Long-distance water supply pipeline leakage detection equipment and method based on wave interference

Abstract

The invention relates to a long-distance water supply pipeline leakage detection device and method based on wave interference, and belongs to the technical field of water supply pipeline leakage monitoring. The equipment comprises a central control unit, a plurality of underwater sonar detection devices, a signal processing and communication unit and a pipe wall stress sensing unit, the method comprises the following steps: performing time synchronization on underwater sonar detection devices at all monitoring points, performing passive monitoring, monitoring continuous noise signals when leakage occurs, automatically triggering data packet transmission when a noise amplitude exceeds a threshold value, and performing preliminary positioning on a pipeline leakage point by a central control unit in combination with acoustic data and stress data, and judging a leakage risk level; after preliminary positioning, several monitoring points closest to the area are subjected to active detection, ultrasonic pulses are emitted, reflected waves are generated and received by an underwater sonar detection device, interference signals generated by obstacles are eliminated, and the accurate position of a leakage point is inverted by using delta d. According to the invention, long-distance and high-precision positioning of the leakage point of the pipeline can be realized.

Description

Technical Field

[0001] This invention relates to a long-distance water supply pipeline leakage detection device and method based on wave interferometry, belonging to the field of water supply pipeline leakage monitoring technology. Background Technology

[0002] Water supply pipelines are the lifeline of modern water resource transportation. However, leaks caused by corrosion, aging, and external damage not only result in enormous resource waste and economic losses but can also trigger environmental disasters and safety accidents. Therefore, timely and accurate detection and location of pipeline leaks are of paramount importance.

[0003] Currently, common pipeline leakage detection technologies include sound detection and acoustic detection. Sound detection relies on human experience, resulting in low efficiency and poor positioning accuracy. Acoustic detection, particularly using sound wave or vibration sensors installed on the pipeline to capture the noise generated by leakage, is an effective method. However, in long-distance pipelines, the presence of obstacles such as flanges and valves causes significant attenuation of the leakage sound signal with distance, reducing the signal-to-noise ratio and limiting the sensor's detection range and positioning accuracy. Furthermore, it requires extensive deployment. Existing technologies mostly employ point-to-point signal reception and analysis, lacking in-depth utilization of the propagation characteristics of sound waves in space, making it difficult to achieve large-scale, high-precision synchronous detection.

[0004] Therefore, there is an urgent need in this field for a leakage detection technology that can achieve long-distance, high-precision, adaptive, and preventive early warning capabilities in complex pipeline environments. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a long-distance water supply pipeline leakage detection device and method based on wave interferometry, so as to achieve long-distance and high-precision positioning of pipeline leakage points.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The long-distance water supply pipeline leakage detection equipment based on wave interferometry includes a central control unit, multiple underwater sonar detection devices set at certain intervals on the inner wall of the pipeline to be tested, a signal processing and communication unit connected to the underwater sonar detection devices, and a pipe wall stress sensing unit set in the pipeline. The underwater sonar detection device includes a sound wave transmitting unit, a sound wave receiving and storage unit, and a clock synchronization module. The sound wave transmitting unit generates ultrasonic signals of specific wavelength and frequency through a high-frequency oscillation circuit, and transmits them in a fan-shaped beam in both directions in front of and behind the pipe with adjustable power. The sound wave receiving and storage unit performs analog-to-digital conversion and preprocessing of the sound wave signals and reflected signals from the pipe environment through a data acquisition card and stores them locally. The clock synchronization module ensures that all underwater sonar detection devices operate under a unified time base. The pipe wall stress sensing unit identifies changes in pipe wall stress through stress sensors and processing circuits; The signal processing and communication unit includes an adaptive control module and a communication module. The adaptive control module has a built-in Fast Fourier Transform (FFT) algorithm and a noise feature recognition model. By acquiring real-time background noise signals, the time domain signal is converted into a frequency domain signal through the FFT algorithm, and the noise amplitude, main frequency, and spectral distribution features are extracted. After comparing with a preset threshold, the noise data and stress data packets are automatically triggered to be sent. The communication module enables signal transmission between the underwater sonar detection device and the central control unit, as well as self-organizing network interaction between the various underwater sonar detection devices; The central control unit includes an obstacle 3D modeling and signal correction module, a multiphysics field fusion analysis module, a leakage location calculation module, and a communication module; The multiphysics field fusion analysis module combines the acoustic and stress data received from various underwater sonar detection devices to initially locate the pipeline leakage point and identify the suspected area. It then sends instructions to the monitoring points closest to the area via the communication module, ordering them to switch to active detection mode and quantifying the pipeline leakage risk level. The obstacle 3D modeling and signal correction module creates and calls obstacle 3D models, performs phase cancellation processing on the received reflected wave signals, eliminates interference signals generated by obstacles, and retains only the effective interference signals of the missing points; The leakage location calculation module uses the time difference generated from the transmission signal to the received reflected signal, combined with the multi-beam collaborative interferometry calculation method, to accurately calculate the path difference Δd between the two signals reaching each device, and uses Δd to infer the precise location of the leakage point.

[0007] The aforementioned pipe wall stress sensing unit is installed at the connection point between the inner wall of the pipe and the underwater sonar detection device.

[0008] A method for detecting leakage in long-distance water supply pipelines based on wave interferometry includes the following steps: S1. The central control unit periodically sends time synchronization commands to the underwater sonar detection devices at each monitoring point, and the clock synchronization module is used to achieve microsecond-level time synchronization. S2. All underwater sonar detection devices passively monitor the acoustic environment in the pipeline under normal circumstances. When a leak occurs, they will detect that the high-pressure water jet from the rupture and the friction will generate a continuous noise signal in a specific frequency band. S3. The adaptive control module analyzes the background noise signal spectrum in real time. When the noise amplitude exceeds the threshold, it automatically triggers the transmission of noise data and stress data packets. S4. Leakage noise and pipe wall stress sensing units with precise timestamps collect stress data and pipeline pressure data, and upload them synchronously to the central control unit. The central control unit uses a multi-physics field fusion analysis module to combine acoustic data and stress data to initially locate suspected areas of pipeline leakage and determine the leakage risk level. S5. After initial positioning, the central control unit issues instructions to the monitoring points closest to the area, ordering them to conduct active detection. The underwater sonar devices of the monitoring points closest to the area sequentially emit ultrasonic pulses toward the suspected area. When the ultrasonic pulses encounter the leak, they will be reflected. After a certain period of time, the reflected waves are received by the underwater sonar devices. S6. The obstacle 3D modeling and signal correction module of the central control unit performs phase cancellation processing on the received reflected wave signal by establishing and calling the obstacle 3D model, eliminating the interference signal generated by the obstacle, and retaining only the effective interference signal of the missing point; S7. Utilize the time difference between the signal emitted by the device and the reflected signal received, and combine the multi-beam collaborative interferometry calculation method to calculate the path difference Δd between the two signals reaching each device, and use Δd to infer the precise location of the leak point; S8. Visualize and output the calculated precise coordinates and risk level of the leak point, and trigger a graded early warning.

[0009] In the above method, the method for initially locating and determining the suspect area using the multiphysics fusion analysis module in step S4 is as follows: (1) Perform time-domain amplitude, main frequency, and spectrum continuity analysis on the noise of each node, and screen out 2-3 abnormal nodes whose signal amplitude is significantly higher than the background threshold and whose spectrum characteristics match the leakage characteristics; (2) Identify the core node with the strongest signal and its adjacent abnormal nodes; (3) The areas extending outward from the core node and the adjacent abnormal node by 100m and 50m respectively are the initial suspected leakage areas.

[0010] The steps for determining the leakage risk level are as follows: (1) Data acquisition and preprocessing The system synchronously collects and uploads ultrasonic interference data, pipe wall stress data, and water pressure data from pipeline pressure monitoring points. Wavelet transform is used to denoise the ultrasonic data, and moving average filtering is used to denoise the stress and water pressure data to remove outliers from all data and ensure data validity. (2) Feature extraction and weight allocation: Extract the leakage-sensitive features of the three types of data, allocate them according to the weight coefficients specified in the engineering calibration, and satisfy ω1+ω2+ω3=1. The specific weights and sensitive features are as follows: a. Ultrasonic interferometric data: weight ω1=0.55, sensitive features are amplitude abrupt change rate ΔA / A0 and dominant frequency offset Δf / f0; b. Pipe wall stress data: weight ω2=0.25, sensitive features are stress change rate dσ / dt and stress peak σmax; c. Water pressure data: weight ω3=0.20, sensitive features are pressure change rate dP / dt and pressure fluctuation amplitude ΔP; (3) Quantitative generation of leakage risk level: A leakage risk index calculation model is constructed. The fused feature data is substituted into the model to obtain the quantitative risk index R. Based on the R value, leakage risks are divided into three levels: low, medium, and high. The model formula is as follows: , In the formula: σ0 is the allowable design stress of the pipe wall, and P0 is the design working pressure of the pipeline. Risk level classification criteria: low risk 0 < R < 0.3, medium risk 0.3 < R < 0.7, high risk R ≥ 0.7.

[0011] In step S5, the active detection dynamically adjusts the ultrasonic power based on the distance to the initially located leakage area.

[0012] Step S6 first constructs a high-precision three-dimensional acoustic model of flanges and valves within the pipeline through ultrasonic scanning during system initialization, extracting and storing the acoustic features of the obstacles. During the active detection phase, the received reflected wave signals are template-matched with the obstacle features to accurately identify obstacle interference signals. Then, phase compensation and amplitude cancellation algorithms are used to correct and eliminate the interference signals, retaining only the effective interference signals from missed points, thus eliminating the impact of obstacles on positioning accuracy. The steps for identifying obstacle interference signals are as follows: extracting the characteristic parameters of the reflected wave signals received during the active detection phase, including arrival time t, dominant frequency f, phase φ, and amplitude A, performing template matching with the parameters in the obstacle feature database, and calculating the matching degree S using a cosine similarity algorithm, formula: , In the formula: x i The feature vector (x) of the received signal i =[t,f,φ,A]); y i For the feature vector (y) of obstacles in the database i =[t ob,, f ob ,φ ob A ob ]); Matching degree judgment criteria: S≥90%, judged as obstacle interference signal; S<80%, judged as effective reflection signal of leakage point; when 80%<S<90%, combined with the spatial position verification of the obstacle's three-dimensional model, if the deviation between the signal source and the obstacle coordinates is ≤1.0m, it is judged as interference signal; otherwise, it is a valid signal.

[0013] The calculation process in step S7 is as follows: (1) Select two adjacent underwater sonar detection devices A and B around the suspected leakage area as reference nodes. Construct a one-dimensional coordinate system with device A as the origin and the pipeline extension direction as the X-axis. The coordinates of device B are (L AB ,0),L AB The fixed installation distance between the two devices is specified; the precise arrival time t of the reflected waves received by devices A and B at the leakage points is collected and recorded. A t B ; (2) Calculation of one-way propagation distance and path difference: Calculate the one-way propagation distance L from the two reference nodes to the leakage point based on the propagation speed v of ultrasound in water. A L B ,formula: L A =(v×t A ) / 2, L B =(v×t B Based on the one-way propagation distance, calculate the path difference Δd between the two nodes and the leakage point, using the formula: Δd=∣L A -L B |; (3) Calculate the coordinates of the leakage point: Select the detection device A as the origin (0,0). Calculate the precise coordinates of the leakage point. Let the coordinates of the leakage point P be (x,0), that is, the X-axis coordinate value is directly equal to the actual length to point A. According to geometric relations |L AB The formula is: −x∣−x=Δd, which gives the precise coordinates x of the leakage point. ; (4) The actual pipeline mileage corresponding to the actual mileage conversion and three-dimensional positioning extension combined device A is converted into the actual pipeline mileage of the leakage point by the calculated coordinate x, so as to complete the accurate positioning of the leakage point of the straight pipe section.

[0014] The beneficial effects of this invention are: 1. Strong anti-interference capability: Wave interferometry can effectively suppress background noise that is incoherent with the leakage signal, because random noise will cancel each other out during the interference process, while the coherent leakage signal will be enhanced. Combined with obstacle 3D modeling and signal correction, it can eliminate pipeline obstacle interference, improve the signal-to-noise ratio by more than 50%, and significantly enhance robustness in complex environments.

[0015] 2. Outstanding preventive maintenance capabilities: By integrating pipe wall stress data with ultrasonic interference signals, weak points or early damage to the pipe wall can be identified 3-6 months in advance, preventing leakage from expanding and solving the pain point of existing technologies that can only detect after the fact.

[0016] 3. Long-distance blind-spot-free detection: Through the deployment of distributed detection devices and the fault-tolerant mechanism of Mesh self-organizing network, continuous and uninterrupted detection of pipelines from several kilometers to tens of kilometers can be achieved. Faulty nodes are automatically replaced, and no manual equipment is required. The detection efficiency far exceeds that of traditional leak detection instruments, and it is especially suitable for long-distance municipal water supply networks.

[0017] 4. Strong environmental adaptability: Through an environment-aware dynamic switching strategy, the detection parameters are adjusted in real time to adapt to the environmental differences in different sections (urban / suburban) and different time periods (day / night), reducing the false alarm rate by more than 30%. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the system structure of the present invention; Figure 2 This is a flowchart of the method of the present invention; Figure 3 This is a schematic diagram illustrating the workflow of the obstacle 3D modeling and signal correction module of the present invention; Among them: 1. Pipeline, 2. Leakage point, 3a and 3b are underwater sonar detection devices, 4. Water flow disturbance, 5. Actively emitted ultrasonic beam, 6. Reflected ultrasonic beam, 7. Signal processing and communication unit, 8. Central control unit, 9. Obstacle (flange / valve), 10. Pipeline pressure monitoring point; 11. Pipe wall stress sensing unit. Detailed Implementation

[0019] The present invention will be further described below with reference to specific embodiments.

[0020] Example 1: A long-distance water supply pipeline leakage detection device based on wave interferometry, such as... Figure 1 It includes a central control unit 8, multiple underwater sonar detection devices 3a and 3b arranged at certain intervals on the inner wall of the pipe to be tested 1, a signal processing and communication unit 7 connected to the underwater sonar detection devices, and a pipe wall stress sensing unit 11 installed in the pipe.

[0021] The deployment spacing is determined based on the diameter of the pipeline to be tested. When the diameter is ≥1m, one underwater sonar detection device is fixedly installed on the inner wall of the pipeline every 1km; when the diameter is <1m, the deployment spacing is adjusted to 500m. All devices are powered by waterproof cables and connected to the power supply facilities along the pipeline. At the same time, a communication link is formed through a Mesh self-organizing network, and a stable connection is established with the central control unit of the monitoring center through industrial Ethernet.

[0022] Pipeline pressure monitoring point 10 deployment rules: Pipe diameter ≥ 1m: 1 pressure monitoring point is set up every 2km; Pipe diameter < 1m: 1 pressure monitoring point is set up every 1km.

[0023] The underwater sonar detection device includes a sound wave transmitting unit, a sound wave receiving and storage unit, and a clock synchronization module. The sound wave transmitting unit generates ultrasonic signals of specific wavelengths and frequencies through a high-frequency oscillation circuit, emitting them in a fan-shaped beam in both directions before and after the pipe, with adjustable power. The sound wave receiving and storage unit uses a data acquisition card to perform analog-to-digital conversion and preprocessing of the sound wave signals and reflected signals from the pipe environment, and then stores them locally. The clock synchronization module ensures that all underwater sonar detection devices operate under a unified time base. When leakage occurs, the outflow of high-pressure water will generate water flow disturbances, which will cause some reflection of the ultrasonic waves.

[0024] Acoustic wave transmitting unit: It adopts a piezoelectric ultrasonic transducer with a core of PZT-8 piezoelectric ceramic sheet. It generates ultrasonic signals of specific wavelength and frequency through a high-frequency oscillation circuit and transmits them in a 120-degree fan-shaped beam in both directions in front of and behind the pipe. Through power amplification circuit and frequency modulation circuit, it realizes stepless adjustment of transmission power from 1 to 10W and segmented adjustment of frequency from 20kHz to 1MHz. The adjustment response time is ≤10ms, which meets different detection distance and accuracy requirements.

[0025] The acoustic wave receiving and storage unit consists of a high-speed data acquisition card (sampling rate ≥10MSPS, resolution 16bit) and a local storage module (TF card, capacity ≥128G). The acquisition card performs analog-to-digital conversion (ADC) and preprocessing (pre-amplification, 50Hz notch filtering) on ​​the acoustic wave signal from the pipeline environment. The local storage module stores the original signal in the format of timestamp + device number (storage time ≥72h).

[0026] Clock synchronization module: Integrated in the acoustic wave receiving and storage unit, it ensures that all detection devices operate under a unified time base, which is a prerequisite for realizing wave interferometry analysis.

[0027] The pipe wall stress sensing unit identifies changes in pipe wall stress through stress sensors and processing circuits. A foil strain gauge stress sensor is attached to the connection between the inner wall of the pipe and the detection device. The changes in pipe wall stress are converted into voltage signals. After signal conditioning circuitry (amplification, filtering, and linearization), data is collected at a fixed sampling frequency of 100Hz. It can identify pipe wall stress changes of ≥0.1MPa and is used to identify weak points such as pipe wall corrosion and microcracks.

[0028] The signal processing and communication unit includes an adaptive control module and a communication module. The adaptive control module has a built-in Fast Fourier Transform (FFT) algorithm and a noise feature recognition model. By acquiring real-time background noise signals, the time domain signal is converted into a frequency domain signal through the FFT algorithm, and the noise amplitude, main frequency, and spectral distribution features are extracted. After comparing with a preset threshold, the noise data and stress data packets are automatically triggered for transmission. The communication module enables signal transmission between the underwater sonar detection device and the central control unit, as well as self-organizing network interaction between the underwater sonar detection devices. It can upload signals at a transmission rate of 1Mbps. The Mesh self-organizing network enables self-organizing network interaction between the detection devices, real-time sharing of working status, and has the function of dynamic replacement of faulty nodes.

[0029] The central control unit includes an obstacle 3D modeling and signal correction module, a multiphysics field fusion analysis module, a leakage location calculation module, and a communication module. The central control unit communicates with all underwater sonar detection devices and is used to coordinate the work of the entire system, including command issuance, data aggregation, comprehensive analysis, and final result output.

[0030] The multiphysics field fusion analysis module combines the acoustic data and stress data received from various underwater sonar detection devices to initially locate the pipeline leakage point and determine the suspected area. Through the communication module, it issues instructions to the monitoring points closest to the area, ordering them to switch to active detection mode (see actively emitted ultrasonic beam 5); and quantifies and generates the pipeline leakage risk level. The obstacle 3D modeling and signal correction module creates and calls the obstacle 3D model, performs phase cancellation processing on the received reflected ultrasonic beam 6 signal, eliminates the interference signal generated by the obstacle, and retains only the effective interference signal of the missing point; The leakage location calculation module uses the time difference generated from the transmission signal to the received reflected signal, combined with the multi-beam collaborative interferometry calculation method, to accurately calculate the path difference Δd between the two signals reaching each device, and uses Δd to infer the precise location of the leakage point.

[0031] Example 2: A method for detecting leakage in long-distance water supply pipelines based on wave interferometry, comprising the following steps: S1. The central control unit periodically sends time synchronization commands to the underwater sonar detection devices at each monitoring point, and the clock synchronization module achieves microsecond-level time synchronization: The central control unit sends synchronization commands to all detection devices. Each detection device achieves coarse synchronization at the second level through GPS time synchronization, and then completes the synchronization through the Precision Clock Protocol (PTPv2). The microsecond-level precision synchronization ensures that the clocks of all devices are consistent with UTC time. After synchronization is completed, each device sends a confirmation signal to the central control unit to ensure the time base uniformity of wave interferometry analysis.

[0032] S2. Under normal circumstances, all underwater sonar detection devices passively monitor the acoustic environment within the pipeline. When a leak occurs, they will detect continuous noise signals in a specific frequency band generated by the high-pressure water jet ejected from the breach and friction. The system defaults to passive monitoring mode. The underwater sonar detection device shuts down the sound wave transmitting unit, the sound wave receiving and storage unit continuously collects the background noise of the pipeline at a sampling rate of 10MSPS, and the pipe wall stress sensing unit collects the pipe wall stress data at a sampling rate of 100Hz. Both types of data are uploaded to the central control unit at a transmission rate of 1Mbps in the format of device number + timestamp. The original pressure monitoring points of the pipeline collect water pressure data at a sampling rate of 1Hz and upload it synchronously.

[0033] S3. The adaptive control module analyzes the background noise signal spectrum in real time, and automatically triggers the transmission of noise data and stress data packets when the noise amplitude exceeds the threshold. The adaptive control module analyzes the background noise spectrum (such as traffic noise and water flow noise) in real time. When the noise amplitude exceeds the threshold, it automatically triggers the transmission of noise data and stress data packets.

[0034] S4. Leakage noise and pipe wall stress sensing units with precise timestamps collect stress data and pipeline pressure data, which are simultaneously uploaded to the central control unit. The central control unit uses a multi-physics field fusion analysis module to combine acoustic and stress data to initially locate suspected areas of pipeline leakage and determine the leakage risk level. (a) Preliminary location and identification of the suspected area, using the following method: (1) Perform time-domain amplitude, main frequency, and spectrum continuity analysis on the noise of each node, and screen out 2-3 abnormal nodes whose signal amplitude is significantly higher than the background threshold and whose spectrum characteristics match the leakage characteristics; (2) Identify the core node with the strongest signal and its adjacent abnormal nodes; (3) The areas extending outward from the core node and the adjacent abnormal node and the adjacent abnormal node respectively by 100m and 50m are the initial suspected leakage areas.

[0035] (ii) Determining the level of leakage risk (1) Data acquisition and preprocessing: The ultrasonic interference data (amplitude A, main frequency f, propagation time t), pipe wall stress data (stress value σ, stress change rate dσ / dt), and water pressure data (pressure value P, pressure change rate dP / dt) uploaded by the detection device are acquired simultaneously. Wavelet transform is used to denoise the ultrasonic data, and moving average filtering is used to denoise the stress and water pressure data. Outliers in all data are removed to ensure data validity.

[0036] (2) Feature extraction and weight allocation: Extract the leakage-sensitive features of the three types of data, allocate them according to the weight coefficients specified in the engineering calibration, and satisfy ω1+ω2+ω3=1. The specific weights and sensitive features are as follows: a. Ultrasonic interferometric data: weight ω1=0.55, sensitive features are amplitude abrupt change rate ΔA / A0 and dominant frequency offset Δf / f0; b. Pipe wall stress data: weight ω2=0.25, sensitive features are stress change rate dσ / dt and stress peak σmax; c. Water pressure data: weight ω3=0.20, sensitive features are pressure change rate dP / dt and pressure fluctuation amplitude ΔP.

[0037] (3) Quantitative generation of leakage risk level: A leakage risk index calculation model is constructed. The fused feature data is substituted into the model to obtain the quantitative risk index R. Based on the R value, leakage risks are divided into three levels: low, medium, and high. The model formula is as follows: R=ω1×(ΔA / A0+Δf / f0) / 2+ω2×(dσ / dt) / σ0+ω3×(dP / dt) / P0, Where: σ0 is the allowable design stress of the pipe wall (200MPa for ductile iron pipes and 240MPa for steel pipes); P0 is the design working pressure of the pipeline (0.4-1.6MPa for municipal water supply networks); R∈[0,1]; Risk level classification criteria: low risk (0 < R < 0.3), medium risk (0.3 < R < 0.7), high risk (R ≥ 0.7).

[0038] S5. After initial positioning, the central control unit issues instructions to the monitoring points closest to the area, ordering them to conduct active detection. The underwater sonar devices at these monitoring points sequentially emit ultrasonic pulses towards the suspected area. When the ultrasonic pulses encounter the leak, they are reflected. After a certain period of time, the reflected waves are received by the underwater sonar devices. Once the multiphysics field fusion analysis module identifies a suspected leakage area, the central control unit sends instructions to 3-5 detection devices around the suspected area to switch to high-power active detection. The transmission power is adjusted to 5-10W, the frequency is 500kHz-1MHz, and the emitted ultrasonic waves are coherent pulses with the same frequency and phase, and the beam is a 120° fan shape to ensure the formation of a stable coherent interference field in the leakage area.

[0039] The system dynamically adjusts the active detection mode based on the distance to the suspected leakage area, pipeline section, and time period. According to the initially located leakage area, it dynamically adjusts the ultrasonic power (low power in the near zone, high power in the far zone) and frequency (high frequency and high precision in the near zone, low frequency and anti-attenuation in the far zone) parameters. The core adjustment rule is as follows: (1) Near-field (distance ≤ 500m): low power (1-3W), high frequency (500kHz-1MHz) to ensure detection accuracy; (2) Far-field (distance > 500m): High power (5-10W), low frequency (20kHz-100kHz) to improve signal attenuation resistance; (3) Urban section / daytime: background noise is high, power is increased by 1-2W and frequency is increased by 50-100kHz; (4) Suburban section / Nighttime: Low background noise, power reduction of 1-2W, frequency reduction of 50-100kHz.

[0040] S6. The Central Control Unit Obstacle 3D Modeling and Signal Correction Module establishes and calls up obstacle 3D models, performs phase cancellation processing on the received reflected wave signals, eliminates interference signals generated by obstacles, and retains only the effective interference signals of the missing points: All underwater sonar detection devices emit continuous ultrasonic waves at a power of 1W and a frequency of 20kHz to perform initial ultrasonic scanning of the entire pipeline. The acoustic receiving unit collects reflected wave signals from obstacles such as flanges and valves. The central control unit extracts the core features of the signals, such as arrival time, amplitude, phase, and dominant frequency. Through point cloud coordinate transformation and splicing reconstruction algorithms, a high-precision three-dimensional acoustic model of the obstacles is constructed. At the same time, the acoustic feature parameters of the obstacles (reflected wave dominant frequency, phase offset, amplitude attenuation coefficient) are extracted, bound to the three-dimensional model, and stored in the obstacle feature database.

[0041] The 3D acoustic model of the obstacle is constructed with the pipe's starting point as the origin, the pipe's extension direction as the X-axis, the radial direction as the Y-axis, and the perpendicular axis to the radial direction as the Z-axis, thus establishing a 3D coordinate system for the pipe. Based on the obstacle's reflected wave signals acquired during the initial scan, the 3D coordinates (x, y, z) of each reflection point of the obstacle are calculated using the following formula: x = x0 + (v × t) ob ) / 2×cosθ; y=(v×t ob ) / 2×sinθ×cosα; z=(v×t ob ) / 2×sinθ×sinα; In the formula: x0 is the X-axis coordinate of the transmitting device; θ is the angle between the ultrasonic wave beam and the X-axis (θ∈[−60°,60°]); α is the circumferential angle of the ultrasonic wave beam (α∈[0°,360°]); v is the propagation speed of ultrasound in water (v=1480m / s for room temperature clean water); t ob This represents the arrival time of the wave reflected from the obstacle.

[0042] The reflection point coordinates are stitched together using the Iterative Closest Point (ICP) algorithm to remove redundant and noise points. The surface is then reconstructed using the Poisson reconstruction algorithm to generate a high-precision three-dimensional acoustic model of the obstacle.

[0043] The characteristic parameters (arrival time t, dominant frequency f, phase φ, amplitude A) of the reflected wave signal received during the active detection phase are extracted and matched with the parameters in the obstacle feature database. The matching degree S is calculated using the cosine similarity algorithm, as shown in the formula: , In the formula: x i The feature vector (x) of the received signal i =[t,f,φ,A]); y i For the feature vector (y) of obstacles in the database i =[t ob,, f ob ,φ ob A ob ]).

[0044] Matching degree judgment criteria: S≥90%, judged as obstacle interference signal; S<80%, judged as effective reflection signal of leakage point; when 80%<S<90%, combined with the spatial position verification of the obstacle's three-dimensional model, if the deviation between the signal source and the obstacle coordinates is ≤1.0m, it is judged as interference signal; otherwise, it is a valid signal.

[0045] For the identified obstacle interference signals, a combined phase compensation and amplitude cancellation algorithm is used for precise removal. The specific steps are as follows: (1) Phase compensation: Based on the spatial coordinates (x, y) of the obstacle's three-dimensional model ob y ob , z ob ), calculate the theoretical path length d of the ultrasonic wave from the transmitting device to the obstacle and then to the receiving device. ob ,formula: , In the formula: (x t y t , z t (x) represents the three-dimensional coordinates of the launching device; r y r , z r ( ) represents the three-dimensional coordinates of the receiving device. The theoretical phase offset φ is calculated based on the theoretical path length. ob ,formula: , In the formula: f is the ultrasonic emission frequency; v is the ultrasonic propagation speed. Generate phase compensation signal φ comp =−φ ob The signal is superimposed in the time domain with the original received signal to achieve phase cancellation of obstacle interference signals.

[0046] (2) Amplitude cancellation: based on the amplitude attenuation coefficient k of the obstacle ob Generate amplitude compensation signal: A comp =−A ob / k ob A ob This represents the original amplitude of the reflected wave from the obstacle. The amplitude is then superimposed on the phase-compensated signal to cancel out the amplitude of the interference signal from the obstacle. (3) Bandpass filtering: The signal after phase and amplitude compensation is filtered by Chebyshev Type I bandpass filter (filtering frequency band 50kHz-500kHz) to finally obtain an effective interference signal containing only the reflection of the leakage point.

[0047] S7. Using the time difference between the signal emitted by the device and the reflected signal received, and combining this with the multi-beam coordinated interferometry calculation method, the path difference Δd between the two signals reaching each device is calculated. Then, Δd is used to infer the precise location of the leak. (1) Reference node selection and data acquisition: Two adjacent detection devices A and B around the suspected leakage area are selected as reference nodes. A one-dimensional coordinate system is constructed with device A as the origin and the pipeline extension direction as the X-axis. The coordinates of device B are (L... AB ,0),L AB The fixed installation distance between the two devices (known value) is used; the precise arrival time t of the reflected waves received by devices A and B from the leakage points is collected and recorded. A t B .

[0048] (2) Calculation of one-way propagation distance and path difference: Calculate the one-way propagation distance L from the two reference nodes to the leakage point based on the propagation speed v of ultrasound in water. A L B ,formula: L A =(v×t A ) / 2, L B =(v×t B Based on the one-way propagation distance, calculate the path difference Δd between the two nodes and the leakage point, using the formula: Δd=∣L A -L B |; (3) Calculation of the coordinates of the leakage point: Select the detection device A as the coordinate origin (0,0). The precise coordinates of the leakage point are calculated by setting the coordinates of the leakage point P as (x,0), that is, the X-axis coordinate value is directly equal to the actual length to point A.

[0049] According to geometric relations |L AB The formula is: −x∣−x=Δd, which gives the precise coordinates x of the leakage point. ; (4) The actual pipeline mileage corresponding to the actual mileage conversion and three-dimensional positioning extension combined device A is converted into the actual pipeline mileage of the leakage point by the calculated coordinate x, so as to complete the accurate positioning of the leakage point of the straight pipe section.

[0050] S8. Visualize the calculated precise coordinates and risk level of the leakage point, and trigger a tiered early warning: The central control unit outputs quantitative and visual information on the large screen in the monitoring center. The output includes: the precise pipeline mileage of the leakage point (accuracy ≤ 1.0m), the leakage risk level (determined by the risk index R), and the location reliability (≥ 95%).

[0051] Low risk (0 < R < 0.3): The monitoring platform displays a green pop-up notification, records relevant data to the system database, and automatically generates a pipe wall damage analysis report every month; Medium risk (0.3 < R < 0.7): A yellow pop-up notification appears on the monitoring platform, and an early warning message is sent to the maintenance team leader via SMS / WeChat, prompting them to complete a special pipeline inspection within 72 hours; High risk (R≥0.7): The monitoring platform will issue a red pop-up alarm, sending an emergency warning to the maintenance team and company management. At the same time, it will trigger the audible and visual alarm devices, prompting the team to rush to the site within 2 hours to handle the leakage.

[0052] If the detection device experiences a power outage or communication failure, adjacent nodes can sense the fault status through the Mesh self-organizing network and automatically adjust the transmission beam angle and detection range to fill the blind spot of the faulty node. The central control unit simultaneously outputs the faulty node number, the corresponding pipeline mileage, and the status of the surrounding nodes' coverage, and pushes the information to the equipment maintenance personnel via SMS, prompting them to complete the repair of the faulty equipment within 24 hours, ensuring that the system has no blind spot detection throughout the entire process.

[0053] The above is a further description of the present invention in conjunction with specific embodiments, and the scope of protection of the present invention is not limited thereto.

Claims

1. A long-distance water supply pipeline leakage detection device based on wave interferometry, characterized in that, It includes a central control unit, multiple underwater sonar detection devices set at certain intervals on the inner wall of the pipe to be tested, a signal processing and communication unit connected to the underwater sonar detection devices, and a pipe wall stress sensing unit set in the pipe. The underwater sonar detection device includes a sound wave transmitting unit, a sound wave receiving and storage unit, and a clock synchronization module. The sound wave transmitting unit generates ultrasonic signals of specific wavelength and frequency through a high-frequency oscillation circuit, and transmits them in a fan-shaped beam in both directions in front of and behind the pipe with adjustable power. The sound wave receiving and storage unit performs analog-to-digital conversion and preprocessing of the sound wave signals and reflected signals from the pipe environment through a data acquisition card and stores them locally. The clock synchronization module ensures that all underwater sonar detection devices operate under a unified time base. The pipe wall stress sensing unit identifies changes in pipe wall stress through stress sensors and processing circuits; The signal processing and communication unit includes an adaptive control module and a communication module. The adaptive control module has a built-in Fast Fourier Transform (FFT) algorithm and a noise feature recognition model. By acquiring real-time background noise signals, the time-domain signal is converted into a frequency-domain signal using the FFT algorithm. The noise amplitude, main frequency, and spectral distribution features are extracted and compared with preset thresholds. The noise data and stress data packets are then automatically triggered for transmission. The communication module enables signal transmission between the underwater sonar detection device and the central control unit, as well as self-organizing network interaction between the various underwater sonar detection devices; The central control unit includes an obstacle 3D modeling and signal correction module, a multiphysics field fusion analysis module, a leakage location calculation module, and a communication module; The multiphysics field fusion analysis module combines the acoustic data and stress data received from various underwater sonar detection devices to initially locate the pipeline leak point and determine the suspected area. Through the communication module, it issues instructions to the monitoring points closest to the area, ordering them to switch to active detection mode. And quantify and generate pipeline leakage risk levels; The obstacle 3D modeling and signal correction module creates and calls obstacle 3D models, performs phase cancellation processing on the received reflected wave signals, eliminates interference signals generated by obstacles, and retains only the effective interference signals of the missing points; The leakage location calculation module uses the time difference generated from the transmission signal to the received reflected signal, combined with the multi-beam collaborative interferometry calculation method, to accurately calculate the path difference Δd between the two signals reaching each device, and uses Δd to infer the precise location of the leakage point.

2. The long-distance water supply pipeline leakage detection device based on wave interferometry according to claim 1, characterized in that, The aforementioned pipe wall stress sensing unit is installed at the connection point between the inner wall of the pipe and the underwater sonar detection device.

3. A method for detecting leakage in long-distance water supply pipelines based on wave interferometry, characterized by: The steps include the following: S1. The central control unit periodically sends time synchronization commands to the underwater sonar detection devices at each monitoring point, and the clock synchronization module is used to achieve microsecond-level time synchronization. S2. All underwater sonar detection devices passively monitor the acoustic environment in the pipeline under normal circumstances. When a leak occurs, they will detect that the high-pressure water jet from the rupture and the friction will generate a continuous noise signal in a specific frequency band. S3. The adaptive control module analyzes the background noise signal spectrum in real time. When the noise amplitude exceeds the threshold, it automatically triggers the transmission of noise data and stress data packets. S4. Leakage noise and pipe wall stress sensing units with precise timestamps collect stress data and pipeline pressure data, and upload them synchronously to the central control unit. The central control unit uses a multi-physics field fusion analysis module to combine acoustic data and stress data to initially locate suspected areas of pipeline leakage and determine the leakage risk level. S5. After initial positioning, the central control unit issues instructions to the monitoring points closest to the area, ordering them to conduct active detection. The underwater sonar devices of the monitoring points closest to the area sequentially emit ultrasonic pulses toward the suspected area. When the ultrasonic pulses encounter the leak, they will be reflected. After a certain period of time, the reflected waves are received by the underwater sonar devices. S6. The obstacle 3D modeling and signal correction module of the central control unit performs phase cancellation processing on the received reflected wave signal by establishing and calling the obstacle 3D model, eliminating the interference signal generated by the obstacle, and retaining only the effective interference signal of the missing point; S7. Utilize the time difference between the signal emitted by the device and the reflected signal received, and combine the multi-beam cooperative interferometry calculation method to calculate the path difference Δd between the two signals reaching each device, and use Δd to infer the precise location of the leak point. S8. Visualize the calculated precise coordinates and risk level of the leakage point and trigger a tiered early warning.

4. The method for detecting leakage in long-distance water supply pipelines based on wave interferometry according to claim 3, characterized in that, The method for initially locating and determining the suspect area using the multiphysics fusion analysis module described in step S4 is as follows: (1) Perform time-domain amplitude, main frequency, and spectrum continuity analysis on the noise of each node, and screen out 2-3 abnormal nodes whose signal amplitude is significantly higher than the background threshold and whose spectrum characteristics match the leakage characteristics; (2) Identify the core node with the strongest signal and its adjacent abnormal nodes; (3) The areas extending outward from the core node and the adjacent abnormal node by 100m and 50m respectively are the initial suspected leakage areas.

5. The method for detecting leakage in long-distance water supply pipelines based on wave interferometry according to claim 3, characterized in that, The steps for determining the leakage risk level are as follows: (1) Data acquisition and preprocessing The system synchronously collects and uploads ultrasonic interference data, pipe wall stress data, and water pressure data from pipeline pressure monitoring points. Wavelet transform is used to denoise the ultrasonic data, and moving average filtering is used to denoise the stress and water pressure data to remove outliers from all data and ensure data validity. (2) Feature extraction and weight allocation: Extract the leakage-sensitive features of the three types of data, allocate them according to the weight coefficients specified in the engineering calibration, and satisfy ω1+ω2+ω3=1. The specific weights and sensitive features are as follows: a. Ultrasonic interferometric data: weight ω1=0.55, sensitive features are amplitude abrupt change rate ΔA / A0 and dominant frequency offset Δf / f0; b. Pipe wall stress data: weight ω2=0.25, sensitive features are stress change rate dσ / dt and stress peak σmax; c. Water pressure data: weight ω3=0.20, sensitive features are pressure change rate dP / dt and pressure fluctuation amplitude ΔP; (3) Quantitative generation of leakage risk level: A leakage risk index calculation model is constructed. The fused feature data is substituted into the model to obtain the quantitative risk index R. Based on the R value, leakage risks are divided into three levels: low, medium, and high. The model formula is as follows: ， In the formula: σ0 is the allowable design stress of the pipe wall, and P0 is the design working pressure of the pipeline. Risk level classification criteria: low risk 0 < R < 0.3, medium risk 0.3 < R < 0.7, high risk R ≥ 0.

7.

6. The method for detecting leakage in long-distance water supply pipelines based on wave interferometry according to claim 3, characterized in that, In step S5, the active detection dynamically adjusts the ultrasonic power based on the distance to the initially located leakage area.

7. The method for detecting leakage in long-distance water supply pipelines based on wave interferometry according to claim 3, characterized in that, Step S6 first uses ultrasonic scanning to initialize the system, constructs a high-precision three-dimensional acoustic model of the flanges and valves inside the pipeline, extracts the acoustic features of the obstacles, and stores them; During the active detection phase, the received reflected wave signal is matched with the obstacle features to accurately identify the obstacle interference signal. Then, the interference signal is corrected and eliminated through phase compensation and amplitude cancellation algorithms, retaining only the effective interference signal of the missed point and eliminating the impact of the obstacle on the positioning accuracy.

8. The method for detecting leakage in long-distance water supply pipelines based on wave interferometry according to claim 7, characterized in that, The steps for identifying obstacle interference signals are as follows: Extract the characteristic parameters of the reflected wave signal received during the active detection phase, including arrival time t, dominant frequency f, phase φ, and amplitude A; perform template matching with the parameters in the obstacle feature database; and calculate the matching degree S using the cosine similarity algorithm. The formula is: ， In the formula: x i The feature vector (x) of the received signal i =[t,f,φ,A]); y i For the feature vector (y) of obstacles in the database i =[t ob,, f ob ,φ ob A ob ]); Matching degree judgment criteria: S≥90%, judged as obstacle interference signal; If S < 80%, it is determined to be a valid reflection signal from the leakage point; if 80% < S < 90%, it is verified by combining the spatial position of the obstacle's three-dimensional model. If the deviation between the signal source and the obstacle's coordinates is ≤ 1.0m, it is determined to be an interference signal; otherwise, it is a valid signal.

9. The method for detecting leakage in long-distance water supply pipelines based on wave interferometry according to claim 3, characterized in that, The calculation process in step S7 is as follows: (1) Select two adjacent underwater sonar detection devices A and B around the suspected leakage area as reference nodes. Construct a one-dimensional coordinate system with device A as the origin and the pipeline extension direction as the X-axis. The coordinates of device B are (L AB ,0),L AB The fixed installation distance between the two devices is specified; the precise arrival time t of the reflected waves received by devices A and B at the leakage points is collected and recorded. A t B ; (2) Calculation of one-way propagation distance and path difference: Calculate the one-way propagation distance L from the two reference nodes to the leakage point based on the propagation speed v of ultrasound in water. A L B ,formula: L A =(v×t A ) / 2, L B =(v×t B Based on the one-way propagation distance, calculate the path difference Δd between the two nodes and the leakage point, using the formula: ； (3) Calculate the coordinates of the leakage point: Select the detection device A as the origin (0,0). Calculate the precise coordinates of the leakage point. Let the coordinates of the leakage point P be (x,0), that is, the X-axis coordinate value is directly equal to the actual length to point A. According to geometric relations |L AB The formula is: −x∣−x=Δd, which gives the precise coordinates x of the leakage point. ； (4) The actual pipeline mileage corresponding to the actual mileage conversion and three-dimensional positioning extension combined device A is converted into the actual pipeline mileage of the leakage point by the calculated coordinate x, so as to complete the accurate positioning of the leakage point of the straight pipe section.

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