A method and system for finely adjusting the damping resistance of a transient electromagnetic transmitting coil

Abstract

This application belongs to the field of geophysical exploration technology, specifically disclosing a method and system for fine adjustment of the damping resistance of a transmitting coil in transient electromagnetic methods. The method involves: converting the current-off waveform of the transmitting coil into a digital current-off waveform, extracting characteristic parameters from the digital current-off waveform; inputting the characteristic parameters into a classification model to obtain the damping state of the current-off waveform; and adjusting the damping resistance based on a binary weighted adjustment method using conductance mapping according to the damping state. This application can significantly improve the steepness of the falling edge of the transmitting current, effectively suppress ringing, make the falling edge of the transient signal clearer, and improve the signal-to-noise ratio and spatial resolution of shallow and deep exploration.

Description

Technical Field

[0001] This application belongs to the field of geophysical exploration technology, and more specifically, relates to a method and system for fine adjustment of the damping resistance of a transient electromagnetic transmitting coil. Background Technology

[0002] Transient electromagnetic method (TEM) is a geophysical exploration technique based on the principle of electromagnetic induction. It generates a primary magnetic field by transmitting a step current signal to a grounded conductor or an ungrounded return line. Subsequently, a secondary eddy current field induced by the underground conductor is measured using an intermittent device within the primary pulsed magnetic field. By analyzing the time-varying relationship of the secondary induced voltage, the typical structure of the underground medium can be inverted. This method has advantages such as high construction efficiency, strong anti-interference capability, and independence from high-resistivity layers, and is widely used in hydrogeological surveys, mineral exploration, and engineering hazard detection projects.

[0003] As can be seen from the above, the quality of the falling edge of the transmitted current in transient electromagnetic methods is the core factor determining the detection accuracy, directly affecting the resolution and signal integrity of shallow targets. An ideal falling edge requires an extremely short turn-off time and a strictly monotonically exponential decay pattern without oscillations or overshoot. If severe current oscillations exist in the circuit, the induced secondary field will completely overwhelm the early response signal of the shallow target; if the current falling rate is too slow, the eddy current field intensity of the deep target will be significantly attenuated, significantly reducing the signal-to-noise ratio. The core function of the damping resistor is to balance the RLC equivalent circuit of the transmitting coil, making the circuit operate in a critically damped state, allowing the transmitted current to fall at the fastest speed, thus balancing shallow resolution and deep penetration.

[0004] Most mainstream transient electromagnetic transmission systems currently use fixed damping resistors or adjustable resistors with a limited range. Fixed resistors cannot adapt to different coils, while adjustable resistors with a limited range have large steps (usually tens of ohms), making it difficult to accurately match the critical damping resistance value. This results in the transmitter current cutoff waveform often not reaching the optimal value in actual operation, affecting the detection effect, especially for shallow high-resolution detection. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this application is to provide a method and system for fine adjustment of the damping resistance of a transient electromagnetic transmitting coil. This aims to solve the problem that existing transient electromagnetic transmitting systems mostly use fixed damping resistances or adjustable resistances with limited ranges. Fixed resistances cannot adapt to different coils, while adjustable resistances with limited ranges have large steps, making it difficult to match the critical damping resistance value. This results in the transmitting current turn-off waveform not reaching the optimal value, and consequently, the shallow resolution of the detection is low.

[0006] The first aspect of this application relates to a method for finely adjusting the damping resistance of a transmitting coil in a transient electromagnetic method, specifically including the following steps:

[0007] The current turn-off waveform of the transmitting coil is converted into a digital current turn-off waveform, and the characteristic parameters of the digital current turn-off waveform are extracted from it.

[0008] The feature parameters are input into the classification model to obtain the damping state of the current turn-off waveform;

[0009] The damping resistance is adjusted according to the damping state using a binary weighted adjustment method based on conductance mapping.

[0010] In some implementations, the binary weighted adjustment method for conductance mapping specifically includes the following steps:

[0011] The conductivity space is determined based on the range of values ​​for the damping resistor;

[0012] Based on the linear additivity of the conductance space, the conductance space is divided into equal step sizes to construct an impedance adjustment module with linear response;

[0013] The basic conductance provided by the first resistor is calculated based on the number of parallel branches in the impedance adjustment module and the minimum conductance space.

[0014] Adjusting the relay state regulates the total conductance, thereby adjusting the damping resistance;

[0015] An impedance adjustment module is provided at the port of the transmitting coil, which includes several parallel conductance branches. Each parallel branch contains a first resistor that provides basic conductance, a second resistor that provides incremental conductance, and a relay; the first resistor and the second resistor are connected in parallel.

[0016] In the relay reset state, the first resistors are connected in parallel to form a basic conductance network. When the relay is energized, the first resistors are disconnected, and the conductance increments are superimposed according to binary weighted summation.

[0017] In some implementations, when the damping state is underdamped, the damping resistance is reduced by increasing the parallel conductance at the transmitting coil port; when the damping state is overdamped, the damping resistance is increased by reducing the parallel conductance at the transmitting coil port.

[0018] In some implementations, the characteristic parameters of the digital current turn-off waveform include overshoot amplitude, turn-off time constant, attenuation coefficient, and oscillation frequency.

[0019] In some implementations, the method for training a classification model includes the following steps:

[0020] A mathematical model of the transmitting coil is constructed based on its inductance, internal resistance, and damping resistance, and a transfer function including the damping resistance is generated.

[0021] Based on the range of values ​​of the damping resistor of the transmitting coil, combined with the transfer function, the current turn-off waveform corresponding to each damping resistor value is calculated according to a preset step size, generating a current turn-off waveform dataset that includes underdamped, critically damped and overdamped states.

[0022] Feature parameters are extracted from each current-off waveform data to obtain the damping coefficient. Based on the damping coefficient, the waveform is classified and labeled according to its damping state. <1 indicates underdamping. =1 is the critical damping. >1 indicates overdamping;

[0023] The extracted feature parameters are used as input, and the damped state category is used as output. The KNN algorithm is used to train the classification model.

[0024] The second aspect of this application relates to a system for finely adjusting the damping resistance of a transient electromagnetic transmitting coil, comprising: a current sensor, an analog-to-digital converter, an FPGA module, an impedance adjustment module, and a control module;

[0025] The current sensor is used to detect the current-off waveform of the transmitting coil in real time.

[0026] An analog-to-digital converter is used to convert the current-off waveform of the transmitting coil into a digital current-off waveform.

[0027] The FPGA module is used to extract the feature parameters of the digital current turn-off waveform, input the feature parameters into the classification model, and obtain the damping state of the current turn-off waveform.

[0028] The control module is used to control the impedance adjustment module based on the damping state and the binary weighted adjustment method of conductance mapping, so as to adjust the damping resistance.

[0029] In some implementations, the impedance adjustment module is connected in parallel to the port of the transmitting coil and includes several parallel conductance branches. Each parallel conductance branch includes a first resistor that provides basic conductance, a second resistor that provides incremental conductance, and a relay; the first resistor and the second resistor are connected in parallel.

[0030] When the relay is in the reset state, the first resistors are connected in parallel to form a basic conductance network; when the relay is energized, the first resistors are disconnected, and the conductance increments are superimposed according to binary weighted summation.

[0031] More preferably, the relay in each parallel conduction branch has six terminals, including two common terminals, two normally open terminals, and two normally closed terminals; the common terminals are connected in parallel across the transmitting coil; the normally open terminals are connected to a first resistor, and the normally closed terminals are connected to a second resistor; in the reset state, the relay switches are simultaneously switched to the normally open terminals, and when an enable signal arrives, the relay switches are simultaneously switched to the normally closed terminals; when the relay switches are switched to the normally closed terminals, the second resistor is connected; when the relay switches are switched to the normally open terminals, the first resistor is connected.

[0032] In some implementations, the control module includes:

[0033] The conductivity space determination unit is used to determine the conductivity space based on the range of values ​​of the damping resistor.

[0034] The building block of the impedance adjustment module is used to divide the conductance space into equal step sizes based on the linear additivity of the conductance space, and to build an impedance adjustment module with linear response.

[0035] The basic conductance determination unit is used to calculate the basic conductance provided by the first resistor based on the number of parallel branches in the impedance adjustment module and the minimum value of the conductance space.

[0036] The damping resistor adjustment unit is used to adjust the relay state, thereby adjusting the total conductance and thus the damping resistor.

[0037] In some implementations, in the damping resistor adjustment unit, when the damping state is underdamped, the damping resistance is reduced by increasing the parallel conductance at the transmitting coil port; when the damping state is overdamped, the damping resistance is increased by reducing the parallel conductance at the transmitting coil port.

[0038] In some implementations, the transient electromagnetic transmitting coil damping resistance fine adjustment system further includes a classification model training module, which includes:

[0039] The transfer function generation unit is used to construct a mathematical model of the transmitting coil based on the inductance, internal resistance, and damping resistance of the transmitting coil, and to generate a transfer function that includes the damping resistance.

[0040] The waveform dataset generation unit is used to calculate the current turn-off waveform corresponding to each damping resistor value based on the range of values ​​of the damping resistor of the transmitting coil, combined with the transfer function, and according to a preset step size, to generate a current turn-off waveform dataset that includes underdamped, critically damped, and overdamped states.

[0041] The classification and labeling unit is used to extract feature parameters from each current-off waveform data to obtain the damping coefficient, and then... The waveform is classified and labeled according to its damping state; among which, <1 indicates underdamping. =1 is the critical damping. >1 indicates overdamping;

[0042] The training unit is used to train a classification model using the extracted feature parameters as input and the damped state category as output, employing the KNN algorithm.

[0043] In some implementations, the total conductance in the damping resistor adjustment unit is:

[0044]

[0045] in, Total conductivity; Based on basic conductivity; This indicates the relay status: 1 for activated and 0 for reset. To close the first i Increment of conductance for each relay; This represents the total number of parallel branches with high conductivity. Maximum conductivity; Minimum conductivity; ; .

[0046] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art:

[0047] This application provides a method for fine adjustment of the damping resistance of a transient electromagnetic transmitting coil. In a real-time environment, based on the transient electromagnetic waveform detected after power-on, the damping state is identified by inputting it into a KNN classification model, and the damping resistance is optimized accordingly. This method improves the sensitivity and response speed of the transient electromagnetic transmitting coil damping matching system, exhibits good adaptability under various complex working conditions, and significantly optimizes the performance of transient electromagnetic detection.

[0048] This invention can complete the rapid switching of resistance value in a very short time without replacing any physical components or requiring manual intervention. It greatly improves the adaptability of transient electromagnetic equipment under different coils and different ground conditions, and can significantly improve the steepness of the falling edge of the transmitting current, effectively suppress ringing, make the falling edge of the transient signal clearer, and improve the signal-to-noise ratio and spatial resolution of shallow and deep detection. Attached Figure Description

[0049] Figure 1 This is a flowchart illustrating the method for finely adjusting the damping resistance of the transient electromagnetic transmitting coil provided in the embodiments of this application;

[0050] Figure 2 This is a schematic diagram of a parallel network for relay control provided in an embodiment of this application;

[0051] Figure 3This is a schematic diagram of the overall architecture connection provided in the embodiments of this application;

[0052] Figure 4 This is a flowchart of the KNN algorithm training process provided in this application embodiment, including steps such as feature extraction, model training, and parameter optimization;

[0053] Figure 5 The embodiment of this application provides a critical damping resistance of 150. Schematic diagram. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A existing alone, A and B existing simultaneously, and B existing alone. In this application, the symbol " / " indicates that the related objects are in an "or" relationship, for example, A / B means A or B.

[0056] In this application, the terms “first” and “second” are used to distinguish different objects, rather than to describe a specific order of objects.

[0057] In this application, the term "electrical connection" can refer to a direct circuit connection or a signal transmission via a communication protocol.

[0058] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0059] In the description of the embodiments in this application, unless otherwise stated, "multiple" means two or more.

[0060] The embodiments of this application are described below with reference to the accompanying drawings.

[0061] To address the challenge of matching fixed damping resistors to the electrical characteristics of different transmitting coils, a 256-level fine-grained adaptive adjustable damping resistor system suitable for transient electromagnetic transmission systems is proposed. The core of this system lies in two aspects: first, using the K-Nearest Neighbors (KNN) algorithm to train a classification model, enabling accurate identification of the damping state of the turn-off waveform; second, based on the conductance mapping principle, transforming the complex damping adjustment problem into a linear superposition of conductances, achieving high-precision digital adjustment; and finally, through a dual-resistor parallel structure combined with a relay matrix, continuous adjustability over a wide resistance range is achieved.

[0062] Specifically, this application comprises two parts: an offline training component and an online tuning component;

[0063] In the offline training section, the inductance of the transmitting coil is first used as a basis. L Internal resistance r and damping resistor R A mathematical model of the transmitting coil is established, and a transfer function including the damping resistor is generated. The result is a second-order RLC circuit model with the following transfer function:

[0064]

[0065] Because in transient electromagnetic transmission systems, the damping resistance of the transmitting coil is typically around 100Ω. Up to 1000 Therefore, by using the transfer function, the current-off waveform corresponding to each resistance value is calculated with a certain step size, generating a waveform dataset containing three states: underdamped, critically damped, and overdamped; where the critical damping condition is:

[0066]

[0067] For each waveform data, characteristic parameters such as turn-off time constant, overshoot amplitude, attenuation coefficient, and oscillation frequency are extracted, and then analyzed based on the damping coefficient. The values ​​are used to classify and label the waveforms, where, <1 indicates underdamping. =1 is the critical damping. >1 indicates overdamping; the extracted waveform features are used as input and the damping state category is used as output. The KNN algorithm is used to train the classification model, and the K value and distance metric are optimized through cross-validation to ensure that the model has good generalization ability; after training, the model parameters are quantized and converted into a fixed-point format suitable for FPGA implementation.

[0068] In the online adjustment section, the control board controls the high-speed ADC to acquire the falling edge of the transmitting coil current waveform in real time. The acquired data is digitally filtered and normalized before being sent to the FPGA. A KNN classifier is used to determine in real time whether the current waveform is underdamped, critically damped, or overdamped. Based on the identification results, the damping resistor is adjusted in a fine manner. The adjustment is based on a binary weighted adjustment method using conductance mapping, as specifically implemented below:

[0069] In terms of circuit topology, this application makes full use of the superposition characteristics of the linear conductors when resistors are connected in parallel;

[0070]

[0071] in, This is the total conductivity value; These are the individual conductance values; This is the resistance value; N The number of resistors;

[0072] Compared to the nonlinear relationship in the resistance space, the conductance space exhibits strict linear additiveness. Therefore, by dividing the conductance space into equal-step intervals, a high-precision, linearly responsive impedance adjustment module can be constructed. The resistance adjustment range of this application is 100... Up to 1000 The corresponding conductance variation range is from 0.001S to 0.01S; the conductance space is divided into 256 equal step levels, with each step increment being:

[0073]

[0074] in, The maximum conductivity value is 0.01S in this application. The minimum conductivity value is 0.001S in this application. The conductance step size;

[0075] Specifically, the impedance adjustment module consists of 8 sets of relay-resistor units, each set containing two resistors and one relay; one resistor is used to provide the basic conductance ( When the relay is in the reset state, the circuit is closed, and the eight basic resistors are connected in parallel to form a basic conductance network with a total conductance of 0.001S. The device is in the maximum damping state with a resistance of 1000Ω. Another resistor is used to provide incremental conductance ( When the relay is energized, it closes and conducts, the base resistance is disconnected, and the conductance increment increases according to binary weighting, specifically:

[0076]

[0077] in, To close the firsti Increment of conductance for each relay;

[0078] Based on the relay status (using binary variables) (Indicates that 1 is activated and 0 is reset), the total conductance expression is:

[0079]

[0080] in, This indicates the relay status: 1 for activated and 0 for reset. Based on the fundamental conductance, the corresponding total resistance is:

[0081]

[0082] Combining Appendix 1 with the range of values ​​for the damping resistance of the transient electromagnetic transmitting coil (100) Up to 1000 ), basic resistance All set to 8000 The incremental conductance can be calculated using the following formula:

[0083]

[0084] Table 1

[0085]

[0086] In terms of hardware connectivity, such as Figure 3 He Ru Figure 4 As shown, the core processing module first controls the transmitter board to drive the transmitting coil to emit rectangular pulse signals. The coil is connected to a high-speed current sensor via a shielded cable to detect the falling edge quality of the pulse signal in real time. This current sensor has a high-speed interface that connects to a high-speed analog-to-digital converter (ADC) with ultra-high sampling rate and resolution. The ADC transmits the acquired current waveform data to the FPGA in real time via a communication interface for subsequent processing. The FPGA internally implements a KNN model for waveform recognition to accurately detect and classify transient electromagnetic waveforms. The FPGA adopts a parallel computing architecture, which effectively improves the processing speed and ensures that data processing can be completed within microseconds. Figure 2 As shown, the relay damping resistor module is connected in parallel across the two ends of the transmitting coil interface. The value of the damping resistor is precisely adjusted according to the real-time feedback data of the KNN model to ensure that the transmitting coil RLC circuit is in a critical damping state.

[0087] In the connection method of the relay resistor module, such as Figure 2Each branch shown consists of one relay and two resistors; for ease of understanding, each relay and resistor is assigned a number; assuming there are 8 parallel branches, the relays in each branch are represented by K1 to K8, and the resistors are labeled as follows: and ,in, i Number the branch roads (1 to 8);

[0088] Each branch relay has six terminals: common terminal (COM1, COM2), normally open terminal (NO1, NO2), and normally closed terminal (NC1, NC2). Specifically, the common terminal of relay K1 is connected to the output terminal of this branch (i.e., connected in parallel across the transmitting coil), and NO1 and NO2 are connected to high-resistance terminals respectively. NC1 and NC2 are connected to the low resistance values ​​respectively. In the reset state, the relay switch is simultaneously set to the NO terminal. When an enable signal arrives, the relay switch simultaneously sets to the NC terminal. Thus, when relay K1 selects the NC state, this branch is connected. When K1 selects the NO state, then access is enabled. The same connection method applies to relays K2 through K8 and their corresponding resistors. and This allows each branch to select an appropriate resistance value as needed.

[0089] During operation, the N-model executes adjustment methods based on the real-time feedback of the identification results: if an underdamped state is identified, the parallel conductance is increased through an 8-bit control word, thereby reducing the equivalent damping resistance; if an overdamped state is identified, the parallel conductance is decreased, increasing the equivalent damping resistance; if a critically damped state is identified, the current setting remains unchanged; the step size for each adjustment can be adaptively set according to the degree of deviation: initially, a larger step size is used for rapid approximation, and when approaching the critical damping, the step size is reduced for fine adjustment; because the damping resistance is set as a discrete value, a limit value for the damping resistance is set to prevent oscillation.

[0090] Through this adaptive and refined damping resistor adjustment method, this application can complete the rapid switching of resistance value in a very short time without replacing any physical components or requiring manual intervention, which greatly improves the adaptability of transient electromagnetic equipment under different coils and different ground conditions.

[0091] Figure 5 To connect two 5m×5m turns of equivalent area 50 to the self-developed CTEM transient electromagnetic instrument. The diagram shows the turn-off effect of the transmitting coil achieving the critical damping state by equipping it with this adaptive fine damping adjustment system.

[0092] Actual tests show that the system can significantly improve the steepness of the falling edge of the transmit current, effectively suppress ringing, make the falling edge of the transient signal clearer, and improve the signal-to-noise ratio and spatial resolution of shallow and deep detection.

[0093] Example

[0094] like Figure 1 As shown, this application provides a method for finely adjusting the damping resistance of a transient electromagnetic transmitting coil. The core of this method includes current monitoring of the transient electromagnetic transmitting coil and adaptive adjustment of the damping resistance. Specifically, it includes the following steps:

[0095] Transmitting coil detection: The system first starts the transmitting coil, and the transmitting current begins to flow; during the transmission process, the current sensor monitors the current changes in the transmitting coil in real time;

[0096] Current detection: A fast current sensor is used to capture the current waveform of the transmitting coil, ensuring that the collected data accurately reflects the true changes in the current;

[0097] High-speed ADC (A / D) conversion: The collected analog current signal is digitized through a high-speed analog-to-digital converter; this converter has an ultra-high sampling rate and resolution to ensure data accuracy;

[0098] FPGA processing: The converted digital signal is sent to the FPGA for further processing. The FPGA performs complex calculations such as feature extraction and pattern recognition. The parallel computing architecture of this process can significantly improve the processing speed.

[0099] Feature extraction: The FPGA extracts several key features from the current waveform, such as overshoot amplitude, turn-off time constant and attenuation coefficient, to form a feature vector for subsequent analysis.

[0100] KNN classification model: The extracted feature vectors will be input into a pre-trained KNN (K-Nearest Neighbors) classification model, which will analyze the current waveform state to determine its damping state;

[0101] Waveform damping state judgment: Based on the output of the KNN classification model, the system determines whether the current waveform state is underdamped, critically damped, or overdamped. This judgment is crucial for the subsequent adjustment process.

[0102] Damping resistance adjustment: Underdamped state: If underdamped, the system will increase the parallel conductance to reduce the equivalent damping resistance and improve the attenuation rate of the current waveform; Critically damped state: If critically damped, the system will maintain the current damping setting to ensure stable system performance; Overdamped state: If overdamped, the system will reduce the parallel conductance and increase the equivalent damping resistance to ensure that the signal attenuation rate is not too slow.

[0103] Update control signal: The system updates the control signal based on the identified waveform state and adjustment requirements, instructing the corresponding analog switch or relay to adjust the resistance;

[0104] Adjusting the damping resistance: Finally, the system adjusts the required resistance value by controlling a relay or analog switch, completing an adaptive damping adjustment process;

[0105] Through the above steps, the modified adaptive fine adjustment method can identify the damping state based on the transient electromagnetic waveform detected after power-on in a real-time environment, input it into the KNN classification model, and optimize the adjustment of the damping resistance accordingly. This method improves the sensitivity and response speed of the system, shows good adaptability under various complex working conditions, and significantly optimizes the performance of transient electromagnetic detection.

[0106] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for fine adjustment of a damping resistor of a transient electromagnetic method transmitting coil, characterized in that, The method comprises the following steps: The current off waveform of the transmitting coil is converted into a digital current off waveform, and a characteristic parameter of the digital current off waveform is extracted; The characteristic parameter is input into a classification model to obtain a damping state of the current off waveform; According to the damping state, a binary weighted adjustment method based on conductance mapping is used to adjust the damping resistor; The binary weighted adjustment method based on conductance mapping comprises the following steps: A conductance space is determined according to the value range of the damping resistor; Based on the linear additivity of the conductance space, the conductance space is divided into equal steps to construct an impedance adjustment module with linear response; According to the number of parallel branches in the impedance adjustment module and the minimum value of the conductance space, the basic conductance provided by the first resistor is calculated; Based on the damping state, the relay state is adjusted to adjust the total conductance and further adjust the damping resistor; The impedance adjustment module is arranged at the port of the transmitting coil, and comprises a plurality of parallel conductance parallel branches, each of which comprises a first resistor providing a basic conductance, a second resistor providing an incremental conductance, and a relay; the first resistor and the second resistor are connected in parallel. In the relay reset state, the first resistors are connected in parallel to form a basic conductance network, and when the relay is attracted, the first resistors are disconnected, and the conductance increment is added according to the binary weighting.

2. The method of fine adjustment of a damped resistance according to claim 1, characterized in that, The characteristic parameters of the digital current off waveform include overshoot amplitude, off time constant, damping coefficient and oscillation frequency.

3. The method of fine adjustment of a damped resistance according to claim 1, characterized in that, The method for training the classification model comprises the following steps: A mathematical model of the transmitting coil is constructed according to the inductance, internal resistance and damping resistor of the transmitting coil to generate a transfer function containing the damping resistor; According to the value range of the damping resistor of the transmitting coil, the transfer function is combined to calculate the current off waveform corresponding to each damping resistor value at a predetermined step, and a current off waveform dataset containing under-damping, critical damping and over-damping states is generated; The feature parameters are extracted from each current off waveform data to obtain a damping coefficient, and the damping coefficient is used to The waveform is classified and labeled according to the damping state; wherein, <1 is under-damped, =1 is critical damping, >1 is over-damped; The extracted characteristic parameters are used as input, and the damping state category is used as output. The KNN algorithm is used to train the classification model.

4. A system for fine adjustment of the damping resistance of a transient electromagnetic transmitting coil, characterized in that, It comprises: a current sensor, an analog-to-digital converter, an FPGA module, an impedance adjustment module and a control module; The current sensor is used to detect the current off waveform of the transmitting coil in real time; The analog-to-digital converter is used to convert the current off waveform of the transmitting coil into a digital current off waveform; The FPGA module is used to extract the characteristic parameters of the digital current off waveform, input the characteristic parameters into the classification model, and obtain the damping state of the current off waveform; The control module is used to control the impedance adjustment module based on the binary weighted adjustment method based on conductance mapping according to the damping state to adjust the damping resistor; The control module comprises: a conductance space determination unit for determining a conductance space according to the value range of the damping resistor; a construction unit of the impedance adjustment module for dividing the conductance space into equal steps based on the linear additivity of the conductance space to construct an impedance adjustment module with linear response; a basic conductance determination unit for calculating the basic conductance provided by the first resistor according to the number of parallel branches in the impedance adjustment module and the minimum value of the conductance space; The damping resistance adjusting unit is used for adjusting the relay state, adjusting the total conductance, and adjusting the damping resistance. The impedance adjusting module is connected in parallel with the port of the transmitting coil, and includes a plurality of parallel conductance parallel branches. Each parallel branch includes a first resistor providing a basic conductance, a second resistor providing an incremental conductance, and a relay. The first resistor and the second resistor are connected in parallel. When the relay is in a reset state, the first resistor forms a basic conductance network in parallel. When the relay is attracted, the first resistor is disconnected, and the conductance increment is added according to binary weighting.

5. The damped-resistor fine adjustment system of claim 4, wherein, The relay in each conductance parallel branch has six terminals, including two common terminals, two normally open terminals, and two normally closed terminals. The common terminals are connected in parallel across the transmitting coil. The normally open terminals are connected to the first resistor, and the normally closed terminals are connected to the second resistor. In the reset state, the relay switch is opened to the normally open terminals at the same time. When the enable signal comes, the relay switch is closed to the normally closed terminals at the same time. When the relay switch is closed to the normally closed terminals, the second resistor is connected. When the relay switch is closed to the normally open terminals, the first resistor is connected.

6. The damped-resistor fine adjustment system of claim 4, wherein, The classification model training module includes: The transfer function generation unit is configured to construct a mathematical model of the transmitting coil according to the inductance, internal resistance, and damping resistance of the transmitting coil, and generate a transfer function including the damping resistance. The waveform data set generation unit is configured to calculate a current off waveform corresponding to each damping resistance value according to a preset step length based on a value range of the damping resistance of the transmitting coil and in combination with the transfer function, and generate a current off waveform data set including under-damping, critical damping, and over-damping states. The classification labeling unit is used for extracting feature parameters from each current off waveform data to obtain a damping coefficient, and classifying and labeling the damping state of the waveform according to the damping coefficient The classification labeling unit is used for extracting feature parameters from each current off waveform data to obtain a damping coefficient, and classifying and labeling the damping state of the waveform according to the damping coefficient <1 is under-damped, =1 is critical damping, >1 is over-damped; The training unit is configured to take the extracted feature parameters as input and the damping state category as output, and train the classification model by using a KNN algorithm.

7. The fine adjustment system of a damped resistance according to claim 4 or 5, characterized in that The total conductance in the damping resistance adjusting unit is: wherein, is the total conductance; is the base conductance; represents the relay state, 1 for pull-in and 0 for reset; is the conductance increment when the i-th relay is closed; i is the total number of parallel branches of conductance; is the maximum conductance; is the minimum conductance; , , .

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