A method and platform for collaborative intelligent detection using UAV transient electromagnetic and ground-penetrating radar

Abstract

This invention pertains to geophysical exploration technology and provides a method and platform for collaborative intelligent detection using UAV transient electromagnetic and ground-penetrating radar. The technical solution involves: acquiring preliminary detection data of the detection area; determining the initial depth and location of the target based on the preliminary detection data; determining a collaborative detection allocation scheme for the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module based on the required detection accuracy and depth at the initial depth and location of the target; analyzing the relationship between meteorological data acquired by the UAV transient electromagnetic detection module and the corresponding receiving location under the collaborative detection allocation scheme to obtain the optimal detection location; performing collaborative detection on the target body in the target area at the optimal detection location to obtain the collaborative detection results; and performing three-dimensional joint inversion imaging based on the collaborative detection results to obtain the imaging results. This approach reduces resource consumption and improves the reliability of the detection.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration technology, and in particular relates to a method and platform for intelligent detection using a combination of unmanned aerial vehicle transient electromagnetic and ground penetrating radar. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In the field of geophysical exploration, accurately detecting the electrical characteristics of subsurface media is crucial for tasks such as geological hazard investigation and resource exploration. In recent years, unmanned aerial vehicle (UAV) technology has made significant progress in this field, especially UAV transient electromagnetic technology and UAV ground-penetrating radar technology. Due to their flexibility and efficiency, they have rapidly become key technologies for areas that are difficult to cover by traditional exploration methods, such as swamps, glaciers, and plateaus.

[0004] Unmanned aerial vehicle (UAV) transient electromagnetic technology detects underground structures through ground-based transmission and aerial reception, covering depths from a few meters to several kilometers, providing an effective means of exploring deep geological structures. Meanwhile, UAV ground-penetrating radar technology is renowned for its high-resolution detection of subsurface structures. Although its detection depth is relatively limited, and its accuracy may decrease significantly with increasing depth, it still holds irreplaceable advantages in detecting shallow geological structures.

[0005] However, the limitations in accuracy of UAV transient electromagnetic technology and the limitations in depth of UAV ground-penetrating radar technology make it difficult for a single technology to meet the detection needs under complex geological conditions. Existing methods suffer from problems such as low efficiency, high cost, and inaccurate data, and lack intelligent systems that can automatically select the best detection combination and dynamically adjust the detection strategy based on pre-detection data. Summary of the Invention

[0006] To address at least one of the technical problems mentioned above, this invention provides a collaborative intelligent detection method and platform for UAV transient electromagnetic and ground-penetrating radar. This method integrates the advantages of UAV transient electromagnetic and UAV ground-penetrating radar technologies to perform collaborative intelligent detection, achieving comprehensive, efficient, and high-precision detection of underground structures. This greatly improves the efficiency and accuracy of underground structure detection and provides strong technical support for fields such as resource exploration, environmental monitoring, and disaster prevention.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of this invention provides a method for intelligent detection using a combination of transient electromagnetic and ground-penetrating radar from an unmanned aerial vehicle (UAV), comprising the following steps: Obtain preliminary detection data of the detection area; The initial depth and location of the target are determined based on preliminary detection data of the detection area; Based on the requirements for detection accuracy and depth under the initial depth and position of the target, a collaborative detection allocation scheme for the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module is determined. By analyzing the relationship between meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module under the collaborative detection allocation scheme and the corresponding receiving positions, the optimal receiving position is obtained. At the optimal receiving position, the target body in the target area is detected collaboratively to obtain the collaborative detection results. Based on the collaborative detection results, three-dimensional joint inversion imaging is performed to obtain the imaging results.

[0008] Furthermore, the step of determining a collaborative detection allocation scheme between the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module based on the initial depth and position of the target and the requirements for detection accuracy and depth includes: When the initial depth of the target is less than the first preset value, the target is determined to be in the shallow layer. At this time, the UAV ground-penetrating radar module is used as the main detection module and the UAV transient electromagnetic detection module is used as the secondary detection module. When the initial depth of the target is greater than the second preset value, it is determined that the target is in a deep layer, and the detection depth is increased. As the depth increases, the UAV transient electromagnetic detection module is used as the main detection module and the UAV ground-penetrating radar module is used as the secondary detection module. When the initial depth of the target being detected is greater than the third preset value, the UAV ground-penetrating radar module is turned off; Among them, the first preset value < the second preset value < the third preset value.

[0009] Furthermore, the preliminary detection data for the detection area includes: UAV transient electromagnetic detection data and UAV ground-penetrating radar data; among which, the UAV transient electromagnetic detection data includes the turn-off time of the secondary field, attenuation voltage, apparent resistivity, apparent conductivity, the acquisition location of the UAV transient electromagnetic detection module, and the coil attitude information acquired by the attitude sensor; the UAV ground-penetrating radar data includes reflected wave signals, physical characteristics of the reflected waves collected by the receiving antenna, and the acquisition location of the UAV ground-penetrating radar.

[0010] Furthermore, the analysis of the meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module under the collaborative detection allocation scheme, and the corresponding receiving positions, yields the optimal receiving position, including: The meteorological data and collection location data acquired by the corresponding UAV detection module are used as input features, and the optimal receiving location is used as the target variable to train the machine learning model. The loss function of the machine learning model is minimized, and the optimal receiving location information is output.

[0011] Furthermore, when performing three-dimensional joint inversion based on the collaborative detection results, the results detected by the main detection module are used as the primary method, while the results detected by the secondary detection module are used as secondary methods. The results of the secondary detection module are used to supplement and correct the results detected by the main detection module.

[0012] Furthermore, the initial depth and location of the target are determined based on preliminary detection data of the detection area, including: inferring the depth by measuring the decay time of the electromagnetic field underground using transient electromagnetic detection, and determining the location based on resistivity profiles; determining the depth by measuring the time from transmission to reception of electromagnetic waves using ground penetrating radar, recording the movement trajectory and position information of the antenna during the measurement process, and combining the radar data to determine the planar position of the target.

[0013] A second aspect of the present invention provides a collaborative intelligent detection platform for transient electromagnetic and ground-penetrating radar from unmanned aerial vehicles, comprising: The preliminary exploration data acquisition module is used to acquire preliminary exploration data of the exploration area; The target initial information acquisition module is used to determine the initial depth and position of the target based on the preliminary detection data of the detection area; The collaborative detection scheme determination module is used to determine the collaborative detection allocation scheme between the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module based on the requirements for detection accuracy and depth under the initial depth and position of the detection target. The collaborative detection adjustment module is used to analyze the relationship between the meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module under the collaborative detection allocation scheme and the corresponding receiving position, so as to obtain the optimal receiving position; The cooperative detection module, based on the optimal receiving position, performs cooperative detection on the target body in the target area, obtains the cooperative detection results, and performs three-dimensional joint inversion imaging based on the cooperative detection results to obtain the imaging results.

[0014] Furthermore, both the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module use ground-based transmission for their transmitting modules and air-based reception modules for their receiving modules. The UAV ground-penetrating radar module uses either low-altitude flight reception at a set altitude or fixed-point ground reception.

[0015] Furthermore, the receiving modules of the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module are mounted on a dedicated UAV. The dedicated UAV includes a hollow frame and a power system. The hollow frame includes multiple arms, and the power system is located at the end of each arm. In the middle of the hollow frame is a coil storage compartment that accommodates a split receiving coil. The power system includes a coaxially distributed rotor shaft, insulated wings, and a double-layer motor. The insulated wings are divided into upper and lower layers, both connected to the rotor shaft. The inner and outer layers of the double-layer motor rotate in opposite directions to eliminate electromagnetic signal interference generated when the internal rotor rotates.

[0016] Furthermore, the UAV transient electromagnetic detection module includes a first weather collection module, a first transmitting module, and a first receiving module; The first meteorological data collection module is used to monitor temperature, humidity, air pressure, wind speed, and wind direction; The first transmitting module includes an electromagnetic transmitter and a transmitting antenna. The transmitter is used to transmit a square wave of a set frequency into the ground, and the transmitting antenna is used to pass a bipolar pulse current to generate a primary magnetic field. The first receiving module includes a receiving coil, a first positioning system, and a data acquisition recorder. The receiving coil is used to continuously receive secondary induced magnetic field signals generated by the underground medium. The positioning system is used to record the location of data points and the acquisition location. The attitude sensor includes at least an integrated three-component tilt sensor, an electronic compass, an altimeter, a thermometer, and a barometer. The data acquisition recorder is used to record and store the secondary induced magnetic field signals received by the receiving coil, the data acquired by the positioning system, and the coil attitude information acquired by the attitude sensor. The UAV ground-penetrating radar module includes a second weather collection module, an antenna, a transmitter, a receiver, and a second positioning system; The second meteorological data collection module is used to monitor temperature, humidity, air pressure, wind speed, and wind direction in real time; The antenna is used to transmit and receive electromagnetic wave signals, and the transmitter is used to generate short pulse electromagnetic pulses, which are transmitted underground through the antenna. The receiver is designed to detect signals reflected back from underground. The second positioning system is used to record the location of data points and the collection location.

[0017] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention utilizes the collaborative detection of a UAV transient electromagnetic detection module and a UAV ground-penetrating radar module. It intelligently combines and adjusts these modules at different detection depths and in different environments to achieve optimal detection results. It is applicable to various complex environments, such as swamps, glaciers, and plateaus, and has broad application prospects. 2. This invention can automatically determine the depth and location of the target based on pre-detection data and intelligently select the most suitable detection combination. In addition, the system can dynamically adjust the detection strategy based on the actual detection environment and target through machine learning algorithms, automatically optimize the receiving point and detection parameters, reduce resource consumption, and improve detection quality.

[0018] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0020] Figure 1 This is a flowchart of a method for collaborative intelligent detection using transient electromagnetic radiation and ground-penetrating radar provided by an embodiment of the present invention; Figure 2 This is a schematic diagram of a UAV transient electromagnetic and ground-penetrating radar collaborative intelligent detection platform provided in an embodiment of the present invention. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0024] Addressing the issues of inefficiency, high cost, and inaccurate data in existing methods mentioned in the background section, and lacking intelligent systems to automatically select the optimal detection combination and dynamically adjust detection strategies based on pre-detection data, this invention utilizes transient electromagnetic and ground-penetrating radar equipment mounted on an unmanned aerial vehicle (UAV) platform for collaborative intelligent detection. This enables comprehensive, efficient, and high-precision detection of underground structures, overcoming the shortcomings of existing technologies and bringing revolutionary progress to the field of geophysical exploration. This integrated method and platform will greatly improve the efficiency and accuracy of underground structure detection, providing strong technical support for resource exploration, environmental monitoring, and disaster prevention.

[0025] Example 1 like Figure 1 As shown, this embodiment provides a method for intelligent detection using a combination of UAV transient electromagnetic and ground-penetrating radar, including the following steps: Step 1: Obtain preliminary detection data for the detection area; Before coordinating detection, an automated pre-detection process is implemented through the transient electromagnetic detection module and the ground-penetrating radar module of the UAV group. During this stage, the control units of the transient electromagnetic detection module and the ground-penetrating radar module of the UAV group set the detection module of the UAV group to automatic cruise detection mode and perform preliminary detection on the designated detection area.

[0026] In this embodiment, the preliminary detection data of the detection area includes meteorological data, transient electromagnetic detection data, and ground-penetrating radar data of the detection area; Meteorological data includes key meteorological parameters such as temperature, humidity, air pressure, wind speed, and wind direction, which are used to assess the climate conditions and environmental characteristics of the detection area. The collected wind speed and direction data are crucial for correcting the drone's flight path, ensuring a stable and accurate trajectory even under complex weather conditions. Furthermore, temperature and humidity data are equally important for calibrating the performance of electromagnetic sensors, helping them adapt to environmental changes and thus improving the accuracy and reliability of the detection data. This step provides the foundational data for subsequent precise detection.

[0027] The transient electromagnetic detection data includes the turn-off time of the secondary field, decay voltage, apparent resistivity, apparent conductivity, UAV acquisition location, and coil attitude information acquired by the attitude sensor. Ground penetrating radar data includes reflected wave signals, physical characteristics of the reflected waves collected by the receiving antenna such as wavelength, waveform, amplitude, and the location of the UAV ground penetrating radar.

[0028] Step 2: Determine the initial depth and location of the target based on the preliminary detection data of the detection area; In this embodiment, the depth can be inferred by measuring the decay time of the electromagnetic field underground using transient electromagnetic detection, and the location can be determined based on the resistivity profile. Alternatively, the depth can be determined by measuring the time from transmission to reception of electromagnetic waves using ground-penetrating radar. During the measurement process, the movement trajectory and position information of the antenna are recorded, and combined with radar data, the planar position of the target can be determined.

[0029] The choice of which data to use depends on the specific circumstances. For example, radar detection is more accurate in shallow layers (within 30m), while transient electromagnetic detection data is used if the target is more than 100m away and the initial depth of the radar is not a reliable reference.

[0030] Step 3: Based on the required detection accuracy at the initial depth and position of the target, determine the collaborative detection allocation scheme between the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module; Based on the detection accuracy of the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module at different depths, the collaborative detection module is intelligently assigned to a main detection module and a secondary detection module, specifically including the following steps: When the depth of the target is less than the first preset value, the target is determined to be in the shallow layer. The UAV ground-penetrating radar module has relatively high accuracy. At this time, the UAV ground-penetrating radar module is used as the main detection module and the UAV transient electromagnetic detection module is used as the secondary detection module. When the depth of the target is greater than the second preset value, it is determined that the target is in a deep layer and the detection depth is increased. When the accuracy of the UAV ground-penetrating radar is lower than that of the UAV transient electromagnetic detection module as the depth increases, the UAV transient electromagnetic detection module is used as the main detection module and the UAV ground-penetrating radar module is used as the secondary detection module. When the target's depth exceeds the third preset value, the UAV's ground-penetrating radar module is turned off; In this embodiment, the first preset value < the second preset value < the third preset value. When setting the preset value, for example, it can be selected that the detection accuracy of ground penetrating radar decreases with increasing depth in the 0-30m range, and the detection accuracy of transient electromagnetic (which can detect depths of 500m) decreases with increasing depth in the 0-100m range. It can be set that ground penetrating radar is the main sensor in the 0-10m range, transient electromagnetic is the main sensor in the 10-30m range, and ground penetrating radar is turned off in the greater than 30m range.

[0031] When preliminary detection results indicate that the detection depth or accuracy of a single detection module is sufficient to meet the needs of the target (for example, when the detection depth exceeds a certain depth, the reliability of the ground-penetrating radar interpretation results decreases), the system will automatically shut down another detection module to optimize resource allocation. This intelligent scheduling mechanism not only improves detection efficiency but also reduces energy consumption.

[0032] Step 4: Analyze the relationship between the meteorological data obtained under the collaborative detection allocation scheme and the positions of the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module to obtain the optimal receiving position; In this embodiment, the optimal receiving location information is obtained based on the relationship between the meteorological data acquired under the cooperative detection allocation scheme and the receiving location of the UAV, specifically including: Meteorological data and drone-collected location data are used as input features, with the optimal receiving location as the target variable. The collected data is used to train a machine learning model, and the loss function is minimized. The model performance is evaluated on the validation set and the final performance is evaluated on the test set to ensure that the model can accurately determine the optimal receiving location.

[0033] In this embodiment, the acquired data is divided into training, validation, and test sets according to a certain ratio. The machine learning algorithm can be random forest, support vector machine, etc. The algorithm is meticulously trained using the training set and validated through testing. The algorithm accurately outputs the optimal receiving position information and feeds it directly back to the UAV control system, automatically adjusting the optimal receiving points of the main detection module and the secondary detection module to adapt to different detection environments.

[0034] This environmental adaptability ensures that the detection module maintains optimal performance under varying climatic and geographical conditions.

[0035] Step 5: Based on the optimal receiving position, perform cooperative detection on the target body in the target area, obtain the cooperative detection results, and perform three-dimensional joint inversion imaging based on the cooperative detection results to obtain the imaging results.

[0036] In this embodiment, based on the collaborative detection results, a three-dimensional joint inversion imaging interpretation is performed on the UAV semi-airborne transient electromagnetic detection results and UAV ground-penetrating radar data. During the joint inversion, the results of the main detection module (such as semi-airborne transient electromagnetic detection) are primary, and the results of the secondary detection module (such as ground-penetrating radar) are secondary. A multi-source data fusion algorithm and a joint inversion strategy are adopted to fully utilize the complementary advantages of the two detection technologies for joint inversion imaging. Specifically, in order to improve the accuracy and reliability of the inversion imaging, a multi-level optimization strategy is adopted during the inversion process, including multi-scale joint inversion, the introduction of constraint conditions (such as geological prior information, physical parameter correlation, etc.), and artificial intelligence-based model parameter dynamic adjustment technology. The multi-scale joint inversion process includes: Low-frequency to high-frequency step-by-step inversion: First, invert the low-frequency data to obtain large-scale structural information, and then introduce high-frequency data to refine local features; Progressively complex models: Start with a simple initial model (such as a uniform model) and gradually introduce more complex model parameters and details; Block-based optimization: Based on the complexity of the target region, the region is divided into several sub-regions, the inversion results are optimized separately, and finally integrated.

[0037] The constraints introduced include: Geological prior information: Using geological surveys, borehole data, or historical research results, set reasonable initial values ​​or constraints for the model; Physical parameter correlation: Introduce relationships between various physical parameters (such as the correlation between density and velocity) to improve the physical consistency of the model through joint constraints; Regularization methods: Employ gradient constraints, smoothing constraints, or sparse constraints to prevent overfitting or unstable solutions; Dynamic adjustment based on artificial intelligence: Dynamic parameter optimization: Using artificial intelligence algorithms (such as genetic algorithms, particle swarm optimization, or deep learning) to adjust the inversion parameters in real time; Model update strategy: Through iterative optimization, dynamically adjust the model structure and parameters to gradually approach the true solution; Uncertainty analysis: Based on Bayesian methods or Monte Carlo simulation, assess the uncertainty of the model results and optimize the inversion credibility.

[0038] During the data fusion process, the differences between the two detection methods are balanced and the overall consistency of the inversion results is enhanced by optimizing feature extraction and weight allocation.

[0039] The feature extraction process includes: Signal processing: Preprocessing data from different detection methods (denoising, filtering, etc.); Multidimensional feature extraction: Extracting key features from various types of data, such as waveform, amplitude, phase, and spectral features; Weight allocation optimization includes: Data quality assessment: Evaluate the quality of various types of data based on indicators such as signal-to-noise ratio, coverage, and resolution; Dynamic weight allocation: The weights of different data are dynamically adjusted based on the importance or credibility of the data; Objective function optimization: Achieving comprehensive utilization of data through weighted objective functions (such as the least squares method); Data fusion and consistency enhancement include: Cooperative constraint inversion: During the inversion process, cooperative optimization is performed by utilizing the coupling relationship between different data types (such as the correlation between velocity field and resistivity field); Consistency assessment of results: Consistency analysis is performed on the joint inversion results to ensure the matching between different physical parameters; Iterative update: Based on the inconsistency of the inversion results, the weights and constraints are readjusted to further optimize the model.

[0040] In the inversion process, the results of the main detection module play a dominant role, ensuring the stability and physical rationality of the inversion process by updating and optimizing the model parameters; the results of the secondary detection module serve as auxiliary information to supplement and correct the results of the main detection module.

[0041] Step 6: Visualize the inversion results using 3D imaging to intuitively display the structural features. Verify the inversion results by combining them with real geological data or experimental data, and correct the model accordingly.

[0042] Finally, through 3D visualization technology, the joint inversion imaging results are presented in an intuitive form. Combined with geological background information and historical exploration data, the interpretation of the results is further improved, providing more accurate and comprehensive decision-making basis for resource exploration, environmental monitoring, and engineering construction. Simultaneously, this method can be widely applied to the detection of underground structures under complex geological conditions, possessing high practical value and potential for widespread application. Through this collaborative intelligent detection, the present invention enables refined detection of the target, improving detection accuracy and efficiency. Furthermore, this collaborative intelligent detection method also considers energy consumption and detection costs, achieving efficient resource utilization by optimizing detection paths and strategies.

[0043] Example 2 This embodiment provides a collaborative intelligent detection platform for transient electromagnetic and ground-penetrating radar from unmanned aerial vehicles (UAVs), including: The preliminary exploration data acquisition module is used to acquire preliminary exploration data of the exploration area; The target initial information acquisition module is used to determine the initial depth and position of the target based on the preliminary detection data of the detection area; The collaborative detection scheme determination module is used to determine the collaborative detection allocation scheme between the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module based on the requirements for detection accuracy and depth under the initial depth and position of the detection target. The collaborative detection adjustment module is used to analyze the relationship between the meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module under the collaborative detection allocation scheme and the corresponding receiving position, so as to obtain the optimal receiving position; The cooperative detection module, based on the optimal receiving position, performs cooperative detection on the target body in the target area, obtains the cooperative detection results, and performs three-dimensional joint inversion imaging based on the cooperative detection results to obtain the imaging results.

[0044] In this embodiment, the UAV group detection module consists of a UAV transient electromagnetic detection module and a UAV ground-penetrating radar module. These two modules work together to achieve refined detection at different depths in the detection area.

[0045] The receiving modules of the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module are mounted on a dedicated UAV, adopting the structure described in "Sun Huaifeng, Chen Chengdong, Yang Yang, et al. A dedicated UAV for a semi-airborne transient electromagnetic detection and receiving system: CN202010243335.1 [P]. CN111422343A [2025-01-14].". Specifically, it adopts a multi-rotor UAV, including a hollow frame and a power system. The hollow frame has multiple arms, and the power system is installed at the end of each arm. The middle of the hollow frame has a coil storage compartment for accommodating split receiving coils. The power system includes a coaxially distributed rotor shaft, insulated wings, and a double-layer motor. The insulated wings are divided into upper and lower layers, both connected to the rotor shaft. The inner and outer layers of the double-layer motor rotate in opposite directions to eliminate electromagnetic signal interference generated when the internal rotor rotates, and the insulated wings will not generate electromagnetic interference by cutting magnetic field lines.

[0046] Both the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module use ground-based transmission; the receiving modules use air-based reception. The UAV ground-penetrating radar module can receive signals at low altitude (less than 5m) or at a fixed ground location to reduce ground interference and improve signal reception quality.

[0047] In the preliminary detection data acquisition module, the meteorological data of the detection area includes two parts: one part is acquired by the UAV transient electromagnetic detection module, and the other part is acquired by the UAV ground-penetrating radar module. The transient electromagnetic detection data is acquired through the UAV transient electromagnetic detection module, specifically as follows: The UAV transient electromagnetic detection module includes a first weather collection module, a first transmitting module, and a first receiving module; The first meteorological collection module is used to monitor key meteorological parameters such as temperature, humidity, air pressure, wind speed and wind direction in real time, and to assess the climate conditions and environmental characteristics of the detection area. The first transmitting module includes a high-power electromagnetic transmitter and a transmitting antenna. The transmitting electrode is used to transmit a square wave of a set frequency into the ground, and the transmitting antenna is used to pass a bipolar pulse current to generate a primary magnetic field.

[0048] In this embodiment, the bipolar pulse current can be a trapezoidal wave, a half-sine wave, a triangular wave, etc. The first receiving module includes a receiving coil, a positioning system, an attitude sensor, and a data acquisition recorder. The receiving coil is used to continuously receive secondary induced magnetic field signals generated by the underground medium. The positioning system is used to locate underground features and UAV features, and accurately record the position and acquisition location of data points during the measurement process. The attitude sensor includes at least an integrated three-component tilt sensor, an electronic compass, an altimeter, a thermometer, and a barometer. The data acquisition recorder is used to record and store the secondary induced magnetic field signals received by the receiving coil, the data acquired by the positioning system, and the coil attitude information acquired by the attitude sensor.

[0049] The UAV transient electromagnetic detection module also includes a power supply module and a first control unit. The power supply module provides necessary power support for the transmitter and receiver. The first control unit includes a UAV flight control system and a transient electromagnetic detection control system. The UAV flight control system is responsible for tasks such as UAV takeoff, flight, hovering, and landing; the transient electromagnetic detection control system is responsible for tasks such as controlling the operating status of the transmitter and receiver, data acquisition, and storage.

[0050] The ground-penetrating radar data was acquired through the UAV's ground-penetrating radar module, specifically as follows: The UAV ground-penetrating radar module includes a second meteorological collection module, an antenna, a transmitter, a receiver, and a positioning system; The second meteorological collection module is mounted on the drone to monitor key meteorological parameters such as temperature, humidity, air pressure, wind speed and wind direction in real time, and to assess the climate conditions and environmental characteristics of the detection area based on the meteorological parameters.

[0051] The antenna is used to transmit and receive electromagnetic wave signals, and the number of antennas is greater than or equal to 1.

[0052] The transmitter is used to generate short-pulse electromagnetic pulses, which are transmitted underground via an antenna.

[0053] The receiver is designed to detect signals reflected back from underground.

[0054] The positioning system is used to locate underground features and UAV features, and accurately records the location of data points and collection locations during the measurement process.

[0055] The flight altitude of the UAV ground-penetrating radar module is precisely controlled in two ways: ground-based fixed-point detection and / or low-altitude flight model. These two methods ensure that the radar module maintains an optimal flight altitude during mission execution, enabling efficient and accurate scanning of the detection area.

[0056] The UAV ground-penetrating radar module also includes a storage module, a display, a power module, and a second control unit; The storage module is used to store the collected information and can be a storage device such as a hard drive or memory card. The display is used to monitor the data collection process in real time and also includes output for visualizing the processed data. The power module is responsible for powering the ground-penetrating radar system and, depending on the application, can be powered by a battery or connected to an external power source.

[0057] The control unit can be a microcontroller or an FPGA, and includes a user interface, a display, and controls for setting measurement parameters, initiating data collection, and adjusting system settings.

[0058] In the collaborative detection scheme determination module, the step of determining the collaborative detection allocation scheme between the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module based on the requirements for detection accuracy and depth under the initial depth and position of the detection target includes: When the initial depth of the target is less than the first preset value, the target is determined to be in the shallow layer. At this time, the UAV ground-penetrating radar module is used as the main detection module and the UAV transient electromagnetic detection module is used as the secondary detection module. When the initial depth of the target is greater than the second preset value, it is determined that the target is in a deep layer, and the detection depth is increased. As the depth increases, the UAV transient electromagnetic detection module is used as the main detection module and the UAV ground-penetrating radar module is used as the secondary detection module. When the initial depth of the target being detected is greater than the third preset value, the UAV ground-penetrating radar module is turned off; Among them, the first preset value < the second preset value < the third preset value.

[0059] The steps and methods involved in the platform of the above embodiment two correspond to those in embodiment one. For specific implementation details, please refer to the relevant description section of embodiment one.

[0060] Example 3 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method for collaborative intelligent detection using unmanned aerial vehicle transient electromagnetic and ground-penetrating radar.

[0061] Example 4 This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the above-described method for collaborative intelligent detection using transient electromagnetic and ground-penetrating radar from an unmanned aerial vehicle.

[0062] Example 5 This embodiment provides a program product, which is a computer program product, including a computer program. When the computer program is executed by a processor, it implements the steps in the above-described method for collaborative intelligent detection of transient electromagnetic signals and ground-penetrating radar by unmanned aerial vehicles.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An unmanned aerial vehicle transient electromagnetic and ground penetrating radar collaborative intelligent detection method, characterized in that, Includes the following steps: Obtain preliminary detection data of the detection area; The initial depth and location of the target are determined based on preliminary detection data of the detection area; Based on the requirements for detection accuracy and depth under the initial depth and position of the target, a collaborative detection allocation scheme for the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module is determined. The relationship between meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module and the corresponding receiving position under the cooperative detection allocation scheme is analyzed to obtain the optimal receiving position; based on the optimal receiving position, the target body in the target area is cooperatively detected to obtain the cooperative detection results, and the imaging results are obtained by three-dimensional joint inversion imaging based on the cooperative detection results. The analysis of the meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module under the collaborative detection allocation scheme, and the corresponding receiving location, to obtain the optimal receiving location, includes: The meteorological data and collection location data acquired by the corresponding UAV detection module are used as input features, and the optimal receiving location is used as the target variable to train the machine learning model. The loss function of the machine learning model is minimized, and the optimal receiving location information is output. 2.The unmanned aerial vehicle transient electromagnetic and ground penetrating radar collaborative intelligent detection method of claim 1, wherein, The method for determining the collaborative detection allocation scheme between the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module, based on the requirements for detection accuracy and depth under the initial depth and position of the target, includes: When the initial depth of the target is less than the first preset value, the target is determined to be in the shallow layer. At this time, the UAV ground-penetrating radar module is used as the main detection module and the UAV transient electromagnetic detection module is used as the secondary detection module. When the initial depth of the target is greater than the second preset value, it is determined that the target is in a deep layer, and the detection depth is increased. As the depth increases, the UAV transient electromagnetic detection module is used as the main detection module and the UAV ground-penetrating radar module is used as the secondary detection module. When the initial depth of the target being detected is greater than the third preset value, the UAV ground-penetrating radar module is turned off; Among them, the first preset value < the second preset value < the third preset value.

3. The method for intelligent detection using a combination of UAV transient electromagnetic and ground-penetrating radar as described in claim 1, characterized in that, The preliminary detection data for the detection area includes: UAV transient electromagnetic detection data and UAV ground-penetrating radar data; among which, the UAV transient electromagnetic detection data includes the turn-off time of the secondary field, attenuation voltage, apparent resistivity, apparent conductivity, the acquisition location of the UAV transient electromagnetic detection module, and the coil attitude information acquired by the attitude sensor; the UAV ground-penetrating radar data includes reflected wave signals, physical characteristics of the reflected waves collected by the receiving antenna, and the acquisition location of the UAV ground-penetrating radar.

4. The method for intelligent detection using a combination of UAV transient electromagnetic and ground-penetrating radar as described in claim 2, characterized in that, When performing 3D joint inversion based on the collaborative detection results, the results of the main detection module are used as the primary method, while the results of the secondary detection module are used as the secondary method. The results of the secondary detection module are used to supplement and correct the results of the main detection module.

5. The method for intelligent detection using a combination of UAV transient electromagnetic and ground-penetrating radar as described in claim 1, characterized in that, The initial depth and location of the target are determined based on preliminary detection data of the detection area, including: inferring depth by measuring the decay time of the electromagnetic field underground using transient electromagnetic detection, and determining location based on resistivity profiles; and determining depth using ground penetrating radar by measuring the time from transmission to reception of electromagnetic waves. During the measurement process, the movement trajectory and position information of the antenna are recorded, and combined with radar data, the planar position of the target is determined.

6. A collaborative intelligent detection platform combining unmanned aerial vehicle transient electromagnetic and ground-penetrating radar, characterized in that, include: The preliminary exploration data acquisition module is used to acquire preliminary exploration data of the exploration area; The target initial information acquisition module is used to determine the initial depth and position of the target based on the preliminary detection data of the detection area; The collaborative detection scheme determination module is used to determine the collaborative detection allocation scheme between the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module based on the requirements for detection accuracy and depth under the initial depth and position of the detection target. The collaborative detection adjustment module is used to analyze the relationship between meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module under the collaborative detection allocation scheme and the corresponding receiving positions, to obtain the optimal receiving position; the analysis of the relationship between meteorological data acquired by the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module under the collaborative detection allocation scheme and the corresponding receiving positions to obtain the optimal receiving position includes: The meteorological data and collection location data obtained by the corresponding UAV detection module are used as input features, and the optimal receiving location is used as the target variable to train the machine learning model. The loss function of the machine learning model is minimized, and the optimal receiving location information is output. The cooperative detection module, based on the optimal receiving position, performs cooperative detection on the target body in the target area, obtains the cooperative detection results, and performs three-dimensional joint inversion imaging based on the cooperative detection results to obtain the imaging results.

7. The UAV transient electromagnetic and ground-penetrating radar collaborative intelligent detection platform as described in claim 6, characterized in that, Both the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module use ground-based transmission modules and air-based reception modules. The UAV ground-penetrating radar module uses either low-altitude flight reception at a set altitude or fixed-point ground reception.

8. The UAV transient electromagnetic and ground-penetrating radar collaborative intelligent detection platform as described in claim 6, characterized in that, The receiving modules of the UAV transient electromagnetic detection module and the UAV ground-penetrating radar module are mounted on a dedicated UAV. The dedicated UAV includes a hollow frame and a power system. The hollow frame includes multiple arms, and the power system is located at the end of each arm. In the middle of the hollow frame is a coil storage compartment that accommodates a split receiving coil. The power system includes a coaxially distributed rotor shaft, insulated wings, and a double-layer motor. The insulated wings are divided into upper and lower layers, both of which are connected to the rotor shaft. The inner and outer layers of the double-layer motor rotate in opposite directions to eliminate electromagnetic signal interference generated when the internal rotor rotates.

9. The UAV transient electromagnetic and ground-penetrating radar collaborative intelligent detection platform as described in claim 6, characterized in that, The UAV transient electromagnetic detection module includes a first meteorological collection module, a first transmitting module, and a first receiving module; The first meteorological data collection module is used to monitor temperature, humidity, air pressure, wind speed, and wind direction; The first transmitting module includes an electromagnetic transmitter and a transmitting antenna. The transmitter is used to transmit a square wave of a set frequency into the ground, and the transmitting antenna is used to pass a bipolar pulse current to generate a primary magnetic field. The first receiving module includes a receiving coil, a first positioning system, an attitude sensor, and a data acquisition recorder. The receiving coil is used to continuously receive secondary induced magnetic field signals generated by the underground medium. The first positioning system is used to record the location of data points and the acquisition location. The attitude sensor includes at least an integrated three-component tilt sensor, an electronic compass, an altimeter, a thermometer, and a barometer. The data acquisition recorder is used to record and store the secondary induced magnetic field signals received by the receiving coil, the data acquired by the positioning system, and the coil attitude information acquired by the attitude sensor. The UAV ground-penetrating radar module includes a second weather collection module, an antenna, a transmitter, a receiver, and a second positioning system; The second meteorological data collection module is used to monitor temperature, humidity, air pressure, wind speed, and wind direction in real time; The antenna is used to transmit and receive electromagnetic wave signals, and the transmitter is used to generate short pulse electromagnetic pulses, which are transmitted underground through the antenna. The receiver is designed to detect signals reflected back from underground. The second positioning system is used to record the location of data points and the collection location.

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