Ultra-wideband low-altitude electromagnetic integrated measurement device and method

Abstract

The present invention discloses an ultra-wideband low-altitude electromagnetic integrated measurement device, comprising a short-offset electromagnetic measurement device, a ground-penetrating radar measurement device, an infrared imaging measurement device, and a power supply for the short-offset electromagnetic measurement device, the ground-penetrating radar measurement device, and the infrared imaging measurement device, all of which are arranged in a horizontal plate. The short-offset electromagnetic measurement device is used to measure electromagnetic primary and secondary field data. The ground-penetrating radar measurement device is used to measure parameters related to electromagnetic reflection waves. The infrared imaging measurement device is used to image the measurement area using infrared rays. The present invention also discloses an ultra-wideband low-altitude electromagnetic integrated measurement method, which can realize the measurement, inversion, and imaging of multiple parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of electromagnetic integrated measurement, in particular to an ultra-wideband low-altitude electromagnetic integrated measurement device and method. Background Art

[0002] Currently, commonly used electromagnetic exploration methods based on low-altitude measurements include short-offset electromagnetic (SEE) and ground-penetrating radar (GPR). SEE, based on the principle of electromagnetic induction, transmits electromagnetic waves and receives reflected signals. By calculating and analyzing the amplitude and phase of the electromagnetic field, information about the conductivity of the subsurface medium can be obtained. GPR maintains a constant spacing between the transmitting and receiving antennas and moves along the survey line at a fixed measurement interval, recording electromagnetic reflections along the entire survey line. Infrared imagers can also measure infrared electromagnetic waves, detecting and identifying targets by exploiting the difference in infrared radiation energy between the target and the background received by the infrared detector. All three techniques utilize a single device to measure the relevant parameters.

[0003] In terms of data processing, joint constraint methods are generally based on physical property correlation and structural coupling. Physical property correlation constraints can be used when different physical parameters exhibit rock-physical coupling. However, when physical parameter variations lack obvious directionality, cross-gradient constraints are of limited effectiveness. Numerous researchers have proposed joint inversions of different parameters. For example, Yi Ke conducted a two-dimensional joint inversion of resistivity and permittivity using RMT and DC in the 10 kHz-1 MHz operating frequency band. Li Jie also studied the joint inversion of resistivity and thermal conductivity using magnetotelluric methods and low-temperature fields. Summary of the Invention

[0004] In order to solve the problems existing in the prior art, the purpose of the present invention is to provide an ultra-wideband low-altitude electromagnetic integrated measurement device and method, which can realize the measurement, inversion and imaging of multiple parameters.

[0005] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is: an ultra-wideband low-altitude electromagnetic integrated measurement device, including a short-offset electromagnetic measurement device, a ground-penetrating radar measurement device, an infrared imaging measurement device and a power supply for the short-offset electromagnetic measurement device, the ground-penetrating radar measurement device and the infrared imaging measurement device, all of which are arranged in a horizontal plate; wherein the short-offset electromagnetic measurement device is used to measure electromagnetic primary and secondary field data; the ground-penetrating radar measurement device is used to measure parameters related to electromagnetic reflection waves; and the infrared imaging measurement device is used to use infrared rays to image the measurement area.

[0006] As a further improvement of the present invention, a slide rail for adjusting the offset distance of the short-offset electromagnetic measurement device is further provided in the horizontal plate.

[0007] As a further improvement of the present invention, counterweights for maintaining the balance of the electromagnetic integrated measuring device are further provided on both sides and the middle of the horizontal plate.

[0008] As a further improvement of the present invention, the power supply is externally placed on a horizontal plate.

[0009] The present invention also provides an ultra-wideband low-altitude electromagnetic integrated measurement method, comprising the following steps:

[0010] Step 1: Use a drone to drag the ultra-wideband low-altitude electromagnetic integrated measurement device described above via a connecting cable; measure short-offset electromagnetic data, ground-penetrating radar data, and infrared imaging data based on the survey area and survey mission, and transmit the data to a terminal for data processing;

[0011] Step 2: Transmitting measurement data to the terminal: For short-offset electromagnetic data measurement, the transmitting coil excites a primary electromagnetic field with a certain intensity and containing different frequencies, and the receiving coil simultaneously receives the superimposed primary and secondary field data. For ground-penetrating radar data measurement, the transmitting antenna excites an electromagnetic wave signal of a certain frequency, and the receiving antenna receives the reflected electromagnetic wave data. For infrared detection, the power signal radiated from the surface is directly measured or converted into an electrical signal to calculate the surface temperature. At the same time, several temperature measurement points are set up in different areas of the surface to measure the temperature within a certain range underground.

[0012] Step 3: Establish a multi-parameter processing module: perform a joint inversion of the three parameters of resistivity, dielectric constant, and temperature simultaneously. The temperature model is added as known information to the inversion of the other two parameters, and the objective function is solved until the inversion fit error is met or the maximum number of iterations is reached.

[0013] Step 4. Establish a multi-parameter image fusion module: select two types of parameter data within a certain range of underground depth in the same measurement interval for image fusion, realize the pairwise combination of multiple parameters, and realize the fusion of images of different depths within an extremely shallow depth range.

[0014] As a further improvement of the present invention, the step 3 specifically includes the following steps:

[0015] Step 3.1: Establish temperature model:

[0016] ① According to soil heterogeneity and actual needs, the sampling area is divided into irregular random sampling or regular sampling, and several temperature measurement points are set to measure the temperature parameters within a certain range from the surface to the underground. The function of the temperature change of a single sampling point with depth T(z)=T0e is established. -αz , where T0 is the surface temperature and α is the attenuation factor;

[0017] ② Use different interpolation methods for the attenuation factor according to the sampling method: For random sampling, find the expected value c of the attenuation factor of all known sampling points, and then use the simple Kriging interpolation method to find the surface position (x i ,y i ) attenuation factor α(x i ,y i ), whose formula is where λ k Is able to satisfy the surface position (x i ,y i ) with the smallest difference between the estimated value and the true value;

[0018] For regular sampling, select the surface location (x i ,y i ) The four nearest sampling points P n (n=1,2,3,4) is obtained by the spatial area inverse weighted method, that is, connecting the four selected sampling points to form a rectangle, and drawing two perpendicular lines through the calculation point perpendicular to the sides of the rectangle, and dividing the area W of four different sizes by the rectangle and the perpendicular lines n (n=1,2,3,4), calculate Get the surface position (x i ,y i ) attenuation factor α(x i ,y i );

[0019] ③ The infrared imaging measurement device in the integrated device measures the surface temperature parameters of a large area in order to obtain the surface position (x i ,y i ) of the surface temperature T0(x i ,y i );

[0020] ④ Place the same position (x i ,y i ) attenuation factor α(x i ,y i ) and the surface temperature T0(x i ,y i ) combination, we get the function of the temperature at that location changing with depth T(z)=T0e -αz ; The temperature parameters at different depths underground at that location are calculated from this; after multiple calculations in a certain order, multiple sets of regularly arranged one-dimensional discrete temperature parameters are obtained. After combining them and performing linear interpolation calculations, the three-dimensional temperature model required for joint inversion is obtained;

[0021] Step 3.2: Input the resistivity and permittivity data from short-offset electromagnetic and ground-penetrating radar measurements and their corresponding initial models; then, input the constructed temperature model.

[0022] Step 3.3: Based on the separate inversion of resistivity and dielectric constant, the cross-gradient terms of resistivity and dielectric constant, the cross-gradient terms of resistivity and temperature, and the cross-gradient terms of dielectric constant and temperature are added to solve the joint inversion iterative calculation. The objective function is:

[0023]

[0024] in, are the measured short-offset electromagnetic data and ground-penetrating radar data, F1 and F2 are forward operators, and is the covariance matrix of the data and the model, m1, m2 and m3 are the resistivity model, dielectric constant model and temperature model, m 0,1 、m 0,2 are the resistance prior model and the dielectric constant prior model, λ1 and λ2 are regularization factors, μ1, μ2 and μ3 are the cross gradient term weights;

[0025] Step 3.4: Calculate the inversion fitting error of the current resistivity model and dielectric constant model to determine whether the termination condition is met. If so, save the current resistivity model and dielectric constant model, stop the iteration, and jump to step 3.5. If not, continue the iteration. The temperature model remains unchanged as a constraint in the inversion.

[0026] Step 3.5: Stop the inversion and output the calculated resistivity model and dielectric constant model.

[0027] The present invention can measure three parameters simultaneously or asynchronously, and realizes a multi-parameter (resistivity, dielectric constant and temperature) joint inversion algorithm of electromagnetic method, ground penetrating radar and infrared imaging.

[0028] Multi-parameter acquisition: The present invention sets the UAV flight route, measurement device combination, and measurement method according to the survey area; Multi-parameter processing: The present invention processes multiple parameters. Appropriate inversion parameters are set based on the number and type of data to be processed. The joint inversion process is a simultaneous inversion of three parameters. The temperature model is added as known information to the inversion of the other two parameters, and the objective function is solved until the inversion fitting error is met or the maximum number of iterations is reached; Multi-parameter image fusion: Multi-parameter image fusion is performed by combining multi-parameter data of different depths in the same area and extremely shallow depth range to explain the multi-parameter abnormal characteristics.

[0029] The beneficial effects of the present invention are:

[0030] The present invention combines the measurement of resistivity, dielectric constant and temperature to achieve large-area multi-parameter measurement, avoiding interference caused by environmental conditions, machines and humans, and is beneficial to setting the corresponding acquisition parameter types and acquisition methods according to actual survey work, greatly saving measurement time and costs; it realizes a multi-parameter (resistivity, dielectric constant and temperature) joint inversion algorithm based on electromagnetic method, ground penetrating radar and infrared imaging and a multi-parameter image extremely shallow depth fusion method. Visualizing the processing results is helpful to interpret the multi-parameter abnormal characteristics of the study area. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The measurement schematic diagram provided by the present invention;

[0032] Figure 2 A top view of the integrated device provided by the present invention;

[0033] Figure 3 A side view of the integrated device provided by the present invention;

[0034] Figure 4 Schematic diagram of the measurement principle provided by the present invention;

[0035] Figure 5 The random temperature measurement point distribution diagram provided by the present invention;

[0036] Figure 6 The present invention provides a distribution diagram of equidistant temperature measurement points;

[0037] Figure 7 Schematic diagram of the principle of the area inverse weighted method provided by the present invention;

[0038] Figure 8 Schematic diagram of the fusion of surface temperature and apparent resistivity images provided by the present invention;

[0039] Figure 9 Schematic diagram of the fusion of surface temperature and dielectric constant images provided by the present invention;

[0040] Figure 10 Schematic diagram of the fusion of surface temperature and inverted resistivity image provided by the present invention;

[0041] Figure 11 Schematic diagram of the fusion of surface temperature and inverted dielectric constant images provided by the present invention. DETAILED DESCRIPTION

[0042] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0043] Example

[0044] In this embodiment, the following steps are performed to achieve multi-parameter measurement, processing, and imaging:

[0045] Step 1, follow the Figure 1 The measurement diagram shown in the figure is used to measure data, that is, a drone drags the integrated device of the present invention through a connecting cable. The integrated device diagram is shown in FIG. Figure 2 and Figure 3 As shown, the contents and functions are as follows:

[0046] 1: Short-offset electromagnetic measurement device: measures electromagnetic primary and secondary field data;

[0047] 2: Slide rail: can adjust the offset distance of the short offset electromagnetic measurement device;

[0048] 3: Ground penetrating radar measurement device: measures parameters related to electromagnetic reflection waves;

[0049] 4: Infrared imaging measuring device: uses infrared rays to image the measurement area;

[0050] 5: Power supply: provides power to devices 1, 3, and 4 (externally located on the horizontal plate for easy replacement);

[0051] 6: Counterweight: maintain the balance of the entire integrated device;

[0052] 7: Signal shielding layer: prevents each measuring device from being affected by adjacent devices.

[0053] This device integrates short-offset electromagnetic (SEE), ground-penetrating radar (GPR), and infrared imaging, enabling both single-parameter and multi-parameter acquisition, either synchronously or asynchronously. To perform data measurement, a drone tows the integrated device via a connecting cable. Based on the survey area and mission, SEE data, GPR data, and infrared imaging data are measured and transmitted to a terminal for processing.

[0054] Step 2: Transmit the measurement data to the terminal. The measurement principle is as follows Figure 4 As shown in the figure, for short-offset electromagnetic data measurement, the transmitting coil excites a primary electromagnetic field of varying frequencies and strength. The receiving coil simultaneously receives the superimposed primary and secondary field data. For ground-penetrating radar data measurement, the transmitting antenna excites an electromagnetic wave signal of a single frequency, and the receiving antenna receives the reflected electromagnetic wave data. For infrared detection, the power signal radiated from the surface is directly measured or converted into an electrical signal to calculate the surface temperature. Simultaneously, several temperature measurement points are set up in different areas of the surface to measure the temperature within 1 meter of the ground.

[0055] Step 3: Establish a multi-parameter processing module:

[0056] The three parameters of resistivity, dielectric constant and temperature are jointly inverted simultaneously. The temperature model is added as known information to the inversion of the other two parameters. The following objective function is solved until the inversion fitting error is met or the maximum number of iterations is reached. The detailed process is as follows:

[0057] (1) Establish a temperature model.

[0058] ① According to soil heterogeneity and actual needs, the sampling area is divided into irregular random sampling (such as Figure 5 ), or regular sampling (as shown in Figure 6 Set up several temperature measurement points to measure the temperature parameters within the range of 1m from the surface to the underground, and establish a function of the temperature change of a single sampling point with depth: T(z) = T0e -αz , where T0 is the surface temperature and α is the attenuation factor.

[0059] ② Use different interpolation methods for the attenuation factor according to the sampling method. For random sampling, find the expected value c of the attenuation factor of all known sampling points, and then use the simple Kriging interpolation method to find the surface position (x i ,y i ) attenuation factor α(x i ,y i ), whose formula is where λ k Is able to satisfy the surface position (x i ,y i ) with the smallest difference between the estimated value and the true value;

[0060] For regular sampling, select the surface location (x i ,y i ) The four nearest sampling points P n (n=1,2,3,4) is obtained by the spatial area inverse weighted method, that is, connecting the four selected sampling points to form a rectangle, and drawing two perpendicular lines through the calculation point perpendicular to the sides of the rectangle, and dividing the area W of four different sizes by the rectangle and the perpendicular lines n (n=1,2,3,4)(e.g. Figure 7 As shown), calculate Get the surface position (x i ,y i ) attenuation factor α(x i ,y i ).

[0061] ③ The infrared imaging measurement device in the integrated device measures the surface temperature parameters of a large area in order to obtain the surface position (x i ,y i ) of the surface temperature T0(x i ,y i).

[0062] ④ Place the same position (x i ,y i ) attenuation factor α(x i ,y i ) and the surface temperature T0(x i ,y i ) combination, we get the function of the temperature at that location changing with depth T(z)=T0e -αz This allows the calculation of temperature parameters at different depths underground. By performing the above calculations multiple times in a certain order, we can obtain multiple sets of regularly arranged one-dimensional discrete temperature parameters. Combining these and performing linear interpolation calculations yields the three-dimensional temperature model required for joint inversion.

[0063] (2) Input the resistivity and dielectric constant data measured by short-offset electromagnetic method and ground penetrating radar and their corresponding initial models. Then, input the temperature model constructed in step (1).

[0064] (3) Based on the traditional resistivity inversion and dielectric constant inversion, the cross-gradient terms of resistivity and dielectric constant, the cross-gradient terms of resistivity and temperature, and the cross-gradient terms of dielectric constant and temperature are added to solve the joint inversion iterative calculation. The objective function is:

[0065]

[0066] in, are the measured short-offset electromagnetic data and ground-penetrating radar data, F1 and F2 are forward operators, and is the covariance matrix of the data and the model, m1, m2 and m3 are the resistivity model, dielectric constant model and temperature model, m 0,1 、m 0,2 are the resistance prior model and the dielectric constant prior model, λ1 and λ2 are regularization factors, and μ1, μ2 and μ3 are the cross-gradient term weights.

[0067] (4) Calculate the inversion fitting difference of the current resistivity model and dielectric constant model to determine whether the termination condition is met: if so, save the current resistivity model and dielectric constant model and stop the iteration, and jump to step (5); if not, continue the iteration, and the temperature model always remains unchanged as constraint information in the inversion.

[0068] (5) Stop inversion and output the calculated resistivity model and dielectric constant model.

[0069] Step 4: Establish a multi-parameter image fusion module:

[0070] This embodiment can select two types of parameter data with an underground depth of 1m in the same measurement interval for image fusion, which can not only realize the pairwise combination of multiple parameters, but also realize the fusion of images at different depths.

[0071] The surface temperature obtained by infrared imaging is fused with the resistivity at a depth of 0.5 meters obtained by short-offset electromagnetic method. Figure 8 .

[0072] The surface temperature obtained by infrared imaging is fused with the dielectric constant at a depth of 0.5 meters obtained by ground penetrating radar. Figure 9 .

[0073] Furthermore, for the joint inversion results, the present invention can still use image fusion to visualize the data, which helps to make the interpretation intuitive and characterized.

[0074] The surface temperature obtained by infrared imaging is fused with the resistivity and dielectric constant at a depth of 0.5 meters obtained by joint inversion. Figure 10 and Figure 11 shown.

[0075] The above-described embodiments merely represent specific implementations of the present invention. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, and all such variations and improvements fall within the scope of protection of the present invention.

Claims

1. An ultra-wideband low-altitude electromagnetic integrated measurement method, characterized in that: The following steps are involved: Step 1: Use a drone to drag an ultra-wideband low-altitude electromagnetic integrated measurement device via a connecting cable; measure short-offset electromagnetic data, ground-penetrating radar data, and infrared imaging data based on the survey area and survey mission, and transmit the data to the terminal for data processing; The ultra-wideband low-altitude electromagnetic integrated measurement device includes: a short-offset electromagnetic measurement device, a ground-penetrating radar measurement device, an infrared imaging measurement device, and a power supply for the short-offset electromagnetic measurement device, the ground-penetrating radar measurement device, and the infrared imaging measurement device, all located within a horizontal plate; wherein the short-offset electromagnetic measurement device is used to measure electromagnetic primary and secondary field data; the ground-penetrating radar measurement device is used to measure parameters related to electromagnetic reflection waves; and the infrared imaging measurement device is used to image the measurement area using infrared rays; Step 2: Transmitting measurement data to the terminal: For short-offset electromagnetic data measurement, the transmitting coil excites a primary electromagnetic field with a certain intensity and containing different frequencies, and the receiving coil simultaneously receives the superimposed primary and secondary field data. For ground-penetrating radar data measurement, the transmitting antenna excites an electromagnetic wave signal of a certain frequency, and the receiving antenna receives the reflected electromagnetic wave data. For infrared detection, the power signal radiated from the surface is directly measured or converted into an electrical signal to calculate the surface temperature. At the same time, several temperature measurement points are set up in different areas of the surface to measure the temperature within a certain range underground. Step 3: Establish a multi-parameter processing module: perform a joint inversion of the three parameters of resistivity, dielectric constant, and temperature simultaneously. The temperature model is added as known information to the inversion of the other two parameters, and the objective function is solved until the inversion fit error is met or the maximum number of iterations is reached. The step 3 specifically includes the following steps: Step 3.1: Establish temperature model: ① According to soil heterogeneity and actual needs, the sampling area is divided into irregular random sampling or regular sampling, and several temperature measurement points are set to measure the temperature parameters within a certain range from the surface to the underground. The function of the temperature change of a single sampling point with depth T(z)=T0e is established. -αz , where T0 is the surface temperature and α is the attenuation factor; ② Use different interpolation methods for the attenuation factor according to the sampling method: For random sampling, find the expected value c of the attenuation factor of all known sampling points, and then use the simple Kriging interpolation method to find the surface position (x i ,y i ) attenuation factor α(x i ,y i ), whose formula is where λ k Is able to satisfy the surface position (x i ,y i ) with the smallest difference between the estimated value and the true value; For regular sampling, select the position corresponding to the surface (x i ,y i ) The four nearest sampling points P n’ , n'=1, 2, 3, 4, and the spatial area inverse weighted method is used to obtain it, that is, the four selected sampling points are connected to form a rectangle, and two perpendicular lines are drawn through the calculation point, which are perpendicular to the sides of the rectangle. Four area regions of different sizes are divided by the rectangle and the perpendicular lines. n , n=1, 2, 3, 4, calculate Get the surface position (x i ,y i ) attenuation factor α(x i ,y i ); ③ The infrared imaging measurement device in the ultra-wideband low-altitude electromagnetic integrated measurement device measures the surface temperature parameters of a large area in order to obtain the surface position (x i ,y i ) of the surface temperature T0(x i ,y i ); ④ Place the same position (x i ,y i ) attenuation factor α(x i ,y i ) and the surface temperature T0(x i ,y i ) combination, we get the function of the temperature at that location changing with depth T(z)=T0e -αz ; The temperature parameters at different depths underground at that location are calculated from this; after multiple calculations in a certain order, multiple sets of regularly arranged one-dimensional discrete temperature parameters are obtained. After combining them and performing linear interpolation calculations, the three-dimensional temperature model required for joint inversion is obtained; Step 3.2: Input the resistivity and permittivity data from short-offset electromagnetic and ground-penetrating radar measurements and their corresponding initial models; then, input the constructed temperature model. Step 3.3: Based on the separate inversion of resistivity and dielectric constant, the cross-gradient terms of resistivity and dielectric constant, the cross-gradient terms of resistivity and temperature, and the cross-gradient terms of dielectric constant and temperature are added to solve the joint inversion iterative calculation. The objective function is: in, are the measured short-offset electromagnetic data and ground-penetrating radar data, F1 and F2 are forward operators, and is the covariance matrix of the data and the model, m1, m2 and m3 are the resistivity model, dielectric constant model and temperature model, m 0,1 、m 0,2 are the resistance prior model and the dielectric constant prior model, λ1 and λ2 are regularization factors, μ1, μ2 and μ3 are the cross gradient term weights; Step 3.4: Calculate the inversion fitting error of the current resistivity model and dielectric constant model to determine whether the termination condition is met. If so, save the current resistivity model and dielectric constant model, stop the iteration, and jump to step 3.

5. If not, continue the iteration. The temperature model remains unchanged as a constraint in the inversion. Step 3.5: Stop the inversion and output the calculated resistivity model and dielectric constant model; Step 4. Establish a multi-parameter image fusion module: select two types of parameter data within a certain range of underground depth in the same measurement interval for image fusion, realize the pairwise combination of multiple parameters, and realize the fusion of images of different depths within an extremely shallow depth range.

2. The ultra-wideband low-altitude electromagnetic integrated measurement method according to claim 1, characterized in that: The horizontal plate is also provided with a slide rail for adjusting the offset distance of the short offset electromagnetic measurement device.

3. The ultra-wideband low-altitude electromagnetic integrated measurement method according to claim 1, characterized in that: Counterweights for maintaining the balance of the ultra-wideband low-altitude electromagnetic integrated measurement device are also provided on both sides and the middle of the horizontal plate.

4. The ultra-wideband low-altitude electromagnetic integrated measurement method according to claim 1, characterized in that: The power supply is externally arranged on a horizontal plate.

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