Dam hidden danger electromagnetic data interpretation method and system based on anchoring effect

Abstract

The present application belongs to the technical field of dam internal hidden danger detection, and specifically provides a dam hidden danger electromagnetic data interpretation method and system based on anchoring effect, the core of which is to obtain the deviation curve of the detection target based on the anchoring curve, reflect the apparent resistivity distribution law according to the deviation curve, and deduce the dangerous area. Specifically, the original transient electromagnetic decay curve is collected; the decay curve is denoised, then the signal signal-to-noise ratio is evaluated and the waste channel is removed; the effective signal is subjected to time sequence synthesis processing, and the anchoring curve is screened out; the deviation curve is calculated based on the anchoring curve; the resistivity distribution model is constructed, and the reference curve is calculated; the deviation curve and the reference curve are multiplied according to the time sequence, and the inversion curve is obtained; based on the inversion curve, the apparent resistivity is calculated, and the cloud picture is obtained according to the apparent resistivity; based on the cloud picture, the dam hidden danger area is deduced. The present application can effectively improve the interpretation speed and accuracy of dam hidden danger detection data.

Description

Technical Field

[0001] This invention belongs to the field of dam internal hidden danger detection technology, specifically involving a method and system for electromagnetic data interpretation of dam hidden dangers based on the anchoring effect. Background Technology

[0002] As crucial water conservancy engineering facilities, the safety of dams directly impacts the lives and property of people downstream and the stable development of the social economy. Transient electromagnetic detection (TEM), a highly efficient and non-destructive geophysical detection method, has been widely applied in dam hazard detection in recent years. However, the unique boundary conditions of dams and the complexity of the detection environment present significant challenges to accurate hazard location. These challenges manifest in two main ways: First, dams often have trapezoidal cross-sections, with one side bordering water and the other open space, leading to substantial errors when using traditional half-space or full-space inversion methods. Second, as important water conservancy structures, dams typically have numerous electrical and other ancillary facilities nearby, resulting in strong physical field interference; the data obtained from TEM often contains significant noise and interference. Summary of the Invention

[0003] This invention provides a method and system for electromagnetic data interpretation of dam hazards based on the anchoring effect, which can greatly improve the accuracy and efficiency of dam hazard detection and provide technical support for dam safety assessment and maintenance.

[0004] A method for interpreting electromagnetic data of dam hazards based on the anchoring effect, the method comprising:

[0005] Electromagnetic fields were stimulated in the hidden danger area inside the dam body, and the original transient electromagnetic field signals were collected to obtain the decay curve of the original transient electromagnetic field over time.

[0006] The attenuation curves at the same location are superimposed to suppress uncorrelated noise between the peak values ​​of the original transient electromagnetic field signal, and the superimposed attenuation curves are subjected to correlation noise suppression processing to obtain the transient electromagnetic attenuation curves after noise suppression.

[0007] Signal evaluation and waste channel removal are performed on the transient electromagnetic attenuation curve after noise suppression to obtain the transient electromagnetic attenuation curve with waste channels removed.

[0008] The transient electromagnetic attenuation curves of the discarded channels are processed by time-series synthesis to screen out the anchoring curves.

[0009] Based on the anchoring curve, the deviation between the decay curve of the original transient electromagnetic field over time and the anchoring curve is calculated to form a deviation curve;

[0010] Based on existing geological data and monitoring data of the dam, a stratified resistance distribution model is constructed, and a baseline curve is calculated based on the stratified resistance distribution model.

[0011] The deviation curve and the reference curve are multiplied together in time series to obtain the inversion curve;

[0012] Based on the inversion curve, the apparent resistivity is calculated, and a contour map is obtained based on the apparent resistivity.

[0013] Based on the cloud map, the location of potential dam hazards is inferred, and the transient electromagnetic detection data of dam hazards based on the anchoring effect is interpreted.

[0014] Preferably, the method for superimposing the attenuation curves at the same location includes:

[0015] The attenuation curves at the same location are superimposed, and the average of the superimposed attenuation curves is calculated to complete the superposition process of the attenuation curves; the superposition formula is as follows:

[0016]

[0017] In the formula, This represents the summation of the original transient electromagnetic field signal, where n represents the number of signals.

[0018] Preferably, the method for performing correlation noise suppression processing on the attenuation curve after superposition includes:

[0019] The first-order difference method is used to pre-emphasize the attenuation curve after superposition processing to obtain the pre-emphasized signal;

[0020] The pre-emphasized signal is segmented and windowed;

[0021] The windowed pre-emphasized signal is subjected to short-time Fourier transform to obtain the frequency domain transient electromagnetic field signal;

[0022] The noise signal of the frequency domain transient electromagnetic field signal is filtered out by a filter to obtain a denoised signal;

[0023] The denoised signals are merged and converted into the time domain to complete the suppression of related noise.

[0024] Preferably, the method for obtaining the anchoring curve by performing time-series synthesis processing on the transient electromagnetic attenuation curve of the discarded waste channel includes:

[0025] When identifying the pre-set weak areas between the layers of the embankment, the time-series synthesis method is used to take the average value of the decay curves of the original transient electromagnetic field at each measuring point of the embankment at the same moment as the anchoring curve value at the same moment; the anchoring curve values ​​at each moment are arranged in time sequence to obtain the anchoring curve.

[0026] The methods for obtaining the anchoring curve also include the direct selection method and the first value selection method;

[0027] When the dam structure meets the preset requirements, the direct selection method is used to directly select the measuring points without abnormalities, and the attenuation curve of the measuring points without abnormalities is used as the anchoring curve.

[0028] When conducting a comprehensive comparison of the entire dam area, the first value selection method is used to select the first original transient electromagnetic field signal collected at each measuring point, and the attenuation curve corresponding to the median of all selected first original transient electromagnetic field signals is used as the anchoring curve.

[0029] Preferably, the formula for calculating the deviation curve is:

[0030]

[0031] In the formula, B z B represents the decay curve value. m This represents the anchoring curve value.

[0032] This invention also provides an electromagnetic data interpretation system for dam hazards based on the anchoring effect, used to implement the method, the system comprising:

[0033] The signal acquisition module is used to excite the electromagnetic field in the hidden danger area inside the dam body, acquire the original transient electromagnetic field signal, and obtain the decay curve of the original transient electromagnetic field over time.

[0034] The noise reduction module is used to superimpose the attenuation curves at the same location to suppress uncorrelated noise between the peak values ​​of the original transient electromagnetic field signal, and to perform correlation noise suppression processing on the superimposed attenuation curves to obtain the noise-suppressed transient electromagnetic attenuation curves.

[0035] The waste channel removal module is used to evaluate the signal and remove waste channels from the attenuation curve after noise suppression, and obtain the transient electromagnetic attenuation curve with the waste channels removed.

[0036] The anchoring curve acquisition module is used to perform time-series synthesis processing on the transient electromagnetic attenuation curves of the rejected channels and filter out the anchoring curves.

[0037] The deviation curve acquisition module is used to calculate the deviation between the decay curve of the original transient electromagnetic field changing with time and the anchor curve based on the anchor curve, and form a deviation curve.

[0038] The baseline curve acquisition module is used to construct a resistance distribution layered model based on the existing geological data and monitoring data of the dam, and to calculate the baseline curve based on the resistance distribution layered model.

[0039] The inversion curve acquisition module is used to multiply the deviation curve and the reference curve in a corresponding time series to obtain the inversion curve;

[0040] The cloud map acquisition module is used to calculate the apparent resistivity based on the inversion curve and obtain a cloud map based on the apparent resistivity.

[0041] The hazard location acquisition module is used to infer the location of dam hazards based on the cloud map and complete the interpretation of transient electromagnetic detection data of dam hazards based on the anchoring effect.

[0042] Preferably, the noise reduction module includes a superposition processing unit for superimposing the attenuation curves at the same location; the superposition processing unit includes:

[0043] The superposition sub-unit is used to superimpose attenuation curves at the same location;

[0044] The averaging sub-unit is used to average the superimposed attenuation curves, thus completing the superposition process of the attenuation curves; the superposition formula is as follows:

[0045]

[0046] In the formula, This represents the summation of the original transient electromagnetic field signal, where n represents the number of signals.

[0047] Preferably, the noise reduction module further includes a correlation noise filtering unit for performing correlation noise suppression processing on the attenuation curve after superposition processing; the correlation noise filtering unit includes:

[0048] The pre-emphasis subunit is used to pre-emphasize the attenuation curve after superposition processing using the first-order difference method to obtain the pre-emphasis signal.

[0049] A segmentation and windowing subunit is used to segment and window the pre-emphasis signal;

[0050] The time-frequency conversion subunit is used to perform a short-time Fourier transform on the windowed pre-emphasized signal to obtain a frequency-domain transient electromagnetic field signal.

[0051] The denoising subunit is used to filter out noise signals from the frequency domain transient electromagnetic field signal using a filter to obtain a denoised signal.

[0052] The frequency-time conversion subunit is used to merge the denoised signals and convert them into the time domain to complete the suppression of related noise.

[0053] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described thereon.

[0054] The present invention also provides a computer-readable storage medium storing a computer program that, when executed, implements the method described herein.

[0055] Compared with existing technologies, the beneficial effects of this invention are as follows: It introduces the concept of the anchoring effect into the interpretation of transient electromagnetic detection data for dam hazards. This interpretation method utilizing the anchoring effect is not mentioned in existing background technologies. It combines mathematical statistics, prior information fusion, and other methods with the anchoring effect to eliminate interference signals and establish anchoring curves, which differs from traditional methods of interpreting dam hazard detection data and possesses a certain novelty. Addressing the problem of large errors in traditional inversion methods due to special boundary conditions of dams (trapezoidal cross-section, one side water-adjacent and the other air-adjacent) and complex detection environments (physical field interference from numerous electrical auxiliary facilities), this invention proposes a new solution. By introducing the anchoring effect and establishing anchoring curves to solve for abnormal responses, it overcomes the shortcomings of traditional methods and has significant substantive characteristics. The combination of various specific methods and steps, such as multiple interference elimination methods and multiple methods for selecting anchoring curves, works together to improve detection accuracy and efficiency, representing a significant improvement over existing technologies. This invention can improve the accuracy and efficiency of dam hazard detection, provide technical support for dam safety assessment and maintenance, has practical application value, can be manufactured and used in the field of dam hazard detection, and produce positive effects. Attached Figure Description

[0056] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a flowchart of the electromagnetic data interpretation method for dam hazards based on the anchoring effect, according to an embodiment of the present invention.

[0058] Figure 2 This is a schematic diagram of the electromagnetic data interpretation system for dam hazards based on the anchoring effect, according to an embodiment of the present invention.

[0059] Figure 3 This is a multi-channel measurement diagram of interference data before and after signal removal in an embodiment of the present invention;

[0060] Figure 4 This is a schematic diagram of the attenuation curve in an embodiment of the present invention;

[0061] Figure 5 This is a multi-track plot of deviation data from an embodiment of the present invention;

[0062] Figure 6 This is a cloud diagram representing an embodiment of the present invention;

[0063] Figure description: 1-1 is the primary magnetic field excitation unit; 1-2 is the waveform control unit; 1-3 is the magnetic field receiving unit; 1-4 is the data acquisition and power supply unit; 2 is the data analysis component. Detailed Implementation

[0064] 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.

[0065] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0066] Example 1

[0067] like Figure 1 As shown, a method for interpreting electromagnetic data of dam hazards based on the anchoring effect is presented. The method includes:

[0068] S1: Excite the electromagnetic field in the hidden danger area inside the dam body, collect the original transient electromagnetic field signal, and obtain the decay curve of the original transient electromagnetic field over time; in this embodiment, a transient electromagnetic field source excitation method using a magnetic source or an electric source is used to excite the electromagnetic field in the hidden danger area inside the dam body; a loop device is used to receive the original transient electromagnetic field signal.

[0069] Furthermore, when using a magnetic source as the field source excitation method, an ungrounded multi-turn small loop coil is selected; when using an electrical source as the field source excitation method, a grounding electrode is installed on the dam body. Furthermore, the preferred current emission waveform is a step wave.

[0070] In this embodiment, the decay curve of the two original transient electromagnetic secondary signals over time can be the curve of the receiving coil voltage over time, i.e., the rate of change of the magnetic field. The curve can be selected to represent the change of magnetic field B over time; alternatively, the curve can also represent the change of magnetic field B over time. Furthermore, the secondary magnetic field data can be a three-component magnetic field signal or a single-component magnetic field signal, but it must include the z-direction component. Additionally, the position coordinates of the receiving point are recorded synchronously during data reception; the reception method can be manual numbering or RTK positioning.

[0071] S2: The attenuation curves at the same location are superimposed to suppress uncorrelated noise between the peak values ​​of the original transient electromagnetic field signal. Correlation noise suppression processing is then applied to the superimposed attenuation curves to obtain noise-suppressed transient electromagnetic attenuation curves. Comprehensive and meticulous preprocessing is performed on the raw data obtained from transient electromagnetic detection of dam hazards. The core objective is to completely eliminate all types of interference information contained within it. In actual detection environments, interference information comes from a wide range of complex sources, mainly including external electromagnetic interference, such as electromagnetic radiation generated by high-voltage transmission lines, streetlights, cables, and communication base stations near the dam.

[0072] A further embodiment of the method for superimposing the attenuation curves at the same location includes:

[0073] The secondary field exhibits the alternating sign periodicity of the primary field. By superimposing the attenuation curves at the same location and averaging the superimposed attenuation curves, any uncorrelated noise between the peaks of the transient electromagnetic secondary field signal in the spectrum will be suppressed, thus completing the superposition process of the attenuation curves. The superposition formula is as follows:

[0074]

[0075] In the formula, This represents the summation of the original transient electromagnetic field signal, where n represents the number of signals. This is to average the superimposed attenuation curves to obtain more stable and accurate results, thereby improving the signal-to-noise ratio. However, at the same time, the transient electromagnetic field signal and any coherent noise in the attenuation curve after superposition processing will be enhanced, and further suppression of coherent noise is required.

[0076] A further implementation method for performing correlation noise suppression processing on the attenuation curve after superposition processing includes:

[0077] The first-order difference method is used to pre-emphasize the attenuation curve after superposition processing to obtain the pre-emphasized signal. In this embodiment, the expression of the first-order difference method is: y(n)=x(n)-αx(n-1), where x(n) is the original input signal, y(n) is the pre-emphasized signal, and α is the pre-emphasis coefficient, which takes a value in the range of (0,1), with a preferred value of 0.9.

[0078] The pre-emphasized signal is segmented and windowed. Specifically, when segmenting the signal, the overlap in length between each segment should be no less than 50%. The preferred windowing function is either a Hamming window or a Blackman window. Both windowing functions have the characteristic of taking smaller values ​​at the ends and larger values ​​in the middle, causing the signal amplitude to gradually attenuate at both ends after windowing, avoiding abrupt changes during signal truncation. Windowing can more accurately reflect the true frequency of the signal, significantly reducing interference.

[0079] The windowed pre-emphasized signal is subjected to short-time Fourier transform to obtain the frequency domain transient electromagnetic field signal;

[0080] The noise signal of the frequency domain transient electromagnetic field signal is filtered out by a filter to obtain a denoised signal;

[0081] Noise signal filtering can be achieved by empirically selecting the noise frequency band and performing bandpass filtering, or by further employing methods such as wavelet analysis for filtering.

[0082] The denoised signals are merged and converted into the time domain to complete the suppression of related noise.

[0083] S3: Perform signal evaluation and discarding of the transient electromagnetic attenuation curve after noise suppression to obtain the transient electromagnetic attenuation curve after discarding the discarded channels; specifically, compare the noise-suppressed signal with the adjacent measurement channels to determine the signal. Signals that show an order of magnitude change compared with the adjacent measurement channels after noise reduction are regarded as discarded channels and are discarded.

[0084] S4: Perform time-series synthesis processing on the transient electromagnetic attenuation curves of the discarded channels to screen out the anchoring curves.

[0085] A further implementation method involves performing time-series synthesis processing on the transient electromagnetic attenuation curve of the discarded waste path to obtain the anchoring curve, including:

[0086] When identifying the pre-set weak areas between the layers of the embankment, the time-series synthesis method is used to take the average value of the decay curves of the original transient electromagnetic field at each measuring point of the embankment at the same moment as the anchoring curve value at the same moment; the anchoring curve values ​​at each moment are arranged in time sequence to obtain the anchoring curve.

[0087] The methods for obtaining the anchoring curve also include the direct selection method and the first value selection method;

[0088] When the dam structure meets the preset requirements, the direct selection method is used to directly select the measuring points without abnormalities, and the attenuation curve of the measuring points without abnormalities is used as the anchoring curve.

[0089] When conducting a comprehensive comparison of the entire dam area, the first-value point selection method is used to select the first raw transient electromagnetic field signal collected at each measuring point, and the attenuation curve corresponding to the median of all selected first raw transient electromagnetic field signals is used as the anchoring curve. Specifically,

[0090] (1) Direct selection method: For dams with relatively simple structures and complete geological data, such as homogeneous dams, measurement points without anomalies can be selected based on experience, and the attenuation curve of the measurement point can be used as the anchoring curve. That is, f = B i , where i is the measurement point number.

[0091] (2) Time-series synthesis method: Since the detection signal is a curve that decays over time, the depth of anomaly occurrence is correlated with the time series. The decay curves after noise suppression at each measuring point are processed over time, and the average value at the same moment of each measuring point is taken as the anchor curve value at that moment. The anchor curve values ​​at each moment are arranged in time sequence to form a curve that changes over time as the anchor curve.

[0092] Specifically, the value at time t is B. t =ave(B it ), where i is the number of each measuring point, t is the time, and ave represents the average value. Anchoring curve f = {B} t :t∈T}, where T is the acquisition sequence of the attenuation curve.

[0093] (3) First value selection method: Select the first acquisition point B of each measuring point. i1 The curve corresponding to the median is selected as the anchor curve, f = B. med .

[0094] Furthermore, when the dam structure is relatively simple and geological data is relatively complete, the direct selection method is preferred for establishing the anchoring curve; when identifying relatively weak areas between dam layers, the time-series synthesis method is preferred; and when conducting comprehensive comparisons of the entire dam area, the first-value point selection method is preferred. Alternatively, a combination of the time-series synthesis method and the first-value point selection method can be used for identification.

[0095] S5: Based on the anchoring curve, calculate the deviation between the decay curve of the original transient electromagnetic field changing with time and the anchoring curve to form a deviation curve;

[0096] A further implementation method involves using the following formula to calculate the deviation curve:

[0097]

[0098] In the formula, B z B represents the decay curve value. m This represents the anchoring curve value.

[0099] The obtained deviation data were preliminarily judged and statistically analyzed, and a multi-track deviation map was drawn. According to the detection principle, in areas where the deviation curve shows a positive value, the underground resistance value is lower than the resistance value corresponding to the anchor curve; in areas where the deviation curve shows a negative value, the underground resistance value is higher than the resistance value corresponding to the anchor curve. Based on this, areas with defects were preliminarily delineated. Regarding the positive and negative value areas: the original attenuation curves all showed positive values, but the above formula and anchor curve were used to calculate the difference, therefore the deviation curve has both positive and negative values. Positive values ​​indicate that the magnetic field is stronger than that of the anchor curve, while negative values ​​indicate a weaker magnetic field, indicating differences in underground resistance.

[0100] S6: Based on the existing geological data and monitoring data of the dam, construct a layered resistance distribution model, and calculate the baseline curve based on the layered resistance distribution model;

[0101] Specifically, the corresponding attenuation curve B is calculated based on the resistance distribution layering model. n The deviation curve B ω With B n Multiplying the corresponding time series values ​​yields the inversion curve B. c In this embodiment, the resistivity distribution layering model construction includes: dividing the dam material above the phreatic line and below the phreatic line according to the vertical direction of the dam, and the dam foundation; dividing it horizontally into upstream dam material, downstream dam material, transition material, and core wall; and using the electrical resistivity characteristic values ​​of the dam material in the above-mentioned areas as the resistivity of that area in the model.

[0102] Furthermore, the resistivity distribution stratification model is set based on the properties of features such as the phreatic line and bedrock.

[0103] S7: Multiply the deviation curve and the reference curve by the corresponding time series to obtain the inversion curve;

[0104] S8: Calculate the apparent resistivity based on the inversion curve, and obtain the contour map based on the apparent resistivity;

[0105] Apparent resistivity is calculated using the least squares method:

[0106] The least squares inversion algorithm is a mathematical optimization method that finds the best function match for data by minimizing the sum of squared errors. It is expressed using the L2 norm.

[0107]

[0108] In the formula, d = [d1, d2, ..., d... n [ ] represents the actual observed data; f(m) represents the theoretical observed value. The purpose of the inversion is to find the optimal model m that minimizes the deviation between f(m) and d. To ensure data convergence, the solution is usually obtained by specifying the number of iterations and the minimum error value. In this model experiment, the minimum error value is controlled to be no greater than 1% through six iterations.

[0109] S9: Based on the cloud map, infer the location of potential dam hazards and complete the interpretation of transient electromagnetic detection data of dam hazards based on the anchoring effect.

[0110] In summary, the core of this invention lies in firmly grasping the engineering characteristics of dams as artificial structures, where the physical properties of their filling materials are basically known and the seepage morphology is observable. It introduces the concept of the anchoring effect, using methods such as mathematical statistics and prior information fusion to eliminate interfering signals and establish an anchoring curve for transient electromagnetic observation. Then, using the anchoring curve as a benchmark, it solves for the abnormal responses of other curves, integrates the spatiotemporal distribution patterns of the abnormal responses, and locates the abnormal occurrence areas within the dam. This invention solves the interference of dam boundary conditions on data imagery, greatly improving the accuracy and efficiency of dam hazard detection, and providing technical support for dam safety assessment and maintenance.

[0111] Example 2

[0112] This invention also provides an electromagnetic data interpretation system for dam hazards based on the anchoring effect, used to implement the method of Embodiment 1. The system includes: a signal acquisition module, a noise reduction module, a waste track removal module, an anchoring curve acquisition module, a deviation curve acquisition module, a baseline curve acquisition module, an inversion curve acquisition module, a contour map acquisition module, a hazard location acquisition module, and a display. The waste track removal module, anchoring curve acquisition module, deviation curve acquisition module, baseline curve acquisition module, inversion curve acquisition module, contour map acquisition module, hazard location acquisition module, and display integrate a data analysis component 2. The data analysis component 2 is a high-performance computer equipped with a data processing program. This component can arrange and connect the points according to time to form a multi-track map. Figure 2 As shown.

[0113] The signal acquisition module is used to excite the electromagnetic field in the hidden danger area inside the dam body, acquire the original transient electromagnetic field signal, and obtain the decay curve of the original transient electromagnetic field over time. In this embodiment, the signal acquisition module includes a primary magnetic field excitation unit 1-1, a waveform control unit 1-2, a magnetic field receiving unit 1-3, and an acquisition and power supply unit 1-4. The primary magnetic field excitation unit 1-1 is divided into electrode type and coil type: the electrode type is a long wire connected to the soil through electrodes, and current can be applied; the coil type is a multi-turn coil wound with wire, which can generate a magnetic field after passing through different waveform currents. Specifically, the field source excitation coil wound with multi-turn wire has a diameter of 0.7m and 33 turns. The magnetic field receiving unit 1-3 is a magnetic flux sensor. When the magnetic field passes through the sensor, it causes an electrical signal transformation. The decay curve of the magnetic field change rate is obtained by the voltage change, or the magnetic field decay curve is obtained by integrating the voltage. The magnetic field receiving unit 1-3 is a coil wound with multi-turn wire, with the same center point as the magnetic field excitation module.

[0114] The waveform control unit 1-2 is connected to the primary magnetic field excitation unit 1-1, the magnetic field receiving unit 1-3, and the acquisition and power supply unit 1-4; it can control the waveform of different transmitted currents. Specifically, the waveform control unit 1-2 is a current fast shutdown system that can modulate the transmission of triangular waves and trapezoidal waves. The acquisition and power supply module consists of a laptop computer and a 24V lithium battery.

[0115] The noise reduction module is used to superimpose the attenuation curves at the same location to suppress uncorrelated noise between the peak values ​​of the original transient electromagnetic field signal, and to perform correlation noise suppression processing on the superimposed attenuation curves to obtain the noise-suppressed transient electromagnetic attenuation curves.

[0116] A further embodiment includes a noise reduction module comprising a superposition processing unit for superimposing the attenuation curves at the same location; the superposition processing unit comprises:

[0117] The superposition sub-unit is used to superimpose attenuation curves at the same location;

[0118] The averaging sub-unit is used to average the superimposed attenuation curves, thus completing the superposition process of the attenuation curves; the superposition formula is as follows:

[0119]

[0120] In the formula, This represents the summation of the original transient electromagnetic field signal, where n represents the number of signals.

[0121] A further embodiment includes a correlation noise filtering unit for performing correlation noise suppression processing on the attenuation curve after superposition processing; the correlation noise filtering unit includes:

[0122] The pre-emphasis subunit is used to pre-emphasize the attenuation curve after superposition processing using the first-order difference method to obtain the pre-emphasis signal.

[0123] The segmentation and windowing subunit is used to segment and window the pre-emphasized signal;

[0124] The time-frequency conversion subunit is used to perform a short-time Fourier transform on the windowed pre-emphasized signal to obtain a frequency-domain transient electromagnetic field signal.

[0125] The denoising subunit is used to filter out noise signals from the frequency domain transient electromagnetic field signal using a filter to obtain a denoised signal.

[0126] The frequency-time conversion subunit is used to merge and convert the denoised signal into the time domain to complete the suppression of related noise.

[0127] The waste channel removal module is used to evaluate the signal and remove waste channels from the attenuation curve after noise suppression, and obtain the transient electromagnetic attenuation curve with the waste channels removed.

[0128] The anchoring curve acquisition module is used to perform time-series synthesis processing on the transient electromagnetic attenuation curves of the rejected channels and filter out the anchoring curves.

[0129] The deviation curve acquisition module is used to calculate the deviation between the decay curve of the original transient electromagnetic field changing with time and the anchor curve based on the anchor curve, and form a deviation curve.

[0130] The baseline curve acquisition module is used to construct a resistance distribution layered model based on the existing geological data and monitoring data of the dam, and to calculate the baseline curve based on the resistance distribution layered model.

[0131] The inversion curve acquisition module is used to multiply the deviation curve and the reference curve in a corresponding time series to obtain the inversion curve;

[0132] The cloud map acquisition module is used to calculate the apparent resistivity based on the inversion curve and obtain the cloud map based on the apparent resistivity.

[0133] The hazard location acquisition module is used to infer the location of dam hazards based on the cloud map and complete the interpretation of transient electromagnetic detection data of dam hazards based on the anchoring effect.

[0134] Example 3

[0135] A flood control dike was constructed by artificial filling thirty years ago. It features a sloping dike structure with a crest elevation of approximately 7.5 meters and a crest width of approximately 5.3 meters. During the flood season, significant seepage occurred in some sections of the dike. To identify the internal seepage channels, this patented system and method were employed.

[0136] 1. Acquire signals.

[0137] A magnetic source transient electromagnetic field source is used to excite the electromagnetic field in the hidden danger area inside the dam body, and a loop device is used to receive the secondary magnetic field B. z Data (raw transient electromagnetic field signal) was acquired through continuous sampling, with RTK positioning used during movement. The transmission frequency was 16Hz, the operating frequency was 1.25MHz, and the transmission area was 10.77m². 2 Receiving area 4.02m² 2 .

[0138] 2. Eliminate interference.

[0139] In actual detection environments, interference includes external electromagnetic interference, high-voltage power lines, streetlights, and cables near dams. A superposition processing method is used to superimpose the measurement signals multiple times and then average them. The superposition is performed 100 times, improving the signal-to-noise ratio by 10 times.

[0140] To suppress noise, the signal is first pre-emphasized to increase the frequency of the high-frequency components. Then, the signal is segmented into 120 data channels, and windowing (16 windows) is applied to improve spectral accuracy. Next, a short-time Fourier transform is used to convert the time-domain transient electromagnetic data into the frequency domain. A bandpass filter is then used to remove noise signals. Finally, the segmented signals are merged and converted back to the time domain.

[0141] The noise-suppressed signal was compared with adjacent monitoring channels. It was found that the attenuation curve at station 4252, after noise reduction, showed a change in magnitude compared to adjacent channels. This signal was therefore considered a discarded channel and removed. Figure 3 As shown.

[0142] 3. Select the anchoring curve

[0143] Two methods are proposed for selecting the anchoring curve: direct selection, time-series synthesis, and initial value selection. This section of the dam is a homogeneous dam, and water level observation wells and geological data are available. Therefore, the direct selection method is used to determine the anchoring curve. Geological data reveals that the surface layer of the dam, from 0m to 10m, is mainly composed of clayey silt, grayish-yellow in color, with a small amount of clay or sand; from 10m to 40m, it is mainly composed of silt, with a small amount of thin layers of cohesive soil, and locally fine sand or sandy silt. Based on previous data analysis, no anomalies were found near well #1. The attenuation curve measured at station 4175 (point 58) is used as the anchoring curve. f = B 58 .like Figure 4 As shown.

[0144] 4. Obtain the deviation curve

[0145] Using the processed anchoring curve as a reference, calculate the deviation curve between the original signal curve and the anchoring curve.

[0146]

[0147] Preliminary judgment and numerical statistical analysis were performed on the obtained deviation data, and a multi-track deviation map was drawn. Based on the detection principle, in areas where the deviation curve shows a positive value, the underground resistivity is lower than the resistance value corresponding to the anchor curve; in areas where the deviation curve shows a negative value, the underground resistivity is higher than the resistance value corresponding to the anchor curve. Based on this, it was preliminarily determined that the apparent resistivity deviation near 4462 and 4904 is relatively large, exceeding 20%, potentially indicating leakage problems. Figure 5 As shown.

[0148] 5. Construct the inversion curve

[0149] Based on existing geological data and monitoring data of the dam, a layered resistance distribution model was constructed. The corresponding attenuation curve B was calculated based on the layered resistance distribution model. n The deviation curve Bω With B n Multiplying the corresponding time series values ​​yields the inversion curve B. c The resistivity distribution stratification model is set based on the properties of features such as the seepage line and bedrock.

[0150] 6. Generate a map

[0151] Based on the inversion curves, the apparent resistivity was calculated using the particle swarm optimization algorithm, and a contour map was plotted based on the apparent resistivity. Further analysis revealed leakage channels within the regions of station 4800–4925 (depth 20–30 m) and station 4975–5000 (depth 20–32 m). However, no concentrated low-resistivity area was observed near station 4462, suggesting a lower probability of a concentrated leakage channel. Figure 6 As shown.

[0152] Example 4

[0153] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for interpreting electromagnetic data of dam hazards based on the anchoring effect.

[0154] Example 5

[0155] The present invention also provides a computer-readable storage medium storing a computer program that, when executed, implements a method for interpreting electromagnetic data of dam hazards based on the anchoring effect.

[0156] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for interpreting electromagnetic data of dam hazards based on the anchoring effect, characterized in that, The method includes: Electromagnetic fields were stimulated in the hidden danger area inside the dam body, and the original transient electromagnetic field signals were collected to obtain the decay curve of the original transient electromagnetic field over time. The attenuation curves at the same location are superimposed to suppress uncorrelated noise between the peak values ​​of the original transient electromagnetic field signal, and the superimposed attenuation curves are subjected to correlation noise suppression processing to obtain the transient electromagnetic attenuation curves after noise suppression. Signal evaluation and waste channel removal are performed on the transient electromagnetic attenuation curve after noise suppression to obtain the transient electromagnetic attenuation curve with waste channels removed. The transient electromagnetic attenuation curves of the discarded channels are processed by time-series synthesis to screen out the anchoring curves. Based on the anchoring curve, the deviation between the decay curve of the original transient electromagnetic field over time and the anchoring curve is calculated to form a deviation curve; Based on existing geological data and monitoring data of the dam, a stratified resistance distribution model is constructed, and a baseline curve is calculated based on the stratified resistance distribution model. The deviation curve and the reference curve are multiplied together in time series to obtain the inversion curve; Based on the inversion curve, the apparent resistivity is calculated, and a contour map is obtained based on the apparent resistivity. Based on the cloud map, the location of potential dam hazards is inferred, and the transient electromagnetic detection data of dam hazards based on the anchoring effect is interpreted.

2. The method according to claim 1, characterized in that, The method for superimposing the attenuation curves at the same location includes: The attenuation curves at the same location are superimposed, and the average of the superimposed attenuation curves is calculated to complete the superposition process of the attenuation curves; the superposition formula is as follows: In the formula, This represents the summation of the original transient electromagnetic field signal, where n represents the number of signals.

3. The method according to claim 1, characterized in that, Methods for performing correlation noise suppression processing on the attenuation curve after superposition processing include: The first-order difference method is used to pre-emphasize the attenuation curve after superposition processing to obtain the pre-emphasized signal; The pre-emphasized signal is segmented and windowed; The windowed pre-emphasized signal is subjected to short-time Fourier transform to obtain the frequency domain transient electromagnetic field signal; The noise signal of the frequency domain transient electromagnetic field signal is filtered out by a filter to obtain a denoised signal; The denoised signals are merged and converted into the time domain to complete the suppression of related noise.

4. The method according to claim 1, characterized in that, The method for obtaining the anchoring curve by performing time-series synthesis processing on the transient electromagnetic attenuation curve of the discarded waste channel includes: When identifying the pre-set weak areas between the layers of the embankment, the time-series synthesis method is used to take the average value of the decay curves of the original transient electromagnetic field at each measuring point of the embankment at the same moment as the anchoring curve value at the same moment; the anchoring curve values ​​at each moment are arranged in time sequence to obtain the anchoring curve. The methods for obtaining the anchoring curve also include the direct selection method and the first value selection method; When the dam structure meets the preset requirements, the direct selection method is used to directly select the measuring points without abnormalities, and the attenuation curve of the measuring points without abnormalities is used as the anchoring curve. When conducting a comprehensive comparison of the entire dam area, the first value selection method is used to select the first original transient electromagnetic field signal collected at each measuring point, and the attenuation curve corresponding to the median of all selected first original transient electromagnetic field signals is used as the anchoring curve.

5. The method according to claim 1, characterized in that, The formula for calculating the deviation curve is: In the formula, B z B represents the decay curve value. m This represents the anchoring curve value.

6. An electromagnetic data interpretation system for dam hazards based on the anchoring effect, used to implement the method described in any one of claims 1-5, characterized in that, The system includes: The signal acquisition module is used to excite the electromagnetic field in the hidden danger area inside the dam body, acquire the original transient electromagnetic field signal, and obtain the decay curve of the original transient electromagnetic field over time. The noise reduction module is used to superimpose the attenuation curves at the same location to suppress uncorrelated noise between the peak values ​​of the original transient electromagnetic field signal, and to perform correlation noise suppression processing on the superimposed attenuation curves to obtain the noise-suppressed transient electromagnetic attenuation curves. The waste channel removal module is used to evaluate the signal and remove waste channels from the attenuation curve after noise suppression, and obtain the transient electromagnetic attenuation curve with the waste channels removed. The anchoring curve acquisition module is used to perform time-series synthesis processing on the transient electromagnetic attenuation curves of the rejected channels and filter out the anchoring curves. The deviation curve acquisition module is used to calculate the deviation between the decay curve of the original transient electromagnetic field changing with time and the anchor curve based on the anchor curve, and form a deviation curve. The baseline curve acquisition module is used to construct a resistance distribution layered model based on the existing geological data and monitoring data of the dam, and to calculate the baseline curve based on the resistance distribution layered model. The inversion curve acquisition module is used to multiply the deviation curve and the reference curve in a corresponding time series to obtain the inversion curve; The cloud map acquisition module is used to calculate the apparent resistivity based on the inversion curve and obtain a cloud map based on the apparent resistivity. The hazard location acquisition module is used to infer the location of dam hazards based on the cloud map and complete the interpretation of transient electromagnetic detection data of dam hazards based on the anchoring effect.

7. The system according to claim 6, characterized in that, The noise reduction module includes a superposition processing unit for superimposing the attenuation curves at the same location. The overlay processing unit includes: The superposition sub-unit is used to superimpose attenuation curves at the same location; The averaging sub-unit is used to average the superimposed attenuation curves, thus completing the superposition process of the attenuation curves; the superposition formula is as follows: In the formula, This represents the summation of the original transient electromagnetic field signal, where n represents the number of signals.

8. The system according to claim 6, characterized in that, The noise reduction module also includes a correlation noise filtering unit, which is used to perform correlation noise suppression processing on the attenuation curve after superposition processing. The relevant noise filtering unit includes: The pre-emphasis subunit is used to pre-emphasize the attenuation curve after superposition processing using the first-order difference method to obtain the pre-emphasis signal. A segmentation and windowing subunit is used to segment and window the pre-emphasis signal; The time-frequency conversion subunit is used to perform a short-time Fourier transform on the windowed pre-emphasized signal to obtain a frequency-domain transient electromagnetic field signal. The denoising subunit is used to filter out noise signals from the frequency domain transient electromagnetic field signal using a filter to obtain a denoised signal. The frequency-time conversion subunit is used to merge the denoised signals and convert them into the time domain to complete the suppression of related noise.

9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the method as described in any one of claims 1 to 5.

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