Submarine pipeline offset positioning method and self-adaptive sound source frequency adjusting module

Abstract

The invention relates to an ocean detection positioning technology, in particular to a submarine pipeline offset positioning method and a self-adaptive sound source frequency adjusting module. Comprising the following steps that S1, a combined intelligent pipe cleaner set is installed at an inlet of a submarine pipeline, and a sound source emitting device on the combined intelligent pipe cleaner set conducts self-adaptive adjustment on the frequency of sound wave signals generated by the sound source emitting device according to different media in the submarine pipeline through a self-adaptive sound wave frequency selection method; s2, the AUV moves along with the combined intelligent pipe cleaner set, signals sent by the combined intelligent pipe cleaner set are received in real time, and the signal propagation distance # imgabs0 # between the AUV and the combined intelligent pipe cleaner set is determined through a weighted fusion algorithm; s3, the position estimation # imgabs1 # of the AUV is updated through a Kalman filtering algorithm, and therefore the position of the submarine pipeline where the combined intelligent pipe cleaner is located is determined. The real-time positioning of the seabed offset orbit is realized, so that the real-time positioning requirements of high precision and low error in a complex seabed environment are met.

Description

Technical Field

[0001] The present invention relates to marine exploration and positioning technology, in particular to a method for offset positioning of submarine pipelines and an adaptive sound source frequency adjustment module. Background Art

[0002] At present, submarine pipelines are pipelines that continuously transport a large amount of oil (gas) under the sea through sealed pipelines. They are the main components of the offshore oil and gas field development and production system, and also the fastest, safest, and most economical and reliable offshore oil (gas) transportation method. Due to complex marine geographical environments and hydrodynamic factors, etc., submarine pipelines will experience displacements of varying degrees. In order to ensure the normal transportation and regular inspection of submarine pipelines, the positioning of offset pipelines is crucial.

[0003] In order to achieve the positioning of submarine pipelines, the methods commonly used at present are external detection methods and internal detection methods. Among them, the external detection method usually uses acoustic detection methods, and locates the position of the oil pipeline through acoustic wave detection technology, side-scan sonar, shallow stratum profile, and synthetic aperture sonar. Its existing defect is that the external detection method is greatly affected by the marine environmental topography, especially for pipelines buried under the sea floor, and its positioning effect is poor. The internal detection method mainly uses intelligent pigging devices, and signal transmitters are installed on the intelligent pigging devices, and the oil pipeline is detected through low-frequency electromagnetic waves or ultrasonic waves emitted by the signal transmitters.

[0004] The magnetic flux leakage detector (MFL) technology is a relatively mature detection method in China at present. It receives signals through a subsea pipeline beacon and then feeds back the signals to a communication buoy. However, this method has great limitations: (1) Since electromagnetic signals are easily affected by the seawater environment and the wall thickness of the pipe, the signal attenuation is fast, the detection distance is short, and the requirements for the application scenario are high; (2) This technology requires a coupling agent during the operation process, the positioning efficiency is not high and the real-time performance is poor, and the emergency real-time processing ability in the face of emergencies is not strong. Summary of the Invention

[0005] The purpose of the present invention is to overcome the above-mentioned defects existing in the prior art, and propose a method for offset positioning of submarine pipelines and an adaptive sound source frequency adjustment module, which can adaptively select the frequency of the acoustic signal of the sound source emission device according to the medium, and realize the real-time positioning of the AUV through the method of multi-source information fusion and joint optimization of time delay and intensity, so as to realize the real-time positioning of the submarine offset orbit, so as to meet the real-time positioning requirements of high precision and low error in complex submarine environments.

[0006] The technical solution of the present invention is: a method for offset positioning of submarine pipelines, which includes the following steps: S1. Install the combined intelligent pigging device group at the inlet of the subsea pipeline. The sound source emission device on the combined intelligent pigging device group adaptively adjusts the acoustic emission frequency according to different media in the subsea pipeline through the adaptive acoustic wave frequency selection method. S2. The AUV follows the combined intelligent pigging device group to move, and receives the signals sent by the combined intelligent pigging device group in real time. The signal propagation distance between the AUV and the combined intelligent pigging device group is determined through the weighted fusion algorithm. ; S3. Update the position estimation of the AUV itself through the Kalman filtering algorithm. , so as to determine the position of the subsea pipeline where the combined intelligent pigging device is located.

[0007] In the present invention, the specific implementation process of the frequency optimization algorithm in step S1 is as follows: S1.1. Acquisition and real-time feedback of environmental data; S1.2. According to the monitored environmental data, select the optimal frequency using the frequency optimization algorithm, and adjust the acoustic emission frequency of the sound source emission device. S1.3. Adopt an iterative method to dynamically find the optimal frequency in real time.

[0008] In step S1.2, determine the optimal acoustic emission frequency range f opt ∈[300Hz, 7kHz]; The calculation formula for the propagation speed V signal of the acoustic wave in the pipeline medium is: , where, represents the medium temperature value collected in real time; represents the medium pressure value collected in real time; represents the medium correction term, and its value is: , The attenuation formula of the acoustic wave intensity with the distance d: , where, d represents the distance between the actual measurement point and the sound source, with the unit of m; represents the initial signal intensity, that is, the signal intensity at the sound source, with the unit of dB; represents the reference distance, which is the reference standard for normalization; n(f) represents the attenuation factor, and its formula is: n(f)=af + b , When the medium is petroleum, a = 0.02, b = 1.1; when the medium is natural gas, a = 0.05, b = 1.6; α(f) represents the absorption coefficient of the medium for acoustic signals, with the unit of dB / m, and its calculation formula is: ; Define the comprehensive performance index J(f) to maximize the signal-to-noise ratio and minimize the attenuation: , where d max represents the maximum detection distance of the pipeline; λ represents the weight coefficient, with a value of 0.5; The calculation formula for the signal-to-noise ratio SNR(f) is: , where, represents the environmental noise power, with the unit of dB.

[0009] Solve for the optimal frequency in real time through the gradient ascent method: , Solve for the optimal frequency in real time and dynamically in an iterative manner, , where, represents the frequency update value after the (k + 1)-th iteration; represents the frequency value at the current k-th iteration; is the frequency adjustment step size; represents the comprehensive performance index at the frequency ; Set the stop condition as: ; where, represents the comprehensive performance index calculated at the frequency corresponding to the k-th iteration; represents the performance index value corresponding to the frequency after the next iteration.

[0010] The acoustic signal emitted by the combined intelligent pigging unit generates echo signals during propagation due to the multipath effect. According to the time delay of the echo signal, calculate the distance between the AUV and the combined intelligent pigging unit estimated based on the propagation time delay: , Invert the propagation distance based on the received signal strength, and the formula is: , where, Indicates the correction coefficient of signal attenuation with respect to flow velocity; V flow Indicates the current flow velocity of the medium, with the unit of m / s; Define the time delay weight factor as : , Define the signal strength weight factor as : , Adopt a weighted fusion method to calculate the final signal propagation distance : , where I max Indicates the maximum signal strength received in the environment.

[0011] In step S3, when determining the position of the combined intelligent pig and the submarine pipeline where it is located, based on the position estimation of the AUV itself as a reference, through d obtained in step S2 total and the direction vector , calculate the position (x p , y p , z p ) of the pig in the three-dimensional seabed space: .

[0012] In step S3, the specific process of updating the position estimation of the AUV itself through the Kalman filter algorithm is as follows: According to the sensors on the AUV, obtain the current state vector of the AUV , where x, y, z represent the position coordinates of the AUV in the three-dimensional space, represents the velocity component; The state prediction and covariance update formulas are: , , where, represents the predicted state; represents the control input; represents the predicted covariance matrix; A represents the system state transition matrix; B represents the control input matrix; u k represents the control input quantity; P k represents the state estimation covariance matrix; Q represents the process noise covariance matrix; Dynamically adjust the process noise matrix Q according to the motion state of the AUV and the environmental changes of the AUV: 。

[0013] Among them, represents the adjustment coefficient; V fIow represents the current medium flow velocity; V max represents the preset maximum flow velocity value; Q 0 represents the static reference process noise covariance matrix; The Kalman gain K k+1 has the following calculation formula: , The calculation formula for updating the state estimate is: , Among them, Z K+1 represents the measured value, which is provided by the USBL system, depth gauge, and acoustic reflection positioning system; H represents the observation matrix, and R represents the observation noise covariance matrix; By extracting the first three components from the updated state vector, the current real-time three-dimensional position estimate of the AUV can be obtained: ; Among them, is the first element of the updated state vector, representing the x coordinate of the AUV at the current moment; is the second element of the updated state vector, representing the y coordinate of the AUV at the current moment; is the third element of the updated state vector, representing the z coordinate of the AUV at the current moment.

[0014] This application also discloses an adaptive sound source frequency adjustment module, including: A control module, used to configure the phase register of the DDS signal generation module according to the frequency of the sound source; communicate with other modules for signal control and real-time feedback; A DDS signal generation module, used to adjust the frequency to meet the suitable emission frequency for different media of the subsea pipeline, generate an adjustable frequency signal between 300 Hz and 7 kHz; set the frequency register of the DDS through the SPI interface to generate the target frequency; use the phase accumulator to control the frequency of the output signal; accurately control the frequency by updating the phase register; select to use a low-frequency signal as the reference signal and use the frequency modulation function of the DDS to generate other frequencies; A signal filtering and amplification module, used to filter and adjust the gain of the signal generated by the DDS signal generation module, remove high-order harmonics and enhance the signal amplitude; remove unnecessary high-frequency harmonics; amplify the signal to the required amplitude; A power amplification module, used to boost the signal power so that it can drive the acoustic transducer; An output module for driving the emission of acoustic signals, which uses an acoustic transducer to convert an electrical signal into an acoustic wave through the acoustic transducer. An environmental adaptability module for ensuring the reliability of use under the seabed.

[0015] The beneficial effects of the present invention are as follows: (1) The combined intelligent pigging device group carries the sound source emission device, and adaptively adjusts the sound source frequency of the sound source emission device according to the media in different subsea pipelines, so that the sound source frequency can be adaptively adjusted according to different flowing media in the pipeline, without switching the sound source, saving costs and having strong adaptability; (2) By dynamically adjusting the acoustic wave frequency in a complex seabed environment, the positioning error problem caused by improper frequency setting in the traditional method is solved, ensuring the effect and accuracy of signal propagation. Not only is the positioning accuracy effectively improved, but also the adaptability and real-time performance of subsea pipeline positioning are significantly enhanced; (3) The present invention combines the echo time delay and signal strength information, and uses a weighted fusion algorithm to calculate the accurate position: during the transmission of the echo signal, by combining the time delay information and strength information, different weights are assigned to the signals of different paths, thereby eliminating the error caused by multipath propagation and ensuring the positioning accuracy. Description of the Drawings

[0016] Figure 1 It is a schematic structural diagram of a positioning system for implementing the subsea pipeline offset positioning method; Figure 2 It is a flow chart of adaptively adjusting the acoustic wave emission frequency by using the adaptive sound source frequency adjustment module in the first step of the present application.

[0017] In the figure: 1 subsea pipeline; 2 combined intelligent pigging device group; 3 sound source emission device; 4 AUV; 5 surface working ship; 6 sea surface communication buoy; 7 satellite. Specific Embodiments

[0018] In order to make the above-mentioned objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the drawings.

[0019] In the following description, specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0020] The subsea pipeline offset positioning method described in the present application specifically includes the following steps.

[0021] Step 1: Preparation work. Before positioning the offset of the subsea pipeline, install the combined intelligent pigging unit first.

[0022] Adjust the frequency of the acoustic wave emission according to the medium in the pipeline, and place the combined intelligent pigging unit 2 at the inlet of the subsea pipeline 1. The combined intelligent pigging unit 2 includes several pigging devices. Among them, the pigging device at the front end is a rigid foam pigging device, which is used for preliminary cleaning of the oil pipeline to prevent blockage. A sound source emission device 3 is installed at the pigging device at the rear end. Through the sound source emission device, a uniform and continuous intermediate-frequency acoustic wave signal is emitted in the pipeline. Measure the flow velocity of the medium in the subsea pipeline and calculate the flow velocity of the pigging device in the oil pipeline.

[0023] In addition, the medium in the subsea pipeline 1 is oil or natural gas. According to the different media in the pipeline, select an appropriate acoustic wave frequency. The combined intelligent pigging unit 2 advances in the subsea pipeline 1 by the flow of the medium or the pressure difference as the power. The sound source emission device 3 is mounted on the upper part of the pigging device. During the movement of the combined intelligent pigging unit 2 with the sound source emission device 3, a continuous intermediate-frequency acoustic wave signal is emitted into the subsea pipeline 1, and the information of the subsea pipeline is recorded according to the echo signal of the subsea pipeline. The above information of the subsea pipeline includes the position information of the subsea pipeline, the deliberate leakage points, the blockage points, and the material characteristic information of the pipeline.

[0024] This application can adaptively adjust the sound source frequency of the sound wave signal generated by the sound source emission device 3 according to different media in the subsea pipeline, so that the acoustic wave frequency adapts to the medium in the subsea pipeline.

[0025] This application proposes an adaptive sound source frequency adjustment module, which is used to find the intermediate-frequency band acoustic wave frequency suitable for the oil / gas medium in the pipeline. The module includes a control module, a DDS (Direct Digital Frequency Synthesis) signal generation module, a signal filtering and amplification module, a power amplification module, an output module, and an environmental adaptability module.

[0026] The control module is used to configure the phase register of the DDS signal generation module according to the frequency of the sound source, and can also communicate with other modules for signal control and real-time feedback. The control module in this embodiment can use an STM32 microcontroller.

[0027] The DDS signal generation module is used to adjust the frequency to meet the suitable emission frequency for different media in the subsea pipeline, and generate a frequency signal adjustable between 300 Hz and 7 kHz. Set the frequency register of the DDS through the SPI interface to generate the target frequency. The phase accumulator is used to control the frequency of the output signal, and the frequency is accurately controlled by updating the phase register. Select to use a low-frequency signal as the reference signal and generate other frequencies using the frequency modulation function of the DDS.

[0028] The signal filtering and amplification module is used to filter and adjust the gain of the signals generated by the DDS signal generation module, remove high-order harmonics and enhance the signal amplitude to ensure that the signal quality is suitable for driving the power amplifier and the acoustic transducer. Through the low-pass filter, unnecessary high-frequency harmonics are removed to ensure a smooth output signal and avoid interference. Through the operational amplifier, the signal is amplified to the required amplitude to ensure that the signal strength can effectively drive the downstream power amplifier.

[0029] The power amplification module is used to increase the signal power so that it can drive the acoustic transducer. The power amplification module in this embodiment can adopt a class-D amplifier. The high efficiency of the class-D amplifier makes it suitable for applications that require high power but also need low heat consumption. The class-D amplifier is used to increase the amplitude of the signal and convert it into the power suitable for driving the acoustic transducer.

[0030] The output module is used to drive the emission of acoustic signals. The output module in this embodiment adopts an acoustic transducer. Through the acoustic transducer, the electrical signal is converted into sound waves. The acoustic transducer selected in this application has an intermediate-frequency acoustic wave frequency of 300HZ - 7KHZ and can withstand the pressure and corrosion of the seabed environment at the same time.

[0031] The environmental adaptability module is used to ensure the reliability of use under the seabed, such as waterproofing and corrosion prevention, and ensure that the system has protection functions such as overheating and overcurrent protection to ensure safe and stable operation.

[0032] This application also proposes an adaptive acoustic wave frequency selection method. Through this method, the optimal frequency range can be provided for each medium such as natural gas, petroleum, etc., to ensure that the propagation loss of the signal is minimized.

[0033] In practical applications, environmental factors such as seawater temperature, flow rate, and pressure have a direct impact on the propagation speed and attenuation of sound waves. Therefore, traditional frequency selection methods often cannot meet the dynamic environmental requirements. This application can dynamically adjust the frequency settings on the intelligent pig according to the real-time collected environmental data such as seawater temperature and flow rate, and can also dynamically adjust the frequency according to the changes in the actual environment.

[0034] The above-mentioned adaptive sound source frequency adjustment module can accurately select the best frequency between 300Hz and 7kHz according to the real-time changes in the environment. Specifically, the adaptive sound source frequency adjustment module on the combined intelligent pig group can, according to the collected environmental data and in combination with the preset frequency optimization range, select the most suitable acoustic wave frequency in real time. At this time, the frequency range will be adjusted according to the environmental changes: in warmer waters, the frequency may be higher to adapt to the faster propagation of sound waves; while in colder waters or environments with a larger flow rate, the frequency is lowered to reduce attenuation and maintain a better signal strength.

[0035] The above adaptive acoustic wave frequency selection method includes the following specific steps, as Figure 2 shown.

[0036] First, the acquisition and real-time feedback of environmental data: The environmental parameters such as seawater temperature and flow velocity are monitored in real time through intelligent sensors, and the data is fed back to the control module.

[0037] Then, the frequency optimization algorithm: The control module selects the optimal frequency using the frequency optimization algorithm based on the monitored environmental data and adjusts the output frequency of the DDS signal generation module.

[0038] In a complex seabed environment, according to the medium temperature value collected in real time , the medium pressure value collected in real time , the medium type, and the pipeline geometric parameters, the optimal acoustic wave emission frequency range f opt ∈[300Hz, 7kHz] is dynamically selected to minimize signal attenuation and maximize the signal-to-noise ratio SNR. Within the above acoustic wave emission frequency range, in a relatively warm water bath, the sound source emission frequency may be relatively high to adapt to faster acoustic wave propagation; while in a colder water bath or an environment with a larger flow rate, the acoustic wave emission frequency will be automatically lowered to reduce attenuation and maintain good signal strength.

[0039] Based on the optimization of the UNESCO sound velocity formula and introducing a medium correction term, the propagation velocity V signal of acoustic waves in the pipeline medium is calculated by the formula: , where represents the medium correction term, and its value is: , The attenuation formula of acoustic wave intensity with distance d: .

[0040] where d represents the distance between the actual measurement point and the sound source, with the unit of m; represents the initial signal intensity, that is, the signal intensity at the sound source, with the unit of dB; represents the reference distance, which is the reference standard for normalization, usually selected as 1 meter; n(f) represents the attenuation factor, which is related to the acoustic wave emission frequency f emitted by the pig and the medium absorption characteristics, and its formula is: n(f)=af + b , When the medium is petroleum, a = 0.02, b = 1.1; when the medium is natural gas, a = 0.05, b = 1.6.

[0041] α(f) represents the absorption coefficient of the medium for the acoustic wave signal, with the unit of dB / m, and its calculation formula is: 。

[0042] Define the comprehensive performance index J(f) to maximize the signal-to-noise ratio and minimize the attenuation: , where d max represents the maximum detection distance of the pipeline, and its value is 100m; λ represents the weight coefficient, which is calibrated through simulation, and its value is 0.5.

[0043] The calculation formula for the signal-to-noise ratio SNR(f) is: ; where represents the environmental noise power, with the unit of dB.

[0044] Solve the optimal frequency in real time through the gradient ascent method: , Due to environmental factors, such as temperature, pressure, flow rate, medium, etc., which change with time and position, it is difficult to determine the optimal frequency through a single calculation. By gradually approaching through an iterative method, the frequency that can dynamically make the comprehensive performance index J(f) reach the optimal can be found. Therefore, this application uses an iterative method to dynamically find the optimal acoustic wave emission frequency in real time, improving the effect and accuracy of signal propagation.

[0045] , where represents the frequency update value after the (k + 1)-th iteration; represents the frequency value at the current k-th iteration; is the frequency adjustment step size, which is 10Hz in this embodiment and is used to control the frequency adjustment amplitude of each update; represents the comprehensive performance index at the frequency The gradient at this point expresses the trend of the performance index changing with the frequency.

[0046] When the improvement of the performance index caused by the change in frequency is not obvious, stop the iteration, and set the stop condition as: ; where represents the convergence threshold, with a value of 0.1; represents the comprehensive performance index calculated at the frequency corresponding to the k-th iteration; represents the frequency after the next iteration The corresponding performance index value.

[0047] When the above formula condition is satisfied, it indicates that the optimal acoustic wave emission frequency is approaching.

[0048] According to the feedback of environmental changes, the combined intelligent pigging device group automatically adjusts the acoustic wave emission frequency according to the above method to ensure the best signal propagation effect during each positioning, avoiding the accuracy problem caused by the selection of a fixed acoustic wave emission frequency.

[0049] In the second step, AUV4 follows the combined intelligent pigging device group 2 to move and receives the signals sent by the combined intelligent pigging device group 2 in real time.

[0050] Meanwhile, AUV4 uploads the position information of the oil pipe to the surface working vessel 5 through the ultra-short baseline. The surface working vessel 5 and AUV4 use the ultra-short baseline positioning system for two-way communication. The ultra-short baseline positioning system has excellent performance for mobile target positioning and has the characteristics of fast deployment and flexibility. The staff can understand the working status of the pigging device and AUV cooperation in real time on the surface working vessel.

[0051] The ultra-short baseline positioning system transmits acoustic wave signals through the surface working vessel and calculates the position of the target by receiving the response signals from the AUV. The ultra-short baseline positioning system includes acoustic transponders installed at the bottom of the surface working vessel and the underwater target device AUV.

[0052] In the process of calculating the accurate distance and azimuth between the combined intelligent pigging device group and the AUV in this application, it is set that the acoustic wave signal emitted by the combined intelligent pigging device group will generate echo signals due to the multipath effect during propagation. After the AUV receives the echo signals, the distance between the AUV and the combined intelligent pigging device group is calculated by measuring the time delay and signal intensity of the echo signals.

[0053] Let the time delay of the echo signal be , according to the time delay of the echo signal, calculate the distance d between the AUV and the combined intelligent pigging device group t .

[0054] , where represents the distance value estimated based on the propagation time delay, with the unit of m; Δt is the propagation time delay of the acoustic wave signal from the pigging device to the AUV.

[0055] To further improve the accuracy, an optimization strategy combining time delay and signal intensity is adopted. The formula for inversely inferring the propagation distance according to the received signal intensity is: ; Among them, represents the correction coefficient of flow velocity on signal attenuation, reflecting the influence of flow velocity on signal propagation; V flow represents the current medium flow velocity, with the unit of m / s.

[0056] In order to overcome the instability of a single estimation method in an environment with multipath or strong signal attenuation, the present invention uses a weighted fusion method to calculate the final propagation distance .

[0057] First, define the time delay weight factor and the signal strength , , , , Among them, represents the weight factor of time delay. The shorter the delay time, the higher the weight; represents the weight factor of signal strength. The stronger the signal, the higher the credibility; I max represents the maximum signal strength received in the environment, which is used for normalization processing.

[0058] Through the above weighted fusion method, the influences of time delay and signal strength can be synthesized to obtain a more accurate positioning result. Especially in an environment with strong multipath effects and noise, the robustness of the algorithm is enhanced.

[0059] To further improve the positioning accuracy, the Kalman filtering algorithm is used to fuse the data of multiple sensors of the AUV. In addition to the time delay and intensity information of the echo signal, the accelerometer, gyroscope, and magnetometer of the AUV also provide position information. The state vector of the AUV is , where x, y, and z are the position coordinates of the AUV in three-dimensional space, with the unit of meter (m); is the velocity component, with the unit of meter per second (m / s).

[0060] The basic process of Kalman filtering is to use the current measurement value and the state transition matrix A of the system to update the position estimate of the AUV itself : The state prediction and covariance update formula are: , ; Among them, represents the predicted state; represents the control input; represents the predicted covariance matrix; A represents the system state transition matrix; B represents the control input matrix; u k represents the control input quantity; P k represents the state estimation covariance matrix; Q represents the process noise covariance matrix.

[0061] Dynamically adjust the process noise matrix Q according to the motion state of the AUV such as speed and acceleration, and the environmental changes of the AUV such as flow velocity and pressure difference: ; where, represents the adjustment coefficient, which can dynamically adjust the noise according to factors such as flow velocity and signal quality to ensure the accuracy of the Kalman filter; V fIow represents the current medium flow velocity; V max represents the preset maximum flow velocity value for normalization; Q 0 represents the static reference process noise covariance matrix.

[0062] The Kalman gain K k+1 is calculated as follows: , The calculation formula for updating the state estimation is: , where, Z K+1 represents the measured value provided by the USBL system, depth gauge, and acoustic reflection positioning system; H represents the observation matrix, and R represents the observation noise covariance matrix.

[0063] Extract the first three components from the updated state vector to obtain the current real-time three-dimensional position estimate of the AUV: ; where, is the first element of the updated state vector, representing the x coordinate of the AUV at the current moment; is the second element of the updated state vector, representing the y coordinate of the AUV at the current moment; is the third element of the updated state vector, representing the z coordinate of the AUV at the current moment.

[0064] The three-dimensional coordinate calculation of the combined intelligent pigging device group is based on the current spatial coordinates of the AUV. Through the known relative distance d total and the direction vector , calculate the position (x p , y p , z p ) of the combined intelligent pigging device group and the submarine pipeline it is located in the three-dimensional space of the seabed: ; where: (x, y, z) AUV represents the current real-time position of the AUV; represents the unit direction vector.

[0065] Through the above fusion algorithm, when determining the real-time position of the AUV, acoustic positioning, sensor data, and multipath effects can be considered simultaneously to provide a more accurate positioning result.

[0066] For example Figure 1 As shown, a sea surface communication buoy 6 can also be carried on the AUV4. When the submarine pipeline 1 becomes blocked or leaks, the signal emitted by the combined intelligent pigging device group 2 generates an echo signal when the sound source contacts the inner wall of the submarine pipeline 1. The echo signal not only provides information on the sound source position but can also be used to detect potential pipeline leakage points. By analyzing the echo signal intensity and the time delay of the echo signal , the control module can determine whether the echo signal is abnormally strong or has an abnormal time delay, thereby identifying possible leakage points. Leakage points will cause abnormal reflection intensity of the echo signal, and the intensity of the echo is related to factors such as signal attenuation and the nature of the obstacle.

[0067] By setting a threshold I, when the echo intensity exceeds this threshold, the control system can mark this point as a potential leakage position, record and store it, and then record the position information in the surface buoy. At this time, the AUV4 releases the sea surface communication buoy 6. After the sea surface communication buoy 6 emerges from the water surface, it can use the surface working ship 6 or satellite 7 to locate the position of the pipeline leakage or blockage.

[0068] After the sea surface communication buoy 6 carried by the AUV4 emerges from the water surface, it emits continuous electromagnetic signals to the satellite 7 and the surface working ship 6. The satellite 7 and the surface working ship 6 can locate the position of the pipeline leakage or blockage based on this electromagnetic signal, realizing comprehensive communication among the air, sea surface, and seabed, as Figure 1 shown.

[0069] The above has introduced in detail the method for offset positioning of submarine pipelines and the adaptive sound source frequency adjustment module provided by the present invention. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention. The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for locating a submarine pipeline offset, characterized in that: The following steps are involved: S1. Install the combined intelligent pig group at the entrance of the submarine pipeline. The sound source emission device on the combined intelligent pig group uses an adaptive sound wave frequency selection method to adaptively adjust the sound wave emission frequency generated by it according to different media in the submarine pipeline; S2, the AUV follows the combined intelligent pig group and receives the signal from the combined intelligent pig group in real time, and determines the signal propagation distance between the AUV and the combined intelligent pig group through the weighted fusion algorithm ; S3: Update the AUV's own position estimate through the Kalman filter algorithm , thereby determining the location of the submarine pipeline where the combined intelligent pig is located.

2. The method for locating the offset of a submarine pipeline according to claim 1, characterized in that: The specific implementation process of the frequency optimization algorithm in step S1 is as follows: S1.1、Collection and real-time feedback of environmental data; S1.

2. According to the monitored environmental data, the frequency optimization algorithm is used to select the optimal frequency and adjust the sound wave emission frequency of the sound source emission device; S1.

3. Use an iterative method to dynamically find the optimal frequency in real time.

3. The method for locating the offset of a submarine pipeline according to claim 2, characterized in that: In step S1.2, determine the optimal sound wave emission frequency range f opt ∈[300Hz,7kHz]; The propagation speed of sound waves in the pipeline medium is V signal The calculation formula is: ， in, Indicates the medium temperature value collected in real time; Indicates the medium pressure value collected in real time; Indicates the medium correction item, its value is: ， The attenuation formula of sound wave intensity with distance d is: ， in, d Indicates the distance between the actual measurement point and the sound source, in meters; Indicates the initial signal strength, that is, the signal strength at the sound source, in dB; represents the reference distance, which is used as the reference standard for normalization; n(f) represents the attenuation factor, and its formula is: n(f)=af+b ， When the medium is oil, a=0.02, b=1.1; when the medium is natural gas, a=0.05, b=1.6; α(f) represents the absorption coefficient of the medium to the sound wave signal, the unit is db / m, and its calculation formula is: ； Define the comprehensive performance index J(f) to maximize the signal-to-noise ratio And minimize the falloff: , Among them, d max Indicates the maximum detection distance of the pipeline; λ indicates the weight coefficient, which is 0.5; The calculation formula of signal-to-noise ratio SNR(f) is: , in, Indicates the ambient noise power in dB.

4. The method for locating the offset of a submarine pipeline according to claim 2, characterized in that: In step S1.3, the optimal frequency is solved in real time by the gradient ascent method: , The optimal frequency is solved dynamically in real time using an iterative method. ， in, Represents the frequency update value after the k+1th iteration; Indicates the frequency value at the current k-th iteration; To indicate the frequency adjustment step; Indicates comprehensive performance indicators In frequency The gradient at Set the stop condition to: ； in, Indicates the corresponding frequency at the kth iteration When , the comprehensive performance index is calculated; Indicates the frequency after the next iteration The corresponding performance indicator value.

5. The method for locating the offset of a submarine pipeline according to claim 2, characterized in that: In step S2, the acoustic wave signal emitted by the combined intelligent pipe cleaning device group generates an echo signal due to the multipath effect during the propagation process. , calculate the distance between the AUV and the combined intelligent pig group based on the propagation time delay estimation : , Reversely estimate the propagation distance based on the received signal strength The formula is: ， in, Indicates the correction factor of flow velocity on signal attenuation; V flow Indicates the current medium flow rate in m / s; Define the time delay weight factor as : ， Define the signal strength weight factor as : , The final signal propagation distance is calculated using the weighted fusion method : , Among them, I max Indicates the maximum signal strength received in the environment.

6. The method for locating the offset of a submarine pipeline according to claim 1, characterized in that: In step S3, when determining the position of the combined intelligent pig and the submarine pipeline where it is located, the position of the AUV itself is estimated. As a benchmark, the d obtained in step S2 total With direction vector , calculate the position of the pipe cleaner in the three-dimensional space of the seabed (x p ,y p ,z p ): 。 7. The method for locating the offset of a submarine pipeline according to claim 1, characterized in that: In step S3, the AUV’s own position estimate is updated using the Kalman filter algorithm. The specific process is as follows: Get the current state vector of the AUV based on the sensors on the AUV , where x, y, z represent the position coordinates of the AUV in three-dimensional space, represents the velocity component; The state prediction and covariance update formula is: ， ， in, Indicates the status of the prediction; represents control input; represents the predicted covariance matrix; A represents the system state transfer matrix; B represents the control input matrix; u k Indicates the control input; P k represents the state estimation covariance matrix; Q represents the process noise covariance matrix; According to the motion state of the AUV and the environmental changes of the AUV, the process noise matrix Q is dynamically adjusted: ； in, Indicates the adjustment coefficient; V fIow Indicates the current medium flow rate; V max represents the preset maximum flow rate value; Q0 represents the static reference process noise covariance matrix; Kalman gain K k+1 The calculation formula is: ， The updated state estimate is calculated as: ， Among them, Z K+1 represents the measurement value, which is provided by the USBL system, depth meter, and acoustic reflection positioning system; H represents the observation matrix, and R represents the observation noise covariance matrix; By extracting the first three components in the updated state vector, we can obtain the current real-time 3D position estimate of the AUV: ； in, is the first element of the updated state vector, which represents the x-coordinate of the AUV at the current moment; The second element of the updated state vector represents the y coordinate of the AUV at the current moment; The third element of the updated state vector represents the z coordinate of the AUV at the current moment.

8. An adaptive sound source frequency adjustment module, characterized in that: This module includes: The control module is used to configure the phase register of the DDS signal generation module according to the emission frequency of the sound source; communicate with other modules to perform signal control and real-time feedback; The DDS signal generation module is used to adjust the frequency to meet the suitable transmission frequency for different media of the submarine pipeline, and generate an adjustable frequency signal between 300Hz and 7kHz; set the frequency register of the DDS through the SPI interface to generate the target frequency; use the phase accumulator to control the frequency of the output signal; accurately control the frequency by updating the phase register; select a low-frequency signal as the reference signal and use the frequency modulation function of the DDS to generate other frequencies; The signal filtering and amplification module is used to filter and adjust the gain of the signal generated by the DDS signal generation module, remove high-order harmonics and enhance the signal amplitude; remove unnecessary high-frequency harmonics; amplify the signal to the required amplitude; A power amplifier module, used to increase the signal power so that it can drive the acoustic transducer; The output module is used to drive the emission of the acoustic wave signal, and uses an acoustic transducer to convert the electrical signal into an acoustic wave; Environmental adaptability module; used to ensure reliability for subsea use.

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