Transient electromagnetic intelligent detection device and method for dam hidden danger detection

Abstract

The invention relates to a transient electromagnetic intelligent detection device and method for dam hidden danger detection. The intelligent detection device comprises a device body, a control module, a positioning and attitude determining module, a detection module and an environment recognition module. The operation panel plans a route, sets parameters of a sampling interval, and displays data and environment information; the control module is used for executing an operation panel instruction, controlling the device main body to advance and steer, and automatically advancing and collecting detection data according to a measuring line direction and a sampling point interval; the environment identification module is used for collecting and processing environment information and restoring an operation environment; the detection module is used for emitting electromagnetic waves and collecting an induced voltage value of an underground medium within a certain time; and the positioning and attitude determination module feeds back a pitch angle to the control module in real time. According to the invention, all-terrain transient electromagnetic intelligent detection can be realized on dike top and slope operation, data acquisition, data self-inspection, abnormal data retest, data evaluation and data mapping.

Description

Technical Field

[0001] This invention relates to a transient electromagnetic intelligent detection device and method for detecting potential hazards in dams, belonging to the technical field of dam hazard detection. Background Technology

[0002] Flooding is a prominent problem in China, and dikes and reservoir dams are important components of the flood control system. During long-term service, dikes and reservoir dams are prone to hidden dangers such as seepage, cracks, and cavities. If the distribution of these hidden dangers is not identified in time, it may lead to catastrophic consequences such as dike collapse and dam failure.

[0003] Currently, the commonly used non-destructive testing technologies for dams are mainly electrical and electromagnetic methods. Among them, the transient electromagnetic method is widely used in dam hazard detection due to its advantages such as sensitivity to low-resistivity bodies and large detection depth.

[0004] However, traditional large-loop transient electromagnetic instruments have a large operating area and a cumbersome deployment process, making them unsuitable for linear engineering projects such as dams. Small-loop transient electromagnetic instruments are easy to connect and have fewer restrictions on operating conditions, but currently they mainly rely on manual single-point measurements, which is inefficient and makes it difficult to achieve continuous and rapid detection of linear projects. In addition, the dam site environment (such as metal signs on the dam top, street light poles, and overhead power lines) can significantly affect data quality, and existing equipment currently relies on manual on-site recording of environmental interference information, lacking real-time recording and intelligent identification functions for environmental interference information, resulting in large data interpretation errors and insufficient reliability. Summary of the Invention

[0005] To address the aforementioned problems, this invention discloses a transient electromagnetic intelligent detection device and method for detecting potential hazards in dams, the specific technical solution of which is as follows: A transient electromagnetic intelligent detection device for detecting potential hazards in dams includes a main body, and a control module, a positioning and attitude determination module, a detection module, and an environmental recognition module mounted on the main body; the bottom of the main body is provided with a wheel-track composite chassis, which moves the main body forward or backward. The control module is connected to the environment recognition module, detection module, and positioning and attitude determination module via a line, and interacts with the operating tablet via a wireless network to exchange control commands. The operating tablet plans the route, sets the parameters for the sampling interval, and displays data and environmental information; the control module is used to execute the operating tablet commands, control the main body of the device to move forward and turn, and automatically move and collect detection data according to the survey line orientation and sampling point spacing. By controlling the coil attitude angle, the coil attitude is kept horizontal when working on the top of the dam and the coil attitude is kept at the same elevation angle when working on the slope of the dam. The environmental identification module is used to collect and process environmental information to reconstruct the working environment; The detection module is used to emit electromagnetic waves and collect the induced voltage value of the underground medium over a certain period of time. The positioning and attitude determination module is interconnected with the detection module, and provides real-time feedback of the pitch angle to the control module.

[0006] Furthermore, the wheel-track composite chassis includes four omnidirectional wheels in two rows on both sides of the forward direction and four independent lifting tracks. The lifting tracks can be lowered below the omnidirectional wheels to directly contact the ground, or raised above the omnidirectional wheels so that the omnidirectional wheels contact the ground.

[0007] Furthermore, the environmental recognition module includes a 3D laser scanner, a visible light high-definition camera, and a thermal infrared camera; The visible light high-definition camera and the thermal infrared camera scan the working area and use deep learning algorithms to identify common interference objects; The 3D laser scanner performs 3D environment modeling, merges it with visual data to generate a map, and locates the absolute coordinates of the interfering objects.

[0008] Furthermore, the detection module uses a transient electromagnetic instrument, including a transient electromagnetic instrument receiver, a transmitter, and a transceiver coil. The coil is connected to an active suspension and four casters, and is connected to the main body of the device through non-metallic rods. The active suspension adjusts the coil attitude angle by adjusting the suspension height to ensure that it is consistent with the pitch angle set by the measuring line; The positioning and attitude determination module provides feedback and adjustment, and receives the pitch angle of the coil.

[0009] Furthermore, the positioning and attitude determination module includes an RTK positioning system, a gyroscope, and an encoder. The RTK positioning system and gyroscope are installed at the center of the coil to provide real-time feedback on the coil position and attitude angle. The encoder is fixed on the omnidirectional wheel and calculates the vehicle's travel distance by reading the number of rotations of the omnidirectional wheel. This is used to supplement positioning when the RTK signal is poor and to complement the RTK system for positioning.

[0010] The detection method based on the above-mentioned transient electromagnetic intelligent detection device for dam hazard detection includes the following steps: Step S1, Operation Preparation: Before operation, the intelligent detection device performs a system self-check. The connection status of the environmental recognition module, detection module, and positioning and attitude determination module is debugged by operating the tablet to prepare for operation. Step S2, Mode Selection: When detecting a smooth road surface on the top of the embankment, select the top of the embankment detection mode through the operating tablet, and keep the coil attitude angle horizontal at all times; when detecting the embankment slope, place the coil at the starting point of the slope detection, select the embankment slope detection mode, and make appropriate fine adjustments to the current elevation angle and fix the coil attitude angle according to the relationship between the current elevation angle fed back by the coil gyroscope and the slope of the embankment. Step S3, Engineering Settings: Set the detection area parameters, such as detection area, measurement line spacing, measurement point spacing, and measurement line direction; set the detection parameters, such as coil turns, coil diameter, start and end time, and sampling frequency. Step S4, Operation Start: The intelligent detection device starts to collect RTK coordinate data and automatically starts and stops detection according to the measurement area parameters. The environment recognition module simultaneously performs 3D environment modeling and identifies surrounding interference. The positioning and attitude determination module actively suspends the four universal wheels through the gyroscope angle back control coil to achieve attitude stability during operation. Step S5, Data Self-Check: The control module reads the voltage-time curve value of the measuring point, performs a self-check on the current induced voltage value of the measuring point, and automatically re-measures the measuring points with abnormal values. Step S6, Data Retest: The intelligent detection device is moved to a distance of 0.5 meters around the abnormal measurement point to retest the data. The retest point is located on one side of the measurement line. After the retest data is checked and found to be normal, the next measurement point can be tested. If there is still an abnormality after the retest, the intelligent device is moved to the other side to retest for the second time. If there is an abnormality in both tests, it is recorded as a numerical singularity. Step S7, Data Evaluation: Generate an automatic evaluation of the data based on the percentage of numerical singularities (SPR). Step S8, Data Mapping: Plot apparent resistivity profiles for data with excellent or good evaluation results, and mark the interference information identified by the environment at nearby measurement points to provide support for the analysis of the detection results.

[0011] Furthermore, at the start of step S5, the route and measurement point spacing are set via a tablet computer. The detection module emits electromagnetic waves into the ground at each measurement point and measures the induced voltage value over a certain period of time. Abnormal conditions for the induced voltage value are as follows: Spatial anomaly: , Relative voltage difference rate This represents the current peak voltage at the measuring point. The average of the peak voltage values ​​at five adjacent measuring points; Time anomaly: , The measured attenuation slope is characterized by the measured induced voltage-attenuation time curve. This represents the theoretical attenuation slope. A voltage anomaly is determined if either a spatial anomaly or a temporal anomaly condition is met.

[0012] Furthermore, the numerical range and significance of the percentage of numerical singularities (SPR) in step S6 are as follows: , The number of measurement points for numerical singularities. This represents the total number of measurement points. The evaluation conclusion is excellent, the data consistency is high, no manual intervention is required, and it can be directly used for subsequent analysis; The evaluation conclusion is good, and the data is basically reliable. However, manual spot checks are needed to retest the test points to see if there are still any abnormalities. The evaluation conclusion was unqualified, the data quality was questionable, and the data collection process needed to be fully reviewed and the layout of the measurement points needed to be replanned.

[0013] The beneficial effects of this invention are: This invention utilizes a wheeled-tracked hybrid mobile robot as its core, integrating measurement point start / stop and data acquisition through an onboard automated system, significantly improving operational efficiency. It also integrates an environmental recognition module combining a 3D laser scanner, a visible light high-definition camera, and a thermal infrared camera to identify and record surrounding interference sources (such as metal signs and streetlights) in real time. Furthermore, it proposes a transient electromagnetic intelligent detection method and retesting indicators, enabling automatic retesting of abnormal data and real-time data quality evaluation. This invention provides an innovative solution for the rapid and accurate detection of potential hazards in dams. Attached Figure Description

[0014] Figure 1 This is a side view of the device of the present invention. Figure 2 This is a front view of the device of the present invention. List of reference numerals in the attached figures: 1—Main body of the device, 2—3D laser scanner, 3—Visible light high-definition camera, 4—Universal wheel, 5—Independent lifting track, 6—Non-metallic tow bar, 7—Universal wheel with encoder, 8—Transient electromagnetic coil, 9—RTK positioning system, 10—Gyroscope, 11—Thermal infrared camera. Detailed Implementation

[0015] The present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0016] Combined with appendix Figure 1-2 As can be seen, the device of the present invention includes: device body 1, three-dimensional laser scanner 2, visible light high-definition camera 3, universal wheel 4, independent lifting track 5, non-metallic tow bar 6, universal wheel with encoder 7, transient electromagnetic coil 8, RTK positioning system 9, gyroscope 10, and thermal infrared camera 11.

[0017] The present invention relates to a transient electromagnetic intelligent detection device for potential hazards in dikes, comprising a wheeled and tracked composite mobile robot body, a control module, a positioning and attitude determination module, a detection module, and an environmental recognition module.

[0018] The intelligent detection device includes a wheel-tracked hybrid mobile robot chassis, powered by its own battery. Considering the undulating terrain of some embankments, the robot chassis is a modified off-road chassis. The robot is equipped with a wheel-tracked hybrid walking system, including four omnidirectional wheels 4 and four independently lifting tracks 5. When working on the smooth surface at the top of the embankment, it uses the omnidirectional wheels for movement, and when working on the slopes on both sides of the embankment, it lowers the tracks for movement.

[0019] The intelligent detection device also includes a control module, which can plan the detection route, control the vehicle's forward movement and steering, set the sampling point spacing, display collected data and environmental information, and control the coil's attitude angle to ensure that the coil remains horizontal when working on the top of the dam and maintains the same elevation angle when working on the dam slope. The control module is connected to the environment recognition module, detection module, and positioning and attitude determination module via wiring, and interacts with the operating tablet via a wireless network to exchange control commands.

[0020] The environmental recognition module includes a 3D laser scanner 2, a visible light high-definition camera 3, and a thermal infrared camera 11. It scans the work area using visible light and infrared lenses, uses deep learning algorithms to identify common interference objects, uses the 3D laser scanner to perform 3D environmental modeling, and fuses it with visual data to generate a high-precision map, locating the absolute coordinates of interference objects such as metal signs and street light poles.

[0021] The detection module consists of a coil, a transmitter, and a receiver, with the transmitter and receiver integrated into the vehicle body. The coil is connected to four omnidirectional wheels and an active suspension, allowing the coil's pitch angle to be adjusted according to the terrain. The coil is towed to the rear of the vehicle body via a non-metallic tow bar 6, making contact with the road surface.

[0022] The positioning and attitude determination module includes an RTK positioning system, a gyroscope, and an encoder. The RTK positioning system 9 and the gyroscope 10 are installed at the center of the transient electromagnetic coil 8, which can provide real-time feedback on the position and attitude angle of the transient electromagnetic coil 8. The encoder is fixed on the universal wheel 7 with an encoder and is used for complementary positioning with the RTK system.

[0023] The detection method of the transient electromagnetic intelligent detection device for detecting hidden dangers in dams according to the present invention includes the following steps: Step S1, Operation Preparation: Before operation, the intelligent detection device performs a system self-check. The connection status of the environmental recognition module, detection module, and positioning and attitude determination module is debugged by operating the tablet to prepare for operation. Step S2, Mode Selection: When detecting a smooth road surface on the top of the embankment, select the top of the embankment detection mode through the operating tablet, and keep the coil attitude angle horizontal at all times; when detecting the embankment slope, place the coil at the starting point of the slope detection, select the embankment slope detection mode, and make appropriate fine adjustments to the current elevation angle and fix the coil attitude angle according to the relationship between the current elevation angle fed back by the coil gyroscope and the slope of the embankment. Step S3, Engineering Settings: Set the detection area parameters, such as detection area, measurement line spacing, measurement point spacing, and measurement line direction; set the detection parameters, such as coil turns, coil diameter, start and end time, and sampling frequency. Step S4, Operation Start: The intelligent detection device starts to collect RTK coordinate data and automatically starts and stops detection according to the measurement area parameters. The environment recognition module simultaneously performs 3D environment modeling and identifies surrounding interference. The positioning and attitude determination module actively suspends the four universal wheels through the gyroscope angle back control coil to achieve attitude stability during operation. Step S5, Data Self-Check: The control module reads the voltage-time curve value of the measuring point, performs a self-check on the current induced voltage value of the measuring point, and automatically re-measures the measuring points with abnormal values. At the start of the mission, the route and measurement point spacing are set via a tablet computer. The detection module emits electromagnetic waves into the ground at each measurement point and measures the induced voltage value over a certain period of time. Abnormal induced voltage values ​​are defined as follows: Spatial anomaly: Inter-space anomaly: , Relative voltage difference rate This represents the current peak voltage at the measuring point. The average of the peak voltage values ​​at five adjacent measuring points; Time anomaly: , The measured attenuation slope is characterized by the measured induced voltage-attenuation time curve. This is the theoretical attenuation slope (generally -2.0 to -1.5, estimated based on the site voltage background value). A voltage anomaly is determined if either a spatial anomaly or a temporal anomaly condition is met.

[0024] Step S6, Data Retest: The intelligent detection device is moved to a distance of 0.5 meters around the abnormal measurement point to retest the data. The retest point is located on one side of the measurement line. After the retest data is checked and found to be normal, the next measurement point can be tested. If there is still an abnormality after the retest, the intelligent device is moved to the other side to retest for the second time. If there is an abnormality in both tests, it is recorded as a numerical singularity. Step S7, Data Evaluation: Generate an automatic evaluation of the data based on the percentage of numerical singularities (SPR). , The number of measurement points for numerical singularities. This represents the total number of measurement points. The evaluation conclusion is excellent, the data consistency is high, no manual intervention is required, and it can be directly used for subsequent analysis; The evaluation conclusion is good, and the data is basically reliable. However, manual spot checks are needed to retest the test points to see if there are still any abnormalities. The evaluation conclusion was unqualified, the data quality was questionable, and the data collection process needed to be fully reviewed and the layout of the measurement points needed to be replanned.

[0025] Step S8, Data Mapping: Plot apparent resistivity profiles for data with excellent or good evaluation results, and mark the interference information identified by the environment at nearby measurement points to provide support for the analysis of the detection results.

[0026] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0027] The meaning of "and / or" as used in this application includes situations where each exists alone or both exist simultaneously.

[0028] The term "connection" as used in this application can mean a direct connection between components or an indirect connection between components through other components.

[0029] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A transient electromagnetic intelligent detection device for detecting potential hazards in dams, characterized in that, It includes a main body of the device, as well as a control module, a positioning and attitude determination module, a detection module and an environmental recognition module mounted on the main body of the device; the bottom of the main body of the device is provided with a wheel-track composite chassis, which carries the main body of the device to move forward or backward; The control module is connected to the environment recognition module, detection module, and positioning and attitude determination module via a line, and interacts with the operating tablet via a wireless network to exchange control commands. The operating tablet plans routes, sets parameters for sampling intervals, and displays data and environmental information; The control module is used to execute the operation tablet commands, control the main body of the device to move forward and turn, automatically move and collect detection data according to the survey line orientation and sampling point spacing, and control the coil attitude angle to ensure that the coil attitude is always horizontal when working on the top of the dam and always at the same elevation angle when working on the slope of the dam. The environmental identification module is used to collect and process environmental information to reconstruct the working environment; The detection module is used to emit electromagnetic waves and collect the induced voltage value of the underground medium over a certain period of time. The positioning and attitude determination module is interconnected with the detection module, and provides real-time feedback of the pitch angle to the control module.

2. The transient electromagnetic intelligent detection device for detecting hidden dangers in dams according to claim 1, characterized in that, The wheel-track composite chassis includes four omnidirectional wheels in two rows on both sides of the forward direction and four independent lifting tracks. The lifting tracks can be lowered below the omnidirectional wheels to directly contact the ground, or raised above the omnidirectional wheels to contact the ground.

3. The transient electromagnetic intelligent detection device for detecting hidden dangers in dams according to claim 1, characterized in that, The environmental recognition module includes a 3D laser scanner, a visible light high-definition camera, and a thermal infrared camera. The visible light high-definition camera and the thermal infrared camera scan the working area and use deep learning algorithms to identify common interference objects; The 3D laser scanner performs 3D environment modeling, merges it with visual data to generate a map, and locates the absolute coordinates of the interfering objects.

4. The transient electromagnetic intelligent detection device for detecting hidden dangers in dams according to claim 2, characterized in that, The detection module uses a transient electromagnetic instrument, which includes a transient electromagnetic instrument receiver, a transmitter, and a coil. The coil is connected to an active suspension and four casters, and is connected to the main body of the device through non-metallic rods. The active suspension adjusts the coil attitude angle by adjusting the suspension height to ensure that it is consistent with the pitch angle set by the measuring line; The positioning and attitude determination module provides feedback and adjustment, and receives the pitch angle of the coil.

5. The transient electromagnetic intelligent detection device for detecting hidden dangers in dams according to claim 4, characterized in that, The positioning and attitude determination module includes an RTK positioning system, a gyroscope, and an encoder. The RTK positioning system and gyroscope are installed at the center of the coil to provide real-time feedback on the coil's position and attitude angle. The encoder is fixed to the omnidirectional wheel and calculates the vehicle's travel distance by reading the number of rotations of the omnidirectional wheel. This is used to supplement positioning when the RTK signal is poor and to complement the RTK system for positioning.

6. A detection method based on the transient electromagnetic intelligent detection device for dam hazard detection as described in any one of claims 1-5, characterized in that, Includes the following steps: Step S1, Operation Preparation: Before operation, the intelligent detection device performs a system self-check. The connection status of the environmental recognition module, detection module, and positioning and attitude determination module is debugged by operating the tablet to prepare for operation. Step S2, Mode Selection: When detecting a smooth road surface on the top of the embankment, select the top of the embankment detection mode through the operating tablet, and keep the coil attitude angle horizontal at all times; when detecting the embankment slope, place the coil at the starting point of the slope detection, select the embankment slope detection mode, and make appropriate fine adjustments to the current elevation angle and fix the coil attitude angle according to the relationship between the current elevation angle fed back by the coil gyroscope and the slope of the embankment. Step S3, Engineering Settings: Set the detection area parameters, such as detection area, measurement line spacing, measurement point spacing, and measurement line direction; set the detection parameters, such as coil turns, coil diameter, start and end time, and sampling frequency. Step S4, Operation Start: The intelligent detection device starts to collect RTK coordinate data and automatically starts and stops detection according to the measurement area parameters. The environment recognition module simultaneously performs 3D environment modeling and identifies surrounding interference. The positioning and attitude determination module actively suspends the four universal wheels through the gyroscope angle back control coil to achieve attitude stability during operation. Step S5, Data Self-Check: The control module reads the voltage-time curve value of the measuring point, performs a self-check on the current induced voltage value of the measuring point, and automatically re-measures the measuring points with abnormal values. Step S6, Data Retest: The intelligent detection device is moved to a distance of 0.5 meters around the abnormal measurement point to retest the data. The retest point is located on one side of the measurement line. After the retest data is checked and found to be normal, the next measurement point can be tested. If there is still an abnormality after the retest, the intelligent device is moved to the other side to retest for the second time. If there is an abnormality in both tests, it is recorded as a numerical singularity. Step S7, Data Evaluation: The data is automatically evaluated and generated based on the percentage of numerical singularities (SPR). Step S8, Data Mapping: Plot apparent resistivity profiles for data with excellent or good evaluation results, and mark the interference information identified by the environment at nearby measurement points to provide support for the analysis of the detection results.

7. The transient electromagnetic intelligent detection method for detecting hidden dangers in dams according to claim 6, characterized in that, At the start of step S5, the route and measurement point spacing are set via a tablet computer. The detection module emits electromagnetic waves into the ground at each measurement point and measures the induced voltage value over a certain period. An abnormal induced voltage value is defined as: spatial anomaly. , Relative voltage difference rate This represents the current peak voltage at the measuring point. The average of the peak voltage values ​​at five adjacent measuring points; Time anomaly: , The measured attenuation slope is characterized by the measured induced voltage-attenuation time curve. This represents the theoretical attenuation slope. A voltage anomaly is determined if either a spatial anomaly or a temporal anomaly condition is met.

8. The transient electromagnetic intelligent detection method for detecting hidden dangers in dams according to claim 6, characterized in that, The numerical range and significance of the percentage of singular points (SPR) in step S6 are as follows: , The number of measurement points for numerical singularities. This represents the total number of measurement points. The evaluation conclusion is excellent, the data consistency is high, no manual intervention is required, and it can be directly used for subsequent analysis; The evaluation conclusion is good, and the data is basically reliable. However, manual spot checks are needed to retest the test points to see if there are still any abnormalities. The evaluation conclusion was unqualified, the data quality was questionable, and the data collection process needed to be fully reviewed and the layout of the measurement points needed to be replanned.

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