A method for overall cabin layout design of a ship considering RMS requirements

Abstract

The application relates to the technical field of ship design, in particular to a ship overall cabin layout design method considering RMS requirements. The method comprises the following steps: acquiring RMS design criteria of an overall cabin layout and design indexes of the overall cabin layout; describing the shapes of cabins and equipment, and respectively establishing design index description models according to the described cabins and equipment; acquiring constraint conditions of the overall layout and describing the constraint conditions; establishing a cabin layout optimization model considering the RMS requirements according to the described constraint conditions and the design index description models; selecting an intelligent optimization solving algorithm to solve the cabin layout optimization model, and obtaining a cabin optimization layout design scheme. In the cabin layout process of the overall design of the ship, the reliability, maintainability and supportability requirements are integrated into the overall design, the general quality characteristics such as reliability, maintainability and supportability are coordinated, integrated and synchronous optimization design is carried out, and the design efficiency and quality are improved.

Description

Technical Field

[0001] This application relates to the technical field of ship design, and in particular to a method for designing the overall compartment layout of a ship that takes into account RMS requirements. Background Technology

[0002] The layout design of ship compartments and equipment mainly involves determining the location of various equipment within the limited space of the compartments, and is an important part of the overall ship design. During the overall design of ship compartments, a large number of complex equipment must be arranged within the limited space, meeting various tactical and technical requirements while also satisfying general quality characteristics and the living support needs of the crew as much as possible. The overall layout work is extremely demanding.

[0003] In previous models of product compartment layout design, to comprehensively consider general quality characteristics, the typical approach was to design the compartment layout based on experience, followed by reliability, maintainability, and supportability analysis and verification, and iterative design improvements. This method achieved significant results. However, due to numerous constraints in the overall layout design of ship compartments, repeated iterative modifications involve a wide range of issues and are costly, resulting in low layout design efficiency and a low level of design quality. Some compartment layout designs become difficult to coordinate and modify in the later stages of development. To meet the basic combat technical performance requirements of the equipment, it is necessary to sacrifice or ignore general quality characteristics such as maintainability, reliability, and supportability (RMS), leading to a heavy burden on equipment maintenance and support, and even making maintenance and support difficult to complete. On the other hand, in the design process of general quality characteristics such as maintainability, reliability, and supportability, there are many work items, and the lack of coordination and balance between the various characteristic design schemes easily leads to problems such as neglecting one aspect for another, resulting in problems like "under-design" of individual characteristics. Therefore, in the compartment layout process of the overall ship design, it is necessary to integrate requirements such as reliability, maintainability, and supportability into the overall design, coordinate general quality characteristics such as reliability, maintainability, and supportability, and carry out integrated and synchronous optimization design to improve design efficiency and quality. However, current compartment layout optimization design mainly considers the functional position constraints and geometric constraints of each piece of equipment to optimize attributes such as function and stability. It lacks integrated modeling and analysis considerations for reliability, maintainability and supportability requirements, and there is no suitable method to integrate reliability, maintainability and supportability design into the overall design of ship compartments. This greatly affects the efficiency and effectiveness of the general quality characteristic design work of compartment layout. There is an urgent need for a method for simultaneous design of reliability, maintainability and supportability of the overall ship compartment layout. Summary of the Invention

[0004] Therefore, it is necessary to provide a ship's overall compartment layout design method that takes into account RMS requirements to address the aforementioned technical problems.

[0005] A method for designing the overall compartment layout of a ship considering RMS requirements, the method comprising:

[0006] Obtain the RMS design criteria for the overall cabin layout, the design parameters for the overall cabin layout, and the correlation between the RMS design criteria and the design parameters;

[0007] The external shape of the compartments and equipment is described, and design indicator description models are established for each of the described indicators based on the described compartments and equipment.

[0008] Obtain and describe the constraints of the overall layout, and establish a cabin layout optimization model that considers RMS requirements based on the described constraints and the design index description model.

[0009] An intelligent optimization algorithm is selected to solve the cabin layout optimization model, and the cabin layout optimization design scheme is obtained.

[0010] Solving the cabin layout optimization model includes: extending the application of particle swarm optimization (PSO) for intelligent optimization, using the position and orientation of the equipment as independent variables, applying PSO to optimize and solve multiple design index description models multiple times, and using the equipment position and orientation solution results as part of the initial solution of the RMS layout optimization problem search space; the system initializes and randomly generates a set number of particles as part of the initial solution of the RMS layout optimization problem search space; each particle searches within the solution space by following the optimal particle at a set speed to obtain the optimal solution for the cabin layout design.

[0011] The above method integrates requirements such as reliability, maintainability, and supportability into the overall design of ship compartment layout, coordinates common quality characteristics such as reliability, maintainability, and supportability, and carries out integrated synchronous layout optimization design to improve design efficiency and quality. At the same time, by combining single-objective optimization solution with multi-objective optimization solution, it ensures that the optimization search has good globality and improves the effectiveness of compartment equipment layout optimization solution. Attached Figure Description

[0012] Figure 1 This is an application scenario diagram of a ship's overall compartment layout design method that takes into account RMS requirements in one embodiment.

[0013] Figure 2 This illustrates the relationship between RMS requirements and layout design metrics in one embodiment.

[0014] Figure 3 This is a schematic diagram of the solution process for the cabin layout optimization model in one embodiment;

[0015] Figure 4 This is an empirical layout diagram of the cabin equipment in one embodiment;

[0016] Figure 5 In one embodiment, an optimization algorithm is used to solve for the convergence curve;

[0017] Figure 6 This is an optimized layout diagram of cabin equipment considering RMS requirements in one embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] The ship's overall compartment layout design method considering RMS requirements provided in this application includes the following steps:

[0020] Step 1: Obtain the RMS design criteria and design indicators for the overall cabin layout, as well as the correlation between the RMS design criteria and design indicators. In this way, the layout design of the present invention implements the general quality characteristics requirements such as maintainability, reliability, and supportability into the specific design through the above criteria, which can coordinate the general quality characteristics such as reliability, maintainability, and supportability and avoid the problem of neglecting one aspect for another.

[0021] Step 2: Describe the shape of the cabin and equipment, and establish multiple design indicator description models for multiple indicators based on the described cabin and equipment, the RMS design criteria, design indicators and their relationships.

[0022] Step 3: Obtain and describe the constraints of the overall layout, and establish a cabin layout optimization model that considers RMS requirements based on the described constraints and the design index description model.

[0023] Step 4: Select an intelligent optimization algorithm to solve the cabin layout optimization model and obtain the cabin optimized layout design scheme;

[0024] Solving the cabin layout optimization model includes: extending the application of particle swarm optimization (PSO) for intelligent optimization, using the position and orientation of the equipment as independent variables, applying PSO to optimize and solve multiple design index description models multiple times, and using the equipment position and orientation solution results as part of the initial solution of the RMS layout optimization problem search space; the system initializes and randomly generates a set number of particles as part of the initial solution of the RMS layout optimization problem search space; each particle searches within the solution space by following the optimal particle at a set speed to obtain the optimal solution for the cabin layout design.

[0025] In the above method, during the process of compartment layout in the overall design of the ship, requirements such as reliability, maintainability, and supportability are integrated into the overall design, and general quality characteristics such as reliability, maintainability, and supportability are coordinated to carry out integrated and synchronous layout optimization design, thereby improving design efficiency and quality. At the same time, by combining single-objective optimization solution with multi-objective optimization solution, the optimization search is guaranteed to have good globality, thereby improving the effectiveness of compartment equipment layout optimization solution.

[0026] The RMS design criteria for obtaining the overall cabin layout, the design parameters for the overall cabin layout, and the correlation between the RMS design criteria and the design parameters include:

[0027] Quantitative RMS indicators proposed for a system or product cannot directly guide and constrain system design. Instead, they are implemented in the specific system design through a series of qualitative requirements and guidelines. Under the premise of meeting basic functional requirements, general RMS design guidelines for the overall layout of ship compartments are formulated, including:

[0028] (1) Based on the inherent reliability of the equipment, the layout design should ensure that the equipment can work reliably and continuously. For example, there may be interference distance requirements between equipment, functional proximity requirements between equipment, or orientation requirements.

[0029] (2) Basic requirements for pipeline and cable layout: pipeline and cable length should be as short as possible, and the number of bends and pipeline accessories should be minimized to ensure reliability while reducing maintenance accessories.

[0030] (3) The layout of the compartments should ensure sufficient space for maintenance and testing, and reserve the space necessary for personnel activities and equipment operation and maintenance, so as to ensure the stability of the operation of the compartment equipment and the convenience of operation and maintenance.

[0031] (4) The layout of the compartments should reserve suitable maintenance, testing and support passages to ensure that crew members can pass through easily and without obstacles during patrol inspections, operation and spare parts handling.

[0032] (5) The layout should meet the requirements of the maintenance process and equipment usage process. The equipment layout should ensure that the maintenance process and equipment usage process are smooth, the material handling is convenient, and the occurrence of cross-flow and return of logistics should be reduced or avoided.

[0033] (6) The layout of the cabin equipment should fully consider the cabin openings and the hoisting of large equipment to ensure that the engineering involved in the equipment leaving the cabin and hoisting is minimized.

[0034] The general quality characteristics of the compartment system, such as maintainability, reliability, and supportability, are mainly implemented in the specific design through the above principles. Therefore, in the overall layout design of the compartment, layout design indicators are established based on these principles and by fully considering the general quality characteristics, so as to achieve integrated analysis and design of reliability, maintainability, and supportability requirements.

[0035] According to the design guidelines for cabin equipment, the main design parameters for ship cabin layout include:

[0036] (1) Equipment operating space: Sufficient operating space, maintenance area and passage should be available for the daily maintenance and basic-level repair of each piece of equipment in the compartment. Try to avoid the need to disassemble and move other equipment when repairing one piece of equipment. In particular, the operating space of equipment with low reliability that needs to be frequently inspected and tested should be given special consideration.

[0037] (2) Passage width: The passage width of the ship's compartment layout not only affects the flow of personnel for operation and maintenance, but also the transfer of support resources. It should meet the operation and maintenance requirements as much as possible.

[0038] (3) Overhaul hoisting capacity: The layout and openings of the compartments and equipment should ensure that the ship has good openness, which facilitates the hoisting of equipment overhaul and reduces hoisting distance and hoisting cost.

[0039] (4) Reliable and safe distance: The distance between certain compartment equipment should follow certain principles and requirements to ensure reliable and safe operation, taking into account pipeline and cable connections, equipment interference distance, etc.

[0040] (5) Ease of operation: The layout of the cabin equipment should ensure that the crew can easily inspect, use the equipment and store and move spare parts, and reduce the distance for maintenance and support.

[0041] The RMS layout design objectives for compartments comprehensively consider design principles such as reliability, maintainability, and supportability requirements for compartment equipment layout. The relationship between compartment layout design indicators and RMS requirements is as follows: Figure 2 As shown, the equipment operating space index is mainly related to the reliability, maintainability, and supportability requirements of the cabin equipment; the passage width index is mainly related to the maintainability and supportability requirements; the overhaul hoisting volume index is mainly related to the maintainability and supportability requirements; the reliable safety distance index is mainly related to the reliability requirements of the cabin equipment; and the operational convenience index is mainly related to the maintainability and supportability requirements of the cabin equipment.

[0042] The description of the shape of the compartments and equipment includes:

[0043] To simplify the description of modeling compartments and equipment, based on the shape characteristics of ship compartments and equipment, each piece of equipment is approximated as an envelope of cuboids and cylinders, so that the engine room equipment is represented by rectangular and circular primitives on the compartment deck plane; to facilitate the description of the equipment layout model, a Cartesian coordinate system xoy is defined, and let the RMS layout scheme X of the compartment contain n+m pieces of equipment to be laid out, where the n pieces of equipment are simplified into n rectangular primitives A. i , i∈I n ={1,2,L,n}, m devices are simplified into m circular primitives A i , i∈I m ={n,L,n+m}; if the number of design variables for the layout scheme is 3n+2m, then the layout scheme can be described as follows:

[0044] X = {x1, y1, o1, L, x n ,y n ,o n ,x n+1 ,y n+1 ,L,x n+m ,y n+m}∈R 3n+2m

[0045] Where (x) i ,y i ) represents primitive A i The coordinates of the centroid; o i It determines the rectangular primitive A i A binary variable representing the orientation of the longer side, if o i =1, then the longer side of the rectangle is parallel to the x-axis. If o i If = 0, then the longer side of the rectangle is parallel to the y-axis.

[0046] The step of establishing design indicator description models for each of the described cabins and equipment includes the following: Each design indicator description model is as follows:

[0047] (1) Equipment operating space index

[0048] Sufficient space must be reserved on the side of the equipment's maintenance and operation area to facilitate its operation and maintenance. The reserved operating space for equipment A is measured by the spatial distance between the equipment's operation and maintenance area and surrounding equipment. i In device A j Operational space index ds under influence ij For A j Spatial impact on device A i The probability of operation and maintenance is determined using equipment A. i Maintenance operation area side and surrounding equipment A j Spatial distance between dc ijThe piecewise linear function representation:

[0049]

[0050] Among them, D i,min For device A i The minimum operating space distance threshold required on one side of the maintenance operation area, if dc ij Less than D i,min Then, the surrounding interfering equipment A must be removed. j Only then can equipment A be completed. i Maintenance operations; D i,max For device A i Maintain a satisfactory operating space distance threshold on one side of the maintenance operation area, if dc ij Greater than D i,max Then peripheral device A j Regarding the operating space of device A i Maintenance operations were not interfered with; if DC ij In D i,min and D i,max Between, then peripheral device A j Spatially, it may affect device A i This will have an impact on maintenance.

[0051] Considering the maintenance frequency of each piece of equipment, the overall operating space index of the cabin equipment is described as follows:

[0052]

[0053] A smaller f1(X) indicates a more reasonable allocation of space for cabin equipment maintenance and operation. In the formula, ds i For device A i Operating space index in cabin layout environment; ds i0 For device A i Operating space index under the influence of compartment bulkheads; μ fi For device A i Factors affecting the frequency of maintenance operations on cabin operating space indicators. fi Represented as:

[0054] In the formula f i For device A i Frequency of basic-level maintenance operations.

[0055] (2) Channel width index

[0056] The width of the channel should be maximized while meeting the minimum channel width requirement. The single channel width index is measured using a piecewise function relating the actual channel width to the minimum channel width requirement, expressed as:

[0057]

[0058] Among them, b i PD represents the actual width of the i-th channel. i,min This represents the minimum width requirement for the i-th passage. When the passage width is the same as the minimum width requirement, the passage is basically passable, and the passage width index is 1. When the difference between the passage width and the minimum width requirement is greater than or equal to 60% of the minimum width requirement, it has no impact on personnel flow, material transfer, and equipment passage, and the passage width index is 0.

[0059] Considering the importance of each passageway, the overall passageway width of the cabin is described as follows:

[0060] f2(X)=∑w i *pb i

[0061] A smaller f2(X) indicates a more reasonable allocation of aisle width in the cabin layout, where w... i pb represents the importance weight of the i-th channel. i This represents the channel width index of the i-th channel.

[0062] (3) Overhaul hoisting volume index

[0063] Referring to the mathematical model of logistics costs in the production workshop, the definition of the overhaul hoisting volume index for cabin equipment is as follows:

[0064]

[0065] A smaller f3(X) indicates lower costs for overhauling and hoisting of cabin equipment, where q is the total number of equipment requiring hoisting during overhaul; m k For hoisting equipment A k Quality; T k For device A k The lifting distance to the lifting port. (T) k The formula for calculation is:

[0066] T k =|x k -x d |+|y k -y d |,x d y d These are the location parameters for the hoisting opening.

[0067] (4) Reliable safety distance index

[0068] The reliable safety distance index is measured by the degree to which the distance between layout devices meets functional interdependence requirements, and it is expressed as:

[0069]

[0070] The smaller f4(X) is, the higher the degree to which the distance between devices meets the functional association requirements. In the formula, p is the number of layout devices with functional association requirements; w ij Equipment A to be laid i A j The importance weight of functional relationship requirements between them; ij Equipment A to be laid i A j The distance between them is a description parameter that meets the relevant requirements.

[0071] If device A i A j If there is a functional affinity or proximity requirement between them, then rd ij Described as:

[0072]

[0073] In the formula, om ij For device A i A j The required distance between the centers of mass; d ij For device A i A j The distance between the centers of mass.

[0074] If device A i A j If there is a functional relationship between them and the requirement is far away, then rd ij Described as:

[0075]

[0076] In the formula, OM ij For device A i A j The required distance between the centers of mass, d ij For device A i A j The distance between the centers of mass.

[0077] (5) Ease of operation index

[0078] The ease of operation index is measured by the personnel flow distance when operating, inspecting, and maintaining cabin equipment, and it is expressed as follows:

[0079]

[0080] A smaller f5(X) indicates that it is more convenient and faster for staff to operate and move between equipment in the compartments. In the formula, equipment 0 represents a hatch; f ijT represents the frequency of personnel movement from device i to device j. ij Let T be the flow distance from device i to device j. ij The formula for calculation is:

[0081] T ij =|x i -x j |+|y i -y j |

[0082] The process of obtaining and describing the constraints of the overall layout, and establishing a cabin layout optimization model considering RMS requirements based on the described constraints and the design index description model, includes:

[0083] The constraints for obtaining the overall layout include non-interference constraints, compatibility constraints, and compartment layout domain constraints:

[0084] (1) Non-interference constraint

[0085] In the layout scheme of the cabin equipment, there must be no interference between the various elements. The non-interference constraint description of layout scheme X is as follows:

[0086]

[0087] (2) Adaptability constraint

[0088] Any part of the cabin equipment should be located inside the cabin, and the layout elements should not exceed the given layout space P, satisfying the tolerance constraint, described as follows:

[0089]

[0090] (3) Domain constraints

[0091] Domain constraints mainly refer to the specifications, common sense, and special requirements for the layout of compartment equipment. They manifest as the relationships and constraints on orientation and distance between layout elements, such as axis connection constraints, and can be denoted as:

[0092]

[0093] Then, based on the constraints and objectives of the overall cabin RMS layout, the layout design problem is transformed into a multi-constraint, multi-objective optimization problem, whose cabin layout optimization model is expressed as:

[0094]

[0095] The step of selecting an intelligent optimization algorithm to solve the cabin layout optimization model and obtaining the cabin layout optimization design scheme further includes:

[0096] First, the objectives and constraints in the cabin layout optimization model are processed. A linear weighted sum method is used to construct an evaluation function to transform the multi-objective problem into a single-objective problem. A penalty function is constructed to transform the constrained optimization problem into an unconstrained optimization problem. The fitness function of the cabin layout optimization scheme X is then expressed as:

[0097]

[0098] In the formula, λ i For the sub-objective f i The normalization factor of (X); w i For the sub-objective f i The weighting coefficient of (X); μ j As a penalty factor; φ j (X) represents the degree of constraint violation of constraint j by scheme X.

[0099] Because the above cabin layout optimization is characterized by high dimension, multi-peak, and non-convexity, making it difficult to solve, a particle swarm optimization (PSO) algorithm is extended for intelligent optimization. The PSO algorithm is extended to use the location and orientation of the equipment that can be placed in the cabin as independent variables. First, the PSO algorithm is applied to optimize the five cabin layout RMS indices f1(X), f2(X), f3(X), f4(X), and f5(X) multiple times. The particles obtained from the equipment location and orientation solutions are used as partial initial solutions to the RMS layout optimization problem search space. Simultaneously, the system initializes and randomly generates a set number of particles as partial initial solutions to ensure good globality in the layout optimization search. Based on this, each particle searches within the solution space at a set speed, following the optimal particle, and finally obtains the optimal RMS layout optimization solution, i.e., the cabin optimized layout design scheme. The specific algorithm flow is as follows: Figure 3 As shown.

[0100] This invention relates to a shipboard overall compartment layout design apparatus considering RMS requirements, the apparatus comprising:

[0101] The criteria and indicator acquisition module is used to acquire the RMS design criteria and design indicators of the overall cabin layout, as well as the correlation between the RMS design criteria and design indicators.

[0102] The design index description model establishment module is used to describe the shape of the cabin and equipment, and establish design index description models for multiple indicators based on the described cabin and equipment.

[0103] The cabin layout optimization model building module is used to obtain and describe the constraints of the overall layout, and to build a cabin layout optimization model that considers RMS requirements based on the described constraints and the design index description model.

[0104] The solution module is used to select an intelligent optimization algorithm to solve the cabin layout optimization model and obtain the cabin optimized layout design scheme. Solving the cabin layout optimization model includes: extending the application of particle swarm optimization algorithm for intelligent optimization, using the position and orientation of the equipment as independent variables, applying particle swarm optimization algorithm and performing multiple optimization solutions on multiple design index description models respectively, and using the particles from the equipment position and orientation solution as partial initial solutions of the RMS layout optimization problem search space; the system initializes and randomly generates particles of a set size as partial initial solutions of the RMS layout optimization problem search space; each particle searches within the solution space by following the optimal particle at a set speed, and finally obtains the optimal solution for RMS layout optimization.

[0105] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to perform the following steps:

[0106] Obtain the RMS design criteria for the overall cabin layout, the design parameters for the overall cabin layout, and the correlation between the RMS design criteria and the design parameters;

[0107] The external shape of the compartments and equipment is described, and design indicator description models are established for each of the described indicators based on the described compartments and equipment.

[0108] Obtain and describe the constraints of the overall layout, and establish a cabin layout optimization model that considers RMS requirements based on the described constraints and the design index description model.

[0109] An intelligent optimization algorithm is selected to solve the cabin layout optimization model, and the cabin layout optimization design scheme is obtained.

[0110] Solving the cabin layout optimization model includes: extending the application of particle swarm optimization (PSO) for intelligent optimization, using the position and orientation of the equipment as independent variables, applying PSO to optimize and solve multiple design index description models multiple times, and using the equipment position and orientation solution results as part of the initial solution of the RMS layout optimization problem search space; the system initializes and randomly generates a set number of particles as part of the initial solution of the RMS layout optimization problem search space; each particle searches within the solution space by following the optimal particle at a set speed to obtain the optimal solution for the cabin layout design.

[0111] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0112] Obtain the RMS design criteria for the overall cabin layout, the design parameters for the overall cabin layout, and the correlation between the RMS design criteria and the design parameters;

[0113] The external shape of the compartments and equipment is described, and design indicator description models are established for each of the described indicators based on the described compartments and equipment.

[0114] Obtain and describe the constraints of the overall layout, and establish a cabin layout optimization model that considers RMS requirements based on the described constraints and the design index description model.

[0115] An intelligent optimization algorithm is selected to solve the cabin layout optimization model, and the cabin layout optimization design scheme is obtained.

[0116] Solving the cabin layout optimization model includes: extending the application of particle swarm optimization (PSO) for intelligent optimization, using the position and orientation of the equipment as independent variables, applying PSO to optimize and solve multiple design index description models multiple times, and using the equipment position and orientation solution results as part of the initial solution of the RMS layout optimization problem search space; the system initializes and randomly generates a set number of particles as part of the initial solution of the RMS layout optimization problem search space; each particle searches within the solution space by following the optimal particle at a set speed to obtain the optimal solution for the cabin layout design.

[0117] The present invention also provides a specific embodiment:

[0118] Step 1: Considering RMS requirements, select the engine room layout of a certain ship for design. The rectangular engine room houses equipment such as diesel main engines, gearboxes, diesel generator sets, fire pumps, sewage tanks, and boilers. First, determine the detailed guidelines and requirements for the RMS design of the compartment layout, and select equipment operating space, passageway width, overhaul hoisting capacity, reliable safety distance, and operational convenience as the optimization design indicators for the engine room layout.

[0119] Step two: First, simplify the description of the compartments and equipment, and model the layout scheme of the ship's engine room equipment. The layout space, i.e., the rectangular compartment size, is: D = 4m, H = 4m. There are 12 pieces of equipment to be laid out, of which 8 are simplified into rectangular elements and 4 into circular elements. The number of design variables for this layout scheme is 32, which are the center coordinates of each element and the orientation parameters of the rectangular elements. The arrangement positions and parameters of the engine room equipment are as follows:

[0120] As shown in Table 1.

[0121]

[0122] Table 1. Arrangement and Parameters of Engine Room Equipment

[0123] Simplified cabin layout diagram as follows Figure 4 As shown.

[0124] A descriptive calculation model for the ship's compartment layout RMS indicators (equipment operating space, passageway width, overhaul hoisting capacity, reliable safety distance, and operational convenience) is established based on relevant parameters. The location of the engine room hoisting port (x) is defined. d ,y d = (2.5,0), and the RMS layout optimization operation space and hoisting parameters of the engine room equipment are shown in Table 2.

[0125] No. <![CDATA[D min (m)]]> <![CDATA[D max (m)]]> <![CDATA[f i ]]> Is hoisting required? 1 0.7 1.0 18 1 2 0.7 1.0 10 1 3 0.7 1.0 16 1 4 0.4 0.6 3 0 5 0.4 0.6 5 0 6 0.6 0.8 5 1 7 0.4 0.6 6 0 8 0.6 0.8 6 1 9 0.6 0.8 12 0 10 0.5 0.7 8 0 11 0.5 0.7 2 0 12 0.7 1.0 10 0

[0126] Table 2 Parameters for Maintainability Layout Optimization of Cabin Equipment

[0127] Based on this, an index model f3(X) is constructed for the equipment operating space f1(X) and the overhaul hoisting volume.

[0128] The cabin layout includes four aisles, with the two aisles on either side of the main engine room being the primary aisles. The minimum width requirement for these aisles is PD. min =0.8m, both have an importance weight of 0.3; the minimum width requirement for the two passageways at the front and rear of the cabin is PD. min =0.6m, with the importance weight of the front passage being 0.25 and the importance weight of the rear passage being 0.15, and thus constructing the overall passage width index model f2(X) for the cabin.

[0129] Based on the analysis of the functional requirements of the layout equipment, the functional distance requirements of each equipment are obtained, as shown in Table 3.

[0130] Association distance requirement Weight Association distance requirement Weight om(1,2)=1.5 0.2 om(4,11)=1.2 0.12 om(3,5)=1.6 0.08 om(6,7)=1.2 0.08 om(9,10)=0.8 0.15 om(11,12)=1.6 0.11 OM(8,12)=3 0.18 OM(5,8)=3 0.08

[0131] Table 3. Distance Requirements for Functional Association of Each Device

[0132] Based on this, a reliable safety distance index model f4(X) for the overall cabin is constructed.

[0133] The cabin entrance is located at (x0, y0) = (4, -0.8). Based on the layout equipment functional requirements and empirical statistics, the frequency of maintenance personnel circulation between equipment rooms is shown in Table 4.

[0134]

[0135] Table 4. Frequency of Personnel Circulation in Cabins and Equipment Rooms

[0136] Where 0 represents the cabin entrance, and a model f5(X) is constructed to represent the overall operational convenience index of the cabin.

[0137] Step 3: Determine the constraints of the RMS layout design of the compartment. First, clarify the non-interference constraint G1(X) and compatibility constraint G2(X) of the equipment layout to ensure that there is no interference between the 12 pieces of equipment to be laid out in the compartment and that all equipment is located within the compartment layout space.

[0138] Determine the compartment layout domain constraint G3(X). Based on experience, use constraints to restrict the location, layout range, or relative position of some equipment. Specifically, this includes: the orientation of the diesel engine and gearbox is fixed and arranged on the central axis of the engine room; the layout of the fuel tank and pump is located at the rear of the engine room and on the central axis; the orientation of the diesel generator set is fixed and it is located on one side with the starter battery; the sewage tank and sewage pulverizing pump are arranged coaxially; the sea valve and the suction coarse filter are located in the same area and arranged laterally or longitudinally; the gravity moment balance of the engine room around the central axis, etc.

[0139] Based on the constraints and objectives of the cabin RMS layout, the mathematical model for layout optimization is constructed as follows:

[0140]

[0141] Step 4: Determine the weights of the equipment operating space, passage width, overhaul hoisting volume, reliable safety distance, and operational convenience index as 0.3, 0.3, 0.2, 0.1, and 0.1, respectively, and construct the fitness function F(X) of the cabin layout optimization scheme X.

[0142] Using the center coordinates of the layout elements and the orientation parameters of the rectangular elements as independent variables, and with the positions of the diesel engine, gearbox, and fuel tank fixed, the degrees of freedom of the movable objects in the cabin layout optimization are analyzed to determine the design variable X = [x 1 ,x 2 ,L,x 24 The design has 24 variables, and the corresponding layout device position and orientation variables are X = [x3, y3, o3, L, x8, y8, o8, x9, y9, L, x 11 ,y 11 ].

[0143] First, the RMS index of a single compartment layout is optimized. The number of particles in each solution is 30, and the number of iterations is 100. Each single objective is optimized 10 times, resulting in 50 single-objective optimization particle position and orientation solutions. Simultaneously, 50 position and orientation particles are randomly initialized, for a total of 100 initial particle swarms. Based on this, the velocities of the particles in the initial particle swarms are randomly initialized.

[0144] For each particle, the search domain for the orientation variable is a discrete binary space, i.e., 0 or 1; the search domain for the position variable is the x and y coordinates of the compartment area, with the x-coordinate range being [0, 4] and the y-coordinate range being [-2, 2]. The update rate range for each variable is [-0.2, 0.2]. If the particle's update rate exceeds [-0.2, 0.2], the particle velocity is taken as the boundary value.

[0145] Calculate the fitness function for 100 particles and record the globally optimal position gbest for the t-th iteration. t-1 When the evolutionary generation is updated to t = t + 1, the update rate of each particle is calculated as follows:

[0146]

[0147] Among them, gbest t-1 The global optimal position before the t-th iteration flight; rand is a random number between 0 and 1; c1 is the acceleration factor, with a value of 1.49445; This is the inertia weight, with a value of 0.6.

[0148] The new position and orientation of each particle are calculated based on the particle update rate (if the variable value in a particle exceeds its boundary, the variable stops at the boundary and flies in the opposite direction). Then the fitness value of each particle is calculated. After 500 iterations, the index of a cabin RMS layout optimization scheme is obtained as shown in Table 5.

[0149] Target Optimized layout results Experience layout results <![CDATA[f1(X)]]> 1.93 2.84 <![CDATA[f2(X)]]> 0.96 11.17 <![CDATA[f3(X)]]> 1.58 1.34 <![CDATA[f4(X)]]> 1.12 1.25 <![CDATA[f5(X)]]> 2.41 2.56

[0150] Table 5 Indicators for Cabin Equipment Layout Optimization Scheme

[0151] The optimal fitness function curve of its solution process is as follows: Figure 5 As shown in the figure. Through the solution, compared with the empirical layout, the optimized layout scheme improves the equipment operating space, passage width, reliable safety distance, and operational convenience indicators, indicating that the reliability, maintainability, and supportability of the compartment equipment are optimized through a balanced approach.

[0152] The location and orientation data of each piece of equipment in the cabin equipment layout optimization scheme are shown in Table 6.

[0153]

[0154] Table 6 Data Table of Optimized Layout Scheme

[0155] Its corresponding layout scheme is as follows Figure 6 As shown.

[0156] By comparing the empirical layout scheme with the optimized layout scheme that considers RMS requirements, it can be found that the optimized layout provides good maintenance and operation space for most of the equipment in the engine room. In particular, the diesel main engine, gearbox, and diesel generator set, which are subject to frequent maintenance operations, have suitable passageways and maintenance and operation space on both sides, and maintenance operations will not be affected by interference from other equipment, thus avoiding the need to remove other equipment. In addition, the width of the compartment passageways in the optimized layout scheme better meets the RMS requirements.

[0157] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0158] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for designing the overall cabin layout of a ship considering RMS requirements, characterized in that, The method includes: Obtain the RMS design criteria for the overall cabin layout, the design parameters for the overall cabin layout, and the correlation between the RMS design criteria and the design parameters; The external shape of the cabin and equipment is described, and multiple design index description models are established for multiple indicators based on the described cabin and equipment, the RMS design criteria, design indicators and their relationships. Obtain and describe the constraints of the overall layout, and establish a cabin layout optimization model that considers RMS requirements based on the described constraints and the design index description model. An intelligent optimization algorithm is selected to solve the cabin layout optimization model, and the cabin layout optimization design scheme is obtained. Solving the cabin layout optimization model includes: extending the application of particle swarm optimization (PSO) for intelligent optimization, using the position and orientation of the equipment as independent variables, applying PSO to optimize and solve multiple design index description models multiple times, and using the equipment position and orientation solution results as part of the initial solution of the RMS layout optimization problem search space; the system initializes and randomly generates a set number of particles as part of the initial solution of the RMS layout optimization problem search space; each particle searches within the solution space by following the optimal particle at a set speed to obtain the optimal solution for the cabin layout design. Based on the described compartments and equipment, the RMS design criteria, design indicators, and their relationships, multiple design indicator description models are established for the multiple indicators: Equipment operating space specifications: In the formula, For equipment Operating space index in cabin layout environment; For equipment Operating space index under the influence of compartment bulkheads; For equipment Factors affecting the frequency of maintenance operations on cabin operating space indicators; Channel width specification: In the formula, For the first i Importance weight of each channel; Indicates the first i Channel width specification for each channel; Overhaul hoisting volume indicators: In the formula, This refers to the total number of equipment that requires hoisting during major repairs. For hoisting equipment The quality; For equipment The lifting distance to the lifting port; Reliable safe distance indicators: In the formula, The number of layout devices with functional association requirements; Equipment to be laid , The importance weight of functional relationship requirements between them; Equipment to be laid , The distance between them is a descriptive parameter that meets the relevant requirements; Ease of use index: In the formula, equipment 0 represents the hatch; For equipment To the equipment The frequency of personnel operation and circulation; For equipment To the equipment The circulation distance; The process of obtaining and describing the constraints of the overall layout, and establishing a cabin layout optimization model considering RMS requirements based on the described constraints and the design index description model, includes: The constraints for obtaining the overall layout include non-interference constraints, compatibility constraints, and compartment layout domain constraints: The non-interference constraint description model is as follows: ; The model describing the compatibility constraint is as follows: ; The domain constraint description model is as follows: ; The cabin layout optimization model is a multi-constraint, multi-objective optimization problem, namely: 。 2. The method according to claim 1, characterized in that, The design parameters for the overall layout of the compartment include: equipment operating space, passage width, overhaul hoisting capacity, reliable safety distance, and ease of operation.

3. The method according to claim 2, characterized in that, The description of the shape of the compartments and equipment includes: Each piece of equipment is simplified into a rectangular prism or a cylindrical envelope, so that the engine room equipment is represented by rectangular and circular primitives on the cabin deck plane; a plane rectangular coordinate system is defined. Design a cabin RMS layout scheme Contains 1 Equipment to be deployed, among which The device is simplified to A rectangular primitive , , The device is simplified to A circular primitive , The number of design variables for the layout scheme is The layout scheme can be described as follows: in, For primitives The coordinates of the centroid; It determines the rectangular primitive. The binary variable representing the orientation of the longer side, if Then the longer side of the rectangle and If the axes are parallel, Then the longer side of the rectangle and The axes are parallel.

4. The method according to claim 1, characterized in that, The step of selecting an intelligent optimization algorithm to solve the cabin layout optimization model and obtaining the cabin layout optimization design scheme further includes: The objectives and constraints in the cabin layout optimization model are processed. A linear weighted sum method is used to construct an evaluation function to transform the multi-objective problem into a single-objective problem. A penalty function is constructed to transform the constrained optimization problem into an unconstrained optimization problem. The fitness function of the cabin layout optimization scheme X is then expressed as: In the formula, For sub-objectives The normalization factor; For sub-objectives Weighting coefficients; As a penalty factor; For the plan Violation of constraints The degree of violation of constraints.

5. A design apparatus for a ship's overall compartment layout design method considering RMS requirements as described in any one of claims 1-4, characterized in that, The device includes: The criteria and indicator acquisition module is used to acquire the RMS design criteria and design indicators of the overall cabin layout, as well as the correlation between the RMS design criteria and design indicators. The design index description model establishment module is used to describe the shape of the cabin and equipment, and establish design index description models for multiple indicators based on the described cabin and equipment. The cabin layout optimization model building module is used to obtain and describe the constraints of the overall layout, and to build a cabin layout optimization model that considers RMS requirements based on the described constraints and the design index description model. The solution module is used to select an intelligent optimization algorithm to solve the cabin layout optimization model and obtain the cabin optimized layout design scheme. Solving the cabin layout optimization model includes: extending the application of particle swarm optimization algorithm for intelligent optimization, using the position and orientation of the equipment as independent variables, applying particle swarm optimization algorithm and performing multiple optimization solutions on multiple design index description models respectively, and using the particles from the equipment position and orientation solution as partial initial solutions of the RMS layout optimization problem search space; the system initializes and randomly generates particles of a set size as partial initial solutions of the RMS layout optimization problem search space; each particle searches within the solution space by following the optimal particle at a set speed, and finally obtains the optimal solution for RMS layout optimization.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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