CN114384821A - Ship motion model processing method and device and storage medium - Google Patents
Ship motion model processing method and device and storage medium Download PDFInfo
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Abstract
The invention discloses a processing method, a processing device and a storage medium of a ship motion model, which can construct a ship motion response digital twin model by combining environmental factors, optimize the ship motion response model in real time by combining a motion parameter identification model and realize more accurate prediction of ship motion in real time. The method comprises the following steps: acquiring the wave state of a real environment in real time, and constructing an environment digital twin according to the wave state and a wave mathematical model; analyzing the environmental interference force according to the environmental digital twin body to obtain an analysis result; acquiring sensor data of a real ship, and constructing a ship motion model by combining a motion parameter identification model; according to the analysis result, simulating the ship motion model under the interference of a real-time environment to obtain a ship motion state simulation result; and according to the ship motion state simulation result, calculating to obtain a ship motion state simulation result, wherein the error between the ship motion state simulation result and the real ship motion response is smaller than a threshold value, and obtaining a ship motion response model reflecting the real-time storm flow interference.
Description
Technical Field
The invention relates to the field of ship motion models, in particular to a processing method and device of a ship motion model and a storage medium.
Background
Parameters of the ship motion model are core contents of modeling work in navigation simulation, and data are generally acquired through an actual ship experiment and are calculated through preprocessing, an identification method or an empirical formula in the actual modeling process. In the related art, the parameter identification method is mostly performed based on a ship pool experiment or real ship observation data, and accurate prediction of ship motion response under variable environmental conditions is difficult.
Disclosure of Invention
In order to solve at least one of the above technical problems, the present invention provides a processing method, an apparatus and a storage medium for a ship motion model, which can construct a ship motion response digital twin model in combination with environmental factors, optimize the ship motion response model in real time in combination with a motion parameter identification model, and realize real-time and accurate prediction of ship motion.
In a first aspect, an embodiment of the present invention provides a method for processing a ship motion model, including the following steps:
acquiring the wave state of a real environment in real time, and constructing a mathematical model of the real environment as an environment digital twin body by combining the wave state with a wave mathematical model;
according to the environment digital twin body, analyzing the environment interference force to obtain an analysis result;
acquiring sensor data of a real ship, and constructing a ship motion model by combining a motion parameter identification model according to the sensor data;
according to the analysis result, simulating the ship motion model under the interference of a real-time environment to obtain a ship motion state simulation result;
and according to the ship motion state simulation result, calculating to obtain a ship motion state simulation result, wherein the error between the ship motion state simulation result and the real ship motion response is smaller than a threshold value, and obtaining a ship motion response model reflecting the real-time storm flow interference.
The processing method of the ship motion model has at least the following beneficial effects: the characteristics of the wind wave flow state are acquired in real time from the real environment, and the state corresponding to the real environment is constructed in a digital space by combining a wind wave flow mathematical model, so that the environmental interference force is correspondingly analyzed. Meanwhile, sensor data on the real ship are obtained, and the motion response of the ship motion model under real-time environmental interference is calculated according to the sensor data and the analysis of the wind wave flow model on the environmental interference force. And then, carrying out online optimization on the ship motion response model through error analysis of real ship motion response and the motion response of the ship motion model to obtain the ship motion response model capable of reflecting the interference of the storm flow in real time. Finally, the ship motion response and the environment digital twin body are combined, and real-time mapping and forecasting of the real ship motion response can be achieved. The influence of the stormy wave and current environment is fully considered, a ship motion response digital twin model is constructed, and the ship motion response model is optimized in real time by combining with the motion parameter identification model, so that the ship motion response is accurately forecasted under the condition of dynamically changing stormy wave and current influence.
According to some embodiments of the present invention, the obtaining a wave state of a real environment in real time, and constructing a mathematical model of the real environment as an environment digital twin according to the wave state and a wave mathematical model includes:
acquiring wind interference characteristics, and calculating according to the wind interference characteristics and a wind interference force model to obtain a wind interference model;
obtaining sea wave characteristics, and calculating according to the sea wave characteristics and a wave propagation model to obtain a wave interference model;
acquiring water flow characteristics, and calculating according to the water flow characteristics and a hydrodynamic model to obtain a water flow interference model;
and calculating to obtain the environment digital twin according to the wind interference model, the wave interference model and the water flow interference model.
According to some embodiments of the present invention, the acquiring sensor data of a real ship, and constructing a ship motion model according to the sensor data and in combination with a motion parameter identification model, includes:
acquiring the position information of the real ship, wherein the position information is acquired through a position sensor;
acquiring motion attitude data of the real ship, wherein the motion attitude data is acquired through a motion attitude sensor;
acquiring a ship control input signal;
and according to the position information of the real ship, the motion attitude data of the real ship and the ship control input signal, obtaining a ship motion model by combining motion model parameter identification calculation.
According to some embodiments of the present invention, when the step of calculating, according to the ship motion state simulation result, that an error between the ship motion state simulation result and a real ship motion response is smaller than a threshold value to obtain a ship motion response model reflecting real-time wind, wave and current interference is performed, the method further includes the following steps:
and calculating to obtain that the error between the ship motion state simulation result and the real ship motion response is larger than a threshold value according to the ship motion state simulation result, and optimizing the ship motion response model by combining a parameter optimization algorithm.
According to some embodiments of the invention, the obtaining the wind interference characteristics comprises:
acquiring weather forecast information issued by a preset system;
extracting the wind disturbance features from the weather forecast information, the wind disturbance features including: wind direction, visibility, weather, and temperature information.
According to some embodiments of the invention, the obtaining of the water flow characteristics and the calculating of the water flow disturbance model according to the water flow characteristics and the fluid dynamic model comprise:
constructing a neural network structure;
training the neural network structure through data information characteristics to obtain a trained neural network;
and according to the trained neural network, combining the acquired water flow characteristic data, acquiring the flow field distribution of the position of the ship in real time, and calculating to obtain a water flow interference model.
According to some embodiments of the present invention, according to the ship motion state simulation result, calculating that an error between the ship motion state simulation result and a real ship motion response is greater than a threshold, and optimizing the ship motion response model by combining a parameter optimization algorithm includes:
obtaining the simulation degree of the ship motion state simulation result according to the real-time comparison between the real ship motion response and the ship motion state simulation;
and determining that the error between the real ship motion response and the ship motion state simulation result is greater than a threshold value according to the simulation degree, and optimizing the ship motion response model by combining a parameter optimization algorithm.
According to some embodiments of the present invention, the obtaining the simulation degree of the ship motion state simulation result according to the real-time comparison between the real ship motion response and the ship motion state simulation comprises:
calculating to obtain a simulation error according to the real-time comparison of the real ship motion response and the ship motion state simulation navigational speed, the swaying angular speed and the yawing angular speed;
carrying out dimensionless simulation on the simulation errors, and averaging to obtain parameter judgment errors of the ship motion state simulation;
and obtaining the simulation degree of the ship motion state simulation result according to the parameter evaluation error.
In a second aspect, an embodiment of the present invention further provides a processing apparatus for a ship motion model, including:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor may implement the method for processing a ship motion model according to the first aspect.
In a third aspect, the present invention further provides a computer storage medium, in which a program executable by a processor is stored, and when the program executable by the processor is executed by the processor, the processor is configured to implement the processing method for the ship motion model according to the embodiment of the first aspect.
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FIG. 1 is a block flow diagram of a method for processing a ship motion model according to an embodiment of the present invention;
FIG. 2 is a block flow diagram of another method for processing a ship motion model provided in accordance with an embodiment of the present invention;
FIG. 3 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the invention;
FIG. 4 is a block flow diagram of another method for processing a ship motion model provided in accordance with an embodiment of the present invention;
FIG. 5 is a block flow diagram of another method for processing a ship motion model provided in accordance with an embodiment of the present invention;
FIG. 6 is a block flow diagram of another method for processing a ship motion model provided in accordance with an embodiment of the present invention;
FIG. 7 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the invention;
FIG. 8 is a block flow diagram of another method for processing a ship motion model provided in accordance with an embodiment of the present invention;
FIG. 9 is a block flow diagram of another method for processing a ship motion model provided in accordance with an embodiment of the present invention;
fig. 10 is a schematic block diagram of a processing device for a ship motion model according to an embodiment of the present invention.
Detailed Description
The embodiments described in the embodiments of the present application should not be construed as limiting the present application, and all other embodiments that can be obtained by a person skilled in the art without making any inventive step shall fall within the scope of protection of the present application.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.
The embodiment of the invention provides a processing method of a ship motion model, which can construct a ship motion response digital twin model by combining environmental factors, optimize the ship motion response model in real time by combining a motion parameter identification model and realize real-time and accurate prediction of ship motion. Referring to fig. 1, the method of the embodiment of the present invention includes, but is not limited to, step S110, step S120, step S130, step S140, and step S150.
Specifically, the application process of the embodiment includes the following steps:
s110: and acquiring the wave flow state of the real environment in real time, and constructing a mathematical model of the real environment as an environment digital twin body by combining the wave flow state with a wave flow mathematical model.
S120: and analyzing the environmental interference force according to the environmental digital twin body to obtain an analysis result.
S130: and acquiring sensor data of the real ship, and constructing a ship motion model by combining a motion parameter identification model according to the sensor data.
S140: and according to the analysis result, simulating the ship motion model under the interference of a real-time environment to obtain a ship motion state simulation result.
S150: and according to the ship motion state simulation result, calculating to obtain a ship motion state simulation result, wherein the error between the ship motion state simulation result and the real ship motion response is smaller than a threshold value, and obtaining a ship motion response model reflecting the real-time storm flow interference.
In the working process of the embodiment, the wave state in the real environment is firstly acquired in real time, and the acquired wave state real-time data is combined with the wave mathematical model to construct the mathematical model of the real environment in the digital space, that is, the environment digital twin of the real environment is constructed. The environmental digital twin can simulate the hydrological meteorological state of the water area where the ship is located. The environmental disturbance force can be analyzed through simulation of the environmental digital twin body on the real environment, and an analysis result of the environmental disturbance force is obtained. Meanwhile, the detection data of various sensors on the real ship are obtained. And obtaining a ship motion model through a motion parameter identification model according to the acquired sensor data. Further, according to the analysis result of the environmental disturbance force, the motion response of the ship motion model under the real-time environmental disturbance is calculated by combining the ship motion model, namely, the ship motion model is simulated under the real-time environmental disturbance, and the ship motion state simulation result is obtained. And then, obtaining a ship motion response model capable of reflecting real-time storm flow interference through error analysis between real ship motion response and the motion response of the ship motion model. Specifically, whether the error between the ship motion state simulation result and the real ship motion response is smaller than a threshold value is judged according to the ship motion state simulation result. And when the error between the simulation result of the ship motion state and the real ship motion response is smaller than a threshold value, obtaining a ship motion response model capable of reflecting real-time storm flow interference. Finally, real-time mapping and accurate forecasting of real ship motion response can be achieved according to the ship motion response model and the environment digital twin body.
In the above specific embodiment, the wave flow state in the real environment is acquired, and the wave flow mathematical model is combined to construct the environment digital twin of the real environment, so that the wave flow influence in the real environment can be reflected. Meanwhile, the position and motion attitude data of the ship are sensed through the sensor, and a ship motion model is obtained by combining motion parameter identification. And further, combining the obtained ship motion model and the environment digital twin body, and analyzing and calculating the motion response of the ship motion model under the real-time environment interference. According to the error analysis of the motion response of the ship motion model under the real-time environment interference and the motion response of the real ship, when the error is smaller than a threshold value, the motion response of the ship motion model under the real-time environment interference is consistent with the motion response of the real ship, the real-time storm flow interference can be reflected, and the ship motion response model is obtained. When the error is larger than the threshold value, the motion response of the ship motion model under the interference of the real-time environment cannot follow the motion response of the real ship in real time, parameter optimization is carried out on the ship motion response model by combining the motion parameter identification model, and finally the ship motion response model capable of tracking the motion response of the real ship in real time is obtained, so that the real-time accurate prediction of the ship motion can be realized.
Referring to fig. 2, in some embodiments of the present invention, a wave state of a real environment is obtained in real time, and a mathematical model of the real environment is constructed as an environment digital twin according to the wave state and the wave mathematical model, including but not limited to the following steps:
s210: and acquiring wind interference characteristics, and calculating according to the wind interference characteristics and the wind interference force model to obtain a wind interference model.
S220: and obtaining the wave characteristics, and calculating according to the wave characteristics and the wave propagation model to obtain a wave interference model.
S230: and acquiring water flow characteristics, and calculating according to the water flow characteristics and the hydrodynamic model to obtain a water flow interference model.
S240: and calculating according to the wind interference model, the wave interference model and the water flow interference model to obtain the environment digital twin body.
In the operation process of the above embodiment, the wind, wave and current state in the real environment includes a wind disturbance state, a wave state and a current characteristic. And obtaining a wind interference model by acquiring the wind interference characteristics and combining with the wind interference force model for calculation. Specifically, the ship speed is V, and components u, V and r of the ship speed in x and y axes and the heading direction can be obtained through decomposition under a ship-associated coordinate system; vT,ψTAbsolute wind speed and absolute wind angle, respectively. The relative wind speed can be calculated as in equation (1):
uR＝u+VT cos(ψT-ψ) (1)
vR＝-v+VT sin(ψT-ψ)
in the above formula, uR,vRIs the relative wind speed component of the x, y axes.
By relative wind velocity VRAnd feather angle alphaRThe average wind pressure and force can be obtained as shown in equation (2)Moment estimation formula:
in the formula, CXDenotes the wind pressure coefficient in the x direction, CYRepresenting the wind pressure coefficient in the y-direction, CNIs the yawing wind pressure moment coefficient, ATRepresenting the orthographic projection area of a building on a ship's hull on a water plane, ALShowing the projected area of the upper side of the hull waterline, L showing the total length of the ship, rhoaDenotes the air density, XWINDIndicating the wind pressure acting in the x-direction, YWINDRepresenting the wind pressure acting in the y-direction, NWINDIndicating a yaw wind pressure moment.
It is noted that, with reference to fig. 5, in some embodiments of the present invention, the wind disturbance characteristics are obtained, including but not limited to the following steps:
s510: and acquiring weather forecast information issued by a preset system.
S520: extracting wind interference characteristics from weather forecast information, wherein the wind interference characteristics comprise: wind direction, visibility, weather, and temperature information.
In the working process of the above embodiment, the weather forecast information issued by the preset system is firstly acquired from the preset system. Further, wind interference features are extracted from the acquired weather forecast information. Specifically, the wind interference characteristics include: wind direction, visibility, weather, and temperature information. The wind interference characteristics can be acquired through meteorological information issued by each station in a preset system, and accurate wind direction and wind speed information can be acquired in real time through a wind speed measuring instrument arranged in a supervision water area.
In addition, sea wave characteristics are obtained, and a wind interference model is obtained through calculation by combining a wave propagation model. Because the sea wave is a random phenomenon, factors influencing sea wave parameters are many and complicated, and even under the condition that the external environment is not changed, the parameters of the wave height, the wave length and the like of the wave are random. Therefore, the precise mathematical model is difficult to express, but the change of the sea wave has a certain rule, and the simulation is carried out by combining the observed sea conditions with the sea wave rule model in the simulation research. Specifically, after the sea wave characteristics are obtained, a pearson-moskovich spectrum is selected to decompose the sea wave into multiple levels of harmonics according to the spectrum, and the single harmonic energy in unit area is shown as a formula (3):
where ρ is sea water density, g is gravity acceleration, and ζ isaiThe i-th harmonic amplitude.
By using harmonic superposition principle, in omegai～ωiThe energy of the random wave between + Δ ω is shown in equation (4):
when Δ ω → 0, the energy of a random long peak wave in a unit area is expressed as shown in equation (5):
regarding sea waves as a smooth random process, the propagation model of long peak waves can be expressed as formula (6) without considering the sea waves in the rest period and the growth period:
zeta in the formulaai,ki,ωi,εiRespectively, the amplitude, wave number, angular frequency and initial phase of the ith harmonic. The disturbance force of the waves can be calculated from equation (7).
Therein, ζDMean wave amplitude, χ encounter angle, CXD(λ)、CYD(λ)、CND(lambda) is the test coefficient, L is the total length of the vessel, XWAVEWave force in the x direction, YWAVEWave force in the y direction, NWAVEIs the yawing wave moment.
Meanwhile, the water flow is a fluid motion, and a water flow interference model is obtained by acquiring the characteristics of the water flow and combining with a fluid dynamic model for calculation. Specifically, the Navier-Stokes equation is adopted to describe the acquired water flow motion law, and a specific appropriate form formula is shown as a formula (8):
where t denotes the motion time and u denotes the vector velocity field. In the two-dimensional case, u has a component (u, v), and in the three-dimensional space u contains three spatial components (u, v, w); and ρ represents the density constant of the fluid; ε represents the viscosity coefficient; f represents all external forces.
Then, the Euler grid method is adopted, a splitting method is used as a main idea for solving the NS equation, and the above formula is decomposed into four sub-term parts shown as a formula (9) for solving:
the calculation of the projection step needs to satisfy the incompressibility of the fluid, so the calculation of the pressure value is involved in the velocity solving process, and the poisson equation which needs to be solved finally is formed as shown in the formula (10):
referring to fig. 6, in some embodiments of the present invention, the water flow characteristics are obtained, and the water flow disturbance model is calculated by combining the water flow characteristics with the hydrodynamic model, including but not limited to the following steps:
s610: and constructing a neural network structure.
S620: and training the neural network structure through the data information characteristics to obtain the trained neural network.
S630: and according to the trained neural network, combining the acquired water flow characteristic data, acquiring the flow field distribution of the position where the ship is located in real time, and calculating to obtain a water flow interference model.
Because the flow field is in a real-time changing state, the calculation speed of the projection step is high. In the above embodiment, the operation of the projection step is accelerated by the neural network, so as to obtain a flow field capable of receiving real-time data and changing accordingly. Specifically, a neural network structure is constructed firstly, and the neural network structure is trained through corresponding data information characteristics to obtain a trained neural network. After the trained neural network is obtained, the disturbance force of the water flow can be calculated according to the flow field distribution of the position of the ship to be measured by combining the water flow characteristic data, so that a water flow disturbance model is obtained.
Assuming a water velocity of VCIn the direction of velocity psiCLet CX(β)、CY(β)、CN(β) are the force and moment coefficients of the flow, respectively, then equation (11) is obtained:
wherein A isfw,AswIs the orthographic projection and the side projection area, X, below the ship waterlineCURRENTDisturbance force of flow in the x direction, YCURRENTDisturbance force of flow in the y direction, NCURRENTIs the disturbance moment of the yawing flow.
According to the obtained wind interference model, the wave interference model and the water flow interference model, the environment digital twin body is obtained through calculation by combining with the wind wave flow mathematical model, the real environment state can be restored in the digital space, the influence of the wind wave flow in the real environment is introduced into the consideration range of the ship motion response model, and the real environment is mapped in the digital space in real time.
Referring to fig. 3, in some embodiments of the present invention, sensor data of a real ship is acquired, and a ship motion model is constructed according to the sensor data and in combination with a motion parameter identification model, including but not limited to the following steps:
s310: and acquiring the position information of the real ship, wherein the position information is acquired by a position sensor.
S320: and acquiring the motion attitude data of the real ship, wherein the motion attitude data is acquired by a motion attitude sensor.
S330: a vessel maneuvering input signal is obtained.
S340: and according to the position information of the real ship, the motion attitude data of the real ship and the ship control input signal, obtaining a ship motion model by combining motion model parameter identification calculation.
In the above-described embodiment, the position information of the real ship is first acquired by the position sensor. Specifically, the position sensor includes a GPS positioning sensor or a beidou positioning sensor or the like. And then acquiring the motion attitude data of the real ship, and specifically detecting the motion attitude of the ship through a motion attitude sensor carried on the real ship. Furthermore, the control input signal of the ship is obtained, and the input control signal is obtained. And calculating to obtain a motion model of the ship by combining the obtained real ship position information, motion attitude information and input control signals with a motion parameter identification model.
Specifically, considering a four-degree-of-freedom mmg (maneuvering Modeling group) separate equation, ignoring the ship heave motion and pitch motion, the ship motion equation can be simplified as shown in equation (12):
on the basis of a four-degree-of-freedom MMG model, the ship body is in a slender shape which is symmetrical left and right, namely, the inertia product about an xz plane is ignored; approximately, the ship is symmetrical front and back, namely Ixy is 0 Iyz, Ixx is 0; in view of the rolling motion of the vessel,ignoring heave and pitch motions and their coupling, i.e.
τ＝[X,Y,Z,K,M,N]The total sum of external force and external moment acting on the movement of the ship comprises the action of a ship body and additional equipment in fluid and the action of interference force and moment, and can be split as shown in a formula (13):
τ＝τI+τH+τP+τR+τF (13)
wherein in each component τIRepresenting the fluid inertia force, tau, experienced by the vesselHDenotes viscous force, τPIndicating propeller thrust, tauRIndicating steering force, tauFIndicating the fin force and its moment. A complete nonlinear mathematical model is established by analyzing each force and moment, and the model is shown as a formula (14):
wherein, m'x,m′yDimensionless variables, x ', being vessel masses and additional masses in the x and y directions'cIs a dimensionless variable of an x-axis coordinate of the center of the ship in a ship body coordinate system, F 'and N' are dimensionless variables of force and moment, I 'respectively'xx,I′zz,J′xx,J′zzAre dimensionless variables corresponding to the rotational moments of inertia and the additional rotational moments of inertia of the x-axis and the z-axis, respectively. X'uuIn dimensionless form of coefficient of direct flight drag, X'vv,X′vr,X′rrIn dimensionless form, Y ', of longitudinal hydrodynamic derivative'v,Y′r,N′v,N′rIn dimensionless form of linear hydrodynamic derivative, Y'vv,Y′vr,N′rr,N′vvr,N′vrrIn a dimensionless form of the nonlinear hydrodynamic derivative; phi is the roll angle, KpIs the coefficient of the roll angular velocity, d is the average draught, GM is the initial steady center height, W is the displacement of the ship, ρ is the density of water; t is tpIs a thrust derating coefficient, DpDiameter of the propeller, JpIs the advancing speed coefficient of the variable pitch propeller, KTIs the thrust coefficient of the paddle; t is tRIs the rudder force derating coefficient, xRIs the longitudinal coordinate of the point of action of the transverse force, aHAs a correction factor for transverse forces, zHIs the transverse moment of the hull, FNPositive fluid pressure acting on the rudder; a. theFIs the projected area of the fin, CLaIs the slope of the lift coefficient of the fin, afTo rotate the fin angle, betafIs the angle between the normal to the fin and the horizontal plane, NφIs a linear damping coefficient, Nvφ,NrφIs a nonlinear damping coefficient.
An MMG separation type ship motion model is used as a frame of an identification model, wherein ship control data such as a rudder angle delta and a propeller rotating speed n and ship motion response data such as a navigational speed u, a swaying speed v, a swaying angular speed p and a yawing angular speed r are input quantities of the identification algorithm. The output of the identification algorithm is an estimate of the parameter vector
The components of which are the various hydrodynamic derivatives. By deforming the nonlinear ship motion mathematical model, the hydrodynamic coefficient is taken as an unknown parameter to be identified, as shown in formula (15):
in the identification process, time sequence data of the navigational speed u, the rolling speed v, the rolling angular speed p, the heading angular speed r, the propeller rotating speed n and the rudder angle delta are collected on a real ship. Then, the unknown parameter a in the identification model can be identified through the identification algorithmi(i＝1,2,3,…,6)，bi(i＝1,2,3,…,7)，ci(i＝1,2,3,…,7)，diAnd (i is 1,2,3, …,6) identifying to obtain the ship motion model.
Referring to fig. 4, in some embodiments of the present invention, when the step of obtaining a ship motion response model reflecting real-time wind and wave flow interference is performed by performing a step of obtaining a ship motion response model reflecting real-time wind and wave flow interference by calculating an error between a ship motion state simulation result and a real ship motion response according to a ship motion state simulation result, the method for processing a ship model according to an embodiment of the present invention further includes, but is not limited to, the following steps:
s410: and calculating to obtain a ship motion state simulation result according to the ship motion state simulation result, wherein the error between the ship motion state simulation result and the real ship motion response is larger than a threshold value, and optimizing a ship motion response model by combining a parameter optimization algorithm.
In the above specific embodiment, through the error analysis of the motion response of the ship motion model under the real-time environmental interference and the motion response of the real ship, when the error between the motion response of the ship motion model under the real-time environmental interference and the motion response of the real ship obtained through the analysis is smaller than the threshold value, the ship motion response model is obtained. When the error between the motion response of the ship motion model under the real-time environment interference and the motion response of the real ship is larger than the threshold value, the fact that the motion response of the ship motion model cannot realize real-time motion response tracking of the real ship under the real-time environment interference is shown. And further, parameter optimization is carried out on the ship motion response model by combining a parameter optimization algorithm.
Specifically, referring to fig. 7, in some embodiments of the present invention, according to the ship motion state simulation result, an error between the ship motion state simulation result and the real ship motion response is calculated to be greater than a threshold, and a ship motion response model is optimized by combining a parameter optimization algorithm, including but not limited to the following steps:
s710: and obtaining the simulation degree of the ship motion state simulation result according to the real-time comparison between the real ship motion response and the ship motion state simulation.
S720: and determining that the error between the real ship motion response and the ship motion state simulation result is greater than a threshold value according to the simulation degree, and optimizing a ship motion response model by combining a parameter optimization algorithm.
In the working process of the above embodiment, according to the real-time comparison between the real ship motion response and the ship motion state simulation, the distance between the real ship and the ship motion state simulation is obtained by continuously tracking the output quantity of the real ship response and the ship motion state simulation, and the simulation degree of the ship motion state simulation result is obtained. The simulation degree of the ship motion state simulation result reflects the error between the ship motion state simulation result and the real ship response. And when the simulation degree of the obtained ship motion state simulation result is low, namely the error between the ship motion state simulation result and the real ship motion response is greater than a threshold value, optimizing a ship motion response model by combining a parameter optimization algorithm.
Specifically, referring to fig. 8, in some embodiments of the present invention, the simulation degree of the ship motion state simulation result is obtained according to the real-time comparison between the real ship motion response and the ship motion state simulation, including but not limited to the following steps:
s810: and calculating to obtain a simulation error according to real-time comparison of the real ship motion response and the ship motion state simulation navigational speed, the swaying angular speed and the yawing angular speed.
S820: and carrying out dimensionless simulation errors, and averaging to obtain the parameter judgment errors of the ship motion state simulation.
S830: and judging the error according to the parameters to obtain the simulation degree of the ship motion state simulation result.
In the above embodiment, the environmental interference and the motion state of the real ship in the real environment are simulated in real time according to the ship motion state simulation, so that the response of the real ship is compared with the ship motion state simulation result. Specifically, the simulation degree of the ship motion response model is judged through continuous tracking of the response of the real ship and the ship motion state simulation. Wherein, the error evaluation function is as follows (16):
in the formula, a subscript m represents a measurement quantity, a subscript s represents a simulation model output quantity, u represents a navigational speed, v represents a yaw speed, p represents a yaw angular velocity, and r represents a heading angular velocity.
The error evaluation function combines the motion response of the ship four-degree-of-freedom model, and the parameter evaluation error of the ship motion state simulation is obtained by calculating the simulation errors of the navigational speed, the swaying angular speed and the heading angular speed and taking an average value after dimensionless. And judging the error according to the obtained parameters to obtain the simulation degree of the ship motion state simulation result. Because the dynamic change of the stormy wave flow environment, the error function value can only approach to 0 as much as possible, after a reasonable acceptance range is set for the error measurement, the ship motion response model can sense the real system change caused by the stormy wave flow change, so that the parameter optimization is carried out, the parameters are corrected in real time, the effective tracking of the real system is kept, and the real-time accurate prediction of the ship motion is realized.
Referring to fig. 9, in some embodiments of the invention, a method of processing a ship model of embodiments of the invention first obtains real environment data. Specifically, the wind interference characteristics are acquired by a preset system. Wherein, the wind disturbance characteristics comprise wind direction, visibility, weather and temperature information. And calculating by combining wind interference characteristic data with a wind interference force model to obtain a wind interference model. Meanwhile, water flow characteristics are obtained through a flow speed and flow direction sensor, and a water flow interference model is obtained through calculation according to the obtained water flow characteristic data and in combination with the fluid dynamic model and the constructed neural network. In addition, the wave characteristics are detected through a wave observation instrument, and a wave interference model is obtained through calculation by combining a wave propagation model. Furthermore, a mathematical model capable of simulating the environmental interference under the real environment in real time is constructed in a digital space according to the wind and wave flow mathematical model by combining the wind interference model, the water flow interference model and the wave interference model, and is used as an environmental digital twin body of the real environment. The real environment state of the position where the ship is located can be simulated through the environment digital twin body. Meanwhile, the position information of the real ship is acquired through the position sensor on the real ship, and the motion attitude and the motion state of the real ship are detected through the motion attitude sensor, so that the position information and the motion state information of the real ship are acquired, namely the motion state of the real ship is sensed and detected. Then, the ship control input signal is sensed to obtain the control information of the ship. And identifying the motion parameters of the real ship according to the motion parameter identification model by combining the real ship motion state information acquired from the real ship and the ship control input signal to obtain a ship motion model. Furthermore, the motion state of the ship is simulated according to the ship motion model and the environment digital twin body. Specifically, the ship motion model is combined with an environment digital twin body capable of reflecting the real environment state in real time, and the ship is simulated in the response state of being interfered by the real environment, so that a ship motion state simulation result is obtained. And comparing the simulation result of the ship motion state with the motion response of the real ship, namely performing error analysis on the simulation result of the ship motion state and the sensed motion state of the real ship. When the error between the ship motion state simulation result and the motion response of the real ship is smaller than the threshold value, the ship motion state simulation can track the motion response of the real ship in real time, and the building of the ship motion response model is completed. When the error between the simulation result of the ship motion state and the motion response of the real ship is not smaller than the threshold value, the distance between the simulation result of the ship motion state and the motion state of the real ship is large, and the real ship motion state cannot be well followed. And further, parameter optimization is carried out on the ship motion response model by combining the motion parameter identification model until the error between the ship motion simulation result and the sensed real ship motion state is smaller than a threshold value, so that the ship motion response model capable of accurately forecasting the ship motion in real time is obtained.
Referring to fig. 10, an embodiment of the present invention also provides a ship model processing apparatus including: at least one processor 1010; at least one memory 1020 for storing at least one program; the at least one memory 1020 has stored thereon an executable program that is executed by the at least one processor 1010, such as performing the steps described in the above embodiments.
An embodiment of the present invention also provides a computer-readable storage medium storing computer-executable instructions for execution by one or more control processors, e.g., to perform the steps described in the above embodiments.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
While the preferred embodiments of the present invention have been described in detail, it will be understood by those skilled in the art that the foregoing and various other changes, omissions and deviations in the form and detail thereof may be made without departing from the scope of this invention.
Claims (10)
1. A processing method of a ship motion model is characterized by comprising the following steps:
acquiring the wave state of a real environment in real time, and constructing a mathematical model of the real environment as an environment digital twin body by combining the wave state with a wave mathematical model;
according to the environment digital twin body, analyzing the environment interference force to obtain an analysis result;
acquiring sensor data of a real ship, and constructing a ship motion model by combining a motion parameter identification model according to the sensor data;
according to the analysis result, simulating the ship motion model under the interference of a real-time environment to obtain a ship motion state simulation result;
and according to the ship motion state simulation result, calculating to obtain a ship motion state simulation result, wherein the error between the ship motion state simulation result and the real ship motion response is smaller than a threshold value, and obtaining a ship motion response model reflecting the real-time storm flow interference.
2. The method for processing the ship motion model according to claim 1, wherein the obtaining of the wave state of the real environment in real time, and the building of the mathematical model of the real environment as the environment digital twin according to the wave state and the wave mathematical model comprise:
acquiring wind interference characteristics, and calculating according to the wind interference characteristics and a wind interference force model to obtain a wind interference model;
obtaining sea wave characteristics, and calculating according to the sea wave characteristics and a wave propagation model to obtain a wave interference model;
acquiring water flow characteristics, and calculating according to the water flow characteristics and a hydrodynamic model to obtain a water flow interference model;
and calculating to obtain the environment digital twin according to the wind interference model, the wave interference model and the water flow interference model.
3. The method for processing the ship motion model according to claim 1, wherein the acquiring sensor data of the real ship, and constructing the ship motion model according to the sensor data and in combination with the motion parameter identification model comprises:
acquiring the position information of the real ship, wherein the position information is acquired through a position sensor;
acquiring motion attitude data of the real ship, wherein the motion attitude data is acquired through a motion attitude sensor;
acquiring a ship control input signal;
and according to the position information of the real ship, the motion attitude data of the real ship and the ship control input signal, obtaining a ship motion model by combining motion model parameter identification calculation.
4. The method for processing the ship motion model according to claim 1, wherein when the step of calculating an error between the ship motion state simulation result and the real ship motion response according to the ship motion state simulation result to be less than a threshold value and obtaining the ship motion response model reflecting the real-time storm flow interference is performed, the method further comprises the following steps:
and calculating to obtain that the error between the ship motion state simulation result and the real ship motion response is larger than a threshold value according to the ship motion state simulation result, and optimizing the ship motion response model by combining a parameter optimization algorithm.
5. The method for processing the ship motion model according to claim 2, wherein the obtaining the wind interference characteristics comprises:
acquiring weather forecast information issued by a preset system;
extracting the wind disturbance features from the weather forecast information, the wind disturbance features including: wind direction, visibility, weather, and temperature information.
6. The method for processing the ship motion model according to claim 2, wherein the obtaining of the water flow characteristics and the calculating of the water flow disturbance model according to the water flow characteristics and the fluid dynamic model comprise:
constructing a neural network structure;
training the neural network structure through data information characteristics to obtain a trained neural network;
and according to the trained neural network, combining the acquired water flow characteristic data, acquiring the flow field distribution of the position of the ship in real time, and calculating to obtain a water flow interference model.
7. The method for processing the ship motion model according to claim 4, wherein the step of optimizing the ship motion response model by combining a parameter optimization algorithm based on the error between the ship motion state simulation result and the real ship motion response calculated according to the ship motion state simulation result and larger than a threshold value comprises:
obtaining the simulation degree of the ship motion state simulation result according to the real-time comparison between the real ship motion response and the ship motion state simulation;
and determining that the error between the real ship motion response and the ship motion state simulation result is greater than a threshold value according to the simulation degree, and optimizing the ship motion response model by combining a parameter optimization algorithm.
8. The method for processing the ship motion model according to claim 7, wherein the obtaining the simulation degree of the ship motion state simulation result according to the real-time comparison between the real ship motion response and the ship motion state simulation comprises:
calculating to obtain a simulation error according to the real-time comparison of the real ship motion response and the ship motion state simulation navigational speed, the swaying angular speed and the yawing angular speed;
carrying out dimensionless simulation on the simulation errors, and averaging to obtain parameter judgment errors of the ship motion state simulation;
and obtaining the simulation degree of the ship motion state simulation result according to the parameter evaluation error.
9. A processing apparatus for a ship motion model, comprising:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method of processing a vessel motion model according to any one of claims 1 to 8.
10. A computer storage medium in which a processor-executable program is stored, wherein the processor-executable program, when executed by the processor, is for implementing a method of processing a vessel motion model according to any one of claims 1 to 8.
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