A method, system, electronic device and storage medium for measuring the heave height of the ocean

Abstract

A method, system, electronic device and storage medium for measuring the heave height of the ocean, which relates to the technical field of heave height measurement. The method includes: obtaining the acceleration signal, water pressure information and vertical position information of the ship during navigation; performing integral processing on the acceleration signal to obtain the first heave height data, calculating the second heave height data according to the water pressure information, and calculating the third heave height data according to the vertical position information; performing band-pass frequency division processing on the first heave height data, the second heave height data and the third heave height data to obtain the ocean heave height in multiple frequency bands; calculating the height phase difference corresponding to each frequency band based on each ocean heave height, and screening out the target frequency bands with the height phase difference less than the phase difference threshold; calculating the target heave height of the ship according to the ocean heave height of each target frequency band. Implementing the technical solution provided by this application achieves the effect of improving the accuracy of heave height measurement.

Description

Technical Field

[0001] This application relates to the technical field of heave height measurement, and particularly relates to a method, system, electronic device and storage medium for measuring ocean heave height. Background Art

[0002] With the continuous deepening of ocean resource development and ocean scientific research, the analysis of the motion state of ships during offshore operations has become increasingly important. Among them, the heave height of the ship, as a key parameter to measure the vertical movement of the ship, is of great significance for ship stability assessment, offshore platform operation safety, and ocean environment monitoring.

[0003] Currently, the existing methods for measuring ocean heave height mainly measure the heave height of a ship in navigation through separate measuring devices such as sensors. However, in actual applications, due to the complex sea conditions during ship navigation, it is difficult to comprehensively grasp the heave situation of the ship during navigation by only using a single measuring device for heave height measurement, and the measurement results often have errors, thus reducing the accuracy of ocean heave height measurement. Summary of the Invention

[0004] This application provides a method, system, electronic device and storage medium for measuring ocean heave height, which has the effect of improving the accuracy of ocean heave height measurement.

[0005] In a first aspect, this application provides a method for measuring ocean heave height, including:

[0006] Obtaining the acceleration signal collected by the inertial navigation unit, the water pressure information collected by the pressure sensor, and the vertical position information collected by the GPS receiver during the navigation of the ship;

[0007] Performing integral processing on the acceleration signal to obtain first heave height data, calculating second heave height data according to the water pressure information, and calculating third heave height data according to the vertical position information;

[0008] Performing band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain ocean heave heights in multiple frequency bands;

[0009] Calculating the height phase difference corresponding to each frequency band based on each ocean heave height, and screening out the target frequency bands with the height phase difference less than the phase difference threshold;

[0010] Calculating the target heave height of the ship according to the ocean heave heights in each target frequency band.

[0011] In a second aspect of this application, a system for measuring ocean heave height is provided. The system includes:

[0012] An information acquisition module, configured to acquire an acceleration signal collected by an inertial navigation unit during the navigation of a ship, a water pressure information collected by a pressure sensor, and a vertical position information collected by a GPS receiver;

[0013] A heave height data determination module, configured to perform integral processing on the acceleration signal to obtain a first heave height data, calculate a second heave height data according to the water pressure information, and calculate a third heave height data according to the vertical position information;

[0014] A target frequency band determination module, configured to perform band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain ocean heave heights in multiple frequency bands; calculate a height phase difference corresponding to each frequency band based on each ocean heave height, and screen out a target frequency band with the height phase difference less than a phase difference threshold;

[0015] A height measurement module, configured to calculate a target heave height of the ship according to the ocean heave heights in each target frequency band.

[0016] In a third aspect of the present application, an electronic device is provided, including a memory, a processor, and a program stored on the memory and executable on the processor. When the program is loaded and executed by the processor, it can implement a method for measuring ocean heave height.

[0017] In a fourth aspect of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is enabled to implement a method for measuring ocean heave height.

[0018] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0019] By adopting the above technical solution, by acquiring the acceleration signal of the inertial navigation unit, the water pressure information of the pressure sensor, and the vertical position information of the GPS receiver, the first heave height data, the second heave height data, and the third heave height data are respectively calculated, thereby realizing the collaborative acquisition of multi-source data. Further, by performing band-pass frequency division processing on the three heave height data, the ocean heave height in different frequency bands can be separated, effectively avoiding the errors that may be brought by single-frequency band measurement. At the same time, by calculating the height phase difference corresponding to each frequency band and screening out the target frequency bands with the height phase difference less than the phase difference threshold, the abnormal data caused by the complex sea conditions during ship navigation can be effectively eliminated, improving the reliability of the data. Finally, based on the ocean heave height of the screened target frequency bands, the target heave height of the ship is calculated, ensuring the effectiveness of the measurement data, thereby avoiding the problem that it is difficult to comprehensively grasp the heave situation during ship navigation only by using a single measurement device, and achieving the effect of improving the accuracy of ocean heave height measurement. Description of the Drawings

[0020] Figure 1 is a schematic flowchart of a method for measuring ocean heave height provided by an embodiment of the present application;

[0021] Figure 2 is a schematic structural diagram of a system for measuring ocean heave height provided by an embodiment of the present application;

[0022] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0023] Description of the reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed Embodiments

[0024] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0025] In the description of the embodiments of the present application, words such as "for example" or "for illustration" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "for example" or "for illustration" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of words such as "for example" or "for illustration" is intended to present relevant concepts in a specific manner.

[0026] In the description of the embodiments of the present application, the term "plural" means two or more. For example, plural systems refer to two or more systems, and plural screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "include", "comprise", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0027] Embodiments of the present application provide a method for measuring the heave height of the ocean. In one embodiment, please refer to Figure 1 , Figure 1 which is a schematic flowchart of the method for measuring the heave height of the ocean provided by the embodiments of the present application. This method can be implemented relying on a computer program, which can be integrated into an application or run as an independent tool-type application. This method can also be implemented relying on a single-chip microcomputer and can also run on an ocean heave height measurement system based on the von Neumann architecture. Specifically, this method may include the following steps:

[0028] Step 101: Obtain the acceleration signal collected by the inertial navigation unit, the water pressure information collected by the pressure sensor, and the vertical position information collected by the GPS receiver during the navigation of the ship.

[0029] Among them, the acceleration signal collected by the inertial navigation unit refers to the linear acceleration data of the ship in the vertical direction. This acceleration signal reflects the change in the vertical motion acceleration of the ship under the action of sea waves and contains high-frequency motion information caused by wave impact, hull vibration, etc. Since the sampling frequency of the inertial navigation unit is relatively high, it can accurately capture the instantaneous vertical motion changes of the ship.

[0030] The water pressure information collected by the pressure sensor refers to the water pressure information measured by the pressure sensor installed at the underwater position of the ship. This water pressure information reflects the sum of the hydrostatic pressure and the hydrodynamic pressure at the depth where the sensor is located. Among them, the hydrostatic pressure is proportional to the water depth, and the hydrodynamic pressure changes with the heave motion of the ship. Since the water pressure information is mainly affected by the heave motion of the ship and the change in water depth, it relatively stably reflects the intermediate-frequency motion characteristics of the ship.

[0031] The vertical position information collected by the GPS receiver refers to the height data of the ship relative to the mean sea level. This position information is obtained through the GPS satellite positioning system and can provide the absolute height value of the ship in the earth coordinate system, which can effectively reflect the low-frequency motion and long-term position changes of the ship and provide a reference for the measurement of the heave height.

[0032] Specifically, it is first necessary to obtain multi-source data information during the ship's navigation. Specifically, during the ship's navigation, the acceleration signal of the ship is collected in real time through an inertial navigation unit installed on the ship, and this acceleration signal can reflect the instantaneous motion changes of the ship in the vertical direction; at the same time, the water pressure information is collected through a pressure sensor installed at the underwater position of the ship, and this water pressure information can reflect the pressure changes of the ship at different water depths; in addition, the vertical position information is collected through a GPS receiver installed on the ship's deck, and this vertical position information can reflect the absolute position changes of the ship relative to the sea level. Among them, the acceleration signal collected by the inertial navigation unit has a high sampling frequency and is suitable for capturing the high-frequency motion characteristics of the ship; the water pressure information collected by the pressure sensor is less affected by the buoyancy of seawater and can stably reflect the medium-frequency motion characteristics of the ship; although the vertical position information collected by the GPS receiver has a low sampling frequency, it can effectively reflect the low-frequency motion characteristics of the ship. By synchronously collecting these three different types of data information, the motion characteristics of the ship in different frequency ranges can be comprehensively obtained, laying a foundation for accurately calculating the heave height of the ship subsequently. In practical applications, the sampling frequencies of the inertial navigation unit, the pressure sensor, and the GPS receiver can be set to 100Hz, 10Hz, and 1Hz respectively, and these three types of data are synchronously marked through timestamps to ensure the time consistency of the data. This multi-source data acquisition method overcomes the limitations of a single measurement device in complex sea conditions, improves the reliability and comprehensiveness of data acquisition, and provides rich data support for the accurate calculation of the subsequent heave height.

[0033] Step 102: Integrate the acceleration signal to obtain the first heave height data, calculate the second heave height data based on the water pressure information, and calculate the third heave height data based on the vertical position information.

[0034] Among them, the first heave height data refers to the height data obtained by performing double integration on the vertical acceleration signal collected by the inertial navigation unit. This data mainly reflects the heave motion characteristics of the ship in the high-frequency band and is particularly sensitive to rapid heave changes in a short period of time.

[0035] The second heave height data refers to the height data obtained by converting the water pressure information. This data mainly reflects the actual position changes of the ship in the water. Due to the stability of the water pressure, it can better reflect the heave motion characteristics in the medium-frequency band and is not easily affected by high-frequency interferences such as hull vibrations.

[0036] The third heave height data refers to the GPS vertical position information after differential correction and low-pass filtering. This data reflects the absolute height change of the ship relative to the mean sea level, mainly used to capture the heave motion characteristics in the low-frequency band, and can effectively reflect the slow heave changes caused by factors such as tides and long-period waves, providing a reference benchmark for the overall heave height.

[0037] Specifically, to obtain the heave height data of the ship, corresponding processing and conversion need to be performed on the three collected signals. First, for the acceleration signal collected by the inertial navigation unit, since this signal contains interference information such as zero drift, the zero drift signal needs to be removed by high-pass filtering first, and then the filtered acceleration signal is integrated once to obtain the velocity signal. Since the integration process may introduce cumulative errors, the obtained velocity signal needs to be zero-mean processed to eliminate integration drift, and then the processed velocity signal is integrated twice to finally obtain the first heave height data. For the water pressure information collected by the pressure sensor, considering that the actual installation position of the pressure sensor will affect the measurement result, first obtain the installation depth of the pressure sensor, then calculate the corresponding water depth data according to the water pressure information, and then subtract the installation depth from the water depth data to obtain the second heave height data. For the vertical position information collected by the GPS receiver, since the GPS signal may be affected by factors such as multipath effects and generate errors, the vertical position information needs to be differentially corrected first to improve the accuracy, and low-pass filtering is used to remove the high-frequency noise in the signal, and the corrected and low-pass filtered vertical position information is used as the third heave height data. In this way, the three original signals with different natures are all converted into a unified heave height data format, making subsequent data fusion and analysis processing possible. This processing method not only eliminates the interference factors in various signals, but also maintains the integrity of the motion characteristics in different frequency bands, laying a foundation for subsequent band-pass frequency division processing, so as to more accurately reflect the heave motion characteristics of the ship in different frequency ranges.

[0038] Based on the above embodiments, as an optional embodiment, in step 102: Integrating the acceleration signal to obtain the first heave height data, calculating the second heave height data according to the water pressure information, and calculating the third heave height data according to the vertical position information. This step may further include the following steps:

[0039] Step 201: Use high-pass filtering to remove the zero drift signal in the acceleration signal, and perform a first integration calculation on the high-pass filtered acceleration signal to obtain the velocity signal.

[0040] Specifically, to obtain an accurate speed signal, it is necessary to first perform high-pass filtering on the acceleration signal collected by the inertial navigation unit. Since the inertial navigation unit is affected by factors such as temperature changes and mechanical vibrations during operation, zero drift will occur, which will lead to cumulative errors in the subsequent integration process. Therefore, a second-order Butterworth high-pass filter with a cut-off frequency of 0.01 Hz is used to filter the original acceleration signal. This filter has good phase-frequency characteristics and can effectively remove low-frequency drift while maintaining the signal phase unchanged. The selection of the filter order and cut-off frequency is based on a large amount of experimental data analysis, which can not only ensure the effective suppression of the zero-drift signal but also not overly attenuate the effective motion signal. The filtered acceleration signal is then numerically integrated by the improved trapezoidal integration method, and the integration time step is set to 0.01 s. The trapezoidal integration method is selected because of its good numerical stability and calculation accuracy. By using linear interpolation approximation in each integration interval, the error caused by discrete sampling can be effectively reduced. At the same time, a sliding window technique is adopted during the integration process, and the window length is set to 10 s, which can improve the integration accuracy while ensuring real-time performance. This processing method not only effectively eliminates the zero-drift interference in the acceleration signal but also ensures the accuracy and continuity of the speed signal through a scientific integration strategy.

[0041] Step 202: Perform zero-mean processing on the speed signal, and perform double integration on the zero-mean processed speed signal to obtain the first heave height data.

[0042] Specifically, to further improve the accuracy of heave height calculation, it is necessary to perform zero-mean processing on the obtained speed signal. Specifically, during implementation, the speed signal is first segmented with an observation period of 60 s. The selection of this period takes into account the balance between the periodic characteristics of ship motion and calculation efficiency. When calculating the mean value of each segment of the signal, a weighted average method is used, and different weights are assigned to the data at different times according to the reliability of the signal, which improves the accuracy of mean value calculation. The calculated mean value is subtracted from the original speed signal to obtain a zero-mean speed signal. This processing method can effectively eliminate the DC component and low-frequency drift in the speed signal. Then, the improved Simpson integration method is used to perform double integration on the zero-mean processed speed signal. This method has higher accuracy than the trapezoidal integration. During the integration process, an adaptive step size control strategy is introduced, and the integration step size is dynamically adjusted according to the signal change rate. A smaller step size is used at the places where the signal changes violently to improve the accuracy. At the same time, cubic spline interpolation is used for signal reconstruction in each integration interval to reduce the error caused by sampling discretization. The finally obtained first heave height data has high time resolution and calculation accuracy and can accurately reflect the high-frequency heave motion characteristics of the ship.

[0043] Step 203: Obtain the installation depth of the pressure sensor; calculate the corresponding water depth data based on the water pressure information, and subtract the installation depth from the water depth data to obtain the second heave height data.

[0044] Specifically, to accurately obtain the second heave height data, it is first necessary to precisely measure the installation depth of the pressure sensor. During sensor installation, a high-precision sonar depth finder is used to measure the installation position multiple times, and the optimal installation depth value is determined through statistical methods. Then, based on the water pressure information collected by the pressure sensor, an improved water pressure - water depth conversion model is used for calculation. This model takes into account the variation characteristics of seawater density with depth, temperature, and salinity, and density correction is performed through real-time CTD data. Specifically, a stratified integration method is used to calculate the water depth, dividing the water column into multiple layers, each layer using a different density value to improve the conversion accuracy. At the same time, considering the temperature drift characteristics of the pressure sensor, a temperature compensation mechanism is introduced to correct the pressure value through real-time temperature monitoring data. In addition, a model for the influence of waves on water pressure is established, and the water depth calculation result is corrected by analyzing the dynamic pressure changes caused by waves. Finally, the calculated water depth data is subtracted from the temperature-compensated sensor installation depth to obtain the second heave height data. This processing method comprehensively considers the influence of marine environmental factors and significantly improves the measurement accuracy of heave height based on water pressure.

[0045] Step 204: Perform differential correction on the vertical position information and use low-pass filtering to remove high-frequency noise in the vertical position information; use the corrected and low-pass filtered vertical position information as the third heave height data.

[0046] Specifically, to obtain high-precision third heave height data, it is first necessary to comprehensively perform differential correction on the vertical position information collected by the GPS receiver. The network RTK technology is adopted, and a virtual reference station network is formed by selecting the three nearest GPS reference stations to achieve centimeter-level positioning accuracy. During data transmission, an improved wireless communication protocol is used to ensure the real-time and reliability of the correction data. During differential correction, the correction data of multiple reference stations is fused through the Kalman filtering algorithm, considering the influence of error sources such as atmospheric delay and multipath effect. Then, a low-pass filter with an adaptive cut-off frequency is used to filter the corrected data. This filter can dynamically adjust the cut-off frequency according to the signal-to-noise ratio, varying between 0.05 Hz and 0.2 Hz. At the same time, the wavelet analysis method is used to detect and remove abnormal points to improve the reliability of the data. In addition, a model for the influence of ship attitude on the GPS antenna position is established, and the vertical position is compensated through the data of the attitude sensor. The vertical position information after these processes is used as the third heave height data, which has high long-term stability and absolute accuracy and can effectively reflect the low-frequency heave motion characteristics of the ship.

[0047] Step 103: Perform band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain ocean heave heights in multiple frequency bands.

[0048] Among them, band-pass frequency division processing refers to a processing method that performs frequency-selective filtering on the input signal through a band-pass filter. This method allows signals within a specific frequency range to pass through while suppressing signal components outside this frequency range.

[0049] Ocean heave height refers to the displacement change of a ship in the vertical direction relative to the mean sea level during its voyage at sea. This change comprehensively reflects the vertical motion characteristics of the ship affected by various ocean dynamic factors such as sea waves, wind force, and tides.

[0050] Specifically, to make full use of the advantages of the three heave height data in different frequency ranges, it is necessary to perform band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data. In specific implementation, first, based on the ship motion characteristics and ocean wave theory, the frequency range of the heave motion is divided into three frequency bands: high-frequency band (e.g., 0.5 Hz - 2 Hz), medium-frequency band (e.g., 0.1 Hz - 0.5 Hz), and low-frequency band (e.g., 0 - 0.1 Hz). For each frequency band, a fourth-order Butterworth band-pass filter is used for signal frequency division. The fourth-order filter is selected to ensure a relatively steep cut-off characteristic while avoiding excessive distortion of the signal phase. In actual processing, to reduce the oscillation effect at the frequency band edge, a 0.02 Hz transition band is set between adjacent frequency bands, and a Hanning window function is used for smoothing processing. For the first heave height data, its high-frequency band components are mainly extracted because the inertial navigation unit is sensitive to high-frequency motion; for the second heave height data, its medium-frequency band components are mainly extracted because the water pressure information most accurately reflects the medium-frequency motion characteristics; for the third heave height data, its low-frequency band components are mainly extracted because GPS data is suitable for reflecting slow heave changes. During the frequency division process, a sliding window technique is used for real-time processing. The window length is set to 60 s, and the overlap rate is 50%. This not only ensures the continuity of data processing but also avoids the influence of the window edge effect. Through this band-pass frequency division processing, not only the effective separation of the three heave height data in the frequency domain is achieved, but also a foundation for subsequent data fusion is laid. The finally obtained ocean heave height data in multiple frequency bands has clear physical meanings. The high-frequency band mainly reflects the rapid heave motion of the ship caused by wind and waves, the medium-frequency band reflects the periodic heave motion caused by normal sea waves, and the low-frequency band reflects the slow heave changes caused by tides and long-period waves, thus achieving an accurate description of the ship's heave motion in the full frequency band.

[0051] Based on the above embodiments, as an alternative embodiment, in step 103: perform band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain the ocean heave height of multiple frequency bands. This step may further include the following steps:

[0052] Step 301: Perform Fourier transform on the first heave height data, the second heave height data, and the third heave height data to obtain spectral data.

[0053] Specifically, to analyze the frequency characteristics of the heave height data, it is necessary to perform Fourier transform processing on the three types of heave height data. In specific implementation, first, preprocess the data, including removing outliers and linear trends, and use the Hanning window function to window the data to reduce spectral leakage. Then, adopt the fast Fourier transform algorithm for frequency domain conversion, and select 1024-point FFT to ensure sufficient frequency resolution. To improve the reliability of spectral estimation, the Welch method is used for power spectral density estimation. The data is divided into multiple overlapping segments (overlap rate 50%), and the periodogram is calculated for each segment of data and then averaged. Through this processing method, not only the accuracy of spectral analysis is improved, but also the influence of random noise is effectively reduced. The obtained spectral data contains amplitude spectrum and phase spectrum information, and completely retains the frequency characteristics of the heave motion.

[0054] Step 302: Divide the spectral data into segmented spectral data corresponding to multiple frequency bands according to a preset frequency interval, and extract the significant wave height and heave period in each segmented spectral data.

[0055] Specifically, based on the ship motion characteristics and ocean wave theory, the obtained spectral data is divided into multiple frequency bands according to a preset frequency interval. Specifically, the frequency range of 0 - 2 Hz is divided into a high-frequency band (0.5 Hz - 2 Hz), a medium-frequency band (0.1 Hz - 0.5 Hz), and a low-frequency band (0 - 0.1 Hz). During the division process, a band-limited filter is used to segment the spectral data, and a transition band (bandwidth 0.02 Hz) is used at the frequency band junction to reduce the mutation effect. For the segmented spectral data of each frequency band, the significant wave height is calculated through the zero-order and second-order spectral moments. The specific method is to take the square root of the area under the spectral curve and multiply it by a preset coefficient to obtain the significant wave height value; the heave period is calculated through the ratio of the -1-order and 0-order spectral moments. This period reflects the main period characteristics of the motion in each frequency band. At the same time, an adaptive threshold mechanism is introduced to automatically adjust the determination criterion of the effective frequency components according to the signal-to-noise ratio, improving the accuracy of feature extraction.

[0056] Step 303: Calculate the corresponding ocean heave height by combining the significant wave height and heave period of each frequency band.

[0057] Specifically, to obtain the ocean heave height of each frequency band, it is necessary to calculate by combining the extracted significant wave height and heave period. During specific implementation, first, a heave motion model based on ocean wave theory is constructed, which takes into account the superposition effect of waves in different frequency bands. For each frequency band, according to its significant wave height and heave period, the modified Longuet-Higgins probability distribution model is used to calculate the corresponding heave height. A frequency band weight coefficient is introduced during the calculation process, and this coefficient is dynamically adjusted based on the signal-to-noise ratio and reliability of the data in each frequency band. At the same time, considering the phase relationship of the motions in different frequency bands, the final heave height is determined through phase superposition analysis. This calculation method not only considers the independent contributions of the motions in each frequency band but also includes the interactions between them, making the obtained ocean heave height more in line with the actual situation. The ocean heave heights of each frequency band finally obtained can accurately reflect the vertical motion characteristics of the ship on different time scales, providing a reliable basis for ship motion attitude analysis and operation safety assessment.

[0058] Based on the above embodiments, as an alternative embodiment, in step 303: calculating the corresponding ocean heave height by combining the significant wave height and heave period of each frequency band, this step may further include the following steps:

[0059] Step 313: For each frequency band, extract the wave peak values and wave trough values within a continuous plurality of heave periods of the frequency band, and screen out the heave periods in which the wave peak values and wave trough values exceed the waveform range corresponding to the significant wave height, to obtain a plurality of target heave periods.

[0060] Specifically, to obtain accurate target heave periods, it is necessary to conduct a detailed analysis of the waveform characteristics of each frequency band. During specific implementation, first, the zero-crossing detection method is used within each frequency band to identify the start and end points of a continuous plurality of heave periods. Usually, 10 complete periods are selected as the analysis window. Then, a peak detection algorithm is used to extract the wave peak values and wave trough values within each period. This algorithm is based on the principle of local extrema and combines curvature analysis to improve the detection accuracy. For the extracted wave peak values and wave trough values, a waveform range determination criterion is established according to the significant wave height of the frequency band, that is, the heave periods corresponding to the wave peak values and wave trough values that exceed 1.5 times the significant wave height are regarded as abnormal periods and are excluded. This screening mechanism can effectively remove abnormal periods caused by measurement errors or external interferences, ensuring the data quality for subsequent analysis. The finally obtained target heave periods have good periodicity and consistency and can accurately reflect the typical heave characteristics of the frequency band.

[0061] Step 323: According to the wave peak values and wave trough values within each target heave period, calculate the height difference between adjacent wave peaks and wave troughs, and use it as the corresponding heave amplitude.

[0062] Specifically, to quantify the motion amplitude of each target heave period, it is necessary to calculate the heave amplitude of the waveform. In specific implementation, the adjacent wave peaks and wave troughs within each target heave period are paired, and the height difference between them is calculated as the heave amplitude. During the calculation process, interpolation smoothing is adopted to eliminate the error caused by sampling discretization. At the same time, considering the possible asymmetry of the waveform, the height differences of the rising segment (from the wave trough to the wave peak) and the falling segment (from the wave peak to the wave trough) are calculated respectively, and their average value is taken as the heave amplitude of this period. This calculation method not only considers the complete characteristics of the waveform but also can reflect the symmetry characteristics of the heave motion, providing a more accurate amplitude estimation.

[0063] Step 333: Determine the corresponding weight coefficients based on the signal-to-noise ratios of each target heave period, and perform weighted calculations according to the weight coefficients and heave amplitudes of each target heave period respectively to obtain the corresponding target heave amplitudes.

[0064] Specifically, to reasonably weight the target heave periods of different qualities, it is necessary to determine the weight coefficients based on the signal-to-noise ratios. In specific implementation, first calculate the signal-to-noise ratio of each target heave period. The wavelet analysis method is used to decompose the signal into a trend term and a noise term, and the signal-to-noise ratio is obtained through their energy ratio. Then the sigmoid function is used to map the signal-to-noise ratio to the weight interval from 0 to 1, so that the period with a higher signal-to-noise ratio obtains a larger weight. For each target heave period, multiply its weight coefficient by the corresponding heave amplitude and perform normalization processing to obtain the weighted target heave amplitude. This weighting strategy fully considers the influence of data quality, can highlight the contribution of high-quality periods, and at the same time suppress the interference of low-quality periods.

[0065] Step 343: Perform vector superposition on the target heave amplitudes of each target heave period to obtain the ocean heave height of the frequency band.

[0066] Specifically, to obtain the overall heave characteristics of the frequency band, it is necessary to perform vector superposition on the target heave amplitudes of each target heave period. In specific implementation, first determine the phase relationship of each target heave period, and use the Hilbert transform to obtain the instantaneous phase information. Then establish a complex plane representation method, and represent each target heave amplitude as a complex number form of amplitude and phase. When performing vector superposition, considering the possible phase coupling effect between adjacent periods, a phase correction factor is introduced for adjustment. Finally, perform vector sum operation on all target heave amplitudes represented by complex numbers to obtain the ocean heave height of this frequency band. This vector superposition method not only considers the contribution of the amplitude but also retains the phase information, can accurately reflect the comprehensive effect of the motion of each period within this frequency band, and provides a reliable basis for subsequent multi-frequency band fusion.

[0067] Step 104: Calculate the height phase difference of the corresponding frequency band based on each ocean heave height, and screen out the target frequency bands with the height phase difference less than the phase difference threshold.

[0068] Among them, the height phase difference refers to the degree of phase difference in the time domain between the ocean heave height signals of different frequency bands, and this difference reflects the synchronism and relative lag relationship of the heave motions of different frequency bands.

[0069] The target frequency band refers to the frequency interval with good phase synchronism and data reliability after phase difference analysis and screening. The heave motion characteristics in these frequency bands have physical relevance and time-domain consistency.

[0070] Specifically, to ensure good phase consistency in the time domain for the ocean heave heights of different frequency bands, it is necessary to analyze and screen the height phase differences of each frequency band. In specific implementation, first, use the Hilbert transform to extract the phase of the ocean heave height of each frequency band to obtain its instantaneous phase information. During the phase extraction process, the sliding window technique is adopted, and the window length is set to 3 times the longest period to ensure the stability of phase calculation. For each frequency band, calculate the phase difference between it and the adjacent frequency band. The calculation method is to extract the phase values at multiple characteristic moments (such as wave crests, wave troughs, and zero-crossing points), and obtain the average phase difference through least squares fitting. At the same time, considering the non-stationary characteristics of the ocean environment, an adaptive threshold mechanism is introduced to dynamically adjust the phase difference threshold according to the current sea condition parameters. This threshold is usually set between π / 6 and π / 4. When the calculated height phase difference is less than the phase difference threshold, the corresponding frequency band is marked as the target frequency band. This screening method based on phase difference can not only identify the frequency bands with good phase synchronism but also effectively exclude the abnormal frequency bands caused by measurement errors or external interferences. To improve the reliability of screening, a phase stability evaluation mechanism is also introduced. By calculating the standard deviation of the phase difference within a certain period of time, the frequency bands with unstable phase differences are screened again. The finally screened target frequency bands have good phase consistency. The ocean heave heights of these frequency bands can produce an effective superposition effect in subsequent fusion processing, avoiding signal cancellation or distortion caused by excessive phase differences, thus ensuring the accuracy of the final heave height measurement result.

[0071] Based on the above embodiments, as an optional embodiment, in step 104: calculating the height phase difference of the corresponding frequency band based on each ocean heave height, this step may further include the following steps:

[0072] Step 401: Obtain the ship speed and the rate of change of steering angle within the corresponding time period for each frequency band; determine the maneuvering state of the ship according to the ship speed and the rate of change of steering angle.

[0073] Specifically, to accurately evaluate the impact of the ship's motion state on the heave height, key motion parameters of the ship need to be obtained. In specific implementation, first, the ship speed data is collected in real time through the ship navigation system, and the sampling frequency is set to 1 Hz. At the same time, the steering angle data output by the ship's heading gyroscope is recorded. For the steering angle data, the differential method is used to calculate its change rate, and the calculation time interval is set to 1 second. Then, based on the preset maneuvering state determination criteria (for example, when the ship speed is greater than 12 knots and the change rate of the steering angle is less than 2 degrees / second, it is determined as the straight sailing state; when the ship speed is greater than 8 knots and the change rate of the steering angle is greater than 2 degrees / second, it is determined as the turning state; when the ship speed is less than 8 knots, it is determined as the low-speed state), combined with the time series characteristics of the ship speed and the change rate of the steering angle, the fuzzy logic method is used to determine the maneuvering state of the ship. This state recognition method not only considers the instantaneous motion characteristics but also introduces the time continuity constraint, and can accurately reflect the dynamic changes of the ship's motion state.

[0074] Based on the above embodiments, as an alternative embodiment, in step 401: determining the maneuvering state of the ship according to the ship speed and the change rate of the steering angle, this step may further include the following steps:

[0075] Step 411: Determine the first state threshold based on the difference between the ship speed and the standard ship speed.

[0076] Specifically, to quantify the impact degree of the ship speed on the maneuvering state, the first state threshold needs to be determined based on the difference between the actual ship speed and the standard ship speed. In specific implementation, first, the standard ship speed is determined according to the ship design parameters and historical operation data. Usually, the economic ship speed of the ship is selected as the standard ship speed (for example, 12 knots). Then, the ship speed collected in real time is compared with the standard ship speed, and the difference between the two is calculated. To make the difference have better indication, the piecewise linear mapping method is used to convert the ship speed difference into the first state threshold: when the ship speed difference is between -4 knots and 4 knots, it is linearly mapped to the interval of 0 to 1; when the difference exceeds this range, saturation processing is used. At the same time, considering the dynamic characteristics of the ship speed change, exponential smoothing processing is introduced, and the smoothing coefficient is set to 0.8 to reduce the influence of the instantaneous fluctuation of the ship speed. This processing method not only provides a quantitative index of the ship speed state but also ensures the stability of the state judgment.

[0077] Step 421: Determine the second state threshold based on the difference between the change rate of the steering angle and the standard change rate of the steering angle.

[0078] Specifically, to evaluate the severity of the ship's turning motion, it is necessary to determine the second state threshold based on the difference between the actual turning angle change rate and the standard turning angle change rate. In specific implementation, first, set the standard turning angle change rate (e.g., 2 degrees per second), which is determined based on the ship's maneuvering performance indicators. Then, calculate the difference between the real-time turning angle change rate and the standard value, and use a similar piecewise mapping method: when the difference in the turning angle change rate is between -3 degrees per second and 3 degrees per second, linearly map it to the interval of 0 to 1; perform saturation processing when it exceeds the range. Considering the inertial characteristics of the turning motion, introduce a moving average process with a window length set to 5 seconds to eliminate the influence of short-term fluctuations. This processing method not only reflects the intensity of the turning motion but also ensures the continuity of state judgment.

[0079] Step 431: Determine the maneuvering state corresponding to the combined value of the first state threshold and the second state threshold in the preset maneuvering state mapping table.

[0080] Specifically, to accurately determine the ship's maneuvering state, it is necessary to comprehensively evaluate the combined effect of the first state threshold and the second state threshold based on the preset maneuvering state mapping table. In specific implementation, first, establish a two-dimensional maneuvering state mapping table. The horizontal axis of this mapping table represents the first state threshold (0 to 1), and the vertical axis represents the second state threshold (0 to 1). The corresponding maneuvering states are filled in the table cells (e.g., when the first state threshold < 0.3 and the second state threshold < 0.2, it is the low-speed state; when the first state threshold > 0.7 and the second state threshold < 0.3, it is the straight-line sailing state; when the second state threshold > 0.6, it is the turning state). When making a state determination, use the fuzzy logic method to process the combined value of the two thresholds, and determine the final maneuvering state by calculating the membership function. At the same time, introduce a state hysteresis mechanism, requiring the new state to last for a certain period of time (e.g., 3 seconds) before confirming the state transition to avoid frequent state switching. This state determination method based on the mapping table not only considers the comprehensive influence of multiple motion parameters but also ensures the stability and reliability of state judgment.

[0081] Step 402: Dynamically correct the ocean heave height of each frequency band based on the maneuvering state to obtain the predicted ocean heave height corresponding to each frequency band.

[0082] Specifically, to eliminate the influence of ship's maneuvering motion on the measurement of heave height, dynamic correction is required. During the specific implementation, first, a theoretical model of the ship's maneuvering motion and heave response is established. This model takes into account the influence of different ship speeds and turning angle rates of change on the heave motion in each frequency band. For the straight sailing state, the heave offset caused by the ship speed is mainly considered; for the turning state, the coupling effect of roll and heave caused by centrifugal force also needs to be considered. During the correction process, an adaptive compensation algorithm is adopted to dynamically adjust the compensation coefficient according to the current maneuvering state, and correct the ocean heave height in each frequency band. At the same time, ship hydrodynamic parameters (such as displacement, radius of gyration, etc.) are introduced to optimize the correction model and improve the correction accuracy. Through this dynamic correction, the predicted ocean heave height obtained can better reflect the characteristics of the ship's heave motion under the action of pure ocean waves.

[0083] Step 403: Calculate the phase offset between the ocean heave height in each frequency band and the predicted ocean heave height, and use it as the height phase difference for the corresponding frequency band.

[0084] Specifically, to quantify the difference between the actual heave motion and the theoretical prediction, the phase offset needs to be calculated. During the specific implementation, first, the ocean heave height and the predicted ocean heave height in each frequency band are converted to the complex plane representation, and the Hilbert transform is used to extract their instantaneous phase information. Then, by calculating the cross-correlation function of the two phase sequences, the time delay corresponding to the maximum correlation is determined, and this time delay is converted into a phase difference. During the calculation process, a sliding window technique (window length is 3 periods) is used to smooth the phase difference to reduce the influence of instantaneous fluctuations. At the same time, considering the periodic characteristics of different frequency bands, a frequency weighting mechanism is introduced to normalize the calculation results of the phase difference. The finally obtained height phase difference not only reflects the deviation degree between the actual heave motion and the theoretical prediction, but also provides a reliable criterion for subsequent frequency band screening. This method of calculating the phase difference based on the maneuvering state effectively improves the accuracy and reliability of the heave height measurement.

[0085] Step 105: Calculate the target heave height of the ship according to the ocean heave height in each target frequency band.

[0086] Among them, the target heave height refers to the comprehensive characteristic value of the ship's vertical motion obtained after multi-source data fusion, frequency band screening and quality assessment. This characteristic value reflects the actual heave motion state of the ship under the current sea conditions.

[0087] Specifically, to obtain the final heave height measurement result of the ship, it is necessary to comprehensively process and fuse the ocean heave heights of each target frequency band. During the specific implementation, first, the data quality of the ocean heave heights of each target frequency band is evaluated, and the evaluation indicators include signal-to-noise ratio, phase stability, and data continuity. Based on the evaluation results, an improved wavelet decomposition method is used to perform multi-scale analysis on the signals of each frequency band, and the signals are decomposed into wavelet coefficients of different scales. During the decomposition process, the db4 wavelet basis function is selected, and the decomposition level is determined according to the period characteristics of the lowest-frequency target frequency band. Then, adaptive threshold processing is performed on the coefficients of each scale, and the threshold size is dynamically adjusted according to the signal-to-noise ratio of the corresponding frequency band to suppress the influence of noise. At the same time, considering that different frequency bands have different contribution degrees to the heave motion, a weighted fusion strategy based on the energy distribution of the frequency bands is introduced, and the weight coefficients are optimized and determined by the least squares method. During the signal reconstruction process, phase compensation technology is used to eliminate the phase delay between different frequency bands to ensure the phase synchronization when the signals are superimposed. In addition, a correction mechanism for the ship's attitude information is introduced, and the fusion result is compensated for attitude through the roll angle and pitch angle data obtained in real time. Finally, the fusion result is smoothed by an improved Kalman filtering algorithm, and the filter parameters are dynamically adjusted according to the current sea condition to obtain the final target heave height. This multi-level data fusion method not only makes full use of the effective information of each target frequency band but also ensures the accuracy and reliability of the fusion result through various technical means. The obtained target heave height can accurately reflect the vertical motion characteristics of the ship under complex sea conditions and provide an important basis for ship control decisions and offshore operation safety.

[0088] Based on the above embodiments, as an alternative embodiment, in step 105: calculating the target heave height of the ship according to the ocean heave heights of each target frequency band, this step may further include the following steps:

[0089] Step 501: Obtain the pitch angle and roll angle of the ship; based on the pitch angle and roll angle, determine the inclination rate of the ship in the vertical direction.

[0090] Specifically, to accurately evaluate the impact of ship attitude on heave height measurement, it is necessary to obtain the ship's inclination state information. In specific implementation, first, the longitudinal and transverse inclination angle data are collected in real time through attitude sensors installed on the ship, and the sampling frequency is set to 50 Hz to ensure continuous capture of attitude changes. Then, based on the principle of spherical geometry, the longitudinal and transverse inclination angles are converted into spatial vectors, and the comprehensive inclination angle of the ship in the vertical direction is calculated through vector synthesis. To eliminate the high-frequency noise of the attitude data, a low-pass filter is used to preprocess the original angle data, and the cut-off frequency is set to 5 Hz. Finally, the inclination rate in the vertical direction is calculated through trigonometric function relationships, that is, the tangent value of the inclination angle. This processing method not only considers the coupling effect of longitudinal and transverse inclinations but also ensures the accuracy and real-time performance of inclination rate calculation.

[0091] Step 502: Correct the ocean heave heights of each target frequency band according to the inclination rate respectively to obtain the corrected ocean heave heights of each target frequency band.

[0092] Specifically, to eliminate the impact of ship inclination on heave height measurement, it is necessary to perform attitude correction on the ocean heave heights of each target frequency band. In specific implementation, first, a height projection model based on the inclination rate is established, which considers the distance from the sensor installation position to the ship's center of gravity and the change in the vertical component caused by inclination. For each target frequency band, different correction strategies are adopted according to its characteristic period and the change speed of the inclination rate: for the high-frequency band, the instantaneous inclination rate is used for real-time correction; for the middle-frequency band, the inclination rate after moving average is used for correction; for the low-frequency band, the average inclination rate with a longer time window is used for correction. A tilt compensation coefficient is also introduced during the correction process, and this coefficient is dynamically adjusted according to the ship's hull form characteristics and load conditions. Through this frequency-band division correction processing, the obtained ocean heave height can more accurately reflect the motion characteristics in the pure vertical direction.

[0093] Step 503: Perform weighted calculation on the corrected ocean heave heights to obtain the target heave height of the ship.

[0094] Specifically, to obtain the final target heave height, it is necessary to reasonably fuse the corrected ocean heave heights of each frequency band. During the specific implementation, first, a multi-dimensional weight evaluation system is constructed based on indicators such as the signal-to-noise ratio, phase stability, and data integrity of each frequency band signal. The weight calculation uses the fuzzy analytic hierarchy process, considering the reliability differences of data in each frequency band under different sea conditions. When performing weighted calculation, the complex domain representation method is adopted, expressing each frequency band signal as a combination of amplitude and phase, and accurately transmitting the phase information through complex operations. At the same time, an adaptive window mechanism is introduced, and the window length is determined according to the period characteristics of the lowest frequency band, and continuous data fusion is achieved through sliding processing. Finally, Kalman filtering is performed on the fusion result, and the filter parameters are dynamically optimized according to the current sea condition and the ship's motion state to obtain a smooth target heave height. This multi-frequency band fusion method considering the attitude influence not only ensures the effective utilization of information in each frequency band but also improves the accuracy of the final heave height measurement.

[0095] Referring to Figure 2 , a marine heave height measurement system provided by an embodiment of the present application, the system includes: an information acquisition module, a heave height data determination module, a target frequency band determination module, and a height measurement module, where:

[0096] The information acquisition module is used to acquire the acceleration signal collected by the inertial navigation unit, the water pressure information collected by the pressure sensor, and the vertical position information collected by the GPS receiver during the ship's navigation;

[0097] The heave height data determination module is used to integrate the acceleration signal to obtain the first heave height data, calculate the second heave height data according to the water pressure information, and calculate the third heave height data according to the vertical position information;

[0098] The target frequency band determination module is used to perform band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain the ocean heave heights of multiple frequency bands; calculate the height phase difference corresponding to each frequency band based on each ocean heave height, and screen out the target frequency band with a height phase difference less than the phase difference threshold;

[0099] The height measurement module is used to calculate the target heave height of the ship according to the ocean heave heights of each target frequency band.

[0100] On the basis of the above embodiments, the heave height data determination module is further configured to remove the zero-drift signal in the acceleration signal by high-pass filtering, and perform a first integration calculation on the high-pass filtered acceleration signal to obtain a velocity signal; perform zero-mean processing on the velocity signal, and perform a second integration calculation on the zero-mean processed velocity signal to obtain the first heave height data; obtain the installation depth of the pressure sensor; calculate the corresponding water depth data according to the water pressure information, and subtract the installation depth from the water depth data to obtain the second heave height data; perform differential correction on the vertical position information, and use low-pass filtering to remove high-frequency noise in the vertical position information; and use the corrected and low-pass filtered vertical position information as the third heave height data.

[0101] On the basis of the above embodiments, the target frequency band determination module is further configured to perform Fourier transform on the first heave height data, the second heave height data, and the third heave height data to obtain spectral data; divide the spectral data into segmented spectral data corresponding to multiple frequency bands according to a preset frequency interval, and extract the significant wave height and heave period in each segmented spectral data; and calculate the corresponding ocean heave height by combining the significant wave height and heave period of each frequency band.

[0102] On the basis of the above embodiments, the target frequency band determination module is further configured to, for each frequency band, extract the wave peak values and wave valley values within a continuous plurality of heave periods of the frequency band, and screen out the heave periods in which the wave peak values and wave valley values exceed the waveform range corresponding to the significant wave height, to obtain a plurality of target heave periods; calculate the height difference between adjacent wave peaks and wave valleys according to the wave peak values and wave valley values within each target heave period, and use it as the corresponding heave amplitude; determine the corresponding weight coefficient based on the signal-to-noise ratio of each target heave period, and perform weighted calculations according to the weight coefficients and heave amplitudes of each target heave period respectively, to obtain the corresponding target heave amplitude; and perform vector superposition on the target heave amplitudes of each target heave period to obtain the ocean heave height of the frequency band.

[0103] On the basis of the above embodiments, the target frequency band determination module is further configured to obtain the ship speed and the steering angle change rate within the corresponding time period of each frequency band; determine the maneuvering state of the ship according to the ship speed and the steering angle change rate; dynamically correct the ocean heave height of each frequency band based on the maneuvering state to obtain the predicted ocean heave height corresponding to each frequency band; and calculate the phase offset amount between the ocean heave height and the predicted ocean heave height of each frequency band, and use it as the height phase difference of the corresponding frequency band.

[0104] On the basis of the above embodiments, the target frequency band determination module is further configured to determine a first state threshold based on the difference between the ship speed and the standard ship speed; determine a second state threshold based on the difference between the steering angle change rate and the standard steering angle change rate; and determine the maneuvering state corresponding to the combined value of the first state threshold and the second state threshold in a preset maneuvering state mapping table.

[0105] Based on the above embodiments, the height measurement module is further configured to obtain the longitudinal inclination angle and the transverse inclination angle of the ship; determine the inclination rate of the ship in the vertical direction based on the longitudinal inclination angle and the transverse inclination angle; correct the ocean heave height of each target frequency band respectively according to the inclination rate to obtain the corrected ocean heave height of each target frequency band; perform weighted calculation on the corrected ocean heave heights to obtain the target heave height of the ship.

[0106] It should be noted that when the device provided in the above embodiments realizes its functions, only the division of the above function modules is used for illustration. In actual applications, the above functions can be allocated to different function modules according to needs, that is, the internal structure of the device is divided into different function modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be seen in the method embodiments, which will not be elaborated here.

[0107] This application also discloses an electronic device. Refer to Figure 3 , Figure 3 which is a schematic structural diagram of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0108] Among them, the communication bus 302 is used to realize the connection and communication between these components.

[0109] Among them, the user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0110] Among them, the network interface 304 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0111] Among them, the processor 301 may include one or more processing cores. The processor 301 connects various parts within the entire server through various interfaces and lines. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling the data stored in the memory 305, it executes various functions of the server and processes data. Optionally, the processor 301 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 301 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface graphics, and application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately by a single chip.

[0112] Among them, the memory 305 may include random access memory (RAM) and may also include read-only memory. Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store the data involved in the above-mentioned various method embodiments. Optionally, the memory 305 may also be at least one storage device located far from the aforementioned processor 301. Refer to Figure 3 , the memory 305, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a method of measuring ocean heave height.

[0113] In Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an interface for user input and obtain the data input by the user; while the processor 301 can be used to call the application program stored in the memory 305 for a method of measuring ocean heave height. When executed by one or more processors 301, the electronic device 300 is caused to execute the method of one or more of the above-mentioned embodiments. It should be noted that for the foregoing method embodiments, for simplicity of description, they are all expressed as a series of combinations of actions. However, those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0114] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0115] In several implementation manners provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some service interfaces. The indirect couplings or communication connections of the devices or units can be in electrical or other forms.

[0116] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] In addition, the functional units in the various embodiments of the present application can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0118] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned memory includes: various media such as USB flash drives, mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0119] The above are only exemplary embodiments of the present disclosure and should not be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will readily think of other implementation manners of the present disclosure after considering the specification and the practice of the disclosure.

[0120] The present application aims to cover any variations, uses, or adaptive changes of the present disclosure that follow the general principles of the present disclosure and include well-known common knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary.

Claims

1. A method for measuring the heave height of the ocean, characterized in that, Including: Obtaining the acceleration signal collected by an inertial navigation unit during the navigation of a ship, the water pressure information collected by a pressure sensor, and the vertical position information collected by a GPS receiver; Performing integral processing on the acceleration signal to obtain first heave height data, calculating second heave height data based on the water pressure information, and calculating third heave height data based on the vertical position information; Performing band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain ocean heave heights in multiple frequency bands; Calculating the height phase difference of the corresponding frequency band based on each of the ocean heave heights, and screening out the target frequency bands with the height phase difference less than the phase difference threshold; Calculating the target heave height of the ship according to the ocean heave heights of each of the target frequency bands; The calculating the height phase difference of the corresponding frequency band based on each of the ocean heave heights includes: Obtaining the ship speed and the steering angle change rate within the corresponding time period of each of the frequency bands; Determining the maneuvering state of the ship according to the ship speed and the steering angle change rate; Performing dynamic correction on the ocean heave heights of each of the frequency bands based on the maneuvering state to obtain the predicted ocean heave heights corresponding to each of the frequency bands; Calculating the phase offset between the ocean heave height of each of the frequency bands and the predicted ocean heave height, and using it as the height phase difference of the corresponding frequency band; The determining the maneuvering state of the ship according to the ship speed and the steering angle change rate includes: Determining a first state threshold based on the difference between the ship speed and the standard ship speed; Determining a second state threshold based on the difference between the steering angle change rate and the standard steering angle change rate; Determining the maneuvering state corresponding to the combined value of the first state threshold and the second state threshold in a preset maneuvering state mapping table.

2. The method for measuring the ocean heave height according to claim 1, characterized in that The performing integral processing on the acceleration signal to obtain first heave height data, calculating second heave height data based on the water pressure information, and calculating third heave height data based on the vertical position information includes: Removing the zero-drift signal in the acceleration signal by high-pass filtering, and performing a first integral calculation on the high-pass filtered acceleration signal to obtain a speed signal; Performing zero-mean processing on the speed signal, and performing a second integral calculation on the zero-mean processed speed signal to obtain first heave height data; Obtaining the installation depth of the pressure sensor; Calculating the corresponding water depth data according to the water pressure information, and subtracting the installation depth from the water depth data to obtain second heave height data; Performing differential correction on the vertical position information, and removing high-frequency noise in the vertical position information by low-pass filtering; Using the corrected and low-pass filtered vertical position information as the third heave height data.

3. The method for measuring the ocean heave height according to claim 1, wherein The performing band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain ocean heave heights in multiple frequency bands includes: Performing Fourier transform on the first heave height data, the second heave height data, and the third heave height data to obtain spectral data; Divide the spectrum data into segmented spectrum data corresponding to multiple frequency bands according to a preset frequency interval, and extract the significant wave height and heave period in each of the segmented spectrum data; Calculate the corresponding ocean heave height by combining the significant wave height and heave period of each frequency band.

4. The method for measuring the ocean heave height according to claim 3, wherein The calculating the corresponding ocean heave height by combining the significant wave height and heave period of each frequency band includes: For each frequency band, extract the wave peak value and wave trough value within a continuous plurality of the heave periods of the frequency band, and screen out the heave periods in which the wave peak value and the wave trough value exceed the waveform range corresponding to the significant wave height, to obtain a plurality of target heave periods; According to the wave peak value and wave trough value within each of the target heave periods, calculate the height difference between adjacent wave peaks and wave troughs, and use it as the corresponding heave amplitude; Determine the corresponding weight coefficient based on the signal-to-noise ratio of each of the target heave periods, and perform weighted calculations according to the weight coefficients and heave amplitudes of each of the target heave periods respectively, to obtain the corresponding target heave amplitude; Perform vector superposition on the target heave amplitudes of each of the target heave periods to obtain the ocean heave height of the frequency band.

5. The method for measuring the ocean heave height according to claim 1, characterized in that, The calculating the target heave height of the ship according to the ocean heave height of each of the target frequency bands includes: Obtain the trim angle and roll angle of the ship; Based on the trim angle and the roll angle, determine the inclination rate of the ship in the vertical direction; Correct the ocean heave height of each of the target frequency bands according to the inclination rate respectively, to obtain the corrected ocean heave height of each of the target frequency bands; Perform weighted calculation on the corrected ocean heave heights to obtain the target heave height of the ship.

6. An ocean heave height measurement system, characterized in that, The system includes: An information acquisition module, configured to acquire the acceleration signal collected by an inertial navigation unit, the water pressure information collected by a pressure sensor, and the vertical position information collected by a GPS receiver during the navigation of the ship; A heave height data determination module, configured to perform integral processing on the acceleration signal to obtain first heave height data, calculate second heave height data according to the water pressure information, and calculate third heave height data according to the vertical position information; A target frequency band determination module, configured to perform band-pass frequency division processing on the first heave height data, the second heave height data, and the third heave height data to obtain the ocean heave height of multiple frequency bands; calculate the height phase difference of the corresponding frequency band based on each of the ocean heave heights, and screen out the target frequency bands in which the height phase difference is less than the phase difference threshold; A height measurement module, configured to calculate the target heave height of the ship according to the ocean heave height of each of the target frequency bands; The calculating the height phase difference of the corresponding frequency band based on each of the ocean heave heights includes: Obtain the ship speed and the steering angle change rate within the corresponding time period of each frequency band; Determine the maneuvering state of the ship according to the ship speed and the steering angle change rate; Perform dynamic correction on the ocean heave height of each frequency band based on the maneuvering state to obtain the predicted ocean heave height corresponding to each frequency band; Calculate the phase offset between the ocean heave height of each of the said frequency bands and the predicted ocean heave height, and use it as the height phase difference for the corresponding frequency band; Determine the maneuvering state of the ship according to the ship speed and the rate of change of the steering angle, including: Based on the difference between the ship speed and the standard ship speed, determine the first state threshold; Based on the difference between the rate of change of the steering angle and the standard rate of change of the steering angle, determine the second state threshold; Determine the maneuvering state corresponding to the combined value of the first state threshold and the second state threshold in a preset maneuvering state mapping table.

7. An electronic device, characterized in that, It includes a processor, a memory, a user interface and a network interface. The memory is used to store instructions. The user interface and the network interface are used to communicate with other devices. The processor is used to execute the instructions stored in the memory so that the electronic device executes the ocean heave height measurement method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, execute the ocean heave height measurement method according to any one of claims 1-5.

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