A method for assisting correction of magnetoelectric method detection data using optical fiber technology

Abstract

The application relates to a method for correcting magnetoelectric method detection data by using optical fiber technology, and the method comprises the following steps: arranging a multi-source optical fiber sensor in a magnetoelectric method detection area to establish an optical fiber sensing network, wherein the magnetoelectric method detection area comprises magnetoelectric method detection points; synchronously collecting magnetoelectric method detection data and optical fiber sensing network monitoring data corresponding to a first time step and a second time step respectively; determining a correction range of each detection point in the magnetoelectric method detection area and a correction value distribution of each detection point in the correction range; identifying factors that interfere with the magnetoelectric method detection data according to the optical fiber sensing network monitoring data corresponding to the first time step and the second time step by using a wavelet transform algorithm and an adaptive filtering algorithm; and constructing a Kalman correction matrix. By using the method, interference factors can be accurately and efficiently identified and removed, and the accuracy and reliability of the magnetoelectric method detection data can be improved.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration technology, and in particular to a method and apparatus for using fiber optic technology to assist in the correction of magnetoelectric detection data. Background Technology

[0002] Magnetoelectric method is a geophysical exploration method that infers the electrical structure of underground media by measuring changes in natural electromagnetic fields. It utilizes natural electromagnetic fields as a source, measuring the electric and magnetic field components at the Earth's surface to calculate the resistivity distribution underground. Magnetoelectric measurements do not require grounding electrodes, are less affected by high-resistivity shielding layers, and can probe to great depths, enabling rapid and effective detection in complex environments. However, because the magnetic field signal measured by the magnetoelectric method is relatively weak and susceptible to environmental electromagnetic interference, it suffers from poor anti-interference capabilities, insufficient depth resolution, and low detection accuracy. Summary of the Invention

[0003] Therefore, it is necessary to provide a method and apparatus for assisting in the correction of magnetoelectric detection data using fiber optic technology, which can enhance the accuracy and reliability of magnetoelectric detection data and address the aforementioned technical problems.

[0004] In a first aspect, this application provides a method for correcting magnetoelectric detection data using fiber optic technology. This method involves performing steps S1-S5 to obtain a Kalman correction matrix for correcting the magnetoelectric detection data. Steps S1-S5 include:

[0005] Step S1: Deploy multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensing network, wherein the magnetoelectric detection area includes each magnetoelectric measurement point.

[0006] Step S2: Simultaneously collect magnetoelectric detection data and fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively.

[0007] Step S3: Based on the response characteristics of the fiber optic sensor corresponding to the first time step and the second time step, the relationship between optical wavelength drift and strain, the relationship between optical wavelength drift and magnetic field strength, and the resolution of magnetic field change, the correction range of each measuring point in the magnetoelectric detection area is determined, and the correction value distribution of each measuring point corresponding to the first time step and the second time step within the correction range is calculated respectively.

[0008] Step S4: Wavelet transform algorithm and adaptive filtering algorithm are used to identify factors that interfere with the magnetoelectric detection data based on the fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively.

[0009] Step S5: Based on the distribution of correction values ​​of each measuring point within the correction range corresponding to the first time step and the second time step, and the identified factors that interfere with the magnetoelectric detection data, construct a Kalman correction matrix. The Kalman correction matrix is ​​used to correct the magnetoelectric detection data.

[0010] In one embodiment, step S1, which involves deploying multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensing network, includes:

[0011] Fiber optic sensors that sense changes in at least one physical field are deployed along the magnetoelectric method survey line, so that the monitoring data of the fiber optic sensing network and the detection data of the magnetoelectric method are spatially aligned. The physical field changes include temperature, stress, and strain.

[0012] In one embodiment, the response characteristics of the fiber optic sensor corresponding to the first time step and the second time step in step S3 are as follows:

[0013] ;

[0014] in, The strain of the magnetostrictive rod in the fiber optic sensor at each time step is denoted as ; This represents the elongation of the magnetostrictive rod in the fiber optic sensor at each time step. The initial length of the magnetostrictive rod in the fiber optic sensor corresponds to each time step. It is the magnetostriction coefficient; This represents the magnitude of the applied magnetic field at each time step, i.e., the magnetic induction intensity.

[0015] In one embodiment, the optical wavelength drift and strain relationships corresponding to the first and second time steps in step S3 are as follows:

[0016] ;

[0017] in, This represents the wavelength shift of light at each time step. The wavelength of light; , The elastic-optical coefficient of the optical fiber; , The effective refractive index for the fundamental mode and higher-order modes; This represents the effective refractive index difference between the fundamental mode and higher-order modes.

[0018] In one embodiment, the relationship between the optical wavelength drift and the magnetic field strength corresponding to the first time step and the second time step in step S3 is as follows:

[0019] ;

[0020] in, This represents the wavelength shift of light at each time step. This represents the sensitivity coefficient of the fiber optic sensor.

[0021] In one embodiment, the magnetic field change resolutions corresponding to the first time step and the second time step in step S3 are as follows:

[0022] ;

[0023] in, The resolution of the magnetic field change corresponding to each time step; The mean square error of the light wavelength fluctuation.

[0024] In one embodiment, the correction range for each measuring point corresponding to the first time step and the second time step in step S3 is as follows:

[0025] ;

[0026] in, This represents the minimum magnetic field strength corresponding to each time step; This represents the maximum magnetic field strength corresponding to each time step.

[0027] In one embodiment, the distribution of correction values ​​for each measuring point corresponding to the first time step and the second time step in step S3 is as follows:

[0028] ;

[0029] in, This represents the average wavelength shift at each time step. This represents the standard deviation of the wavelength drift at each time step.

[0030] In one embodiment, step S5 includes:

[0031] Based on the magnetoelectric detection data corresponding to the second time step, the distribution of correction values ​​for each measuring point within the correction range, and the identified factors interfering with the magnetoelectric detection data, as well as the magnetoelectric detection data corresponding to the first time step, the distribution of correction values ​​for each measuring point within the correction range, and the identified factors interfering with the magnetoelectric detection data, a Kalman correction matrix is ​​constructed. The posterior estimate is output through a linear combination of prior estimation and measurement residuals. With water content as an intermediate variable, the weighted average of the correction range for each measuring point, the distribution of correction values ​​for each measuring point within the correction range, and the identified factors interfering with the magnetoelectric detection data is used as the final correction value.

[0032] Secondly, this application also provides a device for assisting in the correction of magnetoelectric detection data using fiber optic technology, comprising:

[0033] The fiber optic sensor network establishment module is used to deploy multi-source fiber optic sensors in the magnetoelectric detection area and establish a fiber optic sensor network, wherein the magnetoelectric detection area includes each magnetoelectric measurement point.

[0034] The data acquisition module is used to synchronously acquire magnetoelectric detection data and fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively.

[0035] The calibration numerical calculation module is used to determine the calibration range of each measuring point in the magnetoelectric detection area based on the response characteristics of the fiber optic sensor corresponding to the first time step and the second time step, the relationship between optical wavelength drift and strain, the relationship between optical wavelength drift and magnetic field strength, and the magnetic field change resolution, and to calculate the calibration numerical distribution of each measuring point within the calibration range corresponding to the first time step and the second time step, respectively.

[0036] The interference factor identification module is used to identify factors that interfere with the magnetoelectric detection data based on the fiber optic sensor network monitoring data corresponding to the first and second time steps, respectively, using wavelet transform algorithm and adaptive filtering algorithm.

[0037] The detection data correction module is used to construct a Kalman correction matrix based on the distribution of correction values ​​of each measuring point within the correction range corresponding to the first and second time steps, and the identified factors that interfere with the magnetoelectric detection data. The Kalman correction matrix is ​​used to correct the magnetoelectric detection data.

[0038] The aforementioned method and apparatus for assisting in the correction of magnetoelectric detection data using fiber optic technology involves: deploying multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensing network, wherein the magnetoelectric detection area includes various magnetoelectric measurement points; synchronously acquiring magnetoelectric detection data and fiber optic sensing network monitoring data corresponding to a first time step and a second time step; determining the correction range for each measurement point in the magnetoelectric detection area based on the response characteristics of the fiber optic sensors corresponding to the first and second time steps, as well as the relationships between optical wavelength drift and strain, optical wavelength drift and magnetic field strength, and magnetic field change resolution, and calculating the correction value distribution of each measurement point within the correction range corresponding to the first and second time steps; using wavelet transform and adaptive filtering algorithms to identify factors interfering with the magnetoelectric detection data based on the fiber optic sensing network monitoring data corresponding to the first and second time steps; and constructing a Kalman correction matrix based on the correction value distribution of each measurement point within the correction range corresponding to the first and second time steps and the identified factors interfering with the magnetoelectric detection data. The Kalman correction matrix is ​​used to correct the magnetoelectric detection data. This application utilizes a fiber optic sensor network to monitor environmental parameters in real time, enabling timely detection of factors that interfere with magnetoelectric detection data and improving the real-time performance and accuracy of data correction. Simultaneously, fiber optic sensing technology offers advantages such as resistance to electromagnetic interference and high sensitivity, effectively enhancing the precision, accuracy, reliability, and stability of magnetoelectric detection data. The method and field deployment structure of this application are simple, easy to implement, and have broad application prospects. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of data before the magnetoelectric method detection data is assisted in by fiber optic technology in one embodiment;

[0040] Figure 2 This is a schematic diagram of data after using fiber optic technology to assist in the correction of magnetoelectric detection data in one embodiment;

[0041] Figure 3 This is a flowchart illustrating a method for assisting in the correction of magnetoelectric detection data using fiber optic technology in one embodiment.

[0042] Figure 4 This is a schematic diagram of the fiber-optic assisted correction setup in one embodiment;

[0043] Figure 5 A schematic diagram of the demodulator structure in one embodiment. Figure 1 ;

[0044] Figure 6 A schematic diagram of the demodulator structure in one embodiment. Figure 2 ;

[0045] The following are the labels in the diagram: 1. Wire; 2. Electrode; 3. Optical fiber; 4. Ground surface; 5. Demodulator; 6. Current transmitter; 7. Computer; 8. Magnetometer probe; 9. Bluetooth antenna; 10. Indicator light; 11. Demodulation mode knob; 12. Display screen; 13. Magnetometer probe interface; 14. USB interface; 15. Voltage adjustment knob; 16. Switch; 17. Fiber optic interface. Detailed Implementation

[0046] The main advantages of the magnetoelectric method include no need for artificial sources, large detection depth, and sensitivity to high-resistivity layers, making it widely used in oil and gas exploration, mineral resource exploration, and geothermal exploration. However, in the magnetoelectric method, the magnetic field signal is usually weak and easily affected by environmental electromagnetic interference (such as industrial electromagnetic noise and atmospheric electromagnetic interference), leading to a decline in data quality. Therefore, the correction and denoising of magnetoelectric method data are key steps to improve detection accuracy.

[0047] Fiber optic sensing technology employs contact measurement, enabling the detection of minute changes in physical quantities. It also exhibits excellent electrical insulation and chemical stability, thus possessing advantages such as high detection accuracy and resolution, and strong anti-interference capabilities. To improve the detection accuracy and resolution of magnetoelectric methods when probing ultra-deep geological bodies, and to enhance the accuracy and reliability of magnetoelectric detection data, this application proposes a method for assisting in the correction of magnetoelectric detection data using fiber optic technology.

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0049] In one exemplary embodiment, a method for assisting in the correction of magnetoelectric detection data using fiber optic technology is provided, comprising:

[0050] Step S1: Deploy multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensing network, wherein the magnetoelectric detection area includes each magnetoelectric measurement point.

[0051] Step S2: Simultaneously collect magnetoelectric detection data and fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively.

[0052] Step S3: Based on the response characteristics of the fiber optic sensor corresponding to the first time step and the second time step, as well as the relationship between optical wavelength drift and strain, the relationship between optical wavelength drift and magnetic field strength, and the resolution of magnetic field change, determine the correction range of each measuring point in the magnetoelectric detection area, and calculate the distribution of correction values ​​of each measuring point within the correction range corresponding to the first time step and the second time step.

[0053] Step S4: Using wavelet transform algorithm and adaptive filtering algorithm, identify the factors that interfere with the magnetoelectric detection data based on the fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively.

[0054] For example, monitoring data from fiber optic sensor networks are analyzed to identify factors that may interfere with magnetoelectric detection data;

[0055] Step S5: Based on the distribution of correction values ​​of each measuring point within the correction range corresponding to the first time step and the second time step, and the identified factors that interfere with the magnetoelectric detection data, construct a Kalman correction matrix. The Kalman correction matrix is ​​used to correct the magnetoelectric detection data.

[0056] In an exemplary embodiment, step S1 involves deploying multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensing network. This includes deploying fiber optic sensors along the magnetoelectric measurement line to sense at least one physical field change, such that the monitoring data of the fiber optic sensing network is spatially aligned with the magnetoelectric detection data. The physical field change includes temperature, stress, and strain.

[0057] Specifically, establishing an optical fiber sensing network involves deploying optical fiber sensors along the magnetoelectric method survey line that can sense changes in physical fields such as temperature, stress, and strain, ensuring that the environmental parameters monitored in real time by the optical fiber sensing network are spatially aligned with the data detected by the magnetoelectric method.

[0058] Furthermore, magnetoelectric detection data and fiber optic sensor network monitoring data are collected simultaneously to ensure that the two data are synchronized in time.

[0059] Furthermore, by analyzing the response characteristics of the fiber optic sensor, and considering the relationship between optical wavelength drift and strain, magnetic field strength, and magnetic field change resolution, the correction range for each measuring point, as well as the distribution of correction values ​​within the correction range for each measuring point, were determined. When the correction value distributions of different measuring points overlapped, a weighted average was used as the fiber optic correction value for that point.

[0060] In an exemplary embodiment, the formula for calculating the response characteristics of the fiber optic sensor is:

[0061] ;

[0062] in, The strain of the magnetostrictive rod in the fiber optic sensor corresponds to the first and second time steps; The elongation of the magnetostrictive rod in the fiber optic sensor corresponds to the first time step and the second time step. The initial length of the magnetostrictive rod in the fiber optic sensor corresponds to the first time step and the second time step. It is the magnetostriction coefficient; It refers to the magnitude of the applied magnetic field corresponding to the first and second time steps. Specifically, it refers to the strain of the magnetostrictive rod. This represents the strain of a magnetostrictive material under the action of an applied magnetic field; the elongation of a magnetostrictive rod. This represents the length change of a magnetostrictive material under the influence of an applied magnetic field; the initial length of a magnetostrictive rod. Represents the original length of the magnetostrictive material; magnetostriction coefficient This represents the relationship between the strain of a magnetostrictive material and the strength of the applied magnetic field; the magnitude of the applied magnetic field. This indicates the strength of the magnetic field applied to the magnetostrictive material.

[0063] In an exemplary embodiment, the formula for calculating the relationship between optical wavelength drift and strain corresponding to the first time step and the second time step is as follows:

[0064] ;

[0065] in, This represents the wavelength shift of light corresponding to the first and second time steps. The wavelength of light; , The elastic-optical coefficient of the optical fiber; , The effective refractive index for the fundamental mode and higher-order modes; This represents the effective refractive index difference between the fundamental mode and higher-order modes.

[0066] Furthermore, the formula for calculating the relationship between optical wavelength drift and strain corresponding to the first and second time steps can also be expressed as:

[0067] ;

[0068] in, This represents the wavelength shift of light corresponding to the first and second time steps. This represents the contribution of the strain component to the relative change in effective refractive index, and is the wavelength shift measured by the fiber optic sensor. Converted to strain components and ; and This represents the strain component experienced by the fiber optic sensor.

[0069] In an exemplary embodiment, the formula for calculating the relationship between the optical wavelength drift and the magnetic field strength corresponding to the first time step and the second time step is as follows:

[0070] ;

[0071] in, This represents the wavelength shift of light corresponding to the first and second time steps. This represents the sensitivity coefficient of the fiber optic sensor. denoted as magnetic flux density.

[0072] In an exemplary embodiment, the formula for calculating the magnetic field change resolution corresponding to the first time step and the second time step is:

[0073] ;

[0074] in, This represents the resolution of the magnetic field change corresponding to the first and second time steps; The mean square error of optical wavelength jitter; This represents the sensitivity coefficient of the fiber optic sensor.

[0075] In an exemplary embodiment, the correction range can be expressed as:

[0076] ;

[0077] in, This represents the minimum magnetic field strength corresponding to the first and second time steps. This represents the maximum magnetic field strength corresponding to the first and second time steps.

[0078] Specifically, the calculation of the correction range needs to consider both the response characteristics of the fiber optic sensor and the resolution of the magnetic field change. Assume the minimum wavelength drift that the fiber optic sensor can detect is... The maximum wavelength shift is The corresponding range of magnetic field strength is as follows:

[0079] ;

[0080] ;

[0081] Therefore, the correction range can be expressed as:

[0082] ;

[0083] in, and These are determined by the minimum and maximum detectable wavelength shifts of the fiber optic sensor, respectively.

[0084] Furthermore, to calculate the correction range more accurately, the response characteristics of the fiber optic sensor and the resolution of the magnetic field change can be combined. Assuming the wavelength drift of the fiber optic sensor... It follows a normal distribution with a mean of . The standard deviation is Then the correction range can be expressed as:

[0085] ;

[0086] ;

[0087] in, This is a constant, typically taking the value 2 or 3, representing the range of the confidence interval. For example, when... At this point, the correction range covers approximately 95% of the wavelength drift. Therefore, the formula for calculating the correction range can be further expressed as:

[0088] ;

[0089] ;

[0090] Based on the above derivation, the final expression for the correction range is:

[0091] ;

[0092] in, This represents the average wavelength shift. This represents the standard deviation of the wavelength shift. This is the sensitivity coefficient.

[0093] In an exemplary embodiment, the probability model for correcting the numerical distribution can be expressed as:

[0094] ;

[0095] in, This is the average of the wavelength shifts corresponding to the first and second time steps; This represents the standard deviation of the wavelength shift corresponding to the first and second time steps.

[0096] Furthermore, assuming that within the correction range, the magnetic field strength from Increase to The corresponding wavelength shift range can be expressed as:

[0097] ;

[0098] Then each magnetic field strength Corresponding wavelength shift The probability distribution can be expressed as:

[0099] .

[0100] In an exemplary embodiment, step S4 employs wavelet transform and adaptive filtering algorithms to identify factors interfering with the magnetoelectric detection data based on the fiber optic sensor network monitoring data corresponding to the first and second time steps. Specifically, wavelet transform is a time-frequency analysis method that can decompose a signal into components of different scales, making it suitable for the analysis of non-stationary signals. The specific formula for wavelet transform is as follows:

[0101] ;

[0102] in, These are wavelet coefficients. For scale parameters, For translation parameters, These are wavelet basis functions.

[0103] Furthermore, adaptive filtering is a filtering method that automatically adjusts filter parameters based on the input signal, suitable for removing noise and interference. Specifically, the formula for adaptive filtering is:

[0104] ;

[0105] in, For filtered output, These are the filter coefficients. This is the input signal.

[0106] For example, factors that interfere with magnetoelectric method (MED) detection data include temperature changes, stress and strain changes, and environmental electromagnetic interference. Temperature fluctuations, in particular, affect the performance of fiber optic sensors, thus impacting the accuracy of MED detection data. For instance, during periods of significant diurnal temperature variation or seasonal changes, temperature changes detected by the fiber optic sensor may cause optical wavelength drift, affecting the measurement results of magnetic field strength. Analyzing temperature monitoring data within the fiber optic sensor network can identify the interference of temperature changes on the detection data. For example, suppose the fiber optic sensor detects a temperature increase from 15°C to 25°C, resulting in an increase of 0.5 nm in optical wavelength drift. By analyzing the relationship between temperature and optical wavelength drift, the degree of interference of temperature changes on MED detection data can be identified. Furthermore, stress and strain changes in the formation can affect the fiber optic sensor. For example, minor deformations or geological tectonic activity in the formation may cause changes in the strain of the fiber optic sensor, thus affecting the measurement of optical wavelength drift. By monitoring stress and strain data within the fiber optic sensor network, the interference of these factors on MED detection data can be identified. For example, suppose the fiber optic sensor detects a 10 MPa increase in stress, resulting in a 0.3 nm increase in optical wavelength drift. By analyzing the relationship between stress and optical wavelength drift, the interference of stress changes on magnetoelectric detection data can be identified. Furthermore, nearby high-voltage transmission lines, communication base stations, or large electrical equipment can generate strong electromagnetic fields, which can interfere with the weak magnetic field signals detected by magnetoelectric methods. Anomalies in magnetic field strength detected by the fiber optic sensing network can identify the presence of this interference. For instance, suppose the fiber optic sensor detects an increase in the monitored optical wavelength drift from 1550.0 nm to 1550.1 nm, resulting in a 5 μT increase in the monitored magnetic field strength. By analyzing the magnetic field response characteristics of the fiber optic sensor, the degree of electromagnetic interference affecting the magnetoelectric detection data can be identified.

[0107] In an exemplary embodiment, step S5 includes:

[0108] Combining the current time step's magnetoelectric detection data, the distribution of correction values ​​at each measuring point within the correction range, and the identified factors interfering with the magnetoelectric detection data, along with the previous time step's magnetoelectric detection data, a Kalman calibration matrix is ​​constructed. Moisture content is used as an intermediate variable. A posterior state estimate is constructed through a linear organization of prior estimates and weighted measurement variables and their predicted differences, and the results are then corrected. The weighted average of the fiber optic calibration value and the fiber-assisted magnetoelectric self-calibration value is used as the final calibration value. The fiber optic calibration value represents the correction range and the distribution of correction values ​​at each measuring point within the correction range, while the fiber-assisted magnetoelectric self-calibration value represents the identified factors interfering with the magnetoelectric detection data. For example, the first time step can be the previous time step, and the second time step can be the current time step.

[0109] Specifically, in step S5, the magnetoelectric detection data is corrected by constructing a Kalman correction matrix. Kalman filtering is a recursive filtering algorithm that estimates the system state through a weighted sum of prior estimates and measured values. The basic formula for Kalman filtering is as follows:

[0110] ;

[0111] ;

[0112] ;

[0113] ;

[0114] ;

[0115] in, For prior state estimation, To estimate the error covariance a priori, For Kalman gain, For posterior state estimation, To estimate the error covariance in the posterior timescale, Here is the state transition matrix. For the control matrix, For the observation matrix, For process noise covariance, To observe the noise covariance.

[0116] Furthermore, the image before correction is as follows: Figure 1 As shown, the corrected image is as follows Figure 2 As shown, the corrected contour map is denser, indicating that the corrected location and extent of leakage are more accurate.

[0117] In one embodiment, such as Figure 3 As shown, after determining the magnetoelectric method (MED) detection area, fiber optic sensors for temperature, stress, and strain are deployed at regular intervals along the longitudinal direction of the MED measurement line or at key locations within the detection area to establish a fiber optic sensor network. After the device is deployed, MED detection data and monitoring data from the fiber optic sensor network are collected simultaneously. On one hand, the monitoring data from the fiber optic sensor network (i.e., fiber optic monitoring data) is analyzed using signal processing algorithms such as wavelet transform and adaptive filtering to identify factors that may interfere with the MED detection data, and a Kalman correction matrix is ​​constructed to achieve self-calibration of the fiber optic-assisted MED detection data. On the other hand, the response characteristics of the fiber optic sensors are analyzed by examining the magnetic field excited by the MED method. The calibration range for each measurement point and the distribution of calibration values ​​within the calibration range for each measurement point (i.e., fiber optic calibration data) are determined based on the relationship between optical wavelength drift and strain, magnetic field strength, and magnetic field change resolution. When the calibration value distributions of different measurement points overlap, a weighted average is used as the fiber optic calibration value for that point. The weighted average of the fiber optic calibration data and the fiber optic-assisted MED self-calibration data is the final calibration value.

[0118] In one embodiment, a schematic diagram of the fiber-optic assisted correction deployment is shown below. Figure 4 As shown, two electrodes are inserted into the ground and connected to a current transmitter via wires to define the magnetoelectric detection area. The wires should be arranged in a "U" shape to facilitate noise reduction later. Along the longitudinal direction of the magnetoelectric survey line, optical fibers are pre-buried to a certain depth within the detection area according to engineering requirements. The optical fibers and the magnetometer probe are connected to a demodulator for data acquisition, and the acquired data is remotely transmitted to a computer via a Bluetooth antenna for real-time data processing and analysis. The demodulator structure is as follows. Figure 5 and Figure 6 As shown. Figure 4 Includes 1. wires, 2. electrodes, 3. optical fibers, 4. ground surface, 5. demodulator, 6. current transmitter, 7. computer, and 8. magnetometer probe. Figure 5 Includes Bluetooth antenna 9, indicator light 10, demodulation mode knob 11, display screen 12, magnetometer probe interface 13, USB interface 14, voltage adjustment knob 15, and switch 16. Figure 6 Includes fiber optic interface 17 and Bluetooth antenna 9.

[0119] In one embodiment, this application designs a method for assisting in the correction of magnetoelectric detection data using fiber optic technology, comprising the following steps: deploying multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensor network; synchronously acquiring magnetoelectric detection data and monitoring data from the fiber optic sensor network; determining the correction range for each measuring point and calculating the distribution of correction values ​​for each measuring point within the correction range; analyzing the monitoring data from the fiber optic sensor network to identify factors that may interfere with the magnetoelectric detection data; and constructing a Kalman correction matrix to correct the magnetoelectric detection data based on the correction data distribution and the identified interference factors. Compared with traditional technologies, this application has advantages such as real-time monitoring, resistance to strong electromagnetic interference, and high sensitivity, and can accurately and efficiently identify and eliminate interference factors, thereby improving the accuracy and reliability of magnetoelectric detection data.

[0120] At least some steps in the flowcharts involved in the embodiments described above may include multiple steps or multiple stages, which may be executed at different times, or may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0121] Based on the same inventive concept, this application also provides an apparatus for implementing the method of using fiber optic technology to assist in the correction of magnetoelectric detection data as described above. The solution provided by this apparatus is similar to the solution described in the above method. Therefore, the specific limitations of one or more apparatus embodiments for using fiber optic technology to assist in the correction of magnetoelectric detection data provided below can be found in the limitations of the method for using fiber optic technology to assist in the correction of magnetoelectric detection data above, and will not be repeated here.

[0122] In one exemplary embodiment, an apparatus for assisting in the correction of magnetoelectric detection data using fiber optic technology is provided, comprising:

[0123] The fiber optic sensor network establishment module is used to deploy multi-source fiber optic sensors in the magnetoelectric detection area and establish a fiber optic sensor network, wherein the magnetoelectric detection area includes each magnetoelectric measurement point.

[0124] The data acquisition module is used to synchronously acquire magnetoelectric detection data and fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively.

[0125] The calibration numerical calculation module is used to determine the calibration range of each measuring point in the magnetoelectric detection area based on the response characteristics of the fiber optic sensor corresponding to the first time step and the second time step, as well as the relationship between optical wavelength drift and strain, the relationship between optical wavelength drift and magnetic field strength, and the magnetic field change resolution, and to calculate the calibration numerical distribution of each measuring point within the calibration range corresponding to the first time step and the second time step.

[0126] The interference factor identification module is used to identify factors that interfere with the magnetoelectric detection data based on the fiber optic sensor network monitoring data corresponding to the first and second time steps, using wavelet transform and adaptive filtering algorithms.

[0127] The detection data correction module is used to construct a Kalman correction matrix based on the distribution of correction values ​​of each measuring point within the correction range corresponding to the first and second time steps, as well as the identified factors that interfere with the magnetoelectric detection data. The Kalman correction matrix is ​​used to correct the magnetoelectric detection data.

[0128] The various modules in the aforementioned device for assisting in the correction of magnetoelectric detection data using fiber optic technology can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0129] For those skilled in the art, various modifications and improvements can be made without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application shall be determined by the appended claims.

Claims

1. A method for assisting in the correction of magnetoelectric detection data using fiber optic technology, characterized in that, The method is used to perform steps S1-S5 to obtain the Kalman correction matrix and correct the magnetoelectric detection data, wherein steps S1-S5 include: Step S1: Deploy multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensing network, wherein the magnetoelectric detection area includes each magnetoelectric measurement point. Step S2: Simultaneously collect magnetoelectric detection data and fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively. Step S3: Based on the response characteristics of the fiber optic sensor corresponding to the first time step and the second time step, the relationship between optical wavelength drift and strain, the relationship between optical wavelength drift and magnetic field strength, and the resolution of magnetic field change, the correction range of each measuring point in the magnetoelectric detection area is determined, and the correction value distribution of each measuring point corresponding to the first time step and the second time step within the correction range is calculated respectively. Step S4: Wavelet transform algorithm and adaptive filtering algorithm are used to identify factors that interfere with the magnetoelectric detection data based on the fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively. Step S5: Based on the distribution of correction values ​​of each measuring point within the correction range corresponding to the first time step and the second time step, and the identified factors that interfere with the magnetoelectric detection data, construct a Kalman correction matrix. The Kalman correction matrix is ​​used to correct the magnetoelectric detection data.

2. The method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 1, characterized in that, Step S1, which involves deploying multi-source fiber optic sensors in the magnetoelectric detection area to establish a fiber optic sensing network, includes: Fiber optic sensors that sense changes in at least one physical field are deployed along the magnetoelectric method survey line, so that the monitoring data of the fiber optic sensing network and the detection data of the magnetoelectric method are spatially aligned. The physical field changes include temperature, stress, and strain.

3. The method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 1, characterized in that, The response characteristics of the fiber optic sensor corresponding to the first time step and the second time step in step S3 are as follows: ； in, The strain of the magnetostrictive rod in the fiber optic sensor corresponds to each time step; The elongation of the magnetostrictive rod in the fiber optic sensor corresponds to each time step. The initial length of the magnetostrictive rod in the fiber optic sensor corresponds to each time step. It is the magnetostriction coefficient; This represents the magnitude of the applied magnetic field at each time step, i.e., the magnetic induction intensity.

4. The method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 3, characterized in that, The optical wavelength drift and strain relationships corresponding to the first and second time steps in step S3 are as follows: ； in, This represents the wavelength shift of light at each time step. The wavelength of light; , The elastic-optical coefficient of the optical fiber; , The effective refractive index for the fundamental mode and higher-order modes; This represents the effective refractive index difference between the fundamental mode and higher-order modes.

5. The method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 4, characterized in that, The relationship between the optical wavelength drift and the magnetic field strength corresponding to the first and second time steps in step S3 is as follows: ； in, This represents the wavelength shift of light at each time step. This represents the sensitivity coefficient of the fiber optic sensor.

6. The method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 5, characterized in that, The magnetic field change resolutions corresponding to the first and second time steps in step S3 are as follows: ； in, The resolution of the magnetic field change corresponding to each time step; The mean square error of the light wavelength fluctuation.

7. The method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 6, characterized in that, The correction range for each measuring point corresponding to the first time step and the second time step in step S3 is as follows: ； in, This represents the minimum magnetic field strength corresponding to each time step; This represents the maximum magnetic field strength corresponding to each time step.

8. A method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 7, characterized in that, The distribution of correction values ​​for each measuring point corresponding to the first time step and the second time step in step S3 is as follows: ； in, This represents the average wavelength shift at each time step. This represents the standard deviation of the wavelength shift corresponding to each step size.

9. A method for assisting in the correction of magnetoelectric detection data using fiber optic technology according to claim 1, characterized in that, Step S5 includes: Based on the magnetoelectric detection data of the second time step, the distribution of correction values ​​at each measuring point within the correction range, and the identified factors interfering with the magnetoelectric detection data, as well as the magnetoelectric detection data of the first time step, the distribution of correction values ​​at each measuring point within the correction range, and the identified factors interfering with the magnetoelectric detection data, a Kalman correction matrix is ​​constructed. The posterior estimate is output through a linear combination of prior estimation and measurement residuals. With water content as an intermediate variable, the weighted average of the correction range at each measuring point, the distribution of correction values ​​at each measuring point within the correction range, and the identified factors interfering with the magnetoelectric detection data is used as the final correction value.

10. A device for assisting in the correction of magnetoelectric method detection data using fiber optic technology, characterized in that, The device includes: The fiber optic sensor network establishment module is used to deploy multi-source fiber optic sensors in the magnetoelectric detection area and establish a fiber optic sensor network, wherein the magnetoelectric detection area includes each magnetoelectric measurement point. The data acquisition module is used to synchronously acquire magnetoelectric detection data and fiber optic sensor network monitoring data corresponding to the first time step and the second time step, respectively. The calibration numerical calculation module is used to determine the calibration range of each measuring point in the magnetoelectric detection area based on the response characteristics of the fiber optic sensor corresponding to the first time step and the second time step, the relationship between optical wavelength drift and strain, the relationship between optical wavelength drift and magnetic field strength, and the magnetic field change resolution, and to calculate the calibration numerical distribution of each measuring point within the calibration range corresponding to the first time step and the second time step, respectively. The interference factor identification module is used to identify factors that interfere with the magnetoelectric detection data based on the fiber optic sensor network monitoring data corresponding to the first and second time steps, respectively, using wavelet transform algorithm and adaptive filtering algorithm. The detection data correction module is used to construct a Kalman correction matrix based on the distribution of correction values ​​of each measuring point within the correction range corresponding to the first and second time steps, and the identified factors that interfere with the magnetoelectric detection data. The Kalman correction matrix is ​​used to correct the magnetoelectric detection data.

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