A method, device and equipment for imaging obstacles in a tunnel construction area
By adaptively optimizing the modal decomposition and reconstruction of seismic exploration data, the problem of inaccurate obstacle imaging during shield tunneling was solved, achieving high-precision obstacle imaging and ensuring construction safety.
Patent Information
- Application Number
- CN202610630538.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-09
- Publication Date
- 2026-07-10
Smart Images
Figure CN122362486A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of geological exploration technology for tunnel boring machine (TBM) construction, and more specifically, to an imaging method, apparatus, and equipment for obstacles in the TBM construction area. Background Technology
[0002] Shield tunneling is widely used in projects such as subways, urban expressways, integrated utility tunnels, and river and sea crossings. During shield tunneling, obstacles such as boulders, old piles, unexplored underground structures, karst caves, and abrupt changes in hardness often exist in the strata ahead, which can easily lead to risks such as cutterhead jamming, abnormal cutter wear, surface subsidence, and sudden water and mud inrushes.
[0003] During shield tunneling, accurate detection of underground obstacles (such as boulders, karst caves, and fracture zones) is a crucial aspect of ensuring construction safety. Currently, the imaging process of obstacles in the shield tunneling area lacks an adaptive optimization method for the number of modes, making it difficult to match the processing requirements of seismic detection data. This can easily lead to poor diffraction wave field reconstruction results, ultimately resulting in insufficient accuracy of the imaging results of obstacles in the shield tunneling area, failing to accurately reflect the actual situation of the obstacles. Summary of the Invention
[0004] The purpose of this application is to provide an imaging method, device, and equipment for obstacles in a shield tunneling area, which solves the above-mentioned problems existing in the prior art and can improve the detection accuracy and stability of obstacles in front of the shield tunneling area.
[0005] Firstly, a method for imaging obstacles in a shield tunneling construction area is provided, the method including: Obtain seismic detection data of the target shield tunneling area; Based on the initial number of modes obtained from the configuration, geometric mode decomposition is performed on the seismic detection data to obtain multiple initial mode components; wherein, the initial mode components include: initial diffraction components; Calculate the overall score for each initial modal component; Calculate the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score; Based on the fitness value corresponding to the initial number of modes, the initial number of modes is adaptively optimized within the configured mode search interval to obtain the optimal number of modes; If the initial number of modes is the optimal number of modes, then the initial diffraction components are reconstructed to obtain the diffraction wave field; The diffracted wave field is subjected to offset imaging to obtain the imaging results of obstacles in the target shield construction area.
[0006] In an optional implementation, the calculation of the overall score for each initial modal component includes: For any initial mode component, the initial mode component is transformed to the frequency domain through Fourier transform to obtain the two-dimensional Fourier spectrum of the initial mode component; Based on the two-dimensional Fourier spectrum of the initial modal components, calculate the frequency domain directivity coefficient and energy percentage of the initial modal components; The initial modal components are smoothed along the survey line direction in the spatial domain to obtain smoothed initial modal components; Based on the initial modal components and the smoothed initial modal components, the spatial coherence coefficient corresponding to the initial modal components is calculated; The comprehensive score of the initial modal components is calculated based on the frequency domain directivity coefficient, the energy percentage, and the spatial coherence coefficient.
[0007] In an optional implementation, calculating the frequency domain directivity coefficients of the initial mode components based on their two-dimensional Fourier spectra includes: The two-dimensional Fourier spectrum of the initial modal components is divided into multiple sector regions according to the polar angle; Calculate the energy of the spectrum in each sector region of the two-dimensional Fourier frequency spectrum to obtain the energy of each sector region; The frequency domain directivity coefficients of the initial modal components are calculated based on the energy of each sector region.
[0008] In an optional implementation, the energy percentage of the initial modal component is calculated based on the two-dimensional Fourier spectrum of the initial modal component, including: Calculate the energy percentage of the initial modal component based on the two-dimensional Fourier spectrum of the initial modal component; The energy of the initial modal components is normalized to obtain the energy percentage of the initial modal components.
[0009] In an optional implementation, calculating the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score includes: The initial modal component whose overall score is greater than the configured preset threshold is identified as the initial reflection component; The initial modal component whose overall score is not greater than the configured preset threshold is determined as the initial diffraction component; Calculate the diffraction wave energy ratio, modal energy entropy, and modal orthogonality coefficient of the initial number of modes; Based on the diffraction wave energy ratio, the modal energy entropy, and the modal orthogonality coefficient, the fitness value corresponding to the initial number of modes is determined.
[0010] In an optional implementation, based on the fitness value corresponding to the initial number of modes, the initial number of modes is adaptively optimized within a configured mode search interval to obtain the optimal number of modes, including: An improved sparrow search algorithm is adopted, which selects the optimal number of modes within the configured mode search interval based on the fitness value corresponding to the initial number of modes and with the goal of minimizing the fitness value.
[0011] In an optional implementation, the method further includes: If the initial number of modes is not the optimal number of modes, then the seismic detection data is subjected to geometric mode decomposition based on the optimal number of modes to obtain the target diffraction components; The diffraction components of the target are reconstructed to obtain the diffraction wave field; The diffracted wave field is subjected to offset imaging to obtain the imaging results of obstacles in the target shield construction area.
[0012] Secondly, an imaging device for obstacles in a tunnel boring machine (TBM) construction area is provided, the device comprising: The acquisition unit is used to acquire seismic detection data of the target shield tunneling area; The decomposition unit is used to perform geometric mode decomposition on the seismic exploration data according to the initial number of modes obtained from the configuration, to obtain multiple initial mode components; wherein, the initial mode components include: initial diffraction components; The first calculation unit is used to calculate the comprehensive score of each initial modal component; The second calculation unit is used to calculate the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score; The optimization unit is used to adaptively optimize the initial number of modes within a configured mode search interval based on the fitness value corresponding to the initial number of modes, so as to obtain the optimal number of modes. A reconstruction unit is used to reconstruct the initial diffraction components to obtain a diffraction wave field if the initial number of modes is the optimal number of modes. An imaging unit is used to perform offset imaging on the diffracted wave field to obtain imaging results of obstacles in the target shield construction area.
[0013] Thirdly, an electronic device is provided, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in memory, it implements any of the steps described in the first aspect above.
[0014] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of any of the methods described in the first aspect above.
[0015] This application obtains initial modal components by performing geometric mode decomposition on seismic exploration data. After comprehensive scoring and fitness value calculation, it adaptively optimizes the number of modes within the mode search interval to obtain the optimal number of modes. Then, based on the optimal number of modes, it reconstructs the diffraction wave field and completes migration imaging. This achieves adaptive optimization of the number of modes, enabling high-quality diffraction wave field reconstruction based on the optimal number of modes. It effectively improves the accuracy of obstacle imaging results in the shield tunneling area, accurately presents the actual condition of obstacles in the target area, and provides a reliable basis for relevant decisions in shield tunneling construction. Attached Figure Description
[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 An architecture diagram of an imaging system for obstacles in a tunnel boring machine (TBM) construction area is provided in this application embodiment. Figure 2 A schematic flowchart illustrating an imaging method for obstacles in a tunnel boring machine (TBM) construction area, provided as an embodiment of this application. Figure 3 A schematic diagram of the structure of an imaging device for obstacles in a shield tunneling area provided in this application embodiment; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise defined, the technical or scientific terms used in this application should have the ordinary meaning understood by those skilled in the art. The words "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are only used to distinguish different components. The words "comprising" or "including," etc., mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but do not exclude other elements or objects. The words "connected," "coupled," or "connected," etc., are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.
[0019] The imaging method for obstacles in the shield tunneling area provided in this application embodiment can be applied to... Figure 1 In the system architecture shown, such as Figure 1 As shown, the system may include: a server and a seismic wave detection device; the seismic wave detection device is used to collect seismic detection data of the target shield tunneling construction area; the server is used to perform the imaging of obstacles in the shield tunneling construction area provided in this embodiment; the server may be a physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.
[0020] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments and features in the embodiments of this application can be combined with each other without conflict.
[0021] Figure 2 This is a schematic flowchart illustrating an imaging method for obstacles in a tunnel boring machine (TBM) construction area, as provided in an embodiment of this application. Figure 2 As shown, the method may include: Step S210: Obtain seismic detection data of the target shield tunneling area.
[0022] In practice, seismic detection equipment is used to collect seismic detection data of the target shield tunneling area; the seismic detection data can be post-stack profiles or common offset gathers.
[0023] Step S220: Based on the configuration, obtain the initial number of modes, perform geometric mode decomposition on the seismic exploration data, and obtain multiple initial mode components.
[0024] The initial modal components include: the initial diffraction component and the initial reflection component.
[0025] In practice, based on the initial number of modes obtained from the configuration, geometric mode decomposition (GMD) is performed on the seismic exploration data to obtain multiple initial mode components.
[0026] Step S230: Calculate the comprehensive score of each initial modal component.
[0027] In practice For any initial mode component, it is transformed to the frequency domain using a Fourier transform to obtain its two-dimensional Fourier spectrum. This spectrum is then divided into multiple sector regions based on polar angles. Each sector region corresponds to a set of wavefield components with similar tilt angles or slopes. The energy of the spectrum within each sector region in the two-dimensional Fourier transform is calculated to obtain the energy of each sector region. Based on the energy of each sector region, the frequency domain directivity coefficient of the initial mode component is calculated. ;in, The frequency domain directivity coefficient represents the k-th initial mode component. The larger the frequency domain directivity coefficient, the more concentrated the energy is in a certain direction, and the more it conforms to the quasi-linear characteristics of continuous reflection. The smaller the frequency domain directivity coefficient, the more dispersed the energy of the corresponding initial mode is, and the more it conforms to the diffraction characteristics. The k-th initial modal component represents the first... The energy of each sector; S represents the number of sector regions in the initial modal components; The initial modal components are smoothed along the survey line in the spatial domain to obtain smoothed initial modal components. Based on the initial modal components and the smoothed initial modal components, the spatial coherence coefficients corresponding to the initial modal components are calculated. ;in, This represents the spatial coherence coefficient of the k-th initial modal component; It represents a very small constant to avoid a denominator of 0; This represents the k-th smoothed initial modal component; This represents the k-th initial mode component. The larger the spatial coherence coefficient, the smaller the energy loss of the corresponding initial mode component after lateral smoothing. It is relatively flat, has good linear characteristics, and is closer to the reflection mode. The smaller the spatial coherence coefficient, the more dispersed the energy of the corresponding initial mode, the worse the linear characteristics, and the closer it is to the diffraction mode. The energy of the initial modal components is calculated based on the two-dimensional Fourier spectrum of the initial modal components; where, , , The energy of the k-th initial mode component is represented; the energy of the initial mode component is normalized to obtain the energy ratio of the initial mode component; K represents the number of initial modes configured; the energy of the reflected wave mode is often much stronger than that of the diffracted wave mode, so the mode energy ratio is used to help distinguish between the reflected mode and the diffracted mode; The comprehensive score of the initial modal components is calculated based on the frequency domain directivity coefficient, energy proportion, and spatial coherence coefficient; among which, , ;in, , and These are the weights corresponding to the frequency domain directivity coefficient, energy proportion, and spatial coherence coefficient, respectively. Since reflected waves usually have the characteristics of concentrated energy, strong directionality, and good spatial continuity, while diffracted waves exhibit a more uniform energy distribution and are more spatially dispersed.
[0028] Step S240: Calculate the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score.
[0029] In practice, the initial modal component whose comprehensive score is greater than the configured preset threshold is determined as the initial reflection component; the initial modal component whose comprehensive score is not greater than the configured preset threshold is determined as the initial diffraction component. Calculate the diffraction wave energy ratio, modal energy entropy, and modal orthogonality coefficient corresponding to the initial number of modes; where the diffraction wave energy ratio... The calculation formula is: ; This represents the m-th initial diffraction component; This represents the initial set of diffraction components; the formula for calculating modal energy entropy is: ;in, , ; This represents the energy percentage of the k-th initial mode component; ; This represents the total energy of all initial modal components; The initial modal components are subjected to mean removal and normalization, and flattened into unit norm vectors. The preprocessed modal components corresponding to each initial modal component are obtained; the preprocessed modal components are concatenated column by column to obtain the modal matrix. The correlation coefficient matrix is obtained by performing a fine-grained correlation matrix calculation on the mode matrix. ; where the elements in the correlation coefficient matrix , Let represent the correlation coefficient between the i-th initial modal component and the j-th initial modal classification; extract all off-diagonal elements from the correlation coefficient matrix and calculate the modal orthogonality coefficient; the formula for calculating the modal orthogonality coefficient is: ; Substituting the diffraction wave energy proportion, modal energy entropy, and modal orthogonality coefficients into the pre-constructed fitness function yields the fitness value. The fitness function is constructed based on the diffraction wave energy proportion, modal energy entropy, and modal orthogonality coefficients. The fitness function can be: ;in, The weighting coefficients for the diffraction wave energy proportion, modal energy entropy, and modal orthogonality coefficient are respectively, and can all be 1 / 3.
[0030] In practical applications, from a geophysical perspective, the energy of diffracted waves in real seismic records is usually smaller than that of reflected waves, and their spatial coherence is weaker. Therefore, under reasonable decomposition results, the energy proportion carried by diffracted modes should be kept at a low level. When the number of modes... When the initial mode division is too small or coarse, some high-tilt or locally weakly correlated reflection components are difficult to include in the reflection mode set. In order to be fully characterized, they are often squeezed into the set of diffraction modes. This increases the proportion of diffraction energy. To avoid this phenomenon, this application explicitly constrains the proportion of diffraction wave energy in the fitness function, guiding ISSA to adjust... Its corresponding mode division allows the reflected energy aliased into the diffraction mode to gradually return. Therefore, the proportion of diffracted wave energy can be regarded as a measure of the current parameters. A key indicator of whether the division is reasonable is that its stable decrease means that the physical separation of reflection and diffraction in the modal space is gradually improving; The physical characteristics of seismic data indicate that most high-energy, highly coherent reflected waves are concentrated in a few modes, while low-energy, less correlated diffracted waves are mainly distributed in the remaining modes. This corresponds to the energy proportion of each mode. Ideally, the energy proportion of a few modes is significantly larger, while the energy proportion of the remaining modes exhibits a rapidly decreasing distribution pattern. In this case, the normalized energy entropy... It tends to 0. Conversely, if the energy entropy... If the fitness function approaches 1, it indicates that the GMDF algorithm decomposes the overall wavefield into a large number of similar modes, and the reflected wave and diffracted wave information are highly coupled in the mode space. Based on the above analysis, this application uses a fitness function with a larger... This is penalized. Furthermore, it guides the ISSA algorithm during optimization, concentrating strong energy and strongly correlated information in a small number of modes, while concentrating weak energy and weakly correlated information in the remaining large number of modes. This provides a clear energy structure basis for the identification of reflection and diffraction modes. In summary, penalizing these modes in the fitness function avoids the generation of redundant modes and guides the ISSA algorithm to perform optimization effectively. During the optimization process, a modal basis with low correlation was obtained, which provides a clearer physical representation for subsequent reflection and diffraction wave mode identification.
[0031] Step S250: Based on the fitness value corresponding to the initial number of modes, adaptively optimize the initial number of modes within the configured mode search interval to obtain the optimal number of modes.
[0032] In practice, the Improved Sparrow Search Algorithm (ISSA) is used within the configured modal search interval. The solution is performed internally, that is, the optimal number of modes is adaptively obtained with the goal of minimizing the fitness value. ; ; through the By taking the minimum value, an effective balance is achieved among the three types of seismic wavefield physical properties: the proportion of diffraction wave energy, the distribution of modal energy, and the correlation between modes. This yields modal components that can accurately characterize the physical features of different wavefields in seismic data, providing a stable and interpretable decomposition basis for subsequent identification of reflected and diffracted wave modes.
[0033] Step S260: If the initial number of modes is the optimal number of modes, then the initial diffraction components are reconstructed to obtain the diffraction wave field.
[0034] In another embodiment of this application, if the initial number of modes is not the optimal number of modes, then the seismic detection data is subjected to geometric mode decomposition based on the optimal number of modes to obtain the target diffraction component; the target diffraction component is reconstructed to obtain the diffraction wave field; and the diffraction wave field is subjected to migration imaging to obtain the imaging result of the obstacle in the target shield construction area.
[0035] In another embodiment of this application, the diffraction components of the target are reconstructed to obtain a diffraction wave field; the diffraction wave field is then used for offset imaging to obtain an imaging result of obstacles in the target shield tunneling area, which may include: The diffraction components of the target are spatiotemporally mapped and superimposed to reconstruct a diffraction wavefield containing only the characteristics of the diffraction wave. Based on a pre-constructed ground velocity model, the diffraction wavefield is subjected to wavefield extension and migration imaging processing to focus the diffraction wave energy to the actual underground scattering point location, generating the imaging result of obstacles in the target shield tunneling area. Specifically, based on the configured ground velocity model, the diffraction wavefield is extended to obtain an underground extended wavefield to simulate the propagation path of the diffraction wave in the underground medium. Using the configured imaging conditions, the underground extended wavefield is superimposed and focused, retaining only the superposition result of the diffraction wave energy at the scattering point location, that is, focusing the energy of the diffraction wave to the actual underground scattering point location, obtaining underground scattering point imaging data. The wavefield energy is mapped to pixel values in the spatial domain to generate two-dimensional or three-dimensional imaging profiles. The underground scattering point imaging data is subjected to coordinate alignment, normalization, noise suppression, and anomaly enhancement processing, and then mapped to a visualization image to obtain the imaging result of obstacles in the target shield tunneling area.
[0036] Step S270: Perform offset imaging on the diffracted wave field to obtain the imaging results of obstacles in the target shield construction area.
[0037] In practice, the Kirchhoff migration algorithm is used to perform migration imaging with diffracted wave fields, thereby obtaining accurate imaging results of small-scale discontinuous geological bodies in front of the target shield tunneling area.
[0038] This application first establishes the physical differences between diffracted and reflected waves in the common offset domain. Then, it optimizes the fitness function using an improved Sparrow Search Algorithm (ISSA) to adaptively determine the optimal number of modes within a given interval, thereby performing modal decomposition on the original seismic data. Next, it constructs a modal scoring system using frequency domain directivity, spatial coherence, and energy contribution as quantitative indicators to achieve high-quality separation of the diffracted wave field, providing reliable suggestions for the effective identification and accurate positioning of small-scale obstacles ahead during shield tunneling.
[0039] This application constructs a fitness function that includes wavefield theoretical property constraints such as diffraction energy proportion, modal energy entropy, and modal orthogonality, and introduces an improved sparrow search algorithm (ISSA) to adaptively determine the optimal number of modes within a given interval; under the optimal number of modes, geometric mode decomposition is performed on the seismic data to obtain a mode set; further, the modes are quantitatively calculated and classified from indicators such as frequency domain directivity, spatial coherence, and energy contribution, and the diffracted wavefield is reconstructed; Kirchhoff migration imaging is performed on the separated diffracted wavefield.
[0040] This application improves the resolution and positioning accuracy of small-scale obstacles such as boulders, old piles, cavities, and soft-hard aberrations during tunnel boring machine (TBM) excavation, providing a reliable basis for TBM parameter optimization, early warning, and risk management. Using diffraction waves from tunnel pre-exploration seismic data as target information, this application leverages the high response characteristics of diffraction waves to small-scale discontinuity boundaries. A high-fidelity extraction of diffraction waves is achieved through an integrated process of adaptive mode number optimization, geometric mode decomposition, and modal comprehensive evaluation. Combined with migration imaging, this enables precise positioning of small-scale obstacles. This application effectively suppresses strong reflected wave interference in the data, improves diffraction wave separation accuracy, and enhances the ability to identify small-scale obstacles in front of the TBM. It is applicable to TBM construction scenarios such as subways, tunnels, and integrated utility tunnels.
[0041] Corresponding to the above method, this application also provides an imaging device for obstacles in the shield tunneling area, such as... Figure 3 As shown, the device includes: Acquisition unit 310 is used to acquire seismic detection data of the target shield tunneling construction area; The decomposition unit 320 is used to obtain the number of initial modes according to the configuration, and to perform geometric mode decomposition on the seismic exploration data to obtain multiple initial mode components; wherein, the initial mode components include: initial diffraction components; The first calculation unit 330 is used to calculate the comprehensive score of each initial modal component; The second calculation unit 340 is used to calculate the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score; The optimization unit 350 is used to adaptively optimize the initial number of modes within a configured mode search interval based on the fitness value corresponding to the initial number of modes, so as to obtain the optimal number of modes. The reconstruction unit 360 is used to reconstruct the initial diffraction components to obtain the diffraction wave field if the initial number of modes is the optimal number of modes. Imaging unit 370 is used to perform offset imaging of the diffracted wave field to obtain the imaging results of obstacles in the target shield construction area.
[0042] The functions of each functional unit of the imaging device for obstacles in the shield tunneling area provided in the above embodiments of this application can be realized through the above-described methods and steps. Therefore, the specific working process and beneficial effects of each unit in the imaging device for obstacles in the shield tunneling area provided in the embodiments of this application will not be repeated here.
[0043] This application also provides an electronic device, such as... Figure 4As shown, it includes a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440.
[0044] Memory 430 is used to store computer programs; When the processor 410 executes the program stored in the memory 430, it performs the following steps: Obtain seismic detection data of the target shield tunneling area; Based on the initial number of modes obtained from the configuration, geometric mode decomposition is performed on the seismic exploration data to obtain multiple initial mode components; among them, the initial mode components include: initial diffraction components; Calculate the overall score for each initial modal component; Calculate the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score; Based on the fitness value corresponding to the initial number of modes, the initial number of modes is adaptively optimized within the configured mode search interval to obtain the optimal number of modes; If the initial number of modes is the optimal number of modes, then the initial diffraction components are reconstructed to obtain the diffraction wave field; By performing offset imaging on the diffracted wave field, the imaging results of obstacles in the target shield tunneling area are obtained.
[0045] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.
[0046] The communication interface is used for communication between the aforementioned electronic devices and other devices.
[0047] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.
[0048] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.
[0049] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments for solving the problem can be found in [reference needed]. Figure 2 The steps in the illustrated embodiments are used to implement the electronic device. Therefore, the specific working process and beneficial effects of the electronic device provided in this application will not be repeated here.
[0050] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform the imaging method for obstacles in the shield tunneling area described in any of the above embodiments.
[0051] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the imaging method for obstacles in the shield tunneling area described in any of the above embodiments.
[0052] Those skilled in the art will understand that the embodiments in this application can be provided as methods, systems, or computer program products. Therefore, the embodiments in this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments in this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0053] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0054] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0055] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0056] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.
[0057] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of this application and its equivalents, then these modifications and variations are also intended to be included in the embodiments of this application.
Claims
1. A method for imaging obstacles in a shield tunneling construction area, characterized in that, The method includes: Obtain seismic detection data of the target shield tunneling area; Based on the initial number of modes obtained from the configuration, geometric mode decomposition is performed on the seismic detection data to obtain multiple initial mode components; wherein, the initial mode components include: initial diffraction components; Calculate the overall score for each initial modal component; Calculate the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score; Based on the fitness value corresponding to the initial number of modes, the initial number of modes is adaptively optimized within the configured mode search interval to obtain the optimal number of modes; If the initial number of modes is the optimal number of modes, then the initial diffraction components are reconstructed to obtain the diffraction wave field; The diffracted wave field is subjected to offset imaging to obtain the imaging results of obstacles in the target shield construction area.
2. The method as described in claim 1, characterized in that, The calculation of the comprehensive score for each initial modal component includes: For any initial mode component, the initial mode component is transformed to the frequency domain through Fourier transform to obtain the two-dimensional Fourier spectrum of the initial mode component; Based on the two-dimensional Fourier spectrum of the initial modal components, calculate the frequency domain directivity coefficient and energy percentage of the initial modal components; The initial modal components are smoothed along the survey line direction in the spatial domain to obtain smoothed initial modal components; Based on the initial modal components and the smoothed initial modal components, the spatial coherence coefficient corresponding to the initial modal components is calculated; The comprehensive score of the initial modal components is calculated based on the frequency domain directivity coefficient, the energy percentage, and the spatial coherence coefficient.
3. The method as described in claim 2, characterized in that, The step of calculating the frequency domain directivity coefficient of the initial mode component based on the two-dimensional Fourier spectrum of the initial mode component includes: The two-dimensional Fourier spectrum of the initial modal components is divided into multiple sector regions according to the polar angle; Calculate the energy of the spectrum in each sector region of the two-dimensional Fourier frequency spectrum to obtain the energy of each sector region; The frequency domain directivity coefficients of the initial modal components are calculated based on the energy of each sector region.
4. The method as described in claim 2, characterized in that, Based on the two-dimensional Fourier spectrum of the initial modal components, the energy percentage of the initial modal components is calculated, including: Calculate the energy percentage of the initial modal component based on the two-dimensional Fourier spectrum of the initial modal component; The energy of the initial modal components is normalized to obtain the energy percentage of the initial modal components.
5. The method as described in claim 1, characterized in that, The step of calculating the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score includes: The initial modal component whose overall score is greater than the configured preset threshold is identified as the initial reflection component; The initial modal component whose overall score is not greater than the configured preset threshold is determined as the initial diffraction component; Calculate the diffraction wave energy ratio, modal energy entropy, and modal orthogonality coefficient of the initial number of modes; Based on the diffraction wave energy ratio, the modal energy entropy, and the modal orthogonality coefficient, the fitness value corresponding to the initial number of modes is determined.
6. The method as described in claim 1, characterized in that, Based on the fitness value corresponding to the initial number of modes, the initial number of modes is adaptively optimized within the configured mode search interval to obtain the optimal number of modes, including: An improved sparrow search algorithm is adopted, which selects the optimal number of modes within the configured mode search interval based on the fitness value corresponding to the initial number of modes and with the goal of minimizing the fitness value.
7. The method as described in claim 1, characterized in that, The method further includes: If the initial number of modes is not the optimal number of modes, then the seismic detection data is subjected to geometric mode decomposition based on the optimal number of modes to obtain the target diffraction components; The diffraction components of the target are reconstructed to obtain the diffraction wave field; The diffracted wave field is subjected to offset imaging to obtain the imaging results of obstacles in the target shield construction area.
8. An imaging device for obstacles in a shield tunneling area, characterized in that, The device includes: The acquisition unit is used to acquire seismic detection data of the target shield tunneling area; The decomposition unit is used to perform geometric mode decomposition on the seismic exploration data according to the initial number of modes obtained from the configuration, to obtain multiple initial mode components; wherein, the initial mode components include: initial diffraction components; The first calculation unit is used to calculate the comprehensive score of each initial modal component; The second calculation unit is used to calculate the fitness value corresponding to the number of initial modes based on each initial modal component and the corresponding comprehensive score; The optimization unit is used to adaptively optimize the initial number of modes within a configured mode search interval based on the fitness value corresponding to the initial number of modes, so as to obtain the optimal number of modes. A reconstruction unit is used to reconstruct the initial diffraction components to obtain a diffraction wave field if the initial number of modes is the optimal number of modes. An imaging unit is used to perform offset imaging on the diffracted wave field to obtain imaging results of obstacles in the target shield construction area.
9. An electronic device, characterized in that, The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.