A conductivity measurement method and system based on integration of ground electrode current field communication and sensing

Abstract

The application provides a conductivity measurement method and system based on ground electrode current field communication and perception integration, relates to the underground medium electrical parameter measurement technical field, and comprises the following steps: at each calibration measurement point, two-channel signals are synchronously collected by using orthogonal electrodes, and after effective signals are intercepted through pretreatment and sliding correlation positioning, the effective signals are vector-synthesized; taking the synthesized signal of the lowest conductivity measurement point as a reference, the consistency correlation coefficient of each measurement point is calculated; taking the consistency correlation coefficient as input and the conductivity as a label, a support vector regression model is trained; the consistency correlation coefficient of the measurement point is also obtained, and the model is input to output the conductivity. The accurate output of the conductivity is realized under the condition that the sample quantity is limited.

Description

Technical Field

[0001] This invention relates to the field of underground dielectric electrical parameter measurement technology, and in particular to a conductivity measurement method and system based on the integration of ground electrode current field communication and sensing. Background Technology

[0002] Currently, underground spaces such as mines, tunnels, and underground utility tunnels typically utilize ground electrode current field communication systems for information transmission. These systems use electrodes inserted underground at both ends to carry information data in the form of electric field current, enabling signal transmission and reception. Existing underground medium conductivity detection schemes are mainly divided into two categories: one is dedicated conductivity detection equipment or formation logging devices, such as using inductive probes, multi-frequency excitation, or multi-spacing measurement methods to invert formation conductivity. Such equipment usually requires drilling, well installation, or additional dedicated probe deployment, making the equipment structure and on-site operation relatively complex, and it is difficult to directly integrate with existing ground electrode current field communication systems. The other category is existing underground communication or current field transmission systems. These systems mainly improve communication distance and received signal-to-noise ratio by optimizing transmission parameters, receiving structure, and signal processing methods. Signal attenuation and waveform changes caused by changes in underground medium conductivity are usually suppressed or compensated as interference factors affecting communication quality, without further utilizing these changes for conductivity measurement. Therefore, existing schemes generally suffer from problems such as independent detection and communication equipment, redundant deployment of on-site systems, and insufficient utilization of medium state information in the received communication signals. Therefore, in order to overcome the above-mentioned defects, the present invention provides a conductivity measurement method and system based on the integration of ground electrode current field communication and sensing. Summary of the Invention

[0003] This invention provides a conductivity measurement method and system based on the integration of ground electrode current field communication and sensing. It uses the same ground electrode current field communication equipment and the same receiving signal to synchronously complete information demodulation and dielectric conductivity measurement. Through dual-channel synchronous acquisition and vector synthesis processing of the L-shaped electrode array, the amplitude measurement deviation caused by the inconsistency between the receiving electrode layout direction and the actual electric field direction can be effectively reduced, allowing the extracted signal features to more accurately reflect changes in dielectric conductivity. The consistency correlation coefficient quantifies the overall deviation of the received signal from the reference signal, comprehensively reflecting the differences in signal mean, variance, and trend, providing stable input features for conductivity measurement. Simultaneously, a support vector regression model is used to establish a nonlinear mapping relationship between the consistency correlation coefficient and conductivity, enabling accurate conductivity output even with a limited sample size.

[0004] This invention provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing, comprising: S1: Simultaneously collect the induced voltage of the underground current field at multiple calibration measurement points based on the receiving channel of the L-shaped electrode array, and obtain the first channel original signal and the second channel original signal of each calibration measurement point; S2: Perform signal preprocessing on the first channel raw signal and the second channel raw signal of each calibration measurement point respectively. Perform sliding correlation operation between the preset synchronization head template and the preprocessed two channel signals respectively. Determine the position of the synchronization head in the received signal according to the peak position in the correlation sequence of each channel. Based on the synchronization head position, extract a fixed length of effective signal to obtain the first channel effective signal and the second channel effective signal of each calibration measurement point. S3: Perform vector synthesis on the first channel effective signal and the second channel effective signal of each calibration measurement point to obtain the synthesized total response signal of each calibration measurement point; S4: Select the target measurement point with the smallest measured conductivity value among all calibration measurement points, and use the synthetic total response signal corresponding to the target measurement point as the reference signal. Calculate the consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal. S5: Using the consistency correlation coefficient of each calibration point as the input feature and the measured conductivity value of each calibration point as the output label, train the support vector regression model; S6: At the test location, repeat steps S1-S3 to obtain the synthetic total response signal at the test location, and calculate the consistency correlation coefficient between the synthetic total response signal and the reference signal selected in step S4 to obtain the consistency correlation coefficient at the test location. Then, input the coefficient into the support vector regression model and output the conductivity measurement value at the test location.

[0005] Preferably, a conductivity measurement method based on integrated communication and sensing of ground electrode current field includes, in step S1, the induced voltage of the underground current field is synchronously acquired at multiple calibration measurement points using a receiving channel based on an L-shaped electrode array, comprising: The L-shaped electrode array consists of a first electrode, a second electrode, and a third electrode. The first electrode serves as a common electrode. The first electrode and the second electrode form a first receiving channel, and the first electrode and the third electrode form a second receiving channel. The arrangement directions of the first receiving channel and the second receiving channel are perpendicular to each other, and the electrode spacing between the two channels is equal.

[0006] Preferably, in a conductivity measurement method based on the integration of ground electrode current field communication and sensing, the signal preprocessing in S2 includes: DC bias correction and FIR bandpass filtering, wherein the passband range of the FIR bandpass filter is determined according to the center frequency of the transmitted signal, and is used to suppress DC components, power frequency interference and out-of-band noise.

[0007] Preferably, in a conductivity measurement method based on ground electrode current field communication and sensing integration, in step S2, the first channel raw signal and the second channel raw signal of each calibration measurement point are preprocessed respectively. A preset synchronization head template is then used to perform sliding correlation calculations with the preprocessed two channel signals. The position of the synchronization head in the received signal is determined based on the peak position in the correlation sequence of each channel. A fixed length of effective signal is then extracted based on the synchronization head position to obtain the first channel effective signal and the second channel effective signal of each calibration measurement point, including: The first channel original signal and the second channel original signal of each calibration measurement point are acquired. The first channel original signal and the second channel original signal are then subjected to DC bias correction and bandpass filtering respectively to obtain the filtered first channel original signal and the second channel original signal. The synchronization head template is resampled to the same sampling rate as the filtered original signals of the first and second channels. The resampled synchronization head template is then subjected to sliding correlation operation with the filtered original signals of the first and second channels to obtain the correlation coefficient sequence for each channel. The peak positions in the correlation coefficient sequences of each channel are detected respectively. Each peak position is used as the starting position of the synchronization head in the received signal of each channel. Based on the starting position of each channel, a signal segment of fixed time length is extracted from the filtered signal of the corresponding channel as the first channel effective signal and the second channel effective signal of the calibration measurement point. The original signals of the first and second channels use the same synchronous positioning and fixed-length truncation method to ensure that the effective signals of different channels and different measurement points are consistent in data length and time position.

[0008] Preferably, in a conductivity measurement method based on the integration of ground electrode current field communication and sensing, in step S3, the effective signals of the first channel and the effective signals of the second channel at each calibration point are vector-synthesized to obtain the synthesized total response signal for each calibration point, including: S31: Using the sampling time axis of the first channel valid signal as a reference, extract the instantaneous amplitude of the first channel valid signal and the second channel valid signal at the same sampling moment; S32: Perform vector synthesis based on the instantaneous amplitude of the first channel valid signal and the instantaneous amplitude of the second channel valid signal at the same sampling time to obtain the synthesized instantaneous amplitude at the current sampling time. ; in, This represents the instantaneous amplitude of the first channel's valid signal corresponding to the i sampling times; This represents the instantaneous amplitude of the valid signal in the second channel corresponding to the i sampling times; This represents the composite instantaneous amplitude corresponding to the i sampling times; i represents the sequence number of the sampling times. S33: Repeat steps S31-S32 point by point for all sampling times to obtain the composite total response signal waveform composed of all composite instantaneous amplitudes, wherein the length of the composite total response signal waveform is equal to the length of the first channel effective signal or the second channel effective signal.

[0009] Preferably, in a conductivity measurement method based on the integration of ground electrode current field communication and sensing, in step S4, a target measurement point with the smallest measured conductivity value is selected from all calibration measurement points, and the synthetic total response signal corresponding to the target measurement point is used as a reference signal. The consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal is calculated, including: The measured conductivity values ​​of each calibration point are sorted according to the decreasing order of the measured conductivity values. The point with the smallest measured conductivity value is selected, and the synthesized total response signal of the point with the smallest measured conductivity value is set as the reference signal. Using the reference signal as the comparison object, the synthetic total response signal of each calibration point is compared with the reference signal point by point according to the sampling time, and the covariance between the two sets of signals, the variance of the reference signal, the variance of the current calibration point signal, the mean of the reference signal, and the mean of the current calibration point signal are calculated. Based on the covariance between the two sets of signals of the composite total response signal of the reference signal and the current calibration point, the variance of the reference signal, the variance of the current calibration point signal, the mean of the reference signal, and the mean of the current calibration point signal, the consistency correlation coefficient of each calibration point relative to the reference signal is calculated, and the consistency correlation coefficient of the reference point itself is 1. ; in, This represents the consistency correlation coefficient of the current calibration measurement point relative to the reference signal; The covariance between the two sets of signals representing the reference signal and the synthesized total response signal of the current calibration measurement point; Represents the variance of the reference signal; This represents the variance of the synthesized total response signal at the current calibration measurement point; Represents the mean of the reference signal; This represents the mean value of the current calibration measurement points.

[0010] Preferably, a conductivity measurement method based on the integration of ground electrode current field communication and sensing, after calculating the consistency correlation coefficient of each calibration measurement point relative to the reference signal, further includes: Determine whether the consistency correlation coefficient of each calibration point decreases monotonically with the measured conductivity value; based on the ascending order of the measured conductivity values ​​of each calibration point, check whether the corresponding consistency correlation coefficient shows a monotonically decreasing trend; if a non-monotonically decreasing measurement point is found, the measurement point with the largest deviation from the overall trend in the change of the consistency correlation coefficient relative to adjacent measurement points is taken as an abnormal measurement point, and the consistency correlation coefficient and measured conductivity value of the abnormal measurement point are treated as invalid data and removed. If the consistency correlation coefficient of each calibration measurement point decreases monotonically with the measured conductivity value, then each calibration measurement point is paired with the measured conductivity value of the same measurement point according to the consistency correlation coefficient of each calibration measurement point relative to the reference signal to form feature-label sample pairs. The support vector regression model is trained based on feature-label sample pairs.

[0011] Preferably, a conductivity measurement method based on the integration of ground electrode current field communication and sensing, in step S5, uses the consistency correlation coefficient of each calibration measurement point as the input feature and the measured conductivity value of each calibration measurement point as the output label to train a support vector regression model, including: Read the feature-label sample pairs of each calibration measurement point. Each feature-label sample pair is composed of a consistency correlation coefficient as the input feature and the measured conductivity value as the output label. The feature-label samples of each calibration point are input into the support vector regression model for training, as shown in the following formula: ; in, This represents the conductivity output by the support vector regression model. This represents the consistency correlation coefficient to be input into the support vector regression model; This represents the input feature value corresponding to the i-th support vector; Represents the kernel function; Indicates the index value of the support vector; This represents the total number of support vectors; This represents the first weight coefficient corresponding to the i-th support vector; Let represent the second weight coefficient corresponding to the i-th support vector, and and Determined by the training process of the support vector regression model; With the coefficient of determination As an evaluation metric for model fit, the trained support vector regression model is evaluated, and the model parameters after training are saved.

[0012] Preferably, a conductivity measurement method based on the integration of ground electrode current field communication and sensing, using the measured conductivity values ​​at each calibration point as output tags, includes: The measured conductivity values ​​of each calibration point were obtained in the following way: multiple measurements were taken at each calibration point using a soil conductivity meter, and the arithmetic mean of the multiple measurements was taken as the measured conductivity value of the calibration point.

[0013] This invention provides a conductivity measurement system based on integrated communication and sensing of ground electrode current field, comprising: The signal acquisition module is used to synchronously acquire the induced voltage of the underground current field at multiple calibration points based on the receiving channel of the L-shaped electrode array, and obtain the first channel original signal and the second channel original signal of each calibration point. The effective signal determination module is used to preprocess the first channel original signal and the second channel original signal of each calibration measurement point, perform sliding correlation operation between the preset synchronization head template and the preprocessed two channel signals, determine the position of the synchronization head in the received signal according to the peak position in the correlation sequence of each channel, and extract a fixed length of effective signal based on the synchronization head position to obtain the first channel effective signal and the second channel effective signal of each calibration measurement point. The effective signal vector synthesis module is used to perform vector synthesis of the first channel effective signal and the second channel effective signal at each calibration measurement point to obtain the synthesized total response signal at each calibration measurement point; The consistency correlation coefficient determination module is used to select the target measurement point with the smallest measured conductivity value among all calibration measurement points, and use the synthetic total response signal corresponding to the target measurement point as the reference signal, and calculate the consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal respectively. The model training module is used to train a support vector regression model by using the consistency correlation coefficient of each calibration point as the input feature and the measured conductivity value of each calibration point as the output label. The result output module is used to control the signal acquisition module, the effective signal determination module, and the effective signal vector synthesis module to sequentially perform signal acquisition, signal preprocessing, and vector synthesis at the test location to obtain the synthesized total response signal at the test location. The module then calculates the consistency correlation coefficient between the synthesized total response signal and the selected reference signal to obtain the consistency correlation coefficient at the test location. This coefficient is then input into the support vector regression model to output the conductivity measurement value at the test location.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: By using the same set of ground electrode current field communication equipment and the same receiving signal, information demodulation and dielectric conductivity measurement are completed synchronously. Through dual-channel synchronous acquisition and vector synthesis processing of the L-shaped electrode array, the amplitude measurement deviation caused by the inconsistency between the receiving electrode layout direction and the actual electric field direction can be effectively reduced, making the extracted signal features more accurately reflect the changes in dielectric conductivity. The overall deviation of the received signal from the reference signal is quantified by the consistency correlation coefficient, which can comprehensively reflect the differences in signal mean, variance and trend, providing stable input features for conductivity measurement. At the same time, the nonlinear mapping relationship between the consistency correlation coefficient and conductivity is established by using the support vector regression model, which can achieve accurate conductivity output under the condition of limited sample size.

[0015] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a conductivity measurement method based on the integration of ground electrode current field communication and sensing in an embodiment of the present invention; Figure 2 This is a schematic diagram of the conductivity measurement principle in a conductivity measurement method based on the integration of ground electrode current field communication and sensing in an embodiment of the present invention. Figure 3 This is a schematic diagram illustrating the comparison between the signal under test and a reference reference in a conductivity measurement method based on the integration of ground electrode current field communication and sensing in an embodiment of the present invention. Figure 4 This is a schematic diagram of an L-shaped electrode receiving array in a conductivity measurement method based on ground electrode current field communication and sensing integration in an embodiment of the present invention. Figure 5 This is a comparison chart of consistency correlation coefficient and conductivity in a conductivity measurement method based on ground electrode current field communication and sensing integration in an embodiment of the present invention. Figure 6 This is a schematic diagram of the ground electrode current field in a conductivity measurement method based on the integration of ground electrode current field communication and sensing in an embodiment of the present invention. Figure 7This is a structural diagram of a conductivity measurement system based on the integration of ground electrode current field communication and sensing in an embodiment of the present invention; Figure 8 This is a physical diagram of a signal transceiver in a conductivity measurement system based on ground electrode current field communication and sensing, as described in an embodiment of the present invention. Detailed Implementation

[0018] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0019] Example 1: This example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing, such as... Figure 1 As shown, it includes: S1: Simultaneously collect the induced voltage of the underground current field at multiple calibration measurement points based on the receiving channel of the L-shaped electrode array, and obtain the first channel original signal and the second channel original signal of each calibration measurement point; S2: Perform signal preprocessing on the first channel raw signal and the second channel raw signal of each calibration measurement point respectively. Perform sliding correlation operation between the preset synchronization head template and the preprocessed two channel signals respectively. Determine the position of the synchronization head in the received signal according to the peak position in the correlation sequence of each channel. Based on the synchronization head position, extract a fixed length of effective signal to obtain the first channel effective signal and the second channel effective signal of each calibration measurement point. S3: Perform vector synthesis on the first channel effective signal and the second channel effective signal of each calibration measurement point to obtain the synthesized total response signal of each calibration measurement point; S4: Select the target measurement point with the smallest measured conductivity value among all calibration measurement points, and use the synthetic total response signal corresponding to the target measurement point as the reference signal. Calculate the consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal. S5: Using the consistency correlation coefficient of each calibration point as the input feature and the measured conductivity value of each calibration point as the output label, train the support vector regression model; S6: At the test location, repeat steps S1-S3 to obtain the synthetic total response signal at the test location, and calculate the consistency correlation coefficient between the synthetic total response signal and the reference signal selected in step S4 to obtain the consistency correlation coefficient at the test location. Then, input the coefficient into the support vector regression model and output the conductivity measurement value at the test location.

[0020] In this embodiment, the execution flow of a conductivity measurement method based on the integration of ground electrode current field communication and sensing includes transmitter signal injection, underground medium propagation, receiver dual-channel acquisition, feature extraction (consistency correlation coefficient), regression model, and conductivity output. A schematic diagram of the conductivity measurement principle is shown below. Figure 2 As shown.

[0021] In this embodiment, a schematic diagram illustrating the comparison between the signal to be measured and a reference standard in a conductivity measurement method based on the integration of ground electrode current field communication and sensing is shown below. Figure 3 As shown.

[0022] In this embodiment, the L-shaped electrode array refers to a receiving electrode group consisting of three buried electrodes arranged in a specific spatial relationship. The first electrode serves as a common electrode, and the first and second electrodes form a first receiving channel. The first and third electrodes form a second receiving channel, with their arrangement directions perpendicular to each other and the electrode spacing between the two channels being equal. The electrodes are inserted vertically into the ground during installation. The electrode spacing between the two channels is set to a preset value. Through this orthogonal arrangement, the two receiving channels can simultaneously acquire the electric field components of the underground current field in two mutually perpendicular directions. A detailed schematic diagram is shown below. Figure 4 As shown.

[0023] In this embodiment, the calibration points refer to the various data acquisition locations reached by the measurement unit moving point by point along a preset survey line at a fixed step size during the model building phase. The measurement unit consists of a transmitter and a receiver, whose relative positions remain fixed. The transmitter-receiver interval is set to a preset threshold, and the unit moves point by point along the survey line at a preset threshold step size. Upon reaching each calibration point, the signal transmitter injects a signal into the ground, and the signal receiver simultaneously acquires the response signals from both channels. At the same time, a soil conductivity meter is used to obtain the measured conductivity value at that location.

[0024] In this embodiment, the first channel raw signal refers to the unprocessed induced voltage time series collected by the first receiving channel (between the first electrode and the second electrode) in the L-shaped electrode array; the second channel raw signal refers to the unprocessed induced voltage time series collected by the second receiving channel (between the first electrode and the third electrode).

[0025] In this embodiment, signal preprocessing refers to DC bias correction and FIR bandpass filtering of the original signal. DC bias correction is to subtract the time mean of the acquired original signal to eliminate the DC component in the signal. The passband range of the FIR bandpass filter is determined according to the center frequency of the transmitted signal. The order of the FIR bandpass filter can be set to 128, and it is designed using the window function method to suppress DC components, power frequency interference at the center frequency, and out-of-band noise.

[0026] In this embodiment, the synchronization header template refers to a time-series signal with known waveform characteristics that is pre-designed and stored at the signal receiver, used to locate the starting position of valid data in the received signal. The original sampling rate of the synchronization header template is a first value (e.g., 2000Hz). Before performing sliding correlation operations with the received signal, it needs to be resampled to a second value (e.g., 500Hz) to keep it consistent with the sampling rate of the received data.

[0027] In this embodiment, the sliding correlation operation refers to the process of using the synchronization header template as a sliding window, sliding it point by point on the preprocessed received signal sequence, and calculating the cross-correlation coefficient between the synchronization header template and the corresponding segment of the received signal at each sliding position. Specifically, let the length of the synchronization header template sequence be M and the length of the received signal sequence be N (N>M). At the k-th sampling point of the received signal, the segment from k to k+M-1 is taken and the correlation coefficient is calculated with the synchronization header template to obtain the correlation sequence R(k), where k=1,2,...,N-M+1. The peak position in the correlation sequence corresponds to the best matching position of the synchronization header in the received signal. After determining the position of the synchronization head in the received signal, on the one hand, a fixed-length signal segment is extracted from the optimal matching position as the effective signal for calculating the consistency correlation coefficient and measuring conductivity. On the other hand, the receiving end determines the starting boundary of the communication data frame based on the synchronization head position, and then demodulates the signal segment after the synchronization head according to the preset communication protocol to recover the original communication signal sent by the transmitting end, thereby realizing underground information transmission. Thus, after the synchronization head is located, the same received signal segment can both demodulate the communication data according to the preset protocol and output the conductivity measurement value after vector synthesis and CCC calculation. Both share the same received signal and the same synchronization head location result, without interfering with each other.

[0028] In this embodiment, the valid signal refers to a signal segment carrying useful information, which is intercepted based on the position of the synchronization head in the received signal. After determining the peak position of the synchronization head, a signal segment of a fixed length (e.g., 2500 sampling points) is intercepted from that position as the valid signal. The sampling rate of the received signal is a preset frequency value (e.g., 500Hz), so the length of the intercepted valid signal is 5 seconds. The two receiving channels use the same synchronization positioning and fixed-length interception method to ensure that the data length and time position are consistent between different channels, different measurement points, and the reference signal.

[0029] In this embodiment, vector synthesis refers to the process of combining the effective signals of two orthogonal receiving channels into a single overall response signal according to the principle of vector superposition. Specifically, taking the sampling time axis of the first channel's effective signal as a reference, the instantaneous amplitude of the second channel's effective signal at the same sampling moment is extracted, and the instantaneous amplitude of the first channel's effective signal at the same sampling moment is used as the basis for further analysis. Instantaneous amplitude of the effective signal of the second channel According to the formula Calculate the synthesized instantaneous amplitude at the current sampling moment. Repeat the above calculation point by point for all sampling moments to obtain the synthesized total response signal waveform composed of all synthesized instantaneous amplitudes, the length of which is equal to the length of the effective signal of the first channel or the effective signal of the second channel.

[0030] In this embodiment, the reference signal refers to the synthetic total response signal corresponding to the target measuring point with the smallest measured conductivity value among all calibration measuring points. The measured conductivity values ​​of each calibration measuring point are sorted, and the measuring point with the smallest measured conductivity value is selected. The synthetic total response signal of this measuring point is set as the reference signal. The reference signal serves as a reference origin for measuring the deviation of the received signals from other measuring points.

[0031] In this embodiment, the consistency correlation coefficient is a dimensionless index used to measure the degree of consistency between two sets of signals. This coefficient comprehensively considers the differences between the two sets of signals in three dimensions: mean, variance, and trend. Its value range is [-1, 1], where a value of 1 indicates that the two sets of signals are completely consistent, a value of -1 indicates that they are completely inconsistent, and a value of 0 indicates that they are independent of each other.

[0032] In this embodiment, the receiving channels are two mutually perpendicular ones, and the induced voltage is in two orthogonal directions of the underground current field.

[0033] In this embodiment, once the reference signal in step S4 is determined, it is stored in the data processing terminal. In step S6, when calculating the consistency correlation coefficient for all test locations, the same reference signal is called. The reference signal remains unchanged before recalibration.

[0034] The beneficial effects of the above technical solution are as follows: By using the same set of ground electrode current field communication equipment and the same receiving signal, information demodulation and dielectric conductivity measurement are completed synchronously. Through dual-channel synchronous acquisition and vector synthesis processing of the L-shaped electrode array, the amplitude measurement deviation caused by the inconsistency between the receiving electrode layout direction and the actual electric field direction can be effectively reduced, making the extracted signal features more accurately reflect the changes in dielectric conductivity. By using the consistency correlation coefficient to quantify the overall deviation of the received signal from the reference signal, it can comprehensively reflect the differences in signal mean, variance and trend of change, providing stable input features for conductivity measurement. At the same time, by using the support vector regression model to establish a nonlinear mapping relationship between the consistency correlation coefficient and conductivity, accurate output of conductivity can be achieved under the condition of limited sample size.

[0035] Example 2: Based on Example 1, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing. In S1, the induced voltage of the underground current field is synchronously collected at multiple calibration measurement points using a receiving channel based on an L-shaped electrode array, including: The L-shaped electrode array consists of a first electrode, a second electrode, and a third electrode. The first electrode serves as a common electrode. The first electrode and the second electrode form a first receiving channel, and the first electrode and the third electrode form a second receiving channel. The arrangement directions of the first receiving channel and the second receiving channel are perpendicular to each other, and the electrode spacing between the two channels is equal.

[0036] In this embodiment, a schematic diagram of the ground electrode current field based on an integrated conductivity measurement method combining ground electrode current field communication and sensing is shown below. Figure 6 As shown.

[0037] In this embodiment, the L-shaped electrode array refers to a receiving electrode group consisting of three buried electrodes arranged in a specific spatial relationship. The first electrode serves as a common electrode, and the first and second electrodes form a first receiving channel. The first and third electrodes form a second receiving channel. The first and second receiving channels are arranged perpendicularly to each other, and the electrode spacing between the two channels is equal. The electrodes are inserted vertically into the ground during installation, with a burial depth maintained at a preset value, for example, 300 mm. The electrode spacing between the two channels is set to a preset value, for example, 1 m. Through this orthogonal arrangement, the two receiving channels can simultaneously acquire the electric field components of the underground current field in two mutually perpendicular directions.

[0038] In this embodiment, the first electrode refers to the common electrode in the L-shaped electrode array, which is buried at the center of the receiving end and forms two receiving channels with the second electrode and the third electrode respectively. During the measurement process, it serves as a common reference end for the two signals.

[0039] In this embodiment, the second electrode refers to the receiving electrode in the L-shaped electrode array that forms a first receiving channel with the first electrode. The burial direction and the line connecting the first electrode form a first direction, which is used to collect the electric field component of the underground current field in that direction.

[0040] In this embodiment, the third electrode refers to the receiving electrode in the L-shaped electrode array that forms the second receiving channel with the first electrode. The burial direction and the line connecting the first electrode form the second direction, which is perpendicular to the first direction. It is used to collect the electric field component of the underground current field in the direction orthogonal to the first direction.

[0041] In this embodiment, the common electrode refers to the electrode in the L-shaped electrode array that serves as a common reference point for both receiving channels. Its physical location is at the inflection point of the L-shaped array. The induced voltages of both channel one and channel two are measured with reference to this electrode, so that the response signals acquired by the two channels have a unified reference standard in time and space.

[0042] In this embodiment, the perpendicularity of the arrangement direction means that the line connecting the first electrode and the second electrode and the line connecting the first electrode and the third electrode form a 90° angle in space. The orthogonal arrangement allows the two receiving channels to collect the electric field components of the underground current field in two orthogonal directions, thereby providing spatially orthogonal projection components for subsequent vector synthesis.

[0043] In this embodiment, equal electrode spacing between the two channels means that the physical distance between the first and second electrodes is equal to the physical distance between the first and third electrodes. Using the same spacing between the two channels ensures that both receiving channels have the same gain under the same electric field strength, guaranteeing consistent weights for the two components during vector synthesis and avoiding amplitude measurement deviations caused by differences in channel gain.

[0044] In this embodiment, both the transmitting and receiving electrodes are made of stainless steel, with a length of 400mm and a diameter of 10mm. They are vertically inserted into the ground at a depth of 300mm during installation. The transmit / receive distance between the transmitting and receiving ends is fixed at 5m. During measurement, they are moved point-by-point along the measurement line as a single measurement unit. Standardizing electrode size, burial depth, and transmit / receive distance helps reduce the impact of differences in electrode contact conditions and propagation distances between different measurement points on the received signal.

[0045] The working principle and beneficial effects of the above technical solution are as follows: By orthogonally arranging three electrodes in an L-shaped electrode array, the orthogonal components of the underground current field are synchronously acquired using two mutually perpendicular receiving channels. In subsequent vector synthesis calculations, the two orthogonal components can be restored to the true electric field strength independent of the azimuth angle of the receiving array. This eliminates the amplitude loss caused by the inconsistency between the electrode connection direction and the electric field direction during single-channel reception, ensuring that the extracted signal characteristics mainly reflect the changes in the conductivity of the underground medium rather than the changes in the receiving end layout direction. This guarantees the stability and comparability of the measurement results at different measuring points and with different layout orientations. Simultaneously, the two channels use the same electrode spacing, ensuring consistent response gain under the same electric field excitation, thus enabling direct vector synthesis. Before the system is put into actual measurement, a one-time inter-channel gain calibration can control the residual gain error between channels within a preset range (e.g., ±0.01dB). Afterward, gain calibration is not required for each measuring point during on-site measurements.

[0046] Example 3: Based on Example 1, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing. The signal preprocessing in S2 includes: DC bias correction and FIR bandpass filtering, wherein the passband range of the FIR bandpass filter is determined according to the center frequency of the transmitted signal, and is used to suppress DC components, power frequency interference and out-of-band noise.

[0047] In this embodiment, DC bias correction refers to the process of subtracting the time mean of the acquired original signal to make the signal zero-mean. Because the receiver front-end analog circuit may have a DC offset, the acquired signal contains a certain DC component. This DC component does not carry dielectric electrical information, and if it directly participates in subsequent processing, it will affect the accuracy of the signal characteristics. By calculating the average value of each channel signal in the time domain, and subtracting this average value from each sampling point of the original signal, a zero-mean signal is obtained, thereby eliminating the interference of the DC component on subsequent correlation calculations and feature extraction.

[0048] In this embodiment, FIR bandpass filtering refers to the process of selecting the frequency band of a signal using a finite-length unit impulse response filter, retaining only signal components within a specified frequency range and suppressing frequency components outside the passband. The FIR filter has linear phase characteristics, ensuring that the waveform of the filtered signal is not distorted and avoiding the introduction of nonlinear phase that could affect the accuracy of subsequent consistency correlation coefficient calculations. In this embodiment, the order of the FIR bandpass filter can be optionally set to 128, and it is designed using the window function method.

[0049] In this embodiment, the passband range refers to the frequency range that the FIR bandpass filter allows to pass through. Signal components within this range are preserved, while signal components outside the range are suppressed. The passband range is determined based on the center frequency of the transmitted signal to ensure that components within the effective signal band can pass through the filter without attenuation. In this embodiment, the center frequency of the transmitted signal is 10Hz. The passband range of the FIR bandpass filter is set to 8–12Hz, with an order of 128. It is designed using a window function method, allowing components within the effective signal band to pass through the filter without attenuation, while simultaneously suppressing 50Hz power line interference and other out-of-band noise.

[0050] In this embodiment, power frequency interference refers to the interference component that couples into the received signal from electromagnetic radiation generated by a power system, such as a 50Hz AC power system. Its frequency is fixed at 50Hz, but may be 60Hz in different countries, and its amplitude may be much larger than the effective signal. Since the effective signal's frequency band range in this embodiment is 8–12Hz (center frequency 10Hz), the power frequency interference (50Hz) is outside the passband and can be effectively suppressed by FIR bandpass filtering.

[0051] In this embodiment, out-of-band noise refers to the general term for various interference signals whose frequencies are outside the effective signal passband, including but not limited to environmental electromagnetic noise, circuit thermal noise, and crosstalk from other wireless signals. The frequency components of these noises are usually distributed over a wide frequency band. By filtering out the frequency components outside the passband through FIR bandpass filtering, the signal-to-noise ratio can be significantly improved.

[0052] In this embodiment, the center frequency of the transmitted signal refers to the nominal frequency of the extremely low-frequency current field signal injected by the transmitter into the underground medium, which is 10Hz in this embodiment. The center frequency of the transmitted signal serves as the basis for setting the passband range of the bandpass filter. The passband range should cover the main lobe energy concentration area of ​​the transmitted signal to ensure maximum retention of the effective signal.

[0053] In this embodiment, the signal transmitter injects a 100V, 10Hz center frequency, and 5s duration MSK signal into the underground medium. Since the transmitted signal lasts 5s, the receiver extracts the effective signal based on this duration, corresponding to 2500 sampling points. The signal receiver's sampling rate is set to 500Hz to ensure oversampling of the 10Hz center frequency signal and effectively suppress 50Hz power frequency aliasing. The original sampling rate of the synchronization header template is 2000Hz; before performing sliding correlation calculations with the received signal, it needs to be resampled to 500Hz to match the sampling rate of the received data.

[0054] The working principle and beneficial effects of the above technical solution are as follows: DC offset correction eliminates the DC offset introduced by the receiver front-end circuit, avoids interference of DC components on peak detection in subsequent sliding correlation operations, and ensures the accuracy of synchronization head positioning; FIR bandpass filtering sets the passband range to a narrow band range centered on the center frequency of the transmitted signal, while suppressing DC components, 50Hz power frequency interference and broadband environmental noise, significantly improving the signal-to-noise ratio of the received signal, and providing a clean signal basis for reliable detection of effective peaks and accurate calculation of consistency correlation coefficients in subsequent sliding correlation operations.

[0055] Example 4: Based on Example 1, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing. In S2, the first channel raw signal and the second channel raw signal of each calibration point are preprocessed respectively. The preset synchronization head template is used to perform sliding correlation operation with the preprocessed two channel signals respectively. The position of the synchronization head in the received signal is determined according to the peak position in the correlation sequence of each channel. Based on the synchronization head position, a fixed length of effective signal is extracted to obtain the first channel effective signal and the second channel effective signal of each calibration point, including: The first channel original signal and the second channel original signal of each calibration measurement point are acquired. The first channel original signal and the second channel original signal are then subjected to DC bias correction and bandpass filtering respectively to obtain the filtered first channel original signal and the second channel original signal. The synchronization head template is resampled to the same sampling rate as the filtered original signals of the first and second channels. The resampled synchronization head template is then subjected to sliding correlation operation with the filtered original signals of the first and second channels to obtain the correlation coefficient sequence for each channel. The peak positions in the correlation coefficient sequences of each channel are detected respectively. Each peak position is used as the starting position of the synchronization head in the received signal of each channel. Based on the starting position of each channel, a signal segment of fixed time length is extracted from the filtered signal of the corresponding channel as the first channel effective signal and the second channel effective signal of the calibration measurement point. The original signals of the first and second channels use the same synchronous positioning and fixed-length truncation method to ensure that the effective signals of different channels and different measurement points are consistent in data length and time position.

[0056] In this embodiment, the peak position refers to the sliding position number corresponding to the element with the maximum value in the correlation coefficient sequence. When the synchronization head template slides to be exactly aligned with the synchronization head waveform in the received signal, the overlap between the two waveforms is the highest, and the correlation coefficient reaches its maximum value, which is represented by a distinct peak in the correlation coefficient sequence. The index position of this peak in the sequence is the starting sampling point position of the synchronization head in the received signal.

[0057] In this embodiment, the starting position refers to the sequence number of the starting sampling point of the synchronization header waveform on the time axis of the received signal. After determining this starting position based on the peak position in the correlation coefficient sequence, it becomes clear from which sampling point of the received signal the effective signal begins, thus providing an accurate positioning reference for subsequent truncation operations.

[0058] In this embodiment, the fixed length refers to the total number of valid signal sampling points truncated from the start position of the synchronization header. This length is predetermined based on the duration of the transmitted signal and the sampling rate of the received signal. In this embodiment, the duration of the transmitted signal is 5 seconds, and the sampling rate of the received signal is 500 Hz; therefore, the fixed length is 2500 sampling points. The fixed length remains consistent across different measurement points and channels to ensure that all signal segments involved in subsequent calculations have the same data length.

[0059] In this embodiment, synchronous positioning refers to the use of the same synchronization header detection and positioning method for both channels. That is, both channels use the same synchronization header template, the same sliding correlation calculation method, and the same peak detection criterion to determine the starting position of the synchronization header in their respective channels. Through synchronous positioning, it is ensured that the effective signals captured by the two channels originate from the same phase position of the same transmitted signal frame in time.

[0060] In this embodiment, fixed-length truncation refers to both channels truncating signal segments from their respective synchronization header starting positions by the same fixed length. Fixed-length truncation ensures that the valid signals truncated by both channels have the same data length.

[0061] In this embodiment, consistent data length means that the total number of sampling points of the effective signal in the first channel is equal to the total number of sampling points of the effective signal in the second channel. Consistent data length is a prerequisite for subsequent vector synthesis operations, because vector synthesis requires point-by-point calculation on the sampling points of the two channels at the same time. If the data lengths of the two channels are inconsistent, point-by-point correspondence cannot be achieved.

[0062] In this embodiment, time-position consistency means that the effective signals of the first and second channels have the same start time and the same time span on the time axis. Since the two channels use synchronous sampling, and the synchronous positioning and fixed-length truncation methods are the same, the two truncated effective signals are strictly aligned in time, and the sampling points corresponding to the same sequence number value come from the same moment. Time-position consistency guarantees the correspondence of the two instantaneous amplitudes at the same sampling moment in subsequent vector synthesis operations.

[0063] The working principle and beneficial effects of the above technical solution are as follows: by using the same synchronous positioning and fixed-length interception method for the two channels, the effective signals of different channels and different measurement points are kept consistent in terms of data length and time position. This provides a dual-channel signal that is strictly aligned in time for subsequent vector synthesis calculations, avoiding vector synthesis errors caused by inconsistencies in the data length or time position of the two channels. This ensures that the synthesized total response signal can accurately reflect the electric field components in two orthogonal directions at the same moment.

[0064] Example 5: Based on Example 1, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing. In S3, the effective signals of the first channel and the effective signals of the second channel at each calibration point are vector-synthesized to obtain the synthesized total response signal for each calibration point, including: S31: Using the sampling time axis of the first channel valid signal as a reference, extract the instantaneous amplitude of the first channel valid signal and the second channel valid signal at the same sampling moment; S32: Perform vector synthesis based on the instantaneous amplitude of the first channel valid signal and the instantaneous amplitude of the second channel valid signal at the same sampling time to obtain the synthesized instantaneous amplitude at the current sampling time. ; in, This represents the instantaneous amplitude of the first channel's valid signal corresponding to the i sampling times; This represents the instantaneous amplitude of the valid signal in the second channel corresponding to the i sampling times; This represents the composite instantaneous amplitude corresponding to the i sampling times; i represents the sequence number of the sampling times. S33: Repeat steps S31-S32 point by point for all sampling times to obtain the composite total response signal waveform composed of all composite instantaneous amplitudes, wherein the length of the composite total response signal waveform is equal to the length of the first channel effective signal or the second channel effective signal.

[0065] In this embodiment, using the sampling time axis as a reference means using the sampling time point of the first channel's valid signal as a time reference standard to determine the sampled value in the second channel's valid signal corresponding to that time point. Since the two channels use synchronous sampling, the two signals have the same sampling time sequence on the time axis. Therefore, the i-th sampling time of the first channel and the i-th sampling time of the second channel are strictly corresponding in time and can be directly paired point by point.

[0066] In this embodiment, the instantaneous amplitude refers to the instantaneous voltage value of the effective signal waveform at a specific sampling moment. For digital signals, the instantaneous amplitude is the numerical value corresponding to the sampling point. This represents the instantaneous amplitude of the effective signal of the first channel at the i-th sampling time. This represents the instantaneous amplitude of the valid signal of the second channel at the i-th sampling moment. The instantaneous amplitudes of the two signals at the same sampling moment constitute a two-dimensional vector. , which represents the electric field components of the underground current field in two orthogonal directions at that moment.

[0067] In this embodiment, the sampling time sequence number i represents the sequential number of each sampling point in the valid signal waveform, i = 1, 2, ..., L, where L is the total number of sampling points of the valid signal. The sampling time sequence number is used to identify the correspondence between the two channel signals on the time axis; sampling points with the same sequence number value belong to the same time. Taking the valid signal of the first channel as a reference, the instantaneous amplitudes of the two channels at the same sampling time, that is, those with the same sequence number value i, are paired and then participate in vector synthesis. and The instantaneous amplitude at that moment is synthesized by combining the square root of the square, thereby ensuring that the point-to-point correspondence between the two signals is accurate.

[0068] In this embodiment, the instantaneous amplitude is synthesized. This refers to combining the instantaneous amplitudes of two orthogonal directions at the same sampling moment into a single scalar value using the principle of vector superposition. The scalar value is equal to the square root of the sum of the squares of the two orthogonal components. The synthesized instantaneous amplitude is numerically equivalent to the total electric field intensity of the underground current field at that moment, and is independent of the azimuth angle of the electrode array. As a scalar value, it has no directional attribute and can be directly used as one-dimensional time series data for subsequent consistency correlation coefficient calculation.

[0069] In this embodiment, the synthesized total response signal waveform refers to a one-dimensional time series composed of the synthesized instantaneous amplitudes at all sampling times arranged in chronological order, denoted as E(n), where n = 1, 2, ..., L. Each sampling point of the synthesized total response signal waveform... For each sampling moment, the entire waveform reflects the complete information of the change of electric field intensity at the measuring point over time.

[0070] In this embodiment, the length of the synthesized total response signal waveform being equal to the length of the first channel effective signal or the second channel effective signal means that if the first channel effective signal has L sampling points and the second channel effective signal has L sampling points, then after performing vector synthesis point-by-point at L time points, the output result will also have L sampling points, and all three signals will have the same number of sampling points. Equal length is a prerequisite for comparing the two sets of signals in the subsequent consistency correlation coefficient calculation, because the consistency correlation coefficient calculation requires both sets of signals to have the same number of sampling points to ensure point-by-point correspondence.

[0071] The working principle and beneficial effects of the above technical solution are as follows: by extracting the instantaneous amplitude of the second channel at the same moment based on the sampling time axis of the effective signal of the first channel, the strict alignment of the two signals on the time axis is ensured; furthermore, by performing vector synthesis of the square root of the sum of the squares of the instantaneous amplitudes in two orthogonal directions at the same moment, a total response amplitude independent of the electrode layout orientation is obtained, eliminating the amplitude loss introduced by the inconsistency between the electrode connection direction and the electric field direction during single-channel reception; on this basis, the total response signal waveform with the same length as the original signal is synthesized point by point at all sampling moments, and the total response signal waveform can be directly used as the input for the calculation of the consistency correlation coefficient, realizing the complete conversion from dual-channel orthogonal components to a total response signal waveform independent of orientation.

[0072] Example 6: Based on Example 1, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing. In S4, the target measurement point with the smallest measured conductivity value is selected from all calibration measurement points, and the synthetic total response signal corresponding to the target measurement point is used as the reference signal. The consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal is calculated, including: The measured conductivity values ​​of each calibration point are sorted according to the decreasing order of the measured conductivity values. The point with the smallest measured conductivity value is selected, and the synthesized total response signal of the point with the smallest measured conductivity value is set as the reference signal. Using the reference signal as the comparison object, the synthetic total response signal of each calibration point is compared with the reference signal point by point according to the sampling time, and the covariance between the two sets of signals, the variance of the reference signal, the variance of the current calibration point signal, the mean of the reference signal, and the mean of the current calibration point signal are calculated. Based on the covariance between the two sets of signals of the composite total response signal of the reference signal and the current calibration point, the variance of the reference signal, the variance of the current calibration point signal, the mean of the reference signal, and the mean of the current calibration point signal, the consistency correlation coefficient of each calibration point relative to the reference signal is calculated, and the consistency correlation coefficient of the reference point itself is 1. ; in, This represents the consistency correlation coefficient of the current calibration measurement point relative to the reference signal; The covariance between the two sets of signals representing the reference signal and the synthesized total response signal of the current calibration measurement point; Represents the variance of the reference signal; This represents the variance of the synthesized total response signal at the current calibration measurement point; Represents the mean of the reference signal; This represents the mean value of the current calibration measurement points.

[0073] In this embodiment, covariance refers to a statistic used to measure the consistency of the changing trends between two sets of signals. Specifically, it is the expected value of the product of the deviations of the reference signal and the synthesized total response signal at the current calibration point from their respective mean values. A positive covariance indicates that the two sets of signals are changing in the same direction, while a negative covariance indicates that they are changing in opposite directions. In this embodiment, the covariance is calculated point-by-point from the reference signal and the signal under test according to the sampling time, and is used to quantify the similarity of the waveform trends of the two sets of signals.

[0074] In this embodiment, variance refers to a statistical measure of the dispersion of the instantaneous amplitude of each sampling point of the signal relative to its mean, specifically the average of the squares of the differences between the instantaneous amplitude of each sampling point and the mean. A larger variance indicates more drastic fluctuations in signal amplitude, while a smaller variance indicates a more stable signal. In this embodiment, the variance of the reference signal and the variance of the signal at the current calibration point are calculated separately to quantify the amplitude fluctuations of the two sets of signals.

[0075] In this embodiment, the mean refers to the arithmetic mean of the instantaneous amplitudes of all sampling points of the signal, representing the DC component or overall offset level of the signal. In this embodiment, the mean of the reference signal and the mean of the signal at the current calibration measurement point are calculated respectively. The difference between the two sets of signal means reflects the degree of offset of the signal in terms of the overall amplitude level.

[0076] In this embodiment, the decreasing order of measured conductivity values ​​refers to arranging the conductivity values ​​measured by the soil conductivity meter at each calibration point from largest to smallest. The point at the end of the arrangement is the point with the smallest measured conductivity value. Since the attenuation effect of the underground medium on the current field signal is weakest when the conductivity is lowest, and the degree of received signal distortion is minimal, the synthesized total response signal at this point is closest to the original signal shape at the transmitting end, and therefore it is selected as the benchmark measuring point.

[0077] In this embodiment, the reference measurement point refers to the measurement point with the smallest measured conductivity value among all calibration measurement points. The synthesized total response signal of this measurement point is set as the reference signal, and its consistency correlation coefficient with the reference signal is mathematically always equal to 1, because any signal is completely consistent with itself.

[0078] In this embodiment, The consistency correlation coefficient, representing the current calibration point's correlation with the reference signal, is a dimensionless index ranging from -1 to 1. A smaller value indicates a greater degree of distortion in the current measurement point's signal relative to the reference signal, and consequently, a higher dielectric conductivity at the corresponding measurement point. The consistency correlation coefficient comprehensively reflects the overall deviation of the measured signal from the reference signal in three dimensions: amplitude attenuation, waveform distortion, and mean shift.

[0079] This embodiment The covariance represents the difference between the reference signal and the synthesized total response signal at the current calibration point. The covariance is calculated as follows: For each sampling time, the two signals are mapped point-by-point. At each sampling time, the mean of each signal is subtracted from the mean of the two signals, and the products are multiplied together. The sum of all products is then divided by the number of sampling points minus one to obtain the covariance value. The covariance reflects the consistency of the changing trends of the two signals.

[0080] In this embodiment, The variance of the reference signal is specifically calculated by squared the difference between the instantaneous amplitude of each sampling point and the mean of the reference signal, summing all the squared values, and dividing by the number of sampling points minus one. The variance reflects the degree of fluctuation of the reference signal amplitude around its mean.

[0081] In this embodiment, The variance of the synthesized total response signal at the current calibration point is specifically calculated by squared the difference between the instantaneous amplitude of each sampling point of the signal at the current measurement point and the mean of the signal at the current measurement point, summing all the squared values, and dividing by the number of sampling points minus one. The variance reflects the degree of fluctuation of the amplitude of the signal at the current measurement point around its mean.

[0082] In this embodiment, This represents the mean value of the current calibration measurement point. Specifically, it is obtained by summing the instantaneous amplitude values ​​of all sampling points of the current measurement point signal and dividing by the number of sampling points to obtain the overall DC offset level of the current measurement point signal.

[0083] In this embodiment, The mean of the reference signal is represented by summing the instantaneous amplitudes of all sampling points of the reference signal and dividing by the number of sampling points to obtain the overall DC offset level of the reference signal. This reflects the degree of difference between the two sets of signals at the DC offset level.

[0084] In this embodiment, the denominator of the consistency correlation coefficient is composed of the sum of three terms: the variance of the reference signal, the variance of the current measurement point signal, and the square of the difference between their means. The variances of the reference signal and the current measurement point signal reflect the degree of fluctuation of the two sets of signals, respectively, while the square of the difference between their means reflects the overall amplitude shift of the two sets of signals. A larger denominator indicates a greater difference in the degree of fluctuation or amplitude level between the two sets of signals. The numerator is twice the covariance, reflecting the consistency of the changing trends of the two sets of signals. A larger ratio of numerator to denominator indicates greater consistency between the two sets of signals. Mathematically, the consistency correlation coefficient naturally requires the numerator to not exceed the denominator. According to the above formula, The theoretical range is [-1, 1]. When the two sets of signals are completely identical, When the two sets of signals are perfectly negatively correlated, .

[0085] The working principle and beneficial effects of the above technical solution are as follows: By selecting the measurement point with the smallest measured conductivity value from multiple calibration measurement points as the benchmark point, a stable reference origin is obtained by utilizing the physical characteristic that signal distortion is minimal when conductivity is lowest. This allows the CCC values ​​of the remaining measurement points to exhibit a monotonically changing trend with increasing conductivity, starting from this reference origin, thus providing input features with clear physical meaning for the regression model. Furthermore, through the joint characterization of covariance, variance, and mean difference, compared to methods using only a single amplitude or single correlation index, the consistency correlation coefficient can simultaneously capture information from three dimensions: signal waveform trend, amplitude fluctuation, and DC offset level. This significantly improves the correlation with dielectric conductivity, providing stable and reliable input features for the subsequent support vector regression model.

[0086] Example 7: Based on Example 6, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing. After calculating the consistency correlation coefficient of each calibration point relative to the reference signal, it further includes: Determine whether the consistency correlation coefficient of each calibration point decreases monotonically with the measured conductivity value; based on the ascending order of the measured conductivity values ​​of each calibration point, check whether the corresponding consistency correlation coefficient shows a monotonically decreasing trend; if a non-monotonically decreasing measurement point is found, the measurement point with the largest deviation from the overall trend in the change of the consistency correlation coefficient relative to adjacent measurement points is taken as an abnormal measurement point, and the consistency correlation coefficient and measured conductivity value of the abnormal measurement point are treated as invalid data and removed. If the consistency correlation coefficient of each calibration measurement point decreases monotonically with the measured conductivity value, then each calibration measurement point is paired with the measured conductivity value of the same measurement point according to the consistency correlation coefficient of each calibration measurement point relative to the reference signal to form feature-label sample pairs. The support vector regression model is trained based on feature-label sample pairs.

[0087] In this embodiment, monotonically decreasing refers to the trend that the dependent variable, i.e., the consistency correlation coefficient, decreases as the independent variable, i.e., the measured value of conductivity, increases. In this embodiment, when the measured conductivity values ​​of each calibration point are arranged from low to high, the corresponding consistency correlation coefficient should show a monotonically decreasing trend from high to low, such as... Figure 5 As shown, the consistency correlation coefficient (CCC) generally decreases with increasing measured conductivity, indicating a stable inverse relationship between CCC and conductivity within the range of 0.1–0.5 mS / cm. This monotonicity allows for a stable regression mapping between CCC and conductivity, providing a data foundation for the effective training of subsequent support vector regression models.

[0088] In actual measurements, due to factors such as electrode contact conditions and local soil heterogeneity, the CCC values ​​of individual measuring points may deviate from the overall trend. When non-monotonic decreasing points appear, the rate of change of the CCC value of each non-monotonic point relative to the CCC values ​​of its adjacent measuring points is calculated, and the point with the largest rate of change deviating from the overall trend is prioritized for elimination. Only one point with the most severe deviation is eliminated at a time. After elimination, the monotonicity of the remaining measuring points is re-evaluated until the remaining measuring points satisfy the monotonically decreasing relationship or the number of remaining samples is lower than a preset lower limit (e.g., 3). If the number of samples after elimination still meets the training requirements, it is used for subsequent model training; if the number of samples is insufficient, the quality of paired samples should be re-examined or the calibration range expanded.

[0089] In this embodiment, for example, the feature-tag sample pairs can be collected under the conditions of a fixed distance between the transmitter and receiver, consistent electrode embedding depth, and a measured conductivity range of 0.1 to 0.5 mS / cm. It should be noted that the above experimental conditions are only specific experimental conditions used in the verification process of this invention, and are used to exemplify the implementation effect of this invention, and do not constitute a limitation on the scope of protection of this invention. When the above conditions change significantly, it is only necessary to supplement the calibration samples under the corresponding conditions and retrain the regression model; the method steps described in this invention will still apply.

[0090] In this embodiment, invalid data refers to measurement point data pairs acquired during the calibration process that fail to meet the monotonicity constraint due to abnormal signal quality or calculation errors. Specifically, it refers to the paired data of the consistency correlation coefficient and the measured conductivity value of the measurement point. Sources of invalid data may include abnormal received signal distortion caused by factors such as poor electrode contact, local environmental interference, and uneven soil medium. If such data is not removed and directly used for model training, it will reduce the prediction accuracy of the regression model.

[0091] In this embodiment, "removal" refers to removing invalid measurement data points from the training sample set, preventing them from participating in the subsequent training of the support vector regression model. The removal operation only targets individual outlier measurement points and does not affect the normal use of the remaining valid measurement data. After removal, the remaining valid data still satisfies the monotonicity constraint and can be used for model training.

[0092] In this embodiment, a feature-label sample pair refers to a training data unit consisting of a pair of input features and an output label. In this embodiment, the input feature is the consistency correlation coefficient (CCC) of the calibrated measurement point, and the output label is the measured conductivity value of that measurement point. The CCC of each calibrated measurement point is paired with a measured conductivity value to form a set of feature-label sample pairs. All feature-label sample pairs of the calibrated measurement points constitute the training sample set, used for training the support vector regression model.

[0093] In this embodiment, one-to-one pairing refers to associating the consistency correlation coefficient calculated for the same calibration point with the measured conductivity value of that point obtained by the soil conductivity meter according to the point correspondence, ensuring that the input features and output labels come from the same measurement point and the same measurement. One-to-one pairing is a basic requirement for constructing supervised learning training data. If the pairing is incorrect (such as pairing the CCC of measurement point A with the conductivity of measurement point B), the model will learn an incorrect mapping relationship, which will seriously affect the model's prediction accuracy.

[0094] The working principle and beneficial effects of the above technical solution are as follows: By introducing a monotonicity judgment mechanism after the consistency correlation coefficient is calculated, measurement point data that do not meet the monotonicity constraint are removed as invalid data. This ensures that all feature-label sample pairs entering the model training satisfy the basic physical law that the consistency correlation coefficient decreases monotonically with the increase of conductivity. This avoids outlier samples from polluting the training set due to abnormal factors such as poor electrode contact and local interference, thereby improving the training quality and prediction accuracy of the support vector regression model. By pairing the consistency correlation coefficient of effective measurement points with the measured conductivity values ​​to form feature-label sample pairs, accurate aligned training data is provided for subsequent supervised learning. This ensures that the mapping relationship learned by the model can truly reflect the influence of changes in dielectric conductivity on the characteristics of the received signal.

[0095] Example 8: Based on Example 7, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing. In S5, the consistency correlation coefficient of each calibration measurement point is used as the input feature, and the measured conductivity value of each calibration measurement point is used as the output label to train a support vector regression model, including: Read the feature-label sample pairs of each calibration measurement point. Each feature-label sample pair is composed of a consistency correlation coefficient as the input feature and the measured conductivity value as the output label. The feature-label samples of each calibration point are input into the support vector regression model for training, as shown in the following formula: ; in, This represents the conductivity output by the support vector regression model. This represents the consistency correlation coefficient to be input into the support vector regression model; This represents the input feature value corresponding to the i-th support vector; Represents the kernel function; Indicates the index value of the support vector; This represents the total number of support vectors; This represents the first weight coefficient corresponding to the i-th support vector; Let represent the second weight coefficient corresponding to the i-th support vector, and and Determined by the training process of the support vector regression model; With the coefficient of determination As an evaluation metric for model fit, the trained support vector regression model is evaluated, and the model parameters after training are saved.

[0096] In this embodiment, This represents the input feature value corresponding to the i-th support vector, which is the consistency correlation coefficient of the calibration measurement point where the i-th support vector is located.

[0097] In this embodiment, This represents the input feature value corresponding to the i-th support vector, which is the consistency correlation coefficient of the calibration measurement point where the i-th support vector is located.

[0098] In this embodiment, a feature-label sample pair refers to a training data unit consisting of a pair of input features and an output label. In this embodiment, the input feature is the consistency correlation coefficient (CCC) of the calibrated measurement point, and the output label is the measured conductivity value of that measurement point. The CCC of each calibrated measurement point is paired with a measured conductivity value to form a set of feature-label sample pairs. All feature-label sample pairs of the calibrated measurement points constitute the training sample set, used for training the support vector regression model.

[0099] In this embodiment, This represents the consistency correlation coefficient to be input into the support vector regression model. In this embodiment, the input feature is the consistency correlation coefficient (CCC) of the calibrated measurement points, and the output label is the measured conductivity value of the calibrated measurement points. Each calibrated measurement point's CCC is paired with a measured conductivity value to form a set of feature-label sample pairs. The feature-label sample pairs of all calibrated measurement points constitute the training sample set, which is used to train the support vector regression model.

[0100] In this embodiment, This represents the kernel function, used to compute the input features of the sample to be predicted. Input features of the i-th support vector The similarity or correlation between features. The kernel function maps input features from the original feature space to a high-dimensional feature space, making a non-linearly separable mapping in the original space linearly separable in the high-dimensional space. In this embodiment, the radial basis function (RBF) kernel function can be optionally used. A larger kernel function value indicates... and The greater the similarity, the greater the impact of the support vectors on the current prediction result.

[0101] In this embodiment, This represents the first weight coefficient corresponding to the i-th support vector; Let represent the second weight coefficient corresponding to the i-th support vector, and and The difference between the two is determined by the training process of the support vector regression model. The effective weight coefficients that constitute the i-th support vector determine the direction and magnitude of the i-th support vector's contribution to the final regression function. When Greater than When the weights are equal, the support vector contributes positively and has a positive impact on the regression function; otherwise, the contribution is negative. The larger the absolute value of the weight coefficient, the greater the influence of the support vector on the shape of the regression curve.

[0102] In this embodiment, the coefficient of determination The dimensionless index is used to measure the goodness of fit of a regression model. It ranges from 0 to 1 and reflects the degree to which the model explains the variance of the training data. The closer the value is to 1, the better the model fit. In this embodiment, The calculation formula is: ,in Let be the measured conductivity value at the i-th measuring point. This is the model's predicted conductivity value for this measurement point. The average of the measured conductivity values ​​at all measuring points is calculated after training. The value of 0.9162 indicates that the model can explain 91.62% of the variation between CCC and dielectric conductivity, and the model fits the sample data well.

[0103] In this embodiment, the model parameters refer to the data that needs to be saved after the support vector regression model is trained, including the input feature values ​​corresponding to each support vector. The first weight coefficients corresponding to each support vector Second weighting coefficient And the bias b (0.2644 in this embodiment). After saving these parameters in the data processing terminal, the model can be directly called to calculate the corresponding conductivity prediction value for the new input CCC value during the actual measurement stage, without the need for repeated training.

[0104] The working principle and beneficial effects of the above technical solution are as follows: By using the consistency correlation coefficient as a single input feature and the measured conductivity value as the output label, a nonlinear mapping relationship between the two is established using a support vector regression model. Leveraging the good generalization performance of SVR under small sample conditions, a stable regression model can still be obtained even in scenarios with a limited number of calibration samples. Furthermore, by introducing a coefficient of determination... As an evaluation index of model fit, it provides a quantitative standard for judging model quality. After training, it stores the support vectors, their weight coefficients, and biases. During field testing, it can directly call the values ​​to output the predicted conductivity value, avoiding repeated complex calculations on site.

[0105] Example 9: Based on Example 8, this example provides a conductivity measurement method based on the integration of ground electrode current field communication and sensing, using the measured conductivity values ​​at each calibration point as output tags, including: The measured conductivity values ​​of each calibration point were obtained in the following way: multiple measurements were taken at each calibration point using a soil conductivity meter, and the arithmetic mean of the multiple measurements was taken as the measured conductivity value of the calibration point.

[0106] In this embodiment, the soil conductivity meter refers to a portable instrument used to measure the electrical conductivity of soil. It applies an alternating voltage to the measured medium by inserting a metal probe into the soil and measures the response current. The conductivity value of the medium is then calculated according to Ohm's law. In this embodiment, the soil conductivity meter can optionally be a JQ-008 high-precision soil detector. This instrument is equipped with a 127mm metal probe, a conductivity measurement range of 0.00–10.00 mS / cm, a resolution of 0.01 mS / cm, and a measurement accuracy of ±2%FS. During use, the metal probe is vertically inserted into the soil to be tested, ensuring close contact between the probe and the soil before reading the conductivity value. The soil conductivity meter is only used during the calibration phase to obtain the measured conductivity values ​​at each measuring point as training labels; it is not needed in subsequent field testing.

[0107] In this embodiment, multiple measurements refer to repeatedly performing multiple independent conductivity measurements at each calibration point. Since soil is a non-uniform medium, a single measurement may contain random errors. By taking multiple measurements and averaging them, the impact of random measurement errors on the measured conductivity value can be effectively reduced, improving the accuracy of the training labels. In this embodiment, the number of measurements can be optionally set to 5.

[0108] In this embodiment, the arithmetic mean refers to the value obtained by adding up the conductivity readings from multiple measurements and dividing by the number of measurements. This value is used as the final measured conductivity value at that measurement point. For example, if the readings obtained from 5 consecutive measurements at a certain measurement point are... , , , , The final measured conductivity value The specific method for using the arithmetic mean is as follows: At each calibration measuring point, after the soil conductivity meter reading stabilizes, multiple measurements are taken and recorded. After all measurements at that measuring point are completed, all readings are added together and divided by the number of measurements. The quotient is taken as the measured conductivity value for that measuring point. Taking the average is the arithmetic mean operation in this embodiment. Compared to a single measurement, using the arithmetic mean effectively reduces the impact of random measurement errors on the measured conductivity value, ensuring higher accuracy of the measured conductivity value used as a model training label.

[0109] The working principle and beneficial effects of the above technical solution are as follows: By using a soil conductivity meter to perform multiple independent measurements at each measuring point during the calibration stage and taking the arithmetic mean, the random error that may be introduced by a single measurement is effectively eliminated, and more accurate measured conductivity values ​​are obtained as training labels for the model. This method does not rely on the ground electrode current field communication system, and is carried out synchronously and independently with the communication signal acquisition. This ensures a one-to-one correspondence between the communication signal and the measured conductivity value in terms of measuring point location and measurement time, and provides high-quality training output labels for the support vector regression model, thereby improving the learning accuracy and generalization performance of the regression model.

[0110] Example 10: This example provides a conductivity measurement system based on the integration of ground electrode current field communication and sensing, such as... Figure 7 As shown, it includes: The signal acquisition module is used to synchronously acquire the induced voltage of the underground current field at multiple calibration points based on the receiving channel of the L-shaped electrode array, and obtain the first channel original signal and the second channel original signal of each calibration point. The effective signal determination module is used to preprocess the first channel original signal and the second channel original signal of each calibration measurement point, perform sliding correlation operation between the preset synchronization head template and the preprocessed two channel signals, determine the position of the synchronization head in the received signal according to the peak position in the correlation sequence of each channel, and extract a fixed length of effective signal based on the synchronization head position to obtain the first channel effective signal and the second channel effective signal of each calibration measurement point. The effective signal vector synthesis module is used to perform vector synthesis of the first channel effective signal and the second channel effective signal at each calibration measurement point to obtain the synthesized total response signal at each calibration measurement point; The consistency correlation coefficient determination module is used to select the target measurement point with the smallest measured conductivity value among all calibration measurement points, and use the synthetic total response signal corresponding to the target measurement point as the reference signal, and calculate the consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal respectively. The model training module is used to train a support vector regression model by using the consistency correlation coefficient of each calibration point as the input feature and the measured conductivity value of each calibration point as the output label. The result output module is used to control the signal acquisition module, the effective signal determination module, and the effective signal vector synthesis module to sequentially perform signal acquisition, signal preprocessing, and vector synthesis at the test location to obtain the synthesized total response signal at the test location. The module then calculates the consistency correlation coefficient between the synthesized total response signal and the selected reference signal to obtain the consistency correlation coefficient at the test location. This coefficient is then input into the support vector regression model to output the conductivity measurement value at the test location.

[0111] In this embodiment, a physical diagram of a specific signal transceiver corresponding to a conductivity measurement system based on ground electrode current field communication and sensing integration is shown below. Figure 8 As shown.

[0112] The beneficial effects of the above technical solution are as follows: By using the same set of ground electrode current field communication equipment and the same receiving signal, information demodulation and dielectric conductivity measurement are completed synchronously. Through dual-channel synchronous acquisition and vector synthesis processing of the L-shaped electrode array, the amplitude measurement deviation caused by the inconsistency between the receiving electrode layout direction and the actual electric field direction can be effectively reduced, making the extracted signal features more accurately reflect the changes in dielectric conductivity. By using the consistency correlation coefficient to quantify the overall deviation of the received signal from the reference signal, it can comprehensively reflect the differences in signal mean, variance and trend of change, providing stable input features for conductivity measurement. At the same time, by using the support vector regression model to establish a nonlinear mapping relationship between the consistency correlation coefficient and conductivity, accurate output of conductivity can be achieved under the condition of limited sample size.

[0113] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A conductivity measurement method based on integrated communication and sensing of ground electrode current field, characterized in that, include: S1: Simultaneously collect the induced voltage of the underground current field at multiple calibration measurement points based on the receiving channel of the L-shaped electrode array, and obtain the first channel original signal and the second channel original signal of each calibration measurement point; S2: Perform signal preprocessing on the first channel raw signal and the second channel raw signal of each calibration measurement point respectively. Perform sliding correlation operation between the preset synchronization head template and the preprocessed two channel signals respectively. Determine the position of the synchronization head in the received signal according to the peak position in the correlation sequence of each channel. Based on the synchronization head position, extract a fixed length of effective signal to obtain the first channel effective signal and the second channel effective signal of each calibration measurement point. S3: Perform vector synthesis on the first channel effective signal and the second channel effective signal of each calibration measurement point to obtain the synthesized total response signal of each calibration measurement point; S4: Select the target measurement point with the smallest measured conductivity value among all calibration measurement points, and use the synthetic total response signal corresponding to the target measurement point as the reference signal. Calculate the consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal. S5: Using the consistency correlation coefficient of each calibration point as the input feature and the measured conductivity value of each calibration point as the output label, train the support vector regression model; S6: At the test location, repeat steps S1-S3 to obtain the synthetic total response signal at the test location, and calculate the consistency correlation coefficient between the synthetic total response signal and the reference signal selected in step S4 to obtain the consistency correlation coefficient at the test location. Then, input the coefficient into the support vector regression model and output the conductivity measurement value at the test location.

2. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 1, characterized in that, In S1, the induced voltage of the underground current field is synchronously acquired at multiple calibration measuring points using a receiving channel based on an L-shaped electrode array, including: The L-shaped electrode array consists of a first electrode, a second electrode, and a third electrode. The first electrode serves as a common electrode. The first electrode and the second electrode form a first receiving channel, and the first electrode and the third electrode form a second receiving channel. The arrangement directions of the first receiving channel and the second receiving channel are perpendicular to each other, and the electrode spacing between the two channels is equal.

3. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 1, characterized in that, The signal preprocessing described in S2 includes: DC bias correction and FIR bandpass filtering, wherein the passband range of the FIR bandpass filter is determined according to the center frequency of the transmitted signal, and is used to suppress DC components, power frequency interference and out-of-band noise.

4. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 1, characterized in that, In S2, the original signals of the first and second channels at each calibration point are preprocessed. A preset synchronization head template is then used to perform sliding correlation operations with the preprocessed signals of the two channels. The position of the synchronization head in the received signal is determined based on the peak position in the correlation sequence of each channel. A fixed length of valid signal is then extracted based on the synchronization head position to obtain the first and second channel valid signals for each calibration point, including: The first channel original signal and the second channel original signal of each calibration measurement point are acquired. The first channel original signal and the second channel original signal are then subjected to DC bias correction and bandpass filtering respectively to obtain the filtered first channel original signal and the second channel original signal. The synchronization head template is resampled to the same sampling rate as the filtered original signals of the first and second channels. The resampled synchronization head template is then subjected to sliding correlation operation with the filtered original signals of the first and second channels to obtain the correlation coefficient sequence for each channel. The peak positions in the correlation coefficient sequences of each channel are detected respectively. Each peak position is used as the starting position of the synchronization head in the received signal of each channel. Based on the starting position of each channel, a signal segment of fixed time length is extracted from the filtered signal of the corresponding channel as the first channel effective signal and the second channel effective signal of the calibration measurement point. The original signals of the first and second channels use the same synchronous positioning and fixed-length truncation method to ensure that the effective signals of different channels and different measurement points are consistent in data length and time position.

5. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 1, characterized in that, In S3, the effective signals of the first channel and the effective signals of the second channel at each calibration point are vector-synthesized to obtain the synthesized total response signal for each calibration point, including: S31: Using the sampling time axis of the first channel valid signal as a reference, extract the instantaneous amplitude of the first channel valid signal and the second channel valid signal at the same sampling moment; S32: Perform vector synthesis based on the instantaneous amplitude of the first channel valid signal and the instantaneous amplitude of the second channel valid signal at the same sampling time to obtain the synthesized instantaneous amplitude at the current sampling time. ； in, This represents the instantaneous amplitude of the first channel's valid signal corresponding to the i sampling times; This represents the instantaneous amplitude of the valid signal in the second channel corresponding to the i sampling times; This represents the composite instantaneous amplitude corresponding to the i sampling times; i represents the sequence number of the sampling times. S33: Repeat steps S31-S32 point by point for all sampling times to obtain the composite total response signal waveform composed of all composite instantaneous amplitudes, wherein the length of the composite total response signal waveform is equal to the length of the first channel effective signal or the second channel effective signal.

6. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 1, characterized in that, In S4, the target measurement point with the smallest measured conductivity value is selected from all calibration measurement points, and the synthetic total response signal corresponding to the target measurement point is used as the reference signal. The consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal is calculated, including: The measured conductivity values ​​of each calibration point are sorted according to the decreasing order of the measured conductivity values. The point with the smallest measured conductivity value is selected, and the synthesized total response signal of the point with the smallest measured conductivity value is set as the reference signal. Using the reference signal as the comparison object, the synthetic total response signal of each calibration point is compared with the reference signal point by point according to the sampling time, and the covariance between the two sets of signals, the variance of the reference signal, the variance of the current calibration point signal, the mean of the reference signal, and the mean of the current calibration point signal are calculated. Based on the covariance between the two sets of signals of the composite total response signal of the reference signal and the current calibration point, the variance of the reference signal, the variance of the current calibration point signal, the mean of the reference signal, and the mean of the current calibration point signal, the consistency correlation coefficient of each calibration point relative to the reference signal is calculated, and the consistency correlation coefficient of the reference point itself is 1. ； in, This represents the consistency correlation coefficient of the current calibration measurement point relative to the reference signal; The covariance between the two sets of signals representing the reference signal and the synthesized total response signal of the current calibration measurement point; Represents the variance of the reference signal; This represents the variance of the synthesized total response signal at the current calibration measurement point; Represents the mean of the reference signal; This represents the mean value of the current calibration measurement points.

7. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 6, characterized in that, After calculating the consistency correlation coefficient of each calibration point relative to the reference signal, the method further includes: Determine whether the consistency correlation coefficient of each calibration point decreases monotonically with the measured conductivity value; based on the ascending order of the measured conductivity values ​​of each calibration point, check whether the corresponding consistency correlation coefficient shows a monotonically decreasing trend; if a non-monotonically decreasing measurement point is found, the measurement point with the largest deviation from the overall trend in the change of the consistency correlation coefficient relative to adjacent measurement points is taken as an abnormal measurement point, and the consistency correlation coefficient and measured conductivity value of the abnormal measurement point are treated as invalid data and removed. If the consistency correlation coefficient of each calibration measurement point decreases monotonically with the measured conductivity value, then each calibration measurement point is paired with the measured conductivity value of the same measurement point according to the consistency correlation coefficient of each calibration measurement point relative to the reference signal to form feature-label sample pairs. The support vector regression model is trained based on feature-label sample pairs.

8. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 7, characterized in that, In S5, the consistency correlation coefficient of each calibration point is used as the input feature, and the measured conductivity value of each calibration point is used as the output label to train a support vector regression model, including: Read the feature-label sample pairs of each calibration measurement point. Each feature-label sample pair is composed of a consistency correlation coefficient as the input feature and the measured conductivity value as the output label. The feature-label samples of each calibration point are input into the support vector regression model for training, as shown in the following formula: ； in, This represents the conductivity output by the support vector regression model. This represents the consistency correlation coefficient to be input into the support vector regression model; This represents the input feature value corresponding to the i-th support vector; Represents the kernel function; Indicates the index value of the support vector; This represents the total number of support vectors; This represents the first weight coefficient corresponding to the i-th support vector; Let represent the second weight coefficient corresponding to the i-th support vector, and and Determined by the training process of the support vector regression model; With the coefficient of determination As an evaluation metric for model fit, the trained support vector regression model is evaluated, and the model parameters after training are saved.

9. The conductivity measurement method based on ground electrode current field communication and sensing integration according to claim 8, characterized in that, The measured conductivity values ​​at each calibration point are used as output labels, including: The measured conductivity values ​​of each calibration point were obtained in the following way: multiple measurements were taken at each calibration point using a soil conductivity meter, and the arithmetic mean of the multiple measurements was taken as the measured conductivity value of the calibration point.

10. A conductivity measurement system based on integrated communication and sensing of ground electrode current field, characterized in that, include: The signal acquisition module is used to synchronously acquire the induced voltage of the underground current field at multiple calibration points based on the receiving channel of the L-shaped electrode array, and obtain the first channel original signal and the second channel original signal of each calibration point. The effective signal determination module is used to preprocess the first channel original signal and the second channel original signal of each calibration measurement point, perform sliding correlation operation between the preset synchronization head template and the preprocessed two channel signals, determine the position of the synchronization head in the received signal according to the peak position in the correlation sequence of each channel, and extract a fixed length of effective signal based on the synchronization head position to obtain the first channel effective signal and the second channel effective signal of each calibration measurement point. The effective signal vector synthesis module is used to perform vector synthesis of the first channel effective signal and the second channel effective signal at each calibration measurement point to obtain the synthesized total response signal at each calibration measurement point; The consistency correlation coefficient determination module is used to select the target measurement point with the smallest measured conductivity value among all calibration measurement points, and use the synthetic total response signal corresponding to the target measurement point as the reference signal, and calculate the consistency correlation coefficient between the synthetic total response signal of each calibration measurement point and the reference signal respectively. The model training module is used to train a support vector regression model by using the consistency correlation coefficient of each calibration point as the input feature and the measured conductivity value of each calibration point as the output label. The result output module is used to control the signal acquisition module, the effective signal determination module, and the effective signal vector synthesis module to sequentially perform signal acquisition, signal preprocessing, and vector synthesis at the test location to obtain the synthesized total response signal at the test location. The module then calculates the consistency correlation coefficient between the synthesized total response signal and the selected reference signal to obtain the consistency correlation coefficient at the test location. This coefficient is then input into the support vector regression model to output the conductivity measurement value at the test location.

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