Underground pipeline detection method, system, device and medium based on phase shift method

Abstract

The application relates to the field of nondestructive detection, and particularly discloses an underground pipeline detection method, system, equipment and medium based on a phase shift method, which comprises the following steps: surveying a target area to determine the estimated position and direction of an underground pipeline; arranging a plurality of preset detectors and a preset seismic source excitation device in a linear array form capable of moving along the direction of the underground pipeline above the estimated position of the underground pipeline, and exciting seismic waves through multiple times to enable a data receiving device to collect data fed back by the detectors to obtain an initial seismic record data set; performing window filtering processing on the initial seismic record data set, and combining the phase shift method to analyze and process the filtered seismic record data set to obtain a dispersion curve; based on a layered medium model, the dispersion curve is inverted to obtain a phase velocity profile of an underground medium, and then a detection result of the underground pipeline is obtained; and the detection result is verified to determine the effectiveness of the detection result.

Description

Technical Field

[0001] This invention relates to the technical field of non-destructive testing, and in particular to a method, system, equipment and medium for detecting underground pipelines based on the phase shift method. Background Technology

[0002] Underground pipelines are a crucial component of urban infrastructure, encompassing various types such as water supply, drainage, gas, electricity, and communications. Their detection is a prerequisite for municipal construction, road development, and pipeline maintenance. Traditional underground pipeline detection methods include excavation detection, electromagnetic detection, and ground-penetrating radar (GPR), but these methods have several drawbacks: excavation detection is destructive, time-consuming, labor-intensive, and prone to damaging road surfaces and existing pipelines; electromagnetic detection is severely affected by underground metal interference and performs poorly on non-metallic pipelines; GPR has limited detection depth, is significantly influenced by the surface moisture content, and presents challenges in data interpretation. While Rayleigh surface wave technology offers advantages such as non-destructive testing, speed, and wide detection depth, current technologies lack specific optimization for underground pipeline detection, resulting in issues like low detector placement efficiency, unclear correlation between wave velocity and pipeline parameters, and insufficient pipeline identification accuracy. Furthermore, traditional phase-shifting methods rely solely on multi-channel superposition of basic phase terms without phase compensation or amplitude preprocessing, leading to problems such as high-frequency energy dispersion, noise sensitivity, spurious frequency generation, and weak shallow signal recognition.

[0003] Therefore, based on the above-mentioned technical problems, this application proposes an underground pipeline detection method, system, equipment, and medium based on the phase-shift method that has high deployment efficiency, high detection accuracy, and can solve the pain points of the traditional phase-shift method. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a phase-shift method, system, equipment and medium for underground pipeline detection with high deployment efficiency and high detection accuracy.

[0005] To achieve the above objectives, the present invention provides an underground pipeline detection method based on the phase shift method, which includes the following steps: Step 1: Survey the target area to determine the estimated location and direction of underground pipelines; Step 2: Arrange multiple preset geophones and preset seismic source excitation devices in a linear array that can move along the direction of the underground pipeline on the ground surface above the estimated location of the underground pipeline. Excite seismic waves multiple times to allow the preset data receiving device to collect the data fed back by the multiple geophones to obtain an initial seismic record dataset. The initial seismic record dataset includes reflected wave signals, Rayleigh surface wave signals, direct wave signals, and noise signals. Step 3: Perform windowing filtering on the initial seismic record dataset to obtain the filtered seismic record dataset; Step 4: Based on the phase shift method, analyze and process the filtered seismic record dataset to obtain the dispersion curve; Step 4 includes the following steps: Step 4.1: Along the extension direction of the receiving component, arrange the filtered seismic record dataset to obtain a fully arranged seismic record dataset, and normalize the fully arranged seismic record dataset to obtain a normalized seismic record dataset. Step 4.2: Summate multiple normalized seismic record datasets to obtain the surface wave energy function, and introduce a focusing factor into the surface wave energy function to obtain an improved surface wave energy function; Step 4.3: With the reference phase velocity fixed, different frequencies are sequentially introduced into the improved surface wave energy function to calculate the corresponding superposition total energy. And based on the superimposed total energy The energy peak value is used to extract the corresponding phase parameters; Step 4.4: Based on the relationship between frequency, true phase velocity and phase parameters, derive the corresponding true phase velocity and import each frequency and its corresponding true phase velocity into the preset computing and processing device, and then fit to obtain the dispersion curve; Step 5: Based on the preset layered medium model, the dispersion curve is inverted to obtain the phase velocity profile of the underground medium, and the phase velocity profile of the underground medium is analyzed and judged to obtain the detection results of the underground pipeline, wherein the detection results include the location of the underground pipeline and the burial depth of the underground pipeline. The specific steps of step 5 include: Step 5.1: Construct an initial layered medium model and set the initial geological parameters of the initial layered medium model based on the actual geological data of the target area. The initial geological parameters include the number of layers, layer thickness, and wave velocity data of each layer. Step 5.2: Based on the damped least squares method, iteratively correct the initial layered medium model until the preset stopping condition is met, and then output the corrected layered medium model. Step 5.3: Import the dispersion curve into the modified layered medium model so that the modified layered medium model can be inverted to obtain the phase velocity profile of the subsurface medium. Step 5.4: Analyze and judge the phase velocity profile to obtain the detection results of underground pipelines; Step 6: Verify the detection results to determine their validity.

[0006] Furthermore, step 1 also includes: selecting the corresponding detector based on the site type of the target area, wherein the site type includes hard surfaces and soft surfaces, and the detector includes a cylindrical flat-bottomed detector suitable for hard surfaces and a conical detector suitable for soft surfaces.

[0007] Furthermore, the specific steps in step 2 include: Step 2.1: After obtaining the estimated location and direction of the underground pipeline, the pre-set receiving component is arranged on the ground surface above the underground pipeline in a direction perpendicular to the direction of the underground pipeline, and multiple detectors are placed on the receiving component at intervals, thereby enabling the multiple detectors to communicate with the data receiving device. Step 2.2: Arrange the seismic source excitation device at the preset location; Step 2.3: The source excitation device generates seismic waves, and the data receiving device receives signal data fed back from multiple detectors to obtain a set of signal data; Step 2.4: Move the receiving component a preset distance along the direction of the underground pipeline, and repeat steps 2.2 to 2.3 to obtain multiple sets of signal data, and then classify and aggregate the multiple sets of signal data to form an initial seismic record dataset.

[0008] Furthermore, the initial seismic record dataset in step 3 is a time-domain signal, and the windowing filtering process includes: Step 3.1: Based on the Fourier transform method, the initial seismic record dataset is converted from a time-domain signal to a spectral signal to obtain the converted seismic record dataset; Step 3.2: Based on the estimated burial depth of underground pipelines, select the corresponding filtering unit, and perform windowing filtering on the converted seismic record dataset through the filtering unit to obtain the filtered seismic record dataset.

[0009] Furthermore, step 6 includes the following specific steps: Step 6.1: Based on the detection results, select the ground penetrating radar corresponding to the detection depth, and make the ground penetrating radar uniformly collect signals along the estimated direction of the underground pipeline to obtain scanning data. Step 6.2: Perform optimization filtering on the scan data to obtain filtered scan data; Step 6.3: Convert the filtered scanning data into a radar image, and identify and analyze the waveform trend of the radar image to obtain the verification detection results; Step 6.4: Based on the verification detection result, determine whether the detection result needs to be corrected. If the positional deviation or depth deviation between the detection result and the verification result is greater than a preset judgment threshold, the detection result is determined to need to be corrected. If the positional deviation or depth deviation between the detection result and the verification result is less than or equal to the preset judgment threshold, the detection result is determined not to need to be corrected.

[0010] Based on the same inventive concept, this application also provides an underground pipeline detection system based on the phase-shift method, including a survey module, a seismic record dataset acquisition module, a filtering module, a dispersion curve acquisition module, a pipeline location estimation module, and a verification module. The survey module is used to survey the target area to determine the estimated location and direction of underground pipelines, and select the corresponding detector based on the site type of the target area. The earthquake record dataset acquisition module is used to arrange multiple preset geophones and preset seismic source excitation devices in a linear array that can move along the direction of the underground pipeline on the ground surface above the estimated location of the underground pipeline, and to excite seismic waves multiple times so that the preset data receiving device can collect the data fed back by the multiple geophones to obtain the initial earthquake record dataset. The filtering module is used to perform windowing filtering on the initial seismic record dataset to obtain a filtered seismic record dataset. The dispersion curve acquisition module is used to analyze and process the filtered seismic record dataset based on the phase shift method to obtain the dispersion curve; The pipeline location estimation module is used to invert the dispersion curve based on a preset layered medium model to obtain a phase velocity profile of the underground medium, and to analyze and judge the phase velocity profile of the underground medium to obtain the detection results of the underground pipeline, wherein the detection results include the location of the underground pipeline and the burial depth of the underground pipeline. The verification module is used to verify the detection results in order to determine the validity of the detection results.

[0011] Based on the same inventive concept, this application also provides a data processing device, including: a memory and a processor, wherein the memory is used to store a computer program; and the processor is used to execute the computer program to implement the underground pipeline detection method based on the phase shift method as described above.

[0012] Based on the same inventive concept, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the underground pipeline detection method based on the phase-shift method as described above.

[0013] The present invention adopts the above-described solution, and its beneficial effects are as follows: 1) This method uses seismic exploration combined with phase shift method to detect underground pipelines. No excavation is required throughout the process. It is a non-destructive detection method that can avoid damaging the road surface, existing pipelines and surrounding environment, and is suitable for various urban pipeline detection scenarios.

[0014] 2) The detectors and seismic source equipment are arranged in a linear array that can move along the pipeline, which can flexibly complete data acquisition over a large area and a long distance. The detection coverage is wide, and the on-site deployment and data acquisition operations are convenient and efficient.

[0015] 3) First, windowing filtering is applied to the original seismic record dataset, which can effectively filter out environmental noise and irrelevant interference waves during the acquisition process, improve the purity of the effective signal, and lay a good foundation for subsequent data analysis.

[0016] 4) By normalizing the amplitude of each seismic signal to eliminate amplitude interference caused by spherical diffusion and wave attenuation, and then introducing a focusing factor to compensate and compress the phase, the energy peak of the shallow high-frequency surface waves after multi-channel superposition is concentrated and the effective signal-to-noise ratio is improved, making the overall data processing more stable. It can accurately extract the effective surface wave information corresponding to the shallow pipeline, greatly suppress random noise and spatial aliasing, and fully ensure the accuracy of the final dispersion curve and the shallow resolution.

[0017] 5) The phase velocity profile of the underground medium is obtained by inverting the dispersion curve using the layered medium model. Based on the profile features, the location and burial depth of the underground pipeline can be determined intuitively and accurately, and the pipeline detection results are accurate and reliable.

[0018] 6) The addition of a detection result verification step can effectively verify the validity of the detection data, promptly identify errors and avoid misjudgments, and further improve the reliability and practicality of the overall detection work. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the underground pipeline detection method based on the phase-shift method in this embodiment.

[0020] Figure 2 This is a schematic diagram of the receiving component in Embodiment 1.

[0021] Figure 3 This is a schematic diagram of the earthquake record dataset in Example 1.

[0022] Figure 4 This is a cross-sectional view of the underground medium phase velocity in Example 1.

[0023] Figure 5 This is a schematic diagram of the dispersion curve in Example 1.

[0024] Figure 6 This is a schematic diagram of the cylindrical flat-bottomed detector in Embodiment 1.

[0025] Figure 7 This is a schematic diagram of the underground pipeline detection system based on the phase-shift method in Embodiment 2.

[0026] Among them, A1-installation port, A2-support bracket, A3-support foot, B1-sealing cover, B2-outer shell, B3-accelerometer sensor unit, and B4-detector base. Detailed Implementation

[0027] To facilitate understanding of the present invention, a more complete description is given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0028] Example 1: See appendix Figure 1-5 As shown in this embodiment, an underground pipeline detection method based on the phase shift method includes the following steps: Step 1: Survey the target area to determine the estimated location and direction of underground pipelines, and select the appropriate geophone based on the site type of the target area. The site type includes hard surfaces (such as urban cement / asphalt roads) and soft surfaces (such as dirt roads). The geophones include cylindrical flat-bottomed geophones suitable for hard surfaces (the flat-bottomed structure allows the geophone to fit snugly against the ground for more accurate data) and conical geophones suitable for soft surfaces (the conical structure allows the geophone to be stably inserted into the soft ground, avoiding the inability to obtain accurate data due to uneven ground). By judging the site type / site attributes of the target area, the appropriate equipment is selected for operation, ensuring that the relevant geophones can operate stably and that the data collected by the relevant geophones is accurate and effective, reducing interference from environmental factors.

[0029] By selecting cylindrical flat-bottomed detectors and conical detectors respectively for hard and soft ground surfaces, good coupling between the detectors and the ground surface is ensured, improving the reception quality of weak signals. This solves the problem of unstable signal reception in traditional surface wave detection under different site conditions, making it more adaptable to complex surface environments. The detection system can work stably on urban roads, hardened surfaces, and soft ground, making it more versatile.

[0030] Step 2: Arrange multiple preset geophones and preset seismic source excitation devices in a linear array that can move along the direction of the underground pipeline on the ground surface above the estimated location of the underground pipeline. Excite seismic waves multiple times so that the preset data receiving device can collect the data fed back by the multiple geophones to obtain the initial seismic record dataset. The specific steps in step 2 include: Step 2.1: After obtaining the estimated location and direction of the underground pipeline, the pre-designed receiving component is placed on the ground surface above the underground pipeline in a direction perpendicular to the pipeline's direction (while ensuring the receiving component is as close to the ground surface as possible). Multiple geophones are then placed on the receiving component at intervals, enabling communication between the geophones and the data receiving equipment to ensure the equipment can receive relevant data. Specifically, the receiving component has mounting openings A1 spaced along a straight line (preferably 12 mounting openings A1), each for installing a geophone. The preferred length of the receiving component is 2.2 m, and the preferred distance between each mounting opening A1 is 0.2 m. m (this distance can be considered as the channel spacing), and the aforementioned receiving component can be considered as a frame structure for supporting multiple detectors. The receiving component includes a support frame A2 and four support legs A3 located at the four corners of the bottom of the support frame A2. The bottom structure of the support legs A3 can be replaced with flat-bottomed support legs A3 or conical support legs A3 depending on the type of location (e.g., ...). Figure 6 The diagram illustrates the structure of a cylindrical flat-bottomed detector used in this embodiment, including a sealing cover B1, a housing B2, an acceleration sensing unit B3, and a round-bottomed detector base B4. The specific model, structure, and other parameters of the acceleration sensing unit B3 can be selected / set according to actual conditions, and are not subject to excessive restrictions here. Additionally, the conical support foot A3 is not shown in the reference figure. Step 2.2: Arrange the seismic source excitation device at a preset location, preferably 1 m away from the first or last end of the receiving component; Step 2.3: The seismic source excitation device generates seismic waves, and the data receiving device receives data fed back from multiple detectors to obtain a set of signal data; Step 2.4: Move the receiving component along the direction of the underground pipeline by a preset distance (preferably the same size as the aforementioned pipeline spacing, i.e., 0.2 m), and repeat steps 2.2 to 2.3 to obtain multiple sets of signal data. Then, classify and aggregate the multiple sets of signal data to form an initial seismic record dataset. The initial seismic record dataset includes reflected wave signals, Rayleigh surface wave signals, direct wave signals, and noise signals, etc. By intermittently moving the linearly arranged geophones, an array-shaped signal data collection is gradually formed. This array-shaped signal data is different from the conventional square / rectangular array. In this embodiment, the array-shaped signal data is arranged according to the direction of the underground pipeline. Therefore, its overall structure can be regarded as a quadrilateral / parallelogram structure array that better conforms to the actual underground pipeline direction / extends along the underground pipeline direction, thereby overcoming the influence of terrain factors and further improving detection accuracy.

[0031] In addition, the aforementioned seismic source excitation device preferably uses a 12V high-power electric converter (which can convert electrical energy into kinetic energy), and the excitation intensity can be adjusted by the operator according to the detection depth requirements, thereby meeting the detection needs of pipelines at different burial depths. Secondly, the aforementioned detector is preferably a 38 Hz high-sensitivity three-component detector (which can effectively acquire weak signal data).

[0032] Step 3: Apply windowed filtering to the initial seismic record dataset to obtain the filtered seismic record dataset; The initial seismic record dataset in step 3 above is a time-domain signal, and the windowing filtering process includes: Step 3.1: Based on the Fourier transform method, the initial seismic record dataset is converted from a time-domain signal to a spectral signal (i.e., from the time domain to the frequency domain) to obtain the converted seismic record dataset. Specifically, any signal data / surface wave seismic record u is arbitrarily selected, and its Fourier transform is performed to convert it to... The specific calculation formula is as follows: , in, This represents the amplitude spectrum, which contains amplitude information such as surface wave attenuation and spherical diffusion. The horizontal distance from the seismic source to the detector; This represents the phase factor of the phase spectrum / seismic record, which contains frequency information of the surface waves. For frequency; Step 3.2: Based on the estimated burial depth of underground pipelines, select the corresponding filtering unit and apply windowing filtering (e.g., Hamiltonian window) to the converted seismic record dataset using this filtering unit. For example, when detecting underground pipelines with relatively shallow burial depths, a high-pass filter can be used to remove low-frequency environmental interference noise and retain the high-frequency effective Rayleigh surface wave signals reflecting shallow underground pipelines, thereby obtaining the filtered seismic record dataset. The specific seismic record dataset mentioned above can be found in [reference needed]. Figure 3 Indication, among which, Figure 3 The vertical axis represents the seismic wave propagation time, usually in milliseconds (ms). A larger value indicates a longer waveform propagation time and a deeper underground propagation depth. The horizontal axis represents the detector channel number / source-receiver distance, with each column corresponding to the seismic waveform acquired by one detector in the array.

[0033] It should be noted that, compared to conventional surface wave detection, Rayleigh surface waves have the following advantages: 1. Rayleigh surface waves propagate on the surface and concentrate energy in the shallow layer (0–20 m). They have large amplitude and strong signal, which is much stronger than body waves and other surface waves. They are suitable for shallow underground pipeline detection, have good noise resistance, and stable signal.

[0034] 2. Different frequencies of Rayleigh surface waves correspond to different propagation velocities, which can accurately reflect the changes in wave velocity in underground layers (with obvious dispersion characteristics). Fine velocity profiles can be inverted through dispersion curves to accurately identify local wave velocity anomalies caused by pipelines. That is, based on the reflection / scattering distortion characteristics of Rayleigh surface waves at the pipeline interface, combined with the inflection point of the dispersion curve extracted by the phase shift method, the accurate identification of non-metallic pipelines (PVC / PE) can be achieved (with high inversion accuracy).

[0035] 3. Rayleigh surface waves propagate horizontally along the ground surface, and can be received by detectors placed on the ground without drilling; arrays can be flexibly arranged and mobile acquisition can be carried out, making it suitable for long-distance and large-area pipeline surveys, which is non-destructive, fast and low cost.

[0036] 4. Rayleigh surface wave energy is concentrated in the shallow layer of 1–5 m. It is sensitive to shallow, small-scale, low-wave-velocity anomalies such as underground pipelines (PE pipes, concrete pipes), can clearly capture sudden changes in wave velocity, and has good detection effect on non-metallic pipelines (strong pipeline identification ability).

[0037] 5. Rayleigh surface waves have low attenuation and long propagation distance, and a single excitation can cover a relatively long survey line, reducing the number of excitations and improving acquisition efficiency, making them suitable for large-area scenarios such as municipal roads and park pipe networks.

[0038] Step 4: Based on the phase shift method, analyze and process the filtered seismic record dataset to obtain the dispersion curve; Step 4 includes the following steps: Step 4.1: To eliminate amplitude interference caused by spherical diffusion, absorption attenuation, etc., the filtered seismic record dataset is first arranged along the extension direction of the receiving component to obtain a fully arranged seismic record dataset. Then, the fully arranged seismic record dataset is normalized to obtain a normalized seismic record dataset (that is, the filtered signal data of each group in the above filtered seismic record data is arranged and normalized). The above normalization process is to uniformly scale the amplitude of each frequency domain signal to the same order of magnitude, retain only the phase information, smooth out amplitude differences, and eliminate amplitude interference caused by distance and wave attenuation. In the far-field case, the propagation of seismic waves can be considered as planar propagation, that is, waves of different frequencies propagate at different phase velocities, and the phase spectrum... It can be represented as: , Where t is the surface wave propagation time, This is the distance from the seismic source to the nth geophone (i.e., the shot-receiver distance). The phase change per unit distance (phase wavenumber). (Right now The distance between the surface wave propagating to the nth detector and the shot-receiver distance is... The total phase change at that point The surface wave angular frequency, The actual phase velocity at the corresponding frequency, where i is the imaginary unit; The above phase spectrum The expression is used to perform phase correction (phase shift) on each channel signal, which is the core embodiment of the phase shift method.

[0039] Step 4.2: Stack / sum multiple normalized seismic record datasets to obtain the surface wave energy function, the specific formula of which is: , Furthermore, to highlight the energy of the high-frequency phase, a focusing factor τ is introduced to measure the phase change per unit distance. Compensation and correction are performed, and simultaneously, a positive phase τ is subtracted, so that the total phase change at the shot-receiver distance x is reduced from... x changes to This reduces the total phase change (i.e., achieves phase shift compression, enabling phase alignment of shallow high-frequency surface waves and concentration of superimposed energy). The specific formula for calculating the positive focusing factor τ is as follows: , Where τ is the focusing factor, The reference phase velocity; It should be noted that, considering the positive propagation velocity of Rayleigh surface waves in the formation, the reference phase velocity is... Satisfying the hard physical constraint >0, the angular frequency ω is always greater than 0, and the resulting focusing factor τ is also always positive, thus ensuring that the phase compensation amount has practical physical meaning and there is no unreasonable situation of negative phase compensation; secondly, the above-mentioned reference phase velocity The value needs to be selected by comprehensively considering the phase modulation effect and the requirement for anti-spatial aliasing, and its range is limited to the surface wave group velocity. With the average phase velocity of the formation Between (i.e.) If the reference phase velocity surface wave group velocity With the average phase velocity of the formation Taking values ​​at the boundary of the interval will significantly attenuate the phase compensation effect. Therefore, it is not recommended to take boundary values ​​in actual calculations. That is, Rayleigh surface waves in shallow terrestrial strata have positive dispersion characteristics, and the true phase velocity of high-frequency surface waves of interest for shallow pipelines is... Interface group velocity With the average phase velocity of the formation Between; if selected or This will cause the focus factor τ to change phase per unit distance. If the difference is too large, high-frequency phase shift compression cannot be achieved, resulting in surface wave superposition energy dispersion and the generation of a large number of false energy peaks in the dispersion curve, thus failing to achieve the core objective of accurate identification of shallow pipelines. For example, in a scenario where shallow underground pipelines are detected at depths of 1–5 m, considering that the strata in this area are mostly silty clay and sand, the surface wave group velocity... The value ranges from 120 to 220 m / s, representing the average phase velocity of the formation. The value range is 240-380 m / s, therefore the reference phase velocity quantization range is: 150 m / s ≤ ≤320 m / s; By importing the focusing factor τ into the surface wave energy function above, we obtain the improved formula for calculating the surface wave energy function, which is as follows: ; Where N is the total number of channels in the detector array, and n is the number of a single-channel detector. Let n be the distance from the earthquake source to the nth detector. The phase change per unit distance. The surface wave angular frequency, As a focusing factor, The angular frequency of the seismic record acquired by the nth detector after Fourier transform The corresponding frequency domain complex signal, The reference phase velocity is i, where i is the imaginary unit. Specifically, the original single-channel seismic waveform is a time-domain vibration signal that varies with time. It is decomposed into complex frequency domain data of different frequencies through Fourier transform. The frequency in this signal The complex representation of the component carries both amplitude information and original phase information at that frequency; while It is the magnitude (amplitude) of the frequency domain component, and dividing the two completes the amplitude normalization.

[0040] Step 4.3: Fix the reference phase velocity To the improved surface wave energy function Calculate the superposition total energy by sequentially importing different angular frequencies ω. And based on the superimposed total energy The energy peak value is used to extract the corresponding phase parameters (i.e., the energy peak position represents the optimal phase parameter at that frequency / phase change per unit distance). That is, taking the angular frequency ω in the surface wave energy function as the independent variable, the total energy after the superposition of multiple Rayleigh surface wave signals. Energy scanning was conducted as the dependent variable.

[0041] Step 4.4: Based on (surface wave angle) frequency True phase velocity and phase change per unit distance The relationship between them is used to derive the true phase velocity. The above relationship is specifically as follows: , The above true phase velocity The specific calculation formula is as follows: , In order to prevent the denominator of the formula When the value approaches 0, the output has no physical meaning; therefore, a mandatory constraint condition is added. ; Import the angular frequencies ω of each surface wave and their corresponding true phase velocities. The data is imported into a pre-set computing processing device, and then a dispersion curve is obtained through fitting. For details, please refer to [reference needed]. Figure 5 As shown; It should be noted that in conventional surface wave exploration, the FK transform method is generally used to extract dispersion curves. However, in actual engineering geophysical exploration sites, environmental factors exist, such as significant data noise, which can easily lead to spurious frequency phenomena, affecting the detection accuracy. (That is, the FK transform method is quite sensitive to noise and has high requirements for trace spacing and trace number. When affected by factors such as noise interference, unreasonable trace spacing, and insufficient effective signal, the transformation or inversion results may show false or spurious dispersion energy, forming a dispersion curve that appears continuous but does not match the actual strata—the spurious frequency phenomenon). To address this, this method uses the phase-shift method to analyze and process the filtered seismic record dataset. The phase-shift method has the advantages of strong noise resistance, low computational cost, and high resolution. It has lower requirements for trace spacing and can obtain high-resolution surface wave dispersion energy with fewer traces, ensuring detection accuracy. In addition, compared with the traditional phase-shift method that relies solely on the basic phase, this method... Traditional multi-channel superposition methods, without phase compensation and amplitude preprocessing, suffer from drawbacks such as high-frequency energy dispersion, noise sensitivity, spurious frequency generation, and weak shallow signal recognition. This embodiment employs an improved phase-shift method that introduces a focusing factor to compensate and correct the phase, compressing the phase shift of high-frequency Rayleigh surface waves. This concentrates the energy and highlights the peak value of the high-frequency signal corresponding to shallow pipelines during multi-channel superposition, solving the problems of high-frequency energy dispersion and difficulty in identifying effective shallow signals in traditional phase-shift methods. Simultaneously, an amplitude normalization step is added to eliminate amplitude interference caused by spherical diffusion, wave attenuation, and detector coupling differences. Combined with the superposition of multiple moving array data, it effectively suppresses urban site environmental noise, reduces the probability of spurious frequency generation, and achieves higher dispersion curve accuracy. Furthermore, the algorithm parameters and phase focusing interval are adapted to the commonly used high-frequency and shallow detection ranges for underground pipelines, making it more sensitive to capturing the wave velocity abrupt changes in shallow media, especially improving the detection accuracy of non-metallic underground pipelines.

[0042] Step 5: Based on the preset layered medium model, the dispersion curve is inverted to obtain the phase velocity profile of the underground medium, and the phase velocity profile of the underground medium is analyzed and judged to obtain the detection results of the underground pipeline. The detection results include the location of the underground pipeline and the burial depth of the underground pipeline. Step 5 includes the following specific steps: Step 5.1: Construct an initial layered medium model and set the initial geological parameters of the initial layered medium model based on the actual geological data (stratum distribution, soil type and wave velocity pattern) of the target area. The initial geological parameters include the number of layers, layer thickness, and wave velocity data of each layer. Step 5.2: Based on the damped least squares method, iteratively correct the initial layered medium model until the preset stopping condition is met, and then output the corrected layered medium model. Specifically, the initial layered medium model is first used to calculate the theoretical dispersion curve. Then, the fitting residual threshold (i.e., the difference between the theoretical and actual dispersion curves) between the theoretical and actual dispersion curves is calculated. It is then determined whether the fitting residual threshold is less than the stopping correction value (i.e., the stopping condition mentioned above). If the fitting residual threshold is less than the stopping correction value, the corrected layered medium model is output. If the fitting residual threshold is greater than or equal to the stopping correction value, the parameters of the initial layered medium model are corrected using the fitting residual threshold, so that the theoretical dispersion curve calculated by the model continuously approaches the actual dispersion curve (improving model accuracy and computational efficiency). The damped least squares method is used to iteratively correct the initial layered medium model. By constraining model oscillations and reducing the error between the theoretical and measured dispersion curves, the inversion results are made more consistent with the real geological structure, and the inversion process is stable and reliable. Combined with the wave velocity mutation characteristics in the phase velocity profile, the location and burial depth of underground pipelines can be accurately identified, improving the detection success rate of non-metallic pipelines and making pipeline identification more accurate. further, Figure 5 This is a schematic diagram of the dispersion energy spectrum and dispersion fitting results. The horizontal axis represents the surface wave frequency in Hz; the vertical axis represents the Rayleigh surface wave phase velocity in Hz. The gradient grayscale scale on the right side of the figure represents the magnitude of the coherent superposition energy of the multichannel detector signals; higher values ​​and brighter grayscale indicate stronger phase coherence energy. The black dashed line in the figure is the reference boundary for the group velocity in surface wave theory, used to define the effective dispersion value range. The white solid line in the figure represents the measured dispersion curve obtained by performing energy scanning on multichannel seismic data using the improved phase-shift method, extracting energy peak points frequency by frequency, and stitching them together. Each set of coordinates (frequency f, phase velocity...) represents the measured dispersion curve obtained by stitching together the energy peak points. The discrete data representing the actual dispersion of the strata in the field serves as the target fitting benchmark for the analytical solution inversion. The line with discrete black dots is used to characterize the theoretical dispersion result that fits the actual underground strata structure. The line with discrete black dots uses the measured dispersion curve as the fitting reference. The initial geological parameters are input into the above-mentioned layered medium model, and the theoretical dispersion is calculated in the forward direction using the Rayleigh surface wave dispersion analytical equation for the layered medium (the above-mentioned Rayleigh surface wave dispersion analytical equation for the layered medium is a conventional and general technique, and its specific derivation process and transfer matrix construction method are common knowledge in this field. The specific derivation and matrix construction method will not be elaborated here). The model parameters are continuously corrected and iteratively calculated using the damped least squares method until the iteration process meets the above-mentioned stopping condition. Then, the dispersion equation is discretely solved through the corrected layered medium model to obtain the corresponding coordinate black dots, and the black dots are connected in frequency order to obtain the analytical solution dispersion curve.

[0043] Step 5.3: Import the dispersion curve into the corrected layered medium model to perform inversion, thereby obtaining a phase velocity profile that approximates the actual subsurface medium. See [link / reference] for details. Figure 4 As shown; Step 5.4: Analyze and judge the phase velocity profile to obtain the detection results of underground pipelines, among which, Figure 4 The shaded area in the image represents the specific location / detection results of the underground pipeline. Figure 4 The area within the elliptical box indicates the location of the underground pipeline.

[0044] Step 6: Cross-validate the detection results to determine their validity; Step 6 includes the following specific steps: Step 6.1: Based on the detection results, select the ground penetrating radar corresponding to the detection depth, and make the ground penetrating radar uniformly collect signals along the estimated direction of the underground pipeline to obtain scanning data. Step 6.2: Perform optimization filtering on the scan data to obtain filtered scan data; Step 6.3: Convert the filtered scanning data into radar images, and identify and analyze the waveform trend of the radar images to obtain verification detection results; Step 6.4: Based on the verification detection results, determine whether the detection results need to be corrected. If the positional or depth deviation between the detection results and the verification results is greater than a preset judgment threshold, the detection results are determined to need correction. If the positional or depth deviation between the detection results and the verification results is less than or equal to the preset judgment threshold, the detection results are determined not to need correction. Specifically, considering that the detection accuracy of ground penetrating radar in shallow strata (depth range of 5 m) is usually higher than that of conventional surface wave methods, by combining the above-mentioned ground penetrating radar detection with Rayleigh surface wave detection, a dynamic adjustment and correction strategy is realized, avoiding model distortion caused by unfounded adjustments. In addition, the above judgment threshold can be set according to the actual situation, and no specific limitation is made here.

[0045] In summary, the present invention has the following advantages: 1) This invention selects cylindrical flat-bottomed detectors and conical detectors for hard surfaces and soft surfaces respectively, to ensure good coupling between the detectors and the ground surface, improve the reception quality of weak signals, solve the problem of unstable signal reception of traditional surface wave detection under different site conditions, and is more adaptable to complex surface environments, so that the detection system can work stably on urban roads, hard surfaces and soft sites, and has stronger detection applicability.

[0046] 2) Compared to the shortcomings of traditional fk transform, which is susceptible to noise interference and spurious frequency phenomena, this invention uses an improved phase shift method with focusing factor phase correction and amplitude normalization optimization / a phase shift method with added phase compensation for data processing. First, the amplitude of each channel signal is unified by amplitude normalization to eliminate amplitude interference caused by spherical diffusion and formation absorption attenuation. Then, a focusing factor is introduced to compress the phase shift of shallow high-frequency surface waves, making the superposition energy of high-frequency effective signals concentrated and prominent. Combined with multi-channel coherent superposition, it can effectively suppress environmental noise and interference waves, and significantly improve noise resistance. Secondly, the above-mentioned improved phase shift method relaxes the strict requirements on the number of detectors and channel spacing. It can still obtain high-resolution dispersion energy under the conditions of fewer channel gathers and larger channel spacing, suppress spurious dispersion peaks, significantly improve the accuracy of dispersion curves and the stability of shallow signal resolution, and is specifically adapted to the high-frequency weak signal extraction needs of shallow underground pipelines.

[0047] 3) This invention uses the damped least squares method to iteratively correct the initial layered medium model. By constraining model oscillations and reducing the error between theoretical and measured dispersion curves, the inversion results are more consistent with the real geological structure, and the inversion process is stable and reliable. Combined with the wave velocity change characteristics in the phase velocity profile, the location and burial depth of underground pipelines can be accurately identified, improving the success rate of non-metallic pipeline detection and making pipeline identification more accurate.

[0048] 4) This invention employs a dual-method cross-validation approach. By jointly validating the detection results with the ground-penetrating radar results, a dual judgment mechanism for detection and verification is formed, which effectively avoids the ambiguity of a single geophysical exploration method and significantly improves the reliability and accuracy of underground pipeline detection results.

[0049] 5) The entire process is non-destructive, efficient, and widely adaptable. The entire detection process requires no excavation and causes no damage to the ground or existing pipelines. It can quickly complete large-area inspections. It is easy to set up and has high calculation efficiency, making it suitable for rapid location of underground pipelines in various scenarios such as urban municipal roads, park pipe networks, and old residential areas.

[0050] To facilitate explanation, the following detailed explanation is provided with reference to specific embodiments of the underground pipeline detection method based on the phase shift method.

[0051] Background information: A municipal road in a certain city has a hardened surface (cement concrete or asphalt pavement), which is not suitable for direct excavation. It is necessary to accurately locate the non-metallic water supply pipe (PE material) buried underground before construction.

[0052] Pipeline conditions: The pipeline runs parallel to the road, is buried at a depth of about 2 m, and has a diameter D of 20 cm. The surrounding geology is silty clay, with no other dense pipelines interfering.

[0053] Equipment selection: The excitation source equipment adopts an electromagnetic vibrator as the excitation source; the detector adopts a 12-channel 38 Hz three-component detector; the receiving component is selected to be of the type that can be installed with the above three-component detectors (that is, the distance between adjacent mounting ports A1 on the receiving component is 0.2 m, and after each three-component detector is placed, its bottom cylindrical flat base can be tightly coupled with the road surface). Equipment layout: The extension direction of the receiving component is perpendicular to the direction of the underground pipeline; the excitation point of the seismic source is 1.0 m away from the first end of the receiving component, and after completing a single data transmission / obtaining a single set of signal data, it is moved multiple times along the direction of the underground pipeline and the measurement is repeated (the interval between each movement is preferably 2.0 m). Data processing: Repeat steps 3-5 to obtain the phase velocity profile; Interpretation of results: The inversion results are as follows: Figure 4 As shown, at a distance of 40 m and a depth of 2-3 m, there is a significant wave velocity distortion (the wave velocity in the surrounding soil is about 250 m / s, while the wave velocity in the pipeline area suddenly changes to about 200 m / s), which is determined to be a pipeline anomaly. Result verification: Repeat steps 5.1-5.4, and use ground-penetrating radar cross-verification to make a judgment. The detection results are consistent with the verification detection results.

[0054] Example 2: See appendix Figure 7 As shown, based on the same inventive concept, this application also provides an underground pipeline detection system based on the phase shift method, including a survey module, a seismic record dataset acquisition module, a filtering module, a dispersion curve acquisition module, a pipeline location estimation module, and a verification module. The survey module is used to survey the target area to determine the estimated location and direction of underground pipelines. The seismic record dataset acquisition module is used to arrange multiple preset geophones and preset seismic source excitation devices in a linear array that can move along the direction of the underground pipeline on the ground surface above the estimated location of the underground pipeline. By repeatedly exciting seismic waves, the preset data receiving device collects the data fed back by the multiple geophones to obtain the initial seismic record dataset. The filtering module is used to perform windowing filtering on the initial seismic record dataset to obtain a filtered seismic record dataset; The dispersion curve acquisition module is used to analyze and process the filtered seismic record dataset based on the phase shift method to obtain dispersion curves; The pipeline location estimation module is used to invert the dispersion curve based on a preset layered medium model to obtain the phase velocity profile of the underground medium, and to analyze and judge the phase velocity profile of the underground medium to obtain the detection results of the underground pipeline. The detection results include the location of the underground pipeline and the burial depth of the underground pipeline. The verification module is used to verify the detection results in order to determine their validity.

[0055] Example 3: Based on the same inventive concept, this application also provides a data processing device, including: a memory and a processor, wherein the memory is used to store a computer program; and the processor is used to execute the computer program to implement the underground pipeline detection method based on the phase shift method as described above.

[0056] Example 4: Based on the same inventive concept, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the underground pipeline detection method based on the phase-shift method as described above.

[0057] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Any modifications or variations made by those skilled in the art, without departing from the scope of the present invention, using the disclosed technical content, are equivalent embodiments of the present invention. Therefore, all equivalent changes made based on the concept of the present invention without departing from the scope of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for detecting underground pipelines based on the phase-shift method, characterized in that: The method includes the following steps: Step 1: Survey the target area to determine the estimated location and direction of underground pipelines; Step 2: Arrange multiple preset geophones and preset seismic source excitation devices in a linear array that can move along the underground pipeline along its direction on the ground surface above the estimated location of the underground pipeline. Excite seismic waves multiple times to allow the preset data receiving device to collect the data fed back by the multiple geophones to obtain an initial seismic record dataset. The initial seismic record dataset includes reflected wave signals, Rayleigh surface wave signals, direct wave signals, and noise signals. Step 3: Perform windowing filtering on the initial seismic record dataset to obtain the filtered seismic record dataset; Step 4: Based on the phase shift method, analyze and process the filtered seismic record dataset to obtain the dispersion curve; Step 4 includes the following steps: Step 4.1: Along the extension direction of the receiving component, arrange the filtered seismic record dataset to obtain a fully arranged seismic record dataset, and normalize the fully arranged seismic record dataset to obtain a normalized seismic record dataset. Step 4.2: Summate multiple normalized seismic record datasets to obtain the surface wave energy function, and introduce a focusing factor into the surface wave energy function to obtain an improved surface wave energy function; Step 4.3: With the reference phase velocity fixed, different frequencies are sequentially introduced into the improved surface wave energy function to calculate the corresponding superposition total energy. And based on the superimposed total energy Extract the corresponding phase parameters from the energy peak value; Step 4.4: Based on the relationship between frequency, true phase velocity and phase parameters, derive the corresponding true phase velocity and import each frequency and its corresponding true phase velocity into the preset computing and processing device, and then fit to obtain the dispersion curve; Step 5: Based on the preset layered medium model, the dispersion curve is inverted to obtain the phase velocity profile of the underground medium, and the phase velocity profile of the underground medium is analyzed and judged to obtain the detection results of the underground pipeline, wherein the detection results include the location of the underground pipeline and the burial depth of the underground pipeline. The specific steps of step 5 include: Step 5.1: Construct an initial layered medium model and set the initial geological parameters of the initial layered medium model based on the actual geological data of the target area. The initial geological parameters include the number of layers, layer thickness, and wave velocity data of each layer. Step 5.2: Based on the damped least squares method, iteratively correct the initial layered medium model until the preset stopping condition is met, and then output the corrected layered medium model. Step 5.3: Import the dispersion curve into the modified layered medium model so that the modified layered medium model can be inverted to obtain the phase velocity profile of the subsurface medium. Step 5.4: Analyze and judge the phase velocity profile to obtain the detection results of underground pipelines; Step 6: Verify the detection results to determine their validity.

2. The underground pipeline detection method based on phase shift method according to claim 1, characterized in that: Step 1 further includes: selecting the corresponding detector based on the site type of the target area, wherein the site type includes hard surfaces and soft surfaces, and the detector includes a cylindrical flat-bottomed detector suitable for hard surfaces and a conical detector suitable for soft surfaces.

3. The method for detecting underground pipelines based on the phase-shift method according to claim 1, characterized in that: The specific steps in step 2 include: Step 2.1: After obtaining the estimated location and direction of the underground pipeline, the pre-set receiving component is arranged on the ground surface above the underground pipeline in a direction perpendicular to the direction of the underground pipeline, and multiple detectors are placed on the receiving component at intervals, thereby enabling the multiple detectors to communicate with the data receiving device. Step 2.2: Arrange the seismic source excitation device at the preset location; Step 2.3: The source excitation device generates seismic waves, and the data receiving device receives signal data fed back from multiple detectors to obtain a set of signal data; Step 2.4: Move the receiving component a preset distance along the direction of the underground pipeline, and repeat steps 2.2 to 2.3 to obtain multiple sets of signal data, and then classify and aggregate the multiple sets of signal data to form an initial seismic record dataset.

4. The underground pipeline detection method based on phase shift method according to claim 3, characterized in that: The initial seismic record dataset in step 3 is a time-domain signal, and the windowing filtering process includes: Step 3.1: Based on the Fourier transform method, the initial seismic record dataset is converted from a time-domain signal to a spectral signal to obtain the converted seismic record dataset; Step 3.2: Based on the estimated burial depth of underground pipelines, select the corresponding filtering unit, and perform windowing filtering on the converted seismic record dataset through the filtering unit to obtain the filtered seismic record dataset.

5. The underground pipeline detection method based on phase shift method according to claim 1, characterized in that: The specific steps of step 6 include: Step 6.1: Based on the detection results, select the ground penetrating radar corresponding to the detection depth, and make the ground penetrating radar uniformly collect signals along the estimated direction of the underground pipeline to obtain scanning data. Step 6.2: Perform optimization filtering on the scan data to obtain filtered scan data; Step 6.3: Convert the filtered scanning data into a radar image, and identify and analyze the waveform trend of the radar image to obtain the verification detection results; Step 6.4: Based on the verification detection result, determine whether the detection result needs to be corrected. If the positional deviation or depth deviation between the detection result and the verification result is greater than a preset judgment threshold, the detection result is determined to need to be corrected. If the positional deviation or depth deviation between the detection result and the verification result is less than or equal to the preset judgment threshold, the detection result is determined not to need to be corrected.

6. A phase-shift method-based underground pipeline detection system, used to implement the method described in any one of claims 1-5, characterized in that: It includes a survey module, a seismic record dataset acquisition module, a filtering module, a dispersion curve acquisition module, a pipeline location inference module, and a verification module. The survey module is used to survey the target area to determine the estimated location and direction of underground pipelines. The earthquake record dataset acquisition module is used to arrange multiple preset geophones and preset seismic source excitation devices in a linear array that can move along the direction of the underground pipeline on the ground surface above the estimated location of the underground pipeline, and to excite seismic waves multiple times so that the preset data receiving device can collect the data fed back by the multiple geophones to obtain the initial earthquake record dataset. The filtering module is used to perform windowing filtering on the initial seismic record dataset to obtain a filtered seismic record dataset. The dispersion curve acquisition module is used to analyze and process the filtered seismic record dataset based on the phase shift method to obtain the dispersion curve; The pipeline location estimation module is used to invert the dispersion curve based on a preset layered medium model to obtain a phase velocity profile of the underground medium, and to analyze and judge the phase velocity profile of the underground medium to obtain the detection results of the underground pipeline, wherein the detection results include the location of the underground pipeline and the burial depth of the underground pipeline. The verification module is used to verify the detection results in order to determine the validity of the detection results.

7. A computer device, comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the method described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores machine-executable instructions that, when invoked and executed by a processor, cause the processor to perform the method according to any one of claims 1 to 5.

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