Multi-band transient electromagnetic self-adaptive scanning dam leakage channel three-dimensional imaging method

Abstract

The invention discloses a multi-band transient electromagnetic self-adaptive scanning dam leakage channel three-dimensional imaging method. The method comprises the following steps: arranging a plurality of detection nodes on the surface of a dam; the central control unit sends a scanning instruction to the detection node; the detection node scans the dam and uploads the data to the central control unit; and after the data is uploaded, the central control unit calculates an underground three-dimensional resistivity data volume through an inversion algorithm and performs rendering imaging. According to the invention, through combination of multi-band detection and intelligent adaptive scanning, efficient and accurate dam leakage channel three-dimensional visual identification is realized, and the defects of low efficiency, single detection dimension and rigid scanning strategy of a traditional method are effectively overcome.

Description

Technical Field

[0001] This invention relates to the field of dam safety monitoring technology, specifically a three-dimensional imaging method for dam seepage channels using multi-band transient electromagnetic adaptive scanning. Background Technology

[0002] The safe operation of dam projects is of paramount importance. The early detection and accurate location of potential leakage hazards are core issues in the field of engineering safety. Geophysical exploration methods are widely used in dam leakage detection due to their non-destructive and efficient characteristics. Among them, the Transient Electromagnetic Method (TEM) is sensitive to low resistivity bodies. Since the resistivity of water-bearing leakage channels is usually much lower than that of the surrounding dense dam body, TEM technology is theoretically very suitable for leakage detection.

[0003] However, existing TEM-based detection technologies still have many limitations in practical applications, mainly in the following aspects:

[0004] First, existing technologies mostly adopt single-point mobile measurement, that is, after completing the data collection of one measurement point, the manual equipment is moved to the next measurement point. This method of operation is extremely inefficient, time-consuming and labor-intensive for dams that require large-area scanning. In addition, the human interference factors in the measurement point location and measurement parameters are large, making it difficult to ensure the consistency of data.

[0005] Second, traditional TEM interpretation is often based on one-dimensional models or two-dimensional profiles, which cannot accurately depict the complex three-dimensional spatial distribution characteristics of leakage channels (such as direction, burial depth, and morphology). This brings difficulties to the precise treatment of engineering, and the interpretation results have multiple solutions and the reliability needs to be improved.

[0006] Third, the detection depth and resolution of transient electromagnetic methods are limited by the transmission frequency. Using a single fixed frequency for measurement has inherent defects (high frequency transmission has fast attenuation, high resolution for shallow parts but limited detection depth; low frequency transmission has a large detection depth but low resolution for shallow parts). Therefore, existing technical solutions cannot effectively meet the needs of comprehensive and multi-scale detection of dams from shallow to deep parts in the same detection process.

[0007] Fourth, existing systems typically use pre-set, fixed scanning parameters (such as transmission power and frequency) to complete all measurements, which is a "blind test" mode. It cannot dynamically adjust the scanning strategy based on real-time data feedback, resulting in a lot of wasted time and energy in the background area, while in suspected abnormal areas, it may miss or misjudge due to insufficient data collection.

[0008] In summary, there is an urgent need in this field for a method that can overcome the above-mentioned shortcomings and achieve efficient, accurate, intelligent, and low-power three-dimensional imaging of dam seepage channels. Summary of the Invention

[0009] The purpose of this invention is to provide a three-dimensional imaging method for dam seepage channels using multi-band transient electromagnetic adaptive scanning, in order to solve the following problems existing in the practical use of existing dam seepage channel imaging methods: First, the detection mode is inefficient and it is difficult to achieve rapid surveys; second, the detection dimension is insufficient and it is difficult to truly reflect the three-dimensional spatial morphology; in addition, it is difficult to balance detection depth and resolution; and finally, the scanning strategy is rigid.

[0010] To achieve the above objectives, the three-dimensional imaging method for dam seepage channels using multi-band transient electromagnetic adaptive scanning includes the following steps:

[0011] S1. Several detection nodes are set up on the surface of the dam according to a preset pattern;

[0012] S2. The central control unit sends a scanning command to the detection node, wherein the scanning command includes at least the transmission frequency parameter;

[0013] S3. The detection node, according to the scanning command, sends a primary transient electromagnetic pulse of a specified frequency into the underground of the dam, and during the interval between the primary pulses, it collects secondary field attenuation data generated by the attenuation of underground eddy currents.

[0014] S4. The detection node sends the secondary field attenuation data to the central control unit;

[0015] S5. Based on all the received secondary field attenuation data, the central control unit calculates the three-dimensional resistivity data volume of the underground space of the dam through an inversion algorithm. The three-dimensional resistivity data volume is composed of the resistivity values ​​of several voxels.

[0016] S6. The central control unit renders the three-dimensional resistivity data volume to generate and display a three-dimensional image of the dam seepage channel.

[0017] In step S2, the transmission frequency parameter of the scanning command is a multi-band combination parameter, and the command at least one detection node sequentially transmits at least two different fundamental frequencies of transient electromagnetic pulses.

[0018] The central control unit executes an adaptive scanning process: based on the preliminary inversion results or a preset scanning strategy, it dynamically adjusts the scanning parameters of one or more detection nodes, including at least one of the following: transmission power, transmission frequency combination, and data acquisition time length.

[0019] Furthermore, in step S2, the specific process of the central control unit performing adaptive scanning includes:

[0020] Based on the three-dimensional resistivity data obtained from the preliminary inversion, suspected leakage anomaly areas with resistivity below a preset threshold were identified.

[0021] An adaptive scanning command is generated to adjust the scanning parameters of the detection nodes located in the suspected leakage anomaly area and its surrounding area to perform encrypted or enhanced scanning of the area.

[0022] Furthermore, the adaptive scanning process in step S2 also includes a cascaded trigger scanning mode:

[0023] The central control unit first instructs the first group of detection nodes (one node is activated every other detection node) to start and perform a preliminary scan;

[0024] The central control unit analyzes the secondary field attenuation data uploaded by the first group of detection nodes in real time or near real time.

[0025] When the analysis determines that the data of a certain first group of detection nodes is abnormal, the central control unit automatically instructs the second group of detection nodes (the remaining detection nodes around the abnormal detection node) that were originally in standby or dormant state to start up and perform encrypted scanning on the abnormal area.

[0026] Furthermore, the basis for judging the abnormality of the analysis data is: comparing the amplitude, attenuation rate or converted apparent resistivity value of the received secondary field attenuation curve with the background value or theoretical value. If it exceeds the preset abnormality threshold, it is determined that there is an abnormality.

[0027] Furthermore, in step S3, the detection node uses the same set of transmitting coils and receiving coils to transmit pulses of different base frequencies in a time-division manner and collect data.

[0028] Furthermore, the inversion algorithm in step S5 is a least squares optimization algorithm based on regularization constraints, which inverts the secondary field attenuation data in the spatiotemporal domain into the resistivity distribution of the underground three-dimensional space by solving the electromagnetic inverse problem.

[0029] Furthermore, in step S6, rendering the three-dimensional resistivity data volume means: setting a resistivity threshold and using an isosurface extraction method to generate a three-dimensional morphological model of a low-resistivity anomaly below the resistivity threshold, wherein the low-resistivity anomaly represents a leakage channel or a saturated area.

[0030] Furthermore, in step S1, the detection nodes are uniformly distributed on the surface of the dam in a grid or linear array pattern.

[0031] Furthermore, a three-dimensional imaging system for implementing the method of any one of claims 1-8 for dam seepage channels includes:

[0032] Central control unit;

[0033] Several detection nodes are deployed on the surface of the dam, and the detection nodes are communicatively connected to the central control unit;

[0034] The detection node includes a transient electromagnetic instrument, a transmitting coil, a receiving coil, and a node controller;

[0035] The central control unit includes:

[0036] The communication module is used for data interaction with each detection node;

[0037] The control module is used to generate the scanning instructions and adaptive scanning instructions;

[0038] The data processing module is used to run the inversion algorithm to generate a three-dimensional resistivity data volume;

[0039] The visualization module is used to render and display the three-dimensional resistivity data volume;

[0040] The node controller is configured to receive instructions from the control module and control the transient electromagnetic instrument, the transmitting coil, and the receiving coil to perform the operations of steps S3 and S4.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] First, this invention achieves multi-point synchronous or asynchronous data acquisition through a fixed detection node array, which greatly improves data acquisition efficiency. At the same time, it introduces a two-level adaptive scanning mechanism (adaptive adjustment based on inversion results and cascade triggering based on real-time data), which avoids unnecessary energy consumption and time waste, and realizes a leap from "blind testing" to "precise testing and efficient testing".

[0043] Secondly, this invention employs multi-band combined detection, utilizing high frequency to acquire shallow fine structures and low frequency to detect deep hidden dangers, achieving "one machine for multiple uses." Simultaneously, through joint inversion of multi-point data in three-dimensional space, a three-dimensional resistivity data volume is directly generated. Then, through three-dimensional visualization technology, the three-dimensional morphology, spatial orientation, and burial depth of the leakage channel are clearly and intuitively restored, greatly improving the accuracy and reliability of the detection results and reducing the risk of misjudgment.

[0044] Furthermore, once the detection nodes of this invention are deployed, they can be remotely controlled by the central control unit for automated operation. In particular, the cascaded trigger scanning mode requires only some detection nodes to work during normal monitoring, which greatly reduces the overall power consumption of the system. Once an anomaly is detected, the surrounding nodes are awakened, realizing "on-demand scanning". This is very suitable for long-term, unattended automated safety monitoring and reduces the operation and maintenance costs throughout the entire life cycle. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the overall flowchart of the present invention.

[0046] Figure 2 This is a schematic diagram of the process of adaptive adjustment based on the inversion results of the present invention.

[0047] Figure 3 This is a flowchart illustrating the cascaded trigger scanning mode of the present invention.

[0048] Figure 4 This is a schematic diagram showing the distribution of the detection nodes of the present invention on the dam.

[0049] In the picture:

[0050] 1-Dike, 2-Detection node. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] As attached Figure 1-4 As shown:

[0053] The present invention provides a three-dimensional imaging method for dam seepage channels using multi-band transient electromagnetic adaptive scanning, the method comprising the following steps:

[0054] S1, Deployment of Detection Node 2:

[0055] Based on the scale of dam 1 and the key monitoring areas, detection nodes 2 are evenly distributed on the surface of dam 1 in a rectangular grid (e.g., 5m×5m). Each node is precisely located using GPS or Beidou module, and its coordinate information (X, Y, Z) is registered to the central control unit.

[0056] S2. Issue scan command and adaptive scan:

[0057] The control module of the central control unit generates an initial scan command, which includes multi-band combination parameters, requiring each detection node 2 to sequentially emit at least two different fundamental frequencies (such as 25kHz, 5kHz, and 500Hz) transient electromagnetic pulses.

[0058] The adaptive scanning process is implemented in two modes (adaptive adjustment based on inversion results and cascaded trigger scanning mode);

[0059] Adaptive adjustment based on inversion results:

[0060] The data processing module performs rapid three-dimensional inversion on the data obtained from the survey scan to obtain a preliminary resistivity model. The control module analyzes the model and identifies areas with resistivity values ​​below 10 Ω·m as suspected leakage anomaly areas. Subsequently, the control module generates adaptive commands, instructing detection nodes 2 located in these anomaly areas and within a 5-meter radius around them to increase the transmission power of the 500Hz frequency to full power (e.g., 250W) and extend the sampling time of this frequency from 2ms to 10ms to obtain higher quality deep data, thereby achieving "enhanced scanning" of suspicious areas.

[0061] Cascaded trigger scan mode:

[0062] In another operating mode, to save energy, the control module first instructs the first group of detection nodes (e.g., starting one every other detection node) to perform a preliminary scan; after the communication module receives the secondary field attenuation data uploaded by these nodes, the real-time analysis submodule within the control module immediately processes the data.

[0063] The basis for judging anomalies is: calculate the amplitude of the early trace (e.g., 0.1ms) or the converted apparent resistivity. If it is lower than 50% of the background value (the empirical value of the apparent resistivity of the normal dam body in this area, e.g., 20Ω·m), it is judged that there is an anomaly.

[0064] Once a detection node is identified as abnormal, the control module immediately sends a start command to the second group of detection nodes (i.e., the remaining dormant detection nodes around the abnormal detection node) through the communication module, instructing them to join the scan and form a denser detection network to perform "encrypted scanning" of the abnormal area.

[0065] S3. Transmitted Pulse and Acquired Data:

[0066] After receiving the instruction, the node controller of detection node 2 controls the transmitter of the transient electromagnetic instrument to send a current pulse (primary field) of a specific frequency and power to the transmitting coil. After the pulse ends, the switch is immediately switched to connect the same coil to the receiver, and the entire curve of the secondary field induced voltage decaying over time (attenuation curve) is accurately collected during the interval.

[0067] S4, Data Transmission:

[0068] The node controller packages the collected attenuation curve data, corresponding GPS timestamps, node IDs, transmission parameters, etc., and sends them back to the communication module of the central control unit through the communication network.

[0069] S5. Three-dimensional inversion calculation:

[0070] After the data processing module of the central control unit collects all the data, it adopts a least squares optimization algorithm based on regularization constraints. This algorithm discretizes the entire underground space of the dam into thousands of voxels. By iteratively adjusting the resistivity value of each voxel, the error between the electromagnetic response calculated by forward modeling and the measured attenuation curve is minimized. Finally, a three-dimensional data volume (X, Y, Z, Resistivity) containing the spatial location and resistivity value of each voxel is output.

[0071] S6. 3D Rendering and Display:

[0072] The visualization module reads the three-dimensional resistivity data volume. The operator sets a resistivity threshold (e.g., 8 Ω·m), and the module uses an isosurface extraction algorithm (such as the Marching Cubes algorithm) to automatically generate a three-dimensional surface model composed of all voxels with resistivity below the threshold. This model is the inferred leakage channel or saturated area. Through coloring (e.g., using red to represent the lowest resistance and blue to represent the relatively high resistance) and operations such as rotation and cutting, the spatial distribution, burial depth, and direction of the leakage channel can be intuitively viewed on the display interface, providing accurate guidance for engineering risk mitigation.

[0073] A three-dimensional imaging system for implementing the method of any one of claims 1-8, comprising:

[0074] Central control unit;

[0075] Several detection nodes 2 are deployed on the surface of the dam 1, and the detection nodes 2 are communicatively connected to the central control unit;

[0076] The detection node 2 includes a transient electromagnetic instrument, a transmitting coil, a receiving coil, and a node controller;

[0077] The central control unit includes:

[0078] The communication module is used for data interaction with each detection node 2;

[0079] The control module is used to generate the scanning instructions and adaptive scanning instructions;

[0080] The data processing module is used to run the inversion algorithm to generate a three-dimensional resistivity data volume;

[0081] The visualization module is used to render and display the three-dimensional resistivity data volume;

[0082] The node controller is configured to receive instructions from the control module and control the transient electromagnetic instrument, the transmitting coil, and the receiving coil to perform the operations of steps S3 and S4.

[0083] In summary, this multi-band transient electromagnetic adaptive scanning method for three-dimensional imaging of dam seepage channels addresses the following problems in practical applications of existing dam seepage channel imaging methods: First, the detection mode is inefficient, making rapid surveys difficult; second, the detection dimensions are insufficient, making it difficult to accurately reflect the three-dimensional spatial morphology; furthermore, it is difficult to balance detection depth and resolution; and finally, the scanning strategy is rigid.

[0084] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A three-dimensional imaging method for dam seepage channels using multi-band transient electromagnetic adaptive scanning, characterized in that, The method includes the following steps: S1. Several detection nodes (2) are set up on the surface of the dam (1) according to a preset pattern; S2. The central control unit sends a scanning command to the detection node (2), wherein the scanning command includes at least the transmission frequency parameter; S3. The detection node (2) transmits a primary field transient electromagnetic pulse of a specified frequency to the underground of the dam (1) according to the scanning command, and collects secondary field attenuation data generated by the attenuation of underground eddy currents during the interval between the primary field pulses. S4. The detection node (2) sends the secondary field attenuation data to the central control unit; S5. The central control unit calculates the three-dimensional resistivity data volume of the underground space of the dam (1) based on all the received secondary field attenuation data through an inversion algorithm. The three-dimensional resistivity data volume is composed of the resistivity values ​​of several voxels. S6. The central control unit renders the three-dimensional resistivity data volume to generate and display a three-dimensional image of the seepage channel of the dam (1). In step S2, the transmission frequency parameter of the scanning command is a multi-band combination parameter, and the command at least one detection node (2) sequentially transmits at least two different fundamental frequencies of transient electromagnetic pulses. The central control unit performs an adaptive scanning process: based on the preliminary inversion results or a preset scanning strategy, it dynamically adjusts the scanning parameters of one or more detection nodes (2), the scanning parameters including at least one of the following: transmission power, transmission frequency combination, and data acquisition time length.

2. The method according to claim 1, characterized in that, In step S2, the specific process of the central control unit performing adaptive scanning includes: Based on the three-dimensional resistivity data obtained from the preliminary inversion, suspected leakage anomaly areas with resistivity below a preset threshold were identified. An adaptive scanning command is generated to adjust the scanning parameters of the detection nodes (2) located in the suspected leakage abnormal area and its surrounding area to perform encrypted or enhanced scanning of the area.

3. The method according to claim 1, characterized in that, The adaptive scanning process in step S2 also includes a cascaded trigger scanning mode: The central control unit first instructs the first group of detection nodes (one node is activated every other detection node) to start and perform a preliminary scan; The central control unit analyzes the secondary field attenuation data uploaded by the first group of detection nodes in real time or near real time. When the analysis determines that the data of a certain first group of detection nodes is abnormal, the central control unit automatically instructs the second group of detection nodes (the remaining detection nodes around the abnormal detection node) that were originally in standby or dormant state to start up and perform encrypted scanning on the abnormal area.

4. The method according to claim 3, characterized in that, The basis for judging whether the data is abnormal is to compare the amplitude, attenuation rate or the converted apparent resistivity value of the received secondary field attenuation curve with the background value or theoretical value. If it exceeds the preset abnormal threshold, it is determined that there is an abnormality.

5. The method according to claim 1, characterized in that, In step S3, the detection node (2) uses the same set of transmitting coils and receiving coils to transmit pulses of different base frequencies and collect data in a time-division manner.

6. The method according to claim 1, characterized in that, The inversion algorithm in step S5 is a least squares optimization algorithm based on regularization constraints. It inverts the secondary field attenuation data in the spatiotemporal domain into the resistivity distribution of the underground three-dimensional space by solving the electromagnetic inverse problem.

7. The method according to claim 1, characterized in that, The rendering of the three-dimensional resistivity data volume in step S6 refers to: setting a resistivity threshold and using the isosurface extraction method to generate a three-dimensional morphological model of a low-resistivity anomaly below the resistivity threshold, wherein the low-resistivity anomaly represents a leakage channel or a saturated area.

8. The method according to claim 1, characterized in that, In step S1, the detection nodes (2) are evenly distributed on the surface of the dam (1) in a grid or linear array manner.

9. A three-dimensional imaging system for implementing the method described in any one of claims 1-8, characterized in that, include: Central control unit; Several detection nodes (2) are deployed on the surface of the dam (1), and the detection nodes (2) are communicatively connected to the central control unit; The detection node (2) includes a transient electromagnetic instrument, a transmitting coil, a receiving coil, and a node controller; The central control unit includes: The communication module is used to interact with each detection node (2) for data exchange; The control module is used to generate the scanning instructions and adaptive scanning instructions; The data processing module is used to run the inversion algorithm to generate a three-dimensional resistivity data volume; The visualization module is used to render and display the three-dimensional resistivity data volume; The node controller is configured to receive instructions from the control module and control the transient electromagnetic instrument, the transmitting coil, and the receiving coil to perform the operations of steps S3 and S4.

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