CN115358100B - Multi-objective optimization method and device for ocean towing system - Google Patents
Multi-objective optimization method and device for ocean towing system Download PDFInfo
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Abstract
The invention belongs to the technical field of optimization of marine towing systems, and provides a multi-objective optimization method and device for a marine towing system in order to solve the problem that an existing marine towing system optimization model is low in calculation efficiency. The method comprises the steps of obtaining relevant parameters of a towing system; obtaining all target parameter optimal solutions of the marine towing system based on a multi-target optimization model of the marine towing system and related parameters of the towing system so as to guide the marine towing system to complete a marine task; wherein the multi-objective optimization model is constructed based on a towed system model; the towing system model includes a regular elongated structure model and an irregular structure model. The method adopts a mode of combining the proxy model and the analytic model, simplifies the optimization model of the marine towing system, and finally improves the efficiency of the marine towing system in completing marine operation.
Description
Technical Field
The invention belongs to the technical field of optimization of marine towing systems, and particularly relates to a multi-objective optimization method and device for a marine towing system.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
The marine towing system is widely applied to tasks such as marine physics and marine geological exploration. The marine towing system mainly comprises a mother ship, towing cables, a towing body, array cables and a stabilizing device. The mother ship is a power source of the whole system, and drags the system to implement operation. The towing cable is connected with the mother ship and the towing body. The towed body carries different scientific instruments according to different operation tasks. Various signal receivers are arranged on the array cable, so that the seabed information can be obtained in time. The stabilizing device is mostly of a symmetrical structure, backward dragging force is provided for the array cable, the straight state of the array cable is kept, and the quality of received information is further improved.
The towing speed of the towing system is closely related to the working efficiency. The dragging speed is too low, the detection area in unit time is too small, and the working efficiency is low; the dragging speed is too high, the water resistance of the system is increased, the dragging body floats upwards, and the dragging depth cannot meet the detection requirement. Therefore, a plurality of factors are comprehensively considered when determining the dragging speed of the system. In addition, when the height of the seabed changes, the towing depth of the towing body needs to be adjusted by retracting and releasing the towing cable, so that the towing body and the seabed can be kept at a safe distance. For example, when the height of the seabed rises, the towing body needs to be floated by drawing the cable; when the towing body is lowered, the cable is laid to make the towing body sink. In order to adjust the depth of the towed body in time, the length of the towed cable should be shortened as much as possible. However, if the length of the towing cable is too short, the towing depth is too small, and the detection requirement cannot be met. Thus, there are also a number of factors to consider when determining the length of the trailing cable. Due to the complex action relationship among the dragging speed, the dragging cable length and the dragging depth of the system, the design of the deep dragging system is necessarily a multi-objective optimization design problem. The mechanical modeling of the system is an important link of multi-objective optimization design. For regular structures in the system, a concentrated mass method and a finite difference method are commonly used for modeling the regular structures. However, even if a centralized quality method with a small calculation amount among the three methods is selected, when a towed cable with the length of thousands of meters is modeled, the number of control equations of the towed cable still suddenly increases along with the increase of the size of a structure, so that the time consumed for solving the form of the towed cable is increased, and the calculation efficiency of an optimization model is greatly reduced; for an irregular structure in the system, such as a towed body, the hydrodynamic load must be calculated when modeling its mechanics. Computational Fluid Dynamics (CFD) is a common method of calculating the hydrodynamic load of an irregular structure. However, acquiring hydrodynamic loads using CFD requires large computational resources, and also makes the optimization model difficult to solve.
In conclusion, the inventor finds that the current optimized model of the marine towing system is low in calculation efficiency, and the design efficiency of the marine towing system is reduced.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a multi-objective optimization method and a multi-objective optimization device for a marine towing system.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a multi-objective optimization method for an ocean towing system.
A multi-objective optimization method for a marine towing system comprises the following steps:
acquiring relevant parameters of a towing system;
obtaining all target parameter optimization solutions of the marine towing system based on the multi-target optimization model of the marine towing system and the related parameters of the towing system so as to guide the marine towing system to complete a marine task;
wherein the multi-objective optimization model is constructed based on a towed system model; the towing system model comprises a regular elongated structure model and an irregular structure model;
the regular elongated structure model is constructed by adopting a theoretical analytical model, and corresponding mechanical parameters are obtained by solving based on a quasi-static iterative algorithm;
the irregular structure model is a proxy model of the motion state and the drag viscous resistance of the irregular structure established by using an artificial neural network, or an analytic model of the motion state and the drag viscous resistance of the irregular structure established by using a data fitting method.
In one embodiment, the optimization target of the multi-target optimization model is any combination of at least two of the parameters of towing speed, towing cable length, towing depth, towing body suspension position, towing cable tension, towing body pitch angle, towing cable and towing body suspension position, and array cable and towing body suspension position.
As an embodiment, the regular elongated structure model comprises a towed cable model, an umbilical cable model, an acoustic or optical array cable model.
In the process of constructing the towing cable model, a quasi-static model is utilized to determine the towing depth, the relationship between the maximum tension of the towing cable and a design variable, and a mother ship is simplified into a moving mass point to provide position or speed constraint for the system; the tow body is simplified to the forces and moments acting on the trailing end of the tow cable.
In the process of constructing the array cable model, the cable is regarded as a horizontally-placed slender cylinder, and the dragging viscous resistance of the elongated cylinder is solved by using a numerical analysis method.
The invention provides a multi-objective optimization device for an ocean towing system.
A multi-objective optimization device for marine towed systems, comprising:
the parameter acquisition module is used for acquiring related parameters of the towing system;
the target optimization module is used for obtaining all target parameter optimization solutions of the marine towing system based on the multi-target optimization model of the marine towing system and relevant parameters of the towing system so as to guide the marine towing system to complete marine tasks;
wherein the multi-objective optimization model is constructed based on a drag system model; the towing system model comprises a regular elongated structure model and an irregular structure model;
the regular elongated structure model is constructed by adopting a theoretical analytical model, and is solved based on a quasi-static iterative algorithm to obtain corresponding mechanical parameters;
the irregular structure model is a proxy model of the motion state and the drag viscous resistance of the irregular structure established by using an artificial neural network, or an analytic model of the motion state and the drag viscous resistance of the irregular structure established by using a data fitting method.
In one embodiment, the optimization target of the multi-target optimization model is any combination of at least two of the parameters of towing speed, towing cable length, towing depth, towing body suspension position, towing cable tension, towing body pitch angle, towing cable and towing body suspension position, and array cable and towing body suspension position.
As an embodiment, the regular elongated structure model comprises a towed cable model, an umbilical cable model, an acoustic or optical array cable model.
In the process of constructing the towing cable model, a quasi-static model is utilized to determine the towing depth, the relationship between the maximum tension of the towing cable and a design variable, and a mother ship is simplified into a moving mass point to provide position or speed constraint for the system; the towing body is simplified into acting force and moment acting on the tail end of the towing cable.
In the process of constructing the array cable model, the cable is regarded as a horizontally placed slender cylinder, and the drag viscous resistance of the cable is solved by using a numerical analysis method.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a method for optimizing an ocean towing system, namely, a mode of combining a proxy model and an analytical model is adopted, the optimization model of the system is simplified, and aiming at a complex structure in the towing system, the relation between an input variable and an output variable is efficiently expressed by means of a mathematical proxy model, so that the time for calculating the nonlinear hydrodynamic load of the complex structure is greatly shortened when the system is optimized and iterated; aiming at the towing cables with large sizes and regular shapes in the towing system, the invention provides an underwater cable quasi-static iterative algorithm, and the time for calculating the shapes of the towing cables is greatly shortened.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are included to illustrate an exemplary embodiment of the invention and not to limit the invention.
FIG. 1 is a schematic illustration of an ocean towing system according to an embodiment of the present invention;
FIG. 2 (a) is a node of an embodiment of the present invention;
fig. 2 (b) is a node and its corresponding centralized quality method unit according to an embodiment of the present invention;
FIG. 3 illustrates the towed body force and its location of application of an embodiment of the present invention;
FIG. 4 is a node of an embodiment of the present inventionnAnalyzing stress;
FIG. 5 is a quasi-static iterative algorithm of an embodiment of the present invention;
FIG. 6 is a comparison of ProteusDS and quasi-static iteration results for an embodiment of the present invention;
FIG. 7 is a pull agent model of an embodiment of the present invention;
FIG. 8 is a towed body force analysis of an embodiment of the present invention;
FIG. 9 shows the optimization results and pareto fronts for an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. 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 invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Example one
In the present embodiment, the following assumptions are made when the deep-towed system is optimally designed:
(1) When the towing system works, in order to ensure the detection quality, the towing speed should be as stable as possible. The embodiment only considers the optimization problem when the system moves at a constant speed. The hydrodynamic load of each part of the system is only drag viscous resistance, and the additional mass inertia force caused by acceleration is ignored.
(2) The towing system only carries out operation when the sea state is stable, and the towing speed of the system is the relative movement speed of the system and the sea water.
In order to realize the optimal selection of the towing speed and the length of the towing cable, the embodiment establishes a target function of the towing speed and the length of the towing cable on the basis of the towing system model; and (4) taking the dragging depth, the tension of the dragging cable, the hanging position of the dragging body and the like as a multi-objective optimization model of constraint conditions.
The embodiment provides a multi-objective optimization method for an ocean towing system, which specifically comprises the following steps:
step 1: obtaining relevant parameters of towing system
And 2, step: based on the multi-objective optimization model of the marine towing system and the related parameters of the towing system, all the objective parameter optimization solutions of the marine towing system are obtained so as to guide the marine towing system to complete marine tasks.
Wherein the towing system model comprises a regular elongated structure model and an irregular structure model;
the regular elongated structure model is constructed by adopting a theoretical analytical model, and is solved based on a quasi-static iterative algorithm to obtain corresponding mechanical parameters; the irregular structure model is a proxy model of the motion state and the drag viscous resistance of the irregular structure established by using an artificial neural network, or an analytic model of the motion state and the drag viscous resistance of the irregular structure established by using a data fitting method.
It should be noted that, those skilled in the art can select the objective function and the corresponding constraint condition according to the actual requirement, among the parameters including but not limited to the towing speed, the length of the towing cable, the towing depth, the suspension position of the towing body, the tension of the towing cable, the pitch angle of the towing body, the suspension point position of the towing cable and the towing body, and the suspension position of the array cable and the towing body.
Next, taking the optimized target variables of the multi-target optimization model as the towing speed, the length of the towing cable and the pitch angle of the towed body; the specific implementation process of the embodiment is detailed by taking the drag cable length as minimum and the drag speed as maximum as an objective function, and taking the constraints of the drag speed, the drag cable length, the drag depth, the trailer suspension position, the drag cable tension and the pitch angle of the trailer as constraints:
in this embodiment, a concentrated mass method is used to construct a model for a regular structure, and a quasi-static iterative algorithm is used to solve to obtain corresponding mechanical parameters.
It is understood herein that the finite difference method or the finite element method may also be used to model the regular structure, and those skilled in the art may specifically select the method according to the actual situation, and the details are not described herein.
In particular, the regular elongated structural model includes, but is not limited to, a trailing cable (optical-electrical composite cable) model, an umbilical cable model, an acoustic or optical array cable model
In the process of constructing the towing cable model, as shown in fig. 2 (a) and 2 (b), the relationship between the maximum tension of the towing cable and the design variable is determined by using a lumped mass method and a Morrison formula, and the mother ship is simplified into mass points moving at the towing speed; the tow body is simplified to a force acting on the trailing end of the tow cable.
In the process of constructing the array cable model, the array cable is regarded as a slender cylinder, and the dragging viscous resistance of the array cable is solved by utilizing a Morrison formula.
In the specific implementation process, the irregular structure comprises a towed body and a conical stabilizing device, an artificial neural network is used for establishing a proxy model of the motion state and the drag viscous resistance of the towed body, and a data fitting method is used for establishing an analytic model of the motion state and the drag viscous resistance of the conical stabilizing device; it is worth explaining that the artificial neural network can be used for establishing a resistance umbrella agent model, and a data fitting method is used for establishing a towed body analysis model. Since the modeling process is similar, the modeling process is illustrated here in only one case.
In general, a variable that has a large influence on the objective function and is easily adjusted is selected as a design variable. In this embodiment, as shown in fig. 1, the initial towing speed, the towing cable length and the towing body suspension point position are design variables. In fig. 1, the X-Y coordinate system is a global coordinate system, and the X-Y coordinate system is a towed body coordinate system. In the process of carrying out optimization calculation on the multi-objective optimization model, all vectors involved in the optimization calculation are calculated under the same coordinate system (X-Y coordinate system).
Under the assumptions (1) and (2), the multi-objective optimization model is shown in table 1.
TABLE 1 Multi-objective optimization mathematical model
Wherein the content of the first and second substances,
respectively the drag speed module length, the drag speed module length lower boundary and the drag speed module length upper boundary of the system,
respectively the trailing cable length, the trailing cable length lower boundary and the trailing cable length upper boundary,
is the absolute value of the abscissa of the connecting position in the trailer coordinate system (x-y coordinate system),
is the upper boundary thereof, and is,
respectively a pitching angle of the towed body, a pitching angle lower boundary and a pitching angle upper boundary of the towed body,
respectively a drag depth, a drag depth lower boundary and a drag depth upper boundary,
it is the maximum tension of the trailing cable,
is the allowable value of the tension of the towing cable.
The premise for the optimization model to be able to be solved is that all objective functions and constraint conditions can be calculated from the design variables. Therefore, each part in the system needs to be subjected to mechanical modeling, and solving the hydrodynamic load of the underwater structure is a key link for the mechanical modeling. There are generally two methods of solving for hydrodynamic loads. One method is to solve the hydrodynamic load of the elongated structure according to a semi-empirical Morrison formula, and has the advantages that the calculation amount is small, but the method is only suitable for elongated cylindrical structures and cannot be used for calculating the hydrodynamic load of irregular structures; and the other method is to calculate the hydrodynamic load by solving a discrete NaviStokes equation according to a computational fluid dynamics method, and compared with a semi-empirical formula method, the method has the advantages that the calculation amount is large, and the hydrodynamic load of any structure can be calculated.
The method of modeling a regular elongated structure in the system is described next. The regular elongated structure in the system comprises: trailing cables (photoelectric composite cables), array cables. Since they are all elongated structures, their hydrodynamic loads can be solved using the Morrison formula.
The lumped mass method is an effective method for modeling the mechanics of the cable-like structure. When modeling the mechanics of the towing cable, determining the towing depth by using a centralized mass method and a Morrison formula
Maximum tension of towing cable
Relation to design variables. The mother ship being reduced to towing speed
A moving particle; the tow body is simplified to a force acting on the trailing end of the tow cable.
As shown in fig. 2 (a) and 2 (b), the trailing cable is divided into segments according to the lumped mass methodnIndividual particle andn-1 segment unit, elastic force exists between mass points.
Under a global coordinate system (X-Y coordinate system):
the inertial force and drag viscous resistance acting on the unit are distributed to two nodes adjacent to the unit, and the relationship is shown as formula 1,
wherein, the first and the second end of the pipe are connected with each other,
is a nodeiThe mass of (a) is greater than (b),
is a unitiThe mass of (a) of (b),
is a nodeiThe weight of the (c) is greater than the weight of the (c),
is a unitiThe force of gravity in the water is,
is acting on a nodeiThe drag viscous drag in the normal direction is,
is acting on the unitiThe drag viscous drag in the normal direction is,
is acting on the nodeiThe drag viscous resistance in the tangential direction is,
is acting on the unitiDrag viscous drag in the tangential direction.
As shown in fig. 3, the influence of the towing body on the towing cable is simplified into the interaction force therebetween
。
Node pointnThe force analysis of (2) is shown in fig. 4. To facilitate the solution of the quasi-static iterative algorithm, the method is to
Decomposed into forces in the horizontal direction
And force in the vertical direction
To noden And (6) performing stress analysis.
Wherein, the first and the second end of the pipe are connected with each other,
is a unitn-1 internal tension.
In equation (2), the viscous drag resistance can be calculated by the morrison equation. The equation of the balance between the tangential direction and the normal direction in the formula (2) is listed, the Morrison formula is combined and properly arranged, and the node is obtainednIs given by the equation (3)
Wherein the content of the first and second substances,
is a unitn-1 of the angle of rotation of the rotating shaft,
and
are respectively
The force components in the horizontal and vertical directions,
are respectivelyThe tangential and normal drag viscous drag coefficients,
is the density of the seawater, and is,
is the wet density of the towing cable in the water,
is the trailing cable diameter.
In the formula (3), when the drag speed is high
Length of trailing cable
Interaction force
When the parameters associated with the trailing cable are known,
can be calculated by the first equation. Wherein the content of the first and second substances,
may be calculated by the pull agent model described later. Furthermore, the cell tension
Can be calculated from the second equation in equation (3).
For other nodesiIts equilibrium equation is similar to node n.
Wherein, the first and the second end of the pipe are connected with each other,
and
are respectively
Force components in the horizontal and vertical directions.
From formula (3) and formula (4), all
And
all can be composed of
，
And
and (6) obtaining. Drag deeply
And maximum tension of trailing cable
Can be calculated from the equation (5),
wherein the content of the first and second substances,
is a unitiThe amount of axial elongation of (a) is,E is the Young's modulus.
FIG. 5 shows
，
And
and
，
the relationship (2) of (c).
In the above discussion of the above-mentioned embodiments,
all satisfy formula (3). However, there are two problems to be solved. (1)
Number of solutions (2) if in the equation
How the solution is greater than one should be determined
. Therefore, it is necessary to discuss the distribution of the solution of equation (3).
It is assumed that,
the first equation in equation (3) can be normalized,
in order to ensure that the water-soluble organic acid,
then there is a change in the number of,
according to the zero theorem, equation (7) must have roots in the domain,
the existence of the root of equation (7) has been demonstrated, and the uniqueness of the root is discussed next.
To pair
The derivation is carried out, the monotonicity of the signal is judged,
it monotonically increases within the domain of definition, and equation (3) has and only has one relationship to
The root of (2). Similarly, equation (4) also has only one relationship to
The proof process is similar.
In order to verify the accuracy of the quasi-static iterative algorithm, the same parameters of the towing cable are given, the simulation software ProteusDS is used for calculating the stable state of the towing cable and comparing the stable state with the result of the quasi-static iterative algorithm, the comparison result is shown in FIG. 6, the difference between the two nodes is within 0.5m, and the quasi-static iterative algorithm has better accuracy.
TABLE 2 towing cable parameters and towing speed
Due to the presence of the stabilizing device, the array cable remains straight most of the time. Therefore, the array cable can be regarded as a slender cylinder, and the dragging viscous resistance of the array cable can be solved by utilizing the Morrison formula.
Wherein the content of the first and second substances,
in order to be the diameter of the array cable,
is the tangential drag viscous drag coefficient of the array cable,
is the length of the array cable and,
is the drag viscous drag experienced by the array cable.
In the towing system, the irregular structure mainly has a towed body 3 and a stabilizer 5. Specifically, this embodiment takes a towed body and a conical stabilizing device in a certain system as an example, and describes a modeling method of an irregular structure in a towed system. Due to the complex structure of the two, the hydrodynamic load is generally calculated by a computational fluid dynamics method, however, the acquisition of the hydrodynamic load of the structure under a single working condition by the computational fluid dynamics method consumes a large amount of calculation resources, and the iterative calculation of the hydrodynamic load under thousands of working conditions is required for the optimization design. Aiming at irregular structures, both the artificial neural network and the data fitting method are suitable for establishing a mapping relation between the motion state and the drag viscous resistance; the irregular structure modeling process is described here only by taking a towed-body agent model and a cone-shaped stabilizing device analytic model as examples.
The pull agent model building process is described next.
As shown in FIG. 6, for calculation
，
Need only know
And
. Therefore, it is necessary to
And (6) analyzing. The drag body is subjected to viscous drag force
The important components of (1) introduce the towed body modeling process. The method comprises the steps of establishing a database by using simulation software RecurDyn-particles, and then establishing a towed body agent model by combining an artificial neural network to reflect the relationship between the motion state of a towed body and viscous towing resistance of the towed body. As shown in fig. 7, the proxy model takes the drag speed and the pitch angle as input variables and the drag resistance as output variables.
Next, the stabilizer model building process will be described.
And obtaining an analytical model of the conical stabilizing device by using a fitting method. It is assumed that the conical stabilizer experiences drag viscous drag as a function of speed as shown in equation (12).
Wherein, the first and the second end of the pipe are connected with each other,
is the drag viscous drag coefficient and is,
is the major diameter of the conical stabilizing device,
is the drag viscous drag experienced by the conical stabilizer.
In order to determine the drag viscous resistance coefficient, drag viscous resistances corresponding to different speeds are obtained by the combined simulation method. Then obtaining drag viscous resistance coefficient by data fitting
Then, in optimizing the iterative calculation, the drag viscous resistance experienced by the stabilizer at other speeds can be calculated using equation (12).
In the light of the above, the first embodiment,
and
can be prepared from
And
it is found that because the density of the array cable and the stabilizing device is close to that of water, the gravity and the buoyancy force applied to the array cable and the stabilizing device are not considered, and then
This can be obtained from formula (13).
Wherein the content of the first and second substances,
is the viscous drag resistance suffered by the towed body and can be controlled by a towed body proxy model
And
and (5) calculating.
To make it possible to
And
can be calculated from the design variables, it is necessary to discuss
The process of (1).
Listing the balance equation of force and moment of the towed body,
wherein the content of the first and second substances,
is the dragging force of the dragging cable to the dragging body,
and with
Is a pair of mutual acting forces which are,q is that
With respect to the moment arm of the origin,
is the net weight of the towed body in water.
In FIG. 8, all force vectors are derived from the towing speed and the towing pitch angle based on the relationship of the global coordinate system (X-Y coordinate system) and the towed body coordinate system (X-Y coordinate system), and once the force vectors are determined, the towed body suspension point position can be determined by combining the torque balance equation with the towed body geometry. Thus, the suspension point position is ultimately only affected by the tow speed and the tow pitch angle. Position of suspension point of towed body
The relationship is shown in formula (15).
In this way,
and design variables
The relationship of (c) has been derived. However, in the known design variables
When formula (15) relates to
Implicit nonlinear equation of (2). Numerical iteration is an efficient way to solve nonlinear implicit equations. However, there are at least two difficulties in applying numerical iteration methods in the present optimization problem. (1)
The initial value is difficult to determine. (2) Due to the characteristics of the proxy model, the derivative information of equation (15) is difficult to calculate, thereby making the numerical iteration method inefficient. In summary, in
For designing variables, the equation (15) is solved to calculate
Is difficult and the current optimization problem is not solvable. However, if the towed body is pitched
As one of design variablesExplicit calculation by equation (15)
It is relatively easy. Thus, the modified design variable is the towing speed
Length of towing cable
And a pitch angle
. The modified optimization model is shown in table 3.
TABLE 3 New model with modified design variables
In the new optimization model, the process of the optimization,
and
can be obtained by the reaction of formula (5)
And
the calculation results in that,
can be varied by design according to equation (11)
And
it is obtained that,
can be obtained by the reaction of the formula (15)
And
and (6) obtaining. Each variable in the constraint and the objective function can be designed by the variable
、
、
And obtaining the solvable optimization model.
And after all variables of the optimization model can be calculated, selecting a multi-objective optimization algorithm to solve the multi-objective optimization model. For example: NSGA-2 is widely used in optimization design in various fields due to its computational efficiency and robustness. Therefore, in the case, the NSGA-2 solving method is selected, the parameters of the towing cable are selected, and the towing speed is finally obtained by combining the system mechanical model
And trailing cable length
The pareto front as shown in fig. 9.
It should be noted that, those skilled in the art may specifically select a corresponding algorithm to solve the multi-objective optimization model according to the actual situation, and details thereof are not described here.
Example two
The embodiment provides a multi-objective optimization device for a marine towing system, which comprises:
the parameter acquisition module is used for acquiring related parameters of the towing system;
the target optimization module is used for obtaining all target parameter optimization solutions of the marine towing system based on the multi-target optimization model of the marine towing system and relevant parameters of the towing system so as to guide the marine towing system to complete marine tasks;
wherein the multi-objective optimization model is constructed based on a drag system model; the towing system model comprises a regular elongated structure model and an irregular structure model;
the regular elongated structure model is constructed by adopting a theoretical analytical model, and is solved based on a quasi-static iterative algorithm to obtain corresponding mechanical parameters;
the irregular structure model is a proxy model of the motion state and the drag viscous resistance of the irregular structure established by using an artificial neural network, or is an analytic model of the motion state and the drag viscous resistance of the irregular structure established by using a data fitting method.
The optimization target of the multi-target optimization model is any combination of at least two parameters of the parameters of towing speed, towing cable length, towing depth, towing body suspension position, towing cable tension, towing body pitching angle, towing cable and towing body suspension position and array cable and towing body suspension position.
The regular elongated structure model comprises a towed cable model, an umbilical cable model, an acoustic or optical array cable model.
It should be noted that, each module in the present embodiment corresponds to each step in the first embodiment one to one, and the specific implementation process thereof is the same, and is not described in detail here.
EXAMPLE III
The present embodiment provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the method for multi-objective optimization of a marine towing system as described above.
Example four
The embodiment provides an electronic device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the multi-objective optimization method for marine towing system as described above.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A multi-objective optimization method for an ocean towing system is characterized by comprising the following steps:
acquiring relevant parameters of a towing system;
obtaining all target parameter optimization solutions of the marine towing system based on the multi-target optimization model of the marine towing system and the related parameters of the towing system so as to guide the marine towing system to complete a marine task;
wherein the multi-objective optimization model is constructed based on a drag system model; the towing system model comprises a regular elongated structure model and an irregular structure model;
the regular elongated structure model is constructed by adopting a theoretical analytical model, and is solved based on a quasi-static iterative algorithm to obtain corresponding mechanical parameters;
the irregular structure model is a proxy model of the motion state and the drag viscous resistance of an irregular structure established by using an artificial neural network, or an analytic model of the motion state and the drag viscous resistance of the irregular structure established by using a data fitting method;
the optimization target of the multi-target optimization model is any combination of at least two parameters of the parameters of towing speed, length of a towing cable, towing depth, towing body suspension position, towing cable tension, pitching angle of a towing body, towing cable and towing body suspension position and array cable and towing body suspension position;
and (3) constructing a model for the regular structure by adopting a centralized mass method, and solving by adopting a quasi-static iterative algorithm to obtain corresponding mechanical parameters.
2. The marine towing system multi-objective optimization method of claim 1, wherein the regular elongated structural model comprises a towed cable model, an umbilical model, an acoustic or optical array cable model.
3. The multi-objective optimization method for the marine towing system according to claim 2, wherein in the process of constructing the towing cable model, the relation between the towing depth and the maximum tension of the towing cable and the design variable is determined by using a quasi-static model, and the mother ship is simplified into a moving particle to provide position or speed constraint for the system; the towing body is simplified into acting force and moment acting on the tail end of the towing cable.
4. The marine drag system multi-objective optimization method of claim 2, wherein in the process of constructing the array cable model, the cable is regarded as a horizontally placed elongated cylinder, and drag viscous resistance of the cable is solved by using a numerical analysis method.
5. A multi-objective optimization device for a marine towing system is characterized by comprising:
the parameter acquisition module is used for acquiring related parameters of the towing system;
the target optimization module is used for obtaining all target parameter optimization solutions of the marine towing system based on the multi-target optimization model of the marine towing system and relevant parameters of the towing system so as to guide the marine towing system to complete marine tasks;
wherein the multi-objective optimization model is constructed based on a drag system model; the towing system model comprises a regular elongated structure model and an irregular structure model;
the regular elongated structure model is constructed by adopting a theoretical analytical model, and corresponding mechanical parameters are obtained by solving based on a quasi-static iterative algorithm;
the irregular structure model is a proxy model of the motion state and the drag viscous resistance of an irregular structure established by using an artificial neural network, or an analytic model of the motion state and the drag viscous resistance of the irregular structure established by using a data fitting method;
the optimization target of the multi-target optimization model is any combination of at least two parameters of the parameters of towing speed, length of a towing cable, towing depth, towing body suspension position, towing cable tension, pitching angle of a towing body, towing cable and towing body suspension position and array cable and towing body suspension position;
and (3) constructing a model for the regular structure by adopting a centralized mass method, and solving by adopting a quasi-static iterative algorithm to obtain corresponding mechanical parameters.
6. The marine towed system multi-objective optimization device of claim 5, wherein the regular elongated structural model includes a towed cable model, an umbilical model, an acoustic or optical array cable model.
7. The marine towing system multi-objective optimization device of claim 6, wherein in the process of constructing the towing cable model, the relationship between the towing depth and the maximum tension of the towing cable and the design variable is determined by using a quasi-static model, and the mother ship is simplified into a moving particle to provide position or speed constraint for the system; the tow body is simplified to the forces and moments acting on the trailing end of the tow cable.
8. The marine drag system multi-objective optimization device of claim 6, wherein in the process of constructing the array cable model, the cable is regarded as a horizontally placed elongated cylinder, and drag viscous resistance of the cable is solved by using a numerical analysis method.
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