CN114384821B - Ship motion model processing method, device and storage medium - Google Patents
Ship motion model processing method, device and storage medium Download PDFInfo
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Abstract
The application discloses a processing method, a processing device and a storage medium for a ship motion model, which can be used for constructing a ship motion response digital twin model by combining environmental factors and optimizing the ship motion response model in real time by combining a motion parameter identification model so as to realize more accurate prediction of ship motion in real time. The method comprises the following steps: acquiring the wave current state of the real environment in real time, and constructing an environment digital twin body according to the wave current state and a wave current 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 real-time environmental interference to obtain a ship motion state simulation result; and calculating to obtain the error between the ship motion state simulation result and the real ship motion response smaller than a threshold value according to the ship motion state simulation result, and obtaining a ship motion response model reflecting the real-time wind wave current interference.
Description
Technical Field
The present application relates to the field of ship motion models, and in particular, to a method and apparatus for processing 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 in the actual modeling process, data are generally collected through a real ship experiment, and are calculated through preprocessing, an identification method or an empirical formula. In the related art, the parameter identification method is mostly based on ship pool experiments or real ship observation data, and accurate prediction of ship motion response is difficult under changeable environmental conditions.
Disclosure of Invention
In order to solve at least one of the technical problems, the application provides 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.
In a first aspect, an embodiment of the present application provides a method for processing a ship motion model, including the following steps:
acquiring the wave current state of the real environment in real time, and constructing a mathematical model of the real environment as an environment digital twin body according to the wave current state and the wave current mathematical model;
according to the environmental digital twin body, analyzing the environmental interference force to obtain an analysis result;
acquiring sensor data of a real ship, and constructing a ship motion model according to the sensor data and combining a motion parameter identification model;
according to the analysis result, simulating the ship motion model under the real-time environmental interference to obtain a ship motion state simulation result;
and calculating to obtain the error between the ship motion state simulation result and the real ship motion response to be smaller than a threshold value according to the ship motion state simulation result, and obtaining a ship motion response model reflecting real-time wind wave current interference.
The processing method of the ship motion model has at least the following beneficial effects: the characteristics of the wave current state are obtained from the real environment in real time, and the state corresponding to the real environment is constructed in the digital space by combining the wave current mathematical model, so that the environment interference force is correspondingly analyzed. And meanwhile, acquiring sensor data on a real ship, and calculating the motion response of the ship motion model under real-time environment interference according to the sensor data and the analysis of the environment interference force by the wind wave current model. And then, performing online optimization on the ship motion response model through error analysis of the motion response of the real ship and the motion response of the ship motion model, so as to obtain the ship motion response model capable of reflecting the wind wave current interference in real time. Finally, the ship motion response and the environmental digital twin are combined, and real-time mapping and forecasting of the real ship motion response can be realized. The influence of the wind 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 the motion parameter identification model, so that the ship motion response is accurately predicted under the condition of the influence of the dynamically changed wind wave and current.
According to some embodiments of the present application, the acquiring the wind wave current state of the real environment in real time, and constructing a mathematical model of the real environment as an environmental digital twin body according to the wind wave current state and the wind wave current mathematical model, includes:
acquiring air disturbance characteristics, and calculating according to the air disturbance characteristics and the air disturbance force model to obtain an air disturbance model;
acquiring wave characteristics, and calculating according to the 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 the environmental digital twin body according to the air disturbance model, the wave disturbance model and the water flow disturbance model.
According to some embodiments of the application, the acquiring sensor data of a real ship, and constructing a ship motion model according to the sensor data and combining 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 operation input signal;
and according to the position information of the real ship, the motion attitude data of the real ship and the ship operation input signals, combining the motion model parameter identification and calculation to obtain a ship motion model.
According to some embodiments of the present application, 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, and obtaining a ship motion response model reflecting real-time wind, wave and current interference is performed, the method further includes the steps of:
and according to the ship motion state simulation result, calculating that the error between the ship motion state simulation result and the real ship motion response is larger than a threshold value, and optimizing the ship motion response model by combining a parameter optimization algorithm.
According to some embodiments of the application, the acquiring the air-disturbance feature comprises:
acquiring weather forecast information issued by a preset system;
extracting the air disturbance characteristics from the weather forecast information, wherein the air disturbance characteristics comprise: wind direction, visibility, weather and temperature information.
According to some embodiments of the application, the obtaining the water flow characteristics, and calculating the water flow interference model according to the water flow characteristics and the hydrodynamic model, includes:
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 ship at the position in real time, and calculating to obtain a water flow interference model.
According to some embodiments of the present application, according to the ship motion state simulation result, an error between the ship motion state simulation result and a real ship motion response is calculated to be greater than a threshold value, and the ship motion response model is optimized by combining a parameter optimization algorithm, including:
obtaining the simulation degree of the ship motion state simulation result according to the real-time comparison of 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 larger 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 application, 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 includes:
according to real-time comparison of the real ship motion response and the ship motion state simulation navigational speed, the transverse oscillation angular speed and the bow oscillation angular speed, calculating to obtain simulation errors;
dimensionless, taking an average value to obtain a parameter judgment error of the ship motion state simulation;
and obtaining the simulation degree of the ship motion state simulation result according to the parameter judgment error.
In a second aspect, an embodiment of the present application further provides a processing device for a ship motion model, including:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement a method of processing a model of vessel motion as described in the first aspect above.
In a third aspect, an embodiment of the present application further provides a computer storage medium, in which a program executable by a processor is stored, the program executable by the processor being configured to implement a method for processing a 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 application;
FIG. 2 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
FIG. 3 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
FIG. 4 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
FIG. 5 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
FIG. 6 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
FIG. 7 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
FIG. 8 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
FIG. 9 is a block flow diagram of another method for processing a ship motion model according to an embodiment of the present application;
fig. 10 is a schematic block diagram of a processing device for a ship motion model according to an embodiment of the present application.
Detailed Description
The embodiments described herein should not be construed as limiting the application, and all other embodiments, which may be made by those of ordinary skill in the art without the benefit of the present disclosure, are intended to be within the scope 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 to be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with one another 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 application only and is not intended to be limiting of the application.
The embodiment of the application provides a processing method of a ship motion model, which can be used for constructing a ship motion response digital twin model by combining environmental factors and optimizing the ship motion response model in real time by combining a motion parameter identification model so as to realize more accurate prediction of ship motion in real time. Referring to fig. 1, the method of the embodiment of the present application includes, but is not limited to, step S110, step S120, step S130, step S140, and step S150.
Specifically, the application process of the present embodiment includes the following steps:
s110: the method comprises the steps of obtaining the wave current state of the real environment in real time, and constructing a mathematical model of the real environment as an environment digital twin body according to the wave current state and the wave current mathematical model.
S120: and (4) 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 according to the sensor data and the motion parameter identification model.
S140: and according to the analysis result, simulating the ship motion model under the real-time environment interference to obtain a ship motion state simulation result.
S150: and calculating to obtain the error between the ship motion state simulation result and the real ship motion response smaller than a threshold value according to the ship motion state simulation result, and obtaining a ship motion response model reflecting the real-time wind wave current interference.
In the working process of the embodiment, the real-time acquisition of the storm flow state in the real environment is performed first, and the acquired real-time storm flow state data are combined with the storm flow mathematical model to construct a mathematical model of the real environment in the digital space, namely, an environment digital twin body of the real environment is constructed. The environmental digital twin can simulate the hydrological weather state of the water area where the ship is located. The environmental disturbance force can be analyzed through the simulation of the environmental digital twin body to the real environment, and the analysis result of the environmental disturbance force can be obtained. Meanwhile, detection data of various sensors on the real ship are obtained. And obtaining a ship motion model through the motion parameter identification model according to the acquired sensor data. Further, according to the analysis result of the environmental disturbance force and the ship motion model, calculating the motion response of the ship motion model under the real-time environmental disturbance, namely simulating the ship motion model under the real-time environmental disturbance, and obtaining the ship motion state simulation result. And then, obtaining a ship motion response model capable of reflecting real-time wind wave current interference through error analysis between the real ship motion response and the motion response of the ship motion model. Specifically, according to the ship motion state simulation result, whether the error between the ship motion state simulation result and the real ship motion response is smaller than a threshold value is judged. And when the error between the ship motion state simulation result and the real ship motion response is smaller than a threshold value, obtaining a ship motion response model capable of reflecting the real-time wind wave current interference. Finally, according to the ship motion response model and the environmental digital twin, real-time mapping and accurate forecasting of the real ship motion response can be realized.
In the above embodiment, by acquiring the wave current state in the real environment and constructing the environment digital twin body of the real environment by combining the wave current mathematical model, the wave current influence in the real environment can be reflected. And simultaneously, sensing the position and motion attitude data of the ship through the sensor, and combining the motion parameter identification to obtain a ship motion model. Further, the obtained ship motion model and the environmental digital twin are combined, and the motion response of the ship motion model under real-time environmental interference is calculated through analysis. 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 accords with the motion response of the real ship, the real-time wind wave current 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 real-time environment interference cannot follow the motion response of the real ship in real time, the 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 application, the storm flow state of the real environment is obtained in real time, and a mathematical model of the real environment is constructed as an environmental digital twin body according to the storm flow state in combination with a storm flow mathematical model, including but not limited to the following steps:
s210: and acquiring air disturbance characteristics, and calculating according to the air disturbance characteristics and the air disturbance force model to obtain an air disturbance model.
S220: and acquiring the wave characteristics, and calculating according to the wave characteristics and the wave propagation model to obtain the wave interference model.
S230: and obtaining 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 air disturbance model, the wave disturbance model and the water flow disturbance model to obtain the environmental digital twin body.
In the working process of the specific embodiment, the wind and wave current state in the real environment comprises an air disturbance state, a sea wave state and a water current characteristic. And obtaining the air disturbance characteristics, and calculating by combining the air disturbance force model to obtain an air disturbance model. Specifically, let the ship speed be V, the components u, V, r of the speed in the x, y axis and the bow direction can be obtained through decomposition under the ship-following coordinate system; v (V) T ,ψ T Absolute wind speed and absolute wind broadside angle, respectively. The relative wind speed can be calculated as in equation (1):
u R ＝u+V T cos(ψ T -ψ) (1)
v R ＝-v+V T sin(ψ T -ψ)
in the above, u R ,v R Is the relative wind velocity component of the x, y axis.
By relative wind velocity V R Wind-and-air angle alpha R An estimated formula of the average wind pressure and moment as shown in formula (2) can be obtained:
wherein C is X Representing the wind pressure coefficient in the x-direction, C Y Representing the wind pressure coefficient in the y-direction, C N Is a bow wind pressure moment coefficient A T Representing the orthographic projection area of a building on a water plane on a ship body, A L The projection area of the upper side of the water line of the ship body is represented, L represents the total length of the ship, and ρ is represented a Represents air density, X WIND Representing wind acting in the x-directionPressure, Y WIND Representing the wind pressure acting in the y direction, N WIND Representing the bow wind pressure moment.
It should be noted that, referring to fig. 5, in some embodiments of the present application, the air-disturbance feature is obtained, including, but not limited to, the following steps:
s510: and acquiring weather forecast information issued by a preset system.
S520: extracting air interference features from weather forecast information, wherein the air interference features comprise: wind direction, visibility, weather and temperature information.
In the working process of the specific embodiment, firstly, the published weather forecast information is obtained from a preset system. Further, air disturbance features are extracted from the acquired weather forecast information. Specifically, the air-disturbance features include: wind direction, visibility, weather and temperature information. The air disturbance characteristics can be obtained from meteorological information issued by each station in a preset system, and more accurate wind direction and wind speed information can be obtained in real time through a wind speed measuring instrument arranged in a monitored water area.
In addition, the sea wave characteristics are obtained, and the air disturbance model is calculated by combining the wave propagation model. Because the sea wave is a random phenomenon, the factors influencing the parameters of the sea wave are many and complicated, and the parameters such as wave height, wave length and the like of the wave are random even if the external environment is unchanged. Therefore, the method is difficult to express by an accurate mathematical model, but the change of the sea wave has a certain rule, and the simulation is carried out by combining the observed sea condition with the sea wave rule model in the simulation research. Specifically, after the characteristics of the sea waves are obtained, the pearson-Mo Sike three-dimensional odd spectrum is selected to decompose the sea waves into multi-level harmonic waves according to the spectrum, and the single harmonic energy in unit area is shown as a formula (3):
wherein ρ is sea water density, g is gravity acceleration, ζ ai The ith harmonic amplitude.
Using harmonic stacksPrinciple of addition, at ω i ～ω i The energy of the random wave between +Δω is shown in equation (4):
when Δω→0, the energy of the random long peak wave per unit area is expressed as shown in formula (5):
considering sea waves as a smooth random process, irrespective of the rest and growth phases of sea waves, the propagation model of long peak waves can be expressed as in equation (6):
zeta in ai ,k i ,ω i ,ε i The amplitude, wavenumber, angular frequency and initial phase of the ith harmonic, respectively. The disturbance force of the wave can be calculated from equation (7).
Wherein ζ D For average wave amplitude, χ is the encounter angle, C XD (λ)、C YD (λ)、C ND (lambda) is the test coefficient, L is the total length of the ship, X WAVE Is wave force in x direction, Y WAVE For wave force in y direction, N WAVE Is the moment of bow wave.
Meanwhile, the water flow is fluid movement, and a water flow interference model is obtained through acquiring water flow characteristics and combining with a fluid dynamic model. Specifically, the Navier-Stokes equation is adopted to describe the acquired water flow motion law, and a specific proper amount of form formula is shown as formula (8):
where t represents the motion time and u represents the vector velocity field. In the two-dimensional case, u has components (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; epsilon represents the viscosity coefficient; f represents all external forces.
Then, an Euler grid method is adopted, a splitting method is used as a main thought for solving an NS equation, and the method is decomposed into four sub-item subsection solutions as shown in a formula (9):
the calculation of the projection step needs to satisfy the incompressibility of fluid, so that the calculation of the pressure value is involved in the speed solving process, and a poisson equation which finally needs to be solved is formed as shown in a formula (10):
it should be noted that, referring to fig. 6, in some embodiments of the present application, the water flow characteristics are obtained, and the water flow disturbance model is calculated according to the water flow characteristics and the fluid dynamic model, including but not limited to the following steps:
s610: and constructing a neural network structure.
S620: training the neural network structure through the data information characteristics to obtain a 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 ship at the position in real time, and calculating to obtain a water flow interference model.
Because the flow field is in a state of real-time change, a higher requirement is placed on the calculation speed of the projection step. In the above embodiment, the projection step is accelerated by the neural network, so as to obtain a flow field capable of receiving real-time data and changing with the data. Specifically, a neural network structure is firstly constructed, and the neural network structure is trained through corresponding data information characteristics, so that a trained neural network is obtained. 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 tested by combining the water flow characteristic data, so that a water flow disturbance model is obtained.
Let the water flow velocity be V C Velocity direction is psi C Order C X (β)、C Y (β)、C N (β) is the force and moment coefficients of the flow, respectively, then equation (11) is obtained:
wherein A is fw ,A sw X is the orthographic projection area and the side projection area below the waterline of the ship CURRENT Is the disturbance force flowing in the x direction, Y CURRENT For disturbing forces flowing in the y-direction, N CURRENT Is the disturbance moment of the bow flow.
According to the obtained air disturbance model, wave disturbance model and water flow disturbance model, the environmental digital twin body is obtained through calculation by combining with the wind wave flow mathematical model, the real environmental state can be restored in the digital space, the influence of wind wave flow in the real environment is introduced into the consideration range of the ship motion response model, and the real-time mapping of the real environment in the digital space is realized.
Referring to fig. 3, in some embodiments of the present application, sensor data of a real ship is acquired, and a ship motion model is constructed according to the sensor data 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 through a position sensor.
S320: and acquiring the motion attitude data of the real ship, wherein the motion attitude data is acquired through a motion attitude sensor.
S330: and acquiring a ship steering input signal.
S340: and according to the position information of the actual ship, the motion attitude data of the actual ship and the ship steering input signal, combining the motion model parameter identification and calculation to obtain a ship motion model.
In the above 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. Further, 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 acquired real ship position information, motion attitude information and the input control signals with the motion parameter identification model.
Specifically, considering the four degrees of freedom MMG (Maneuvering Modeling Group) split equation, ignoring the heave motion and pitch motion of the vessel, the vessel motion equation may be simplified as shown in equation (12):
on the basis of the four-degree-of-freedom MMG model, the ship body is slender and symmetrical, namely the inertia product about the xz plane is ignored; the ship is approximately considered to be symmetrical in front-back, i.e. ixy=iyz=0, ixx=0; considering vessel roll motions, neglecting heave and pitch motions and their coupling effects, i.e.τ＝[X,Y,Z,K,M,N]The total sum of external force and external moment acting on the ship motion, comprising the actions of a ship body and additional equipment in fluid and the actions of disturbance force and moment, can be split as shown in a formula (13):
τ＝τ I +τ H +τ P +τ R +τ F (13)
wherein τ in each component I Representing the inertial force of fluid to which the ship is subjected,τ H Indicative of adhesive force, tau P Representing propeller thrust, τ R Indicating rudder force tau F Representing the fin force and moment thereof. The complete nonlinear mathematical model is built by analyzing the forces and moments as shown in equation (14):
wherein m ', m' x ,m′ y Is a dimensionless variable, x ', of the ship mass and additional mass in the x and y axis directions' c Is the dimensionless variable of the x-axis coordinate of the ship center in the ship body coordinate system, and F ', N' are the dimensionless variables of force and moment and I ', respectively' xx ,I′ zz ,J′ xx ,J′ zz Is a dimensionless variable of rotational moment of inertia and additional rotational moment of inertia corresponding to the x-axis and the z-axis, respectively. X'. uu In the dimensionless form of the direct resistance coefficient, X' vv ,X′ vr ,X′ rr In the dimensionless form of longitudinal hydrodynamic derivatives, Y' v ,Y′ r ,N′ v ,N′ r In dimensionless form of linear hydrodynamic derivatives, Y' vv ,Y′ vr ,N′ rr ,N′ vvr ,N′ vrr Is a dimensionless form of the nonlinear hydrodynamic derivative; phi is the roll angle, K p The roll angular velocity coefficient is represented by d, average draft, GM, primary steady center height, W, ship displacement and ρ, water density; t is t p For the thrust derating coefficient, D p For propeller diameter, J p K is the advance coefficient of the pitch-variable propeller T Is the thrust coefficient of the paddle; t is t R For rudder force derating coefficient, x R Longitudinal coordinate of point of application of transverse force, a H Is the correction factor of the transverse force, z H Is the transverse moment of the ship body, F N Is a positive pressure of fluid acting on the rudder; a is that F Is the projected area of the fin, C La A is the slope of the lift coefficient of the fin, a f To rotate the fin angle beta f Is the angle between the normal line of the fin and the horizontal plane, N φ Is a linear damping coefficient, N vφ ,N rφ Is a nonlinear damping coefficient.
The MMG separated ship motion model is used as a frame of an identification model, wherein ship control data such as rudder angle delta, propeller rotating speed n and ship motion response data such as navigational speed u, sway speed v, sway angular speed p and bow sway angular speed r are input values of an identification algorithm. The output of the identification algorithm is the estimated value of the parameter vectorThe components are the various hydrodynamic derivatives. By deforming the nonlinear ship motion mathematical model, the hydrodynamic coefficient is used as an unknown parameter to be identified, as shown in the formula (15):
in the identification process, time series data of the navigational speed u, the sway speed v, the roll angular speed p, the yaw angular speed r, the propeller rotating speed n and the rudder angle delta are acquired on a real ship. Then the unknown parameter a in the identification model can be identified by an identification algorithm i (i＝1,2,3,…,6)，b i (i＝1,2,3,…,7)，c i (i＝1,2,3,…,7)，d i And (i=1, 2,3, … and 6) identifying to obtain the ship motion model.
Referring to fig. 4, in some embodiments of the present application, when a step of calculating, according to a 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 and obtaining a ship motion response model reflecting real-time wind wave current interference is performed, a processing method of a ship model provided by an embodiment of the present application further includes, but is not limited to, the following steps:
s410: and calculating to obtain the error between the ship motion state simulation result and the real ship motion response greater than a threshold according to the ship motion state simulation result, 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 analysis shows that the error of the motion response of the ship motion model under the real-time environmental interference and the motion response of the real ship 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 a threshold value, the motion response of the ship motion model is not capable of realizing real-time motion response tracking of the real ship under the real-time environment interference. 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 application, 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 value, 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 of 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 larger 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 specific embodiment, according to real-time comparison of the real ship motion response and the ship motion state simulation, the distance between the real ship response and the ship motion state simulation is obtained through continuous tracking of 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. 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 larger than a threshold value, the ship motion response model is optimized by combining a parameter optimization algorithm.
Specifically, referring to fig. 8, in some embodiments of the present application, based on real-time comparison of real ship motion response and ship motion state simulation, a simulation of ship motion state simulation results is obtained, including, but not limited to, the following steps:
s810: and according to real-time comparison of the real ship motion response and the ship motion state simulation navigational speed, the sway speed, the roll angular speed and the bow roll angular speed, calculating to obtain simulation errors.
S820: and dimensionless simulation errors, and taking an average value to obtain parameter judgment errors of the ship motion state simulation.
S830: and obtaining the simulation degree of the ship motion state simulation result according to the parameter judgment error.
In the specific 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 criterion function is as in formula (16):
in the formula, the subscript m represents a measurement quantity, the subscript s represents a simulation model output quantity, u represents a navigational speed, v represents a yaw speed, p represents a yaw angular speed and r represents a yaw angular speed.
The error judging function combines the motion response of the ship four-degree-of-freedom model, and the parameter judging error of the ship motion state simulation is obtained by calculating the simulation errors of the navigational speed, the transverse oscillation angular speed and the bow oscillation angular speed and taking the average value after dimensionless. And obtaining the simulation degree of the ship motion state simulation result according to the obtained parameter judgment error. Because the dynamic change of the wind wave current environment only approaches 0 as much as possible, after a reasonable receiving range is set for the error measurement, the ship motion response model can sense the real system change caused by the wind wave current change, so that parameter optimization is carried out, parameters are corrected in real time, effective tracking of the real system is maintained, and real-time accurate prediction of the ship motion is realized.
Referring to fig. 9, in some embodiments of the present application, the processing method of the ship model of the embodiment of the present application is first obtained by acquiring real environment data. Specifically, the air-disturbance characteristics are obtained through a preset system. Wherein the air-disturbance characteristics include wind direction, visibility, weather, and temperature information. And calculating by combining the air disturbance characteristic data with an air disturbance force model to obtain an air disturbance model. Meanwhile, the water flow characteristics are acquired through the flow velocity and flow direction sensor, and according to the acquired water flow characteristic data, a fluid dynamic model and a constructed neural network are combined, and a water flow interference model is obtained through calculation. In addition, the wave characteristics are detected through the wave observer, and the wave interference model is calculated by combining the wave propagation model. Further, combining the air disturbance model, the water flow disturbance model and the wave disturbance model, constructing a mathematical model capable of simulating the environment disturbance in real time in the real environment in a digital space according to the wind wave flow mathematical model, and taking the mathematical model as an environment digital twin body of the real environment. The real environment state of the ship 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, the motion gesture and the state of the real ship are detected through the motion gesture sensor, and the position information and the motion state information of the real ship are obtained, namely the motion state of the real ship is sensed and detected. And then, sensing the ship operation input signal to obtain the control information of the ship. And according to the motion parameter identification model, combining the motion state information of the real ship obtained from the real ship and the ship operation input signal, carrying out motion parameter identification on the real ship to obtain a ship motion model. Further, according to the ship motion model and the environmental digital twin body, the motion state of the ship is simulated. 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 response state of the ship under the real environment interference is simulated to obtain a ship motion state simulation result. And comparing the ship motion state simulation result with the motion response of the real ship, namely performing error analysis on the ship motion state simulation result and the perceived real ship motion state. 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 is indicated to be capable of tracking the motion response of the real ship in real time, and the ship motion response model is constructed. When the error between the ship motion state simulation result and the motion response of the real ship is not smaller than the threshold value, the distance between the ship motion state simulation and the real ship motion state is larger, and the real ship motion state cannot be well followed yet. And further, carrying out parameter optimization on the ship motion response model by combining the motion parameter identification model until the error between the ship motion simulation result and the perceived real ship motion state is smaller than a threshold value, so as to obtain the ship motion response model capable of accurately forecasting the ship motion in real time.
Referring to fig. 10, an embodiment of the present application 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, for example, to perform the steps described in the above embodiments.
An embodiment of the present application 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.
Those 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 both 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 known to those skilled 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 be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, 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.
While the preferred embodiment of the present application has been described in detail, the present application is not limited to the above embodiment, and various equivalent modifications and substitutions can be made by those skilled in the art without departing from the spirit of the present application, and these equivalent modifications and substitutions are intended to be included in the scope of the present application as defined in the appended claims.
Claims (10)
1. The processing method of the ship motion model is characterized by comprising the following steps of:
acquiring the wave current state of the real environment in real time, and constructing a mathematical model of the real environment as an environment digital twin body according to the wave current state and the wave current mathematical model;
according to the environmental digital twin body, analyzing the environmental interference force to obtain an analysis result;
acquiring sensor data of a real ship, and constructing a ship motion model according to the sensor data and combining a motion parameter identification model;
according to the analysis result, simulating the ship motion model under the real-time environmental interference to obtain a ship motion state simulation result;
and calculating to obtain the error between the ship motion state simulation result and the real ship motion response to be smaller than a threshold value according to the ship motion state simulation result, and obtaining a ship motion response model reflecting real-time wind wave current interference.
2. The method for processing the ship motion model according to claim 1, wherein the acquiring the storm flow state of the real environment in real time, constructing the mathematical model of the real environment as an environmental digital twin body by combining the storm flow state with the storm flow mathematical model, comprises:
acquiring air disturbance characteristics, and calculating according to the air disturbance characteristics and the air disturbance force model to obtain an air disturbance model;
acquiring wave characteristics, and calculating according to the 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 the environmental digital twin body according to the air disturbance model, the wave disturbance model and the water flow disturbance model.
3. The method for processing the ship motion model according to claim 1, wherein the acquiring the sensor data of the real ship, and constructing the ship motion model according to the sensor data 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 operation input signal;
and according to the position information of the real ship, the motion attitude data of the real ship and the ship operation input signals, combining the motion model parameter identification and calculation to obtain a ship motion model.
4. The method according to claim 1, wherein when the step of calculating, from 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 and obtaining a ship motion response model reflecting real-time wind, wave and current interference is performed, the method further comprises the steps of:
and according to the ship motion state simulation result, calculating that the error between the ship motion state simulation result and the real ship motion response is larger than a threshold value, and optimizing the ship motion response model by combining a parameter optimization algorithm.
5. The method of processing a model of vessel motion according to claim 2, wherein the acquiring air disturbance features comprises:
acquiring weather forecast information issued by a preset system;
extracting the air disturbance characteristics from the weather forecast information, wherein the air disturbance characteristics comprise: wind direction, visibility, weather and temperature information.
6. The method for processing the ship motion model according to claim 2, wherein the obtaining the water flow characteristics and calculating the water flow disturbance model according to the water flow characteristics and the hydrodynamic 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 ship at the position 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 calculating, according to the ship motion state simulation result, that the error between the ship motion state simulation result and the real ship motion response is greater than a threshold value, and optimizing the ship motion response model in combination with a parameter optimization algorithm comprises:
obtaining the simulation degree of the ship motion state simulation result according to the real-time comparison of 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 larger 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:
according to real-time comparison of the real ship motion response and the ship motion state simulation navigational speed, the transverse oscillation angular speed and the bow oscillation angular speed, calculating to obtain simulation errors;
dimensionless, taking an average value to obtain a parameter judgment error of the ship motion state simulation;
and obtaining the simulation degree of the ship motion state simulation result according to the parameter judgment 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 said at least one program is executed by said at least one processor, at least one of said processors is caused to implement a method of processing a model of vessel motion as claimed in any one of claims 1 to 8.
10. A computer storage medium in which a processor-executable program is stored, characterized in that the processor-executable program, when being executed by the processor, is adapted to carry out the method of processing a model of vessel motion according to any one of claims 1 to 8.
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