Method and device for detecting and positioning deep-buried metal pipeline, and electronic equipment

Abstract

The present application relates to the technical field of underground metal pipeline detection, and provides a deep-buried metal pipeline detection positioning method, device and electronic equipment, wherein the method comprises: injecting current into the pipeline to collect three-component magnetic field measured values; obtaining an abnormal magnetic field by vector-differentiating the background magnetic field based on the geoelectric parameter forward theory and the three-component magnetic field measured values; determining an adaptive threshold and a confidence weight based on the statistical characteristics of the background area, and processing to obtain a standardized abnormal field; and obtaining a planar position by ridge line tracking of the standardized abnormal field. Thus, the surface high-resistance layer, stray current and parallel pipeline interference can be effectively stripped, and the pipeline position can be adaptively extracted through ridge line tracking, thereby improving the signal-to-noise ratio of the weak magnetic response of a small-diameter pipeline buried more than 3 meters deep, avoiding the problems of the existing detection instrument needing to know the strike and only relying on peak value judgment, and the problems of radar and resistivity method being subject to high-conductivity soil attenuation, limited detection depth and complicated construction, and ensuring the accurate positioning effect of the deep-buried pipeline with unknown strike.

Description

Technical Field

[0001] This invention relates to the field of underground metal pipeline detection technology, and in particular to a method, device and electronic equipment for detecting and locating deeply buried metal pipelines. Background Technology

[0002] As a crucial component of urban infrastructure, the accurate location information of buried metal pipelines is fundamental for urban planning, construction excavation, and pipeline maintenance. However, due to historical reasons, design drawings for a large number of older pipelines are missing or do not match the actual situation. Furthermore, trenchless construction sections, sections covered by surface buildings, and deeply buried pipelines all pose significant challenges to existing pipeline detection technologies.

[0003] However, pipeline detection methods require prior knowledge of the pipeline's direction to trace it, rendering them ineffective when the direction is unknown. While ground-penetrating radar (GPR) and conventional resistivity methods do not rely on known direction, their detection depth is limited or their construction is cumbersome. Pipeline detection methods are susceptible to interference from parallel pipelines and stray currents; GPR signals attenuate rapidly in high-conductivity soils; and conventional resistivity methods are significantly affected by high-resistivity layers and stray currents. For pipelines buried deeper than 3 meters, the signal-to-noise ratio of these methods drops sharply, making effective identification difficult. Pipeline detection methods rely solely on peak signal strength to determine location, without background field modeling or differential processing; GPR methods rely on manual interpretation; and conventional resistivity methods have a weak response to deeply buried small-diameter pipelines. Summary of the Invention

[0004] This invention provides a method, device, and electronic equipment for detecting and locating deeply buried metal pipelines, which solves the defects of existing underground pipeline detection technologies, such as the need to know the pipeline route in advance, poor anti-interference and anti-geological condition capabilities, limited detection depth, and lack of effective data means such as background field modeling and differential processing, resulting in low signal-to-noise ratio of deeply buried pipelines, difficulty in effective identification, and limited overall applicability.

[0005] This invention provides a method for detecting and locating deeply buried metal pipelines, comprising the following steps.

[0006] Current is injected into the underground target metal pipe through the power supply electrode to excite the target magnetic field underground. The three-component magnetic field measured values ​​are collected at multiple measuring points in the surface survey area located above the target metal pipe. The three-component magnetic field measured values ​​include the component of the target magnetic field at each of the measuring points. Based on the geoelectric parameters of the surface survey area, a background field forward modeling is performed to obtain the theoretical background magnetic field. The measured values ​​of the three-component magnetic field are then vector-differed with the theoretical background magnetic field to obtain the anomalous magnetic field. Within the surface survey area, a background region excluding the target metal pipe is determined. An adaptive threshold is determined based on the statistical characteristics of the background region. A confidence weight for each survey point is generated based on the adaptive threshold. The abnormal magnetic field is processed based on the confidence weight to obtain a standardized abnormal field. Ridge tracing is performed on the standardized anomaly field to obtain the planar position of the target metal pipe.

[0007] According to the present invention, a method for detecting and locating deeply buried metal pipes, wherein determining an adaptive threshold based on the statistical characteristics of the background area includes: A sliding window is constructed with each of the aforementioned measuring points within the surface survey area as the center. Determine the sample mean and sample standard deviation of the abnormal magnetic field within the sliding window; A background reference set is selected in the background region, and a background amplitude reference is determined based on the background reference set; The background signal-to-noise ratio distribution is determined based on the sample mean, the background amplitude benchmark, and the sample standard deviation corresponding to each measurement point in the background region. The preset quantile of the background signal-to-noise ratio distribution is determined as the adaptive threshold.

[0008] According to the present invention, a method for detecting and locating deeply buried metal pipes, wherein generating confidence weights for each measuring point based on the adaptive threshold includes: Based on the sample mean, sample standard deviation and background amplitude benchmark corresponding to each measurement point, the local signal-to-noise ratio index corresponding to each measurement point is determined. Obtain the interquartile range of the local signal-to-noise ratio index within the background region, and determine the smoothing coefficient based on the interquartile range; Based on the local signal-to-noise ratio index, the adaptive threshold, and the smoothing coefficient, the confidence weights corresponding to each measurement point are generated.

[0009] According to the present invention, a method for detecting and locating deeply buried metal pipelines includes processing the anomalous magnetic field based on the confidence weight to obtain a standardized anomalous field, comprising: Extract the magnetic field magnitude of the abnormal magnetic field at each of the aforementioned measurement points; Global extremum mapping is performed on each of the magnetic field magnitudes to obtain a preliminary normalized field. Based on the preliminary normalized field, the standardized anomaly field is determined.

[0010] According to the present invention, a method for detecting and locating deeply buried metal pipes, wherein ridge tracing is performed on the standardized anomaly field to obtain the planar position of the target metal pipe includes: The standardized anomaly field is spatially interpolated and densified using the Kriging interpolation method to generate a continuous anomaly field grid. Determine the two-dimensional horizontal gradient distribution of the continuous anomaly field grid; Local high value seed points are determined in the continuous anomaly field grid, and planar ridge lines are searched along the orthogonal direction of the two-dimensional horizontal gradient starting from the local high value seed points to extract the ridge line skeleton. Curve fitting is performed on the ridge skeleton to obtain the planar position of the target metal pipe.

[0011] According to the present invention, a method for detecting and locating deeply buried metal pipelines, wherein the step of performing background field forward modeling based on the geoelectric parameters of the surface survey area to obtain the theoretical background magnetic field includes: Obtain the soil resistivity distribution model of the surface survey area; A three-dimensional forward modeling grid covering the surface survey area is constructed, and the three-dimensional forward modeling grid is assigned values ​​based on the soil resistivity distribution model to obtain an equivalent background stratum model that does not contain the high conductivity characteristics of the target metal pipe. The theoretical background magnetic field is determined based on the equivalent model of the background strata and the spatial coordinates of the power supply electrode.

[0012] According to the present invention, a method for detecting and locating deeply buried metal pipes is provided, wherein the method of injecting current into the underground target metal pipe through power supply electrodes includes a targeted power supply method and a surface power supply method.

[0013] According to the present invention, a method for detecting and locating deeply buried metal pipes, wherein ridge tracing is performed on the standardized anomaly field to obtain the planar position of the target metal pipe, the method further includes: A dense survey line is laid out in a direction perpendicular to the plane position, and the magnetic anomaly profile curve on the dense survey line is obtained. Construct a theoretical magnetic field profile model; The burial depth of the target metal pipe is obtained by fitting the theoretical magnetic field profile model and the magnetic anomaly profile curve using the nonlinear least squares method.

[0014] The present invention also provides a detection and positioning device for deeply buried metal pipes, comprising the following units: The acquisition unit is used to inject current into the underground target metal pipe through the power supply electrode to excite the target magnetic field underground, and to acquire the measured values ​​of the three-component magnetic field at multiple measuring points in the surface survey area located above the target metal pipe; the measured values ​​of the three-component magnetic field include the component of the target magnetic field at each of the measuring points. The vector difference calculation unit is used to perform background field forward modeling based on the geoelectric parameters of the surface survey area, obtain the theoretical background magnetic field, and perform vector difference between the measured values ​​of the three-component magnetic field and the theoretical background magnetic field to obtain the anomalous magnetic field. The processing unit is configured to determine a background area excluding the target metal pipe within the surface survey area, determine an adaptive threshold based on the statistical characteristics of the background area, generate confidence weights for each of the survey points based on the adaptive thresholds, and process the anomalous magnetic field based on the confidence weights to obtain a standardized anomalous field. The ridge tracing unit is used to perform ridge tracing on the standardized anomaly field to obtain the planar position of the target metal pipe.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-described methods for detecting and locating deeply buried metal pipes.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the deep-buried metal pipeline detection and positioning method as described above.

[0017] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the deep-buried metal pipeline detection and positioning method as described above.

[0018] The present invention provides a method, device, and electronic equipment for detecting and locating deeply buried metal pipelines. It involves injecting current into the pipeline to collect measured values ​​of a three-component magnetic field; obtaining an anomalous magnetic field by vector difference between the background magnetic field based on the forward modeling theory of geoelectric parameters and the measured three-component magnetic field values; determining an adaptive threshold and confidence weight based on the statistical characteristics of the background region to obtain a standardized anomalous field; and tracing the ridgeline of the standardized anomalous field to obtain the planar position. This effectively removes interference from high-resistivity layers, stray currents, and parallel pipelines on the surface, and then adaptively extracts the pipeline position through ridgeline tracing. This improves the signal-to-noise ratio of the weak magnetic response of small-diameter pipelines buried deeper than 3 meters, avoiding the problems of existing detectors requiring prior knowledge of the pipeline's orientation and relying solely on peak values, as well as the limitations of radar and resistivity methods due to attenuation in highly conductive soil, limited detection depth, and cumbersome construction. This ensures accurate positioning of deeply buried pipelines with unknown orientations. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the method for detecting and locating deeply buried metal pipelines provided by the present invention.

[0021] Figure 2 This is a schematic diagram of the physical model of the pipeline detection method provided by the present invention using magnetoresistivity.

[0022] Figure 3 This is a schematic diagram of the process for determining the burial depth of a target metal pipe provided by the present invention.

[0023] Figure 4 This is a schematic diagram of the three-dimensional model of the branch metal pipe provided by the present invention.

[0024] Figure 5 This is a schematic diagram of the branch pipe model and mesh division provided by the present invention.

[0025] Figure 6 This is a schematic diagram of abnormal magnetic field signals under different power supply methods provided by the present invention.

[0026] Figure 7 This is a schematic diagram of the pipeline model burial depth inversion results provided by the present invention.

[0027] Figure 8 This is a schematic diagram illustrating the detection results of an unidentified deeply buried pipeline in a certain region using the method of this invention.

[0028] Figure 9 This is a schematic diagram of the structure of the deep-buried metal pipeline detection and positioning device provided by the present invention.

[0029] Figure 10 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0031] Among related technologies, commonly used buried metal pipeline detection techniques all have certain limitations in practical applications. Pipeline detectors rely on applying alternating current to the pipeline and tracking the peak of the surface magnetic field to locate it. However, this requires knowledge of the pipeline's approximate route and the existence of accessible exposed points. If the route is unknown, the measurement path cannot be determined. Furthermore, for pipelines buried deeper than 3 to 5 meters, severe surface signal attenuation leads to a low signal-to-noise ratio, making effective identification impossible. Ground-penetrating radar (GPR) detects pipelines by emitting high-frequency electromagnetic waves and receiving reflected echoes from underground. However, its effective depth is typically limited to 3 to 5 meters, and electromagnetic waves attenuate rapidly in clay or high-conductivity soils, resulting in poor imaging quality and making it unsuitable for deep-buried environments. Conventional resistivity methods measure apparent resistivity distribution by deploying electrodes, which is not only cumbersome and inefficient, but also makes it difficult to separate minute anomalies caused by deeply buried pipelines from the complex background field. Additionally, while seismic wave methods can detect at greater depths, the reflected signals from deeply buried small-diameter pipelines are extremely weak, and the equipment is bulky and expensive.

[0032] In summary, existing technologies have significant limitations in detecting metal pipes buried at depths greater than 3 to 5 meters with unknown orientations. There is an urgent need for a new method that can effectively detect deeply buried targets without requiring prior knowledge of their orientation.

[0033] This invention provides a method for detecting and locating deeply buried metal pipes. Figure 1 This is a flowchart illustrating the method for detecting and locating deeply buried metal pipelines provided by this invention. Figure 1 As shown, the method includes the following: Step 110: Inject current into the underground target metal pipe through the power supply electrode to excite the target magnetic field underground, and collect the measured values ​​of the three-component magnetic field at multiple measuring points in the surface survey area located above the target metal pipe; the measured values ​​of the three-component magnetic field include the component of the target magnetic field at each of the measuring points.

[0034] Specifically, firstly, current can be injected into the underground target metal pipe through the power supply electrode to excite the target magnetic field underground, and then the three-component magnetic field measured values ​​at multiple measuring points in the surface survey area above the target metal pipe can be collected.

[0035] Among them, the power supply electrode is the physical contact point that transmits electrical energy to the underground medium and the target pipeline; the target metal pipeline refers to the underground buried metal pipeline entity to be detected and located.

[0036] Here, the target magnetic field refers to the spatial magnetic field distribution excited by the injected current propagating through underground metal pipes and the surrounding medium. The surface survey area refers to a two-dimensional or three-dimensional spatial region planned on the ground for collecting magnetic field signals.

[0037] Among them, multiple measuring points refer to the sampling locations of magnetic field sensors specifically arranged within the surface measuring area.

[0038] Here, the measured values ​​of the three-component magnetic field include the components of the target magnetic field at each measuring point. The measured values ​​of the three-component magnetic field refer to the total spatial magnetic field data containing three orthogonal components obtained from actual measurements at each measuring point.

[0039] In a preferred implementation scenario Figure 2 This is a schematic diagram of the physical model of the pipe detection method provided by the present invention, as shown below. Figure 2 As shown, the complete closed-loop process of excitation signal generation, transmission, physical response, and signal acquisition is clearly illustrated. The physical model mainly includes a constant current power supply system deployed on the Earth's surface, paired power supply electrodes connected to the system via wires, an underground pipe (red), and acquisition equipment for surface observation. Specifically, the constant current power supply system serves as the energy source, transmitting electrical energy to the power supply electrodes via wires. Under the coupling effect of the electrodes, a controlled current is injected underground, causing an axially flowing current (yellow) to be generated in the target metal pipe. Based on the principle of electromagnetic induction, the current (yellow) conducted axially along the target metal pipe will generate a surrounding magnetic field (green) in the space around the pipe. The acquisition equipment located on the surface above the pipe captures the vector signal of the magnetic field (green) in real time using a three-component sensor, providing raw data support for subsequent positioning analysis.

[0040] Depending on the site conditions, either targeted power supply or surface power supply can be selected for the power supply electrode connection. Then, the transmitter is turned on, injecting a low-frequency alternating current into the pipeline. The output frequency range is 1Hz to 500Hz, and the output current intensity is dynamically adjusted according to the pipe length, corrosion protection layer condition, and soil background resistivity. The typical operating range is 100mA to 1A. The transmitter's built-in shunt monitors the injected current waveform in real time. Simultaneously, a reference signal is output. Then, synchronous acquisition of the surface magnetic field is performed, i.e., collecting three-dimensional magnetic field data point by point along the planned survey line. A three-component high-sensitivity magnetic sensor is used, with the probe maintaining a consistent height above the ground surface and an orthogonal orientation along the three axes. To facilitate subsequent data processing, the measurement direction is uniformly northward. The acquisition system uses the reference signal output by the transmitter as the synchronization reference, with the sampling frequency set to 100Hz–1kHz. Through digital phase-locked amplification or narrowband spectrum filtering technology, the magnetic field component with the same frequency and phase as the injected current is extracted in real time, effectively suppressing power frequency harmonics, diurnal variations in geomagnetism, traffic micro-seismic activity, and human electromagnetic noise. The measured values ​​of the three-component magnetic field at each measuring point are recorded synchronously. It provides high-precision planar coordinates, and the data is transmitted to the processing terminal in real time via wireless / wired links.

[0041] Step 120: Perform forward modeling of the background field based on the geoelectric parameters of the surface survey area to obtain the theoretical background magnetic field, and perform vector difference between the measured values ​​of the three-component magnetic field and the theoretical background magnetic field to obtain the anomalous magnetic field.

[0042] Specifically, the background field can be forward modeled based on the geoelectric parameters of the surface survey area to obtain the theoretical background magnetic field, and the measured values ​​of the three-component magnetic field can be vector-differed with the theoretical background magnetic field to obtain the anomalous magnetic field.

[0043] Among them, geoelectric parameters refer to the spatial distribution of resistivity, conductivity, and other electrical properties of soil and strata within the surface survey area. The theoretical background magnetic field refers to the pure geomagnetic field response generated by a pure stratum medium under the same power supply excitation, assuming the absence of a target metal pipeline.

[0044] Among them, the abnormal magnetic field refers to the target magnetic field characteristics generated by the conduction current of the target metal pipe after the background of the earth has been stripped away in the measured magnetic field.

[0045] In a preferred implementation scenario, this step can be implemented in the following manner: A survey grid is planned in the surface area between the two pipeline exposure points. The direction of the survey lines can be arbitrarily set and does not need to be aligned with the estimated pipeline route; equally spaced measurement points are set on each survey line, with the distance between adjacent measurement points set to 1m to 5m, and the distance between adjacent survey lines set to 2m to 5m. Simultaneously, high-density electrical resistivity tomography, electromagnetic sounding, or regional geological borehole data are used to obtain a soil resistivity distribution model of the surface survey area. .

[0046] A forward-modeling mesh covering the survey area was constructed using the three-dimensional finite volume method. The formation conductivity and magnetic permeability of the potential pipeline distribution area were equivalently replaced with the surrounding background formation values, without introducing the pipeline's high conductivity / magnetic characteristics, thus forming a pure formation equivalent model "without pipeline electromagnetic disturbance." Based on this pure formation equivalent model, the measured spatial coordinates of the power supply electrodes, and the real-time injected current waveform... Using topographic data, the theoretical background magnetic field at each grid node on the Earth's surface is calculated. The theoretical background magnetic field characterizes the geomagnetic field response under the same excitation conditions when the current is conducted and diffused only through the geological medium. Its calculation process does not depend on the prior precise spatial location of the pipeline under test.

[0047] The obtained three-component measured magnetic field values The theoretical background magnetic field of forward modeling By performing a three-component vector difference, the anomalous magnetic field excited by the pipe conduction current is obtained. : ; in, This anomalous magnetic field originates from the conduction current magnetic field generated by the Biot-Savart law when the injected current is conducted axially along the metal pipe. The magnetic field magnitude forms a strip-shaped anomalous distribution in the surface survey area. The trajectory of the maximum anomalous gradient has a definite mapping relationship with the position of the pipe's planar projection. The amplitude is proportional to the intensity of the injected current, and the direction follows the right-hand screw rule.

[0048] Step 130: Determine a background area within the surface survey area that does not include the target metal pipe; determine an adaptive threshold based on the statistical characteristics of the background area; generate confidence weights for each of the survey points based on the adaptive thresholds; and process the anomalous magnetic field based on the confidence weights to obtain a standardized anomalous field.

[0049] Specifically, a background area excluding the target metal pipe is determined within the surface survey area, and an adaptive threshold is determined based on the statistical characteristics of the background area.

[0050] Here, the background area refers to the pure background stratigraphic reference area within the surface survey area that is not subject to electromagnetic disturbance from the target metal pipe. Statistical characteristics refer to the mathematical distribution patterns and noise fluctuation levels of the anomalous magnetic field data within the background area.

[0051] The adaptive threshold refers to the critical reference value that is automatically calculated based on the current background noise level to distinguish between effective pipeline signals and background interference.

[0052] After determining the adaptive threshold, confidence weights for each measurement point can be generated based on the adaptive threshold. The abnormal magnetic field can then be processed based on the confidence weights to obtain the standardized abnormal field.

[0053] Here, the confidence weight is used to reflect the reliability of the abnormal magnetic field data at each measuring point as belonging to the real pipeline signal. The standardized abnormal field refers to the magnetic field distribution used for target identification after weight modulation and dimensional unification, in which background noise is effectively suppressed and weak abnormal features are reasonably preserved.

[0054] In terms of implementation principle, since the traditional fixed threshold method faces significant limitations under varying environmental noise levels, this step derives an adaptive threshold that dynamically changes with environmental noise by statistically analyzing the data patterns of anomalous magnetic field samples in the background region (without pipe prediction). Furthermore, based on the relative relationship between the data at each measuring point and the adaptive threshold, a soft confidence weight is assigned to each measuring point using a continuous and smooth mapping function. Applying these confidence weights to the anomalous magnetic field enables adaptive filtering and normalization under complex noise environments, outputting a standardized anomalous field with uniform dimensions.

[0055] Step 140: Perform ridge line tracing on the standardized anomaly field to obtain the planar position of the target metal pipe.

[0056] Specifically, after obtaining the standardized anomaly field, ridge line tracing can be performed on the standardized anomaly field to obtain the planar position of the target metal pipe.

[0057] Here, the planar position of the target metal pipe refers to the two-dimensional projection trajectory and direction of the target metal pipe on the horizontal plane of the ground.

[0058] In terms of implementation principle, since the standardized anomaly field exhibits a distinct banded maximum distribution pattern directly above the target metal pipe, its shape resembles a "ridge" on a topographic map. Here, conventional image processing, interpolation techniques, or two-dimensional gradient tracing algorithms can be used to find local anomaly extrema points in the spatial grid as seed points. Subsequently, based on the horizontal gradient direction of the anomaly field distribution, a point-by-point or continuous path search and connection is performed along the trend of maximum values. Through this ridge tracing mechanism, a continuous skeleton trajectory representing the projection of the pipe's centerline can be automatically extracted, thereby outputting the accurate planar position of the target metal pipe. This processing mechanism is entirely data-driven and requires no prior knowledge of the pipe's orientation.

[0059] The method provided in this invention involves injecting current into a pipeline to collect measured values ​​of a three-component magnetic field; obtaining an anomalous magnetic field by vector difference between the background magnetic field based on the forward modeling theory of geoelectric parameters and the measured values ​​of the three-component magnetic field; determining an adaptive threshold and confidence weight based on the statistical characteristics of the background region to obtain a standardized anomalous field; and tracing the ridgeline of the standardized anomalous field to obtain its planar position. This effectively removes interference from the high-resistivity layer, stray currents, and parallel pipelines on the ground, and then adaptively extracts the pipeline position through ridgeline tracing. This improves the signal-to-noise ratio of the weak magnetic response of small-diameter pipes buried at depths greater than 3 meters, avoiding the problems of existing detectors requiring prior knowledge of the pipeline's orientation and relying solely on peak values, as well as the limitations of radar and resistivity methods due to attenuation in highly conductive soil, limited detection depth, and cumbersome construction. This ensures accurate positioning of deeply buried pipelines with unknown orientations.

[0060] Based on the above embodiments, step 130, determining the adaptive threshold based on the statistical characteristics of the background region, includes: Step 1301: Construct a sliding window centered on each of the measuring points within the surface survey area; Step 1302: Determine the sample mean and sample standard deviation of the abnormal magnetic field within the sliding window; Step 1303: Select a background reference set in the background region and determine the background amplitude reference based on the background reference set; Step 1304: Determine the background signal-to-noise ratio distribution based on the sample mean, the background amplitude benchmark, and the sample standard deviation corresponding to each measurement point in the background area; Step 1305: Determine the preset quantile of the background signal-to-noise ratio distribution as the adaptive threshold.

[0061] Specifically, firstly, a sliding window can be constructed with each measuring point in the surface survey area as the center. Then, the sample mean and sample standard deviation of the abnormal magnetic field within the sliding window can be determined.

[0062] The sliding window refers to the set of local neighborhood spatial data intercepted with the current measuring point as the center; the sample mean and sample standard deviation are used to reflect the average level and discrete fluctuation of the abnormal magnetic field intensity within the local neighborhood of the sliding window.

[0063] Furthermore, a background reference set can be selected in the background area, and the background amplitude benchmark can be determined based on the background reference set.

[0064] Among them, the background reference set refers to a pure background data sample library within the surface survey area that is clearly free from interference from the pipeline under test; the background amplitude benchmark is used to reflect the overall median or baseline level of the magnetic field anomaly values ​​within the background reference set.

[0065] Finally, the background signal-to-noise ratio distribution can be determined based on the sample mean, background amplitude benchmark, and sample standard deviation corresponding to each measurement point in the background area, and the preset quantile of the background signal-to-noise ratio distribution can be determined as the adaptive threshold.

[0066] Here, the background signal-to-noise ratio distribution is used to reflect the degree of deviation of each point in the background reference set relative to the background baseline and its distribution pattern. The preset quantile refers to the critical percentage position selected on the statistical probability distribution to separate the effective signal from the noise.

[0067] In a preferred implementation scenario, this step is implemented in the following manner: ① Calculation of local statistics.

[0068] Each measuring point within the surface survey area Built around Sliding window (Preferred values: M=5,7,9), let the total number of measurement points within the sliding window be... (When grid rules) ).

[0069] ② Background benchmark adaptive calibration.

[0070] Select a background reference set in areas of the survey region without pipeline prediction. Calculate the background amplitude benchmark ,in, The magnitude of the magnetic field representing an abnormal magnetic field. Represents each measuring point; background signal-to-noise ratio distribution, i.e., background Value distribution , ,in, Represents the sample mean. Represents the sample standard deviation, adaptive threshold (Background area) The 95th percentile of the statistical distribution approximately follows a standard normal distribution; background noise level. (Interquartile range method).

[0071] Here, the formulas for the sample mean and sample standard deviation are as follows: ; in, Represents the sample mean. This indicates the total number of measurement points within the sliding window. Indicates the coordinates within the sliding window as The magnitude of the abnormal magnetic field generated by the pipeline at the measuring point. This represents the sample standard deviation.

[0072] The method provided in this invention, by introducing a sliding window and statistically adaptive thresholds based on a background reference set, can completely eliminate the dependence on fixed thresholds based on human experience, realize the dynamic calibration of adaptive thresholds according to the electromagnetic noise environment on site, and significantly improve the detection accuracy and robustness under complex geological conditions.

[0073] Based on the above embodiments, step 130, which involves generating confidence weights for each measurement point based on the adaptive threshold, includes: Step 130-1: Based on the sample mean, sample standard deviation and background amplitude benchmark corresponding to each measurement point, determine the local signal-to-noise ratio index corresponding to each measurement point. Step 130-2: Obtain the interquartile range of the local signal-to-noise ratio index within the background region, and determine the smoothing coefficient based on the interquartile range; Step 130-3: Based on the local signal-to-noise ratio index, the adaptive threshold, and the smoothing coefficient, generate the confidence weight corresponding to each measurement point.

[0074] Specifically, firstly, the local signal-to-noise ratio (SNR) for each measurement point can be determined based on the sample mean, sample standard deviation, and background amplitude benchmark, as shown in the following formula: ; in, This represents the local signal-to-noise ratio. Represents the sample mean. Indicates the sample standard deviation. .

[0075] Among them, the local signal-to-noise ratio index is used to reflect the degree of significance of the fluctuation of the signal strength in the local neighborhood of the measurement point relative to the background noise.

[0076] Furthermore, the interquartile range of the local signal-to-noise ratio (SNR) within the background region can be obtained, and the smoothing coefficient can be determined based on the interquartile range, as shown in the following formula: ; in, Represents the smoothing coefficient. This represents the interquartile range of the local signal-to-noise ratio. ∈[1.5,3.0] is the smoothing coefficient, and its value is determined based on the following: when the background noise fluctuates greatly ( Automatically lower when large) To enhance the smoothness of the weight curve and avoid false suppression of weak anomalies; when the background is stable ( (Small) Increasing k by a factor of 100 to enhance anomalous contrast, while maintaining the normalized anomalous field within this range. It is first-order continuous and differentiable in space.

[0077] Then, based on the local signal-to-noise ratio index, adaptive threshold, and smoothing coefficient, the confidence weights corresponding to each measurement point are generated.

[0078] Here, the interquartile range is used to reflect the difference between the upper and lower quartiles in the background signal-to-noise ratio distribution, characterizing the fluctuation range of the background noise; the smoothness coefficient is an adjustment parameter that controls the steepness or flatness of the confidence weight mapping function curve.

[0079] Finally, the confidence weights for each measurement point can be generated based on the local signal-to-noise ratio, adaptive threshold, and smoothing coefficient, as shown in the following formula: ; in, Indicates the confidence weight. This represents the local signal-to-noise ratio. Represents the smoothing coefficient. This indicates an adaptive threshold.

[0080] It should be noted that the derivative property of the sigmoid function is subject to numerical stability constraints. This does not interfere with subsequent gradient extremum tracking.

[0081] Here, a basis-enhanced sigmoid function is used to ensure traceability is preserved in the low signal-to-noise ratio region. Background area , Amplitude attenuation of 25%~50%, preserving traceability of weak anomalies; anomaly area , Amplitude values ​​are fully preserved; transition zone , Balanced change, without step-like jumps.

[0082] Based on the above embodiments, step 130, which involves processing the anomalous magnetic field based on the confidence weight to obtain a standardized anomalous field, includes: Step 21: Extract the magnetic field magnitude of the abnormal magnetic field at each of the measurement points; Step 22: Perform global extremum mapping on each of the magnetic field moduli to obtain a preliminary normalized field; Step 23: Determine the standardized outlier field based on the preliminary normalized field and the confidence weight.

[0083] Specifically, firstly, the magnetic field magnitude of the abnormal magnetic field at each measuring point can be extracted, and then the global extremum mapping process can be performed on each magnetic field magnitude to obtain the preliminary normalized field.

[0084] The magnetic field magnitude of the anomalous magnetic field refers to the combined vector length of the three components of the anomalous magnetic field in space, representing information in the total intensity of the anomalous field. The preliminary normalized field refers to the initial processing result of mapping the global magnitude to a specific dimensional range (such as 0~1) to eliminate absolute amplitude differences.

[0085] Here, the formula for the magnetic field magnitude of the abnormal magnetic field is as follows: ; in, The magnitude of the abnormal magnetic field; This represents the magnetic field component value of the abnormal magnetic field vector in the x-direction; This represents the magnetic field component value of the abnormal magnetic field vector in the y direction; This represents the magnetic field component value of the abnormal magnetic field vector in the z-direction.

[0086] To simultaneously achieve dimensional uniformity and background noise suppression, this method employs a normalization strategy that integrates sliding window statistics and global extremum mapping to further generate a standardized anomaly field with enhanced confidence. The specific steps are as follows: ; in It features unified dimensions and supports threshold interpretation across operating conditions. Represents a standardized anomaly field; Representing coordinates The magnetic field magnitude of the abnormal magnetic field at the measuring point; Indicates the confidence weight; and They represent the entire survey area. Minimum and maximum values ​​of the internal anomalous magnetic field modulus; It is a numerical stability constant used to prevent the denominator from being zero.

[0087] Based on the above embodiments, step 140 includes: Step 140-1: Spatial interpolation and densification of the standardized anomaly field are performed using the Kriging interpolation method to generate a continuous anomaly field grid. Step 140-2: Determine the two-dimensional horizontal gradient distribution of the continuous anomaly field grid; Step 140-3: Determine local high value seed points in the continuous anomaly field grid, and use the local high value seed points as starting points to perform planar ridge line search along the orthogonal direction of the two-dimensional horizontal gradient to extract the ridge line skeleton. Step 140-4: Perform curve fitting on the ridge skeleton to obtain the planar position of the target metal pipe.

[0088] Specifically, firstly, the Kriging interpolation method can be used to spatially interpolate and refine the standardized anomaly field to generate a continuous anomaly field grid.

[0089] Here, the continuous anomaly field grid refers to a smooth data matrix with high spatial resolution formed after interpolation and encryption.

[0090] Secondly, the two-dimensional horizontal gradient distribution of the continuous anomalous field grid is determined. The two-dimensional horizontal gradient distribution refers to the direction and intensity distribution of the most drastic changes in the anomalous field amplitude at each point on the grid.

[0091] Furthermore, local high-value seed points can be determined in the continuous anomalous field grid, and a planar ridge search can be performed along the orthogonal direction of the two-dimensional horizontal gradient using the local high-value seed points as starting points to extract the ridge skeleton.

[0092] Here, a local high-value seed point refers to the coordinate node with the most significant abnormal features in a local area, which serves as the starting point for tracking; the ridge skeleton refers to a discrete topological line segment representing the potential axial projection of the pipeline, formed by connecting a series of maximum points.

[0093] Finally, curve fitting can be performed on the ridge skeleton to obtain the planar position of the target metal pipe.

[0094] In a preferred implementation scenario, this step is implemented in the following manner: For the output standardized anomaly field, extract the pipeline planar position in the following four steps: ① Kriging interpolation encryption.

[0095] Kriging is used to spatially interpolate and densify the original measurement point data. This method constructs a variogram model based on the spatial autocorrelation of the anomalous field, automatically fitting anisotropic parameters, and outputting the estimated variance of each interpolation point while generating a high-resolution continuous anomalous field. The densification factor is adaptively set according to the original measurement point spacing, making the grid resolution significantly better than the original sampling density; the interpolation variance can be used for subsequent quality weighting, and the tracking weight is automatically reduced in low-confidence areas.

[0096] ② Calculation of two-dimensional gradient field.

[0097] The horizontal gradient distribution of the anomaly field is calculated on the encrypted mesh to obtain the gradient intensity and direction at each point. The extension direction of the pipeline anomaly ridge is orthogonal to the gradient direction, and the local tracking path is determined accordingly to ensure that the gradient extrema are strictly aligned with the physical center of the pipeline.

[0098] ③ Global planar ridge line tracing.

[0099] Using local high-value points in the anomalous field as seeds, the search propagates point-by-point within the two-dimensional grid neighborhood along the ridge line: at each step, the node with the largest outlier in the fan-shaped neighborhood of the forward direction is selected as the next tracking point, and the local orientation is dynamically updated. This area tracking logic does not depend on the survey line direction and can automatically cross the gaps between survey points, effectively avoiding breaks and jumps; at the same time, combined with Kriging variance estimation, the tracking results in low-confidence areas are automatically downweighted or marked for verification.

[0100] ④ Centerline fitting output.

[0101] The morphological refinement of the ridge skeleton generated by tracking is performed to remove isolated branches and burrs, while retaining the main path; a smooth curve is used to fit discrete points to output a continuous sequence of coordinates of the center line of the pipeline plane projection and the distribution of the orientation angle.

[0102] The method provided in this invention, through Kriging interpolation combined with two-dimensional gradient planar ridge line tracing, can overcome the limitations of measurement point gaps and measurement line directions, automatically cross the fracture zone to extract continuous center lines, and completely solve the technical problem of blindly probing and easily failing to break lines when the pipeline direction is unknown in traditional methods.

[0103] Based on the above embodiments, step 120, which involves performing background field forward modeling based on the geoelectric parameters of the surface survey area to obtain the theoretical background magnetic field, includes: Step 1201: Obtain the soil resistivity distribution model of the surface survey area; Step 1202: Construct a three-dimensional forward modeling grid covering the surface survey area, and assign values ​​to the three-dimensional forward modeling grid based on the soil resistivity distribution model to obtain an equivalent background stratum model that does not contain the high conductivity characteristics of the target metal pipe; Step 1203: Determine the theoretical background magnetic field based on the background stratum equivalent model and the spatial coordinates of the power supply electrode.

[0104] Specifically, firstly, a soil resistivity distribution model of the surface survey area can be obtained. This soil resistivity distribution model refers to the three-dimensional resistivity structure of the subsurface medium in the survey area, obtained through geological exploration or electrical sounding.

[0105] Then, a three-dimensional forward modeling grid covering the surface survey area can be constructed, and the three-dimensional forward modeling grid can be assigned values ​​based on the soil resistivity distribution model to obtain an equivalent model of the background strata that does not contain the high conductivity characteristics of the target metal pipe.

[0106] Here, the background stratum equivalent model refers to a three-dimensional numerical simulation mesh that has removed the extremely high conductivity of metal pipelines and retained only the natural electrical structure of the earth.

[0107] Finally, the theoretical background magnetic field can be determined based on the equivalent model of the background strata and the spatial coordinates of the power supply electrode. Here, the spatial coordinates of the power supply electrode refer to the three-dimensional position of the physical origin of the current injection into the earth.

[0108] In a preferred implementation scenario, this step is implemented in the following manner: Simultaneously utilize high-density electrical resistivity, electromagnetic sounding, or regional geological borehole data to obtain soil resistivity distribution models. A forward-modeling grid covering the survey area is constructed using the three-dimensional finite volume method. The conductivity and permeability of the strata in the potential pipeline distribution area are equivalently replaced with the values ​​of the surrounding background strata, without introducing the high conductivity / magnetic characteristics of the pipeline, thus forming an equivalent background stratum model "without pipeline electromagnetic disturbance". Based on the equivalent background stratum model, the measured spatial coordinates of the power supply electrodes, the real-time injected current waveform, and topographic data, the theoretical background magnetic field at each grid node on the surface is solved. This theoretical background magnetic field characterizes the geomagnetic field response under the same excitation conditions when the current is only conducted and diffused through the stratum medium, and its calculation process does not depend on the prior precise spatial location of the pipeline under test.

[0109] The method provided in this invention replaces the traditional simple baseline subtraction with forward modeling based on a three-dimensional physical model, and accurately reconstructs the ground return response without the target pipeline from the physical mechanism level, which greatly improves the accuracy of stripping stray current interference from the formation.

[0110] Based on the above embodiments, the method of injecting current into the underground target metal pipe through the power supply electrode includes targeted power supply and surface power supply.

[0111] Specifically, depending on the site conditions, either targeted power supply or surface power supply can be selected for connecting the power supply electrodes: When there are accessible pipe exposure points, such as the outer wall of the pipe in a valve well, the terminal block of a cathodic protection test pile, or a pipe section exposed by a small excavation, the targeted power supply method is used. This involves clamping two power supply electrode clamps onto the outer walls of the metal pipes at the two exposure points, ensuring good electrical contact. One electrode is connected to the positive terminal of the transmitter, and the other to the negative terminal. In this method, the current is directly injected into the pipe and propagates along the pipe wall, resulting in high signal strength and strong anti-interference capability. When the pipe exposure point cannot be found or is inaccessible, such as being buried, encroached upon, or located in a hazardous area, the surface power supply method is used. This involves inserting two power supply electrodes into the ground using grounding pins, placing them on both sides of the expected pipe route. The electrode spacing is set according to the estimated burial depth, typically 1 to 2 times the burial depth. One electrode is connected to the positive terminal of the transmitter, and the other to the negative terminal. In this method, the current enters the pipe through soil coupling without contacting the pipe body, making it suitable for pipe sections without exposure points.

[0112] Based on the above embodiments, step 140 further includes: Step 310: Lay out a dense survey line in a direction perpendicular to the plane position, and obtain the magnetic anomaly profile curve on the dense survey line. Step 320: Construct a theoretical magnetic field profile model; Step 330: The theoretical magnetic field profile model and the magnetic anomaly profile curve are fitted using the nonlinear least squares method to obtain the burial depth of the target metal pipe.

[0113] Specifically, Figure 3 This is a schematic diagram of the process for determining the burial depth of a target metal pipe provided by the present invention, as shown below. Figure 3 As shown, dense survey lines are laid out in a direction perpendicular to the plane position, and magnetic anomaly profile curves on the dense survey lines are obtained.

[0114] Among them, the densified survey line refers to a straight measurement trajectory with higher sampling density arranged in the normal direction of the known pipeline route; the magnetic anomaly profile curve refers to the contour shape of the magnetic anomaly amplitude at each point on the densified survey line as a function of spatial distance.

[0115] Secondly, a theoretical magnetic field profile model is constructed, and the nonlinear least squares method is used to fit the theoretical magnetic field profile model and the magnetic anomaly profile curve to obtain the burial depth of the target metal pipe.

[0116] Here, the theoretical magnetic field profile model refers to the mathematical expression of the spatial magnetic field generated by an ideal current-carrying long straight conductor based on the Biot-Savart law. Burial depth refers to the vertical distance from the center axis of the target metal pipe to the Earth's surface.

[0117] In a preferred implementation scenario, this step is implemented in the following manner: After determining the pipeline's planar location, a denser survey line is laid out perpendicular to the pipeline's direction. The data processing unit first performs background field correction on the measured magnetic field data and extracts the magnetic anomaly profile curve from the denser survey line. According to the Biot-Savart law, the amplitude of the magnetic field generated by an infinitely long straight current-carrying conductor is inversely proportional to its perpendicular distance from the conductor. By fitting the theoretical curve and the measured anomaly curve, the burial depth of the pipeline's centerline can be determined. Typically, the full width at half maximum (FWHM) of the magnetic anomaly has a strictly monotonic relationship with the burial depth; the greater the burial depth, the flatter the anomaly curve and the greater its width.

[0118] Based on the above physical principles, the data processing unit constructs a theoretical magnetic field profile model with the pipe burial depth and equivalent current as undetermined parameters. Let the burial depth of the pipe centerline be... The horizontal distance from the surface measuring point to the pipeline's plane projection point is The perpendicular distance from the observation point to the traverse line is... Substituting into the Biot-Savart law, we obtain the theoretical expression for the magnetic field amplitude: ; in, The magnetic field strength, The permeability of free space, The current intensity in the conductor.

[0119] In actual inversion, to improve the robustness of the algorithm, the full width at half maximum (FWHM) of the measured curve is first used. Estimated initial value of burial depth And extract the initial value of the peak estimated current. Subsequently, a nonlinear least squares method, such as the Levenberg-Marquardt algorithm, is used to fit the theoretical curve to the measured profile, and the parameters that minimize the sum of squared residuals are solved. The final result obtained The value represents a high-precision estimate of the burial depth of the pipeline centerline.

[0120] As an auxiliary criterion, the half-maximum width of the magnetic field profile curve has a monotonically positive correlation with the pipeline burial depth: the greater the burial depth, the flatter the curve shape and the larger the half-maximum width; the smaller the burial depth, the steeper the curve shape and the smaller the half-maximum width. Operators can use this characteristic to quickly verify the inversion results.

[0121] As an alternative, when using gradient tensor measurement, one can... Replace with the formula for the horizontal gradient of the magnetic field Gradient measurement can automatically suppress background field interference in the region, and its extreme value position directly corresponds to the top of the pipeline. The analytical relationship between the half-maximum width and the burial depth is more direct, and the inversion robustness will be significantly improved.

[0122] The method provided in this invention, by constructing a theoretical profile model and performing nonlinear least squares fitting inversion, can fully utilize the physical geometric relationship between the full width of the magnetic field half-maximum and the depth, accurately calculate the three-dimensional spatial depth of the pipeline under deep burial conditions such as greater than 3 meters, make up for the deficiency of traditional surveying methods that can only determine the plane, and output more comprehensive and higher-dimensional high-precision positioning information.

[0123] Based on any of the above embodiments Figure 4 This is a schematic diagram of the three-dimensional model of the branched metal pipe provided by the present invention. Figure 5 This is a schematic diagram of the branch pipe model and mesh generation provided by the present invention, as shown below. Figure 4 , Figure 5 As shown, the 3D model simulates a typical complex underground pipe network structure in a city, including a main pipe and two horizontally distributed branch pipes. Specific model parameters are as follows: the maximum length of the main pipe is 24.3 m, and the diameter of both the main pipe and the branch pipes is 0.605 m. At the connection between the main pipe and the branch pipes, there is a connecting pipe section with a specific structure and a diameter of 1 m. One branch pipe has a horizontal length of 5.19 m, and the other has a horizontal length of 5.95 m, for a total length of 12.14 m. Furthermore, the 3D model identifies key depth information of the pipes, including a local vertical height (or specific segment depth) of 2.44 m and an overall pipe top burial depth of 3 m. During forward modeling, the 3D finite volume method was used to mesh the underground space containing the model. To comprehensively evaluate the impact of different excitation environments on the detection results, this embodiment sets up four typical power supply excitation schemes, namely power supply mode 1 (east-west direction), power supply mode 2 (north-south direction), power supply mode 3 (northwest-southeast direction), and power supply mode 4 (southwest-northeast direction).

[0124] Based on any of the above embodiments, in order to comprehensively evaluate the impact of different power supply excitation schemes on the detection and positioning effect, this embodiment conducts simulation analysis on four different power supply methods. Figure 6 This is a schematic diagram of abnormal magnetic field signals under different power supply methods provided by the present invention, such as... Figure 6 The diagram illustrates the two-dimensional distribution of power supply methods 1 (B_pipe), 2 (B_pipe), 3 (B_pipe), and 4 (B_pipe). Figure 6In each sub-graph, the coordinate range of the horizontal axis X (m) and the vertical axis Y (m) is set between -30 and 30. The yellow dots distributed at the edges of the graph represent the locations of the power supply electrodes. By using the normalized color scale from 0 to 1 on the side of the graph, it can be intuitively observed that regardless of the power supply direction, the metal pipe detection method based on magnetoresistivity of this invention can clearly determine the pipe's direction and planar center position. Based on the successful determination of the pipe's planar position, Figure 7 This is a schematic diagram of the pipeline model burial depth inversion results provided by the present invention, as shown below. Figure 7 As shown, the fitting verification results of the high-precision pipeline burial depth inversion are presented in detail. In this coordinate system, with the horizontal distance x (m) as the horizontal axis and the relative magnetic field amplitude (B / Bmax) as the vertical axis, the noisy measured data with a scattered distribution is intuitively superimposed with the actual theoretical curve and the finally generated weighted inversion fitting curve. It can be seen that the measured data closely follows the distribution of the theoretical model. Figure 7 Furthermore, at the full width at half maximum (FWHM) of a relative amplitude of 0.5, vertical auxiliary lines were used to clearly mark the corresponding positions of the true boundary (h=3) and the inversion boundary (h=2.84), and the relative inversion error of 5.31% was clearly indicated in the upper left corner, fully demonstrating the high accuracy of this nonlinear fitting inversion strategy in depth estimation. To further verify the practical value of this method in real-world complex engineering environments, Figure 8 This is a schematic diagram illustrating the detection results of an unidentified deeply buried pipeline in a certain region using the method of this invention, as provided by this invention. Figure 8As shown, the mapping effects before and after processing were compared. In the measured area with coordinates ranging from 471100 to 471220 east (m) and 3837640 to 3837700 north (m), by observing (a) the results of the magnetoresistivity method before normalization, it can be found that in the background of a large range of color levels from 15000 to 140000 (with significant contour lines such as 65000, 90000, and 115000 distributed in the figure), although the general direction of the anomaly can be roughly determined, the stray response of the strata causes serious background interference. However, when observing (b) the results of the magnetoresistivity method after normalization, combined with the normalized magnetic field strength color scale in the upper right corner ranging from 0.15 to 1, the background noise is effectively suppressed, and the target anomaly field shows extremely clear strip-shaped clustering characteristics. It is important to note that there are some interrupted transition zones between the high-frequency signals in the figure. This is mainly due to the certain intervals between the measuring lines during actual measurement, which leads to normal spatial attenuation and transition in the signal distribution range. The algorithm of this invention, by introducing a confidence soft weight mechanism, reasonably preserves the weak anomaly characteristics of these transition zones, avoiding the one-size-fits-all signal truncation caused by hard thresholds. This allows the subsequent global planar ridge tracking algorithm to automatically cross the gaps between measuring points and accurately extract the continuous pipeline center trajectory along the abnormal maxima. Moreover, this trajectory highly matches the green dots representing the later drilling verification positions, thus confirming the reliability and engineering implementation capability of the deep buried metal pipeline detection and positioning method of this invention in the detection of deep buried metal pipelines with unknown orientations.

[0125] The following describes the detection and positioning device for deeply buried metal pipelines provided by the present invention. The detection and positioning device for deeply buried metal pipelines described below can be referred to in correspondence with the detection and positioning method for deeply buried metal pipelines described above.

[0126] Based on any of the above embodiments, the present invention provides a detection and positioning device for deeply buried metal pipelines. Figure 9 This is a schematic diagram of the structure of the deep-buried metal pipeline detection and positioning device provided by the present invention, as shown below. Figure 9 As shown, the device includes: The acquisition unit 910 is used to inject current into the underground target metal pipe through the power supply electrode to excite the target magnetic field underground, and to acquire the measured values ​​of the three-component magnetic field at multiple measuring points in the surface survey area located above the target metal pipe; the measured values ​​of the three-component magnetic field include the component of the target magnetic field at each of the measuring points. The vector difference calculation unit 920 is used to perform background field forward modeling based on the geoelectric parameters of the surface survey area, obtain the theoretical background magnetic field, and perform vector difference between the measured values ​​of the three-component magnetic field and the theoretical background magnetic field to obtain the anomalous magnetic field. Processing unit 930 is configured to determine a background area excluding the target metal pipe within the surface survey area, determine an adaptive threshold based on the statistical characteristics of the background area, generate confidence weights for each of the survey points based on the adaptive thresholds, and process the anomalous magnetic field based on the confidence weights to obtain a standardized anomalous field. The ridge tracking unit 940 is used to perform ridge tracking on the standardized anomaly field to obtain the planar position of the target metal pipe.

[0127] The device provided in this invention injects current into a pipeline to collect measured values ​​of a three-component magnetic field; it obtains an anomalous magnetic field by vector difference between the background magnetic field based on the forward modeling theory of geoelectric parameters and the measured values ​​of the three-component magnetic field; it determines an adaptive threshold and confidence weight based on the statistical characteristics of the background region, and processes the data to obtain a standardized anomalous field; and it tracks the ridgeline of the standardized anomalous field to obtain the planar position. This effectively removes interference from the high-resistivity layer, stray currents, and parallel pipelines on the ground, and then adaptively extracts the pipeline position through ridgeline tracking. This improves the signal-to-noise ratio of the weak magnetic response of small-diameter pipes buried at depths greater than 3 meters, avoiding the problems of existing detectors requiring prior knowledge of the direction and relying solely on peak values, as well as the limitations of radar and resistivity methods due to attenuation in highly conductive soil, limited detection depth, and cumbersome construction. This ensures accurate positioning of deeply buried pipelines with unknown directions.

[0128] Based on any of the above embodiments, the processing unit 930 is specifically used for: A sliding window is constructed with each of the aforementioned measuring points within the surface survey area as the center. Determine the sample mean and sample standard deviation of the abnormal magnetic field within the sliding window; A background reference set is selected in the background region, and a background amplitude reference is determined based on the background reference set; The background signal-to-noise ratio distribution is determined based on the sample mean, the background amplitude benchmark, and the sample standard deviation corresponding to each measurement point in the background region. The preset quantile of the background signal-to-noise ratio distribution is determined as the adaptive threshold.

[0129] Based on any of the above embodiments, the processing unit 930 is specifically used for: Based on the sample mean, sample standard deviation and background amplitude benchmark corresponding to each measurement point, the local signal-to-noise ratio index corresponding to each measurement point is determined. Obtain the interquartile range of the local signal-to-noise ratio index within the background region, and determine the smoothing coefficient based on the interquartile range; Based on the local signal-to-noise ratio index, the adaptive threshold, and the smoothing coefficient, the confidence weights corresponding to each measurement point are generated.

[0130] Based on any of the above embodiments, the processing unit 930 is specifically used for: Extract the magnetic field magnitude of the abnormal magnetic field at each of the aforementioned measurement points; Global extremum mapping is performed on each of the magnetic field magnitudes to obtain a preliminary normalized field. Based on the preliminary normalized field, the standardized anomaly field is determined.

[0131] Based on any of the above embodiments, the ridgeline tracking unit 940 is specifically used for: The standardized anomaly field is spatially interpolated and densified using the Kriging interpolation method to generate a continuous anomaly field grid. Determine the two-dimensional horizontal gradient distribution of the continuous anomaly field grid; Local high value seed points are determined in the continuous anomaly field grid, and planar ridge lines are searched along the orthogonal direction of the two-dimensional horizontal gradient starting from the local high value seed points to extract the ridge line skeleton. Curve fitting is performed on the ridge skeleton to obtain the planar position of the target metal pipe.

[0132] Based on any of the above embodiments, the vector difference calculation unit 920 is specifically used for: Obtain the soil resistivity distribution model of the surface survey area; A three-dimensional forward modeling grid covering the surface survey area is constructed, and the three-dimensional forward modeling grid is assigned values ​​based on the soil resistivity distribution model to obtain an equivalent background stratum model that does not contain the high conductivity characteristics of the target metal pipe. The theoretical background magnetic field is determined based on the equivalent model of the background strata and the spatial coordinates of the power supply electrode.

[0133] Based on any of the above embodiments, the method of injecting current into the underground target metal pipe through the power supply electrode includes targeted power supply and surface power supply.

[0134] Based on any of the above embodiments, a unit for determining burial depth is further included, wherein the unit for determining burial depth is specifically used for: A dense survey line is laid out in a direction perpendicular to the plane position, and the magnetic anomaly profile curve on the dense survey line is obtained. Construct a theoretical magnetic field profile model; The burial depth of the target metal pipe is obtained by fitting the theoretical magnetic field profile model and the magnetic anomaly profile curve using the nonlinear least squares method.

[0135] Figure 10 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 10As shown, the electronic device may include: a processor 1010, a communications interface 1020, a memory 1030, and a communications bus 1040, wherein the processor 1010, the communications interface 1020, and the memory 1030 communicate with each other through the communications bus 1040. The processor 1010 can call logic instructions in the memory 1030 to execute a method for detecting and locating deeply buried metal pipes. This method includes: injecting current into the underground target metal pipe through power supply electrodes to excite a target magnetic field underground; collecting measured values ​​of a three-component magnetic field at multiple measuring points within a surface survey area above the target metal pipe; the measured values ​​of the three-component magnetic field include the components of the target magnetic field at each measuring point; performing forward modeling of the background field based on the geoelectric parameters of the surface survey area to obtain a theoretical background magnetic field; and performing vector difference between the measured values ​​of the three-component magnetic field and the theoretical background magnetic field to obtain an anomalous magnetic field; determining a background region within the surface survey area that does not include the target metal pipe; determining an adaptive threshold based on the statistical characteristics of the background region; generating confidence weights for each measuring point based on the adaptive threshold; processing the anomalous magnetic field based on the confidence weights to obtain a standardized anomalous field; and performing ridge tracing on the standardized anomalous field to obtain the planar position of the target metal pipe.

[0136] Furthermore, the logical instructions in the aforementioned memory 1030 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part 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 the present 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.

[0137] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the deep-buried metal pipeline detection and positioning method provided by the above methods. The method includes: injecting current into the underground target metal pipeline through a power supply electrode to excite the target magnetic field underground; collecting measured values ​​of three-component magnetic fields at multiple measuring points in a surface survey area located above the target metal pipeline; the measured values ​​of the three-component magnetic fields include the components of the target magnetic field at each measuring point; performing background field forward modeling based on the geoelectric parameters of the surface survey area to obtain a theoretical background magnetic field; and performing vector difference between the measured values ​​of the three-component magnetic fields and the theoretical background magnetic field to obtain an anomalous magnetic field; determining a background region excluding the target metal pipeline in the surface survey area; determining an adaptive threshold based on the statistical characteristics of the background region; generating confidence weights for each measuring point based on the adaptive threshold; processing the anomalous magnetic field based on the confidence weights to obtain a standardized anomalous field; and performing ridge tracing on the standardized anomalous field to obtain the planar position of the target metal pipeline.

[0138] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program performs the deep-buried metal pipeline detection and positioning method provided by the above-described methods. The method includes: injecting current into the underground target metal pipeline through a power supply electrode to excite a target magnetic field underground; collecting measured values ​​of three-component magnetic fields at multiple measuring points in a surface survey area above the target metal pipeline; the measured values ​​of the three-component magnetic fields include the components of the target magnetic field at each of the measuring points; performing background field forward modeling based on the geoelectric parameters of the surface survey area to obtain a theoretical background magnetic field; and performing vector difference between the measured values ​​of the three-component magnetic fields and the theoretical background magnetic field to obtain an anomalous magnetic field; determining a background region excluding the target metal pipeline in the surface survey area; determining an adaptive threshold based on the statistical characteristics of the background region; generating confidence weights for each of the measuring points based on the adaptive thresholds; processing the anomalous magnetic field based on the confidence weights to obtain a standardized anomalous field; and performing ridge tracing on the standardized anomalous field to obtain the planar position of the target metal pipeline.

[0139] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0140] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting and locating deeply buried metal pipelines, characterized in that, include: Current is injected into the underground target metal pipe through the power supply electrode to excite the target magnetic field underground. The three-component magnetic field measured values ​​are collected at multiple measuring points in the surface survey area located above the target metal pipe. The three-component magnetic field measured values ​​include the component of the target magnetic field at each of the measuring points. Based on the geoelectric parameters of the surface survey area, a background field forward modeling is performed to obtain the theoretical background magnetic field. The measured values ​​of the three-component magnetic field are then vector-differed with the theoretical background magnetic field to obtain the anomalous magnetic field. Within the surface survey area, a background region excluding the target metal pipe is determined. An adaptive threshold is determined based on the statistical characteristics of the background region. A confidence weight for each survey point is generated based on the adaptive threshold. The abnormal magnetic field is processed based on the confidence weight to obtain a standardized abnormal field. Ridge tracing is performed on the standardized anomaly field to obtain the planar position of the target metal pipe.

2. The method for detecting and locating deeply buried metal pipelines according to claim 1, characterized in that, The step of determining the adaptive threshold based on the statistical characteristics of the background region includes: A sliding window is constructed with each of the aforementioned measuring points within the surface survey area as the center. Determine the sample mean and sample standard deviation of the abnormal magnetic field within the sliding window; A background reference set is selected in the background region, and a background amplitude reference is determined based on the background reference set; The background signal-to-noise ratio distribution is determined based on the sample mean, the background amplitude benchmark, and the sample standard deviation corresponding to each measurement point in the background region. The preset quantile of the background signal-to-noise ratio distribution is determined as the adaptive threshold.

3. The method for detecting and locating deeply buried metal pipelines according to claim 2, characterized in that, The step of generating confidence weights for each measurement point based on the adaptive threshold includes: Based on the sample mean, sample standard deviation and background amplitude benchmark corresponding to each measurement point, the local signal-to-noise ratio index corresponding to each measurement point is determined. Obtain the interquartile range of the local signal-to-noise ratio index within the background region, and determine the smoothing coefficient based on the interquartile range; Based on the local signal-to-noise ratio index, the adaptive threshold, and the smoothing coefficient, the confidence weights corresponding to each measurement point are generated.

4. The method for detecting and locating deeply buried metal pipelines according to any one of claims 1 to 3, characterized in that, The process of processing the anomalous magnetic field based on the confidence weight to obtain a standardized anomalous field includes: Extract the magnetic field magnitude of the abnormal magnetic field at each of the aforementioned measurement points; Global extremum mapping is performed on each of the magnetic field magnitudes to obtain a preliminary normalized field. Based on the preliminary normalized field, the standardized anomaly field is determined.

5. The method for detecting and locating deeply buried metal pipelines according to any one of claims 1 to 3, characterized in that, The step of ridgeline tracing of the standardized anomaly field to obtain the planar position of the target metal pipe includes: The standardized anomaly field is spatially interpolated and densified using the Kriging interpolation method to generate a continuous anomaly field grid. Determine the two-dimensional horizontal gradient distribution of the continuous anomaly field grid; Local high value seed points are determined in the continuous anomaly field grid, and planar ridge lines are searched along the orthogonal direction of the two-dimensional horizontal gradient starting from the local high value seed points to extract the ridge line skeleton. Curve fitting is performed on the ridge skeleton to obtain the planar position of the target metal pipe.

6. The method for detecting and locating deeply buried metal pipelines according to any one of claims 1 to 3, characterized in that, The process of performing background field forward modeling based on the geoelectric parameters of the surface survey area to obtain the theoretical background magnetic field includes: Obtain the soil resistivity distribution model of the surface survey area; A three-dimensional forward modeling grid covering the surface survey area is constructed, and the three-dimensional forward modeling grid is assigned values ​​based on the soil resistivity distribution model to obtain an equivalent background stratum model that does not contain the high conductivity characteristics of the target metal pipe. The theoretical background magnetic field is determined based on the equivalent model of the background strata and the spatial coordinates of the power supply electrode.

7. The method for detecting and locating deeply buried metal pipelines according to any one of claims 1 to 3, characterized in that, The method of injecting current into the underground target metal pipe through the power supply electrode includes targeted power supply and surface power supply.

8. The method for detecting and locating deeply buried metal pipelines according to any one of claims 1 to 3, characterized in that, The step of ridge tracing the standardized anomaly field to obtain the planar position of the target metal pipe further includes: A dense survey line is laid out in a direction perpendicular to the plane position, and the magnetic anomaly profile curve on the dense survey line is obtained. Construct a theoretical magnetic field profile model; The burial depth of the target metal pipe is obtained by fitting the theoretical magnetic field profile model and the magnetic anomaly profile curve using the nonlinear least squares method.

9. A detection and positioning device for deeply buried metal pipes, characterized in that, include: The acquisition unit is used to inject current into the underground target metal pipe through the power supply electrode to excite the target magnetic field underground, and to acquire the measured values ​​of the three-component magnetic field at multiple measuring points in the surface survey area located above the target metal pipe; the measured values ​​of the three-component magnetic field include the component of the target magnetic field at each of the measuring points. The vector difference calculation unit is used to perform background field forward modeling based on the geoelectric parameters of the surface survey area, obtain the theoretical background magnetic field, and perform vector difference between the measured values ​​of the three-component magnetic field and the theoretical background magnetic field to obtain the anomalous magnetic field. The processing unit is configured to determine a background area excluding the target metal pipe within the surface survey area, determine an adaptive threshold based on the statistical characteristics of the background area, generate confidence weights for each of the survey points based on the adaptive thresholds, and process the anomalous magnetic field based on the confidence weights to obtain a standardized anomalous field. The ridge tracing unit is used to perform ridge tracing on the standardized anomaly field to obtain the planar position of the target metal pipe.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the method for detecting and locating deeply buried metal pipelines as described in any one of claims 1 to 8.

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