A complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic wave signals

Abstract

This invention discloses a method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals, belonging to the field of buried pipeline inspection technology. The method includes acquiring acoustic signals generated by pipeline vibration excitation; determining the horizontal orientation of the pipeline based on amplitude attenuation characteristics; distinguishing normal pipeline segments from complex pipeline segments based on resonant frequency distribution; constructing an elliptical geometric model and calculating the pipeline's burial depth; and generating a visualized image containing pipeline direction, burial depth, and pipeline type identification. This invention achieves integrated high-precision positioning and visualization of complex buried PE pipelines, enabling automatic identification and differentiation of complex pipeline segments such as tees and elbows from normal straight pipe segments. It fundamentally avoids measurement errors caused by changes in soil characteristics, transforming abstract professional detection data into easily understandable visual results, and providing a reliable, efficient, and intelligent complete solution for the refined inspection and management of buried PE pipelines under complex working conditions.

Description

Technical Field

[0001] This invention relates to the field of buried pipeline inspection technology, and in particular to a method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals. Background Technology

[0002] Buried PE pipelines, due to their excellent corrosion resistance, impact resistance, and long service life, have become a core component of urban gas transmission and water supply systems. With the acceleration of urbanization, underground pipeline networks are becoming increasingly dense and complex, placing higher demands on the accurate positioning and condition assessment of buried pipelines. As a non-metallic material, PE pipeline positioning has become a recognized technical challenge in the industry. Positioning technologies for buried PE pipelines mainly include the following: Electromagnetic tracer method: This method involves simultaneously burying a metal tracer line during the laying of the PE pipeline. By applying a specific frequency electromagnetic signal to the tracer line, the distribution of the electromagnetic field on the ground is received to determine the pipeline's direction. However, the tracer line is prone to breakage or poor contact due to construction damage, soil corrosion, and geological subsidence, leading to signal interruption or attenuation and poor reliability of the detection results. Ground penetrating radar method: This method utilizes the reflection characteristics of high-frequency electromagnetic waves in underground media. By analyzing the time and amplitude of the echo signal, underground targets are imaged and located. While non-contact detection is possible, it is significantly affected by geological conditions: electromagnetic waves attenuate rapidly in soils with high water content, high clay content, or uneven density; the interpretation of radar images is highly dependent on the operator's experience, and its ability to identify complex pipelines such as tees and elbows is limited, making it difficult to meet the needs of precise positioning; radio frequency identification (RFID) involves embedding electronic tags at key nodes of the pipeline, but the positioning accuracy of this method is limited by the density of the tags, and the electronic tags are buried underground in a humid and corrosive environment for a long time, resulting in high maintenance costs and making it unsuitable for continuous positioning of large-scale, long-distance pipelines; traditional acoustic positioning methods utilize sound wave signals generated by striking the pipeline or the flow of the medium inside the pipe, but time-domain methods require high precision in identifying the signal starting point and are easily affected by environmental noise; although frequency-domain methods can reflect the frequency response characteristics of the medium, existing acoustic technologies lack the ability to identify complex pipeline structures, cannot distinguish between normal straight pipe sections and irregular pipe sections, and cannot achieve a visual representation of the pipeline route, making it difficult to meet the needs of refined management of modern urban pipe networks.

[0003] However, current common solutions have many drawbacks, including: the electromagnetic tracer method for locating buried PE pipelines relies on pre-buried and easily broken metal wires, which is completely ineffective for pipelines that are not pre-buried; the ground penetrating radar method is significantly affected by soil moisture content and geological conditions, with rapid signal attenuation and unstable imaging resolution; the radio frequency identification method can only achieve discrete point positioning, and the electronic tags are at risk of failure if buried for a long time; traditional acoustic methods mostly use single time domain or frequency domain analysis, which is not only susceptible to environmental noise interference, but also cannot effectively identify complex pipeline structures such as tees and elbows, and lacks visualization capabilities. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the problems existing in the current method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals, this invention is proposed.

[0006] Therefore, the purpose of this invention is to provide a method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals. This method is applicable to solving the problems of existing buried PE pipeline location technologies, such as electromagnetic tracer line method which relies on pre-buried and easily broken metal wires and is completely ineffective for pipelines that are not pre-buried; ground penetrating radar method which is significantly affected by soil moisture content and geological conditions, with rapid signal attenuation and unstable imaging resolution; radio frequency identification method which can only achieve discrete point location, and the risk of failure of electronic tags buried for a long time; and traditional acoustic methods which mostly use single time-domain or frequency-domain analysis, which are not only easily affected by environmental noise, but also cannot effectively identify complex pipeline structures such as tees and elbows, and lack visualization capabilities.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals. This method includes deploying multiple acoustic sensors on the soil surface above the buried PE pipeline to collect acoustic signals generated by pipeline vibration; performing frequency domain transformation analysis on the collected acoustic signals to obtain the attenuation characteristics and resonant frequency distribution of the signal amplitude; locking the horizontal orientation of the pipeline based on the amplitude attenuation characteristics; and distinguishing normal pipeline segments from complex pipeline segments based on the resonant frequency distribution; performing cross-correlation processing on the collected time-domain signals to extract the time delay characteristics of the signals reaching different sensors; constructing an elliptical geometric model and calculating the burial depth of the pipeline based on the time delay characteristics and the geometrical positional relationship of the sensors; and fusing the pipeline type information obtained in the frequency domain analysis and positioning step with the pipeline spatial location information obtained in the time domain analysis and positioning step to construct a three-dimensional surface model of the pipeline and generate a visualized image containing the pipeline direction, burial depth, and pipeline type identification.

[0008] As a preferred embodiment of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals described in this invention, the method involves: when performing frequency domain transformation analysis on the collected acoustic signals, constructing a coupled wave equation between the pipeline and the viscoelastic soil medium, and solving its frequency domain analytical solution through Fourier transform to quantify the exponential decay law of the acoustic amplitude with the propagation distance.

[0009] As a preferred embodiment of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals described in this invention, the method involves: when performing cross-correlation processing on the acquired time-domain signals, three sensors are equidistantly arranged above the pipeline to collect time-domain vibration signals; pairwise cross-correlation analysis is performed on the three signals, and when the signal delay time between the two side sensors is zero, it is determined that the middle sensor is located directly above the pipeline; with the middle sensor and one side sensor as the focus, and combined with the calculated signal arrival time delay of the two sensors, an ellipse equation is established and solved to quantitatively calculate the burial depth of the pipeline.

[0010] As a preferred embodiment of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals described in this invention, the following steps are taken: when constructing the three-dimensional surface model of the pipeline, the complex pipeline is divided into a main pipeline and branch pipelines. The surface of the main pipeline is constructed using cylindrical coordinate system parametric equations, and the surface of the branch pipelines is constructed using translational coordinate system parametric equations. On the constructed surface model, different visual identifiers are assigned to normal pipeline segments, elbows, and tees based on the identified pipeline type, so that they can be clearly distinguished in the visualized image.

[0011] As a preferred embodiment of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals described in this invention, the frequency domain analysis, time domain analysis, and visualization imaging steps are executed in a data interaction development platform. This platform calls signal processing tools through built-in script nodes to realize real-time interaction and processing between sensor hardware data acquisition and each analysis step, and dynamically displays the pipeline position pointer, depth value, and visualization image on the system front panel.

[0012] As a preferred embodiment of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals described in this invention, the system front panel determines the pipeline position by pointer offset and indicator light color, and displays the pipeline depth value below the dial.

[0013] As a preferred embodiment of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals described in this invention, the complex pipeline segment includes tee pipes and elbow pipes.

[0014] Secondly, to further address the aforementioned technical problems, this invention provides a complex buried PE pipeline positioning system based on time-frequency domain fusion of acoustic signals. The system includes: a signal acquisition module for deploying multiple acoustic sensors on the soil surface above the buried PE pipeline to acquire acoustic signals generated by pipeline vibration; a frequency domain analysis module for performing frequency domain transformation analysis on the acquired acoustic signals to obtain the attenuation characteristics and resonant frequency distribution of the signal amplitude, locking the horizontal orientation of the pipeline based on the amplitude attenuation characteristics, and distinguishing normal pipeline segments from complex pipeline segments based on the resonant frequency distribution; a time domain analysis module for performing cross-correlation processing on the acquired time domain signals to extract the time delay characteristics of the signals arriving at different sensors, constructing an elliptical geometric model based on the time delay characteristics and the geometrical positional relationship of the sensors, and calculating the burial depth of the pipeline; and an imaging display module for fusing the pipeline type information obtained from the frequency domain analysis positioning step and the pipeline spatial location information obtained from the time domain analysis positioning step to construct a three-dimensional curved surface model of the pipeline and generate a visual image containing the pipeline direction, burial depth, and pipeline type identification.

[0015] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals as described in the first aspect of the present invention.

[0016] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals as described in the first aspect of the present invention.

[0017] The beneficial effects of this invention are as follows: By constructing an innovative "time-frequency domain fusion" technical route, this invention achieves integrated high-precision positioning and visualization of complex buried PE pipelines. This method utilizes the attenuation characteristics of acoustic wave amplitude in the frequency domain to lock the horizontal orientation of the pipeline and innovatively introduces resonant frequency distribution as an "acoustic fingerprint," achieving for the first time automatic identification and differentiation between complex pipeline sections such as tees and elbows and normal straight pipe sections. Through the equidistant arrangement and cross-correlation analysis of three sensors, combined with an elliptical geometric model, quantitative calculation of burial depth independent of medium wave velocity is achieved, fundamentally avoiding measurement errors caused by changes in soil properties. This invention deeply integrates pipeline type information identified in the frequency domain with spatial location information calculated in the time domain, using cylindrical coordinate systems and translational coordinate systems as references. This invention constructs a three-dimensional surface model using numerical equations, generating a visualized image that includes pipeline direction, burial depth, and pipeline type identification. It is further enhanced with an intuitive interactive interface featuring pointer offset and indicator light colors, transforming abstract professional detection data into easily understandable visual results. This invention effectively overcomes multiple shortcomings of methods such as electromagnetic tracer line reliance on pre-buried facilities, ground-penetrating radar limitations due to geological conditions, and the inability of traditional acoustic methods to identify complex pipelines and their lack of visualization capabilities. It achieves a technological leap from "single-parameter detection" to "multi-dimensional information fusion," from "fuzzy anomaly judgment" to "precise structure identification," and from "professional waveform interpretation" to "intuitive image presentation," providing a reliable, efficient, and intelligent complete solution for the refined detection and management of buried PE pipelines under complex working conditions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart illustrating the implementation of the present invention in Example 1.

[0019] Figure 2 This is a schematic diagram of the elliptical geometric model of the present invention in Example 1. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1 Reference Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals, including the following steps: S1: Deploy multiple acoustic sensors on the soil surface above the buried PE pipeline to collect acoustic signals generated by pipeline vibration.

[0024] Preferably, the acoustic sensor is an accelerometer with a sensitivity of not less than 100mV / g and a frequency response range covering 10Hz-2000Hz, to ensure that it can effectively collect low-frequency acoustic signals generated by pipeline vibration. The deployment spacing of the sensor is determined according to the pipeline burial depth and soil conditions, and is generally set to 0.5m-1.5m.

[0025] Furthermore, the sensors are arranged in an equally spaced linear array to simultaneously acquire vibration signals from multiple points above the pipe in a single measurement. The length of the sensor array should cover the area where the pipe may exist, typically no less than 3m.

[0026] Furthermore, pipeline vibration excitation can be achieved in one of the following ways: (1) knocking on the end of the pipeline exposed above the ground to generate impact vibration; (2) using the natural flow noise of the medium flowing in the pipeline (such as water or gas) as the excitation source; (3) using a special excitation device to apply vibration of a specific frequency to the ground above the pipeline.

[0027] S2: Perform frequency domain transformation analysis on the collected acoustic signal to obtain the attenuation characteristics of the signal amplitude and the resonant frequency distribution. Based on the amplitude attenuation characteristics, locate the horizontal orientation of the pipeline and distinguish between normal pipeline sections and complex pipeline sections based on the resonant frequency distribution.

[0028] Preferably, when performing frequency domain transformation analysis on the collected acoustic signal, a coupled wave equation between the pipeline and the viscoelastic soil medium is constructed, and its frequency domain analytical solution is solved by Fourier transform to quantify the exponential decay law of the acoustic amplitude with the propagation distance.

[0029] Specifically, complex pipeline sections include tees and elbows.

[0030] Furthermore, the coupled wave model of the pipeline and the viscoelastic soil medium comprehensively considers the vibration characteristics of the pipeline, the viscoelasticity of the soil, and the interaction between the two. By performing frequency domain analysis on the wave model, the quantitative relationship between the attenuation of the sound wave amplitude and the distance can be clarified: the farther away from the sound source, the more severe the amplitude attenuation. Therefore, by comparing the amplitude of different detection points, the position with the largest amplitude is the position closest to the top of the pipeline, thereby achieving horizontal orientation locking.

[0031] Specifically, the resonant frequency distribution is obtained by performing a fast Fourier transform on the signals collected by each sensor to obtain the signal spectrum. The peak frequency in the spectrum is identified as the resonant frequency. The resonant frequency of a normal straight pipe section is a single main peak or multiple peaks with regular intervals. However, complex pipeline sections such as tees and elbows will generate additional resonant modes due to structural abrupt changes, which are manifested as new peak frequencies in the spectrum or a shift in the original peak frequencies.

[0032] Furthermore, to eliminate the influence of environmental noise on resonant frequency identification, a wavelet threshold denoising method is used to preprocess the original signal. The appropriate wavelet type is selected for the wavelet basis function, the number of decomposition layers is determined according to the signal characteristics, and a soft threshold function is adopted for the threshold rule to retain the effective components of the signal while removing noise interference.

[0033] Specifically, complex pipeline sections include tees and elbows. The resonant frequency characteristics of tees are characterized by the appearance of multiple new resonant peaks near the main peak frequency of the straight section. The resonant frequency characteristics of elbows are characterized by the main peak frequency shifting towards lower frequencies and the peak shape broadening. By identifying these characteristics, different types of complex pipelines can be effectively distinguished.

[0034] S3: Perform cross-correlation processing on the acquired time-domain signals, extract the time delay features of the signals arriving at different sensors, and construct an elliptical geometric model based on the time delay features and the geometric position relationship of the sensors, and calculate the burial depth of the pipeline.

[0035] Preferably, when performing cross-correlation processing on the collected time-domain signals, three sensors are arranged at equal intervals above the pipeline to collect time-domain vibration signals; pairwise cross-correlation analysis is performed on the three signals, and when the signal delay time between the two side sensors is zero, it is determined that the middle sensor is located directly above the pipeline; with the middle sensor and one side sensor as the focus, combined with the calculated signal arrival time delay of the two sensors, the ellipse equation is established and solved to quantitatively calculate the burial depth of the pipeline.

[0036] Furthermore, cross-correlation analysis calculates the similarity between two signals at different time offsets and finds the time offset that makes them most similar. This offset is the time delay of the signal arriving at the two sensors. In actual processing, fast algorithms can be used to calculate cross-correlation to improve processing efficiency.

[0037] Specifically, such as Figure 2 As shown, three sensors are arranged in a straight line at equal intervals. When the signal delay time of the two side sensors is zero, it indicates that the sound source (pipe) is located directly below the middle sensor. Taking the middle sensor and one side sensor as the foci of an ellipse, the time delay of the signal reaching these two sensors determines the length of the major axis of the ellipse. According to the geometric properties of the ellipse, the sound source must be located on the ellipse with these two sensors as foci. Combining the delay time information of another pair of sensors, the location coordinates of the sound source can be uniquely determined, and then the burial depth of the pipe can be calculated.

[0038] Furthermore, when the soil moisture is high, the sound wave propagation speed will decrease, resulting in an increase in the delay time. To correct for the influence of moisture, moisture-related parameters can be introduced into the wave model, or the actual wave velocity can be obtained through on-site calibration. In this embodiment, the soil viscoelastic parameters are preferably included in the wave model analysis in step S2, and the actual wave velocity can be inverted through the frequency domain analysis results for time domain calculation.

[0039] Specifically, to ensure the accuracy of the cross-correlation analysis, the acquired signal needs to be bandpass filtered. The filter passband is determined based on the resonant frequency range identified in step S2 to filter out interference from irrelevant frequency components.

[0040] Furthermore, when the pipeline is buried at a greater depth or the distance between the sensor and the excitation point is far, the signal-to-noise ratio may decrease. The signal-to-noise ratio can be improved and the signal stability enhanced by averaging multiple taps.

[0041] Specifically, for complex pipelines such as tees and elbows, the sound wave propagation path is different from that of straight pipe sections, which may lead to abnormal delay times. In this case, it is necessary to make appropriate corrections to the elliptical model based on the pipeline type identified in step S2.

[0042] S4: By fusing the pipeline type information obtained from the frequency domain analysis and positioning steps with the pipeline spatial location information obtained from the time domain analysis and positioning steps, a three-dimensional surface model of the pipeline is constructed, generating a visualized image that includes the pipeline direction, burial depth, and pipeline type identification.

[0043] Preferably, when constructing the three-dimensional surface model of the pipeline, the complex pipeline is divided into the main pipeline and the branch pipeline. The surface of the main pipeline is constructed using the parametric equation of the cylindrical coordinate system, and the surface of the branch pipeline is constructed using the parametric equation of the translation coordinate system. On the constructed surface model, according to the identified pipeline type, normal pipeline segments, elbows and tees are given different visual labels, which can be clearly distinguished in the visualization image.

[0044] Specifically, the frequency domain analysis, time domain analysis, and visualization imaging steps are executed in the data interaction development platform. This platform calls signal processing tools through built-in script nodes to realize real-time interaction and processing between the sensor hardware data acquisition and each analysis step, and dynamically displays the pipe position pointer, depth value, and visualization image on the system front panel.

[0045] Furthermore, the system's front panel uses pointer offset and indicator light color to determine the pipe's position and displays the pipe's depth value below the dial.

[0046] In summary, this invention achieves integrated high-precision positioning and visualization of complex buried PE pipelines through an innovative "time-frequency domain fusion" technical approach. This method utilizes the attenuation characteristics of acoustic wave amplitude in the frequency domain to pinpoint the pipeline's horizontal orientation and innovatively introduces resonant frequency distribution as an "acoustic fingerprint," enabling for the first time automatic identification and differentiation between complex pipeline sections such as tees and elbows and normal straight pipe sections. Through equidistant arrangement and cross-correlation analysis of three sensors, combined with an elliptical geometric model, it achieves quantitative calculation of burial depth independent of medium wave velocity, fundamentally avoiding measurement errors caused by changes in soil properties. This invention deeply integrates pipeline type information identified in the frequency domain with spatial location information calculated in the time domain, using parametric equations of cylindrical and translational coordinate systems. By constructing a three-dimensional curved surface model, a visual image containing pipeline direction, burial depth, and pipeline type identification is generated. This image is supplemented with an intuitive interactive interface featuring pointer offset and indicator light colors, transforming abstract professional detection data into easily understandable visual results. This invention effectively overcomes multiple shortcomings of methods such as electromagnetic tracer line reliance on pre-buried facilities, ground penetrating radar limitations due to geological conditions, and the inability of traditional acoustic methods to identify complex pipelines and lack of visualization capabilities. It achieves a technological leap from "single-parameter detection" to "multi-dimensional information fusion," from "fuzzy anomaly judgment" to "precise structure identification," and from "professional waveform interpretation" to "intuitive image presentation." This provides a reliable, efficient, and intelligent complete solution for the refined detection and management of buried PE pipelines under complex working conditions.

[0047] Example 2, an embodiment of the present invention, provides a complex buried PE pipeline positioning system based on time-frequency domain fusion of acoustic signals, comprising: a signal acquisition module for deploying multiple acoustic sensors on the soil surface above the buried PE pipeline to acquire acoustic signals generated by pipeline vibration excitation; a frequency domain analysis module for performing frequency domain transformation analysis on the acquired acoustic signals to obtain the attenuation characteristics and resonant frequency distribution of the signal amplitude, locking the horizontal orientation of the pipeline based on the amplitude attenuation characteristics, and distinguishing normal pipeline segments from complex pipeline segments based on the resonant frequency distribution; a time domain analysis module for performing cross-correlation processing on the acquired time domain signals to extract the time delay characteristics of the signals arriving at different sensors, constructing an elliptical geometric model based on the time delay characteristics and the geometric position relationship of the sensors, and calculating the burial depth of the pipeline; and an imaging display module for fusing the pipeline type information obtained from the frequency domain analysis positioning step and the pipeline spatial location information obtained from the time domain analysis positioning step to construct a three-dimensional curved surface model of the pipeline and generate a visual image containing the pipeline direction, burial depth, and pipeline type identification.

[0048] Example 3 is an embodiment of the present invention, which differs from the previous embodiment in that: If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0049] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0050] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0051] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0052] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals, characterized in that: include: Multiple acoustic sensors are deployed on the soil surface above the buried PE pipeline to collect acoustic signals generated by pipeline vibration. The acquired acoustic signal is subjected to frequency domain transformation analysis to obtain the attenuation characteristics of the signal amplitude and the resonant frequency distribution. The horizontal orientation of the pipeline is determined based on the amplitude attenuation characteristics, and normal pipeline sections are distinguished from complex pipeline sections based on the resonant frequency distribution. The collected time-domain signals are cross-correlated to extract the time delay features of the signals arriving at different sensors. Based on the time delay features and the geometric positional relationship of the sensors, an elliptical geometric model is constructed and the burial depth of the pipeline is calculated. By integrating the pipeline type information obtained from the frequency domain analysis and positioning step and the pipeline spatial location information obtained from the time domain analysis and positioning step, a three-dimensional surface model of the pipeline is constructed, generating a visualized image that includes the pipeline direction, burial depth, and pipeline type identification.

2. The method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals as described in claim 1, characterized in that: When performing frequency domain transformation analysis on the collected acoustic signals, a coupled wave equation between the pipeline and the viscoelastic soil medium is constructed, and its frequency domain analytical solution is solved by Fourier transform to quantify the exponential decay law of the acoustic amplitude with the propagation distance.

3. The method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals as described in claim 1, characterized in that: When performing cross-correlation processing on the collected time-domain signals, three sensors are arranged at equal intervals above the pipe to collect time-domain vibration signals; pairwise cross-correlation analysis is performed on the three signals, and when the signal delay time between the two side sensors is zero, it is determined that the middle sensor is located directly above the pipe. Using the intermediate sensor and a side sensor as the focal point, and combining the calculated time delay of the signal reaching these two sensors, the ellipse equation is established and solved to quantitatively calculate the burial depth of the pipeline.

4. The method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals as described in claim 1, characterized in that: When constructing the three-dimensional surface model of the pipeline, the complex pipeline is divided into the main pipeline and the branch pipeline. The surface of the main pipeline is constructed using the parametric equation of the cylindrical coordinate system, and the surface of the branch pipeline is constructed using the parametric equation of the translation coordinate system. On the constructed surface model, according to the identified pipeline type, normal pipeline segments, elbows and tees are given different visual labels, which can be clearly distinguished in the visualization image.

5. The method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals as described in claim 1, characterized in that: The frequency domain analysis, time domain analysis, and visualization imaging steps are executed in the data interaction development platform. This platform calls signal processing tools through built-in script nodes to realize real-time interaction and processing between the sensor hardware data acquisition and each analysis step, and dynamically displays the pipe position pointer, depth value, and visualization image on the system front panel.

6. The method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals as described in claim 5, characterized in that: The system's front panel uses pointer offset and indicator light color to determine the pipe's position and displays the pipe's depth value below the dial.

7. The method for locating complex buried PE pipelines based on time-frequency domain fusion of acoustic signals as described in claim 1, characterized in that: The complex pipeline section includes tee pipes and elbow pipes.

8. A complex buried PE pipeline positioning system based on time-frequency domain fusion of acoustic signals, based on the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals as described in any one of claims 1 to 7, characterized in that: include, The signal acquisition module is used to deploy multiple acoustic sensors on the soil surface above the buried PE pipeline to collect acoustic signals generated by pipeline vibration. The frequency domain analysis module is used to perform frequency domain transformation analysis on the acquired acoustic signals to obtain the attenuation characteristics of the signal amplitude and the resonant frequency distribution. Based on the amplitude attenuation characteristics, the horizontal orientation of the pipeline is determined, and based on the resonant frequency distribution, normal pipeline segments and complex pipeline segments are distinguished. The time-domain analysis module is used to perform cross-correlation processing on the acquired time-domain signals, extract the time delay characteristics of the signals arriving at different sensors, and construct an elliptical geometric model based on the time delay characteristics and the geometric position relationship of the sensors to calculate the burial depth of the pipeline. The imaging display module is used to fuse the pipeline type information obtained from the frequency domain analysis and positioning step and the pipeline spatial location information obtained from the time domain analysis and positioning step to construct a three-dimensional surface model of the pipeline and generate a visual image containing the pipeline direction, burial depth and pipeline type identification.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the complex buried PE pipeline positioning method based on time-frequency domain fusion of acoustic signals as described in any one of claims 1 to 7.

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