Liquid metal grouting detection method and system based on aviation transient electromagnetism

Abstract

The invention discloses a liquid metal grouting detection method and system based on aviation transient electromagnetism, and the method comprises the steps: forming composite slurry based on a liquid metal substrate and ferromagnetic particles; generating modified slurry based on the composite slurry and a cement-based grouting material; the modified slurry liquid is pressed and injected into a target rock mass fracture; the unmanned aerial vehicle is used for emitting electromagnetic pulses to the target rock mass and collecting secondary field response signals, and detection is completed. An aviation transient electromagnetic technology is adopted to replace a traditional ground geophysical prospecting method, a large-range area is rapidly scanned through the unmanned aerial vehicle carrying equipment, complex terrains (such as mountainous regions and rivers) can be climbed over, shielding of ground buildings can be avoided, the single-day detection efficiency is improved by more than three times, and the detection precision is improved. The method is especially suitable for scenes such as urban dense areas or plateau frozen soil where manual stationing is difficult.

Description

Technical Field

[0001] The present invention relates to the field of intelligent detection of underground structures, and in particular to a liquid metal grouting detection method and system based on aviation transient electromagnetic. Background Art

[0002] Grouting reinforcement of deep geological bodies is a key technology for ensuring the safety of underground projects such as tunnels and mines. Its core lies in precisely controlling the grouting diffusion range to form a continuous, airtight reinforcement barrier. However, traditional cement-based grouting materials have similar dielectric properties to the surrounding rock. Existing geophysical exploration technologies (such as resistivity and ground-penetrating radar) have difficulty effectively distinguishing the grouting consolidation body from the surrounding rock and soil. Consequently, grouting effectiveness evaluation relies heavily on verification through drilling and coring, resulting in low efficiency, high costs, and local blind spots. This severely restricts the intelligent construction and dynamic control of grouting projects under complex geological conditions.

[0003] In recent years, the research and development of modified slurry materials has provided new ideas for grouting monitoring. By introducing conductive additives such as metal particles and carbon fibers, the heterogeneity of slurry conductivity can be improved, and then non-contact detection can be achieved using electromagnetic methods. However, traditional metal additives (such as iron powder and steel fiber) are prone to attenuation of conductivity due to oxidation and sedimentation, and the high dosage requirement (>20wt%) will significantly deteriorate the fluidity and mechanical strength of the slurry, making it difficult to meet practical engineering needs. Liquid metals (such as gallium-based alloys) have become ideal candidate materials for modified slurries due to their room temperature fluidity, self-healing properties and stable conductivity. However, existing research has mostly focused on material modification itself, and lacks systematic integration with high-precision detection technology: traditional ground transient electromagnetic methods are restricted by terrain and are difficult to achieve large-scale rapid scanning. Although airborne transient electromagnetic technology has the advantage of efficient coverage, it cannot accurately extract grouting boundary signals due to the weak difference in electromagnetic response between conventional slurry and surrounding rock.

[0004] In special geological environments such as plateau permafrost areas and water-rich fractured zones, grouting projects often face challenges such as hidden slurry diffusion paths and dynamic evolution of reinforcement range. It is urgent to develop a grouting monitoring technology that combines material modification innovation with high-resolution detection to achieve integrated closed-loop control of "grouting-detection" and provide reliable protection for the safe operation and maintenance of underground projects. Summary of the Invention

[0005] To solve the technical problems in the above background, the present invention provides a liquid metal grouting detection method based on airborne transient electromagnetic, comprising the following steps:

[0006] Based on the liquid metal matrix and ferromagnetic particles, a composite slurry is formed;

[0007] generating a modified slurry based on the composite slurry and cement-based grouting material;

[0008] injecting the modified grout into cracks in the target rock mass;

[0009] The detection is completed by using a drone to emit electromagnetic pulses to the target rock mass and collect secondary field response signals.

[0010] Preferably, the liquid metal substrate and ferromagnetic particles are mixed to form the composite slurry; and the composite slurry is used to form a uniform conductive network in cement.

[0011] Preferably, the composite slurry is added to a cement-based grouting material to generate the modified slurry; the modified slurry utilizes the fluidity of liquid metal to improve the conductive efficiency.

[0012] Preferably, the received secondary field response signal S(t) is a time domain attenuation curve:

[0013] S(t)=Seddy(t)+Shys(t)+n(t)

[0014] Among them, S eddy Indicates eddy current signal; S hys represents the hysteresis signal; n(t) represents the noise; t represents the time;

[0015] The eddy current signal and the hysteresis signal are distinguished by wavelet transform:

[0016]

[0017] Where, ψ(t) represents the wavelet basis function; e represents the natural constant; i represents the imaginary unit; ω0 represents the angular frequency; z represents the damping coefficient;

[0018] The eddy current signal and the hysteresis signal are decomposed in the time-frequency domain to extract the eddy current component with a frequency band greater than 100 Hz and the hysteresis component with a frequency band less than 10 Hz:

[0019] Seddy(t)=Re[a1∫S(t′)ψ*(at′-t)dt′](a=0.01)

[0020] Shys(t)=Re[a1∫S(t′)ψ*(at′-t)dt′](a=1.0)

[0021] Where t′ represents the first-order derivative of t; Seddy(t) represents the time domain characteristics of the eddy current signal, and Shys(t) represents the time domain characteristics of the hysteresis signal.

[0022] Preferably, based on the diffusion equation, the relationship between the conductivity distribution σ(x, y, z) and the eddy current signal is derived:

[0023]

[0024] Where E represents the electric field strength; μ represents the magnetic permeability; σ represents the electrical conductivity;

[0025] Based on the hysteresis loop equation, the associated magnetic permeability μ r (x, y, z) and the phase shift Δφ(x, y, z) of the hysteresis signal:

[0026]

[0027] Wherein, μ′(x, y, z) represents the real part of relative permeability; μ″(x, y, z) represents the imaginary part of relative permeability; η and k represent the empirical coefficients of the material.

[0028] Preferably, the regularized conjugate gradient algorithm is used to invert the underground three-dimensional conductivity distribution to generate sub-meter resolution imaging of the grouting body diffusion boundary and weak zone. The objective function of the inversion algorithm is:

[0029] J= / / W e (d e -G e σ) / / 2+λ1 / / W m (d m -G m μ r ) / / 2+λ2 / / σ-kμr 0.7 / / 2

[0030] Among them, G e , G m represents the finite element forward kernel matrix; d e d m represents the observed data; k represents the experimental calibration coefficient; λ1 and λ2 represent the regularization parameters.

[0031] Preferably, targeted supplementary grouting is performed on uncovered areas based on the three-dimensional imaging results, and local conductivity is improved by adjusting the liquid metal content.

[0032] The present invention also provides a liquid metal grouting detection system based on aviation transient electromagnetic, said system being used to implement the above method, comprising: a mixing module, an adding module, an injection module and a detection module;

[0033] The mixing module is used to form a composite slurry based on a liquid metal substrate and ferromagnetic particles;

[0034] The adding module is used to generate a modified slurry based on the composite slurry and the cement-based grouting material;

[0035] The injection module is used to inject the modified grout into the target rock mass fissures;

[0036] The detection module is used to use the UAV to transmit electromagnetic pulses to the target rock mass and collect secondary field response signals to complete the detection.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] This invention uses airborne transient electromagnetic technology to replace traditional ground-based geophysical exploration methods. Using drone-mounted equipment, it can rapidly scan large areas, traversing complex terrain (such as mountains and rivers) while avoiding obstructions from ground buildings. This technology increases daily detection efficiency by more than three times, making it particularly suitable for scenarios such as densely populated urban areas or permafrost on the plateau, where manual deployment is difficult. Furthermore, liquid metals such as gallium-indium alloys are used as conductive media. These metals flow like water at room temperature and automatically blend evenly with cement slurry, forming a micron-scale conductive network without mechanical stirring. Traditional iron powder requires a 20% or higher addition to achieve comparable conductivity, and is prone to sedimentation and agglomeration, resulting in a decrease in slurry strength.

[0039] The present invention adds nano iron powder into liquid metal to make the modified slurry have high conductivity (>10 6 S / m) and strong magnetism (magnetic permeability increased by more than 50 times). During detection, electromagnetic pulses can not only excite eddy currents to generate conductive signals, but also amplify magnetic field differences through the hysteresis effect, thereby improving the accuracy of grouting boundary identification from meter level to sub-meter level. When the slurry solidifies, liquid metal can reconnect the conductive path as the crack expands. Even if the grouting layer is partially cracked, it can still trigger an electromagnetic response through the dynamic conductive network, avoiding the "false negative" detection problem caused by the oxidation failure of traditional iron powder, providing reliable protection for long-term monitoring of underground projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 Schematic diagram of the magnetic liquid metal grouting detection method based on airborne transient electromagnetic.

[0042] Explanation of the accompanying symbols: 1. UAV; 2. Tow line; 3. Transient electromagnetic coil; 4. Electromagnetic wave; 5. Grouting machine; 6. Broken rock mass; 7. Magnetic liquid metal slurry. DETAILED DESCRIPTION

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0044] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] Example 1

[0046] like Figure 1 Figure 1 shows a schematic flow chart of the method of this embodiment. On the ground, a grouting machine 5 injects magnetic liquid metal slurry 7 into a fractured rock formation 6, thereby reinforcing the fractured rock mass. In the figure, a drone 1, using a traction line 2, suspends a transient electromagnetic coil 3 and emits electromagnetic waves 4, thereby performing real-time detection of the slurry's diffusion range. After collecting sufficient detection data, data processing can be used to determine the slurry's diffusion range and solidification state.

[0047] The above process will be further detailed below with reference to this embodiment. The specific steps are as follows:

[0048] S1. Forming a composite slurry based on a liquid metal matrix and ferromagnetic particles.

[0049] The liquid metal substrate (including but not limited to gallium-indium alloy) is mixed with ferromagnetic particles to form a composite slurry with both electrical conductivity and magnetic properties, ensuring that it spontaneously forms a uniform conductive network in the cement.

[0050] S2. Generating a modified slurry based on the composite slurry and cement-based grouting materials.

[0051] The composite slurry is added to cement-based grouting materials to generate a modified slurry. The fluidity of liquid metal is utilized to achieve high conductivity at low addition levels, maintaining the slurry's construction performance.

[0052] S3. Inject the modified grout into the target rock mass fissures.

[0053] The modified grout is hydraulically injected into the target rock fissures, and the grouting parameters are adjusted through real-time monitoring to ensure that the conductive network covers the reinforced area.

[0054] S4. Use the UAV to transmit electromagnetic pulses to the target rock mass and collect the secondary field response signal to complete the detection.

[0055] The UAV 1 is equipped with a high-sensitivity electromagnetic detection device to transmit electromagnetic pulses to the grouting area and collect the secondary field response signal. The time domain attenuation curve of the received secondary field signal is:

[0056] S(t)=Seddy(t)+Shys(t)+n(t) (1)

[0057] Among them, S eddy Indicates eddy current signal; S hys represents the hysteresis signal; n(t) represents the noise; t represents the time.

[0058] The high-frequency eddy current signal and the low-frequency hysteresis signal are distinguished by wavelet transform. In this embodiment, the Morlet wavelet basis function is used:

[0059]

[0060] Where ψ(t) represents the wavelet basis function; e represents the natural constant; i represents the imaginary unit; ω0 represents the angular frequency; and z represents the damping coefficient.

[0061] Perform time-frequency decomposition on the eddy current signal and the hysteresis signal to extract the eddy current component in the high frequency band (>100Hz) and the hysteresis component in the low frequency band (<10Hz):

[0062] S eddy (t)=Re[a1∫S(t′)ψ*(at′-t)dt′](a=0.01) (3)

[0063] Shys(t)=Re[a1∫S(t′)ψ*(at′-t)dt′](a=1.0) (4)

[0064] Here, t′ represents the first-order derivative of t.

[0065] Based on the diffusion equation (Equation 5), the relationship between the conductivity distribution σ(x, y, z) and the eddy current signal is derived:

[0066]

[0067] Where E represents the electric field strength, μ represents the magnetic permeability, and σ represents the electrical conductivity.

[0068] Based on the hysteresis loop equation (Eq. 6), the associated magnetic permeability μ r (x, y, z) and the low-frequency signal phase offset Δφ:

[0069]

[0070] Wherein, μ′(x, y, z) represents the real part of relative permeability; μ″(x, y, z) represents the imaginary part of relative permeability; η and κ represent the empirical coefficients of the material.

[0071] Based on the conductivity-permeability coupling equations of Equations 5 and 6, the regularized conjugate gradient algorithm is used to invert the underground three-dimensional conductivity distribution and generate sub-meter resolution images of the grouting diffusion boundary and weak areas. The objective function of the inversion algorithm is:

[0072] J= / / W e (d e -G e σ) / / 2+λ1 / / W m (d m -G m μ r ) / / 2+λ2 / / σ-kμr 0.7 / / 2 (7)

[0073] Among them, G e , G m represents the finite element forward kernel matrix; d e d m represents the observed data; k represents the experimental calibration coefficient; λ1 and λ2 represent the regularization parameters.

[0074] According to the 3D imaging results, targeted supplementary grouting is carried out on uncovered areas to improve local conductivity by adjusting the liquid metal dosage. The specific operation is based on the target conductivity σ target , adjust the liquid metal content c (volume fraction):

[0075] σ(c)=σ base +βc 2 (β=5.0S / mper c 2 ) (8)

[0076] Among them, σ base represents the conductivity of the matrix; β represents the conductivity gain coefficient; c 2 represents the square of the volume fraction of the conductive additive.

[0077] This embodiment utilizes the capillary self-repairing properties of liquid metal to reform a conductive path when rock cracks expand. It also implements long-term health monitoring of the grouting rock mass based on quarterly airborne transient electromagnetic scanning combined with an attenuation rate model.

[0078] Example 2

[0079] This embodiment also provides a liquid metal grouting detection system based on airborne transient electromagnetics, including: a mixing module, an adding module, an injection module and a detection module; the mixing module is used to form a composite slurry based on a liquid metal substrate and ferromagnetic particles; the adding module is used to generate a modified slurry based on the composite slurry and cement-based grouting material; the injection module is used to inject the modified slurry into the cracks of the target rock mass; the detection module is used to use a drone 1 to transmit electromagnetic pulses to the target rock mass and collect secondary field response signals to complete the detection.

[0080] The following will describe in detail how the present invention solves technical problems in practical work in conjunction with this embodiment.

[0081] First, the mixing module creates a composite slurry based on a liquid metal matrix and ferromagnetic particles. This mixture creates a composite slurry that is both conductive and magnetic, ensuring it spontaneously forms a uniform conductive network within the cement.

[0082] The module then adds a modified slurry based on the composite slurry and cement-based grouting material. The composite slurry is then added to the cement-based grouting material to create a modified slurry. The fluidity of liquid metal is utilized to achieve high conductivity at low addition levels, maintaining the slurry's workability.

[0083] The injection module hydraulically injects the modified grout into the target rock mass fissures. The modified grout is hydraulically injected into the target rock mass fissures, and the grouting parameters are adjusted through real-time monitoring to ensure that the conductive network covers the reinforced area.

[0084] Finally, the detection module uses UAV 1 to transmit electromagnetic pulses to the target rock mass and collect secondary field response signals to complete the detection.

[0085] The UAV 1 is equipped with a high-sensitivity electromagnetic detection device to transmit electromagnetic pulses to the grouting area and collect the secondary field response signal. The time domain attenuation curve of the received secondary field signal is:

[0086] S(t)=S eddy (t)+S hys (t)+n(t) (9)

[0087] Among them, S eddy Indicates eddy current signal; S hys represents the hysteresis signal; n(t) represents the noise; t represents the time.

[0088] The high-frequency eddy current signal and the low-frequency hysteresis signal are distinguished by wavelet transform. In this embodiment, the Morlet wavelet basis function is used:

[0089]

[0090] Where ψ(t) represents the wavelet basis function; e represents the natural constant; i represents the imaginary unit; ω0 represents the angular frequency; and z represents the damping coefficient.

[0091] Perform time-frequency decomposition on the eddy current signal and the hysteresis signal to extract the eddy current component in the high frequency band (>100Hz) and the hysteresis component in the low frequency band (<10Hz):

[0092] Seddy(t)=Re[a1∫S(t′)ψ*(at′-t)dt′](a=0.01) (11)

[0093] Shys(t)=Re[a1∫S(t)ψ*(at'-t)dt′](a=1.0) (12)

[0094] Here, t′ represents the first-order derivative of t.

[0095] Based on the diffusion equation (Equation 13), the relationship between the conductivity distribution σ(x, y, z) and the eddy current signal is derived:

[0096]

[0097] Where E represents the electric field strength, μ represents the magnetic permeability, and σ represents the electrical conductivity.

[0098] Based on the hysteresis loop equation (Eq. 14), the associated magnetic permeability μ r (x, y, z) and the low-frequency signal phase offset Δψ:

[0099]

[0100] Wherein, μ′(x, y, z) represents the real part of relative permeability; μ″(x, y, z) represents the imaginary part of relative permeability; η and κ represent the empirical coefficients of the material.

[0101] Based on the conductivity-permeability coupling equations of Equations 13 and 14, the regularized conjugate gradient algorithm is used to invert the underground three-dimensional conductivity distribution and generate sub-meter resolution images of the grouting diffusion boundary and weak areas. The objective function of the inversion algorithm is:

[0102] J= / / W e (d e -G e σ) / / 2+λ1 / / W m (d m -G m μ r ) / / 2+λ2 / / σ-kμ r0.7 / / 2 (15)

[0103] Among them, G e , G mrepresents the finite element forward kernel matrix; d e d m represents the observed data; k represents the experimental calibration coefficient; λ1 and λ2 represent the regularization parameters.

[0104] According to the 3D imaging results, targeted supplementary grouting is carried out on uncovered areas to improve local conductivity by adjusting the liquid metal dosage. The specific operation is based on the target conductivity σ target , adjust the liquid metal content c (volume fraction):

[0105] σ(c)=σ base +βc 2 (β=5.0S / mperc 2 ) (16)

[0106] Among them, σ base represents the conductivity of the matrix; β represents the conductivity gain coefficient; c 2 represents the square of the volume fraction of the conductive additive.

[0107] This embodiment utilizes the capillary self-repairing properties of liquid metal to reform a conductive path when rock cracks expand. It also implements long-term health monitoring of the grouting rock mass based on quarterly airborne transient electromagnetic scanning combined with an attenuation rate model.

[0108] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A liquid metal grouting detection method based on airborne transient electromagnetic, characterized in that the steps include: Based on the liquid metal matrix and ferromagnetic particles, a composite slurry is formed; generating a modified slurry based on the composite slurry and cement-based grouting material; injecting the modified grout into cracks in the target rock mass; The detection is completed by using a drone to emit electromagnetic pulses to the target rock mass and collect secondary field response signals.

2. The liquid metal grouting detection method based on airborne transient electromagnetic according to claim 1, characterized in that: The liquid metal substrate and ferromagnetic particles are mixed to form the composite slurry; and the composite slurry is used to form a uniform conductive network in cement.

3. The liquid metal grouting detection method based on airborne transient electromagnetic according to claim 1, characterized in that: adding the composite slurry into cement-based grouting material to generate the modified slurry; The modified slurry utilizes the fluidity of liquid metal to improve the conductive efficiency.

4. The liquid metal grouting detection method based on airborne transient electromagnetic according to claim 1, characterized in that: The received secondary field response signal S(t) is a time domain attenuation curve: S(t)=Seddy(t)+Shys(t)+n(t) Among them, S eddy Indicates eddy current signal; S hys Represents hysteresis signal; S eddy (t) represents the time domain characteristics of the eddy current signal; S hys (t) represents the time domain characteristics of the hysteresis signal; n(t) represents noise; t represents time; The eddy current signal and the hysteresis signal are distinguished by wavelet transform: Where, ψ(t) represents the wavelet basis function; e represents the natural constant; i represents the imaginary unit; ω0 represents the angular frequency; z represents the damping coefficient; The eddy current signal and the hysteresis signal are decomposed in the time-frequency domain to extract the eddy current component with a frequency band greater than 100 Hz and the hysteresis component below 10 Hz: S eddv (t)=Re[a1∫S(t′)ψ * (at′-t)dt′](a=0.01) S hys (t)=Re[a1∫S(t′)ψ * (at′-t)dt′](a=1.0) Here, t′ represents the first-order derivative of t.

5. The liquid metal grouting detection method based on airborne transient electromagnetic according to claim 4, characterized in that: Based on the diffusion equation, the relationship between the conductivity distribution σ(x,y,z) and the eddy current signal is derived: Where E represents the electric field strength; μ represents the magnetic permeability; σ represents the electrical conductivity; Based on the hysteresis loop equation, the associated magnetic permeability μ r (x, y, z) and the phase shift Δφ(x, y, z) of the hysteresis signal: Wherein, μ′(x, y, z) represents the real part of relative permeability; μ″(x, y, z) represents the imaginary part of relative permeability; η and κ represent the empirical coefficients of the material.

6. The liquid metal grouting detection method based on airborne transient electromagnetic according to claim 5, characterized in that: The regularized conjugate gradient algorithm is used to invert the underground three-dimensional conductivity distribution and generate sub-meter resolution images of the grouting diffusion boundary and weak areas. The objective function of the inversion algorithm is: J= / / W e (d e -G e σ) / / 2+λ1 / / W m (d m -G m m r ) / / 2+λ2 / / σ-km r0.7 / / 2 Among them, G e , G m represents the finite element forward kernel matrix; d e d m represents the observed data; k represents the experimental calibration coefficient; λ1 and λ2 represent the regularization parameters.

7. The liquid metal grouting detection method based on airborne transient electromagnetic according to claim 6, characterized in that: Based on the three-dimensional imaging results, targeted supplementary grouting is carried out on the uncovered areas, and the local conductivity is improved by adjusting the liquid metal dosage.

8. A liquid metal grouting detection system based on airborne transient electromagnetic, the system being used to implement the method according to any one of claims 1 to 7, characterized in that: include: Mixing module, adding module, injecting module and detecting module; The mixing module is used to form a composite slurry based on a liquid metal substrate and ferromagnetic particles; The adding module is used to generate a modified slurry based on the composite slurry and the cement-based grouting material; The injection module is used to inject the modified grout into the target rock mass fissures; The detection module is used to use the UAV to transmit electromagnetic pulses to the target rock mass and collect secondary field response signals to complete the detection.

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