Nonmetal pipeline positioning device and method based on electromagnetic-acoustic wave combined excitation

Abstract

The invention discloses a nonmetal pipeline positioning method and device based on electromagnetic-acoustic wave combined excitation, and the method comprises the following steps: transmitting a high-frequency electromagnetic pulse to a target area, exciting the vibration of a fluid or an air column in a nonmetal pipeline to generate infrasonic waves, the frequency range of the high-frequency electromagnetic pulse being 1-100MHz, the pulse width being 0.1-10ms, and the transmitting power being greater than or equal to 50W; infrasonic wave signals are collected through a distributed vibration sensor array; and carrying out adaptive filtering, time-frequency analysis and wave velocity modeling on the signals, and calculating the position and the burial depth of the pipeline by combining a triangulation positioning algorithm. The method has the advantages that the electromagnetic-sound wave multi-physics field coupling technology is adopted, the non-metal pipeline detection bottleneck is broken through, the positioning precision is improved by 50% or above compared with that of a traditional GPR, the pipeline state can be evaluated synchronously, and an efficient tool is provided for safe operation and maintenance of an urban underground pipe network.

Description

Technical Field

[0001] The present invention relates to the technical field of underground pipeline detection, and particularly to a non-metallic pipeline positioning device and method based on electromagnetic-acoustic combined excitation. Background Art

[0002] Due to the characteristics of non-metallic pipelines such as low conductivity and non-magnetism, traditional electromagnetic induction methods are difficult to effectively detect. Although ground penetrating radar (GPR) can be used for non-metallic pipeline detection, the signal attenuation is serious in complex geological environments (such as high aquifers and rock layers), and it cannot detect empty pipelines (without fluid filling). Existing acoustic detection technologies rely on external sound source excitation, are easily interfered by environmental noise, and have low positioning accuracy. In addition, existing technologies are mostly limited to single physical field detection and it is difficult to balance detection depth and resolution.

[0003] For example, Chinese Patent Publication No. CN115685210A discloses a buried pipeline positioning device and method based on pulsed acoustic wave excitation, including a vibration excitation device, a signal receiving device, a signal processing module, and a vehicle body, wherein the vibration excitation device, the signal receiving device, and the signal processing module are all integrated in the vehicle body; the vibration excitation device is used to generate a short-time acoustic pulse signal with variable intensity of 500 Hz - 1 kHz, the signal receiving device is used to automatically adjust the distance between signal receivers and accurately receive the reflected wave signal reflected from the pipeline surface back to the ground, and the signal processing module is used to output a control signal and sample the analog signal detected by the signal receiver while the hammer generates a short-time pulse signal; through algorithms, on-site longitudinal wave velocity testing, extraction of reflected longitudinal wave signals, and superposition positioning imaging are carried out.

[0004] Another example is Chinese Patent Authorization Publication No. CN115793035B, which discloses an underground non-metallic pipeline detection system and method based on active acoustic wave excitation, including: an active acoustic wave excitation module for applying an excitation acoustic wave to the fluid in the pipeline to be detected; an array receiver module for receiving the excitation acoustic wave; an acoustic wave acquisition and preprocessing module for acquiring the received acoustic wave signal and preprocessing the acoustic wave signal; a pipeline trend calculation module for performing acoustic energy calculation to realize the detection of underground pipeline trend information; a pipeline depth calculation module for detecting the depth of the pipeline; and a power supply module for powering the above modules.

[0005] Both of the above two patents utilize acoustic wave excitation for detection and do not involve the scheme of electromagnetic-acoustic combined excitation. Summary of the Invention

[0006] The technical problem to be solved by the present invention is that the existing acoustic wave detection technology relies on external sound source excitation, is easily interfered by environmental noise, has low positioning accuracy, and is limited to single physical field detection, making it difficult to balance detection depth and resolution. Therefore, a non-metallic pipeline positioning device and method with electromagnetic-acoustic wave combined excitation are provided.

[0007] The technical solution of the present invention is as follows: a non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation, comprising the following steps: emitting high-frequency electromagnetic pulses to the target area to excite the fluid or air column in the non-metallic pipeline to vibrate and generate infrasound waves, wherein the frequency range of the high-frequency electromagnetic pulses is 1MHz-100MHz, the pulse width is 0.1ms-10ms, and the transmission power is ≥50W; collecting infrasound wave signals through a distributed vibration sensor array; performing adaptive filtering, time-frequency analysis and wave velocity modeling on the signals, and calculating the pipeline position and burial depth in combination with a triangulation positioning algorithm.

[0008] The adaptive filtering in the above scheme adopts LMS algorithm to eliminate environmental noise, the time-frequency analysis adopts short-time Fourier transform to extract the frequency and phase characteristics of the sound wave signal, and the wave velocity modeling is based on the sound velocity distribution of the underground medium to establish a layered wave velocity model.

[0009] The adaptive filtering described in the above scheme includes the following steps: input signal: collecting the original sound wave signal x(n), including noise v(n) and effective signal s(n); reference noise: collecting pure environmental noise d(n) as reference input when there is no electromagnetic pulse excitation; filter design: using a transverse filter with an order of L=32; weight update formula: w(n+1)=w(n)+μ·e(n)·x(n), where μ=0.01, e(n)=d(n)-y(n) is the error signal, and y(n) is the filter output; output: filtered signal s′(n)=x(n)-y(n).

[0010] The time-frequency analysis described in the above scheme includes the following steps: Frame processing: Frame the filtered signal s'(n) with a frame length of N = 1024 points and a frame shift of R = 512 points, and add a Hanning window Fourier transform: Calculate FFT for each frame of signal to get the spectrum Feature extraction: Extract the main frequency f peak = argmax k |S(k)|, calculate the phase spectrum φ(k) = ∠S(k); output: time-frequency matrix T(f, t), for subsequent wave velocity modeling and positioning.

[0011] The upper base and the lower base in the above solution are fitted together.

[0012] The wave velocity modeling in the above solution includes the following steps: Geological data input: Define the layered structure according to the geological report of the target area; Ray tracing correction: Use Snell's law to calculate the propagation path and time of sound waves in the layered medium; where θ i is the incident angle, and v i is the sound velocity of the i-th layer; Equivalent wave velocity calculation: Weighted average the sound velocity of each layer to obtain the equivalent wave velocity where d i is the thickness of the i-th layer; Output: A sound velocity-depth relationship table for the triangulation algorithm.

[0013] The triangulation algorithm in the above solution includes the following steps: Time difference estimation: Perform cross-correlation on the signals of sensors S i and S j , and the time difference Δt ij = argmax τ R ij (τ); Phase difference calculation: Extract the phase difference Δφ peak at the main frequency f ij = φ i (f peak ) - φ j (f peak ), and convert it to a distance difference: Coordinate solution: Establish a system of equations: Use the nonlinear least squares method to solve the coordinates (x, y, z), where x and y represent the pipeline center coordinates, and z represents the burial depth.

[0014] The improvement of the above solution also includes: Result visualization: Map the positioning result into a two-dimensional / three-dimensional heat map, and the color gradient represents the burial depth.

[0015] A non-metallic pipeline positioning device based on electromagnetic-acoustic joint excitation includes: An electromagnetic pulse emission module for emitting high-frequency electromagnetic pulses to the target area to excite the vibration of the fluid or gas column in the non-metallic pipeline to generate infrasound waves; A distributed vibration sensor array for collecting infrasound wave signals; A signal processing unit for performing adaptive filtering, time-frequency analysis, and positioning calculation on the infrasound wave signals.

[0016] The electromagnetic pulse emission module in the above solution includes a high-frequency signal generator, a power amplifier, and a directional transmitting antenna.

[0017] The signal processing unit in the above solution integrates an FPGA chip and an AI processor.

[0018] The beneficial effects of the present invention are as follows: By adopting the electromagnetic-acoustic multi-physical field coupling technology, the detection bottleneck of non-metallic pipelines is broken through. The positioning accuracy is improved by more than 50% compared with the traditional GPR, and the pipeline status can be evaluated synchronously, providing an efficient tool for the safe operation and maintenance of urban underground pipe networks, with the following significant advantages: 1. High precision: The positioning error is ≤ ±5 cm, meeting the requirements of complex working conditions; 2. Intelligence: Integrating material identification and risk assessment functions to provide comprehensive decision-making support; 3. Convenience: The design of wireless sensor arrays and interactive terminals simplifies the on-site operation process; 4. Environmental protection: No need to pre-bury tracer wires, reducing the interference of construction on the environment. Brief Description of the Drawings

[0019] Figure 1 is the system architecture diagram of the present invention;

[0020] Figure 2 is the schematic diagram of the electromagnetic-acoustic combined excitation principle of the present invention;

[0021] Figure 3 is the layout of the distributed sensor array and the signal transmission topology;

[0022] Figure 4 is the flow chart of the positioning algorithm of the present invention;

[0023] Figure 5 is an example diagram of the interactive terminal interface;

[0024] In the figure, 1. Electromagnetic pulse emission module, 2. Non-metallic pipeline. Detailed Embodiment

[0025] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0026] The present invention generates acoustic signals by exciting the vibration of the fluid in the pipeline with electromagnetic pulses, and combines a distributed sensor array and an adaptive algorithm to achieve high-precision positioning and status evaluation of non-metallic pipelines. The present invention aims to solve the detection problems of non-metallic pipelines by traditional detection technologies, improve the detection accuracy and efficiency, and provide technical support for the safe operation and maintenance of urban underground pipe networks.

[0027] Such as Figures 1-5As shown in the figure, a non-metallic pipeline positioning method based on electromagnetic-acoustic combined excitation includes the following steps: transmitting high-frequency electromagnetic pulses to the target area to excite the vibration of the fluid or gas column in the non-metallic pipeline to generate infrasound waves. The frequency range of the high-frequency electromagnetic pulses is 1 MHz - 100 MHz, specifically, it can be 1 MHz, 5 MHz, 10 MHz, 20 MHz, 30 MHz, 50 MHz or 100 MHz, adjusted according to the buried depth of the target pipeline. High frequency is used for shallow layers and low frequency for deep layers. The pulse width is 0.1 ms - 10 ms, specifically, it can be 0.1 ms, 0.5 ms, 1 ms, 5 ms or 10 ms. The shorter the pulse width, the higher the time resolution. The transmission power is ≥50 W to ensure penetrating the ground surface and exciting the fluid vibration; collecting infrasound wave signals through a distributed vibration sensor array. The distributed vibration sensor array is arranged in a grid form, and the sensor spacing is 0.5 m - 2 m; performing adaptive filtering, time-frequency analysis and wave velocity modeling on the signals, and calculating the pipeline position and buried depth in combination with the triangulation algorithm.

[0028] A non-metallic pipeline positioning device based on electromagnetic-acoustic combined excitation includes: an electromagnetic pulse emission module for transmitting high-frequency electromagnetic pulses to the target area to excite the vibration of the fluid or gas column in the non-metallic pipeline to generate infrasound waves; a distributed vibration sensor array for collecting infrasound wave signals; a signal processing unit for performing adaptive filtering, time-frequency analysis and positioning calculation on the infrasound wave signals. The electromagnetic pulse emission module includes a high-frequency signal generator, a power amplifier and a directional transmitting antenna. When emitting electromagnetic pulses, the directional transmitting antenna is vertically aligned with the ground to emit electromagnetic pulses, with a duration of 30 seconds and repeated emission at intervals of 1 second to accumulate signal energy.

[0029] Fluid vibration excitation: The electromagnetic wave penetrates the ground surface and acts on the fluid (water / gas) in the pipeline, and the fluid vibration is induced through the eddy current effect or thermal expansion to generate infrasound waves (frequency 10 Hz - 100 Hz).

[0030] The acoustic wave signal acquisition includes sensor array layout and signal synchronous acquisition. Sensor array layout: The sensor type is a MEMS vibration sensor. The layout method is in a grid form, with a spacing of 0.5 m - 2 m (dense in shallow layers and sparse in deep layers). The sensor nodes are built-in with LoRa modules, and the wireless transmission distance is ≥500 m. Signal synchronous acquisition: Start all sensor nodes to synchronously acquire acoustic wave signals at a sampling rate of 1 kHz, and record the timestamp and GPS position information.

[0031] Signal processing and positioning include: eliminating environmental noise (such as vehicle vibration, wind noise), and extracting effective acoustic wave signals; time-frequency analysis: extracting the frequency and phase characteristics of acoustic wave signals to distinguish pipeline vibration signals from interference; wave velocity modeling: based on the acoustic velocity distribution of underground media (soil, rock, etc.), establishing a layered wave velocity model to improve positioning accuracy; triangulation positioning: using the time difference and phase difference of the sensor array, and combining with the wave velocity model to calculate the three-dimensional coordinates and burial depth of the pipeline.

[0032] The adaptive filtering uses the LMS algorithm to eliminate environmental noise, the time-frequency analysis uses the short-time Fourier transform to extract the frequency and phase characteristics of acoustic wave signals, and the wave velocity modeling is based on the acoustic velocity distribution of underground media to establish a layered wave velocity model.

[0033] The adaptive filtering includes the following steps: input signal: collect the original acoustic wave signal x(n), which contains noise v(n) and effective signal s(n); reference noise: collect pure environmental noise d(n) when there is no electromagnetic pulse excitation as the reference input; filter design: use a transversal filter with the order L = 32; weight update formula: w(n + 1) = w(n) + μ·e(n)·x(n), where μ = 0.01 (step factor), e(n) = d(n) - y(n) is the error signal, and y(n) is the filter output; output: the filtered signal s′(n) = x(n) - y(n), and the signal-to-noise ratio is increased by ≥15 dB.

[0034] Time-frequency analysis includes the following steps: frame processing: frame the filtered signal s'(n), with the frame length N = 1024 points and the frame shift R = 512 points, and apply a Hanning window Fourier transform: calculate the FFT for each frame of the signal to obtain the frequency spectrum Feature extraction: extract the main frequency f peak = argmax k |S(k)|, calculate the phase spectrum φ(k) = ∠S(k); output: the time-frequency matrix T(f, t), which is used for subsequent wave velocity modeling and positioning.

[0035] Wave velocity modeling includes the following steps: geological data input: according to the geological report of the target area, define the layered structure, such as: topsoil v 1 = 300 m / s, clay layer v 2 = 1200 m / s, sandstone v 3 = 1800 m / s; ray tracing correction: use Snell's law to calculate the propagation path and time of acoustic waves in layered media; where θ i is the incident angle, and v i is the acoustic velocity of the i-th layer; equivalent wave velocity calculation: perform weighted averaging on the acoustic velocity of each layer to obtain the equivalent wave velocity where d iis the thickness of the i-th layer; Output: a sound speed-depth relationship table for use in the triangulation algorithm.

[0036] The triangulation algorithm includes the following steps: Time difference estimation: Perform cross-correlation on the signals of sensors S i and S j , and the time difference Δt ij = argmax τ R ij (τ); Phase difference calculation: Extract the phase difference Δφ peak at the main frequency f ij = φ i (f peak ) - φ j (f peak ), and convert it to a distance difference: Coordinate solution: Taking four sensors as an example, establish a system of equations: Use a nonlinear least squares method such as the Levenberg-Marquardt algorithm to solve for the coordinates (x, y, z), where x and y represent the pipeline center coordinates and z represents the burial depth. Output: The pipeline center coordinates (x, y) and the burial depth z, with an accuracy of ±5 cm.

[0037] Result visualization: Map the positioning result to a two-dimensional / three-dimensional heat map, where the color gradient represents the burial depth, e.g., red for shallow layers and blue for deep layers. Provide an interactive interface that supports zooming and hazard marking and export in PDF / CSV format.

[0038] The gain of the directional transmitting antenna ≥ 10 dB, and the module adopts a modular design, supporting quick replacement and upgrade. High-sensitivity MEMS vibration sensors (frequency response: 5 Hz - 1 kHz), wireless transmission unit (supporting LoRa protocol). The sensor node is built-in with a lithium battery, and the battery life ≥ 24 hours.

[0039] Signal processing unit: The FPGA chip realizes real-time filtering and feature extraction, and the embedded AI processor runs the positioning algorithm. Supports offline mode and cloud data synchronization.

[0040] Interactive terminal: The touch display screen displays the three-dimensional pipeline map in real time, supports zooming and hazard marking export in PDF / CSV format.

[0041] As an embodiment of the present invention: For the positioning of urban water supply PVC pipelines, 1. Parameter settings: Electromagnetic pulse frequency: 20 MHz, pulse width 1 ms; Sensor spacing 1 m. 2. Operation steps: Arrange 16 vibration sensors along the road to form a 4×4 grid. Transmit electromagnetic pulses and continuously excite for 30 seconds to collect acoustic signals. The signal processing unit automatically generates a pipeline trend map with a burial depth of 1.2 m.

[0042] In the description of this specification, the description referring to the term "embodiment" means that the specific features or characteristics described in connection with the embodiment are included in at least one embodiment of the present invention. In this specification, the schematic expression of the above term does not necessarily refer to the same embodiment. Moreover, the specific features or characteristics described can be combined in any one or more embodiments in a suitable manner.

[0043] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and the description in the specification are only used to illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and all these changes and improvements fall within the scope of the present invention claimed.

Claims

1. A non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation, characterized in that: The following steps are involved: High-frequency electromagnetic pulses are emitted to the target area to stimulate the vibration of the fluid or air column in the non-metallic pipeline to generate infrasound waves. The frequency range of the high-frequency electromagnetic pulses is 1MHz-100MHz, the pulse width is 0.1ms-10ms, and the transmission power is ≥50W; the infrasound wave signals are collected through a distributed vibration sensor array; the signals are adaptively filtered, time-frequency analyzed and wave velocity modeled, and the pipeline position and burial depth are calculated in combination with the triangulation positioning algorithm.

2. The non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation according to claim 1 is characterized in that: The adaptive filtering adopts LMS algorithm to eliminate environmental noise, the time-frequency analysis adopts short-time Fourier transform to extract frequency and phase characteristics of sound wave signals, and the wave velocity modeling is based on the sound velocity distribution of underground media to establish a layered wave velocity model.

3. The non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation according to claim 1 is characterized in that: The adaptive filtering The method comprises the following steps: input signal: collecting the original sound wave signal x(n), including the noise v(n) and the effective signal s(n); reference noise: collecting the pure environmental noise d(n) as the reference input when there is no electromagnetic pulse excitation; Filter design: Use a transversal filter with an order of L = 32; weight update formula: w(n+1) = w(n) + μ·e(n)·x(n), where μ = 0.01, e(n) = d(n)-y(n) is the error signal, and y(n) is the filter output; Output: filtered signal s′(n)=x(n)-y(n).

4. The non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation according to claim 1 is characterized in that: The time-frequency analysis The following steps are included: Frame processing: Frame the filtered signal s'(n) with a frame length of N = 1024 points and a frame shift of R = 512 points, and add a Hanning window Fourier transform: Calculate FFT for each frame of signal to get the spectrum Feature extraction: Extract the main frequency f peak = argmax k |S(k)|, calculate the phase spectrum φ(k) = ∠S(k); Output: time-frequency matrix T(f, t), used for subsequent wave velocity modeling and positioning.

5. The non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation according to claim 1 is characterized in that: The wave velocity modeling includes the following steps: geological data input: defining the layered structure according to the geological report of the target area; ray tracing correction: using Snell's law to calculate the propagation path and time of the sound wave in the layered medium; where θ i is the incident angle, v i is the sound velocity of the i-th layer; Equivalent wave velocity calculation: weighted average of the sound velocity of each layer to obtain the equivalent wave velocity where d i is the thickness of the i-th layer; Output: sound speed-depth relationship table, used for triangulation positioning algorithm.

6. The non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation according to claim 1 is characterized in that: The triangulation positioning algorithm includes the following steps: time difference estimation: i and S j The signal is cross-correlated, with a time difference of Δt ij = argmax τ R ij (τ); Phase difference calculation: Extract the main frequency f peak The phase difference Δφ at ij =φ i (f peak )-φ j (f eak ), converted to distance difference: Coordinate solution: Establish a set of equations: Use nonlinear least squares method to solve the coordinates (x, y, z), where x and y represent the coordinates of the pipeline center and z represents the buried depth.

7. The non-metallic pipeline positioning method based on electromagnetic-acoustic wave combined excitation according to claim 1 is characterized in that: Also includes: Result visualization: Map the positioning results into a 2D / 3D heat map, with color gradient indicating burial depth.

8. A non-metallic pipeline positioning device based on electromagnetic-acoustic wave combined excitation, characterized in that: include: An electromagnetic pulse transmitting module is used to transmit high-frequency electromagnetic pulses to the target area to stimulate the vibration of the fluid or air column in the non-metallic pipe to generate infrasound waves; Distributed vibration sensor array for collecting infrasound signals; The signal processing unit is used to perform adaptive filtering, time-frequency analysis and positioning calculation on the infrasound signal.

9. The non-metallic pipeline positioning device based on electromagnetic-acoustic wave combined excitation according to claim 8 is characterized in that: The electromagnetic pulse transmitting module includes a high-frequency signal generator, a power amplifier and a directional transmitting antenna.

10. The non-metallic pipeline positioning device based on electromagnetic-acoustic wave combined excitation according to claim 8, characterized in that: The signal processing unit integrates an FPGA chip and an AI processor.

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