CN116678404A - Ship heave measurement method based on multiple Fourier linear combiner - Google Patents
Ship heave measurement method based on multiple Fourier linear combiner Download PDFInfo
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Abstract
The application discloses a ship heave measurement method based on a multiple Fourier linear combiner, which belongs to the heave measurement field and comprises the following steps: acquiring vertical acceleration under a carrier coordinate system through a strapdown inertial navigation system, and performing N-point fast Fourier transform on the vertical acceleration to obtain relevant frequency domain information of sea wave surging; constructing a vertical velocity comprehensive filter, filtering the vertical acceleration and obtaining the vertical velocity; fitting the vertical speed through a KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted vertical speed through a KF-BMFLC compensation model to obtain a target vertical speed; constructing a heave comprehensive filter, and filtering the target vertical speed to obtain heave displacement; and fitting the heave displacement through a KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted heave displacement through a KF-BMFLC compensation model to obtain the target heave displacement. The method is suitable for measurement and control scenes requiring high precision.
Description
Technical Field
The application relates to a ship heave measurement method based on a multiple Fourier linear combiner, and belongs to the field of heave measurement.
Background
When a ship or an offshore platform is at sea, six degrees of freedom of spatial movement are generated due to the influence of multiple factors such as wind, waves and the like, including angular movement (pitching, rolling and yawing) around three axes and linear movement (swaying, pitching and heaving, i.e. heaving) along three axes. Among them, heave motion with a certain periodicity has the greatest influence and harm to the system. Therefore, accurate measurement of real-time heave information is of great significance for ship anti-roll control, offshore stable platform compensation and the like. The strapdown inertial navigation system (strapdown inertial navigation system, SINS) has strong autonomy, and can realize autonomous measurement without receiving any external information. Therefore, SINS-based heave measurement methods have wide applicability. However, since the altitude channel of the SINS is interfered by low-frequency harmonic waves such as dc errors of the accelerometer in addition to the schler oscillation, the antenna specific force information calculated by the SINS must be filtered to obtain accurate heave motion information.
For SINS-based heave measurement, students at home and abroad do a lot of work. A high-pass filter with a self-adaptive function is proposed in Numerical Simulation andTestingAnalysis ofAdaptive Heave Motion Measurements published by WenlinYang, and parameters of the filter are self-adaptively corrected according to an actual environment, but the high-pass filter has the problems of phase advance, amplitude attenuation and the like, and the measured heave information error is larger. Yan Gongmin in the naval vessel heave measurement based on inertial navigation and no delay filter published in the navigation positioning academy, an IIR digital low-pass filter is designed firstly, and then the IIR digital low-pass filter is converted into a digital high-pass filter without delay by adopting a complementary method, but the parameters are demanding and have no real-time property. In patent document of application number 201710202159.5, named as a ship heave measurement method based on Band-limited Fourier linear combination, a Band-limited Fourier linear combination (Band-limitedMultiple Fourier Linear Combiner, BMFLC) algorithm is applied to measurement of ship heave information, and the problem of phase lead after a high-pass filter is solved by using the Band-limited Fourier linear combination. However, the prior heave frequency information is not available, and the LMS algorithm is adopted for weight iteration, so that the algorithm accuracy is slightly lower. In the application patent number 202211669949.1, the name is 'adaptive ship heave measurement method based on strapdown inertial navigation', the BMFLC algorithm is used for compensating the amplitude-phase error problem of the high-pass filter, the iteration of the weight adopts a recursive least square algorithm, and although the calculation complexity is relatively low, the joint estimation can be carried out on data at a plurality of moments, and if noise exists in the data, the estimation precision is greatly reduced.
Disclosure of Invention
The application aims to provide a ship heave measurement method based on a multiple Fourier linear combiner, which solves the problems of amplitude attenuation and phase error of traditional heave measurement, effectively improves the measurement accuracy of heave information and has real-time performance.
To achieve the above object, a first aspect of the present application provides a ship heave measurement method based on a multiple fourier linear combiner, including:
acquiring vertical acceleration under a carrier coordinate system based on a strapdown inertial navigation system;
performing N-point fast Fourier transform on the vertical acceleration to obtain relevant frequency domain information of sea wave surging;
constructing a vertical velocity comprehensive filter according to the related frequency domain information, and filtering the vertical acceleration through the vertical velocity comprehensive filter to obtain a vertical velocity;
fitting the vertical speed through a KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted vertical speed through a KF-BMFLC compensation model to obtain a target vertical speed;
constructing a heave comprehensive filter according to the related frequency domain information, and filtering the target vertical speed through the heave comprehensive filter to obtain heave displacement;
and fitting the heave displacement through the KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted heave displacement through the KF-BMFLC compensation model to obtain the target heave displacement.
In one embodiment, the constructing a vertical-speed synthesis filter from the related frequency domain information includes:
and taking the related frequency domain information as prior information, and determining the cut-off frequency of the vertical-speed comprehensive filter according to the related frequency domain information, wherein the vertical-speed comprehensive filter is as follows:
wherein, xi is the damping coefficient, omega c For the cut-off frequency, s is the laplace operator.
In one embodiment, said filtering said vertical acceleration by said vertical synthesis filter and obtaining a vertical velocity comprises:
let vertical acceleration a z Through the vertical velocity synthesis filter, to the vertical acceleration a z Integrating once and high-pass filtering to remove vertical speed error caused by low-frequency signal and output vertical speed v with amplitude-phase error z 。
In one embodiment, said fitting said vertical velocity by KF-BMFLC fitting model comprises:
determining a base band according to the related frequency domain information, and equally dividing the base band by M parts to obtain a plurality of frequency points f r ；
The frequency points f r As the fundamental frequency, the vertical velocity v is applied by a sine-cosine function z A linear fit was performed.
In one embodiment, said fitting said vertical velocity by KF-BMFLC fitting model further comprises:
weight W k As a state quantity, the optimal weight is solved by using Kalman filtering to improve fitting accuracy, wherein the solving of the optimal weight by using Kalman filtering comprises: the weight is iteratively updated by the following formula:
W k|k-1 ＝λW k-1|k-1
P k|k-1 ＝λ 2 P k-1|k-1
W k|k ＝W k|k-1 +K k e k
P k|k ＝(I-K k X k )P k|k-1 +Q
wherein k is a time series, X k ＝[X 1k X 2k …X rk ] T The basic fitting quantity of each frequency point of KF-BMFLC in the self-adaptive frequency band is obtained, wherein r=1, 2 … M, M is the number of frequency points in the self-adaptive frequency band, and f r To fit the fundamental frequency, T is the system sampling period, v k Is vertical velocity v z Meta-at time kElement, v k To the original signal v k Results obtained by KF-BMFLC fitting, W k ＝[W 1k W 2k …W 2Mk ] T Is W k One element of (B), i.e. BMFLC weight, W k-1|k-1 W is the state quantity at time k-1 k|k-1 For one-step prediction of state quantity k-1 time to k time, W k|k The state quantity at the moment k, lambda is forgetting factor, u k Is state noise, v k To measure noise, K k For Kalman gain, Q is the covariance matrix of the state noise, R is the covariance matrix of the measurement noise, P k-1|k-1 Estimating an error covariance matrix for a posterior at time k-1, P k|k-1 For the estimated error covariance matrix from time k-1 to time k, P k|k A covariance matrix of the estimated error at the moment k; e, e k And I is an identity matrix for the deviation of KF quantity measurement and estimation quantity.
In one embodiment, the performing amplitude-phase compensation on the fitted vertical velocity through the KF-BMFLC compensation model includes:
and performing amplitude-phase compensation on the fitted vertical speed by the following formula:
m r ＝|H 1 (jω i )|；p r ＝∠H 1 (jω i )
v′ k ＝X′ k T W k
in which the fundamental frequency angular frequency omega i ＝2πf r ，m r For the amplitude attenuation quantity, p, of each fundamental frequency point of BMFLC r For the phase advance of each fundamental frequency point, v' k For v k And (5) obtaining the target vertical speed after the amplitude-phase compensation.
In one embodiment, the filtering the target vertical velocity by the heave integrated filter to obtain a heave displacement includes:
and enabling the target vertical speed to pass through the heave comprehensive filter so as to perform primary integration and high-pass filtering on the target vertical speed subjected to amplitude phase compensation and output heave displacement with amplitude phase error.
In one embodiment, said fitting the heave displacement by the KF-BMFLC fitting model and performing amplitude-phase compensation of the fitted heave displacement by the KF-BMFLC compensation model comprises:
determining a base band according to the related frequency domain information, equally dividing the base band by M parts to obtain a plurality of frequency points, linearly fitting the heave displacement by using a sine-cosine function by using the plurality of frequency points as base frequencies, taking a weight as a state quantity, and solving an optimal weight by using Kalman filtering to improve fitting precision and obtain a fitting result;
and performing amplitude-phase compensation on the fitting result through the KF-BMFLC compensation model to obtain the target heave displacement.
A second aspect of the present application provides an electronic device, comprising: a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the first aspect or any implementation of the first aspect as described above when the computer program is executed.
A third aspect of the present application provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of the first aspect or any implementation of the first aspect.
From the above, the application provides a ship heave measurement method based on a multiple Fourier linear combiner, which can monitor the dominant frequency of sea waves to obtain relevant frequency domain information of sea wave surges, and takes the relevant frequency domain information as prior information, so that parameters of a vertical speed comprehensive filter and a heave comprehensive filter and a base frequency band of a BMFLC are adaptively changed, and further, a proposed KF-BMLFC fitting model and a KF-BMLFC compensation model are utilized to obtain target heave displacement, high-precision measurement of heave information is realized, and references are provided for ship heave operation, ship-borne aircraft lifting and active heave compensation of various offshore platforms. Compared with a least mean square and recursive least square weight iteration method, a Kalman Filtering (KF) weight iteration algorithm represents the state of the system as a Gaussian distribution, and the mean value and the covariance matrix of the state are updated according to the current observation data and the noise model. The Kalman filtering utilizes the prior knowledge and the noise model of the system, so that the Kalman filtering method has better noise suppression and state estimation precision, and is suitable for measurement and control scenes requiring high precision.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a ship heave measurement method according to an embodiment of the application;
FIG. 2 is a Bode diagram of a vertical-speed synthesis filter according to an embodiment of the present application;
FIG. 3 is a Bode diagram of a heave synthesis filter according to an embodiment of the application;
FIG. 4 is a schematic diagram of KF-BMFLC according to an embodiment of the present application;
FIG. 5 is a schematic diagram of an amplitude-phase compensation according to an embodiment of the present application;
fig. 6 is an error comparison diagram of a conventional ship heave measurement method according to an embodiment of the present application and a ship heave measurement method according to the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Example 1
The embodiment of the application provides a ship heave measurement method based on a multiple Fourier linear combiner, which comprises the following steps of:
s100, acquiring vertical acceleration of a carrier coordinate system based on a strapdown inertial navigation system;
optionally, the SINS is built in the carrier to start and perform relevant initialization work such as alignment and the like. Collecting and storing the carrier coordinate system calculated by the strapdown inertial navigation system after the initialization is finishedVertical acceleration a z Wherein the carrier is a ship or an offshore platform.
S200 to the vertical acceleration a z Performing N-point fast Fourier transform (Fast Fourier Transform, FFT) to obtain relevant frequency domain information of sea wave surging;
in one application scenario, the conventional high-pass filter adopts a fixed cut-off frequency, and cannot correctly select the cut-off frequency suitable for the current sea state, so that the filtering error is larger. Therefore, the embodiment of the application has great significance for the design of the subsequent vertical speed comprehensive filter and heave comprehensive filter by carrying out frequency domain analysis on the wave information and taking the wave dominant frequency (namely the related frequency domain information) as prior information. In addition, the prior frequency information can also divide the window frequency band of the KF-BMFLC more accurately, reduce the fitting bandwidth and the fundamental frequency interval of the KF-BMFLC, enable the estimation result to cover the fundamental frequency points in the frequency band as much as possible, thereby realizing high-precision fitting of signals in the frequency band and further improving the compensation precision of amplitude and phase.
S300, constructing a vertical velocity comprehensive filter (also called a vertical velocity comprehensive adaptive filter) according to the related frequency domain information, and filtering the vertical acceleration through the vertical velocity comprehensive filter to obtain a vertical velocity;
optionally, the constructing a vertical-speed synthesis filter according to the related frequency domain information includes:
s310, using the related frequency domain information as prior information, determining the cut-off frequency of the vertical speed comprehensive filter according to the related frequency domain information, and further determining the transfer function of the vertical speed comprehensive adaptive filter, wherein the vertical speed comprehensive filter is as follows:
wherein, xi is the damping coefficient, omega c For the cut-off frequency, s is the laplace operator.
In one embodiment, the Bode diagram of the vertical-speed synthesis filter is shown in FIG. 2The cut-off frequency of the filter can be adaptively adjusted according to the wave prior information, and the filtering error is smaller. In addition, the high-pass filter in the filter is a second-order Butterworth analog filter, so the damping coefficient xi is generally taken
Optionally, the filtering the vertical acceleration through the vertical velocity synthesis filter and obtaining a vertical velocity includes:
s320 enables the vertical acceleration a z Through the vertical velocity synthesis filter, to the vertical acceleration a z Performing once integration and high-pass filtering to remove vertical speed error caused by low-frequency signals such as zero offset of an accelerometer and the like, and outputting vertical speed v z Wherein the output vertical velocity v z There is an amplitude-phase error caused by the inherent characteristics of the high-pass filter.
S400, fitting the vertical speed through a KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted vertical speed through a KF-BMFLC compensation model to obtain a target vertical speed;
optionally, fig. 4 is a schematic block diagram of KF-BMFLC, and the fitting the vertical velocity by using KF-BMFLC fitting model includes:
s410, selecting a proper base frequency band near the dominant frequency according to the related frequency domain information, and equally dividing M parts in the base frequency band to obtain a plurality of frequency points f r Dividing the frequency point f after dividing equally r The vertical velocities are linearly fitted as a sine and cosine function of the fundamental frequency. BMFLC fitting model y k And fundamental frequency spacing (frequency resolution) Δf as follows:
in the method, in the process of the application,as the direct current component, the high-pass filter attenuates the direct current component more, so the high-pass filter can ignore the direct current component; a, a r And b r Respectively sine and cosine coefficients; f (f) M Fitting an upper limit of a frequency band; f (f) 1 Fitting a lower band limit; m is the number of fundamental frequency points, usually 25-200.
S420, weighting W k As state quantity, kalman filtering is used for solving the optimal weight, so that fitting can reach higher precision. The iterative process of solving for the optimal weights using kalman filtering is as follows:
W k|k-1 ＝λW k-1|k-1
P k|k-1 ＝λ 2 P k-1|k-1
W k|k ＝W k|k-1 +K k e k
P k|k ＝(I-K k X k )P k|k-1 +Q
wherein k is a time series, X k ＝[X 1k X 2k …X rk ] T The basic fitting quantity of each frequency point of KF-BMFLC in the self-adaptive frequency band is obtained, wherein r=1, 2 … M, M is the number of frequency points in the self-adaptive frequency band, and f r To be simulatedFundamental frequency is combined, T is the sampling period of the system, v k Is vertical velocity v z The element at time k, v k To the original signal v k Results obtained by KF-BMFLC fitting, W k ＝[W 1k W 2k …W 2Mk ] T Is W k One element of (B), i.e. BMFLC weight, W k-1|k-1 W is the state quantity at time k-1 k|k-1 For one-step prediction of state quantity k-1 time to k time, W k|k The state quantity at the moment k, lambda is forgetting factor, u k Is state noise, v k To measure noise, K k For Kalman gain, Q is the covariance matrix of the state noise, R is the covariance matrix of the measurement noise, P k-1|k-1 Estimating an error covariance matrix for a posterior at time k-1, P k|k-1 For the estimated error covariance matrix from time k-1 to time k, P k|k A covariance matrix of the estimated error at the moment k; e, e k And I is an identity matrix for the deviation of KF quantity measurement and estimation quantity.
In practical application, when the weight updating method is selected, comprehensive consideration needs to be carried out according to specific scenes and data characteristics. If noise exists in the data and the noise can be modeled through a Kalman filtering model, a Kalman filtering method can be selected for weight updating, so that estimation accuracy is improved. It should be noted that the kalman filtering method needs to determine the state transition matrix and the observation matrix of the system in advance, and the computational complexity is relatively high. High accuracy fitting calculations are based on high computational complexity, and therefore a trade-off between computational complexity and estimation accuracy is required.
Optionally, the fitting of the vertical velocity by the KF-BMFLC fitting model includes:
s430, calculating the amplitude-phase frequency characteristics corresponding to each fundamental frequency point of the KF-BMFLC according to the vertical speed comprehensive adaptive filter, and enabling the fitted signals to pass through a KF-BMFLC compensation model to realize the vertical speed v z To obtain accurate target vertical velocity v 'by compensating the amplitude and phase of the magnetic field' z (i.e., sag information), FIG. 5 is a schematic diagram of KF-BMFLC amplitude and phase compensation, after fitting by a KF-BMFLC compensation model pairThe process of amplitude-phase compensation of said vertical velocity of (2) is as follows:
m r ＝|H 1 (jω i )|；p r ＝∠H 1 (jω i )
v′ k ＝X′ k T W k
in which the fundamental frequency angular frequency omega i ＝2πf r ，m r For the amplitude attenuation quantity, p, of each fundamental frequency point of BMFLC r For the phase advance of each fundamental frequency point, v' k For v k And (5) obtaining the target vertical speed after the amplitude-phase compensation.
Further, the amplitude attenuation m of each fundamental frequency point r And a phase lead amount p r The calculation formula is as follows:
s500, constructing a heave comprehensive filter (also called a vertical heave comprehensive self-adaptive filter) according to the related frequency domain information, and filtering the target vertical velocity through the heave comprehensive filter to obtain heave displacement;
optionally, the constructing a heave synthesis filter according to the relevant frequency domain information includes:
s510, using the related frequency domain information as prior information, determining the cut-off frequency of the heave comprehensive filter according to the related frequency domain information, and further determining the transfer function of the vertical heave comprehensive adaptive filter, wherein the heave comprehensive filter is as follows:
wherein, xi is the damping coefficient, omega c For the cut-off frequency, s is the laplace operator.
In one embodiment, a Bode diagram of the heave integrated filter is shown in fig. 3, and the cut-off frequency of the heave integrated filter can be adaptively adjusted according to the prior information of sea waves, so that the filtering error is smaller. In addition, the high-pass filter in the filter is a second-order Butterworth analog filter, so the damping coefficient xi is generally taken
Optionally, the filtering the target vertical velocity through the heave integrated filter to obtain a heave displacement includes:
s520, the target vertical velocity is passed through the heave synthesis filter to compensate the amplitude and phase of the target vertical velocity v' k Integrating once and high-pass filtering, and outputting heave displacement x z Wherein the heave displacement is present with an amplitude phase error caused by the inherent characteristics of the high pass filter.
And S600, fitting the heave displacement through the KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted heave displacement through the KF-BMFLC compensation model to obtain the target heave displacement.
Optionally, the process of fitting the heave displacement through the KF-BMFLC fitting model and performing amplitude-phase compensation on the fitted heave displacement through the KF-BMFLC compensation model is similar to the process of step S400, the fundamental frequency is unchanged all the time in the fitting process, and the fitting weight W is determined k As state quantity, the original signal is used as quantity measurement, and the fitting weight is optimally estimated by a Kalman filtering algorithm. In the subsequent amplitude-phase compensation process, only the basic fit quantity X is calculated rk Adjusting amplitude and phase, and using the optimal weight W estimated at the previous moment without adjusting the fitting weight k The accurate target heave displacement x 'can be obtained through the iteration method' k (i.e., heave information). The method specifically comprises the following steps:
s610, determining a baseband according to the related frequency domain information, and equally dividing the baseband by M parts to obtain a plurality of frequency points f r The frequency points f r As a fundamental frequency, the heave displacement x is subjected to a sine-cosine function z Performing linear fitting;
s620 weight W k As state quantity and using Kalman filtering to solve the optimal weight to improve fitting accuracy and obtain fitting result x' k The specific weight iteration process is as follows:
W k|k-1 ＝λW k-1|k-1
P k|k-1 ＝λ 2 P k-1|k-1
W k|k ＝W k|k-1 +K k e k
P k|k ＝(I-K k X k )P k|k-1 +Q
wherein x is k For heave displacement x z The element at time k, x k For heave displacement x k Fitting the obtained result by adopting KF-BMFLC;
s630, calculating the amplitude-phase frequency characteristics of each fundamental frequency point of the KF-BMFLC according to the vertical heave comprehensive adaptive filter, and enabling the fitted signals to pass throughAfter passing through the KF-BMFLC compensation model, the method can realize the alignment of x z To obtain accurate target heave displacement x' z . The process of amplitude-phase compensation through the KF-BMFLC compensation model is as follows:
m r ＝|H 1 (jω i )|；p r ＝∠H 1 (jω i )
x′ k ＝X′ k T W k
wherein x 'is' k For x k And carrying out amplitude and phase compensation to obtain accurate target heave displacement.
In one embodiment, in order to verify the effect of the ship heave measurement method, the embodiment of the application measures heave through a conventional digital high-pass filter (method a), a conventional digital high-pass filter and a digital all-pass filter (method B) in combination, and the method provided by the application measures heave (method C), and the obtained error comparison chart is shown in fig. 6. As can be seen from the figure, the root mean square error of the ship heave measurement method provided by the application is only 0.0051m, and the method has higher measurement precision compared with other traditional measurement methods.
From the above, the embodiment of the application provides a ship heave measurement method based on a multiple Fourier linear combiner, which can monitor the dominant frequency of sea waves to obtain relevant frequency domain information of sea wave surges, and takes the relevant frequency domain information as prior information, so that parameters of a heave comprehensive filter and a base frequency band of a BMFLC are adaptively changed, and further, a proposed KF-BMLFC fitting model and a KF-BMLFC compensation model are utilized to obtain target heave displacement, high-precision measurement of heave information is realized, the problems of amplitude attenuation and phase error of traditional heave measurement are solved, the measurement accuracy of heave information is effectively improved, and the method has real-time performance. The method provides references for ship oscillation reduction operation, ship-based aircraft take-off and landing and active heave compensation of various offshore platforms.
Example two
The embodiment of the application provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the memory is used for storing the software program and a module, and the processor executes various functional applications and data processing by running the software program and the module stored in the memory. The memory and the processor are connected by a bus. In particular, the processor implements any of the steps of the above-described embodiment by running the above-described computer program stored in the memory.
It should be appreciated that in embodiments of the present application, the processor may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf Programmable gate arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include read-only memory, flash memory, and random access memory, and provides instructions and data to the processor. Some or all of the memory may also include non-volatile random access memory.
From the above, the electronic device provided by the embodiment of the application realizes the ship heave measurement method according to the first embodiment by running a computer program, can monitor the dominant frequency of sea waves to obtain relevant frequency domain information of sea wave surging, and uses the relevant frequency domain information as prior information, so that parameters of a vertical speed comprehensive filter and a heave comprehensive filter and a base frequency band of a BMFLC are adaptively changed, and further, a proposed KF-BMLFC fitting model and a KF-BMLFC compensation model are utilized to obtain target heave displacement, high-precision measurement of heave information is realized, and references are provided for ship heave reduction operation, ship-based aircraft lifting and active heave compensation of various offshore platforms.
It should be appreciated that the above-described integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer-readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by instructing related hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and the computer program may implement the steps of each of the method embodiments described above when executed by a processor. The computer program comprises computer program code, and the computer program code can be in a source code form, an object code form, an executable file or some intermediate form and the like. The computer readable medium may include: any entity or device capable of carrying the computer program code described above, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, randomAccess Memory), an electrical carrier wave signal, a telecommunications signal, a software distribution medium, and so forth. The content of the computer readable storage medium can be appropriately increased or decreased according to the requirements of the legislation and the patent practice in the jurisdiction.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
It should be noted that, the method and the details thereof provided in the foregoing embodiments may be combined into the apparatus and the device provided in the embodiments, and are referred to each other and are not described in detail.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/device embodiments described above are merely illustrative, e.g., the division of modules or elements described above is merely a logical functional division, and may be implemented in other ways, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. The ship heave measurement method based on the multiple Fourier linear combiner is characterized by comprising the following steps of:
acquiring vertical acceleration under a carrier coordinate system based on a strapdown inertial navigation system;
performing N-point fast Fourier transform on the vertical acceleration to obtain relevant frequency domain information of sea wave surging;
constructing a vertical velocity comprehensive filter according to the related frequency domain information, and filtering the vertical acceleration through the vertical velocity comprehensive filter to obtain a vertical velocity;
fitting the vertical speed through a KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted vertical speed through a KF-BMFLC compensation model to obtain a target vertical speed;
constructing a heave comprehensive filter according to the related frequency domain information, and filtering the target vertical speed through the heave comprehensive filter to obtain heave displacement;
and fitting the heave displacement through the KF-BMFLC fitting model, and performing amplitude-phase compensation on the fitted heave displacement through the KF-BMFLC compensation model to obtain the target heave displacement.
2. The ship heave measurement method according to claim 1, wherein the constructing a vertical-speed synthesis filter from the relevant frequency domain information comprises:
and taking the related frequency domain information as prior information, and determining the cut-off frequency of the vertical-speed comprehensive filter according to the related frequency domain information, wherein the vertical-speed comprehensive filter is as follows:
wherein, xi is the damping coefficient, omega c For the cut-off frequency, s is the laplace operator.
3. The ship heave measurement method according to claim 1, wherein filtering the vertical acceleration by the vertical velocity synthesis filter and obtaining a vertical velocity comprises:
let vertical acceleration a z Through the vertical velocity synthesis filter, to the vertical acceleration a z Integrating once and high-pass filtering to remove vertical speed error caused by low-frequency signal and output vertical speed v with amplitude-phase error z 。
4. The ship heave measurement method according to claim 3, wherein the fitting the vertical velocity by KF-BMFLC fitting model comprises:
determining a base band according to the related frequency domain information, and equally dividing the base band by M parts to obtain a plurality of frequency points f r ；
The frequency points f r As the fundamental frequency, the vertical velocity v is applied by a sine-cosine function z A linear fit was performed.
5. The ship heave measurement method according to claim 4, wherein the fitting the vertical velocity by KF-BMFLC fitting model further comprises:
weight W k As a state quantity, the optimal weight is solved by using Kalman filtering to improve fitting accuracy, wherein the solving of the optimal weight by using Kalman filtering comprises: the weight is iteratively updated by the following formula:
W k|k-1 ＝λW k-1|k-1
P k|k-1 ＝λ 2 P k-1|k-1
W k|k ＝W k|k-1 +K k e k
P k|k ＝(I-K k X k )P k|k-1 +Q
wherein k is a time series, X k ＝[X 1k X 2k … X rk ] T The basic fitting quantity of each frequency point of KF-BMFLC in the self-adaptive frequency band is obtained, wherein r=1, 2 … M, M is the number of frequency points in the self-adaptive frequency band, and f r To fit the fundamental frequency, T is the system sampling period, v k Is vertical velocity v z The element at time k, v k To the original signal v k Results obtained by KF-BMFLC fitting, W k ＝[W 1k W 2k … W 2Mk ] T Is W k One element of (B), i.e. BMFLC weight, W k-1|k-1 W is the state quantity at time k-1 k|k-1 For one-step prediction of state quantity k-1 time to k time, W k|k The state quantity at the moment k, lambda is forgetting factor, u k Is state noise, v k To measure noise, K k For Kalman gain, Q is the covariance matrix of the state noise, R is the covariance matrix of the measurement noise, P k-1|k-1 Estimating an error covariance matrix for a posterior at time k-1, P k|k-1 Estimated error covariance matrix from time k-1 to time k，P k|k A covariance matrix of the estimated error at the moment k; e, e k And I is an identity matrix for the deviation of KF quantity measurement and estimation quantity.
6. The ship heave measurement method according to claim 5, wherein the amplitude-phase compensating the fitted vertical velocity by KF-BMFLC compensation model comprises:
and performing amplitude-phase compensation on the fitted vertical speed by the following formula:
m r ＝|H 1 (jω i )|；p r ＝∠H 1 (jω i )
in which the fundamental frequency angular frequency omega i ＝2πf r ，m r For the amplitude attenuation quantity, p, of each fundamental frequency point of BMFLC r For the phase advance of each fundamental frequency point, v' k For v k And (5) obtaining the target vertical speed after the amplitude-phase compensation.
7. The ship heave measurement method according to claim 1, wherein filtering the target vertical velocity through the heave synthesis filter to obtain a heave displacement comprises:
and enabling the target vertical speed to pass through the heave comprehensive filter so as to perform primary integration and high-pass filtering on the target vertical speed subjected to amplitude phase compensation and output heave displacement with amplitude phase error.
8. The ship heave measurement method according to claim 7, wherein the fitting the heave displacement by the KF-BMFLC fitting model and the amplitude-phase compensating the fitted heave displacement by the KF-BMFLC compensating model comprises:
determining a base band according to the related frequency domain information, equally dividing the base band by M parts to obtain a plurality of frequency points, linearly fitting the heave displacement by using a sine-cosine function by using the plurality of frequency points as base frequencies, taking a weight as a state quantity, and solving an optimal weight by using Kalman filtering to improve fitting precision and obtain a fitting result;
and performing amplitude-phase compensation on the fitting result through the KF-BMFLC compensation model to obtain the target heave displacement.
9. An electronic device, comprising: memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 8 when the computer program is executed.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117288188A (en) * | 2023-11-27 | 2023-12-26 | 中国船舶集团有限公司第七〇七研究所 | Wave heave measurement compensation calculation method |
| CN117909665A (en) * | 2024-03-18 | 2024-04-19 | 青岛哈尔滨工程大学创新发展中心 | Ship motion envelope forecast data processing method and system based on Fourier filtering |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117288188A (en) * | 2023-11-27 | 2023-12-26 | 中国船舶集团有限公司第七〇七研究所 | Wave heave measurement compensation calculation method |
| CN117288188B (en) * | 2023-11-27 | 2024-03-19 | 中国船舶集团有限公司第七〇七研究所 | Wave heave measurement compensation calculation method |
| CN117909665A (en) * | 2024-03-18 | 2024-04-19 | 青岛哈尔滨工程大学创新发展中心 | Ship motion envelope forecast data processing method and system based on Fourier filtering |
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