Shield tunnel boulder body acoustic wave detection method and system based on morphological structure constraint

Abstract

The present application belongs to the technical field of adverse geological body imaging, and provides a shield tunnel boulder body acoustic wave detection method and system based on morphological structure constraint. In the present application, large boulders are regarded as near-circular shapes, the low-frequency response interface in low-frequency reverse time migration is flipped, the front edge envelope boundary with the local convex feature towards the direction of the working face is determined, so that the initial model constructed is more consistent with the geometric shape of the boulder target body, and a reasonable boundary basis is provided for the subsequent closure construction of the envelope area. At the same time, the smooth gradual change representation method with gradually increasing velocity from the boundary to the inside is adopted, the front edge envelope boundary and the empirical boundary are closed to obtain the prior envelope area, which can not only retain the stable advantage of low-frequency imaging in target body positioning, but also weaken the adverse effects of imaging migration and boundary ambiguity on subsequent high-frequency imaging, and can provide better safety construction basis.

Description

Technical Field

[0001] This invention belongs to the field of imaging technology for adverse geological bodies, and particularly relates to a method and system for acoustic detection of boulder bodies in shield tunnels based on morphological and structural constraints. Background Technology

[0002] When detecting large boulders during tunnel construction, the propagation characteristics of sound waves of different frequencies in the underground medium can ensure detection effectiveness. Low-frequency waves, with their longer wavelengths, possess strong penetration and good stability, making them suitable for overall perception of underground structures. High-frequency waves, with their shorter wavelengths, offer higher spatial resolution and can more clearly delineate the boundaries of anomalies. In terms of wave velocity modeling, the reverse-time migration results of low-frequency primary reflection waves are used to extract potential information about the target body, constructing an initial wave velocity model for high-frequency reverse-time migration, providing stable constraints for subsequent high-frequency imaging.

[0003] However, boulders typically appear as locally isolated, blocky anomalous bodies in strata. When constructing the low-frequency initial wave velocity model, the prior envelope region in the model constructed using conventional zoning and boundary delineation methods differs significantly from the local features of the boulders, especially in the direction towards the working face. This results in inaccurate final imaging identification. Furthermore, because low-frequency wavelengths are longer, the imaging results are affected by finite band effects, wavefield focusing width, and imaging kernel expansion. The anomalous response often manifests as a relatively broad and gentle energy accumulation band, causing the low-frequency imaging response to spatially deviate from the true frontal interface of the boulders, exhibiting a certain degree of ambiguity. If this imaging response is directly treated as a rigid boundary and a closed model is constructed, it can easily lead to distorted estimation of the target body's range, thereby misleading subsequent high-frequency imaging and failing to provide a reliable basis for safe construction. Summary of the Invention

[0004] To address the aforementioned problems, this invention proposes a method and system for acoustic detection of boulder bodies in shield tunnels based on morphological constraints. This invention treats large boulders as nearly circular and flips the low-frequency response interface in low-frequency reverse-time offset to determine a leading-edge envelope boundary with locally convex features towards the tunnel face. This makes the constructed initial model more consistent with the geometry of the boulder target, providing a reasonable boundary basis for subsequent envelope closure construction. Simultaneously, a smooth gradient characterization method with gradually increasing velocity from the boundary to the interior is used to close the leading-edge envelope boundary and empirical boundary to obtain a guided initial model. This method retains the stability advantage of low-frequency imaging in target positioning while mitigating the adverse effects of imaging offset and boundary blurring on subsequent high-frequency imaging, providing a better basis for safe construction.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: In a first aspect, the present invention provides a method for acoustic detection of boulder bodies in shield tunnels based on morphological constraints, comprising: The incomplete boundary of the boulder determined by the low-frequency reverse time offset is used as the initial constraint; Based on the initial constraints, the boundary is regarded as the starting surface of the boulder's geometric constraints, and it is extended into the interior of the boulder along the exploration direction to determine the a priori region that characterizes the spatial extent of the boulder. The large boulder is considered to be nearly circular; based on the prior region, the low-frequency response interface in the low-frequency reverse time migration is flipped to determine the leading edge envelope boundary with local outward convexity towards the working face. In the exploration direction, the low-frequency response interface is used as a benchmark. The low-frequency response interface is enlarged on a geometric scale to determine the empirical boundary corresponding to the back envelope of the boulder. A smooth gradient representation method is adopted, in which the velocity gradually increases from the boundary to the interior, to close the leading edge envelope boundary and the empirical boundary to obtain the prior envelope region.

[0006] Furthermore, the determination of the empirical boundary includes: defining the exploration direction as a direction perpendicular to the working face and pointing towards the interior of the area to be explored; using the low-frequency response interface as a reference, enlarging the low-frequency response interface on a geometric scale and extending it along the exploration direction to establish an empirical boundary corresponding to the rear envelope of the target body; during the translation process, the midpoint is used as a control reference point.

[0007] Furthermore, the spacing between the control low-frequency response interface and the empirical boundary is twice the length of the front interface.

[0008] Furthermore, the prior envelope region is labeled as the inner region, and the portion outside the inner region is denoted as the outer region. A boundary transition region of preset thickness is constructed around the boundary of the prior envelope. By adjusting the smoothness weights, the velocity variation capability of different regions is controlled, resulting in a smooth gradient where the velocity gradually increases from the boundary to the interior. The objective function of the model construction is: ; in, This is the initial velocity model to be built; It is a geological background velocity model; It is a smoothness weighting function for spatial variations; It is the velocity gradient; For the entire detection range.

[0009] Furthermore, the initial velocity model in the outer region is the background equivalent medium velocity field; the boundary transition region introduces a rapid velocity transition constraint in the front interface region, so that the velocity smoothly transitions from the background value to the anomaly velocity, the normal smoothness factor rapidly decreases from the background value to the minimum smoothness, and rapidly increases from the minimum smoothness to the maximum smoothness along the normal multi-layer mesh.

[0010] Furthermore, the boundary velocity of the boundary transition region is: ; ; ; in, The velocity difference between the anomalous body and the background medium; The weight function is defined in the boundary region; The distance from the point to the known boundary; To achieve minimum smoothness, It represents maximum smoothness; The width of the Gaussian kernel; The length is the exponentially decaying length.

[0011] Furthermore, the internal region adopts a gradual velocity structure that increases progressively from the leading edge inwards and then gradually decreases towards the trailing edge.

[0012] Furthermore, let's assume Point Normalized position coordinates along the exploration direction within the prior envelope, and the internal velocity: ; ; in, This is the internal gradient weight function; Shape parameters used to control the degree of internal reinforcement.

[0013] Furthermore, two sets of boulder models with different diameters were selected for numerical verification. Both models were set as a single boulder anomaly in a background of strong scattering by pebbles. First, the front interface information of the anomaly was extracted using the reverse time migration results of low-frequency primary reflection waves. Then, a traditional high-frequency smoothed inverse propagation wave field initial model and an initial model based on local outward convexity features were constructed respectively. Finally, the differences in high-frequency reverse time migration results under the two types of initial model conditions were compared.

[0014] Secondly, the present invention also provides an acoustic wave detection system for boulder bodies in shield tunnels based on morphological and structural constraints, comprising: The initial constraint determination module is configured to: obtain the incomplete boundary of the boulder determined by the low-frequency reverse time offset as the initial constraint; The prior area determination module is configured to: based on the initial constraints, treat the boundary as the starting surface of the boulder geometric constraints, extend it along the exploration direction into the interior of the boulder, and determine the prior area that characterizes the spatial extent of the boulder. The leading edge envelope boundary determination module is configured to: treat the large boulder as nearly circular; based on the prior region, flip the low-frequency response interface in the low-frequency reverse time offset to determine the leading edge envelope boundary with local outward convexity towards the working face. The empirical boundary determination module is configured to: in the exploration direction, using the low-frequency response interface as a reference, enlarge the low-frequency response interface on a geometric scale to determine the empirical boundary corresponding to the back envelope of the boulder. The model building module is configured to use a smooth gradient representation method that gradually increases the velocity from the boundary to the interior to close the leading edge envelope boundary and the empirical boundary to obtain the prior envelope region.

[0015] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in the first aspect.

[0016] Fourthly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to implement the steps of the acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in the first aspect.

[0017] Fifthly, the present invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in the first aspect.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention first considers the boundary as the starting surface of the boulder's geometric constraints based on the initial constraints, extending it inward along the exploration direction to determine the a priori region characterizing the boulder's spatial extent. Then, the large boulder is considered nearly circular. Based on the a priori region, the low-frequency response interface in the low-frequency reverse-time migration is flipped to determine the leading-edge envelope boundary with local outward convexity towards the working face. In the exploration direction, using the low-frequency response interface as a reference, the interface is geometrically enlarged to determine the empirical boundary corresponding to the boulder's rear envelope. Finally, a smooth, gradual characterization method with progressively increasing velocity from the boundary inward is used to close the leading-edge envelope boundary and the empirical boundary to obtain the a priori envelope region. By treating the large boulder as nearly circular and flipping the low-frequency response interface in the low-frequency reverse time migration, a leading-edge envelope boundary with local outward convexity towards the working face is determined. This makes the constructed initial model more consistent with the geometry of the boulder target, providing a reasonable boundary basis for the subsequent envelope closure construction. At the same time, a smooth gradient characterization method with gradually increasing velocity from the boundary to the interior is adopted to close the leading-edge envelope boundary and the empirical boundary to obtain a guided initial model. This not only retains the stability advantage of low-frequency imaging in target positioning but also reduces the adverse effects of imaging offset and boundary blur on subsequent high-frequency imaging, providing a better basis for safe construction. Attached Figure Description

[0019] The accompanying drawings, which form part of this embodiment, are used to provide a further understanding of this embodiment. The illustrative embodiments and their descriptions are used to explain this embodiment and do not constitute an improper limitation of this embodiment.

[0020] Figure 1 The outline of a large boulder in a tunnel construction according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the prior envelope region in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the smoothness distribution of the entire spatial domain in Embodiment 1 of the present invention; Figure 4 This is a model of a large boulder with a diameter of 1.2m, as described in Embodiment 1 of the present invention. Figure 5 The image shows the 300Hz imaging result of a large boulder with a diameter of 1.2m in Embodiment 1 of the present invention. Figure 6 This is the initial model of the Gaussian smoothed inverse propagation wavefield for imaging a 1.2m diameter boulder in Embodiment 1 of the present invention; Figure 7 The image shows the 1000Hz imaging result of a large boulder with a diameter of 1.2m, corresponding to the initial model of the Gaussian smoothed inverse propagation wavefield in Embodiment 1 of the present invention. Figure 8 As in Embodiment 1 of the present invention Figure 7 A magnified view of the corresponding part; Figure 9 This is the initial model of incomplete boundary prior constraints for imaging a large boulder with a diameter of 1.2m in Embodiment 1 of the present invention; Figure 10 The image shows the 1000Hz imaging result of a large boulder with a diameter of 1.2m, corresponding to the incomplete boundary prior constraint initial model of Embodiment 1 of the present invention. Figure 11 As in Embodiment 1 of the present invention Figure 10 A magnified view of the corresponding part; Figure 12 This is a 3.0m diameter boulder model from Embodiment 1 of the present invention; Figure 13 The image shows the 300Hz imaging result of a large boulder with a diameter of 3.0m in Embodiment 1 of the present invention. Figure 14 This is the initial model of the Gaussian smoothed inverse propagation wavefield for imaging a 3.0m diameter boulder in Embodiment 1 of the present invention; Figure 15 The image shows the 1000Hz imaging result of a large boulder with a diameter of 3.0m, corresponding to the initial model of the Gaussian smoothed inverse propagation wavefield in Embodiment 1 of the present invention. Figure 16 As in Embodiment 1 of the present invention Figure 15 A magnified view of the corresponding part; Figure 17 This is the initial model of incomplete boundary prior constraints for imaging a large boulder with a diameter of 3.0m in Embodiment 1 of the present invention; Figure 18 The image shows the 1000Hz imaging result of a large boulder with a diameter of 3.0m, corresponding to the incomplete boundary prior constraint initial model of Embodiment 1 of the present invention. Figure 19 As in Embodiment 1 of the present invention Figure 18 A magnified view of the corresponding part. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. 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 application pertains.

[0023] Example 1: This embodiment provides a method for acoustic detection of boulder bodies in shield tunnels based on morphological and structural constraints, including: S1. Prior characterization of the incomplete boundary of the large boulder: Reverse time migration (RTM) is highly sensitive to the initial velocity model. When there is a significant deviation between the initial model and the actual underground structure, the forward and reverse propagating wave fields cannot be effectively focused at the true location of the target, leading to problems such as interface misalignment, morphological distortion, and false anomalies in the imaging results. Therefore, to achieve a multi-frequency acoustic fusion imaging strategy that first shapes low-frequency (e.g., wave signals equal to or less than 300Hz) signals and then performs edge extraction at high-frequency (e.g., wave signals equal to or greater than 1000Hz) frequencies, it is necessary to first address the sensitivity of high-frequency RTM to the initial model. This is a prerequisite for ensuring the stability and reliability of RTM imaging of large boulders.

[0024] Compared to high-frequency sound waves, low-frequency sound waves have longer wavelengths and stronger penetrating power. They also exhibit a relatively weaker response to small-scale scatterers within the pebble layer, making it easier to maintain the overall stability of the wave field propagation. For large boulder targets, low-frequency first reflections primarily respond to the geometric features of the large-scale target. While the imaging results have limited resolution and cannot precisely depict the true boundaries of the target, they can stably characterize the overall spatial position of the target and its interface response towards the observation system. Therefore, low-frequency first reflections are more suitable as a boundary prior source for initial model construction. Leveraging the advantage of relatively stable imaging of low-frequency signals against complex backgrounds, the interface portion of the target most easily characterized by the low-frequency wave field can be prioritized. For example, for large boulders in front of the tunnel face, low-frequency RTM often first images the front interface of the target facing the seismic source.

[0025] From a practical engineering perspective, large boulders typically appear in strata as locally isolated, blocky high-velocity anomalies, with their projected shape on a two-dimensional cross-section often resembling a circle or ellipse. To illustrate this more clearly, the external outline of the large boulder in this embodiment has been simplified, as shown below. Figure 1 As shown, although the large boulders in the strata exhibit certain morphological differences, they generally possess geometric characteristics of local closure, continuous boundaries, and blunt, rounded shapes. In terms of two-dimensional imaging and velocity model construction, approximating the large boulders as near-circular or near-elliptical anomalies not only aligns with common engineering geological appearances but also facilitates reasonable inferences about their potential spatial extent when only the frontal interface information is known.

[0026] However, the frontal interface response obtained from low-frequency RTM imaging typically does not strictly coincide with the actual frontal boundary of a large boulder. This is because low-frequency wavelengths are longer, and the imaging results are affected by finite bandgap effects, wavefield focusing width, and imaging kernel expansion, resulting in anomalies that often manifest as a relatively broad and gentle energy concentration band. This causes the low-frequency imaging response to spatially deviate from the actual frontal interface, exhibiting a certain degree of blurring. If this imaging response is directly treated as a rigid boundary and a closed model is constructed, it can easily lead to distortion in the estimation of the target's extent, thus misleading subsequent high-frequency imaging. To address this, this embodiment adopts a smooth, gradual characterization method with velocity increasing progressively from the boundary to the interior, rather than an abrupt, anomalous boundary representation. This method retains the stability advantage of low-frequency imaging in target localization while mitigating the adverse effects of imaging offset and boundary blurring on subsequent high-frequency imaging.

[0027] This embodiment combines the typical geometric features of a large boulder with low-frequency imaging results, employing an empirical extension strategy based on the front interface scale to construct an initial model. First, the spatial range of the front interface response of the large boulder is extracted using low-frequency RTM results, and this range is considered the main constraint of the known boundary of the target body. Then, based on the characteristic that large boulders are typically approximately closed in two-dimensional profiles and have similar front and rear scales, the rear interface is extended along the interior direction of the target body over a limited distance to construct the envelope region of the potential distribution of the anomalous body. Considering that the overall thickness of the large boulder is usually not much smaller than the lateral distribution range of its front interface, this embodiment sets the distance between the front and rear boundaries to approximately twice the length of the front interface, using this as the basis for determining the empirical location of the rear interface, thus obtaining a moderately enveloped potential anomalous body region under incomplete prior conditions. If the back interface is set too close, the initial model may not be able to effectively cover the real large boulder, and the high-frequency imaging will still be affected by the boundary truncation. If the back interface is set too far, the prior area will be too large, the constraint effect will be weakened, and too many background areas may be incorrectly included in the candidate range of the anomalous body. Taking 2 times as the extension range not only conforms to the typical near-circular or near-elliptical geometric features of the large boulder, but also can avoid the spatial range of the anomalous body being seriously overestimated while retaining the prior envelope capability.

[0028] S2. Initial model construction based on incomplete boundary prior constraints: This embodiment, based on obtaining partial boundary information of the anomalous body using low-frequency RTM results, constructs a priori envelope region to characterize the large boulder anomalous body, starting from the known partial boundaries. This envelope is divided into two parts: a transition region and an internal region, with different forms of smoothing constraints applied to each part. Finally, a numerical simulation example of large boulder detection is used to verify the effectiveness of the method in improving high-frequency RTM results.

[0029] The low-frequency primary reflection wave reverse time migration result essentially reflects the equivalent wavefield response band of the target body, rather than a precise geometric characterization of the true frontal interface of the boulder. The original low-frequency imaging result exhibits a concave curve characteristic towards the facet in its local morphology. This morphology is closer to the wavefield response distribution itself than fully corresponding to the true boundary of the target body. If this is directly used as the boundary of the anomalous body for initial model construction, the resulting prior region will be insufficient to fully represent the near-circular or elliptical geometric shape of the boulder itself. Therefore, this embodiment does not directly use the original response curve extracted by low-frequency RTM, but instead, while preserving its position and scale information, introduces the circular geometric prior of the boulder to regularize the expression of the original response boundary.

[0030] Specifically, the incomplete boundary extracted by low-frequency RTM is used as the initial constraint for constructing the prior envelope region. The known boundary is regarded as the starting surface of the geometric constraint of the anomaly, and it extends into the target body along the exploration direction, thereby forming a prior region to characterize the possible spatial range of the anomaly. Figure 2 As shown, the underground boulder anomaly is assumed to be... The low-frequency response interface in the red region was obtained through low-frequency RTM imaging results. The midpoint is denoted as By flipping it symmetrically, the leading edge of the prior envelope region can be obtained. The midpoint of this boundary is denoted as This boundary represents the equivalent leading-edge envelope obtained by incorporating the geometric priors of the target body. For large boulders that are nearly circular or nearly elliptical, the geometry of their leading interface in a two-dimensional cross-section typically exhibits a locally convex feature towards the facet. Therefore, this embodiment defines the regularized leading-edge envelope boundary. This is characterized as an arc-shaped boundary bulging towards the working face. This makes the initial model more consistent with the geometry of the large boulder target and provides a reasonable boundary basis for the subsequent closure of the envelope area. The exploration direction is defined as the direction perpendicular to the working face and pointing towards the interior of the area to be explored, i.e., the normal direction. Based on the known low-frequency response interface... Based on this, it is appropriately enlarged geometrically and extended along the exploration direction to establish an empirical boundary corresponding to the rear envelope of the target body. During the translation, the midpoint As a control reference point, its corresponding translated point is denoted as... Simultaneously, control the low-frequency response interface. and the boundary of experience The spacing between them is twice the length of the front interface, ensuring that the constructed prior region has a sufficient envelope. Then, the upper boundary, lower boundary, and connecting boundaries on both sides are closed together to form a region extending inward from the known partial boundaries. This region is defined as the prior envelope region (guiding the initial model).

[0031] In summary, the overall structure forms an asymmetrical, lenticular geometric framework that bulges in the middle and converges at both ends. Compared to the parallel boundaries obtained by simply translating the front interface, this construction method better conforms to the geometric characteristics of a large boulder that is locally closed and overall blunt and rounded.

[0032] It should be noted that in this embodiment, the distance of the rear boundary extension is set as the known low-frequency response interface. The empirical scale is twice that of the previous one, and it is designed to satisfy the a priori construction principle of adequate envelope and avoid missing envelope under incomplete boundary conditions. This parameter has achieved good results in subsequent numerical experiments.

[0033] like Figure 3 As shown, the prior envelope region is denoted as the internal region. The internal area The portion outside of this area is referred to as the outer region. Therefore, the entire detection domain It can be divided into three components: the background region outside the prior envelope (external region) A boundary transition region of a certain thickness constructed around the prior envelope boundary. and internal areas Compared with the traditional boundary and interior dichotomy, by dividing the region into background, transition zone and envelope regions, and constructing differentiated velocity model constraints for different regions, it is possible to avoid excessive disturbance to the propagation of high-frequency wave fields caused by abrupt velocity changes at the boundary, and to make use of incomplete boundary prior information.

[0034] Based on the aforementioned regional division, this embodiment describes the initial model construction process as a spatially constrained smooth optimization problem. Its objective is to ensure the stability of the model while enabling the velocity model to exhibit differentiated structural characteristics in different regions. The corresponding model (objective function) construction can be expressed as: ; in, This is the initial velocity model to be built; It is a geological background velocity model; It is a smoothness weighting function for spatial variations; This is the velocity gradient, used to control the smoothness of the model. The objective function aims to adjust the smoothness weights... It has the ability to control the speed changes in different regions, forming a rapid transition in the boundary transition region and a gradually enhanced anomalous structure within the prior envelope region.

[0035] First, in the outer area In this model, the medium mainly consists of formation media and densely distributed pebbles. The pebbles are not considered as target anomalies in this embodiment and are therefore not imaged or considered. The fluctuation characteristics of the formation medium are relatively stable. Therefore, the mesh in the outer region will be subject to uniform smooth constraints with reasonable weights; this is called the external constraint. In the outer region... In this context, assuming the medium is a stable background stratum, a strong smoothing constraint is applied, and the corresponding velocity model satisfies... This constraint ensures the stability of the wave field propagation path and avoids the introduction of spurious velocity disturbances in the external region. The background is the equivalent medium velocity field.

[0036] For the boundary transition region Since low-frequency primary reflection waves can stably characterize the approximate location of the front interface of an anomalous body, the boundary transition region... This should be considered the rapid transition zone where the velocity gradient change is most significant. Considering that real geological interfaces typically exhibit abrupt or strong gradient changes in velocity, this embodiment introduces a rapid velocity transition constraint in the front interface region, allowing the velocity to smoothly transition from the background value to the anomaly velocity. Rapid transition means that the normal smoothness factor changes from the background value... To minimum smoothness Rapidly decrease, and along the normal multi-layer mesh from minimum smoothness Quickly increase to maximum smoothness The boundary velocity is: ; in, The velocity difference between the anomalous body and the background medium; Here, we define a weighting function in the boundary region to control the spatial distribution of velocity changes. The weighting function is defined as follows: ; Simultaneously define a smoothness factor: ; in, The distance from the point to the known boundary; To achieve minimum smoothness, It represents maximum smoothness; The Gaussian kernel width controls the velocity amplitude of the anomaly. The attenuation; The exponential decay length controls the strength of the regularization constraint. The velocity gradient decays. This allows for a larger velocity gradient near the boundary, gradually restoring smoothness further away from the boundary. This process preserves the velocity contrast at the interface while avoiding numerical instability caused by overly sharp interfaces. This constraint also considers that the constructed virtual interior region covers the potential distribution range of the target volume.

[0037] For internal areas Since this area is considered the most likely spatial location for large boulders, a velocity structure distinctly different from the background medium needs to be introduced within it. However, considering the internal region... The candidate region is constructed based on incomplete boundary priors, rather than a precise recovery of the true boundary. If a constant value is directly assigned to the entire region, it can easily lead to an overly strong prior, which in turn inhibits the subsequent ability of high-frequency RTM to re-identify the true boundary. Therefore, this embodiment adopts a gradual velocity construction method, progressively increasing from the leading edge inwards and then gently releasing towards the trailing edge. Let... Point The normalized position coordinates along the exploration direction within the prior envelope area, with values ​​ranging from [0, 1], where... Corresponding leading edge envelope boundary , Corresponding trailing edge compensation boundary Then the velocity in the internal region can be written as: ; in, This is the internal gradual weighting function. To ensure that the velocity is stronger in the middle of the envelope and weaker near the two side boundaries, this embodiment uses: ; in, Shape parameters are used to control the degree of internal reinforcement. When When the weight is between 1 and 2, the weight function is smaller near the front and rear boundaries and reaches a higher value in the middle region, thus forming a center-enhanced velocity distribution that conforms to the characteristics of a large boulder-like body. Compared with constant assignment, this construction method can effectively enclose the main body region of the target body without producing excessively strong abrupt changes at the boundaries, which is more conducive to subsequent high-frequency RTM correction and focusing on the true boundary position. Correspondingly, the smoothing weights inside the envelope region should also show a trend of gradually releasing from the strong constraint at the leading edge towards the interior, and then gradually returning to the background constraint near the trailing edge.

[0038] This construction results in a gradual increase in velocity from the boundary to the interior within the prior envelope region, thus providing reasonable spatial constraints for the anomaly when the true boundary location is uncertain. By applying background constraints, transition constraints, and gradual anomaly constraints to the outer, boundary, and interior regions respectively, this paper constructs an initial velocity model for reverse-time migration imaging. This model inherits the constraint concept of incomplete boundary prior information and conforms to the physical laws of acoustic wave propagation and imaging, providing stable and geologically sound initial conditions for subsequent high-frequency acoustic wave fine imaging. S3. Typical numerical verification: To verify the effectiveness of the method in reverse time migration imaging of large boulders, two typical large boulder models with diameters of 1.2m and 3.0m were selected for numerical verification. Both models were set as a single high-speed boulder anomaly in a background of strong scattering by pebbles, with a background medium wave velocity of 1200m / s and a boulder wave velocity of 3500m / s. First, the front interface information of the anomaly was extracted using the reverse time migration results of low-frequency first reflected waves. Then, two types of high-frequency imaging initial models were constructed: a traditional high-frequency smoothed inverse propagation wave field initial model and an initial model for acoustic detection of boulder bodies in shield tunnels based on morphological constraints. Finally, the differences in high-frequency reverse time migration results under the two initial model conditions were compared, and the effect of incomplete boundary priors on improving the anomaly positioning accuracy and boundary recovery capability was analyzed.

[0039] For a large boulder model with a diameter of 1.2m, such as Figure 4 As shown, the target object is relatively small and is more susceptible to interference from scattered waves from surrounding small pebbles in a strong scattering background. The 300Hz low-frequency reverse time migration results are as follows... Figure 5 As shown, although low-frequency imaging struggles to recover the complete boundary of the target body, it does create a relatively stable local imaging response on the side of the anomalous body closer to the observation system. This response clearly indicates the approximate location of the target body's front interface, providing a basis for constructing boundary priors. Based on this, the following method is still used... Figure 6 The traditional high-frequency smoothed inverse propagation wavefield initial model shown fails to introduce geometric constraints related to the target's position in the region where the anomalous body is located, only providing an overall smooth propagation background. The 1000Hz imaging results obtained under these conditions are as follows: Figure 7 and Figure 8 As shown, although the anomalous body has been imaged to some extent, its energy is mainly concentrated in local areas, the boundary recovery is incomplete, and the imaging result is closer to an magnified local bright spot. The continuity and geometric shape of the front and back interfaces of the anomalous body are not clear enough, indicating that when relying solely on the smooth initial model, high-frequency imaging is more susceptible to the influence of the scattering background and will result in local imaging instability.

[0040] In contrast, constructing a front interface information extracted using low-frequency imaging, such as Figure 9 After the initial model with incomplete boundary prior constraints is shown, a fan-shaped, gradually changing prior region extending inward along the exploration direction forms in front of the anomaly, which conforms to the wave propagation characteristics. Although the model does not directly give the complete boundary of the target body, by introducing gradually increasing velocity constraints within the region where the anomaly may exist, the high-frequency reverse-time migration wavefield has a clearer propagation background and a more reasonable energy focusing direction within this region. The 1000Hz imaging results obtained under these conditions are as follows... Figure 10 and Figure 11 As shown, the local energy focusing degree is significantly enhanced, and the imaging results are better than those shown. Figure 7The results are more concentrated and the front interface position is more clearly defined, indicating that incomplete boundary priors can improve the stability of high-frequency imaging and the ability to locate anomalies under small-scale target conditions. For a target of 1.2m in size, since the target size is close to the lower limit of high-frequency resolution, its complete boundary is still difficult to fully recover, but the prior constraint has significantly improved the focusing effect of the anomaly and the front interface recognition effect.

[0041] For example Figure 12 The large boulder model shown has a diameter of 3.0m, and the 300Hz imaging result is as follows. Figure 13 As shown, low-frequency RTM can reconstruct the anomaly's front interface relatively stably and reflect the large spatial scale of the target body, providing a reliable prior boundary for subsequent initial model construction. When using... Figure 14 The imaging results at 1000Hz are shown in the traditional high-frequency smoothed inverse propagation wavefield initial model. Figure 15 and 16 As shown, a strong anomalous response appears in the high-frequency results, but the imaging position of the anomalous body is offset relative to the real model. The recovered interface does not completely correspond to the real boundary of the target body, manifesting as a spatial shift of the anomalous response accompanied by morphological distortion. This indicates that for large-scale anomalous bodies, if the high-frequency reverse-time migration lacks prior constraints related to the geometric position of the target body, even with high-resolution high-frequency migration, misjudgment of the anomalous body's position may occur due to inaccurate wavefield propagation paths and focusing positions.

[0042] After introducing incomplete boundary prior constraints, the initial model constructed is as follows: Figure 17 As shown. Compared to the 1.2m model, due to the larger frontal interface scale of the 3.0m target, the coverage area of ​​the fan-shaped gradient region formed by the prior model is correspondingly expanded, thus more fully encompassing the potential distribution area of ​​the target. The 1000Hz imaging results obtained under the guidance of this model are shown below. Figure 18 and Figure 19 As shown, the imaging position of the anomaly is more consistent with the real model, the positional relationship between the front and back interfaces is more reasonable, and the overall shape of the front and back interfaces basically matches the boundary of the real boulder. Figure 15 In comparison, high-frequency imaging under incomplete boundary prior constraints effectively suppresses the imaging migration problem of anomalous bodies and improves the geometric accuracy and boundary recovery capability of high-frequency reverse-time migration results. This indicates that when the target body is large in scale and its front interface can be stably indicated at low frequencies, the gradual initial model constructed by the incomplete boundary prior can more effectively transfer low-frequency boundary information to the high-frequency imaging process, thereby achieving progressive imaging from "low-frequency shaping" to "high-frequency edge lifting".

[0043] Example 2: This embodiment provides a morphological and structural constraint-based acoustic detection system for boulder bodies in shield tunnels, including: The initial constraint determination module is configured to: obtain the incomplete boundary of the boulder determined by the low-frequency reverse time offset as the initial constraint; The prior area determination module is configured to: based on the initial constraints, treat the boundary as the starting surface of the boulder geometric constraints, extend it along the exploration direction into the interior of the boulder, and determine the prior area that characterizes the spatial extent of the boulder. The leading edge envelope boundary determination module is configured to: treat the large boulder as nearly circular; based on the prior region, flip the low-frequency response interface in the low-frequency reverse time offset to determine the leading edge envelope boundary with local outward convexity towards the working face. The empirical boundary determination module is configured to: in the exploration direction, using the low-frequency response interface as a reference, enlarge the low-frequency response interface on a geometric scale to determine the empirical boundary corresponding to the back envelope of the boulder. The model building module is configured to use a smooth gradient representation method that gradually increases the velocity from the boundary to the interior to close the leading edge envelope boundary and the empirical boundary to obtain the prior envelope region.

[0044] The working method of the system is the same as that of the acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints in Example 1, and will not be repeated here.

[0045] Example 3: This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in Embodiment 1.

[0046] Example 4: This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the program, it implements the steps of the acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints described in Embodiment 1.

[0047] Example 5: This embodiment provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in Embodiment 1.

[0048] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. A method for acoustic detection of boulder bodies in shield tunnels based on morphological and structural constraints, characterized in that, include: The incomplete boundary of the boulder determined by the low-frequency reverse time offset is used as the initial constraint; Based on the initial constraints, the boundary is regarded as the starting surface of the boulder's geometric constraints, and it is extended into the interior of the boulder along the exploration direction to determine the a priori region that characterizes the spatial extent of the boulder. The large boulder is considered to be nearly circular; based on the prior region, the low-frequency response interface in the low-frequency reverse time migration is flipped to determine the leading edge envelope boundary with local outward convexity towards the working face. In the exploration direction, the low-frequency response interface is used as a benchmark. The low-frequency response interface is enlarged on a geometric scale to determine the empirical boundary corresponding to the back envelope of the boulder. A smooth gradient representation method is adopted, in which the velocity gradually increases from the boundary to the interior, to close the leading edge envelope boundary and the empirical boundary to obtain the prior envelope region.

2. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 1, characterized in that, The determination of the empirical boundary includes: defining the exploration direction as a direction perpendicular to the working face and pointing into the area to be explored; using the low-frequency response interface as a reference, enlarging the low-frequency response interface on a geometric scale and extending it along the exploration direction to establish an empirical boundary corresponding to the rear envelope of the target body; during the translation process, the midpoint is used as a control reference point.

3. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 2, characterized in that, The spacing between the control low-frequency response interface and the empirical boundary is twice the length of the front interface.

4. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 1, characterized in that, The prior envelope region is labeled as the inner region, and the portion outside the inner region is denoted as the outer region. A boundary transition region of preset thickness is constructed around the boundary of the prior envelope. By adjusting the smoothness weights, the velocity variation capability of different regions is controlled, resulting in a smooth gradient where the velocity gradually increases from the boundary to the interior. The objective function of the model construction is: ； in, This is the initial velocity model to be built; It is a geological background velocity model; It is the smoothness weighting function for spatial variations; It is the velocity gradient; For the entire detection range.

5. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 4, characterized in that, The initial velocity model in the outer region is the background equivalent medium velocity field; the boundary transition region introduces a rapid velocity transition constraint in the front interface region, so that the velocity smoothly transitions from the background value to the anomaly velocity, the normal smoothness factor rapidly decreases from the background value to the minimum smoothness, and rapidly increases from the minimum smoothness to the maximum smoothness along the normal multi-layer mesh.

6. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 5, characterized in that, The boundary velocity of the boundary transition region is: ； ； ； in, The background is the equivalent medium velocity field; The velocity difference between the anomalous body and the background medium; The weight function is defined in the boundary region; The distance from the point to the known boundary; To achieve minimum smoothness, It represents maximum smoothness; The width of the Gaussian kernel; The length is the exponentially decaying length.

7. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 4, characterized in that, The internal region adopts a gradual velocity construction method that increases gradually from the leading edge inward and then releases gently towards the trailing edge.

8. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 4, characterized in that, set up Point Normalized position coordinates along the exploration direction within the prior envelope, and the internal velocity: ； ； in, This is the internal gradient weight function; Shape parameters used to control the degree of internal reinforcement.

9. The acoustic wave detection method for boulder bodies in shield tunnels based on morphological constraints as described in claim 1, characterized in that, Numerical verification was carried out using two sets of boulder models with different diameters. Both models were set as a single boulder anomaly in a background of strong scattering by pebbles. First, the front interface information of the anomaly was extracted using the reverse time migration results of low-frequency primary reflection waves. Then, a traditional high-frequency smoothed inverse propagation wave field initial model and an initial model based on local outward convexity features were constructed respectively. Finally, the differences in high-frequency reverse time migration results under the two initial model conditions were compared.

10. A morphological and structural constraint-based acoustic detection system for boulder bodies in shield tunnels, characterized in that, include: The initial constraint determination module is configured to: obtain the incomplete boundary of the boulder determined by the low-frequency reverse time offset as the initial constraint; The prior area determination module is configured to: based on the initial constraints, treat the boundary as the starting surface of the boulder geometric constraints, extend it along the exploration direction into the interior of the boulder, and determine the prior area that characterizes the spatial extent of the boulder. The leading edge envelope boundary determination module is configured to: treat the large boulder as nearly circular; based on the prior region, flip the low-frequency response interface in the low-frequency reverse time offset to determine the leading edge envelope boundary with local outward convexity towards the working face. The empirical boundary determination module is configured to: in the exploration direction, using the low-frequency response interface as a reference, enlarge the low-frequency response interface on a geometric scale to determine the empirical boundary corresponding to the back envelope of the boulder. The model building module is configured to use a smooth gradient representation method that gradually increases the velocity from the boundary to the interior to close the leading edge envelope boundary and the empirical boundary to obtain the prior envelope region.

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