minimize the classification error rate, or determined through receiver operating characteristic curves, cluster analysis, or classification model training. For measurement points that do not meet any defined classification rule or whose different feature indicators conflict with each other, a suspected anomaly label is output, and no forced classification is performed.

[0058] The shield tunnel's inspection area is continuously inspected according to a predetermined step size. Each measuring point is repeatedly vibrated and data is collected multiple times, and the results of repeated collections are superimposed and averaged. The grout layer thickness, defect type, and confidence level of each inspection point are mapped into the three-dimensional unfolded model of the shield tunnel. For multiple adjacent measuring points exhibiting the same abnormal characteristics consecutively, they are merged into the same defect area; for a single low-confidence abnormal measuring point, verification is performed through repeated inspections or drilling.

[0059] In summary, this invention overcomes the technical bottleneck of limited frequency band by employing an ultra-wideband sweep excitation frequency of 1kHz to 100kHz, effectively balancing the penetration required for detection depth with the high resolution of minute defects, and solving the problem of missed defect detection caused by the single frequency band in the traditional impact echo method; it also achieves a fundamental breakthrough in anti-interference technology, and for the first time adopts a method specifically targeting the interference from the unique joint and bolt hole structures of shield tunnel segments. f - k The joint analysis algorithm of domain and morphological components accurately separates and eliminates structural noise, enabling the effective extraction of grout layer reflection signals submerged by clutter, significantly improving the detection signal-to-noise ratio under complex working conditions; it realizes multi-dimensional and accurate evaluation of grouting quality, breaking through the limitations of traditional methods that rely solely on wave velocity or amplitude as a single indicator, and integrates unique parameters of ultra-wideband signals such as quality factor Q value and phase deflection angle, which can accurately distinguish three different media states: air voids, water pockets, and grout compaction, thus achieving a refined evaluation of grouting quality.

[0060] Figure 3 A shield tunnel ultra-wideband elastic wave anti-interference grouting detection system is shown, comprising: The calibration acquisition unit 301 is configured to: combine the deployed elastic wave detection array, which includes an ultra-wideband excitation source and a multi-channel high-frequency broadband receiving sensor, to acquire the effective longitudinal body wave apparent velocity range, grouting body group velocity model, reference spectrum, and classification threshold based on calibration operations; The wave field acquisition unit 302 is configured to: control the ultra-wideband excitation source to emit a linear sweep frequency elastic wave signal, and acquire the original spatiotemporal wave field signal through a multi-channel high-frequency broadband receiving sensor; The frequency domain filtering unit 303 is configured to: perform frequency-wavenumber domain transformation on the original spatiotemporal wavefield signal, construct a two-dimensional filtering mask using the effective longitudinal volume wave apparent velocity range, perform interference suppression through the two-dimensional filtering mask, and obtain the initial filtered field. The wavefield reconstruction unit 304 is configured to: perform morphological component analysis on the initial filtered field, remove structural interference texture components, and reconstruct the target reflected wavefield. The parameter analysis unit 305 is configured to: extract at least three characteristic parameters from the target reflected wave field, including propagation time difference, quality factor, phase deflection angle, high-frequency energy attenuation rate, reflection energy ratio, and transmission energy ratio; combine the grouting body group velocity model; use the characteristic parameters to calculate the grouting layer thickness; and determine the grouting body state based on the characteristic parameters and the classification threshold. The evaluation generation unit 306 is configured to generate grouting quality evaluation results by binding detection point information and reference spectrum correlation calibration information.

[0061] It is understood that the aforementioned units can be individually or entirely merged into one or more other units, or some of the units can be further divided into multiple functionally smaller units. This achieves the same operation without affecting the technical effects of the embodiments of the present invention. The aforementioned units are based on logical functional division. In practical applications, the function of one unit can be implemented by multiple units, or the function of multiple units can be implemented by one unit. In other embodiments of the present invention, the system may also include other units. In practical applications, these functions can also be implemented with the assistance of other units, and can be implemented collaboratively by multiple units.

[0062] According to another embodiment of the present invention, the system of this embodiment can be constructed by running a computer program (including program code) capable of performing the steps involved in the corresponding method of the present invention on a general-purpose computing device, such as a computer, which includes processing elements and storage elements such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM). The computer program can be recorded on, for example, a computer-readable recording medium, loaded into the aforementioned computing device through the computer-readable recording medium, and run therein.

[0063] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can implement the described functions using different methods for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0064] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic cable, digital cable) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0065] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A shield tunnel ultra-wideband elastic wave anti-interference grouting detection method, characterized in that, Includes the following processes: Combining the deployed elastic wave detection array, which includes an ultra-wideband excitation source and a multi-channel high-frequency broadband receiving sensor, the effective longitudinal body wave apparent velocity range, grouting mass velocity model, reference spectrum, and classification threshold are obtained based on calibration operations. The ultra-wideband excitation source is controlled to emit a linear sweep frequency elastic wave signal, and the original spatiotemporal wave field signal is acquired by a multi-channel high-frequency broadband receiving sensor. The original spatiotemporal wavefield signal is transformed by frequency-wavenumber domain. A two-dimensional filter mask is constructed using the effective longitudinal volume wave apparent velocity range. Interference suppression is performed through the two-dimensional filter mask to obtain the initial filter field. Morphological component analysis was performed on the initial filtered field to remove structural interference texture components and reconstruct the target reflected wave field. At least three characteristic parameters are extracted from the target reflected wave field, including propagation time difference, quality factor, phase deflection angle, high-frequency energy attenuation rate, reflection energy ratio, and transmission energy ratio. Combined with the grouting body group velocity model, the thickness of the grouting layer is calculated using the characteristic parameters, and the state of the grouting body is determined based on the characteristic parameters and the classification threshold. By binding the detection point information and the reference spectrum correlation calibration information, the grouting quality evaluation results are generated.

2. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 1, characterized in that, The linear sweep frequency elastic wave signal is the magnetostrictive sweep frequency excitation output signal. The linear sweep frequency elastic wave signal contains low-frequency components for deep exploration and high-frequency components for high-resolution detection of local defects. The original spatiotemporal wavefield signal is subjected to a two-dimensional Fourier transform to obtain the frequency-wavenumber domain wavefield. The apparent propagation speed is calculated based on the frequency and wavenumber of each wavefield component in the frequency-wavenumber domain wavefield. A two-dimensional filter mask is used to attenuate or zero out the surface waves and structural scattered waves of the tube segments whose propagation apparent velocity is not within the effective longitudinal volume wave apparent velocity range, and the initial filter field is obtained by inverse transformation.

3. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 2, characterized in that, The initial filtered field is decomposed into smooth volume wave components and texture components. Based on the spatial location, propagation direction, apparent propagation speed, and arrival time of the texture components, structural interference texture components are identified. The structural interference texture components are removed, while the smooth volume wave components and the anomalous texture components without structural interference are retained, and the target reflected wave field is reconstructed.

4. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 1, characterized in that, The process of extracting quality factors includes: The test point spectrum and reference spectrum of the target reflected wave field are obtained. The spectral logarithm of the test point spectrum and the reference spectrum is calculated. The relative frequency of the spectral logarithm is linearly fitted. The quality factor of the test area is calculated based on the slope obtained from the fitting. The normalized quality factor index is obtained by combining the quality factor of the grouting compaction calibration area.

5. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 1, characterized in that, The process of extracting the phase deflection angle includes: Two sets of analytical signals are obtained by performing Hilbert transform on the target reflection signal and the reference signal of the grouting compaction calibration area. The instantaneous phase of the target signal and the instantaneous phase of the reference signal are obtained from the two sets of analytical signals. The phase difference is obtained by performing phase expansion and period normalization on the two sets of instantaneous phases. The phase difference is used as the phase deflection angle.

6. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 1, characterized in that, The process of extracting the high-frequency energy decay rate includes: The high-frequency energy of the target reflected wave and the reference signal of the grouting compaction calibration area within the preset high-frequency band are obtained respectively. The high-frequency energy attenuation rate is calculated based on the high-frequency energy of the target and the reference energy of the reference area.

7. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 1, characterized in that, The process of calculating the thickness of the grouting layer includes: The propagation time difference between the reflected waves at the interface between the pipe segment and the grouting layer and the reflected waves at the interface between the grouting layer and the stratum is obtained. The velocity of the grouting mass group at the center frequency output by the grouting mass group velocity model is read. Combined with the propagation angle of the elastic wave inside the grouting layer, the thickness of the grouting layer is calculated.

8. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 1, characterized in that, The grouting body status is determined based on classification thresholds, including: If the phase deflection angle falls within the preset angle range and the normalized quality factor is lower than the first threshold within the classification threshold, it is determined to be an air void. If the phase deflection angle does not fall within the preset angle range and the high-frequency energy attenuation rate is higher than the second threshold within the classification threshold, it is determined to be a water-containing defect. If the reflected energy ratio is lower than the third threshold within the classification threshold and the transmitted energy ratio is higher than the fourth threshold within the classification threshold, it is determined to be a grouting compaction. If the judgment results of multiple characteristic parameters conflict with each other, it is determined to be a suspected anomaly.

9. The method for detecting ultra-wideband elastic wave anti-interference grouting in shield tunnels as described in claim 1, characterized in that, Generate grouting quality evaluation results, including: The spatial coordinates, grout layer thickness, grout body state, and characteristic parameters of each detection point are bound together. Spatial interpolation is then performed on the bound data to generate a three-dimensional unfolded diagram of the grout layer of the shield tunnel, outputting the defect center location, defect range, and suggested review location.

10. A shield tunnel ultra-wideband elastic wave anti-interference grouting detection system, characterized in that, include: The calibration acquisition unit is configured to: combine the deployed elastic wave detection array, which includes an ultra-wideband excitation source and a multi-channel high-frequency broadband receiving sensor, to acquire the effective longitudinal body wave apparent velocity range, grouting body group velocity model, reference spectrum, and classification threshold based on calibration operations; The wave field acquisition unit is configured to control an ultra-wideband excitation source to emit a linear sweep frequency elastic wave signal, and acquire the original spatiotemporal wave field signal through a multi-channel high-frequency broadband receiving sensor. The frequency domain filtering unit is configured to: perform frequency-wavenumber domain transformation on the original spatiotemporal wavefield signal, construct a two-dimensional filtering mask using the effective longitudinal volume wave apparent velocity range, perform interference suppression through the two-dimensional filtering mask, and obtain the initial filtered field. The wavefield reconstruction unit is configured to perform morphological component analysis on the initial filtered field, remove structural interference texture components, and reconstruct the target reflected wavefield. The parameter analysis unit is configured to: extract at least three characteristic parameters from the target reflected wave field, including propagation time difference, quality factor, phase deflection angle, high-frequency energy attenuation rate, reflection energy ratio, and transmission energy ratio; combine the grouting body group velocity model; use the characteristic parameters to calculate the grouting layer thickness; and determine the grouting body state based on the characteristic parameters and classification threshold. The evaluation generation unit is configured to generate grouting quality evaluation results by binding detection point information and reference spectrum correlation calibration information.

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