Accurate positioning system and method for advanced detection of anomalous body along with excavation

Abstract

The invention relates to the technical field of geological exploration, in particular to a system and a method for accurately positioning an abnormal body through advanced exploration during excavation. The magnetic field fusion correction unit is used for obtaining a net magnetic field in the tunnel; the magnetic resonance detection unit is combined with a net magnetic field in a tunnel to detect water content characteristics and porosity characteristics of a target stratum position in front of a tunneling face; the bio-magnetic marking unit injects a tracer agent into the target stratum position and continuously monitors the target stratum position, and a bio-magnetic signal is generated after the target stratum position reaches the target tracer agent concentration; and the magnetic anomaly positioning feedback unit outputs the center coordinates of the abnormal body and triggers early warning at the same time. According to the system and the method for accurately positioning the abnormal body during excavation advanced detection, high-precision and low-false-alarm-rate positioning of the abnormal body such as a water-containing structure is realized, and meanwhile, the real-time performance and the reliability of excavation advanced detection under complex geological conditions are remarkably improved through dynamic integral region adjustment and a closed-loop feedback mechanism.

Description

Technical Field

[0001] This invention relates to the field of geological exploration technology, and more specifically, to a system and method for precise positioning of anomalies during excavation. Background Technology

[0002] In tunnel engineering, water-bearing structures (such as faults and karst caves) are the most dangerous geological anomalies. However, anomalies also include lithological change zones and cavities, which pose significant challenges in tunneling exploration: First, dynamic changes in the geomagnetic background and interference from the movement of tunneling equipment result in high noise in the magnetic field signal, making it difficult to extract the target anomaly features; second, single physical field (such as resistivity) detection has limited ability to identify water-bearing anomalies and is easily affected by lithological differences; third, traditional passive magnetic monitoring lacks an active signal enhancement mechanism for the target area, resulting in insufficient accuracy in locating anomalies in low water content or microfracture zones.

[0003] Existing technologies often rely on single magnetic measurements or single physical field detection, which are often affected by factors such as on-site motion interference, changes in geomagnetic background, and differences in target properties. It is difficult to achieve high-precision, low-false-alarm anomaly location without stopping the machine. Therefore, this paper proposes a system and method for accurate anomaly location during tunneling advance detection. Summary of the Invention

[0004] The purpose of this invention is to provide a system and method for precise positioning of anomalies during tunneling, in order to solve the problem mentioned in the background art that single magnetic measurement or single physical field detection is often affected by factors such as on-site motion interference, changes in geomagnetic background, and differences in target physical properties, making it difficult to achieve high-precision, low-false-alarm anomaly positioning without stopping the machine.

[0005] To achieve the above objectives, on the one hand, the present invention aims to provide a system for precise positioning of anomalies during excavation and advance detection, comprising:

[0006] The magnetic field fusion correction unit is used to collect surface magnetic field data and original magnetic field data inside the tunnel in real time, and introduces a gradient-displacement coupling term to correct the original magnetic field data inside the tunnel to obtain the net magnetic field inside the tunnel.

[0007] A magnetic resonance detection unit is used to trigger and receive nuclear magnetic resonance echoes at the target stratum location through a controlled excitation sequence, and combine the net magnetic field inside the tunnel to detect the water content and porosity characteristics of the target stratum location in front of the excavation face.

[0008] A biomagnetic labeling unit is used to inject a tracer into a target formation location and continuously monitor it. When the target formation location reaches the target tracer concentration, a biomagnetic signal is generated.

[0009] The magnetic anomaly location feedback unit is used to construct an objective function based on water content characteristics, porosity characteristics and biomagnetic signals, and to perform inversion using total variational regularization, outputting the coordinates of the anomaly center and triggering an early warning.

[0010] As a further improvement to this technical solution, the net magnetic field obtained in the tunnel by the magnetic field fusion correction unit is specifically as follows:

[0011] Surface magnetic field data and raw magnetic field data inside the tunnel were collected using magnetic sensors, respectively.

[0012] A gradient-displacement coupling term is introduced to compensate and correct the interference generated by spatial gradient changes and measuring point displacement in the original magnetic field data inside the tunnel, resulting in corrected magnetic field data inside the tunnel.

[0013] The corrected magnetic field inside the tunnel is fused with the surface reference field, and background components unrelated to the target anomaly are filtered out to obtain the net magnetic field that reflects the true magnetic environment inside the tunnel.

[0014] As a further improvement to this technical solution, the magnetic resonance detection unit includes a controlled excitation module and an echo processing module;

[0015] Among them, the controlled excitation module is used to generate controlled electromagnetic pulses of target frequency and intensity, and periodically excite the target stratum position in front of the tunnel face to excite hydrogen nuclei in the stratum to generate nuclear magnetic resonance time-domain echo signals.

[0016] The echo processing module is used to receive and analyze the generated nuclear magnetic resonance time-domain echo signal. By combining the relaxation time analysis algorithm with the net magnetic field data in the tunnel, it obtains the water content and porosity characteristics of the water-bearing structure at the target stratum.

[0017] As a further improvement to this technical solution, the steps of the echo processing module to retrieve the water content and porosity characteristics of the water-bearing structures at the target stratum are as follows:

[0018] The attenuation portion of the time-domain echo signal is exponentially fitted using a relaxation time analysis algorithm, and the transverse relaxation time is solved using the nonlinear least squares method. and initial signal strength Based on the initial signal strength Obtain a baseline value for the number of hydrogen nuclei; combine this with net magnetic field data within the tunnel, based on... The relationship between spectral distribution and the number of hydrogen nuclei in the formation is used to determine the location of the target formation. Moisture content ,based on Spectral distribution and pore structure models are used to determine the location of the target strata. porosity .

[0019] As a further improvement to this technical solution, in the biomagnetic labeling unit, the tracer is loaded with ferromagnetic nanoparticles and has magnetotactic properties.

[0020] As a further improvement to this technical solution, the magnetic anomaly positioning feedback unit includes a target judgment module, an advanced drilling control module, and an anomaly fusion positioning module.

[0021] The target judgment module is used to determine whether the target formation is located in a high-risk water-bearing area by using water content and porosity characteristics. If the target formation is located in a high-risk water-bearing area, a drilling command is triggered. If the target formation is still located in a high-risk water-bearing area after being marked by the biomagnetic marker unit, anomaly location and anomaly warning are triggered.

[0022] The advanced drilling control module is used to move the drill bit to the target formation location according to the drilling command and control the injection of tracer from the biomagnetic labeling unit;

[0023] After triggering anomaly localization, the anomaly fusion localization module detects the intensity of biomagnetic signals in real time, constructs an objective function based on water content characteristics, porosity characteristics, and biomagnetic signals, and uses total variational regularization for inversion to obtain the coordinates of the anomaly center.

[0024] As a further improvement to this technical solution, the target judgment module determines whether the target formation is located in a high-risk water-bearing area by using water content characteristics and porosity characteristics. Specifically, the water content characteristics are greater than the water content threshold and the porosity characteristics are greater than the porosity threshold.

[0025] As a further improvement to this technical solution, if the abnormal fusion positioning module detects that the intensity of the biomagnetic signal is less than the distortion intensity threshold, it generates a secondary marking signal and transmits the secondary marking signal to the advanced drilling control module. If the intensity of the biomagnetic signal is still less than the distortion intensity threshold after the secondary marking signal is executed, it sends a drilling controller instruction to the advanced drilling control module to add an offset drilling. The content of the secondary marking signal includes increasing the injection pressure and increasing the tracer concentration.

[0026] As a further improvement to this technical solution, the specific steps for the anomaly fusion localization module to obtain the center coordinates of the anomaly are as follows:

[0027] S41. Multi-source data fusion of water content characteristics, porosity characteristics and biomagnetic signals is performed. Data fitting terms are established in high-risk water-bearing areas and target formation locations respectively. Total variational regularization is introduced to constrain the spatial distribution stability of water content, thereby constructing the objective function.

[0028] S42. Based on the constructed objective function, the preconditional conjugate gradient method is used for iterative optimization to obtain the optimized water content distribution, thereby minimizing the objective function;

[0029] S43. Based on the optimized water content distribution, calculate the weighted centroid coordinates in the high-risk water-bearing area, and output the final anomaly center coordinates by combining the location uncertainty of the nuclear magnetic resonance time-domain echo signal and the biomagnetic signal.

[0030] On the other hand, the present invention provides a method for precise positioning of anomalies detected during tunneling, used in any of the above-mentioned precise positioning systems for anomalies detected during tunneling, comprising the following steps:

[0031] S1. Real-time acquisition of surface magnetic field data and original magnetic field data inside the tunnel, and introduction of gradient-displacement coupling term to correct the original magnetic field data inside the tunnel to obtain the net magnetic field inside the tunnel.

[0032] S2. Trigger and receive nuclear magnetic resonance echoes at the target stratum location through a controlled excitation sequence, and combine the net magnetic field inside the tunnel to detect the water content and porosity characteristics of the target stratum location in front of the tunnel face.

[0033] S3. Determine whether the target formation is located in a high-risk water-bearing zone by using water content and porosity characteristics. If the target formation is located in a high-risk water-bearing zone, trigger a drilling command and move the drill bit to the target formation location based on the drilling command.

[0034] S4. Based on the drilling tool, a tracer is injected into the target formation location and continuously monitored. When the target formation location reaches the target tracer concentration, a biomagnetic signal is generated. If the target formation location is still in a high-risk water-bearing area after marking, anomaly location and anomaly warning are triggered.

[0035] S5. After triggering anomaly localization, the intensity of the biomagnetic signal is detected in real time. Based on water content characteristics, porosity characteristics and biomagnetic signal, an objective function is constructed and inversion is performed using total variational regularization to obtain the coordinates of the anomaly center.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] A system and method for precise location of anomalies in tunneling advance detection overcomes the problems of large signal interference and low positioning accuracy in traditional tunneling advance detection by integrating biomagnetic markers, geomagnetic dynamic correction and magnetic resonance constraint technology. Biomagnetic markers are used to actively enhance the specificity of target signals, geomagnetic dynamic correction is combined to eliminate tunneling motion interference in real time, and magnetic resonance constraint provides accurate water content and porosity parameters. A target function for multi-source data fusion is constructed, and a total variational regularized inversion algorithm is used to achieve high-precision and low false alarm rate location of anomalies such as water-bearing structures. At the same time, through dynamic integral region adjustment and closed-loop feedback mechanism, the real-time performance and reliability of tunneling advance detection under complex geological conditions are significantly improved. Attached Figure Description

[0038] Figure 1 This is an overall flowchart of the present invention;

[0039] Figure 2 This is a flowchart illustrating the overall method of the present invention;

[0040] The meanings of the labels in the diagram are as follows:

[0041] 1. Magnetic field fusion correction unit; 2. Magnetic resonance detection unit; 21. Controlled excitation module; 22. Echo processing module; 3. Biomagnetic labeling unit; 4. Magnetic anomaly localization feedback unit; 41. Target judgment module; 42. Advanced drilling control module; 43. Anomaly fusion localization module. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0043] Example 1: Please refer to Figure 1 As shown, a system for precise localization of anomalies during excavation is provided, comprising a magnetic field fusion correction unit 1, a magnetic resonance detection unit 2, a biomagnetic labeling unit 3, and a magnetic anomaly localization feedback unit 4;

[0044] The geomagnetic dynamic correction unit 1 is used to acquire surface magnetic field data and raw magnetic field data inside the tunnel in real time, and introduces a gradient-displacement coupling term to correct the raw magnetic field data inside the tunnel to obtain the net magnetic field inside the tunnel; the net magnetic field inside the tunnel is transmitted to the magnetic resonance detection unit 2 and provides a background field for the biomagnetic labeling unit 3.

[0045] The surface magnetic field data consists of time-series vector magnetic field data acquired by triaxial magnetic field sensors deployed above the tunnel surface; the tunnel interior magnetic field data consists of time-series vector magnetic field data acquired by triaxial magnetic field sensors deployed at the tunnel face. However, unlike the surface data, the tunnel interior magnetic field data, in addition to including the background geomagnetic field component, also includes:

[0046] Magnetic anomalies caused by geological structures (such as rock masses containing magnetic minerals);

[0047] Electromagnetic interference generated by tunneling equipment and electrical devices;

[0048] The spatial structure of the tunnel disturbs the magnetic field distribution.

[0049] In magnetic field fusion correction unit 1, the net magnetic field inside the tunnel is obtained as follows:

[0050] Surface magnetic field data and raw magnetic field data inside the tunnel were collected using magnetic sensors, respectively.

[0051] A gradient-displacement coupling term is introduced to compensate for and correct the interference generated by spatial gradient changes and measurement point displacement in the original magnetic field data inside the tunnel, resulting in corrected magnetic field data inside the tunnel. The corrected magnetic field inside the tunnel is then fused with the surface reference field to filter out background components unrelated to the target anomaly, thus obtaining a net magnetic field that reflects the true magnetic environment inside the tunnel.

[0052]

[0053] In the formula, for Net magnetic field inside the tunnel; for The original magnetic field data inside the tunnel was directly measured by a vector magnetometer array installed at the tunnel face; for Earth's surface magnetic field data at that time; This is the influence coefficient of the Earth's surface magnetic field data; This is the coefficient for the influence of magnetic field distortion; for Time tunnel magnetic field gradient tensor; for Relative displacement at time; The time delay between the surface reference signal and the tunnel end. It is a magnetic field distortion variable;

[0054] Tunnel Cleaning Magnetic Field The magnetic characteristics used to characterize the surrounding rock of a tunnel and the geological bodies ahead of it are derived from the original magnetic field data within the tunnel. The net magnetic field data obtained after surface reference field correction and gradient-displacement coupling term compensation effectively suppresses background geomagnetic disturbances and non-geological factors, providing a reliable magnetic field input for high-precision positioning of anomalies.

[0055] The magnetic resonance detection unit 2 is used to trigger and receive nuclear magnetic resonance echoes at the target stratum location through a controlled excitation sequence, and combine the net magnetic field inside the tunnel to detect the water content and porosity characteristics of the target stratum location in front of the excavation face.

[0056] The magnetic resonance detection unit 2 includes a controlled excitation module 21 and an echo processing module 22;

[0057] Among them, the controlled excitation module 21 is used to generate controlled electromagnetic pulses of target frequency and intensity to periodically excite the target stratum position in front of the tunnel face, thereby exciting hydrogen nuclei in the stratum to generate nuclear magnetic resonance time-domain echo signals. After absorbing the energy of the electromagnetic pulse, the hydrogen nuclei undergo energy level transitions and then release energy through a relaxation process to form a detectable time-domain echo signal. The intensity and relaxation time of the wave signal directly reflect the water content and porosity of the stratum.

[0058] The echo processing module 22 is used to receive and analyze the generated nuclear magnetic resonance time-domain echo signal, and obtain the water content characteristics and porosity characteristics of the water-bearing structure at the target stratum by combining the relaxation time analysis algorithm with the net magnetic field data in the tunnel.

[0059] The steps of echo processing module 22 to retrieve the water content and porosity characteristics of water-bearing structures at the target stratum location are as follows:

[0060] The attenuation portion of the time-domain echo signal is exponentially fitted using a relaxation time analysis algorithm, and the transverse relaxation time is solved using the nonlinear least squares method. and initial signal strength Based on the initial signal strength Obtain a baseline value for the number of hydrogen nuclei; combine this with net magnetic field data within the tunnel, based on... The relationship between spectral distribution and the number of hydrogen nuclei in the formation is used to determine the location of the target formation. Moisture content ,based on Spectral distribution and pore structure models are used to determine the location of the target strata. porosity ;

[0061] The attenuation portion of the time-domain echo signal is exponentially fitted using a relaxation time analysis algorithm. The exponential fitting model is as follows:

[0062]

[0063] In the formula, The time-domain echo signal at time t;

[0064] Through experimental data points Fit the best and This minimizes the error between the model and the measured data.

[0065] It is proportional to the total number of hydrogen nuclei in the formation, because the intensity of the nuclear magnetic resonance signal is determined by the collective behavior of the magnetic moments of hydrogen nuclei;

[0066]

[0067] In the formula, Water content at the target formation location; target formation location This indicates the three-dimensional coordinates of the probe point within the strata; The initial signal strength at the target stratum location represents the time... The transverse magnetization of hydrogen nuclei in the strata; The gyromagnetic ratio of the hydrogen nucleus ( ); The formation density (mass per unit volume) at the target formation location varies with spatial location. change; This refers to the lateral relaxation time; The gradient-signal response coefficients were determined through laboratory calibration. The magnetic field gradient (unit: T / m) is generated by the sweep coil; the integral term above represents the three-dimensional coordinates of the probe point in the strata.

[0068]

[0069] In the formula, Porosity at the target formation location; To control the steepness of the curve; For the target stratum location The geometric mean of the spectrum represents the weighted average of the hydrogen nucleus relaxation times in the formation, obtained by... The geometric mean of the spectrum can distinguish between mobile fluids and bound fluids; This is the threshold offset (to distinguish between large and small pores). The gradient-porosity coupling coefficient corrects the influence of the magnetic field gradient on the porosity distribution; the coupling term between the magnetic field gradient and spatial position corrects the spatial non-uniformity of the signal integral and porosity, eliminating errors caused by magnetic field non-uniformity.

[0070] The biomagnetic labeling unit 3 is used to inject tracers into the target formation and continuously monitor them. A biomagnetic signal is generated when the target tracer concentration is reached at the target formation location. The injection time, volume, location, concentration, and biomagnetic signal are recorded. By actively injecting tracers into the target formation location and monitoring the entire process, the migration and enrichment behavior of the tracers in the formation can be dynamically grasped, ensuring a clear time-space-concentration correspondence in the detection process. The generation of the biomagnetic signal is triggered when the tracer concentration reaches a preset threshold, avoiding misjudgments due to background noise interference and improving the reliability and repeatability of the detection signal. Simultaneously, the injection parameters (time, volume, location, concentration) and response signal (biomagnetic signal) are recorded synchronously, providing a complete data chain support for subsequent anomaly inversion and localization, enhancing the system's data traceability and analytical reliability.

[0071] The target concentration is a concentration of ≥10 within the aquifer. 9CFU / cm 3 The minimum effective concentration threshold of the tracer in the aqueous structure was set to ensure that the tracer microorganisms formed a sufficiently dense biomagnetic source in the target area, thereby generating a magnetic anomaly signal that could be effectively identified by the far-field sensor. This concentration threshold was experimentally verified based on the magnetosome production capacity of microbial magnetosomes and the adsorption characteristics of the formation. It can ensure that the signal strength meets the detection sensitivity requirements, while avoiding the waste of resources and environmental disturbance caused by excessive injection, thus achieving a balance between detection sensitivity and engineering economy.

[0072] In the biomagnetic labeling unit 3, the tracer carries ferromagnetic nanoparticles and has magnetotactic properties. The tracer carries natural or artificially synthesized ferromagnetic nanoparticles (such as magnetite nanocrystals) and has the ability to directionally migrate to magnetotactic microorganisms, which actively accumulate in aquifer channels or fracture zones under the guidance of an external weak magnetic field or hydraulic gradient, significantly enhancing the magnetic signal contrast of the target area. This feature breaks through the diffusion limitations of traditional passive tracers, improves the spatial focusing ability of the tracer, and thus improves the accuracy of anomaly localization, especially suitable for fine identification of microfractures or low-permeability aquifers.

[0073] The magnetic anomaly localization feedback unit 4 is used to construct an objective function based on water content characteristics, porosity characteristics and biomagnetic signals and perform inversion using total variational regularization, output the coordinates of the anomaly center and trigger an early warning at the same time;

[0074] The magnetic anomaly localization feedback unit 4 includes a target judgment module 41, an advanced drilling control module 42, and an anomaly fusion localization module 43;

[0075] The target judgment module 41 is used to determine whether the target formation is located in a high-risk water-bearing area by using water content characteristics and porosity characteristics. If the target formation is located in a high-risk water-bearing area, a drilling command is triggered. If the target formation is still located in a high-risk water-bearing area after being marked by the biomagnetic marker unit 3, anomaly location and anomaly warning are triggered.

[0076] In the target judgment module 41, the location of the target stratum is determined to be in a high-risk water-bearing area by the water content characteristics and porosity characteristics. Specifically, the water content characteristics are greater than the water content threshold and the porosity characteristics are greater than the porosity threshold.

[0077] This module employs a tiered response strategy: when a high-risk aquifer is identified, the advanced drilling control module 42 immediately executes directional drilling to reduce the risk of water inrush. If the biomagnetic marker feedback indicates that the risk has not been eliminated, the anomaly fusion positioning module 43 outputs the coordinates of the anomaly center through total variational regularization inversion and links with early warning terminals (such as audible and visual alarms and data push) to achieve precise positioning and real-time intervention.

[0078] The advanced drilling control module 42 is used to move the drill bit to the target formation location according to the drilling command and control the injection of tracer in the biomagnetic labeling unit 3. According to the drilling command from the target judgment module 41, it precisely moves the drill bit to the target formation location to perform advanced drilling operations, reducing the risk of water inrush. After the anomaly fusion positioning module 43 triggers the secondary labeling signal, it dynamically adjusts the injection parameters of the biomagnetic labeling unit 3 to enhance the injection of tracer and increase the intensity of the biomagnetic signal. If the signal is still insufficient after secondary labeling, an additional offset drilling command is added to expand the detection range, covering potential unidentified anomalies and ensuring detection integrity.

[0079] After triggering anomaly localization, the anomaly fusion localization module 43 detects the intensity of the biomagnetic signal in real time, constructs an objective function based on water content characteristics, porosity characteristics and biomagnetic signal, and uses total variational regularization to perform inversion to obtain the coordinates of the anomaly center.

[0080] If the anomaly fusion localization module 43 detects that the intensity of the biomagnetic signal is less than the distortion intensity threshold, it generates a secondary labeling signal and transmits it to the advanced drilling control module 42. If, after the secondary labeling signal is executed, the intensity of the biomagnetic signal is still less than the distortion intensity threshold, it sends a drilling controller offset drilling command to the advanced drilling control module 42. The secondary labeling signal includes increasing the injection pressure and increasing the tracer concentration. This forms a closed-loop feedback chain of signal detection, parameter optimization, and drilling intervention, ensuring the stability of the system under complex geological conditions. The triggering mechanism of the offset drilling command enhances the system's adaptability to unknown anomalies.

[0081] The specific steps for the anomaly fusion localization module (43) to obtain the coordinates of the anomaly center are as follows:

[0082] S41. Multi-source data fusion is performed on water content characteristics, porosity characteristics and biomagnetic signals. Data fitting terms are established in high-risk water-bearing areas and target strata locations respectively. Total variational regularization is introduced to constrain the spatial distribution stability of water content. The objective function associates physical parameters with proportional coefficients and empirical formulas, and combined with adaptive regularization parameters, to achieve high-precision inversion and positioning of anomalies.

[0083] ;

[0084] In the formula, water content and porosity are the variables to be inverted; In position The signal amplitude (V) at that location is measured by magnetic resonance detection unit 2; To be at the observation position Biomagnetic signals at the location; As a linear operator, it maps water content distribution to biomagnetic field distribution; This is the total variational regularization term for water content, used for stable inversion and boundary preservation; The regularization strength; The sensitivity of decay time to porosity; The minimum effective porosity threshold;

[0085]

[0086] Total variational regularization suppresses spatial oscillations in water content (such as spurious high water content points caused by noise); it preserves sharp boundaries of water-bearing structures (such as water inrush channel interfaces).

[0087] The high-risk water-bearing area is the three-dimensional spatial range to be explored in front of the tunnel face, and its specific boundary is determined by the effective detection depth of the magnetic resonance detection unit. Let be the target stratum location, and be the set of spatial locations of the magnetic sensor array deployed within the tunnel; where the first integral is in the anomaly region. Inside, The second integral is defined in the three-dimensional space of the maximum detection distance in front of the tunnel face. (The location of the receiving array arranged inside the tunnel) is used for this purpose. The location of the magnetic sensor array inside the tunnel is determined by the deployment position; the maximum detection distance and sensor deployment parameters are configured according to the detection accuracy requirements.

[0088] S42. Based on the constructed multi-source fusion objective function, the preconditional conjugate gradient method is used for iterative optimization to obtain the optimized water content distribution, thereby minimizing the objective function; specifically including:

[0089] Initial values ​​for water content and porosity distribution were set, and measured data from the magnetic resonance detection unit and the biomagnetic labeling unit 3 were loaded.

[0090] In each iteration, the gradient direction of the objective function with respect to water content and porosity distribution is calculated, and the convergence is accelerated by combining the precondition matrix;

[0091] Update the parameters along the gradient direction with a preset step size until the convergence condition is met (relative error less than 10%). (or reaching the maximum number of iterations);

[0092] In each iteration, a total variational regularization term is applied to suppress noise and preserve the boundary characteristics of water content distribution. Iterative optimization algorithms (such as the preconditional conjugate gradient method) automatically adapt to complex geological conditions and adjust inversion parameters in real time to ensure stable coordinate output even under tunneling disturbances.

[0093] S43. Based on the optimized water content distribution, calculate the weighted centroid coordinates within the high-risk water-bearing area, and combine the uncertainties of the localization of the nuclear magnetic resonance time-domain echo signal and the biomagnetic signal to output the final anomaly center coordinates; As a weighting function

[0094]

[0095]

[0096] In the formula, It is the centroid of a hydrous structure; The coordinates of the final anomaly center; The location uncertainty of the nuclear magnetic resonance time-domain echo signal; The location uncertainty of the biomagnetic signal; The location of the extreme point of the biomagnetic signal is determined by combining the positioning uncertainty of magnetic resonance and biomagnetic signal to calculate the final coordinates, thus overcoming the limitations of a single data source and reducing the false alarm rate.

[0097] Example 2: Please refer to Figure 2 As shown, a method for precise location of anomalies in advance detection during tunneling is provided, which is used in any of the above-mentioned precise location systems for anomalies in advance detection during tunneling, and includes the following steps:

[0098] S1. Real-time acquisition of surface magnetic field data and original magnetic field data inside the tunnel, and introduction of gradient-displacement coupling term to correct the original magnetic field data inside the tunnel to obtain the net magnetic field inside the tunnel.

[0099] S2. Trigger and receive nuclear magnetic resonance echoes at the target stratum location through a controlled excitation sequence, and combine the net magnetic field inside the tunnel to detect the water content and porosity characteristics of the target stratum location in front of the tunnel face.

[0100] S3. Determine whether the target formation is located in a high-risk water-bearing zone by using water content and porosity characteristics. If the target formation is located in a high-risk water-bearing zone, trigger a drilling command and move the drill bit to the target formation location based on the drilling command.

[0101] S4. Based on the drilling tool, a tracer is injected into the target formation location and continuously monitored. When the target formation location reaches the target tracer concentration, a biomagnetic signal is generated. If the target formation location is still in a high-risk water-bearing area after marking, anomaly location and anomaly warning are triggered.

[0102] S5. After triggering anomaly localization, the intensity of the biomagnetic signal is detected in real time. Based on water content characteristics, porosity characteristics and biomagnetic signal, an objective function is constructed and inversion is performed using total variational regularization to obtain the coordinates of the anomaly center.

[0103] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A system for precise positioning of anomalies detected during excavation, characterized in that, include: The magnetic field fusion correction unit (1) is used to collect surface magnetic field data and original magnetic field data in the tunnel in real time, and introduce gradient-displacement coupling term to correct the original magnetic field data in the tunnel to obtain the net magnetic field in the tunnel. The magnetic resonance detection unit (2) is used to trigger and receive the nuclear magnetic resonance echo at the target stratum location through a controlled excitation sequence, and combine the net magnetic field inside the tunnel to detect the water content and porosity characteristics of the target stratum location in front of the tunnel face. Biomagnetic labeling unit (3), the biomagnetic labeling unit (3) is used to inject tracer into the target formation location and continuously monitor it, and generate a biomagnetic signal when the target formation location reaches the target tracer concentration; The magnetic anomaly location feedback unit (4) is used to construct an objective function based on water content characteristics, porosity characteristics and biomagnetic signals and perform inversion using total variational regularization, output the coordinates of the center of the anomaly, and trigger an early warning.

2. The precise positioning system for anomaly detection during tunneling as described in claim 1, characterized in that: In the magnetic field fusion correction unit (1), the net magnetic field inside the tunnel is obtained as follows: Surface magnetic field data and raw magnetic field data inside the tunnel were collected using magnetic sensors, respectively. A gradient-displacement coupling term is introduced to compensate and correct the interference generated by spatial gradient changes and measuring point displacement in the original magnetic field data inside the tunnel, resulting in corrected magnetic field data inside the tunnel. The corrected magnetic field inside the tunnel is fused with the surface reference field, and background components unrelated to the target anomaly are filtered out to obtain the net magnetic field that reflects the true magnetic environment inside the tunnel.

3. The precise positioning system for anomaly detection during excavation as described in claim 2, characterized in that: The magnetic resonance detection unit (2) includes a controlled excitation module (21) and an echo processing module (22); Among them, the controlled excitation module (21) is used to generate controlled electromagnetic pulses of target frequency and intensity, and periodically excite the target stratum position in front of the tunnel face to excite the hydrogen nuclei in the stratum to generate nuclear magnetic resonance time-domain echo signals. The echo processing module (22) is used to receive and analyze the generated nuclear magnetic resonance time-domain echo signal, and obtain the water content characteristics and porosity characteristics of the water-bearing structure at the target stratum by combining the relaxation time analysis algorithm with the net magnetic field data in the tunnel.

4. The precise positioning system for anomaly detection during excavation as described in claim 3, characterized in that: The steps of the echo processing module (22) to retrieve the water content and porosity characteristics of the water-bearing structures at the target stratum are as follows: The attenuation portion of the time-domain echo signal was exponentially fitted using a relaxation time analysis algorithm. The transverse relaxation time T2 and initial signal intensity S0 were then calculated using the nonlinear least squares method. A baseline value for the number of hydrogen nuclei was obtained based on the initial signal intensity S0. Combined with net magnetic field data within the tunnel, the water content V at the target formation location r was determined based on the relationship between the T2 spectrum distribution and the number of hydrogen nuclei in the formation. water (r), based on the T2 spectrum distribution and pore structure model, the porosity φ(r) at the target formation location r is obtained.

5. The precise positioning system for anomaly detection during excavation as described in claim 4, characterized in that: In the biomagnetic labeling unit (3), the tracer carries ferromagnetic nanoparticles and has magnetotactic properties.

6. The precise positioning system for anomaly detection during tunneling as described in claim 5, characterized in that: The magnetic anomaly positioning feedback unit (4) includes a target judgment module (41), an advanced drilling control module (42), and an anomaly fusion positioning module (43); Among them, the target judgment module (41) is used to determine whether the target stratum is in a high-risk water-bearing area by water content characteristics and porosity characteristics. If the target stratum is in a high-risk water-bearing area, a drilling command is triggered. If the target stratum is still in a high-risk water-bearing area after being marked by the biomagnetic marker unit (3), anomaly location and anomaly warning are triggered. The advanced drilling control module (42) is used to move the drill bit to the target formation position according to the drilling command and control the injection of tracer in the biomagnetic labeling unit (3); After triggering anomaly localization, the anomaly fusion localization module (43) detects the intensity of the biomagnetic signal in real time, constructs an objective function based on water content characteristics, porosity characteristics and biomagnetic signal, and uses total variational regularization to perform inversion to obtain the coordinates of the anomaly center.

7. The precise positioning system for anomaly detection during tunneling as described in claim 6, characterized in that: In the target judgment module (41), the location of the target stratum is determined to be in a high-risk water-bearing area by the water content characteristics and porosity characteristics, specifically, the water content characteristics are greater than the water content threshold and the porosity characteristics are greater than the porosity threshold.

8. The precise positioning system for anomaly detection during tunneling according to claim 7, characterized in that: If the abnormal fusion positioning module (43) detects that the intensity of the biomagnetic signal is less than the distortion intensity threshold, it generates a secondary marking signal and transmits the secondary marking signal to the advanced drilling control module (42). If the intensity of the biomagnetic signal is still less than the distortion intensity threshold after the secondary marking signal is executed, it sends a drilling controller additional offset drilling instruction to the advanced drilling control module (42). The content of the secondary marking signal includes increasing the injection pressure and increasing the tracer concentration.

9. The precise positioning system for anomaly detection during tunneling as described in claim 8, characterized in that: The specific steps for the anomaly fusion localization module (43) to obtain the coordinates of the anomaly center are as follows: S41. Multi-source data fusion of water content characteristics, porosity characteristics and biomagnetic signals is performed. Data fitting terms are established in high-risk water-bearing areas and target formation locations respectively. Total variational regularization is introduced to constrain the spatial distribution stability of water content, thereby constructing the objective function. S42. Based on the constructed objective function, the preconditional conjugate gradient method is used for iterative optimization to obtain the optimized water content distribution, thereby minimizing the objective function; S43. Based on the optimized water content distribution, calculate the weighted centroid coordinates in the high-risk water-bearing area, and output the final anomaly center coordinates by combining the location uncertainty of the nuclear magnetic resonance time-domain echo signal and the biomagnetic signal.

10. A method for precise positioning of anomalies detected during tunneling, used in a precise positioning system for anomalies detected during tunneling as described in any one of claims 1-9, characterized in that: Includes the following steps: S1. Real-time acquisition of surface magnetic field data and original magnetic field data inside the tunnel, and introduction of gradient-displacement coupling term to correct the original magnetic field data inside the tunnel to obtain the net magnetic field inside the tunnel. S2. Trigger and receive nuclear magnetic resonance echoes at the target stratum location through a controlled excitation sequence, and combine the net magnetic field inside the tunnel to detect the water content and porosity characteristics of the target stratum location in front of the tunnel face. S3. Determine whether the target formation is located in a high-risk water-bearing zone by using water content and porosity characteristics. If the target formation is located in a high-risk water-bearing zone, trigger a drilling command and move the drill bit to the target formation location based on the drilling command. S4. Based on the drilling tool, a tracer is injected into the target formation location and continuously monitored. When the target formation location reaches the target tracer concentration, a biomagnetic signal is generated. If the target formation location is still in a high-risk water-bearing area after marking, anomaly location and anomaly warning are triggered. S5. After triggering anomaly localization, the intensity of the biomagnetic signal is detected in real time. Based on water content characteristics, porosity characteristics and biomagnetic signal, an objective function is constructed and inversion is performed using total variational regularization to obtain the coordinates of the anomaly center.

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