Intelligent identification method and system for stratigraphic boundary of superficial profile image

Abstract

The invention relates to an intelligent identification method and system for a stratigraphic boundary of a superficial profile image, and relates to the field of data processing technologies, and the method comprises the steps: obtaining sound wave data in response to a stratigraphic analysis signal; obtaining an initial superficial profile image based on the sound wave data in combination with a preprocessing scheme; extracting stratum feature data and comparison data in the initial shallow profile image according to an extraction scheme; substituting the stratum feature data into the coding function to calculate a one-dimensional data set; decoding the one-dimensional data set according to a decoding scheme to obtain stratum shallow profile data; if the stratum shallow profile data is consistent with the comparison data, forming a stratum boundary image based on the stratum shallow profile data and outputting the stratum boundary image; if the stratum shallow-profile data is not consistent with the comparison data, searching a calibration scheme through the stratum shallow-profile data and the comparison data, and executing the calibration scheme to obtain standard shallow-profile data; and forming and outputting a standard stratum image based on the standard shallow profile data. The method has the effect of improving the reliability and accuracy of the final shallow profile image.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for intelligent identification of stratigraphic boundaries in shallow profile images. Background Technology

[0002] Stratigraphic boundary identification in shallow profile images is a core technical aspect of marine geological exploration, engineering geological survey, and seabed resource exploration. Its accuracy and efficiency directly determine the reliability of subsequent work such as stratigraphic structure inversion, geological hazard prediction, and seabed resource distribution assessment.

[0003] Currently, the industry's stratigraphic boundary identification largely relies on traditional manual interpretation methods. Technicians need to analyze the morphology, amplitude changes, and continuity characteristics of reflected waves in the original shallow profile images one by one based on their professional experience, and manually mark the stratigraphic boundary positions.

[0004] Regarding the aforementioned technologies, data loss is a common problem in the current process of identifying stratigraphic boundaries in shallow profiling images. Most of the data relies on staff interpretation and supplementation, resulting in highly subjective stratigraphic boundary data, and the reliability and accuracy of the data results still have room for improvement. Summary of the Invention

[0005] To improve the reliability and accuracy of the final image, this invention provides a method and system for intelligent identification of stratigraphic boundaries in shallow profile images.

[0006] In a first aspect, the present invention provides a method for intelligent identification of stratigraphic boundaries in shallow profile images, employing the following technical solution: A method for intelligent identification of stratigraphic boundaries in shallow profile images includes: Step 1: Acquire acoustic data in response to the preset formation analysis signal; Step 2: Obtain an initial shallow profile image based on the acoustic data and a preset preprocessing scheme; Step 3: Extract stratigraphic feature data and contrast data from the initial shallow profile image according to the preset extraction scheme; Step 4: Substitute the stratigraphic feature data into the preset encoding function to calculate the one-dimensional data set; Step 5: Decode the one-dimensional data set according to the preset decoding scheme to obtain shallow stratigraphic profile data; Step 6: If the shallow stratigraphic profile data is consistent with the correlation data, generate and output a stratigraphic boundary image based on the shallow stratigraphic profile data; Step 7: If the shallow stratigraphic profile data is inconsistent with the correlation data, find a calibration scheme by comparing the shallow stratigraphic profile data and the correlation data and execute it to obtain standard shallow stratigraphic profile data; Step 8: Generate and output a standard stratigraphic image based on the standard shallow profile data.

[0007] By adopting the above technical solution, the initial shallow profile image is obtained by acquiring acoustic wave data and then preprocessing it. Then, the final standard stratigraphic image is obtained according to the extraction scheme, encoding function, decoding scheme and calibration scheme. This avoids the situation where the final stratigraphic boundary image has a large error compared with the actual situation due to insufficient image data processing, and improves the reliability and accuracy of the stratigraphic boundary image.

[0008] Optionally, methods for acquiring acoustic wave data include: Step 10: Obtain ship parameters; Step 11: Deconstruct the ship's parameters to obtain the instrument number, ship speed, and ship direction; Step 12: Obtain the transmitting instrument number and receiving instrument number based on the ship's orientation and instrument number; Step 13: Determine the transmission and reception angles based on the ship's speed; Step 14: Adjust the launching instrument corresponding to the launching instrument number according to the launching angle; Step 15: Adjust the receiving instrument corresponding to the receiving instrument number according to the receiving angle; Step 16: Obtain the acoustic signal based on the transmitting instrument number, the receiving instrument number, and the preset acoustic scheme to obtain acoustic data.

[0009] By adopting the above technical solution, the ship parameters are acquired and disassembled, and the corresponding transmitting and receiving instrument numbers are matched with the ship's direction and speed. The appropriate transmitting and receiving angles are determined, and then the instruments are manipulated to complete the angle adjustment and execute the acoustic scheme to obtain acoustic signals to obtain acoustic data. This avoids the acoustic signal acquisition deviation caused by the mismatch between the instrument angle and number matching and the ship's navigation state, and improves the accuracy and adaptability of acoustic data acquisition.

[0010] Optionally, methods for obtaining initial shallow profile images based on acoustic data combined with preprocessing schemes include: Step 20: Obtain the acoustic parameters corresponding to the acoustic signal; Step 21: If the acoustic wave parameter is greater than the preset effective threshold, determine the acoustic wave data based on the acoustic wave signal; Step 22: If the acoustic wave parameter is less than the effective threshold, define the acoustic wave signal as lacking an acoustic wave signal; Step 23: Based on the missing acoustic signal and the preset adjacent rules, find the first and second adjacent signals; Step 24: Obtain data number one through adjacent signal number one; Step 25: Obtain data number two through adjacent signal number two; Step 26: Calculate the average data based on data point 1 and data point 2; Step 27: Perform a preprocessing scheme on the acoustic data and the average data to form a complete shallow profile image and define it as the initial shallow profile image.

[0011] By adopting the above technical solution, the validity of the acoustic parameters corresponding to the acoustic signal is determined. For acoustic signals that do not meet the standards, the missing acoustic signals are supplemented by combining adjacent signals and calculating the average data. Then, the valid acoustic data and the supplemented average data are combined to perform a preprocessing scheme to form a complete initial shallow profile image. This avoids the problem of missing shallow profile image data and tomography caused by invalid partial acoustic signals, and improves the reliability of initial shallow profile image acquisition.

[0012] Optionally, it also includes a method for acquiring an initial shallow profile image when the acoustic signal is absent, the method comprising: Step 28: Define the acoustic signal as a missing signal; Step 29: Extract the ship's real-time position using ship parameters; Step 30: Calculate the location of the missing signal based on the missing signal, ship speed, and ship's real-time position; Step 31: Combine the location of the missing signal with the receiver number to form a retransmission plan and execute it to obtain the retransmission signal; Step 32: If the retransmission signal exists, execute step 16 to obtain the retransmission data; Step 33: Perform a preprocessing scheme on the supplementary data and acoustic data to form a supplementary shallow profile image and define it as the initial shallow profile image; Step 34: If the replacement signal is not available, generate and output an abnormal shallow profile image based on the location of the missing signal and the acoustic data.

[0013] By adopting the above technical solution, in the case of a complete absence of acoustic signals, the location of the missing signal is accurately calculated by combining ship parameters. Then, a retransmission signal scheme is formed and executed by combining the receiver instrument number to attempt to obtain the retransmission signal. The final image is obtained by analyzing whether the supplementary image can be obtained. This avoids image tomography or recognition errors caused by the complete absence of signals, and improves the reliability of shallow profile image data and the controllability of the detection work.

[0014] Optionally, methods for combining the location of the missing signal with the receiver instrument number to form a retransmission scheme and executing it to obtain the retransmission signal include: Step 310: Calculate the retransmission angle using the ship's real-time position, ship speed, and the location of the missing signal; Step 311: Calculate the retransmission sound wave parameters based on the difference between the sound wave parameters and the preset sound wave threshold; Step 312: Integrate the retransmission acoustic wave parameters and retransmission angle to form a retransmission signal scheme; Step 313: Adjust the receiving instrument corresponding to the receiving instrument number to the retransmission angle; Step 314: Control the receiving instrument corresponding to the receiving instrument number to transmit and receive the sound wave signal according to the supplementary sound wave parameters to obtain the supplementary signal.

[0015] By adopting the above technical solution, the retransmission angle is accurately calculated by combining the ship's real-time position, speed and the location of the missing signal. The retransmission acoustic parameters are determined based on the acoustic parameters and the distinguishing acoustic threshold. After integrating the two to form a targeted retransmission scheme, the receiving instrument is adjusted to the corresponding angle and the receiving signal is transmitted and received according to the parameters to obtain the retransmission signal. This avoids the problem of retransmission failure or signal distortion caused by improper angle and parameter adaptation during retransmission signal acquisition, and improves the accuracy of retransmission signal acquisition.

[0016] Alternatively, methods for obtaining acoustic wave data may include: Step 35: Find adjacent signals by comparing the sound wave signal with the adjacent rules; Step 36: Obtain the adjacent parameters corresponding to adjacent signals; Step 37: Calculate the difference in acoustic parameters based on adjacent parameters and acoustic parameters; Step 38: If the difference in acoustic parameters is greater than the preset change threshold, obtain the instrument spacing based on the transmitting instrument number and the receiving instrument number; Step 39: Calculate the elapsed time based on the instrument spacing and ship speed, and simultaneously accumulate the waiting time; Step 40: When the waiting time reaches the elapsed time, an update signal is obtained based on the receiving instrument number and the acoustic scheme; Step 41: If the update signal is inconsistent with the sound wave signal, replace the sound wave signal with the update signal to obtain the updated data; Step 42: If the update signal is consistent with the sound wave signal, determine the sound wave data based on the sound wave signal.

[0017] By adopting the above technical solution, adjacent signals are found and adjacent parameters are obtained by using acoustic signals and adjacent rules. The difference between acoustic parameters is calculated to determine the stability of the signal. If the parameter difference exceeds the threshold, the waiting time is calculated by combining the instrument spacing and the ship speed and an updated signal is obtained. The final acoustic data is then determined based on the consistency between the updated signal and the original acoustic signal. This avoids data deviation caused by sudden fluctuations in acoustic signals and improves the stability and accuracy of acoustic data.

[0018] Optionally, if the update signal matches the acoustic signal, the method for determining acoustic data based on the acoustic signal includes: Step 420: Obtain the penetration threshold and combine it with the effective threshold and acoustic parameters to calculate the acoustic adjustment parameters; Step 421: Control the receiving instrument corresponding to the receiving instrument number to adjust according to the acoustic adjustment parameters and execute the acoustic scheme to obtain the adjustment signal; Step 422: If the adjustment signal and the sound wave signal are inconsistent, replace the sound wave signal with the adjustment signal to obtain the adjustment data; Step 423: If the adjustment signal is consistent with the sound wave signal, determine the sound wave data based on the sound wave signal.

[0019] By adopting the above technical solution, when the updated signal is consistent with the original acoustic signal, the acoustic adjustment parameters are calculated, the receiving instrument is adjusted and the adjusted signal is obtained, and then the final acoustic data is determined based on the consistency judgment result between the adjusted signal and the original acoustic signal. This avoids signal deviation caused by the influence of objects obstructing the bottom of the ship, and improves the accuracy and reliability of the acoustic data.

[0020] Optionally, it also includes a method for determining the acoustic wave adjustment parameters, the method comprising: Step 4200: Obtain historical neighbor parameters and future neighbor parameters; Step 4201: Calculate the difference in historical parameters based on the acoustic parameters and historical adjacent parameters; Step 4202: Calculate the difference between future parameters based on the acoustic wave parameters and the parameters of future neighbors; Step 4203: If the historical parameter difference or the future parameter difference is less than the change threshold, step 420 is not executed; Step 4204: When both the historical parameter difference and the future parameter difference are greater than the change threshold, the effective threshold and the penetration threshold are combined to calculate the acoustic adjustment parameters.

[0021] By adopting the above technical solution, historical and future adjacent parameters are obtained and the corresponding parameter differences are calculated. The determination of whether to perform acoustic adjustment parameter calculation is based on the relationship between the parameter difference and the change threshold. Parameter calculation is only performed when both parameter differences exceed the threshold, avoiding unnecessary calculations when no adjustment is needed and improving the overall execution efficiency of the detection process.

[0022] Optionally, methods for obtaining the penetration threshold and calculating the acoustic adjustment parameters by combining the effective threshold with acoustic parameters include: Step 4205: Obtain the types of objects on the bottom of the ship; Step 4206: Find the corresponding penetrating sound wave parameters by matching the type of object on the bottom of the ship with the sound wave parameters; Step 4207: Determine the penetration threshold based on the transmitted acoustic wave parameters; Step 4208: Determine the sound wave adjustment parameters based on the effective threshold and the transmitted sound wave parameters.

[0023] By adopting the above technical solution, the types of objects on the bottom of the ship are obtained and the corresponding penetration sound wave parameters are matched. Based on the penetration threshold determined by the parameters, the sound wave adjustment parameters are calculated together with the effective threshold. This avoids the interference of different obstructing objects on the bottom of the ship to the sound wave detection and improves the reliability and accuracy of sound wave signal acquisition.

[0024] Secondly, this invention provides an intelligent stratigraphic boundary identification system for shallow profile images, employing the following technical solution: A shallow-section image stratigraphic boundary intelligent identification system includes: The acquisition module is used to acquire acoustic wave data, ship parameters, acoustic wave parameters, adjacent parameters, and types of objects on the ship's bottom; The memory is used to store the program for the intelligent identification method of shallow profile image stratigraphic boundaries as described above; The processor loads and executes programs from memory.

[0025] By adopting the above technical solution, the module uniformly collects various detection-related data such as acoustic wave data, and the memory stores the control program of the identification method. Then, the processor loads and executes the program to complete various calculations and identification operations, realizing the modular and systematic design of intelligent identification of stratigraphic boundaries in shallow profile images, and improving the operational stability and execution efficiency of the identification system.

[0026] In summary, the present invention has at least one of the following beneficial technical effects: 1. By responding to the formation analysis signal, then acquiring acoustic data, and then preprocessing it to obtain an initial shallow profile image, and then obtaining the final standard formation image according to the extraction scheme, encoding function, decoding scheme and calibration scheme, the efficient acquisition of shallow profile images of formation boundaries is achieved, avoiding the situation where the image and the actual situation are greatly inaccurate due to the lack of strict data processing, and improving the reliability and accuracy of the final image acquisition. 2. By adjusting the angle of the receiving instrument and retransmitting and receiving the acoustic signal, the reliability of acoustic signal acquisition is improved, avoiding the situation where no effective data can be obtained when the signal is abnormal, and improving the integrity and reliability of subsequent shallow profile image acquisition. 3. By adjusting the relevant parameters of the sound wave and then re-emitting the sound wave to obtain penetrating sound waves, the problem of inaccurate data caused by the presence of organisms or objects in the ocean affecting the sound wave signal is avoided, thus improving the reliability of sound wave signal acquisition. Attached Figure Description

[0027] Figure 1 This is a flowchart of a method for intelligent identification of stratigraphic boundaries in shallow cross-section images according to an embodiment of this application; Figure 2 This is a scene diagram illustrating the implementation of the acoustic wave scheme in an embodiment of this application; Figure 3 This is a scene diagram of transmitting and receiving sound wave signals through a receiving instrument, according to an embodiment of this application. Detailed Implementation

[0028] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0029] This invention discloses an intelligent method for identifying stratigraphic boundaries in shallow profile images. (Refer to...) Figure 1 A method for intelligent identification of stratigraphic boundaries in shallow profile images, comprising: Step 1: Acquire acoustic data in response to the preset formation analysis signal.

[0030] The stratigraphic analysis signal refers to the command signal used to trigger the intelligent identification process of stratigraphic boundaries in shallow profiling images. There are two ways to respond to the stratigraphic analysis signal: one is locally, it can be triggered by the user pressing the button on the instrument's built-in electrical signal button; the other is remotely, it can be triggered by sending a programmable command, which is then parsed and immediately initiates the acoustic wave transmission, reception, and data acquisition process.

[0031] Acoustic data refers to standardized digital data obtained by the instrument from acoustic signals reflected from the seabed strata, which can be used for subsequent shallow profiling image generation and stratigraphic boundary identification. Here, acoustic data is acquired by the system responding to the stratigraphic analysis signal, controlling the transmitting instrument of the shallow profiling instrument to emit acoustic pulses according to preset parameters, and the receiving instrument capturing the acoustic echo signals reflected from the seabed strata in real time. The echo signals are then amplified, filtered, time-depth converted, and digitized sequentially to obtain the acoustic data.

[0032] Step 2: Obtain an initial shallow profile image based on the acoustic data and a preset preprocessing scheme.

[0033] The preprocessing scheme refers to a series of standardized processing procedures performed on acoustic data and the initially generated shallow profile image to improve the quality of the shallow profile image and ensure the accuracy of subsequent stratigraphic boundary identification. Specifically, the preprocessing scheme includes noise removal, Ping repair, multiple suppression, and consistency correction. Noise removal uses wavelet thresholding to suppress random and coherent noise. Ping repair identifies abnormal Pings using the Laida (3σ) criterion and completes missing Pings using mean interpolation. Multiples are weakened using their periodicity and predictive deconvolution. Finally, consistency correction uses a linear grayscale transformation algorithm to uniformly map the grayscale values ​​of the original shallow profile image to a 256-level grayscale range [0, 255]. The specific model of the Laida (3σ) criterion is as follows: Where Vi is the residual of the i-th observation, Xi is the i-th observation, X is the overall mean, and σ is the overall standard deviation; the specific model for mean interpolation here is as follows: Pingc Represents the Ping to be interpolated, Ping i Represents proximity to Ping and w i Here, represents the weight corresponding to the Ping distance, c represents the index of the Ping to be interpolated in the time series, and d represents the half-width of the interpolation window, i.e., d adjacent Pings are selected before and after the Ping to be interpolated for interpolation calculation; the linear grayscale transformation algorithm here is specifically as follows: , where Gray2(i) is the calibrated gray value of the i-th pixel after consistency correction, Gray(i) is the i-th original gray value in the original shallow profile image, min(Gray(i)) is the minimum gray value of the pixel in the original shallow profile image, and max(Gray(i)) is the maximum gray value of the pixel in the original shallow profile image. The initial shallow profile image refers to the basic shallow profile image obtained by the acoustic data through a preprocessing scheme. Here, the initial shallow profile image is obtained by the system sequentially removing noise from the acoustic data through wavelet thresholding, then identifying abnormal Pings through the Laida (3σ) criterion and completing the missing Pings by combining mean interpolation, weakening multiple wave interference through predictive deconvolution, and finally mapping the image gray values ​​to the [0, 255] interval through a linear gray-scale transformation algorithm to complete the consistency correction, ultimately obtaining an initial shallow profile image with continuous effective data, low noise interference, and a unified gray-scale standard.

[0034] Step 3: Extract stratigraphic feature data and comparison data from the initial shallow profile image according to the preset extraction scheme.

[0035] The extraction scheme refers to a standardized feature extraction process used to obtain key information from the initial shallow profile image that can be used for subsequent stratigraphic boundary identification. Stratigraphic feature data refers to the feature data extracted from the initial shallow profile image that can characterize local textures, layer boundaries, and other detailed information of the seafloor strata. Here, the extraction method for stratigraphic feature data involves the system inputting an initial shallow profile image of size H*W*1 into a CNN backbone network consisting of the first four convolutional stages of ResNet-34. After convolution, pooling, and residual connection operations, the image is downsampled by a factor of 16 to obtain the feature map. The comparative data refers to the data extracted from the initial shallow profile image, processed through a complete feature extraction process, and comparable to the shallow stratigraphic profile data obtained through subsequent decoding. Here, the comparative data is extracted by using the full-dimensional feature data obtained after the system performs complete feature extraction on the initial shallow profile image using a CNN-Transformer hybrid coding architecture as the comparative data.

[0036] Step 4: Substitute the stratigraphic feature data into the preset encoding function to calculate the one-dimensional data set.

[0037] The encoding function refers to the feature encoding process built on a CNN-Transformer hybrid architecture. A one-dimensional dataset refers to the one-dimensional feature sequence obtained after processing a two-dimensional stratigraphic feature map through serialization, positional encoding, and a multi-layer Transformer encoder. Here, the one-dimensional dataset is calculated by flattening the two-dimensional stratigraphic feature map Fc in spatial dimension, reshaping it into a one-dimensional sequence. Then add learnable positional codes to the sequence. Obtain the sequence with location information Then the sequence The input consists of an L-layer stacked Transformer encoder. Each layer sequentially passes through a multi-head self-attention module and a feedforward network, along with residual connections and layer normalization. Finally, after an L-layer transformation, the output is a one-dimensional sequence S(l) integrating global context information to obtain a one-dimensional data set. The residual connections are specifically... S (l−1） Represents the input sequence of the (l-1)th layer, Z (l） S represents the output of the l-th layer attention module. (l） is the final output sequence of the l-th layer, LayerNorm is the layer normalization operation, MultiHeadAttention is the multi-head self-attention module, and FFN is the feedforward network.

[0038] Step 5: Decode the one-dimensional data set according to the preset decoding scheme to obtain shallow stratigraphic profile data.

[0039] The decoding scheme refers to a feature decoding process built on a U-Net-like upsampling architecture. The shallow stratigraphic profile data refers to the stratigraphic boundary identification results, presented as pixel-level class probability maps, output by the U-Net-like decoding process. Here, the shallow stratigraphic profile data is obtained by the system restoring the one-dimensional data set to a two-dimensional feature map. Then, through the U-Net-like upsampling architecture decoding process, feature fusion, upsampling, and output prediction operations are performed sequentially. Feature fusion uses skip connections to concatenate the intermediate layer features of the corresponding scale of the CNN backbone network with the current layer features of the decoder in the channel dimension. Upsampling uses transposed convolution operations to gradually expand the feature map size to the original input size. Finally, a 1×1 convolutional layer maps the number of feature channels to 2, and a softmax function is used to generate a pixel-level class probability map as the shallow stratigraphic profile data.

[0040] Step 6: If the shallow stratigraphic profile data is consistent with the correlation data, generate and output a stratigraphic boundary image based on the shallow stratigraphic profile data.

[0041] Stratigraphic boundary images are visual images that intuitively display the location, distribution, and hierarchical structure of seafloor strata boundaries. The formation of these stratigraphic boundary images involves the system using consistent shallow stratigraphic profile data as a basis, classifying each pixel according to a pixel-level probability map to determine its background or stratigraphic interface category, and then extracting contours and optimizing edges of the stratigraphic interface pixels. The final result is a visually appealing stratigraphic boundary image that clearly displays the location, distribution, and hierarchical structure of seafloor strata boundaries. The system can store the generated stratigraphic boundary images, display them visually in an interactive interface, or export them to a common image format file as needed.

[0042] If the shallow stratigraphic profile data is consistent with the correlation data, it indicates that the processed data is not abnormal. Therefore, stratigraphic boundary images are generated and output based on the shallow stratigraphic profile data.

[0043] Step 7: If the shallow stratigraphic profile data is inconsistent with the correlation data, find a calibration scheme by comparing the shallow stratigraphic profile data with the correlation data and execute it to obtain standard shallow stratigraphic profile data.

[0044] The calibration scheme refers to the model calibration process based on a hybrid loss function. Specifically, this calibration scheme employs a hybrid loss function combining Dice loss and weighted cross-entropy loss. The function model is as follows: Where Ltotal is the total loss value, LDice is the Dice loss, λ is the weighting coefficient, and LWCE is the weighted cross-entropy loss; Dice loss promotes the overlap between the predicted and actual regions and is insensitive to class imbalance; weighted cross-entropy loss assigns higher weights λ to minority classes (interfaces). Standard shallow profile data refers to shallow profile data that can accurately characterize the boundary features of seafloor strata. The standard shallow profile data is obtained by substituting inconsistent shallow profile data and correlation data into the hybrid loss function to calculate the total loss value. Using the total loss value as the optimization objective, the encoding and decoding parameters of the model are adjusted through backpropagation, and iterative optimization is continued until the total loss value drops to a threshold and the deviation between the shallow profile data and the correlation data meets the accuracy requirements, thus obtaining the standard shallow profile data.

[0045] If the shallow stratigraphic profile data is inconsistent with the correlation data, it indicates that there is an error in the obtained stratigraphic boundary data. Therefore, a calibration scheme is found and implemented by comparing the shallow stratigraphic profile data with the correlation data to obtain standard shallow stratigraphic profile data.

[0046] Step 8: Generate and output a standard stratigraphic image based on the standard shallow profile data.

[0047] A standard stratigraphic image is a standardized visual image that accurately and intuitively displays the location, distribution, and hierarchical structure of seafloor strata. The standard stratigraphic image is generated by the system using standard shallow profile data as a basis, classifying the pixel-level category probability map to determine the background or stratigraphic interface category of each pixel, and then performing contour extraction and edge optimization on the stratigraphic interface pixels to generate the standard stratigraphic image. The output method of the standard stratigraphic image is the same as described in step 6 and will not be repeated here.

[0048] The methods for acquiring acoustic wave data include: Step 10: Obtain ship parameters.

[0049] Ship parameters refer to various core technical parameters and operational status parameters that affect shallow seabed profiling and data acquisition. These parameters are acquired by the system using onboard navigation, power monitoring, and hydrological operation terminals to collect the ship's basic technical parameters and dynamic status parameters during operation in real time. Simultaneously, the system integrates the ship's factory-calibrated inherent technical parameters, summarizing them to obtain the required ship parameters.

[0050] Step 11: Deconstruct the ship's parameters to obtain the instrument number, ship speed, and ship direction.

[0051] Instrument serial number refers to a unique identifier for all types of detection instruments and equipment carried by the vessel during seabed shallow profiling operations. This instrument serial number is obtained by having personnel in the field pre-assign unique serial numbers to the instruments installed on the vessel and input them into the system. When the system receives vessel parameters, it automatically retrieves the corresponding instrument serial number and outputs it. Vessel speed refers to the actual speed of the vessel in the water during seabed shallow profiling operations. The vessel speed is calculated by extracting speed-related monitoring data from the acquired vessel parameters, then performing unit conversion and accuracy calibration. Vessel heading refers to the actual bearing and course angle of the vessel during seabed shallow profiling operations. The vessel heading is calculated by extracting course-related monitoring data from the acquired vessel parameters, then performing angle calibration and bearing conversion.

[0052] Step 12: Obtain the transmitting instrument number and receiving instrument number based on the ship's orientation and instrument number.

[0053] The transmitting instrument number refers to the unique identifier of the instrument responsible for transmitting the sound waves. This identifier is obtained by first determining the ship's forward bearing based on its direction, then matching the transmitting instrument at that bearing, and finally extracting its unique identifier. The receiving instrument number refers to the unique identifier of the instrument responsible for receiving the sound waves. This identifier is obtained by first determining the ship's aft bearing based on its direction, then matching the receiving instrument at that bearing, and finally extracting its unique identifier. Both the transmitting and receiving instruments are independent shallow-section instruments; they are distinguished as transmitting and receiving instruments for more efficient and accurate signal transmission and reception.

[0054] Step 13: Determine the launch angle and reception angle based on the ship's speed.

[0055] The transmission angle refers to the tilt angle at which the transmitting instrument emits the sound waves towards the seabed to ensure effective reception by the receiving instrument. The transmission angle is determined by the system calculating the optimal tilt angle for effective reception of the sound waves using the ship's speed, the laws of sound wave propagation, and the instrument deployment spacing. The receiving angle refers to the tilt angle at which the receiving instrument receives the sound waves reflected from the seabed to ensure effective reception of the sound waves. The receiving angle is determined by the system calculating the optimal tilt angle for effective capture of the reflected sound waves using the ship's speed, the transmission angle, the laws of sound wave propagation, and the instrument deployment spacing.

[0056] Step 14: Adjust the launching instrument corresponding to the launching instrument number according to the launching angle.

[0057] The adjustment method for the transmitting instrument here is that the system sends an angle adjustment command to the transmitting acoustic instrument corresponding to the transmitting instrument number according to the transmission angle. After receiving the command, the instrument completes mechanical attitude adjustment through its own angle adjustment mechanism to complete the angle adjustment of the transmitting instrument.

[0058] Step 15: Adjust the receiving instrument corresponding to the receiving instrument number according to the receiving angle.

[0059] The adjustment method for the receiving instrument here is that the system sends an angle adjustment command to the receiving acoustic instrument corresponding to the receiving instrument number according to the receiving angle. After receiving the command, the instrument completes mechanical attitude adjustment through its own angle adjustment mechanism to complete the angle adjustment of the receiving instrument.

[0060] Step 16: Obtain the acoustic signal based on the transmitting instrument number, the receiving instrument number, and the preset acoustic scheme to obtain acoustic data.

[0061] The acoustic scheme refers to a combination of parameter configurations and operating commands used to control the shallow profiling instrument to complete the transmission and reception of sound waves. Here, the acoustic scheme is set by those skilled in the art according to actual detection needs and input into the system. The acoustic signal refers to the probing acoustic vibration signal emitted by the transmitting instrument according to the acoustic scheme, reflected by the seabed strata, and captured by the receiving instrument. Here, the acoustic signal is obtained by the system identifying the corresponding shallow profiling instrument based on the transmitting and receiving instrument numbers, then controlling the transmitting instrument to emit sound waves according to the parameter configuration and operating commands of the acoustic scheme, and finally capturing the acoustic signal through the receiving instrument. See [link to details]. Figure 2 The transmitting instrument emits sound waves, which are then received by the receiving instrument to provide data for subsequent data analysis. The method for obtaining sound wave data has been described in step 1 and will not be repeated here.

[0062] The methods for obtaining initial shallow profile images based on acoustic data combined with preprocessing schemes include: Step 20: Obtain the acoustic parameters corresponding to the acoustic signal.

[0063] Acoustic parameters refer to the core technical indicators of the sound waves emitted by the shallow profiling instrument, including but not limited to key parameters such as sound wave intensity and frequency. The acoustic parameters are obtained by extracting the corresponding technical indicator data from the sound wave signals collected during the detection process, followed by data analysis and verification.

[0064] Step 21: If the acoustic wave parameter is greater than the preset effective threshold, determine the acoustic wave data based on the acoustic wave signal.

[0065] The effective threshold refers to the pre-set technical indicator critical value used to determine whether the sound wave parameters meet the requirements of shallow seabed profiling operations. This effective threshold is obtained by researchers in the field through experiments based on actual detection needs.

[0066] If the acoustic wave parameter is greater than the effective threshold, it means that the signal is normally received by the receiving instrument and there will be no abnormality in the data. Therefore, the acoustic wave data is determined based on the acoustic wave signal.

[0067] Step 22: If the acoustic wave parameter is less than the effective threshold, define the acoustic wave signal as lacking an acoustic wave signal.

[0068] Lack of acoustic signal refers to acoustic signals with weak intensity that cannot meet the requirements for shallow probing operations of seabed strata.

[0069] If the acoustic wave parameter is less than the effective threshold, it indicates that the acoustic wave is abnormal and effective acoustic wave data cannot be extracted. Therefore, the acoustic wave signal is defined as lacking acoustic wave signal.

[0070] Step 23: Based on the missing acoustic signal and the preset adjacent rules, find the first adjacent signal and the second adjacent signal.

[0071] The adjacency rule refers to the rule for finding adjacent valid acoustic signals when an acoustic signal is missing. This adjacency rule is pre-defined by those skilled in the art based on chronological order, treating two consecutive times as adjacent, and then inputting the defined rules into the system. The first adjacent signal refers to a valid acoustic signal that appears immediately before the time of the missing acoustic signal acquisition. The method for finding the first adjacent signal is that the system searches for the acoustic signal immediately before the time of the missing acoustic signal acquisition, according to the chronological order requirements of the adjacency rule. The second adjacent signal refers to a valid acoustic signal that appears immediately after the time of the missing acoustic signal acquisition. The method for finding the second adjacent signal is that the system searches for the acoustic signal immediately after the time of the missing acoustic signal acquisition, according to the chronological order requirements of the adjacency rule.

[0072] Step 24: Obtain data number 1 through adjacent signal number 1.

[0073] "Data No. 1" refers to the acoustic data related to seabed strata detection obtained after analyzing and converting the adjacent signal that appeared immediately before the acquisition time of the acoustic signal. Data No. 1 is obtained by the system performing data analysis, signal feature extraction, and format conversion on the retrieved adjacent signal.

[0074] Step 25: Obtain the second data through the second adjacent signal.

[0075] Data No. 2 refers to the acoustic data related to seabed strata detection obtained after analyzing and converting the adjacent signal that appears immediately after the missing acoustic signal acquisition time. This data No. 2 is obtained by the system performing data analysis, signal feature extraction, and format conversion on the retrieved adjacent signal No. 2.

[0076] Step 26: Calculate the average data based on data one and data two.

[0077] The average data refers to the acoustic reference data for seabed strata detection and completion, obtained by calculating the values ​​of data one and data two using mean interpolation. The average data is calculated by averaging the corresponding values ​​of data one and data two using mean interpolation.

[0078] Step 27: Perform a preprocessing scheme on the acoustic data and the average data to form a complete shallow profile image and define it as the initial shallow profile image.

[0079] A complete shallow profile image refers to a complete shallow profile image of the seabed strata obtained by integrating acoustic data and averaged data. Here, the complete shallow profile image is formed by the system performing the remaining preprocessing steps based on the acoustic data and averaged data to obtain a complete shallow profile image of the seabed strata, which is then considered the initial shallow profile image.

[0080] This also includes a method for obtaining an initial shallow profile image when the acoustic signal is absent, the method comprising: Step 28: Define the acoustic signal as a missing signal.

[0081] A missing signal refers to an acoustic signal that was not successfully received by the receiving instrument during the detection process. If the receiving instrument does not receive the acoustic wave emitted by the transmitting instrument, then that acoustic signal is considered a missing signal.

[0082] Step 29: Extract the ship's real-time position using ship parameters.

[0083] The real-time position of a vessel refers to its actual geographical location at sea during detection operations. The real-time position is extracted by the system from the vessel's parameters, providing the relevant data on its actual geographical location.

[0084] Step 30: Calculate the location of the missing signal based on the missing signal, ship speed, and ship real-time position.

[0085] The location of a missing signal refers to the geographical location of the unreceived signal on the ship's detection route. The system calculates this location using linear interpolation, taking the missing signal acquisition time sequence as the time node. This is combined with the ship's speed-to-time distance traveled per unit time, and the real-time position coordinates of the ship corresponding to valid signals acquired before and after that time sequence. Through a spatial linear extrapolation algorithm, the system calculates the ship's latitude, longitude, or planar coordinates on the detection route at the time of the missing signal acquisition.

[0086] Step 31: Combine the location of the missing signal with the receiver number to form a retransmission plan and execute it to obtain the retransmission signal.

[0087] A signal retransmission scheme refers to a specialized operational plan, including instrument control and signal transmission / reception parameter configuration, for re-acquiring acoustic signals from missing signal locations. This scheme is formed by the system matching suitable detection parameters and formulating instrument control commands based on the geographical coordinates of the missing signal location and the receiving instrument number, integrating these into a targeted signal retransmission operational plan. Details will be provided in the following steps. Signal retransmission refers to the acquisition of received acoustic signals at the missing signal location. The acquisition method involves the system controlling the corresponding receiving instrument according to the established signal retransmission scheme to complete the acquisition and reception of acoustic signals at the missing signal location, thus obtaining the retransmitted signal.

[0088] Step 32: If the resend signal exists, execute step 16 to obtain the resend data.

[0089] The supplementary data refers to the acoustic data related to seabed strata detection obtained after analyzing and converting the supplementary signal. The method of obtaining the supplementary data here is the same as that described in step 16, and the obtained acoustic data is regarded as the supplementary data.

[0090] If a retransmission signal exists, it indicates that the first received signal was not received due to an underwater anomaly. However, the signal can be received normally after retransmission. Therefore, step 16 is executed to obtain the retransmission data.

[0091] Step 33: Perform a preprocessing scheme on the supplementary data and acoustic data to form a supplementary shallow profile image and define it as the initial shallow profile image.

[0092] Supplementary shallow profile images refer to shallow profile images of the seabed strata that complete the missing data by integrating supplementary data with the original acoustic data and processing it according to a preprocessing scheme. The formation of supplementary shallow profile images involves the system integrating the supplementary data with the acoustic data, completing data processing and image generation according to the remaining preprocessing scheme to form a supplementary shallow profile image, which is then defined as the initial shallow profile image.

[0093] Step 34: If the replacement signal is not available, generate and output an abnormal shallow profile image based on the location of the missing signal and the acoustic data.

[0094] An anomalous shallow profile image refers to a shallow profile exploration image of the seabed strata marked with missing data areas on an initial shallow profile image. The anomalous shallow profile image is generated by the system generating an initial shallow profile image based on valid acoustic data, locating the missing signal positions, and marking the missing areas in the corresponding regions of the initial shallow profile image. The output method of the anomalous shallow profile image is the same as described in step 6, and will not be repeated here.

[0095] If the retransmission signal is not available, it means that the distance between the seabed and the ship is beyond the range of the instrument's detection, causing the instrument to be unable to receive the transmitted sound waves. Therefore, an abnormal shallow profile image is generated and output based on the location of the missing signal and the sound wave data.

[0096] The method of combining the location of the missing signal with the receiving instrument number to formulate a retransmission scheme and executing it to obtain the retransmission signal includes: Step 310: Calculate the retransmission angle using the ship's real-time position, ship speed, and the location of the missing signal.

[0097] The retransmission angle refers to the azimuth angle at which the receiving instrument faces the location of the missing signal and transmits sound waves to that location. The system uses the installation location of the receiving instrument as the origin of the coordinate system. It calculates the Cartesian coordinates of the missing signal location relative to the receiving instrument using latitude and longitude coordinates. Then, it uses the arctangent function of the Cartesian coordinate system to calculate the azimuth angle of the receiving instrument pointing to the missing signal location. After correction based on the ship's real-time heading, the retransmission angle is obtained. Here, the retransmission angle is the angle at which the system considers the receiving instrument as both the transmitter and receiver of sound waves; therefore, the retransmission angle is the angle of the receiving instrument.

[0098] Step 311: Calculate the re-emitted sound wave parameters based on the difference between the sound wave parameters and the preset sound wave threshold.

[0099] The distinguishing sound wave threshold refers to a pre-set critical value for judging sound wave characteristics, used to differentiate between sound waves emitted by the receiving instrument itself and sound waves reflected after being emitted by the transmitting instrument. This distinguishing sound wave threshold is obtained experimentally by those skilled in the art, representing a critical value that clearly distinguishes the two types of sound waves, and then input into the system. The retransmitted sound wave parameters refer to the relevant technical data such as the frequency, amplitude, and transmission power of the sound wave when the receiving instrument transmits a retransmitted sound wave to the location of the missing signal. The retransmitted sound wave parameters are calculated by the system combining the original sound wave parameters and the distinguishing sound wave threshold, and determining the retransmitted sound wave parameters through feature differentiation calculations.

[0100] Step 312: Integrate the re-sending acoustic wave parameters and the re-sending angle to form a re-sending signal scheme.

[0101] The method for forming the retransmission signal scheme here is that the system integrates the calculated retransmission acoustic wave parameters and retransmission angle, and combines them with the corresponding receiver instrument's control command specifications to generate a complete retransmission signal operation scheme that includes instrument transmission angle calibration and retransmission acoustic wave parameter configuration.

[0102] Step 313: Adjust the receiving instrument corresponding to the receiving instrument number to the retransmission angle.

[0103] The method for adjusting the receiving instrument here is the same as that described in step 15, and will not be repeated here.

[0104] Step 314: Control the receiving instrument corresponding to the receiving instrument number to transmit and receive the sound wave signal according to the supplementary sound wave parameters to obtain the supplementary signal.

[0105] The method for transmitting and receiving sound wave signals here is as follows: the system defines the receiving instrument as both a transmitter and receiver, and issues instructions to it to transmit the sound wave signal according to the parameters for retransmission. Simultaneously, the instrument receives and collects the sound wave signal reflected from the location of the missing signal in real time, thereby obtaining the retransmission signal. See [link / reference] for details. Figure 3When it is necessary to retransmit the sound waves, the receiving instrument will simultaneously perform its original transmission operation to supplement the data.

[0106] The methods for obtaining acoustic wave data also include: Step 35: Find neighboring signals by comparing the sound wave signals with the neighboring rules.

[0107] Adjacent signals refer to other acoustic signals that are adjacent to the target acoustic signal. The method for finding adjacent signals here is that the system selects acoustic signals that are sequentially connected to the target acoustic signal from the set of detected acoustic signals according to the adjacency rules.

[0108] Step 36: Obtain the adjacent parameters corresponding to the adjacent signals.

[0109] Adjacent parameters refer to the acoustic wave characteristic parameters, acquisition location, acquisition timing, and other related technical data corresponding to adjacent signals. The method for acquiring adjacent parameters here is that the system stores the acquired acoustic wave parameters, and when the system finds an adjacent signal, it automatically matches the corresponding acoustic wave parameters as the adjacent parameters for output.

[0110] Step 37: Calculate the difference in acoustic parameters based on adjacent parameters and acoustic parameters.

[0111] The acoustic parameter difference refers to the numerical difference between the adjacent parameters of an adjacent signal and the acoustic parameters of the target acoustic signal. The acoustic parameter difference is calculated by subtracting the adjacent parameters from the target acoustic parameter along their corresponding dimensions.

[0112] Step 38: If the difference in acoustic parameters is greater than the preset change threshold, obtain the instrument spacing based on the transmitting instrument number and the receiving instrument number.

[0113] The variation threshold refers to a pre-set critical value for the difference in acoustic parameters used to determine whether abnormal fluctuations have occurred. This variation threshold is determined by those skilled in the art based on the actual data acquisition requirements, setting the acceptable threshold for variation differences and inputting it into the system.

[0114] Instrument spacing refers to the actual spatial distance between the transmitter corresponding to the transmitter's serial number and the receiver corresponding to the receiver's serial number. The instrument spacing is obtained by those skilled in the art through measurement based on the positions of the two instruments during installation and then input into the system.

[0115] If the difference in acoustic parameters is greater than the change threshold, it indicates that the difference between two adjacent data points is large. In order to ensure the accuracy and reliability of the data, the instrument spacing is obtained based on the transmitter instrument number and the receiver instrument number.

[0116] Step 39: Calculate the elapsed time based on the instrument spacing and ship speed, and simultaneously accumulate the waiting time.

[0117] Elapsed time refers to the travel time required for the receiving instrument to reach the detection location corresponding to a sound wave whose acoustic parameter difference exceeds a threshold. This elapsed time is calculated by dividing the distance between the instruments by the distance between them and the ship's speed by the distance itself. Waiting time refers to the accumulated ship travel time from the moment the acoustic parameter difference is determined to exceed the threshold until the receiving instrument reaches the corresponding detection location. This waiting time is accumulated by the system continuously tracking and adding up the elapsed time from the moment the instrument distance and speed calculations are triggered until the receiving instrument reaches the target detection location.

[0118] Step 40: When the waiting time reaches the elapsed time, an update signal is obtained based on the receiving instrument number and the acoustic scheme.

[0119] The update signal refers to the sound wave signal that has been retransmitted and received. Here, the update signal is obtained by the system controlling the receiving instrument corresponding to the receiving instrument number to retransmit the sound wave according to the sound wave scheme and then completing the signal reception.

[0120] When the waiting time reaches the elapsed time, it means that the ship has reached the geographical location of the sound wave. If the sound wave is sent again after this time, it may cause problems such as no reception or weak reception signal. Therefore, an updated signal is obtained based on the receiving instrument number and the sound wave scheme. If the waiting time has not reached the elapsed time, the waiting time continues to accumulate.

[0121] Step 41: If the update signal is inconsistent with the sound wave signal, replace the sound wave signal with the update signal to obtain the updated data.

[0122] Updated data refers to the acoustic data from seabed strata detection obtained by updating the signal through signal analysis and processing. The method for obtaining updated data has been described in step 1, and the obtained acoustic data is defined as updated data.

[0123] If the updated signal is inconsistent with the sound wave signal, it means that the previously obtained sound wave signal may have been blocked, resulting in inaccurate data transmission. Therefore, the sound wave signal is replaced with the updated signal to obtain updated data.

[0124] Step 42: If the update signal is consistent with the sound wave signal, determine the sound wave data based on the sound wave signal.

[0125] If the updated signal matches the acoustic signal, it indicates that there is no abnormality in the acoustic signal at that location. Therefore, the acoustic data is determined based on the acoustic signal.

[0126] Among them, if the update signal is consistent with the sound wave signal, the method for determining the sound wave data based on the sound wave signal includes: Step 420: Obtain the penetration threshold and combine it with the effective threshold and acoustic parameters to calculate the acoustic adjustment parameters.

[0127] The penetration threshold refers to the critical value set by which sound waves can effectively penetrate obstructions such as marine life and submarines on the ship's bottom and obtain effective detection signals from the seabed. This penetration threshold is obtained by researchers in the field through experiments to determine the sound wave's penetration capability through various objects that may appear in the ocean, and then inputting this value into the system. The specific method of obtaining this threshold will be described in the following steps. The sound wave adjustment parameters are the sound wave technical parameters used to adjust the sound wave emission characteristics of the receiving instrument, enabling the sound waves to penetrate obstructions on the ship's bottom and meet the requirements for effective seabed detection. These parameters are calculated by substituting the obtained penetration threshold, effective threshold, and current sound wave parameters into a preset sound wave feature adjustment algorithm, and then performing multi-dimensional numerical calculations to obtain the appropriate sound wave adjustment parameters.

[0128] Step 421: Control the receiving instrument corresponding to the receiving instrument number to adjust according to the acoustic adjustment parameters and execute the acoustic scheme to obtain the adjustment signal.

[0129] The adjustment signal refers to the acoustic wave signal emitted and received by the receiving instrument after adjusting its transmission characteristics according to the acoustic wave adjustment parameters and executing the preset acoustic wave scheme. The adjustment signal is obtained by the system controlling the receiving instrument corresponding to the instrument number to adjust and emit acoustic waves according to the acoustic wave adjustment parameters, and then collecting and receiving the emitted and reflected acoustic wave signals according to the acoustic wave scheme.

[0130] Step 422: If the adjustment signal and the sound wave signal are inconsistent, replace the sound wave signal with the adjustment signal to obtain the adjustment data.

[0131] Adjustment data refers to the acoustic wave data for seabed strata detection obtained by signal analysis processing of the adjustment signal. The method for obtaining adjustment data has been described in step 1, and the obtained acoustic wave data is defined as adjustment data.

[0132] If the adjustment signal and the sound wave signal are inconsistent, it means that the previous update signal was still blocked by objects or marine life, resulting in an inaccurate signal. In order to avoid large data differences, the sound wave signal is replaced with the adjustment signal to obtain the adjustment data.

[0133] Step 423: If the adjustment signal is consistent with the sound wave signal, determine the sound wave data based on the sound wave signal.

[0134] If the adjustment signal matches the sound wave signal, it indicates that there is no object or biological obstruction causing the signal abnormality. Therefore, the sound wave data is determined based on the sound wave signal.

[0135] This also includes a method for determining the acoustic wave adjustment parameters, which includes: Step 4200: Obtain historical neighbor parameters and future neighbor parameters.

[0136] Historical adjacent parameters refer to the acoustic characteristic-related technical parameters corresponding to the signal preceding the acquisition time of the target acoustic signal. These parameters are obtained by the system filtering out the parameters corresponding to the signal immediately preceding the acquisition time of the target acoustic signal according to adjacent rules. Future adjacent parameters refer to the acoustic characteristic-related technical parameters corresponding to the signal following the acquisition time of the target acoustic signal. These parameters are also obtained by the system filtering out the parameters corresponding to the signal immediately following the acquisition time of the target acoustic signal according to adjacent rules.

[0137] Step 4201: Calculate the difference in historical parameters based on the acoustic parameters and historical adjacent parameters.

[0138] The historical parameter difference refers to the numerical difference between the acoustic parameters corresponding to the target acoustic signal and their historical adjacent parameters. This historical parameter difference is calculated by subtracting the historical adjacent parameters from the target acoustic signal's numerical values.

[0139] Step 4202: Calculate the difference between future parameters based on the acoustic parameters and the parameters of future neighbors.

[0140] The future parameter difference refers to the numerical difference between the acoustic parameters corresponding to the target acoustic signal and their future adjacent parameters. The future parameter difference is calculated by subtracting the acoustic parameters from their future adjacent parameters.

[0141] Step 4203: If the historical parameter difference or the future parameter difference is less than the change threshold, step 420 is not executed.

[0142] When the difference between historical parameters or future parameters is less than the change threshold, it indicates that the acoustic parameter has a large difference from only one of the historical parameters and future parameters. The other side may be the same terrain with no abnormalities, so step 420 is not executed.

[0143] Step 4204: When both the historical parameter difference and the future parameter difference are greater than the change threshold, the effective threshold and the penetration threshold are combined to calculate the acoustic adjustment parameters.

[0144] When both the historical parameter difference and the future parameter difference are greater than the change threshold, it indicates that the sound wave parameters are indeed abnormal, possibly due to obstruction by an object. Therefore, the sound wave adjustment parameters are calculated by combining the effective threshold and the penetration threshold.

[0145] The method for obtaining the penetration threshold and calculating the acoustic adjustment parameters by combining the effective threshold with the acoustic parameters includes: Step 4205: Obtain the types of objects on the bottom of the ship.

[0146] The types of objects on the ship's bottom refer to the specific categories of various objects, such as marine organisms and man-made objects, that appear in the detection area on the bottom of the ship and may obstruct the sound waves detected by the shallow-probe instrument. The method for obtaining these types of objects is as follows: Personnel in the field integrate potential ocean objects and related data and input them into the system. The system then uses the detection equipment on board the ship to identify obstructing objects on the ship's bottom and within the detection area. Finally, the types of objects on the ship's bottom are determined by matching the obstructing objects.

[0147] Step 4206: Find the corresponding penetrating sound wave parameters by matching the type of object on the bottom of the ship with the sound wave parameters.

[0148] The penetration acoustic parameters refer to the acoustic characteristic parameters that adapt to the specific types of objects obstructing the ship's bottom, enabling sound waves to effectively penetrate such objects and achieve effective seabed strata detection. The method for finding these penetration acoustic parameters involves researchers in the field obtaining acoustic penetration data for various seabed organisms or objects through prior experiments, mapping them one-to-one, and inputting this data into the system. When the system receives the type of object on the ship's bottom, it automatically retrieves and matches the corresponding penetration acoustic parameters based on the current acoustic parameters.

[0149] Step 4207: Determine the penetration threshold based on the penetration acoustic wave parameters.

[0150] The penetration threshold is determined by the system using the retrieved sound wave parameters as the core basis, and combining the sound wave penetration ability judgment rules to extract and calibrate the corresponding minimum sound wave penetration ability critical value as the penetration threshold.

[0151] Step 4208: Determine the sound wave adjustment parameters based on the effective threshold and the transmitted sound wave parameters.

[0152] The method for determining the acoustic adjustment parameters here is as follows: the system uses the effective threshold as a constraint on the effectiveness of acoustic detection, and then combines it with the penetrating acoustic parameters of the object that is obstructed by the bottom of the ship. The acoustic parameter fusion calculation model is used to perform weighted calculations to obtain the acoustic adjustment parameters that satisfy the effectiveness of stratum detection and the penetrability of the object.

[0153] Based on the same inventive concept, embodiments of the present invention provide an intelligent identification system for stratigraphic boundaries in shallow profile images.

[0154] One of them, a shallow profile image stratigraphic boundary intelligent identification system, includes: The acquisition module is used to acquire acoustic wave data, ship parameters, acoustic wave parameters, adjacent parameters, and types of objects on the ship's bottom; The memory is used to store the program for an intelligent method of identifying stratigraphic boundaries in shallow profile images; The processor loads and executes programs from memory.

[0155] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0156] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for intelligent identification of stratigraphic boundaries in shallow profile images, characterized in that, include: Step 1: Acquire acoustic data in response to the preset formation analysis signal; Step 2: Obtain an initial shallow profile image based on the acoustic data and a preset preprocessing scheme; Step 3: Extract stratigraphic feature data and contrast data from the initial shallow profile image according to the preset extraction scheme; Step 4: Substitute the stratigraphic feature data into the preset encoding function to calculate the one-dimensional data set; Step 5: Decode the one-dimensional data set according to the preset decoding scheme to obtain shallow stratigraphic profile data; Step 6: If the shallow stratigraphic profile data is consistent with the correlation data, generate and output a stratigraphic boundary image based on the shallow stratigraphic profile data; Step 7: If the shallow stratigraphic profile data is inconsistent with the correlation data, find a calibration scheme by comparing the shallow stratigraphic profile data and the correlation data and execute it to obtain standard shallow stratigraphic profile data; Step 8: Generate and output a standard stratigraphic image based on the standard shallow profile data.

2. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 1, characterized in that, Methods for acquiring acoustic wave data include: Step 10: Obtain ship parameters; Step 11: Deconstruct the ship's parameters to obtain the instrument number, ship speed, and ship direction; Step 12: Obtain the transmitting instrument number and receiving instrument number based on the ship's orientation and instrument number; Step 13: Determine the transmission and reception angles based on the ship's speed; Step 14: Adjust the launching instrument corresponding to the launching instrument number according to the launching angle; Step 15: Adjust the receiving instrument corresponding to the receiving instrument number according to the receiving angle; Step 16: Obtain the acoustic signal based on the transmitting instrument number, the receiving instrument number, and the preset acoustic scheme to obtain acoustic data.

3. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 2, characterized in that, Methods for obtaining initial shallow profile images based on acoustic data combined with preprocessing schemes include: Step 20: Obtain the acoustic parameters corresponding to the acoustic signal; Step 21: If the acoustic wave parameter is greater than the preset effective threshold, determine the acoustic wave data based on the acoustic wave signal; Step 22: If the acoustic wave parameter is less than the effective threshold, define the acoustic wave signal as lacking an acoustic wave signal; Step 23: Based on the missing acoustic signal and the preset adjacent rules, find the first and second adjacent signals; Step 24: Obtain data number one through adjacent signal number one; Step 25: Obtain data number two through adjacent signal number two; Step 26: Calculate the average data based on data point 1 and data point 2; Step 27: Perform a preprocessing scheme on the acoustic data and the average data to form a complete shallow profile image and define it as the initial shallow profile image.

4. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 3, characterized in that, It also includes a method for obtaining an initial shallow profile image when the acoustic signal is absent, the method comprising: Step 28: Define the acoustic signal as a missing signal; Step 29: Extract the ship's real-time position using ship parameters; Step 30: Calculate the location of the missing signal based on the missing signal, ship speed, and ship's real-time position; Step 31: Combine the location of the missing signal with the receiver number to form a retransmission plan and execute it to obtain the retransmission signal; Step 32: If the retransmission signal exists, execute step 16 to obtain the retransmission data; Step 33: Perform a preprocessing scheme on the supplementary data and acoustic data to form a supplementary shallow profile image and define it as the initial shallow profile image; Step 34: If the replacement signal is not available, generate and output an abnormal shallow profile image based on the location of the missing signal and the acoustic data.

5. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 4, characterized in that, The methods for combining the location of the missing signal with the receiver number to formulate and execute a retransmission scheme to obtain the retransmission signal include: Step 310: Calculate the retransmission angle using the ship's real-time position, ship speed, and the location of the missing signal; Step 311: Calculate the retransmission sound wave parameters based on the difference between the sound wave parameters and the preset sound wave threshold; Step 312: Integrate the retransmission acoustic wave parameters and retransmission angle to form a retransmission signal scheme; Step 313: Adjust the receiving instrument corresponding to the receiving instrument number to the retransmission angle; Step 314: Control the receiving instrument corresponding to the receiving instrument number to transmit and receive the sound wave signal according to the supplementary sound wave parameters to obtain the supplementary signal.

6. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 4, characterized in that, Other methods for obtaining acoustic wave data include: Step 35: Find adjacent signals by comparing the sound wave signal with the adjacent rules; Step 36: Obtain the adjacent parameters corresponding to adjacent signals; Step 37: Calculate the difference in acoustic parameters based on adjacent parameters and acoustic parameters; Step 38: If the difference in acoustic parameters is greater than the preset change threshold, obtain the instrument spacing based on the transmitting instrument number and the receiving instrument number; Step 39: Calculate the elapsed time based on the instrument spacing and ship speed, and simultaneously accumulate the waiting time; Step 40: When the waiting time reaches the elapsed time, an update signal is obtained based on the receiving instrument number and the acoustic scheme; Step 41: If the update signal is inconsistent with the sound wave signal, replace the sound wave signal with the update signal to obtain the updated data; Step 42: If the update signal is consistent with the sound wave signal, determine the sound wave data based on the sound wave signal.

7. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 6, characterized in that, If the update signal matches the sound wave signal, the methods for determining sound wave data based on the sound wave signal include: Step 420: Obtain the penetration threshold and combine it with the effective threshold and acoustic parameters to calculate the acoustic adjustment parameters; Step 421: Control the receiving instrument corresponding to the receiving instrument number to adjust according to the acoustic adjustment parameters and execute the acoustic scheme to obtain the adjustment signal; Step 422: If the adjustment signal and the sound wave signal are inconsistent, replace the sound wave signal with the adjustment signal to obtain the adjustment data; Step 423: If the adjustment signal is consistent with the sound wave signal, determine the sound wave data based on the sound wave signal.

8. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 7, characterized in that, It also includes a method for determining the acoustic wave adjustment parameters, which includes: Step 4200: Obtain historical neighbor parameters and future neighbor parameters; Step 4201: Calculate the difference in historical parameters based on the acoustic parameters and historical adjacent parameters; Step 4202: Calculate the difference between future parameters based on the acoustic wave parameters and the parameters of future neighbors; Step 4203: If the historical parameter difference or the future parameter difference is less than the change threshold, step 420 is not executed; Step 4204: When both the historical parameter difference and the future parameter difference are greater than the change threshold, the effective threshold and the penetration threshold are combined to calculate the acoustic adjustment parameters.

9. The intelligent stratigraphic boundary identification method for shallow profile images according to claim 7, characterized in that, Methods for obtaining the penetration threshold and combining it with the effective threshold and acoustic parameters to calculate the acoustic adjustment parameters include: Step 4205: Obtain the types of objects on the bottom of the ship; Step 4206: Find the corresponding penetrating sound wave parameters by matching the type of object on the bottom of the ship with the sound wave parameters; Step 4207: Determine the penetration threshold based on the transmitted acoustic wave parameters; Step 4208: Determine the sound wave adjustment parameters based on the effective threshold and the transmitted sound wave parameters.

10. A shallow profile image stratigraphic boundary intelligent identification system, characterized in that, include: The acquisition module is used to acquire acoustic wave data, ship parameters, acoustic wave parameters, adjacent parameters, and types of objects on the ship's bottom; A memory for storing a control method and a program for a shallow profile image stratigraphic boundary intelligent identification method as described in any one of claims 1 to 9; The processor loads and executes programs from memory.

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