Ultra-deep underground pipeline detection method and device, storage medium and program product

Abstract

The invention discloses an ultra-deep underground pipeline detection method and device, a storage medium and a program product, and the method comprises the steps: transmitting a multi-frequency electromagnetic wave signal, receiving an acoustic response generated by the multi-frequency electromagnetic wave signal, and determining an underground geological structure in combination with a preset geological material frequency spectrum database. A composite detection signal is generated by simulating an underground propagation path of a multi-frequency electromagnetic wave signal and performing phase adjustment and power adjustment. And finally determining position information and depth information of the pipeline in the generated underground structure image by transmitting a composite detection signal and processing a return signal by using a time reversal mirror technology. According to the method, multi-frequency electromagnetic wave signals, acoustic response analysis, geological material characteristics and signal processing technologies are comprehensively utilized, and the precision and reliability of ultra-deep underground pipeline detection can be effectively improved.

Description

Technical Field

[0001] The present application relates to the technical field of pipeline detection, and in particular to a method, device, storage medium and program product for detecting ultra-deep underground pipelines. Background Art

[0002] With the acceleration of urbanization and the improvement of industrialization, underground pipelines have become increasingly complex. The safety, maintenance and upgrading of these pipelines require precise positioning and detection technology. Effective underground pipeline detection technology is essential for urban planning, construction and disaster prevention, especially during road construction and new construction to avoid damage to existing underground pipelines.

[0003] At present, underground pipeline detection mainly relies on ground penetrating radar (GPR) technology. Ground penetrating radar detects underground objects by emitting pulsed electromagnetic waves and receiving signals reflected from underground structures. This method can determine the location and depth of underground objects to a certain extent.

[0004] Although existing technology can provide basic information about underground pipelines, it still has several major drawbacks. First, geological radar is not effective in soils with high electrical conductivity because the electromagnetic waves decay quickly and the signal strength is greatly reduced, thus affecting the detection accuracy. Summary of the invention

[0005] The present application provides a method, device, storage medium and program product for detecting ultra-deep underground pipelines, which are used to improve the accuracy of detection.

[0006] In a first aspect, the present application provides a method for detecting ultra-deep underground pipelines, which is applied to a detection device, and the method includes: after transmitting a multi-frequency electromagnetic wave signal underground, receiving an acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground; determining the underground geological structure based on a preset geological material spectrum database and the frequency domain characteristics of the acoustic response, the geological material spectrum database including characteristic responses of various geological materials under the action of electromagnetic wave signals of different frequencies, and the underground geological structure is used to represent the composition and distribution of underground geological materials; simulating the propagation path of the multi-frequency electromagnetic wave signal underground according to the underground geological structure; performing phase adjustment and power adjustment on the multi-frequency electromagnetic wave signal according to the propagation path to obtain a composite detection signal; after transmitting the composite detection signal underground, receiving a return signal; processing the return signal by time reversal mirror technology to generate an underground structure image, and the underground structure image is used to visualize the underground space; determining the location information and depth information of the pipeline in the underground structure image.

[0007] By adopting the above technical solution, the detection device determines the underground geological structure by emitting multi-frequency electromagnetic wave signals and receiving the acoustic response generated by them, combined with the preset geological material spectrum database. By simulating the propagation path of the multi-frequency electromagnetic wave signal underground and performing phase adjustment and power adjustment, a composite detection signal is generated. The detection device transmits the composite detection signal and uses the time reversal mirror technology to process the return signal, and finally determines the location information and depth information of the pipeline in the generated underground structure image. This method comprehensively utilizes multi-frequency electromagnetic wave signals, acoustic response analysis, geological material characteristics and signal processing technology, which can effectively improve the accuracy and reliability of ultra-deep underground pipeline detection. It is especially suitable for ultra-deep pipeline detection under complex geological conditions, which can overcome the limitations of traditional methods in depth and accuracy, and provide more accurate information support for underground pipeline planning, construction and maintenance.

[0008] In combination with some embodiments of the first aspect, in some embodiments, after transmitting a multi-frequency electromagnetic wave signal underground, receiving the acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground specifically includes: extracting multiple acoustic responses by analyzing the received signals of multiple distributed sensors; and determining the emission positions of the multiple acoustic responses according to the setting positions of the multiple distributed sensors.

[0009] By adopting the above technical solution, the detection device extracts multiple acoustic responses by analyzing the received signals of multiple distributed sensors, and determines the emission positions of these acoustic responses according to the setting positions of the distributed sensors, so as to obtain more comprehensive and accurate underground acoustic information. The arrangement of multiple distributed sensors can cover a larger detection range and capture acoustic responses from different directions and depths. By determining the emission positions of the acoustic responses, the underground structure and material distribution can be mapped more accurately. This method significantly improves the spatial resolution and quality of the acoustic response data, and provides more reliable and detailed input information for subsequent geological structure analysis and pipeline positioning, thereby improving the accuracy and reliability of the entire detection process.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after the step of transmitting a multi-frequency electromagnetic wave signal underground and receiving an acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground, the method further includes: performing time-frequency analysis on the acoustic response to obtain a time-frequency feature graph; based on the time-frequency feature graph, extracting the frequency domain characteristics of the acoustic response, the frequency domain characteristics including frequency distribution, spectral peak position and spectral peak intensity.

[0011] By adopting the above technical solution, the detection device performs time-frequency analysis on the received acoustic response to obtain a time-frequency feature map, and based on this, extracts the frequency domain characteristics of the acoustic response, including frequency distribution, spectral peak position and spectral peak intensity. This in-depth signal analysis process can capture and analyze the characteristics of the acoustic response more comprehensively. Time-frequency analysis can reveal the changing patterns of signals in the time and frequency dimensions, and the extracted frequency domain characteristics directly reflect the acoustic characteristics of different geological materials and structures, thereby providing a key basis for subsequent geological structure identification and pipeline positioning, and significantly improving the accuracy and reliability of the detection results. At the same time, this method also enhances the adaptability of the detection device to complex geological environments, and can better distinguish and identify different types of underground structures and geological materials.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the propagation path of the multi-frequency electromagnetic wave signal underground is simulated according to the underground geological structure, specifically including: constructing an underground three-dimensional model based on the underground geological structure; after transmitting the simulated multi-frequency electromagnetic wave signal to the underground three-dimensional model at different incident points and incident angles, receiving the phase, amplitude and arrival time of the simulated multi-frequency electromagnetic wave signal through a simulated sensor in the underground three-dimensional model; and calculating the propagation paths of electromagnetic wave signals of different frequencies in the underground three-dimensional model according to the phase, amplitude and arrival time of the simulated multi-frequency electromagnetic wave signal.

[0013] By adopting the above technical solution, the detection device can more accurately predict the propagation path of the actual detection signal underground by constructing an underground three-dimensional model and simulating the propagation of multi-frequency electromagnetic wave signals in the underground three-dimensional model. By emitting simulated multi-frequency electromagnetic wave signals at different incident points and incident angles, and analyzing the phase, amplitude and arrival time of the simulated electromagnetic wave signals received by the simulated sensor, the propagation characteristics of the multi-frequency electromagnetic wave signals in complex geological structures can be fully understood. This simulation method based on the underground three-dimensional model takes into account the three-dimensional structure and diversity of the underground environment, and can more realistically reflect the propagation, reflection and attenuation of multi-frequency electromagnetic wave signals between different geological layers. The propagation path information obtained provides an accurate basis for subsequent signal adjustment, which helps to optimize the design of the actual detection signal and improve the depth and accuracy of detection, especially in ultra-deep pipeline detection under complex geological conditions. It has significant advantages.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the multi-frequency electromagnetic wave signal is phase-adjusted and power-adjusted according to the propagation path to obtain a composite detection signal, specifically including: based on the propagation path, calculating the propagation loss of electromagnetic wave signals of different frequencies and the phase shift generated by electromagnetic wave signals of different frequencies during the propagation process; performing phase compensation on the multi-frequency electromagnetic wave signal according to the phase shift; amplifying the transmission power of the multi-frequency electromagnetic wave signal according to the propagation loss; and obtaining the composite detection signal by synthesizing the electromagnetic wave signals of each frequency after phase adjustment and power adjustment.

[0015] By adopting the above technical solution, the detection device calculates the propagation loss and phase offset of electromagnetic wave signals of different frequencies, and performs phase compensation and power adjustment accordingly, and finally synthesizes a composite detection signal. This sophisticated signal processing process can effectively overcome the adverse effects of the underground environment on the detection signal. Phase compensation can correct the phase distortion caused by geological media to ensure that the electromagnetic wave signal can still maintain good coherence when propagating in deep layers; power adjustment can compensate for the energy loss of electromagnetic wave signals of different frequencies during the propagation process, ensuring that the electromagnetic wave signal can reach the target depth and produce sufficiently strong reflections. By synthesizing optimized electromagnetic wave signals of various frequencies, the obtained composite detection signal has stronger penetration ability and higher signal-to-noise ratio, which can effectively improve the depth and accuracy of ultra-deep pipeline detection, and is especially suitable for detection tasks under complex geological conditions.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of receiving a return signal after transmitting the composite detection signal underground, the method further includes: comparing the quality index of the return signal with a preset signal quality evaluation parameter to determine whether the quality of the return signal meets a preset condition; if not, determining that the return signal is an unusable signal.

[0017] By adopting the above technical solution, the detection device provides an important quality control mechanism for the detection process by comparing the quality index of the return signal with the preset signal quality evaluation parameter and judging whether the return signal is usable based on the comparison result. This quality evaluation mechanism can timely identify and filter out the return signal that does not meet the quality requirements, avoid using low-quality or severely interfered return signals for subsequent analysis, and thus improve the reliability of the detection results.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of determining the location information and depth information of the pipeline in the underground structure image, the method further includes: drawing a pipeline distribution map based on the location information and depth information of the pipeline; and sending the pipeline distribution map to a user.

[0019] By adopting the above technical solution, after determining the location information and depth information of the pipeline, the detection device further draws a pipeline distribution map and sends it to the user, which greatly improves the visualization and practicality of the detection results. The pipeline distribution map intuitively displays the spatial layout and depth distribution of underground pipelines, allowing users to quickly and accurately understand the overall situation of underground pipelines. By sending the distribution map to the user, the timely sharing and effective use of the detection results are achieved, and the efficiency of information transmission is improved.

[0020] In a second aspect, an embodiment of the present application provides a detection device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the detection device to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, and when the above-mentioned computer program product runs on a detection device, the above-mentioned detection device executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a detection device, enable the detection device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the detection device provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Due to the use of a detection method that combines multi-frequency electromagnetic wave signals with acoustic response analysis, and the use of a geological material spectrum database for underground structure identification, the present invention can more accurately determine the underground structure and material distribution in a complex geological environment, effectively solving the problem that the single-frequency detection method in the prior art is difficult to cope with complex geological conditions, thereby achieving high precision and high reliability in ultra-deep underground pipeline detection. This innovative detection method not only increases the detection depth, but also significantly enhances the ability to identify different types of geological materials, making it possible to accurately locate pipelines in complex strata that were previously difficult to accurately detect.

[0025] 2. Due to the use of signal propagation path simulation and adaptive signal optimization technology based on the underground three-dimensional model, the present invention can dynamically adjust the phase and power of the detection signal according to specific geological conditions, effectively solving the problem in the prior art that the detection signal is susceptible to interference and attenuation when propagating in deep layers, thereby realizing efficient transmission and reception of the detection signal. This intelligent signal processing method significantly improves the adaptability of the detection device to complex geological environments, allowing the detection signal to penetrate deeper strata and maintain a good signal-to-noise ratio. By accurately simulating and optimizing the detection signal, the present invention not only improves the depth and accuracy of detection, but also enhances the anti-interference ability of the detection device, providing a reliable technical guarantee for the accurate positioning of ultra-deep underground pipelines.

[0026] 3. Due to the use of time-reversal mirror technology to process the return signal and the combination of a high-quality signal screening mechanism, the present invention can effectively extract weak deep reflection signals and reconstruct high-resolution underground structure images, effectively solving the problems of deep signal processing difficulty and low imaging quality in the prior art, thereby achieving precise positioning and visualization of ultra-deep underground pipelines. This advanced signal processing and imaging technology not only improves the accuracy of the detection results, but also greatly improves the clarity and detail of the underground structure images. By generating high-quality pipeline distribution maps and delivering them to users in a timely manner, the present invention greatly enhances the practicality and decision-making support capabilities of the detection results, and provides more reliable and intuitive information support for the planning, construction and maintenance of underground pipelines. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the ultra-deep underground pipeline detection method in the embodiment of the present application; Figure 2 is another flow chart of the ultra-deep underground pipeline detection method in the embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of the detection device in the embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] The following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of the ultra-deep underground pipeline detection method in an embodiment of the present application.

[0031] S101, after transmitting a multi-frequency electromagnetic wave signal underground, receiving an acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground; Among them, the detection device refers to the equipment used to perform ultra-deep underground pipeline detection tasks, including signal transmitters, receivers and data processing units. Multi-frequency electromagnetic wave signals refer to electromagnetic wave signals of different frequencies, which are used to detect underground structures. Acoustic response refers to the sound wave signal generated by the interaction of electromagnetic wave signals with different geological materials during underground propagation, which is used to reflect the characteristics of underground structures.

[0032] The detection device performs this step when it starts to perform the ultra-deep underground pipeline detection task. Specifically, the detection device first transmits a pre-designed multi-frequency electromagnetic wave signal to the underground through a signal transmitter. These multi-frequency electromagnetic wave signals may include low frequency, medium frequency and high frequency to meet the detection needs of different depths and geological materials. During the underground propagation process, the electromagnetic wave signal interacts with various geological structures and geological materials to produce acoustic responses. The detection device receives these acoustic responses through multiple high-sensitivity sensors arranged on the surface. The received acoustic responses will be recorded and transmitted to the data processing unit to provide raw data for subsequent analysis.

[0033] Optionally, in general, after transmitting a multi-frequency electromagnetic wave signal underground, receiving the acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground can be achieved in the following way: extracting multiple acoustic responses by analyzing the received signals of multiple distributed sensors; and determining the emission positions of multiple acoustic responses based on the setting positions of multiple distributed sensors.

[0034] S102, determining the underground geological structure based on a preset geological material spectrum database and the frequency domain characteristics of the acoustic response, wherein the geological material spectrum database includes characteristic responses of various geological materials under the action of electromagnetic wave signals of different frequencies, and the underground geological structure is used to represent the composition and distribution of underground geological materials; Among them, the geological material spectrum database refers to a pre-established data set containing the characteristic features of various geological materials under the action of electromagnetic wave signals of different frequencies. The frequency domain characteristics represent the characteristics of the acoustic response in the frequency dimension, including frequency distribution, spectral peak position and intensity, etc. The underground geological structure refers to the spatial distribution and organizational form of various geological materials in the underground space. The characteristic response represents the unique acoustic signal pattern generated by a specific geological material when it is excited by an electromagnetic wave signal.

[0035] The detection device executes this step immediately after receiving the acoustic response. Specifically, the detection device first performs time-frequency analysis on the received acoustic response to extract its frequency domain characteristics. Then, the detection device compares and matches the extracted frequency domain characteristics with the characteristic responses in the preset geological material spectrum database. Through this comparison, the detection device can identify the geological material corresponding to the acoustic response. Combining the analysis results of multiple receiving points, the detection device further infers the spatial distribution of underground geological materials, thereby constructing a complete underground geological structure. The underground geological structure includes not only the types of various geological materials, but also information such as their spatial position, thickness and distribution range.

[0036] S103, simulating the underground propagation path of the multi-frequency electromagnetic wave signal according to the underground geological structure; The propagation path refers to the trajectory of the electromagnetic wave signal from the transmitting point to the receiving point in the underground space. Simulation means predicting the propagation behavior of the electromagnetic wave signal in the complex geological structure by computer simulation.

[0037] The detection device performs this step after determining the underground geological structure. Specifically, the detection device first constructs an accurate underground three-dimensional model based on the determined underground geological structure. This underground three-dimensional model contains the electromagnetic characteristic parameters of various geological materials, such as dielectric constant, conductivity, etc. Then, the detection device simulates the propagation process of multi-frequency electromagnetic wave signals in this underground three-dimensional model. During the simulation, the detection device considers the propagation speed, attenuation characteristics, reflection and refraction behavior of electromagnetic wave signals of different frequencies in various geological materials. By changing the incident angle and incident position of the electromagnetic wave signal, the detection device can obtain multiple possible propagation paths. For each propagation path, the detection device calculates key parameters such as phase change, energy loss and arrival time of the electromagnetic wave signal. Finally, the detection device generates a detailed propagation path map showing the propagation trajectory and characteristics of electromagnetic wave signals of different frequencies in complex geological structures.

[0038] Optionally, in general, simulating the propagation path of multi-frequency electromagnetic wave signals underground according to the underground geological structure can be achieved in the following way: constructing an underground three-dimensional model based on the underground geological structure; after transmitting simulated multi-frequency electromagnetic wave signals to the underground three-dimensional model at different incident points and incident angles, receiving the phase, amplitude and arrival time of the simulated multi-frequency electromagnetic wave signals through simulated sensors in the underground three-dimensional model; calculating the propagation paths of electromagnetic wave signals of different frequencies in the underground three-dimensional model according to the phase, amplitude and arrival time of the simulated multi-frequency electromagnetic wave signals.

[0039] S104, performing phase adjustment and power adjustment on the multi-frequency electromagnetic wave signal according to the propagation path to obtain a composite detection signal; Phase adjustment refers to the correction of the phase of the electromagnetic wave signal to compensate for the phase distortion caused by the geological medium during the propagation process. Power adjustment refers to the redistribution of the energy of electromagnetic wave signals of different frequencies to compensate for the propagation loss. Composite detection signal refers to the multi-frequency electromagnetic wave signal after optimization and adjustment.

[0040] The detection device performs this step immediately after simulating the propagation path. Specifically, the detection device first analyzes the simulated propagation path and calculates the phase shift and energy loss of electromagnetic wave signals of different frequencies during the propagation process. For phase adjustment, the detection device calculates the corresponding phase compensation value for each frequency component (following the example in step S101, such as low frequency, medium frequency and high frequency) to ensure that the electromagnetic wave signal can maintain good coherence when reaching the target depth. In terms of power adjustment, the detection device will increase the power of low-frequency electromagnetic wave signals required for deep detection according to the attenuation characteristics of electromagnetic wave signals of different frequencies, and appropriately reduce the power of high-frequency electromagnetic wave signals that are easily attenuated. The detection device implements these adjustments through digital signal processing technology, and may use methods such as adaptive filters or digital phase shifters. The adjusted electromagnetic wave signals of each frequency are synthesized into a new composite detection signal. The verification detection signal has stronger penetration ability and higher signal-to-noise ratio, which can effectively improve the accuracy and reliability of ultra-deep pipeline detection.

[0041] Optionally, under normal circumstances, the phase adjustment and power adjustment of the multi-frequency electromagnetic wave signal according to the propagation path to obtain a composite detection signal can be achieved in the following way: based on the propagation path, the propagation loss of electromagnetic wave signals of different frequencies and the phase shift generated by electromagnetic wave signals of different frequencies during the propagation process are calculated; according to the phase shift, the phase compensation of the multi-frequency electromagnetic wave signal is performed; according to the propagation loss, the transmission power of the multi-frequency electromagnetic wave signal is amplified; and the composite detection signal is obtained by synthesizing the electromagnetic wave signals of each frequency after phase adjustment and power adjustment.

[0042] S105, after transmitting the composite detection signal underground, receiving a return signal; The return signal refers to the signal that returns to the surface after the composite detection signal propagates underground and interacts with various geological structures and pipelines, and contains information about the location of underground structures and pipelines.

[0043] The detection device performs this step after obtaining the optimized composite detection signal. Specifically, the detection device first transmits the composite detection signal underground through the signal transmitter. During the underground propagation process, the composite detection signal will have complex interactions with different geological layers, groundwater, cavities and target pipelines, including reflection, refraction, scattering, etc. The detection device captures these return signals through multiple high-sensitivity receivers arranged on the surface. The receiver may use broadband receiving technology to ensure that the return signal containing all frequency components can be captured. The received return signal will be amplified, filtered, and converted into a digital signal through a high-speed analog-to-digital converter. The detection device will record the amplitude, phase, arrival time and other characteristics of these return signals to provide raw data for subsequent signal processing and image reconstruction.

[0044] S106, processing the return signal by using a time reversal mirror technology to generate an underground structure image, where the underground structure image is used to visualize the underground space; Among them, time reversal mirror technology refers to a signal processing method that focuses and enhances the target echo by inverting and retransmitting the signal in the time domain. The underground structure image represents a two-dimensional or three-dimensional visualization of the underground space reconstructed by processing the return signal, which is used to intuitively display the underground geological structure and possible pipeline locations.

[0045] The detection device performs this step after receiving the return signal. Specifically, the detection device first pre-processes the received return signal, including denoising, spectrum analysis, etc. Then, the detection device applies the time reversal mirror algorithm to process these return signals. In this process, the return signal is reversed in the time domain and virtually re-transmitted in the computer model. This processing can effectively focus the scattered signal and enhance the echo from a specific target (such as a pipeline). The detection device may use multiple iterations of the time reversal process to further improve the image quality. The processed return signal is used to reconstruct the underground structure image, and synthetic aperture technology or beamforming algorithms may be used to improve the image resolution. The generated underground structure image can be a two-dimensional profile or a three-dimensional stereogram, clearly showing the geological structure at different depths, possible cavities or aquifers, and potential pipeline locations. The detection device may use pseudo-color technology to enhance the visualization of different structures for easy identification and interpretation.

[0046] S107: Determine the position information and depth information of the pipeline in the underground structure image.

[0047] The location information refers to the coordinates or relative position of the pipeline on the horizontal plane. The depth information indicates the vertical distance of the pipeline or the depth of the stratum where the pipeline is buried. The pipeline refers to various pipes, cables or other linear facilities buried underground.

[0048] The detection device performs this step immediately after generating the underground structure image. Specifically, the detection device first performs image analysis and feature extraction on the generated underground structure image, which involves the use of computer vision algorithms, such as edge detection, shape recognition, etc., to identify linear or circular structures in the underground structure image that may represent pipelines. The detection device will consider the electromagnetic properties of the pipeline material and analyze the reflection intensity and reflection pattern in the underground structure image to distinguish between pipelines and other geological structures. For the identified potential pipelines, the detection device will accurately calculate its pixel coordinates in the underground structure image and convert them into actual geographic coordinates or relative position information. The depth information is calculated by analyzing the round-trip time of the signal and the propagation speed of underground electromagnetic waves. The detection device may use multi-perspective or multi-frequency data fusion technology to improve the accuracy of position and depth measurement. Finally, the detection device determines the location information and depth information of the pipeline in the underground structure image.

[0049] The detection device determines the underground geological structure by emitting multi-frequency electromagnetic wave signals and receiving the acoustic response generated by them, combined with the preset geological material spectrum database. By simulating the propagation path of multi-frequency electromagnetic wave signals underground and performing phase and power adjustments, a composite detection signal is generated. The detection device transmits the composite detection signal and uses time reversal mirror technology to process the return signal, and finally determines the location information and depth information of the pipeline in the generated underground structure image. This method comprehensively utilizes multi-frequency electromagnetic wave signals, acoustic response analysis, geological material characteristics and signal processing technology, which can effectively improve the accuracy and reliability of ultra-deep underground pipeline detection. It is especially suitable for ultra-deep pipeline detection under complex geological conditions. It can overcome the limitations of traditional methods in depth and accuracy, and provide more accurate information support for underground pipeline planning, construction and maintenance.

[0050] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the ultra-deep underground pipeline detection method in the embodiment of the present application.

[0051] S201, after transmitting a multi-frequency electromagnetic wave signal underground, receiving an acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground; For details, please refer to step S101, which will not be described in detail here.

[0052] S202, performing time-frequency analysis on the acoustic response to obtain a time-frequency characteristic graph; Among them, acoustic response refers to the vibration or reflection signal generated by underground pipelines or other underground structures after being stimulated by sound waves. Time-frequency analysis refers to a signal processing technology that is used to simultaneously analyze the characteristic changes of signals in the time domain and frequency domain. The time-frequency characteristic graph refers to a graph that comprehensively displays the three dimensions of time, frequency and signal strength, usually using color or grayscale to represent the signal strength.

[0053] The detection device performs this step after receiving the acoustic response signal. Specifically, the detection device first preprocesses the received acoustic response, including operations such as denoising, signal enhancement and digitization. Then, the detection device selects a suitable time-frequency analysis method, such as short-time Fourier transform (STFT), wavelet transform or Wigner-Ville distribution. Taking STFT as an example, the detection device divides the entire acoustic response into multiple overlapping short-time windows, performs Fourier transform on each window, and obtains the spectrum information within the time period. The detection device carefully selects the size and overlap of the time window to strike a balance between time resolution and frequency resolution. During the transformation process, the detection device may apply different window functions (such as Hanning window or Gaussian window) to reduce spectral leakage. For nonlinear or rapidly changing signals, the detection device may select more advanced time-frequency analysis methods, such as wavelet packet transform or adaptive time-frequency analysis, to capture the transient characteristics of the signal. After completing the time-frequency transformation, the detection device will generate a time-frequency feature map, which usually uses time as the horizontal axis and frequency as the vertical axis, and uses color depth or brightness to represent the energy distribution at different time and frequency points. The detection device may apply various image enhancement techniques, such as contrast adjustment, pseudo-color mapping, etc., to highlight key features.

[0054] S203, extracting frequency domain characteristics of the acoustic response based on the time-frequency characteristic graph, where the frequency domain characteristics include frequency distribution, spectrum peak position, and spectrum peak intensity; Among them, frequency domain characteristics refer to various features and properties in the frequency dimension. Frequency distribution refers to the distribution of signal energy in different frequency ranges. Spectral peak position refers to the frequency point where energy is concentrated in the spectrum. Spectral peak intensity refers to the amplitude or relative intensity of these energy concentration points.

[0055] The detection device executes this step immediately after obtaining the time-frequency feature map. Specifically, the detection device first performs digital image processing on the time-frequency feature map, including filtering, edge enhancement and other operations, so as to more accurately extract the frequency domain characteristics. Then, the detection device uses a peak detection algorithm to identify the position of the spectrum peak, which may involve setting thresholds, local maximum search and other technologies. For each detected spectrum peak, the detection device records its frequency position and corresponding intensity value. In order to obtain the frequency distribution, the detection device may integrate or average the time-frequency feature map in the frequency dimension to obtain a spectrum overview during the entire observation time. The detection device may use statistical methods to describe the frequency distribution, such as calculating parameters such as the center frequency, bandwidth, skewness and kurtosis of the spectrum. During the extraction process, the detection device pays special attention to the characteristic frequency range related to the pipeline material and structure, and may assign different weights to different frequency bands based on the pre-existing knowledge base. In addition, the detection device may also analyze the changes in frequency domain characteristics over time, such as the drift or attenuation of the spectrum peak, which may reflect certain dynamic characteristics of the pipeline or the influence of the surrounding environment. Finally, the detection device will organize the extracted frequency domain characteristics into structured data, including the frequency-intensity pairs of the main spectral peaks, the statistical description of the frequency distribution, the energy proportion of the characteristic frequency bands, etc., providing important basis for subsequent pipeline identification and status assessment.

[0056] S204, determining the underground geological structure based on a preset geological material spectrum database and the frequency domain characteristics of the acoustic response, wherein the geological material spectrum database includes characteristic responses of various geological materials under the action of electromagnetic wave signals of different frequencies, and the underground geological structure is used to represent the composition and distribution of underground geological materials; For details, please refer to step S101, which will not be described in detail here.

[0057] S205, simulating the underground propagation path of the multi-frequency electromagnetic wave signal according to the underground geological structure; For details, please refer to step S101, which will not be described in detail here.

[0058] S206, performing phase adjustment and power adjustment on the multi-frequency electromagnetic wave signal according to the propagation path to obtain a composite detection signal; For details, please refer to step S101, which will not be described in detail here.

[0059] S207, after transmitting the composite detection signal underground, receiving a return signal; For details, please refer to step S101, which will not be described in detail here.

[0060] S208, comparing the quality index of the returned signal with a preset signal quality evaluation parameter to determine whether the quality of the returned signal meets a preset condition; The return signal refers to the acoustic or electromagnetic wave signal reflected from the underground structure. The quality index refers to various numerical parameters used to evaluate the quality of the return signal, such as signal-to-noise ratio, bandwidth, dynamic range, etc. The preset signal quality evaluation parameter refers to a predetermined standard value or threshold used to determine whether the return signal is usable. The preset condition means that the quality of the return signal needs to meet the minimum requirements of the preset signal quality evaluation parameter, which is usually a set of thresholds or rules.

[0061] The detection device performs this step after receiving and preliminarily processing the return signal. Specifically, the detection device first calculates various quality indicators of the return signal, which may include: signal-to-noise ratio (SNR), which is calculated by comparing the return signal energy with the background noise energy; bandwidth, which is determined by analyzing the spectrum range of the return signal; dynamic range, which is obtained by measuring the ratio between the maximum value of the return signal and the minimum detectable value. The detection device may also calculate indicators such as peak amplitude, average power, and coherence of the return signal. Then, the detection device compares these calculated quality indicators with preset signal quality evaluation parameters one by one. The preset parameters may come from industry standards, equipment specifications, or experience-based set values. For example, the signal-to-noise ratio may need to be higher than 15dB, the bandwidth needs to reach more than 80% of the rated bandwidth of the detection device, and the dynamic range is required to exceed 60dB. The detection device may use a weighted scoring method to assign different weights to different quality indicators, and then calculate the overall score. Finally, the detection device determines whether the return signal meets the preset conditions based on the comparison results. This judgment may be binary (satisfied / not satisfied) or multi-level (excellent / good / qualified / unqualified).

[0062] S209: If not satisfied, determine that the returned signal is an unavailable signal; Among them, "unsatisfactory" means that the quality index of the return signal does not meet the minimum requirement of the preset signal quality evaluation parameter. "Unusable signal" means the quality is lower than the acceptable standard and cannot be used for subsequent analysis and processing of the return signal.

[0063] The detection device executes this step immediately after completing the signal quality assessment and determining that the return signal does not meet the preset conditions. Specifically, the detection device will first reconfirm the determination result and may perform a secondary check to eliminate the possibility of misjudgment. If it is confirmed that the return signal does not meet the quality requirements, the detection device will mark the return signal as "unavailable". This marking process may include adding a specific flag bit to the data file, or moving the signal data to a data area specifically for storing low-quality signals.

[0064] S210, processing the return signal by using a time reversal mirror technology to generate an underground structure image, where the underground structure image is used to visually represent the underground space; For details, please refer to step S101, which will not be described in detail here.

[0065] S211, determining the position information and depth information of the pipeline in the underground structure image; For details, please refer to step S101, which will not be described in detail here.

[0066] S212, drawing a pipeline distribution map according to the location information and depth information of the pipeline; Among them, location information refers to the horizontal position data of the pipeline in the plane coordinate system, usually including longitude and latitude or x, y coordinates in the local coordinate system. Depth information represents the vertical distance of the buried pipeline, that is, the distance from the surface to the top of the pipeline. Pipeline distribution map refers to a graphic used to intuitively display the spatial distribution of underground pipelines, including plane layout and vertical section. Drawing refers to the use of computer graphics technology to convert digitized location information and depth information into a visual graphic representation.

[0067] The detection device performs this step after completing the calculation of the location information and depth information of the pipeline. Specifically, the detection device will first organize and verify all the obtained location information and depth information to ensure the integrity and consistency of the data. This may include the detection and processing of outliers, such as data points that are obviously deviated, which may need to be re-verified or eliminated. Then, the detection device will select appropriate drawing software or graphics library, commonly used ones may include AutoCAD, ArcGIS or custom drawing modules. The detection device will first draw a plan, usually with a map or aerial image of the detection area as the base map, and then superimpose the horizontal location information of the pipeline on it. In the plan, the detection device may use different line types, colors or symbols to distinguish pipelines of different types or depths. For complex pipeline networks, the detection device may use layered display technology to allow users to selectively view pipelines of specific types or depth ranges. Next, the detection device will draw a vertical profile as needed, which usually includes selecting key profile lines, and then drawing the vertical distribution of the pipeline based on the intersection of the pipeline with these profile lines and their corresponding depth information. In the cross-section diagram, the detection device may add geological layer information to show the relationship between the pipeline and the stratum. Finally, the detection device draws a complete pipeline distribution map.

[0068] S213: Send the pipeline distribution map to the user.

[0069] Transmission refers to the process of transmitting data to a designated recipient through a network or other communication methods. A user refers to an individual or organization that operates a detection device or needs to receive a pipeline distribution map, which may include engineers, planners, or relevant decision makers.

[0070] The detection device performs this step immediately after completing the drawing and quality inspection of the pipeline distribution map. Specifically, the detection device first determines the format of sending the pipeline distribution map based on the preset user preferences or pre-settings, which may include common image formats such as PNG, JPEG, vector graphics formats such as SVG, DXF, or professional GIS data formats such as Shapefile, GeoJSON, etc. The detection device may prepare files in multiple formats to meet the needs of different users.

[0071] Next, the detection device will select an appropriate transmission method, which may include direct transmission through the internal network, uploading to a designated cloud storage service, sending via email, or using a dedicated data sharing platform. The detection device will consider the security of the data and may encrypt the file or use a secure transmission protocol such as HTTPS, SFTP, etc.

[0072] The implementation of this method, due to the use of a detection method combining multi-frequency electromagnetic wave signals with acoustic response analysis, and the use of a geological material spectrum database for underground structure identification, the present invention can more accurately determine the underground structure and material distribution under complex geological environments, effectively solving the problem that the single frequency detection method in the prior art is difficult to cope with complex geological conditions, thereby achieving high precision and high reliability in ultra-deep underground pipeline detection. This innovative detection method not only improves the detection depth, but also significantly enhances the ability to identify different types of geological materials, so that pipelines can be accurately located in complex strata that were previously difficult to accurately detect. Due to the use of signal propagation path simulation and adaptive signal optimization technology based on underground three-dimensional models, the present invention can dynamically adjust the phase and power of the detection signal according to specific geological conditions, effectively solving the problem that the detection signal in the prior art is susceptible to interference and attenuation when propagating in deep layers, thereby achieving efficient transmission and reception of the detection signal. This intelligent signal processing method significantly improves the adaptability of the detection device to complex geological environments, allowing the detection signal to penetrate deeper strata and maintain a good signal-to-noise ratio. By accurately simulating and optimizing the detection signal, the present invention not only improves the depth and accuracy of detection, but also enhances the anti-interference ability of the detection device, providing a reliable technical guarantee for the accurate positioning of ultra-deep underground pipelines. Due to the use of time reversal mirror technology to process the return signal and combined with a high-quality signal screening mechanism, the present invention can effectively extract weak deep reflection signals and reconstruct high-resolution underground structure images, effectively solving the problems of deep signal processing difficulty and low imaging quality in the prior art, thereby achieving accurate positioning and visualization of ultra-deep underground pipelines. This advanced signal processing and imaging technology not only improves the accuracy of the detection results, but also greatly improves the clarity and detail of the underground structure image. By generating high-quality pipeline distribution maps and delivering them to users in a timely manner, the present invention greatly enhances the practicality and decision-making support capabilities of the detection results, and provides more reliable and intuitive information support for the planning, construction and maintenance of underground pipelines.

[0073] The following describes the detection device in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of a detection device in an embodiment of the present application.

[0074] It should be noted that Figure 3 The structure of the detection device shown is only an example and should not bring any limitation to the function and scope of use of the embodiment of the present invention.

[0075] like Figure 3As shown, the detection device includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, the ROM 302 and the RAM 303 are connected to each other through the bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0076] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0077] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0078] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0079] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0080] Specifically, the detection device of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the ultra-deep underground pipeline detection method provided by the above embodiment is implemented.

[0081] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the detection device described in the above embodiment; or may exist independently without being assembled into the detection device. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the detection device, the detection device implements the ultra-deep underground pipeline detection method provided in the above embodiment.

[0082] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0083] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0084] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for detecting ultra-deep underground pipelines, characterized in that: Applied to a detection device, the method comprises: After transmitting a multi-frequency electromagnetic wave signal underground, receiving an acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground; Determine the underground geological structure based on a preset geological material spectrum database and the frequency domain characteristics of the acoustic response, wherein the geological material spectrum database includes characteristic responses of various geological materials under the action of electromagnetic wave signals of different frequencies, and the underground geological structure is used to represent the composition and distribution of underground geological materials; Simulating the underground propagation path of the multi-frequency electromagnetic wave signal according to the underground geological structure; Performing phase adjustment and power adjustment on the multi-frequency electromagnetic wave signal according to the propagation path to obtain a composite detection signal; After transmitting the composite detection signal underground, receiving a return signal; Processing the return signal by time reversal mirror technology to generate an underground structure image, wherein the underground structure image is used to visually represent the underground space; The position information and depth information of the pipeline are determined in the underground structure image.

2. The method according to claim 1, characterized in that After transmitting the multi-frequency electromagnetic wave signal underground, receiving the acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground specifically includes: By analyzing the received signals of multiple distributed sensors, multiple acoustic responses are extracted; The emission positions of the plurality of acoustic responses are determined according to the arrangement positions of the plurality of distributed sensors.

3. The method according to claim 2, characterized in that After the step of receiving the acoustic response generated by the multi-frequency electromagnetic wave signal propagating underground after transmitting the multi-frequency electromagnetic wave signal underground, the method further includes: Performing time-frequency analysis on the acoustic response to obtain a time-frequency characteristic graph; Based on the time-frequency feature graph, frequency domain characteristics of the acoustic response are extracted, and the frequency domain characteristics include frequency distribution, spectrum peak position and spectrum peak intensity.

4. The method according to claim 1, characterized in that The simulating the underground propagation path of the multi-frequency electromagnetic wave signal according to the underground geological structure specifically includes: Based on the underground geological structure, construct an underground three-dimensional model; After emitting simulated multi-frequency electromagnetic wave signals to the underground three-dimensional model at different incident points and incident angles, receiving the phase, amplitude and arrival time of the simulated multi-frequency electromagnetic wave signals through a simulated sensor in the underground three-dimensional model; The propagation paths of electromagnetic wave signals of different frequencies in the underground three-dimensional model are calculated according to the phase, amplitude and arrival time of the simulated multi-frequency electromagnetic wave signal.

5. The method according to claim 4, characterized in that The phase adjustment and power adjustment of the multi-frequency electromagnetic wave signal according to the propagation path to obtain a composite detection signal specifically includes: Based on the propagation path, calculating the propagation loss of electromagnetic wave signals of different frequencies and the phase shift generated by the electromagnetic wave signals of different frequencies during the propagation process; performing phase compensation on the multi-frequency electromagnetic wave signal according to the phase shift; amplifying the transmission power of the multi-frequency electromagnetic wave signal according to the propagation loss; The composite detection signal is obtained by synthesizing the electromagnetic wave signals of each frequency after phase adjustment and power adjustment.

6. The method according to claim 1, characterized in that After the step of receiving a return signal after transmitting the composite detection signal underground, the method further comprises: Compare the quality index of the returned signal with a preset signal quality evaluation parameter to determine whether the quality of the returned signal meets a preset condition; If not, the returned signal is determined to be an unavailable signal.

7. The method according to claim 1, characterized in that After the step of determining the position information and depth information of the pipeline in the underground structure image, the method further includes: Draw a pipeline distribution map according to the position information and depth information of the pipeline; The pipeline distribution map is sent to a user.

8. A detection device, characterized in that: The detection device includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the detection device to execute the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on the detection device, the detection device is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a detection device, the detection device is caused to execute the method according to any one of claims 1 to 7.

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