A method for analyzing the thickness of cobalt-rich crusts for in-situ detection

Abstract

The present invention relates to the technical field of deep-sea resource exploration, and in particular to a crust thickness analysis method for in-situ detection of cobalt-rich crusts, comprising the following steps: S1: measuring and recording the magnetic field strength and direction of the current area, and establishing initial magnetic field data; S2: identifying abnormal magnetic field fluctuation areas; S3: shielding the measurement fluctuation area using a magnetic shielding layer preset around the equipment; S4: adjusting the amplitude and phase of the received acoustic wave signal to eliminate or reduce the signal deviation caused by the magnetic field change; S5: obtaining a comprehensive echo signal representing the crust thickness; S6: calculating the thickness of the cobalt-rich crust; S7: generating a crust thickness distribution map. The present invention, through multi-band acoustic wave fusion, real-time magnetic field correction and thickness distribution map generation technology, realizes high-precision anti-interference measurement and intuitive visualization of the thickness of the cobalt-rich crust, providing reliable data support for deep-sea resource development.

Description

Technical Field

[0001] The present invention relates to the technical field of deep sea resource exploration, and in particular to a crust thickness analysis method for in-situ detection of cobalt-rich crusts. Background Art

[0002] With the increasing global demand for deep-sea resources, cobalt-rich crusts have become an important target for deep-sea mineral resource development because they are rich in rare metals such as cobalt and nickel. The thickness of cobalt-rich crusts is a key parameter in resource evaluation and development decisions, and directly affects the estimation of resource reserves and the formulation of mining plans. However, cobalt-rich crusts are distributed in complex deep-sea environments, usually in areas with strong magnetic field interference and variable hydrological conditions, which brings many challenges to thickness measurement. Current detection technologies mostly rely on acoustic wave measurement. Although acoustic wave technology has good penetration in deep-sea environments, it is easily disturbed in environments with strong magnetic field fluctuations, resulting in data deviations. In addition, changes in sound velocity in deep-sea environments will also affect the accuracy of thickness measurements and cannot provide stable and reliable data support. Therefore, in order to achieve high-precision cobalt-rich crust thickness measurement, a technical solution that can overcome magnetic field interference and adapt to complex seabed environments is urgently needed.

[0003] The existing technology has great limitations in measuring the thickness of cobalt-rich crusts, especially in complex magnetic field environments. It is difficult to achieve effective anti-interference processing of acoustic signals. At the same time, the continuity and accuracy of thickness data are not fully guaranteed. Existing equipment is difficult to generate intuitive and complete thickness distribution maps, which affects the visual interpretation of data. Based on this, a thickness analysis method for cobalt-rich crusts is proposed to solve the above problems. Summary of the invention

[0004] Based on the above purpose, the present invention provides a crust thickness analysis method for in-situ detection of cobalt-rich crusts.

[0005] A method for analyzing the thickness of cobalt-rich crusts for in-situ detection, comprising the following steps:

[0006] S1: Arrange the detection equipment in the target seabed area, start the equipment to collect preliminary environmental magnetic field data, measure and record the magnetic field strength and direction of the current area through sensors, and establish initial magnetic field data as a reference for subsequent detection;

[0007] S2: While starting the thickness detection, continuously monitor the magnetic field changes in the detection area, compare the real-time collected magnetic field data with the initial magnetic field data to identify the abnormal magnetic field fluctuation area, and mark the time and regional location of the abnormal fluctuation in the data record;

[0008] S3: When an abnormal magnetic field fluctuation area is detected, the magnetic shielding layer preset around the device is used to shield the measurement fluctuation area to block the interference of the external magnetic field on the sensor;

[0009] S4: Based on the real-time collected magnetic field change data, analyze the specific impact of magnetic field interference on the acoustic wave signal, and adjust the amplitude and phase of the received acoustic wave signal to eliminate or reduce the signal deviation caused by the magnetic field change;

[0010] S5: Use multi-band acoustic wave transmission technology to transmit acoustic wave signals of multiple frequencies to the target area in sequence and receive echo signals of each frequency band; at the same time, perform independent denoising on the signals of each frequency band to screen out clear signals that are not disturbed by the magnetic field, and fuse the signals of different frequency bands to obtain a comprehensive echo signal representing the thickness of the crust;

[0011] S6: Based on the processed integrated echo signal, measure the time difference from the emission to the reception of the sound wave, and calculate the thickness of the cobalt-rich crust in combination with the seabed sound velocity data. According to the specific situation of the real-time magnetic field changes, dynamically adjust the parameters in the calculation to ensure the accuracy of the thickness measurement;

[0012] S7: After the thickness measurement is completed, a crust thickness distribution map is generated, and the measurement results and thickness data are transmitted to the ground terminal through an output device.

[0013] Optionally, the S1 specifically includes:

[0014] S11: Place the detection device in the target seabed area, and start the data acquisition mode through the built-in three-axis magnetic field sensor, so that the sensor measures the surrounding magnetic field signals at a fixed sampling frequency to obtain the data of the magnetic field strength and direction of the target seabed area;

[0015] S12: converting the magnetic field signal detected by the three-axis magnetic field sensor into numerical data, and decomposing the magnetic field signal into components in three directions, namely, magnetic field strength in the vertical direction, horizontal north-south direction, and horizontal east-west direction, through a signal processing unit of the device;

[0016] S13: Continuously collect magnetic field data within a certain period of time at a fixed sampling frequency, and smooth the collected data of multiple sampling points to calculate the average magnetic field value after smoothing, thereby eliminating sudden interference of a single measurement;

[0017] S14: Integrate the smoothed data to generate initial magnetic field data for the current seabed area, and use this data as benchmark data for subsequent detection.

[0018] Optionally, the S2 specifically includes:

[0019] S21: When the detection device starts the thickness detection, the real-time magnetic field monitoring function is turned on to obtain the magnetic field strength and direction of the detection area at a fixed sampling frequency, and the real-time magnetic field data collected each time is stored in the data processing unit so as to be compared with the initial magnetic field data one by one;

[0020] S22: Calculate each magnetic field intensity value in the real-time collected magnetic field data with the corresponding intensity value in the initial magnetic field data to find the difference between the two to identify magnetic field fluctuations. The difference calculation formula is: ΔB = B t -B0, where B t represents the magnetic field intensity value collected in real time, B0 represents the initial magnetic field intensity value, and ΔB represents the amplitude of magnetic field fluctuation; if ΔB exceeds the preset threshold, it is judged as abnormal magnetic field fluctuation;

[0021] S23: For data determined to be abnormal magnetic field fluctuations, the time T and spatial position P of the fluctuation are recorded, wherein T is obtained through the internal clock of the data processing unit and indicates the time when the abnormal fluctuation occurs; P indicates the current coordinate position of the detection equipment on the seabed, which is provided by the positioning system of the detection equipment;

[0022] S24: The recorded time T, spatial position P and corresponding magnetic field fluctuation amplitude ΔB of the abnormal magnetic field fluctuation are stored in an abnormal record file for future use.

[0023] Optionally, the S3 specifically includes:

[0024] S31: After detecting an abnormal magnetic field fluctuation area, start the magnetic shielding control system, activate the preset magnetic shielding layer, and put the magnetic shielding layer into a working state. The magnetic shielding layer surrounds the sensor of the detection equipment to form a shielding space;

[0025] S32: The magnetic shielding layer is made of Permalloy or nickel-iron alloy material, and is used to absorb and guide external abnormal magnetic field signals, reduce the penetration strength of the magnetic field, and thus shield the interference of the external magnetic field on the sensor;

[0026] S33: When the magnetic shielding layer is in working state, an internal stable magnetic field environment is generated, so that the sensor of the detection equipment is only affected by the magnetic field in the shielding space, ensuring that the signal received by the sensor is not disturbed by external magnetic field fluctuations;

[0027] S34: After the shielding is completed, the data collected by the detection device in the abnormal area is recorded as data in the shielding state, and the magnetic field environment in the shielding state is marked, so as to confirm the anti-interference processing status of the data in the subsequent processing steps.

[0028] Optionally, the S4 specifically includes:

[0029] S41: after receiving the magnetic field data collected in real time, calculating the magnetic field intensity variation ΔB in the data, which is used to characterize the amplitude of the magnetic field fluctuation;

[0030] S42: Compare the amplitude ΔB of the magnetic field fluctuation with the amplitude A of the received sound wave signal, analyze the influence of the magnetic field change on the sound wave signal, and calculate the amplitude deviation ΔA and phase deviation of the sound wave signal under the condition of magnetic field change The formula is: ΔA = k·ΔB; Among them, k is the influence coefficient of magnetic field change on signal amplitude, m is the influence coefficient of magnetic field change on signal phase, ΔA represents amplitude deviation, Indicates phase deviation;

[0031] S43: Based on the calculated amplitude deviation ΔA and phase deviation The amplitude and phase of the received sound wave signal are compensated and adjusted to eliminate the interference caused by the magnetic field change; the adjusted signal amplitude A' and phase The calculation formula is: A′=A-ΔA; Where A′ represents the adjusted signal amplitude, represents the adjusted signal phase, A is the amplitude of the received sound wave signal, is the phase of the original signal received;

[0032] S44: Using the adjusted acoustic wave signal for subsequent thickness measurement to ensure that the accuracy of signal processing is not affected by the interference of magnetic field fluctuations.

[0033] Optionally, the S5 specifically includes:

[0034] S51: After the detection device is started, a multi-frequency acoustic wave transmitter is used to sequentially transmit acoustic wave signals of multiple frequencies to the target area, and the transmitted frequency is recorded after each transmission;

[0035] S52: receiving echoes of multi-band sound wave signals, recording echo signals of each frequency band in sequence through an echo receiver, and associating each echo signal with its corresponding transmission frequency;

[0036] S53: Perform independent denoising on the echo signals of each frequency band, remove the background noise and sudden interference noise in the non-target frequency range through filtering algorithm, and select clear signals that are not interfered by the magnetic field;

[0037] S54: inputting the denoised echo signals of different frequency bands into a signal fusion unit, performing weighted fusion on the signals of each frequency band according to the frequency and intensity, and integrating the characteristics of the signals of different frequency bands to obtain a group of comprehensive echo signals representing the thickness of the crust;

[0038] S55: The fused integrated echo signal is transmitted to the data processing unit as basic data for subsequent thickness calculation.

[0039] Optionally, the S54 specifically includes:

[0040] S541: Define the echo signal of each frequency band as signal strength I i and frequency f i , where i represents different frequency band numbers;

[0041] S542: According to the frequency f of each frequency band signal i Assign weight coefficient w i , setting high-frequency signals to have higher weights to improve resolution; weight coefficient w i Calculated according to the following formula: Among them, n1 is the total number of frequency bands, w i is the weight coefficient of the i-th frequency band; the sum of the weights of all frequency bands is 1;

[0042] S543: The signal strength I of each frequency band is i According to the weight coefficient w i Weighted, the weighted signal strength I is obtained i ′, the calculation formula is: i ′=I i × i , where I i ′ is the weighted signal strength, I i is the signal strength, w i is the corresponding weight coefficient;

[0043] S544: The weighted signal strength I i ′ is comprehensively superimposed to generate a comprehensive echo signal intensity I representing the crust thickness total , the formula is: Among them, I total It represents the final integrated echo signal strength, which is used to characterize the overall thickness characteristics of the target area; n1 is the total number of frequency bands;

[0044] S545: The obtained integrated echo signal strength I total Serves as the basic signal for thickness analysis.

[0045] Optionally, the S6 specifically includes:

[0046] S61: Comprehensive echo signal strength I after receiving and processing total Afterwards, the time difference ΔT from the emission to the reception of the sound wave is recorded using an internal time measurement unit, wherein the time difference ΔT represents the round-trip time of the sound wave in the cobalt-rich crust layer;

[0047] S62: After obtaining the time difference ΔT, call the pre-measured seabed sound velocity V in the seabed environment s data; and combined with the seabed sound speed V s The thickness D of the cobalt-rich crust is calculated by the time difference ΔT. The calculation formula is: Where D is the thickness of the cobalt-rich crust, V s is the seabed sound speed, ΔT is the time difference;

[0048] S63: When calculating the thickness, dynamically adjust the parameters in the calculation according to the specific situation of the real-time magnetic field change; determine the influence of the magnetic field change on the sound wave propagation speed through the real-time collected magnetic field data, and introduce a correction factor to adjust the seabed sound speed accordingly, so that the seabed sound speed data can reflect the influence of the real-time magnetic field environment, thereby ensuring the accuracy of the thickness calculation;

[0049] S64: The thickness is recalculated using the corrected seabed sound velocity parameters to compensate for the interference caused by the magnetic field changes and obtain the corrected cobalt-rich crust thickness data.

[0050] Optionally, the S63 specifically includes:

[0051] S631: Before calculating the thickness, the amplitude ΔB of the magnetic field fluctuation in the current detection area is collected in real time, which represents the deviation of the current magnetic field relative to the initial magnetic field reference, and is used to determine the degree of magnetic field change;

[0052] S632: Calculate the influence coefficient C of magnetic field change on seabed sound velocity based on the amplitude ΔB of magnetic field fluctuation m , which is used to quantify the interference effect of magnetic field changes on the propagation speed of sound waves. The formula is: C m =α×ΔB, where α is the sensitivity coefficient of the seabed sound velocity to the magnetic field change; C m is the influence coefficient of magnetic field change on the seabed sound speed;

[0053] S633: The influence coefficient C m Introduce the seabed sound speed correction formula to adjust the seabed sound speed V s To obtain the corrected seabed sound velocity V s ′, so that the seabed sound velocity data can reflect the influence of the real-time magnetic field environment; the seabed sound velocity calculation formula after correction is: V s ′=V s ×(1+C m ), where V s is the speed of sound on the seafloor, V s ′ is the corrected seabed sound speed, C m is the influence coefficient of magnetic field change on the seabed sound speed;

[0054] S634: The corrected seabed sound velocity V s ′ is used in subsequent thickness calculations to compensate for the seabed sound velocity deviation caused by magnetic field changes.

[0055] Optionally, the S7 specifically includes:

[0056] S71: After completing the thickness measurement, perform spatial mapping processing on the thickness data, associate the thickness data of each measurement point with its corresponding geographical location data, and generate a thickness data set of the measurement area;

[0057] S72: Based on the thickness data set, the thickness data between the measurement points are processed continuously by an interpolation algorithm to generate a crust thickness distribution map of the target area; and corresponding colors or gray levels are set according to the thickness values ​​to visually display the thickness differences of different areas, so that the distribution map can intuitively reflect the thickness characteristics of the target area;

[0058] S73: after the crust thickness distribution map is generated, the measurement results and thickness data are formatted, and the thickness distribution map, the thickness value of each measurement point and its corresponding geographical location data are organized into a transmission file;

[0059] S74: The formatted data file is transmitted to the ground terminal through the output device, and the data transmission is performed by wired transmission or wireless communication.

[0060] Beneficial effects of the present invention:

[0061] The present invention effectively reduces the interference of complex deep-sea magnetic field environment on thickness measurement through real-time magnetic field monitoring, dynamic correction and multi-band acoustic wave signal fusion, improves the accuracy and stability of cobalt-rich crust thickness detection, and the weighted fusion processing of multi-band acoustic wave signals combined with the application of interpolation algorithm makes the measurement data continuous in space, thus ensuring the integrity and anti-interference performance of thickness data.

[0062] The present invention intuitively displays the thickness changes in the measurement area by mapping thickness values ​​with colors or grayscale levels, and provides a clear and easy-to-read thickness distribution map for the ground terminal. This visual presentation method is helpful for deep-sea resource evaluation and mining decision-making, and provides reliable data support for the development of cobalt-rich crust resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0064] Figure 1 A schematic diagram of a crust thickness analysis method according to an embodiment of the present invention;

[0065] Figure 2 The figure is a schematic diagram of a process of obtaining a comprehensive echo signal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0066] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0067] like Figure 1-Figure 2 As shown, a crust thickness analysis method for in-situ detection of cobalt-rich crusts comprises the following steps:

[0068] S1: Arrange the detection equipment in the target seabed area, start the equipment to collect preliminary environmental magnetic field data, measure and record the magnetic field strength and direction of the current area through sensors, and establish initial magnetic field data as a reference for subsequent detection;

[0069] S2: While starting the thickness detection, continuously monitor the magnetic field changes in the detection area, compare the real-time collected magnetic field data with the initial magnetic field data to identify the abnormal magnetic field fluctuation area, and mark the time and regional location of the abnormal fluctuation in the data record;

[0070] S3: When an abnormal magnetic field fluctuation area is detected, the magnetic shielding layer preset around the device is used to shield the measurement fluctuation area to block the interference of the external magnetic field on the sensor, ensuring that the acoustic wave sensor in the key area can collect signals in an interference-free environment;

[0071] S4: Based on the real-time collected magnetic field change data, analyze the specific impact of magnetic field interference on the acoustic wave signal, and adjust the amplitude and phase of the received acoustic wave signal to eliminate or reduce the signal deviation caused by the magnetic field change;

[0072] S5: Use multi-band acoustic wave transmission technology to transmit acoustic wave signals of multiple frequencies to the target area in sequence and receive echo signals of each frequency band; at the same time, perform independent denoising on the signals of each frequency band to screen out clear signals that are not disturbed by the magnetic field, and fuse the signals of different frequency bands to obtain a comprehensive echo signal representing the thickness of the crust;

[0073] S6: Based on the processed integrated echo signal, measure the time difference from the emission to the reception of the sound wave, and calculate the thickness of the cobalt-rich crust in combination with the seabed sound velocity data. According to the specific situation of the real-time magnetic field changes, dynamically adjust the parameters in the calculation to ensure the accuracy of the thickness measurement;

[0074] S7: After the thickness measurement is completed, a crust thickness distribution map is generated, and the measurement results and thickness data are transmitted to the ground terminal through the output device, providing reliable reference data for the subsequent development of cobalt-rich crusts.

[0075] S1 specifically includes:

[0076] S11: Place the detection device in the target seabed area, and start the data acquisition mode through the built-in three-axis magnetic field sensor, so that the sensor measures the surrounding magnetic field signals at a fixed sampling frequency to obtain the data of the magnetic field strength and direction of the target seabed area;

[0077] S12: Convert the magnetic field signal detected by the three-axis magnetic field sensor into numerical data, and decompose the magnetic field signal into components in three directions through the signal processing unit of the device, namely, the magnetic field strength in the vertical direction, the horizontal north-south direction, and the horizontal east-west direction; the total magnetic field strength B is calculated according to the following formula: Where B represents the total magnetic field strength, B x Represents the vertical component of the magnetic field, B y represents the horizontal north-south component, B z Represents the horizontal east-west component in order to accurately record the magnetic field distribution characteristics of the area;

[0078] S13: At a fixed sampling frequency, continuously collect magnetic field data within a certain period of time, and smooth the collected data at multiple sampling points to calculate the average magnetic field value after smoothing, eliminate the sudden interference of a single measurement, and ensure that the recorded magnetic field data is stable and reliable; the smoothing process uses the mean calculation, and the formula is: Among them, B avg represents the average magnetic field value after smoothing, B i represents the magnetic field intensity at the i-th sampling point, and n represents the total number of sampling times;

[0079] S14: Integrate the smoothed data to generate initial magnetic field data for the current seabed area, and use this data as the benchmark data for subsequent detection to provide a basis for data comparison in real-time monitoring. Through the above steps S11 to S14, accurate collection and processing of initial magnetic field data are achieved to ensure that the recorded magnetic field intensity and direction data have high stability and accuracy, providing a reliable reference benchmark for identifying magnetic field fluctuations and implementing interference correction in subsequent detection processes, which helps to improve the anti-interference ability of thickness measurement.

[0080] S2 specifically includes:

[0081] S21: When the detection device starts the thickness detection, the real-time magnetic field monitoring function is turned on to obtain the magnetic field strength and direction of the detection area at a fixed sampling frequency, and the real-time magnetic field data collected each time is stored in the data processing unit so as to be compared with the initial magnetic field data one by one;

[0082] S22: Calculate each magnetic field intensity value in the real-time collected magnetic field data with the corresponding intensity value in the initial magnetic field data to find the difference between the two to identify magnetic field fluctuations. The difference calculation formula is: ΔB = B t -B0, where B t represents the magnetic field intensity value collected in real time, B0 represents the initial magnetic field intensity value, and ΔB represents the amplitude of magnetic field fluctuation; if ΔB exceeds the preset threshold, it is judged as abnormal magnetic field fluctuation;

[0083] S23: For data determined to be abnormal magnetic field fluctuations, the time T and spatial position P of the fluctuation are recorded, wherein T is obtained through the internal clock of the data processing unit and indicates the time when the abnormal fluctuation occurs; P indicates the current coordinate position of the detection equipment on the seabed, which is provided by the positioning system of the detection equipment;

[0084] S24: The recorded time T, spatial position P and corresponding magnetic field fluctuation amplitude ΔB of the abnormal magnetic field fluctuation are stored in the abnormal record file for backup, so as to shield or further process the abnormal area in the subsequent steps; through the above steps S21 to S24, the real-time magnetic field changes in the detection area can be effectively monitored, the abnormal magnetic field fluctuation area can be identified in time, and the time and position of the abnormality can be accurately recorded, which provides accurate interference information for magnetic shielding and data correction in the subsequent steps, and improves the anti-interference performance of the thickness detection system.

[0085] S3 specifically includes:

[0086] S31: After detecting an abnormal magnetic field fluctuation area, start the magnetic shielding control system, activate the preset magnetic shielding layer, and put the magnetic shielding layer into a working state. The magnetic shielding layer surrounds the sensor of the detection equipment to form an effective shielding space;

[0087] S32: The magnetic shielding layer is made of Permalloy or nickel-iron alloy materials, which have high magnetic permeability and are used to absorb and guide external abnormal magnetic field signals, reduce the penetration strength of the magnetic field, and thus shield the interference of the external magnetic field on the sensor;

[0088] S33: When the magnetic shielding layer is in working state, an internal stable magnetic field environment is generated, so that the sensor of the detection equipment is only affected by the magnetic field in the shielding space, ensuring that the signal received by the sensor is not disturbed by external magnetic field fluctuations;

[0089] S34: After the shielding is completed, the data collected by the detection equipment in the abnormal area is recorded as the data in the shielding state, and the magnetic field environment in the shielding state is marked, so as to confirm the anti-interference processing status of the data in the subsequent processing steps; through the above steps S31 to S34, the high magnetic permeability magnetic shielding layer composed of Permalloy or nickel-iron alloy is used to effectively shield the key measurement area in the abnormal magnetic field fluctuation area, ensuring that the sensor collects data in a stable magnetic field environment, thereby reducing the interference of the external magnetic field on the measurement accuracy, and providing technical guarantee for the accuracy of the thickness analysis results.

[0090] S4 specifically includes:

[0091] S41: after receiving the magnetic field data collected in real time, calculating the magnetic field intensity variation ΔB in the data, which is used to characterize the amplitude of the magnetic field fluctuation, the magnetic field intensity variation ΔB has been defined in step S22;

[0092] S42: Compare the amplitude ΔB of the magnetic field fluctuation with the amplitude A of the received sound wave signal, analyze the influence of the magnetic field change on the sound wave signal, and calculate the amplitude deviation ΔA and phase deviation of the sound wave signal under the condition of magnetic field change The formula is: ΔA = k·ΔB; Among them, k is the influence coefficient of magnetic field change on signal amplitude, m is the influence coefficient of magnetic field change on signal phase, ΔA represents amplitude deviation, Indicates phase deviation;

[0093] S43: Based on the calculated amplitude deviation ΔA and phase deviation The amplitude and phase of the received sound wave signal are compensated and adjusted to eliminate the interference caused by the magnetic field change; the adjusted signal amplitude A' and phase The calculation formula is: A′=A-ΔA; Where A′ represents the adjusted signal amplitude, represents the adjusted signal phase, A is the amplitude of the received sound wave signal, is the phase of the original signal received;

[0094] S44: Use the adjusted acoustic wave signal for subsequent thickness measurement to ensure that the accuracy of signal processing is not affected by the interference of magnetic field fluctuations; through the above steps S41 to S44, the amplitude and phase of the acoustic wave signal are compensated and adjusted based on the real-time collected magnetic field change data, which successfully reduces the interference of magnetic field fluctuations on the accuracy of signal reception, ensures the accuracy and stability of the acoustic wave signal in thickness measurement, and effectively improves the anti-interference ability of the detection equipment under complex magnetic field conditions.

[0095] S5 specifically includes:

[0096] S51: After the detection device is started, multiple frequency sound wave signals are sequentially transmitted to the target area through the multi-band sound wave transmitter, and the transmitted frequency is recorded after each transmission to ensure that the sound wave signals of different frequency bands are respectively propagated and returned in the detection area;

[0097] S52: receiving echoes of multi-band acoustic wave signals, recording echo signals of each frequency band in sequence through an echo receiver, and associating each echo signal with its corresponding transmission frequency for subsequent denoising and analysis;

[0098] S53: Perform independent denoising on the echo signals of each frequency band, and remove the background noise and sudden interference noise in the non-target frequency range through filtering algorithms, so as to ensure that the echo signals of each frequency band only retain valid data with clear features, and screen out clear signals that are not interfered by the magnetic field;

[0099] S54: inputting the denoised echo signals of different frequency bands into a signal fusion unit, performing weighted fusion on the signals of each frequency band according to the frequency and intensity, integrating the characteristics of the signals of different frequency bands, and obtaining a group of comprehensive echo signals representing the thickness of the crust, so as to reflect the thickness information of the target area;

[0100] S55: The fused integrated echo signal is transmitted to the data processing unit as the basic data for the subsequent thickness calculation, providing an accurate detection signal for the thickness analysis in the subsequent steps; through the above steps S51 to S55, the sequential emission, independent denoising, screening and fusion of multi-band acoustic wave signals are realized, and a comprehensive echo signal with anti-interference characteristics is successfully obtained, which provides a stable and reliable signal basis for the thickness measurement of cobalt-rich crust and improves the measurement accuracy and the stability of signal processing.

[0101] S54 specifically includes:

[0102] S541: Define the echo signal of each frequency band as signal strength I i and frequency f i , where i represents different frequency band numbers; the signal strength and frequency of each frequency band are collected for subsequent weighted processing;

[0103] S542: According to the frequency f of each frequency band signal i Assign weight coefficient w i , setting high-frequency signals to have higher weights to improve resolution; weight coefficient w i Calculated according to the following formula: Among them, n1 is the total number of frequency bands, w i is the weight coefficient of the i-th frequency band; the sum of the weights of all frequency bands is 1;

[0104] S543: The signal strength I of each frequency band is i According to the weight coefficient w i Weighted, the weighted signal strength I is obtained i ′, the calculation formula is: i ′=I i × i , where I i ′ is the weighted signal strength, I i is the signal strength, w i is the corresponding weight coefficient;

[0105] S544: The weighted signal strength I i ′ is comprehensively superimposed to generate a comprehensive echo signal intensity I representing the crust thickness total , the formula is: Among them, I total It represents the final integrated echo signal strength, which is used to characterize the overall thickness characteristics of the target area; n1 is the total number of frequency bands;

[0106] S545: The obtained integrated echo signal strength I total As the basic signal for thickness analysis, it can be used for accurate calculation of crust thickness in subsequent steps; through the above steps S541 to S545, the echo signals of different frequency bands are frequency- and intensity-weighted fused to generate a comprehensive echo signal representing the crust thickness, ensuring the resolution advantage of high-frequency signals while retaining the comprehensive characteristics of multi-band signals, providing optimized signal input for accurate calculation of crust thickness, and effectively improving the measurement accuracy and stability.

[0107] S6 specifically includes:

[0108] S61: Comprehensive echo signal strength I after receiving and processing total Afterwards, the time difference ΔT from the emission to the reception of the sound wave is recorded using an internal time measurement unit, wherein the time difference ΔT represents the round-trip time of the sound wave in the cobalt-rich crust layer;

[0109] S62: After obtaining the time difference ΔT, call the pre-measured seabed sound velocity V in the seabed environment s data; and combined with the seabed sound speed V s The thickness D of the cobalt-rich crust is calculated by the time difference ΔT. The calculation formula is: Where D is the thickness of the cobalt-rich crust, V s is the seabed sound speed, ΔT is the time difference;

[0110] S63: When calculating the thickness, dynamically adjust the parameters in the calculation according to the specific situation of the real-time magnetic field change; determine the influence of the magnetic field change on the sound wave propagation speed through the real-time collected magnetic field data, and introduce a correction factor to adjust the seabed sound speed accordingly, so that the seabed sound speed data can reflect the influence of the real-time magnetic field environment, thereby ensuring the accuracy of the thickness calculation;

[0111] S64: Recalculate the thickness using the corrected seabed sound velocity parameters to compensate for the interference caused by the magnetic field change, obtain the corrected cobalt-rich crust thickness data, and ensure the accuracy and stability of the thickness measurement; through the above steps S61 to S64, based on the time difference measurement of the comprehensive echo signal and the dynamic correction of the seabed sound velocity data, the thickness data of the cobalt-rich crust is successfully calculated, and the anti-interference ability of the thickness measurement is improved through real-time correction of the magnetic field, ensuring the measurement accuracy and adaptability of the detection equipment in complex deep-sea environments.

[0112] S63 specifically includes:

[0113] S631: Before calculating the thickness, the amplitude ΔB of the magnetic field fluctuation in the current detection area is collected in real time, which represents the deviation of the current magnetic field relative to the initial magnetic field reference and is used to determine the degree of magnetic field change. The calculation formula of the amplitude ΔB of the magnetic field fluctuation has been defined in the previous step;

[0114] S632: Calculate the influence coefficient C of magnetic field change on seabed sound velocity based on the amplitude ΔB of magnetic field fluctuation m , which is used to quantify the interference effect of magnetic field changes on the propagation speed of sound waves. The formula is: C m =Δ×ΔB, where α is the sensitivity coefficient of the seabed sound velocity to the magnetic field change, which is a preset constant and represents the response degree of the seabed sound velocity to the unit magnetic field change; C m is the influence coefficient of magnetic field change on the seabed sound speed;

[0115] S633: The influence coefficient C m Introduce the seabed sound speed correction formula to adjust the seabed sound speed V s To obtain the corrected seabed sound velocity V s ′, so that the seabed sound velocity data can reflect the influence of the real-time magnetic field environment; the seabed sound velocity calculation formula after correction is: V s ′=V s ×(1+C m ), where V s is the speed of sound on the seafloor, V s ′ is the corrected seabed sound speed, C m is the influence coefficient of magnetic field change on the seabed sound velocity; by introducing C m Dynamically adjust the seabed sound speed to adapt to real-time magnetic field changes;

[0116] S634: The corrected seabed sound velocity V s ′ is used for subsequent thickness calculations to compensate for the seabed sound velocity deviation caused by magnetic field changes and ensure the accuracy of thickness measurement results; through the above steps S631 to S634, the seabed sound velocity correction factor is introduced based on the real-time magnetic field data, and the seabed sound velocity is effectively adjusted to adapt to the changes in the real-time magnetic field environment, ensuring the accuracy of the seabed sound velocity data under complex magnetic field conditions.

[0117] S7 specifically includes:

[0118] S71: after completing the thickness measurement, performing spatial mapping processing on the thickness data, associating the thickness data of each measurement point with its corresponding geographical location data, and generating a thickness data set of the measurement area, so as to construct complete crust thickness distribution information;

[0119] S72: Based on the thickness data set, the thickness data between the measurement points are processed continuously by an interpolation algorithm to generate a crust thickness distribution map of the target area; and corresponding colors or gray levels are set according to the thickness values ​​to visually display the thickness differences of different areas, so that the distribution map can intuitively reflect the thickness characteristics of the target area;

[0120] The specific calculation steps are as follows:

[0121] S721: After obtaining the thickness data set, calculate the coordinates (x i ,y i ) and the corresponding thickness value D i To provide basic data for subsequent interpolation processing, x i and i Indicates the horizontal and vertical coordinates of the i-th measurement point, D i Indicates the thickness value of the measuring point;

[0122] S722: Use a bilinear interpolation algorithm to continuously process the thickness data between adjacent measurement points; for the thickness value D(x, y) of any target point (x, y), interpolate the data of the surrounding four measurement points; the interpolation formula is as follows: Among them, D 11 ,D 21 ,D 12 and D 22 They represent the thickness values ​​of the four corners of the area where the target point (x, u) is located, and (x1, y1) and (x2, y2) represent the coordinates of the four corner points. The formula interpolates the thickness data of the surrounding measurement points to obtain continuous thickness distribution data in the target area.

[0123] S723: discretizing the thickness value D(x, y) obtained by interpolation calculation, and setting the color or grayscale based on the thickness value; mapping the thickness value D(x, y) to a preset color or grayscale interval so as to reflect the difference of different thickness areas on the generated distribution map; a higher thickness value corresponds to a darker color or a higher grayscale, and a lower thickness value corresponds to a lighter color or a lower grayscale;

[0124] S724: Generate a two-dimensional distribution diagram of the thickness values ​​and corresponding colors or gray levels of all target points to obtain an intuitive crust thickness distribution diagram to clearly show the thickness changes at different positions in the measurement area.

[0125] S73: after the crust thickness distribution map is generated, the measurement results and thickness data are formatted, and the thickness distribution map, the thickness value of each measurement point and its corresponding geographical location data are organized into a transmission file to meet the receiving format and data structure requirements of the ground terminal;

[0126] S74: The formatted data file is transmitted to the ground terminal through the output device, and the data is transmitted by wired transmission or wireless communication. After receiving the transmission file, the ground terminal can directly read the thickness distribution map and the measurement results, so as to provide real-time and reliable reference data for the subsequent development of cobalt-rich crust resources. Through the above steps S71 to S74, the visualization processing and reliable transmission of the thickness data are realized, and the measurement results are provided to the ground terminal in the form of an intuitive crust thickness distribution map, so as to ensure the integrity and real-time nature of the data, and provide accurate and easy-to-interpret basic data for the precise analysis and development decision-making of deep-sea resources.

[0127] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0128] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for analyzing the thickness of cobalt-rich crusts for in-situ detection, characterized in that: The following steps are involved: S1: Arrange the detection equipment in the target seabed area, start the equipment to collect preliminary environmental magnetic field data, measure and record the magnetic field strength and direction of the current area through sensors, and establish initial magnetic field data as a reference for subsequent detection; S2: While starting the thickness detection, continuously monitor the magnetic field changes in the detection area, compare the real-time collected magnetic field data with the initial magnetic field data to identify the abnormal magnetic field fluctuation area, and mark the time and regional location of the abnormal fluctuation in the data record; S3: When an abnormal magnetic field fluctuation area is detected, the magnetic shielding layer preset around the device is used to shield the measurement fluctuation area to block the interference of the external magnetic field on the sensor; S4: Based on the real-time collected magnetic field change data, analyze the specific impact of magnetic field interference on the acoustic wave signal, and adjust the amplitude and phase of the received acoustic wave signal to eliminate or reduce the signal deviation caused by the magnetic field change; S5: Use multi-band acoustic wave transmission technology to transmit acoustic wave signals of multiple frequencies to the target area in sequence and receive echo signals of each frequency band; at the same time, perform independent denoising on the signals of each frequency band to screen out clear signals that are not disturbed by the magnetic field, and fuse the signals of different frequency bands to obtain a comprehensive echo signal representing the thickness of the crust; S6: Based on the processed integrated echo signal, measure the time difference from the emission to the reception of the sound wave, and calculate the thickness of the cobalt-rich crust in combination with the seabed sound velocity data. According to the specific situation of the real-time magnetic field changes, dynamically adjust the parameters in the calculation to ensure the accuracy of the thickness measurement; S7: After the thickness measurement is completed, a crust thickness distribution map is generated, and the measurement results and thickness data are transmitted to the ground terminal through an output device.

2. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection according to claim 1, characterized in that: The S1 specifically includes: S11: Place the detection device in the target seabed area, and start the data acquisition mode through the built-in three-axis magnetic field sensor, so that the sensor measures the surrounding magnetic field signals at a fixed sampling frequency to obtain the data of the magnetic field strength and direction of the target seabed area; S12: converting the magnetic field signal detected by the three-axis magnetic field sensor into numerical data, and decomposing the magnetic field signal into components in three directions, namely, magnetic field strength in the vertical direction, horizontal north-south direction, and horizontal east-west direction, through a signal processing unit of the device; S13: Continuously collect magnetic field data within a certain period of time at a fixed sampling frequency, and smooth the collected data of multiple sampling points to calculate the average magnetic field value after smoothing, thereby eliminating sudden interference of a single measurement; S14: Integrate the smoothed data to generate initial magnetic field data for the current seabed area, and use this data as benchmark data for subsequent detection.

3. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection of cobalt-rich crusts according to claim 1, characterized in that: The S2 specifically includes: S21: When the detection device starts the thickness detection, the real-time magnetic field monitoring function is turned on to obtain the magnetic field strength and direction of the detection area at a fixed sampling frequency, and the real-time magnetic field data collected each time is stored in the data processing unit so as to be compared with the initial magnetic field data one by one; S22: Calculate each magnetic field intensity value in the real-time collected magnetic field data with the corresponding intensity value in the initial magnetic field data to find the difference between the two to identify magnetic field fluctuations. The difference calculation formula is: ΔB = B t -B0, where B t represents the magnetic field intensity value collected in real time, B0 represents the initial magnetic field intensity value, and ΔB represents the amplitude of magnetic field fluctuation; if ΔB exceeds the preset threshold, it is judged as abnormal magnetic field fluctuation; S23: For data determined to be abnormal magnetic field fluctuations, the time T and spatial position P of the fluctuation are recorded, wherein T is obtained through the internal clock of the data processing unit and indicates the time when the abnormal fluctuation occurs; P indicates the current coordinate position of the detection equipment on the seabed, which is provided by the positioning system of the detection equipment; S24: The recorded time T, spatial position P and corresponding magnetic field fluctuation amplitude ΔB of the abnormal magnetic field fluctuation are stored in an abnormal record file for future use.

4. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection according to claim 1, characterized in that: The S3 specifically includes: S31: After detecting an abnormal magnetic field fluctuation area, start the magnetic shielding control system, activate the preset magnetic shielding layer, and put the magnetic shielding layer into a working state. The magnetic shielding layer surrounds the sensor of the detection equipment to form a shielding space; S32: The magnetic shielding layer is made of Permalloy or nickel-iron alloy material, and is used to absorb and guide external abnormal magnetic field signals, reduce the penetration strength of the magnetic field, and thus shield the interference of the external magnetic field on the sensor; S33: When the magnetic shielding layer is in working state, an internal stable magnetic field environment is generated, so that the sensor of the detection equipment is only affected by the magnetic field in the shielding space, ensuring that the signal received by the sensor is not disturbed by external magnetic field fluctuations; S34: After the shielding is completed, the data collected by the detection device in the abnormal area is recorded as data in the shielding state, and the magnetic field environment in the shielding state is marked, so as to confirm the anti-interference processing status of the data in the subsequent processing steps.

5. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection according to claim 3 is characterized in that: The S4 specifically includes: S41: after receiving the magnetic field data collected in real time, calculating the magnetic field intensity variation ΔB in the data, which is used to characterize the amplitude of the magnetic field fluctuation; S42: Compare the amplitude ΔB of the magnetic field fluctuation with the amplitude A of the received sound wave signal, analyze the influence of the magnetic field change on the sound wave signal, and calculate the amplitude deviation ΔA and phase deviation of the sound wave signal under the condition of magnetic field change The formula is: ΔA = k·ΔB; Among them, k is the influence coefficient of magnetic field change on signal amplitude, m is the influence coefficient of magnetic field change on signal phase, ΔA represents amplitude deviation, Indicates phase deviation; S43: Based on the calculated amplitude deviation ΔA and phase deviation The amplitude and phase of the received sound wave signal are compensated and adjusted to eliminate the interference caused by the magnetic field change; the adjusted signal amplitude A' and phase The calculation formula is: A′=A-ΔA; Where A′ represents the adjusted signal amplitude, represents the adjusted signal phase, A is the amplitude of the received sound wave signal, is the phase of the original signal received; S44: Using the adjusted acoustic wave signal for subsequent thickness measurement to ensure that the accuracy of signal processing is not affected by the interference of magnetic field fluctuations.

6. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection of cobalt-rich crusts according to claim 1, characterized in that: The S5 specifically includes: S51: After the detection device is started, a multi-frequency acoustic wave transmitter is used to sequentially transmit acoustic wave signals of multiple frequencies to the target area, and the transmitted frequency is recorded after each transmission; S52: receiving echoes of multi-band sound wave signals, recording echo signals of each frequency band in sequence through an echo receiver, and associating each echo signal with its corresponding transmission frequency; S53: Perform independent denoising on the echo signals of each frequency band, remove the background noise and sudden interference noise in the non-target frequency range through filtering algorithm, and select clear signals that are not interfered by the magnetic field; S54: inputting the denoised echo signals of different frequency bands into a signal fusion unit, performing weighted fusion on the signals of each frequency band according to the frequency and intensity, and integrating the characteristics of the signals of different frequency bands to obtain a group of comprehensive echo signals representing the thickness of the crust; S55: The fused integrated echo signal is transmitted to the data processing unit as basic data for subsequent thickness calculation.

7. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection according to claim 6, characterized in that: The S54 specifically includes: S541: Define the echo signal of each frequency band as signal strength I i and frequency f i , where i represents different frequency band numbers; S542: According to the frequency f of each frequency band signal i Assign weight coefficient w i , setting high-frequency signals to have higher weights to improve resolution; weight coefficient w i Calculated according to the following formula: Among them, n1 is the total number of frequency bands, w i is the weight coefficient of the i-th frequency band; the sum of the weights of all frequency bands is 1; S543: The signal strength I of each frequency band is i According to the weight coefficient w i Weighted, the weighted signal strength I is obtained i ′, the calculation formula is: i ′=I i × i , where I i ′ is the weighted signal strength, I i is the signal strength, w i is the corresponding weight coefficient; S544: The weighted signal strength I i ′ is comprehensively superimposed to generate a comprehensive echo signal intensity I representing the crust thickness total , the formula is: Among them, I total It represents the final integrated echo signal strength, which is used to characterize the overall thickness characteristics of the target area; n1 is the total number of frequency bands; S545: The obtained integrated echo signal strength I total Serves as the basic signal for thickness analysis.

8. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection according to claim 7, characterized in that: The S6 specifically includes: S61: Comprehensive echo signal strength I after receiving and processing total Afterwards, the time difference ΔT from the emission to the reception of the sound wave is recorded using an internal time measurement unit, wherein the time difference ΔT represents the round-trip time of the sound wave in the cobalt-rich crust layer; S62: After obtaining the time difference ΔT, call the pre-measured seabed sound velocity V in the seabed environment s data; and combined with the seabed sound speed V s The thickness D of the cobalt-rich crust is calculated by the time difference ΔT. The calculation formula is: Where D is the thickness of the cobalt-rich crust, V s is the seabed sound speed, ΔT is the time difference; S63: When calculating the thickness, dynamically adjust the parameters in the calculation according to the specific situation of the real-time magnetic field change; determine the influence of the magnetic field change on the sound wave propagation speed through the real-time collected magnetic field data, and introduce a correction factor to adjust the seabed sound speed accordingly, so that the seabed sound speed data can reflect the influence of the real-time magnetic field environment, thereby ensuring the accuracy of the thickness calculation; S64: The thickness is recalculated using the corrected seabed sound velocity parameters to compensate for the interference caused by the magnetic field changes and obtain the corrected cobalt-rich crust thickness data.

9. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection according to claim 8, characterized in that: The S63 specifically includes: S631: Before calculating the thickness, the amplitude ΔB of the magnetic field fluctuation in the current detection area is collected in real time, which represents the deviation of the current magnetic field relative to the initial magnetic field reference, and is used to determine the degree of magnetic field change; S632: Calculate the influence coefficient C of magnetic field change on seabed sound velocity based on the amplitude ΔB of magnetic field fluctuation m , which is used to quantify the interference effect of magnetic field changes on the propagation speed of sound waves. The formula is: C m =α×ΔB, where α is the sensitivity coefficient of the seabed sound velocity to the magnetic field change; C m is the influence coefficient of magnetic field change on the seabed sound speed; S633: The influence coefficient C m Introduce the seabed sound speed correction formula to adjust the seabed sound speed V s To obtain the corrected seabed sound velocity V s ′, so that the seabed sound velocity data can reflect the influence of the real-time magnetic field environment; the seabed sound velocity calculation formula after correction is: V s ′=V s ×(1+C m ), where V s is the speed of sound on the seafloor, V s ′ is the corrected seabed sound speed, C m is the influence coefficient of magnetic field change on the seabed sound speed; S634: The corrected seabed sound velocity V s ′ is used in subsequent thickness calculations to compensate for the seabed sound velocity deviation caused by magnetic field changes.

10. The method for analyzing the thickness of cobalt-rich crusts for in-situ detection according to claim 1, characterized in that: The S7 specifically includes: S71: After completing the thickness measurement, perform spatial mapping processing on the thickness data, associate the thickness data of each measurement point with its corresponding geographical location data, and generate a thickness data set of the measurement area; S72: Based on the thickness data set, the thickness data between the measurement points are processed continuously by an interpolation algorithm to generate a crust thickness distribution map of the target area; and corresponding colors or gray levels are set according to the thickness values ​​to visually display the thickness differences of different areas, so that the distribution map can intuitively reflect the thickness characteristics of the target area; S73: after the crust thickness distribution map is generated, the measurement results and thickness data are formatted, and the thickness distribution map, the thickness value of each measurement point and its corresponding geographical location data are organized into a transmission file; S74: The formatted data file is transmitted to the ground terminal through the output device, and the data transmission is performed by wired transmission or wireless communication.

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