Ship mooring piece split design method based on multi-process forming parameter optimization

Abstract

This invention discloses a method for the modular design of ship mooring components based on multi-process forming parameter optimization, relating to the field of precision forming and process optimization design technology for ship structural components. The method includes: generating multiple candidate modular structure schemes and their corresponding multi-process forming paths; constructing a process state vector to characterize the equivalent stiffness, plate thickness variation, and residual stress after forming a single segment; establishing a cross-process state association mechanism based on the recursive process state vector; performing stability analysis on forming parameters within the process disturbance range based on the cross-process state association mechanism to determine a robust value range for forming parameters that meets the target assembly accuracy requirements; and quantitatively comparing and optimizing each candidate modular structure scheme based on the value range. This method solves the technical problems in existing technologies where modular design of ship mooring components relies on experience, and the coupling effect of multi-process forming is difficult to quantify and evaluate, leading to difficulties in ensuring assembly accuracy and insufficient process robustness.

Description

Technical Field

[0001] This application relates to the field of precision forming and process optimization design technology for ship structural components, and in particular to a method for the separate design of ship mooring components based on multi-process forming parameter optimization. Background Technology

[0002] Ship mooring components, as typical large load-bearing structural parts, are usually characterized by large size, complex curved surfaces, and high load-bearing requirements. Their manufacturing process often involves sheet metal forming, followed by modular manufacturing and welding assembly. To meet the requirements of forming equipment capacity, transportation conditions, and on-site assembly, mooring components often require reasonable modular structure design during the design phase, and corresponding multi-process forming routes should be developed for each modular structure.

[0003] In practical engineering, there is a significant coupling relationship between the split design of ship mooring components and the selection of forming process parameters. On the one hand, different split structure schemes will lead to changes in the number of forming processes, process sequence, and forming parameter range; on the other hand, the changes in structural mechanical state generated during multiple forming processes (such as bending, rolling, and tapering) will accumulate and be transmitted between processes, significantly affecting the forming behavior of subsequent processes and the final geometric accuracy. However, the analysis of the above-mentioned multi-process forming process in the existing technology is mostly based on single processes or local processes, making it difficult to systematically characterize the influence relationship between preceding processes and subsequent processes.

[0004] Existing methods for designing modular ship mooring components typically rely on engineering experience or simple geometric rules for scheme selection. Forming parameters are mostly determined through empirical values ​​or single-point trial calculations, lacking quantitative assessment methods for the stability of forming results under process disturbances. Under multi-stage continuous forming conditions, the evolution of mechanical states such as plate thickness variation, residual stress, and structural stiffness is difficult to effectively incorporate into a unified analysis framework, resulting in insufficient accuracy in predicting forming precision and difficulty in assessing assembly errors in advance.

[0005] Furthermore, in existing technologies, the selection of split structure schemes is usually not effectively linked with the robustness analysis of forming parameters. There is a lack of technical means to objectively compare different split schemes based on the overall stability of the multi-process forming process, which can easily lead to problems such as the forming process being sensitive to process fluctuations and the difficulty in ensuring assembly accuracy.

[0006] Therefore, there is an urgent need for a design method that can systematically quantify the mechanical state transmission relationship between processes under multi-process forming conditions, and on this basis, analyze the robustness of forming parameters, thereby realizing the rational selection of the split structure scheme of ship mooring components. Summary of the Invention

[0007] The purpose of this application is to provide a method for the modular design of ship mooring components based on the optimization of multi-process forming parameters. This addresses the technical problems in existing technologies, such as the difficulty in quantifying the mechanical coupling relationship between multiple forming processes, the difficulty in assessing the robustness of multi-process forming parameters under process disturbance conditions, and the inability to objectively compare and select the best modular structure based on forming accuracy and stability.

[0008] In view of the above technical problems, this application provides a method for the split design of ship mooring components based on the optimization of multi-process forming parameters.

[0009] A first aspect of this application provides a method for the modular design of ship mooring components based on multi-process forming parameter optimization, the method comprising:

[0010] Obtain the overall structural dimensions, material type, and target assembly accuracy requirements of the ship's mooring components;

[0011] Under the conditions of meeting the forming equipment capacity and transportation constraints, multiple candidate split structure schemes are generated according to the overall structural dimensions. Each candidate split structure scheme is composed of several single-segment structures, and a corresponding multi-process forming path is determined for each candidate split structure scheme.

[0012] Based on the material type and initial sheet state, a process state vector is constructed to characterize the structural mechanical state of a single segment structure in the candidate split structure scheme after the forming process is completed.

[0013] For each candidate split structure scheme, a cross-process state association mechanism is established based on its corresponding multi-process forming path. The cross-process state association mechanism quantifies the influence of the mechanical state of the preceding process on the forming parameter response of the subsequent process based on the process state vector.

[0014] Based on the cross-process state association mechanism, the stability analysis of the process forming parameters within its preset process disturbance range is performed so that the forming result of the candidate split structure scheme meets the forming parameter value range of the target assembly accuracy requirement.

[0015] Based on the range of the forming parameters, each candidate split structure scheme is compared, and the target split structure scheme is selected and output.

[0016] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0017] By constructing process state vectors characterizing the equivalent stiffness, thickness variation, and residual stress of a single-segment structure after forming, and establishing a cross-process state correlation mechanism based on state vector recursion, the mechanical state coupling relationship between multiple forming processes is quantified. Based on the cross-process state correlation mechanism, robustness analysis is performed within the preset disturbance range of forming parameters, which determines the robust value range of forming parameters for each candidate split structure scheme, thus achieving the evaluation of the robustness of multi-process forming parameters. By quantitatively comparing and optimizing each candidate split structure scheme within the robust range of forming parameters, the final target split structure scheme can be selected, optimizing the assembly accuracy and process robustness of ship mooring components. This method overcomes the problems of difficulty in guaranteeing assembly accuracy, difficulty in quantifying the coupling effect of multi-process forming parameters, and lack of objective basis for scheme selection in traditional empirical design, improving design efficiency and manufacturing reliability. It solves the technical problems in the existing technology of difficulty in quantifying the mechanical state coupling relationship between multiple forming processes in the split design of ship mooring components, difficulty in evaluating the robustness of multi-process forming parameters under process disturbance conditions, and inability to objectively compare and optimize different split structure schemes based on forming accuracy stability.

[0018] The above description is merely an overview of the technical solution of this application. In order to more clearly explain the technical means of this application, and to enable its implementation in accordance with the contents of the specification, and to make the above and other objectives, features and advantages of this application more apparent and understandable, specific embodiments of this application are described below. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0020] Figure 1 This is a flowchart illustrating the method for designing separate ship mooring components based on multi-process forming parameter optimization, as provided in the embodiments of this application. Detailed Implementation

[0021] This application provides a method and system for the design of ship mooring components based on the optimization of multi-process forming parameters. It solves the technical problems in the prior art, such as the difficulty in quantifying the mechanical coupling relationship between multiple forming processes, the difficulty in assessing the robustness of multi-process forming parameters under process disturbance conditions, and the inability to objectively compare and select different component structure schemes based on the stability of forming accuracy.

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0023] It should be noted that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products, or devices.

[0024] Example 1, as Figure 1 As shown, this application provides a method for the modular design of ship mooring components based on multi-process forming parameter optimization, wherein the method includes:

[0025] Obtain the overall structural dimensions, material type, and target assembly accuracy requirements of the ship's mooring components;

[0026] Specifically, in this embodiment, the steps of obtaining the overall structural dimensions, material type, and target assembly accuracy requirements of the ship's mooring components can be implemented as follows: First, based on the ship's overall design drawings or a three-dimensional digital model, the overall structural dimensions of the ship's mooring components to be designed are read. These overall structural dimensions include at least the overall length, maximum outer diameter, end connection structure dimensions, and geometric dimensions of key functional areas. The overall structural dimensions can be derived from two-dimensional engineering drawings, three-dimensional CAD models, or digital model data obtained through measurement methods such as laser scanning. Second, based on design specifications or a bill of materials, the material type of the ship's mooring components is determined. This material type includes at least the material grade, yield strength, elastic modulus, and allowable forming temperature range, for example, using Q345B marine structural steel or equivalent high-strength low-alloy steel. Further, based on the ship's final assembly process requirements or relevant industry standards, the target assembly accuracy requirements are determined. These target assembly accuracy requirements include at least one of the following: dimensional tolerances, roundness, or coaxiality tolerances of key assembly interfaces. For example, the dimensional deviation between the mooring components and the deck mounting base is specified to be no greater than ±1.0 mm. The overall structural dimensions, material types, and target assembly accuracy requirements mentioned above serve as the basic input parameters for generating candidate split structure schemes, constructing process state vectors, and executing cross-process state association mechanisms. These parameters are uniformly stored in the design calculation system for subsequent steps to access.

[0027] Under the conditions of meeting the forming equipment capacity and transportation constraints, multiple candidate split structure schemes are generated according to the overall structural dimensions. Each candidate split structure scheme is composed of several single-segment structures, and a corresponding multi-process forming path is determined for each candidate split structure scheme.

[0028] Furthermore, the multi-process forming path includes a bending process, a rolling process, and a cone forming process executed sequentially.

[0029] Specifically, after obtaining the overall structural dimensions of the ship's mooring components, these dimensions are used as basic input data for generating subsequent component structure schemes. In this embodiment, the dimensions of the aforementioned guide bollard are used, and its overall structural dimensions specifically include: an overall axial length (total height) of H = 3.5 m, and a maximum outer diameter of... =1.2 m, nominal wall thickness is =45 mm. Simultaneously, the forming equipment capacity parameters and transportation constraint parameters are determined and recorded. The forming equipment capacity parameters include at least: the maximum allowable plate width for bending equipment is 3.0 m, and the maximum bending force is 25000 kN; the maximum allowable forming diameter for rolling equipment is 2.6 m, and the maximum effective roll gap is 3.2 m; the maximum allowable forming cone angle for cone forming equipment is 15°. The transportation constraint parameters include at least: the maximum allowable transport length for a single structure is 4.5 m, the maximum outer diameter is 2.6 m, and the maximum transport weight is 18 t. With the above dimensional and constraint parameters clearly defined, the overall structure is first discretized along its axial direction. Specifically, using the overall axial length as a reference, multiple candidate segmentation points are set in the axial direction with a fixed step size of 1.0 m, and different axial segmentation combinations are enumerated based on these candidate segmentation points. For each axial segmentation combination, the axial length, maximum outer diameter, and theoretical weight calculated based on the material density of each individual segment are calculated. Subsequently, the axial length, maximum outer diameter, and theoretical weight of each single-segment structure are compared with the transportation constraint parameters and forming equipment capability parameters item by item. If the axial length of any single-segment structure exceeds 4.5m, or the maximum outer diameter exceeds 2.6m, or the theoretical weight exceeds 18t, the corresponding axial segmentation combination is determined to not meet the constraint conditions and is removed from the candidate combinations. Under the premise that the axial segmentation combination meets the transportation constraint and forming equipment capability constraint, for single-segment structures containing taper or variable cross-section features, the target cone angle is calculated and compared with the maximum forming cone angle of 15° allowed by the cone forming equipment. If the target cone angle is greater than the maximum forming cone angle, the corresponding segmentation combination is determined to be unfeasible and is removed. After the above axial and circumferential constraint screening, the remaining segmentation combinations constitute multiple candidate split structure schemes, including at least a scheme composed of 3 single-segment structures and a scheme composed of 4 single-segment structures. For each remaining candidate split structure scheme, the corresponding multi-process forming path is further determined based on the geometric shape and forming characteristics of each single-segment structure. Specifically, for a single-segment structure formed from a flat material, the initial bending angle required is first calculated based on the target radius of curvature, and this bending angle is used as the forming parameter input for the bending process. Subsequently, the bent semi-formed structure continues to undergo a rolling process, forming the target arc or cylindrical shape by setting the roller gap and roller pressure parameters. When the single-segment structure has a taper requirement, a tapering process is performed after completing the rolling process, forming the target tapered structure by controlling the forming angle parameters. Thus, a multi-process forming path, including bending, rolling, and tapering processes, is determined for each single-segment structure in each candidate split structure scheme, and these processes are executed sequentially.The multiple candidate split-structure schemes and their corresponding multi-process forming paths are uniformly recorded and output, serving as the input basis for subsequent construction of process state vectors, establishment of cross-process state correlation mechanisms, and execution of forming parameter stability analysis. The number of single segments, process sequence, and process parameters described in this embodiment are only for illustrating the technical principles and implementation methods of the present invention and do not constitute a limitation on the scope of protection of the present invention. Through the above implementation methods, multiple candidate split-structure schemes can be generated under the premise of meeting the forming equipment and transportation conditions, providing specific inputs for subsequent cross-process state analysis and robustness assessment.

[0030] Based on the material type and initial sheet state, a process state vector is constructed to characterize the structural mechanical state of a single segment structure in the candidate split structure scheme after the forming process is completed.

[0031] Furthermore, the process state vector is composed of state parameters in the following three dimensions:

[0032] Equivalent stiffness state parameters are used to describe the structural stiffness state of a single segment in the candidate split structure scheme after the forming process is completed.

[0033] The plate thickness variation state parameter is used to describe the plate thickness variation state of a single segment structure in the candidate split structure scheme after the forming process is completed.

[0034] The residual stress state parameter is used to describe the residual stress state of a single segment of the candidate split structure after the forming process is completed.

[0035] Specifically, this embodiment takes the design of a guide bollard used on a 300,000-ton VLCC as an example. The overall structural dimensions of the guide bollard are: a total height of 3500 mm and a maximum outer diameter of 1200 mm, which is a variable cross-section column structure. Its material type is specified as FH40 grade marine high-strength steel, and the corresponding material parameter is elastic modulus. MPa, Poisson's ratio Yield strength MPa. The target assembly accuracy requirement is set as: the radial misalignment between any two mating ports. millimeters, axial clearance Millimeters. After obtaining the overall structural dimensions, material type, and target assembly accuracy requirements, while meeting the "maximum forming press tonnage" requirement... "tons" and "single-segment land transport length" Under the constraint of "millimeters", two candidate split structure schemes are generated based on the overall structural dimensions: Candidate split structure scheme A: The cable guide pile is divided into two equal sections along the axial direction, each section being a conical section approximately 1750 millimeters in length. Candidate split structure scheme B: The cable guide pile is divided into three sections at the structural abrupt change point: an upper conical section, a middle straight section, and a lower conical section. A corresponding multi-process forming path is determined for each candidate split structure scheme. Taking the first section of scheme A as an example, its corresponding multi-process forming path is determined to be a bending process, a rolling process, and a conical forming process executed sequentially. Taking the straight section of Scheme B as an example, its corresponding multi-process forming path is determined to be the sequential execution of bending and rolling processes. Subsequently, based on the material type and initial sheet metal state, a process state vector is constructed to characterize the structural mechanical state of the first segment of Scheme A after the forming process. The initial sheet metal state is defined as: initial sheet thickness 45 mm, initial residual stress state parameter set to 0 MPa. This process state vector is obtained through programmed post-processing of the numerical simulation results of the process and consists of the following three dimensions of state parameters: 1. Equivalent stiffness state parameter. After completing the elastoplastic forming numerical simulation of the bending process, five characteristic sections are selected along the workpiece axis; the moment of inertia of each section is calculated by fitting the nodal coordinate data of each section. According to the formula Calculate the bending stiffness of each characteristic segment, where Calculate the length of the feature segments; calculate the stiffness values ​​of the five feature segments. to The arithmetic mean was determined as the equivalent stiffness state parameter for the bending process. 2. Plate thickness variation parameters: In the same simulation result, 100 sampling points are uniformly selected on the workpiece surface; the current plate thickness at each sampling point is obtained. And calculate the difference between it and the initial plate thickness of 45 mm. ; 100 plate thickness differences to The arithmetic mean of the values ​​is determined as the plate thickness change state parameter after the bending process is completed, and is denoted as the plate thickness change state parameter in the state vector of this process. 3. Residual stress state parameters: In the same simulation results, the Von Mises residual stress values ​​were read at the same 100 sampling points. Calculate the root mean square (RMS) of these 100 residual stress values, and determine the RMS value as the residual stress state parameter after the bending process is completed, denoted as the residual stress state parameter in the state vector of this process. Thus, the process state vector of the first segment of Scheme A after the bending process is completed is obtained, denoted as... This vector serves as a quantitative representation of the mechanical state of a single-segment structure after a specific process, and is the basic input data for establishing a cross-process state correlation mechanism.

[0036] For each candidate split structure scheme, a cross-process state association mechanism is established based on its corresponding multi-process forming path. The cross-process state association mechanism quantifies the influence of the mechanical state of the preceding process on the forming parameter response of the subsequent process based on the process state vector.

[0037] Furthermore, the cross-process state association mechanism is implemented through cross-process state recursive calculation, including:

[0038] Based on the process sequence of the multi-process forming path, state update calculations are performed step by step starting from the second forming process.

[0039] For each current forming process, the process state vector after the completion of its preceding forming process is used as the state input, and combined with the forming parameters preset for the current forming process, the state input is used to perform a state update calculation to obtain the process state vector after the completion of the current forming process.

[0040] The process state vector after the completion of the current forming process is used as the state input when performing state update calculation for the next adjacent forming process. This process is repeated until the process state vector of the final process is obtained.

[0041] Furthermore, the state update calculation includes:

[0042] For any current forming process, the equivalent stiffness state parameter, plate thickness variation state parameter and residual stress state parameter in the process state vector after the immediate forming process is completed are multiplied by the state transfer coefficient that corresponds to the state parameter to obtain the corresponding state inheritance quantity.

[0043] For the forming parameters corresponding to the current forming process, the forming parameters that have an influence relationship with the equivalent stiffness state parameter, the plate thickness change state parameter and the residual stress state parameter are multiplied by the parameter action coefficient that corresponds to the forming parameter to obtain the corresponding parameter action amount.

[0044] The state inheritance quantity, parameter action quantity, and process inherent bias quantity corresponding to the equivalent stiffness state parameter, plate thickness variation state parameter, and residual stress state parameter are algebraically summed. The summation results are used as the values ​​of the equivalent stiffness state parameter, plate thickness variation state parameter, and residual stress state parameter after the completion of the current forming process, respectively, to form the process state vector after the completion of the current forming process.

[0045] Furthermore, the state transfer coefficient, parameter action coefficient, and process inherent bias are determined through the following calibration process:

[0046] Based on the split structure, material type and forming process conditions of the ship mooring component, numerical simulation is used to obtain the state vector of the preceding process with a preset reference value as input and the reference process state vector corresponding to the forming parameters of the current process.

[0047] While keeping the values ​​of other parameters unchanged except for the disturbed parameter, a preset disturbance amplitude is applied to each state parameter in the preceding process state vector and each forming parameter in the current process forming parameter, and numerical simulation is performed to obtain the corresponding disturbed process state vector.

[0048] The change in the state parameters of the disturbance process state vector obtained from the state parameters in the disturbance preceding process state vector and the corresponding state parameters in the reference process state vector are used to calculate the corresponding state transfer coefficient in combination with the preset disturbance amplitude.

[0049] Based on the change in the state parameters of the corresponding state parameters in the disturbance process state vector obtained by disturbing the current process forming parameters and the corresponding state parameters in the reference process state vector, and combined with the preset disturbance amplitude, the corresponding parameter action coefficient is calculated.

[0050] Calculate the difference between the values ​​of each state parameter in the baseline process state vector and the preset theoretical target value, and determine the difference as the corresponding process inherent bias;

[0051] The state transfer coefficient, parameter action coefficient, and process inherent bias are applied to the state update calculation to realize the cross-process state recursive calculation.

[0052] Specifically, in a complete embodiment of the present invention, for the first segment of candidate split structure scheme A, a cross-process state association mechanism is established based on its corresponding multi-process forming path. The cross-process state association mechanism quantifies the influence of the mechanical state of the preceding process on the forming parameter response of the subsequent process based on the process state vector. The cross-process state association mechanism is implemented through cross-process state recursive calculation, and its specific implementation is as follows: First, according to the process sequence of the multi-process forming path, starting from the second forming process (i.e., the rolling process), state update calculations are performed step by step. To perform the state update calculation, all coefficients required for the calculation must first be determined through a calibration process. The calibration process is based on the split structure of the ship mooring component (the first segment of scheme A), material type (FH40 steel), and forming process conditions (bending, rolling). In a computer-aided engineering environment, numerical simulation is first performed to obtain the state vector of the preceding process with a preset benchmark value as input and the benchmark process state vector corresponding to the forming parameters of the current process. Specifically, a benchmark value for the process state vector after the bending process is completed is set. (Units are N·mm / rad, mm, MPa respectively). Set the forming parameters for the rolling process, including the roll gap (denoted as...). ) and compression speed (Velocity, denoted as ), and set its baseline value. (Units are mm and mm / s respectively). With and Using the input as input, a complete elastoplastic finite element numerical simulation of a single rolling process is performed. After the simulation, the state vector of the baseline process is calculated by a post-processing program, denoted as... Next, while keeping the values ​​of all parameters except the disturbed parameter unchanged, the state vectors of the preceding processes are sequentially processed. Each state parameter in the process and the forming parameters of the current process Each forming parameter in the process is subjected to a preset perturbation amplitude, and numerical simulation is performed to obtain the corresponding perturbation process state vector. The preset perturbation amplitude is set to ±5% of the reference value. For example, for each forming parameter... , , , , Apply a +5% perturbation (for A +5% disturbance will change its value to mm), and perform simulations respectively to obtain the corresponding disturbance process state vectors. , , , , Then, based on the changes in the corresponding state parameters in the reference process state vector obtained from the state parameters in the preceding process state vector, and in conjunction with the preset disturbance amplitude, the corresponding state transfer coefficient is calculated. This is used to calculate the equivalent stiffness state parameters. right Taking the state transit coefficient as an example, the calculation formula is as follows: ;in, The perturbation state vector The equivalent stiffness state parameter values ​​in the figure. Reference state vector The equivalent stiffness state parameters are calculated. Similarly, the plate thickness variation state parameters can be calculated. right State transfer coefficient and residual stress state parameters right State transfer coefficient By calculating the perturbation simulation data of all state parameters, the state transfer coefficient matrix is ​​finally obtained. Simultaneously, based on the changes in the corresponding state parameters in the disturbed process state vector obtained from the disturbance of the current process forming parameters and the corresponding state parameters in the reference process state vector, and in conjunction with the preset disturbance amplitude, the corresponding parameter action coefficient is calculated. This is used to calculate the equivalent stiffness state parameters. Roller gap Taking the parameter effect coefficient as an example, the calculation formula is: ;in, The perturbation state vector The equivalent stiffness state parameters are calculated. Similarly, the plate thickness variation state parameters are calculated. right The parameter of action coefficient Residual stress state parameters right The parameter of action coefficient and the rate of compression The parameter of action coefficient The parameter action coefficient matrix is ​​formed. Subsequently, the baseline process state vector is calculated. The difference between the values ​​of each state parameter and the preset theoretical target value is determined as the corresponding process-specific bias. The preset theoretical target value is obtained by executing a process with an ideal initial billet state (process state vector is...). and the same reference forming parameters The simulation results were obtained for the input rolling process. Then the inherent bias vector of the process. ,in These represent the inherent biases of equivalent stiffness, plate thickness variation, and residual stress state, respectively. The state transfer coefficient matrix... Parameter coefficient matrix and process inherent bias vector The cross-process state recursive calculation can be achieved by applying this to the state update calculation. For each current forming process (taking the rolling process as an example here), the state update calculation includes: the process state vector after the completion of its immediate predecessor forming process (bending process). As a status input, and combined with the forming parameters preset for the current forming process. The state update calculation is performed on the state input, and its matrix operation expression is as follows: This formula represents the concrete implementation of the cross-process state association mechanism established from bending to rolling. It represents the process state vector after the completion of the current forming process (rolling process). This serves as the state input for the state update calculation in the next adjacent forming process (cone forming process), and so on recursively. For the cone forming process, the same calibration process as above is repeated to obtain its corresponding state transfer coefficient matrix. Parameter coefficient matrix and process inherent bias vector Thus, a state update calculation formula is established. ,Will By substituting the values, the process state vector for the final process (cone forming process) can be calculated. The aforementioned cross-process state recursive calculation process is automated through programming, and can complete one iteration from [previous process] in milliseconds. arrive The full-path state prediction provides an efficient and quantitative evaluation basis for subsequent stability analysis of forming parameters and scheme comparison. Those skilled in the art can use this specific teaching, through conventional finite element simulation and numerical calculation tools, to determine the coefficients corresponding to different processes and different split-body schemes, thereby realizing the aforementioned cross-process state correlation mechanism.

[0053] Based on the cross-process state association mechanism, the stability analysis of the process forming parameters within its preset process disturbance range is performed so that the forming result of the candidate split structure scheme meets the forming parameter value range of the target assembly accuracy requirement.

[0054] Furthermore, based on the cross-process state correlation mechanism, the stability analysis of the forming parameters of the process is performed within its preset process disturbance range, so that the forming result of the candidate split structure scheme meets the forming parameter value range of the target assembly accuracy requirement, including:

[0055] Based on the preset forming parameter reference values ​​for the candidate split structure scheme, within the process disturbance range, multiple sets of sampled forming parameter combinations are generated using a sampling method.

[0056] Each set of the sampled forming parameters is input into the cross-process state association mechanism. By performing the cross-process state recursive calculation, the corresponding final predicted state results are obtained in batches. The final predicted state results are used to evaluate the forming accuracy.

[0057] The final predicted state result corresponding to each set of sampling parameters is compared with the target assembly accuracy requirement, and all sampling forming parameter combinations with qualified prediction results are selected as qualified parameter sample sets.

[0058] In the forming parameter space, a spatial distribution analysis is performed on the qualified parameter sample set to calculate a continuous subspace that can cover the qualified parameter sample set, and this continuous subspace is defined as the value range of the forming parameter.

[0059] Specifically, in a complete embodiment of the present invention, based on the cross-process state correlation mechanism, the stability analysis of the process forming parameters is performed within its preset process disturbance range, so that the forming result of the candidate split structure scheme meets the forming parameter value range of the target assembly accuracy requirement. This embodiment takes the first segment of the aforementioned candidate split structure scheme A of the cable guide pile as the implementation object, and its full-process forming parameters include: bending angle (denoted as...). ), roll gap ( ), pressing speed ( ) and cone pressure (denoted as Its forming parameters are preset to the following baseline values: mm, mm / s, MPa. The process disturbance range is set to ±10% of the baseline values ​​of all forming parameters. Based on the cross-process state correlation mechanism, the stability analysis of the forming parameters of the process is performed within its preset process disturbance range, so that the forming result of the candidate split structure scheme meets the forming parameter value range of the target assembly accuracy requirement. Specifically, this includes the following steps: First, based on the preset forming parameter baseline values ​​for the candidate split structure scheme, within the process disturbance range, multiple sets of sampled forming parameter combinations are generated using a sampling method. In this embodiment, the Latin hypercube sampling method is used in the four-dimensional forming parameter space (dimension is MPa). Generate within) Group sampling shapes parameter combinations. During sampling, ensure that each parameter is within its perturbation range (i.e., (etc.) are sampled uniformly and independently. For example, the first set of sampled parameters generated is 46.2mm mm / s MPa The second group is mm 10.3mm / s MPa This process continues until 500 groups are generated. The second step involves inputting each group of sampled forming parameters into the cross-process state association mechanism. By executing the cross-process state recursive calculation, the corresponding final predicted state results are obtained in batches. These final predicted state results are used to evaluate forming accuracy. In specific operations, this is automated through a program: for the first... Group sampling parameter combination First, based on the bending parameters... Using the established state update formula from the initial state to the bending process, the process state vector after the bending process is calculated. Next, With roller parameters Input the calibrated cross-process state association mechanism formula from bending to rolling. Calculations yielded Then, With cone forming parameters Input the calibrated cross-process state correlation mechanism formula from roll forming to conical forming. Finally, the final predicted state result corresponding to this set of parameters is obtained, that is, the final process state vector. The final predicted state result Includes the final equivalent stiffness Plate thickness variation and residual stress State parameters. To evaluate forming accuracy, the program further considers... The mechanical state information contained therein is used to calculate the predicted values ​​of key geometric dimensions after the segment is formed, including: port ellipticity, through a preset geometric mapping relationship. and average port diameter The geometric mapping relationship is a definite calculation formula established based on the elastoplastic rebound theory, and its specific form is as follows: ,in mm represents the target diameter, and G and H are the geometric mapping coefficient matrix and offset vector obtained through a single independent finite element springback simulation analysis, a mature technique. The above recursive calculation and geometric mapping process is repeated for 500 sets of sampled parameter combinations to obtain 500 sets of corresponding predicted geometric dimensions. . Step 3: Compare the final predicted state results (mapped geometric dimension prediction values) corresponding to each set of sampling parameters with the target assembly accuracy requirements, and screen out all combinations of sampling forming parameters with qualified prediction results as the qualified parameter sample set. The target assembly accuracy requirements are: port ellipticity mm and port diameter deviation mm. The program automatically makes a logical judgment on 500 groups of prediction values one by one with the above requirements. For example, if a certain group of prediction values mm, 1.2mm, then it is determined that this group of parameters is qualified; if =2.3 mm, then it is determined as unqualified. After comparison, 452 groups out of 500 groups of prediction results meet all accuracy requirements. The program stores these 452 combinations of qualified sampling parameters and their corresponding prediction values as a qualified parameter sample set , where represents the th qualified sample. Step 4: In the forming parameter space, perform a spatial distribution analysis on the qualified parameter sample set, calculate a continuous subspace that can cover the qualified parameter sample set, and define this continuous subspace as the forming parameter value range. Specifically in implementation, the program performs boundary analysis on the 452 sample points in in the four-dimensional parameter space. The convex hull algorithm is used to calculate the minimum convex hull of these sample points. However, considering that the parameter intervals are usually regular shapes for operation in engineering applications, in this embodiment, an approximate method is adopted: First, for each parameter dimension which respectively represent ), find the minimum value and the maximum value of the projections of all sample points in this dimension in . Then, define a four-dimensional hyper-rectangular space with as the lower bound and as the upper bound. To ensure that this rectangular space can stably cover the vast majority of qualified samples, the program slightly expands the range of the boundaries of each dimension by to form the final value range of each parameter. For example, the qualified sample range of is calculated as , and after expanding , the determined value range of the bending angle forming parameter is . Similarly, the value range of the roll gap is determined as mm, 46.8mm], the value range of the reduction speed is ​ The range of values ​​is [MPa, 31.5MPa]. The Cartesian product of these four one-dimensional intervals. This constitutes the forming parameter value range corresponding to the first segment of Scheme A, which is a continuous subspace in the four-dimensional parameter space. This range indicates that when all forming parameters take any value within this range, according to the cross-process state correlation mechanism, the forming result has a high probability of meeting the target assembly accuracy requirements, thus providing a robust process window for actual production. Those skilled in the art can, based on this teaching, implement the above-mentioned sampling, batch cross-process state recursive calculation, conformity judgment, and spatial analysis steps through programming, thereby determining the forming parameter value range for any candidate split structure scheme.

[0060] Based on the range of the forming parameters, each candidate split structure scheme is compared, and the target split structure scheme is selected and output.

[0061] Furthermore, the step of comparing each candidate split structure scheme based on the value range of the forming parameters, selecting and outputting the target split structure scheme includes:

[0062] For each candidate split structure scheme, parameter sampling is performed within the corresponding value range of the forming parameter.

[0063] The parameter sampling is a uniform grid sampling performed within the value range of the forming parameters;

[0064] For each sampling point, the corresponding forming parameters are combined and input into the cross-process state association mechanism, and the cross-process state recursive calculation is performed to obtain the predicted final forming geometry.

[0065] Determine whether the predicted final forming geometry meets the target assembly accuracy requirements, and count the proportion of all sampling points that meet the requirements as the process robustness pass rate of the scheme;

[0066] Compare the process robustness pass rates of all schemes, and output the scheme with the highest pass rate as the target split structure scheme.

[0067] Specifically, in a complete embodiment of the present invention, based on the value range of the forming parameters, each candidate split structure scheme is compared, and a target split structure scheme is selected and output. This embodiment uses the aforementioned candidate split structure schemes A and B as comparison objects. Scheme A (two-segment split) and Scheme B (three-segment split) have respectively passed the aforementioned stability analysis steps, determining their corresponding forming parameter value ranges. For Scheme A (using its first segment as a representative process chain), its forming parameters include the bending angle (denoted as...). ), roll gap (denoted as ), pressing speed (denoted as ) and cone pressure (denoted as Its parameter value range is: bending angle range. Roll gap area [mm, 46.8mm], pressing speed range [mm / s, 10.5mm / s], cone pressure range [28.8MPa, 31.5MPa]. For scheme B, its forming parameters include bending angle ( Roller gap and pressing speed Curving angle range Roll gap area [mm, 45.8mm], pressing speed range [9.9mm / s, 10.2mm / s]. The process of comparing candidate split-structure schemes based on the forming parameter value range, selecting and outputting the target split-structure scheme, specifically includes the following steps: Step 1: For each candidate split-structure scheme, parameter sampling is performed within its corresponding forming parameter value range. The parameter sampling is a uniform grid sampling performed within the forming parameter value range. Taking scheme A as an example, in its four-dimensional parameter space... Uniform grid sampling is performed within the range. Specifically, each parameter interval is uniformly divided into 5 levels (i.e., the minimum value, the maximum value, and three intermediate points are taken). For example, for... Its five equal division points are: After generating equally divided points for each of the four parameter intervals according to this rule, their Cartesian product is taken to generate sampling points for all parameter combinations. The total number of sampling points is... There are a total of [number]. The sampling points, of which the first The combination of forming parameters corresponding to each sampling point is denoted as . For example, one of the sampling points is mm mm / s MPa Similarly, for the three-dimensional parameter space of scheme B... Perform uniform grid sampling, dividing each interval into 5 equal parts, to generate... The sampling point, its first The parameter combination of each sampling point is denoted as The second step: For each sampling point, the corresponding forming parameters are combined and input into the cross-process state association mechanism to perform the cross-process state recursive calculation and obtain the predicted final forming geometry. This step is executed automatically in batches by the program. For the first step of scheme A... For each sampling point, the program executes the same recursive calculation chain as in the stability analysis: first, using bending parameters... The process state vector after the bending process is calculated and denoted as follows. Combined with roller round parameters The state update calculation formula is based on the established cross-process state correlation mechanism characterizing bending to rolling. The process state vector after the rolling process is calculated and denoted as follows: ,in B and B are the state transfer coefficient matrix and parameter action coefficient matrix, respectively. This is the inherent bias vector of the process; finally, it is combined with the cone forming parameters. The state update calculation formula, which characterizes the cross-process state correlation mechanism from roll forming to cone forming, is used. The final process state vector is calculated and denoted as... ,in , , These are the corresponding coefficient matrices and vectors. Then, Input a preset geometric mapping relationship, which is used to map the final mechanical state to geometric accuracy. Its expression is: ;in, and They are vectors The equivalent stiffness state parameters and residual stress state parameters in the figure, To design the target diameter. The geometric mapping coefficient matrix. and bias vector The theoretical final state vector, ideally shaped, is determined through the following calibration procedure. and the corresponding target geometric dimensions As a baseline; in numerical simulation, material parameters (such as elastic modulus) are fine-tuned. (or process boundary conditions) generate a set of final state vectors with slight differences. and their corresponding springback geometry Subsequently, multiple linear regression was performed using the least squares method to fit the result. and The linear relationship between them, that is, to obtain and The predicted final forming geometry corresponding to this sampling point is calculated: port ellipticity. and port diameter deviation For scheme B, the first... For each sampling point, the process chain only includes bending and rolling; the program performs a similar recursive calculation (to obtain...). and After that, the predicted final geometric dimensions are calculated using the corresponding geometric mapping relationship. Step 3: Determine whether the predicted final forming geometry meets the target assembly accuracy requirements, and calculate the proportion of all sampled points that meet the requirements, which is taken as the process robustness pass rate of this scheme. The program will process all samples from scheme A. Calculated from each sampling point With unified target assembly precision requirements mm and Automatic comparison was performed using mm). Statistical results show that among them... If the prediction results for each sampling point meet the requirements, then the process robustness pass rate of scheme A is defined as follows: Similarly, for scheme B... Each sampling point is used for judgment, and statistics are obtained. If all sampling points meet the requirements, then the process robustness pass rate of scheme B is defined. Step 4: Compare the process robustness pass rates of all schemes, and output the scheme with the highest pass rate as the target split structure scheme. It should be noted that the process robustness pass rate... and The results are evaluated within the value ranges of forming parameters obtained through independent optimization of each scheme. This comparison essentially reflects the inherent robustness of each scheme in maintaining forming accuracy within its optimal process window, provided that each parameter range is discretized at the same level. Schemes with higher yield rates indicate that their corresponding split-structure designs, under a given process system, have a wider range of process operations that guarantee assembly accuracy, and are therefore considered superior target schemes. (Program Comparison) and ,Sure Therefore, candidate split structure scheme A is selected as the target split structure scheme. The output includes the split design drawings of scheme A (including segment locations and interface types), and the corresponding recommended forming parameter baseline values ​​(e.g., taking the midpoint of each parameter range). , mm, mm / s, The MPa value and its confidence interval (i.e., the previously determined range of forming parameter values) are output together as the final design and process guidance document. This embodiment fully demonstrates how to use the range of forming parameter values ​​to quantitatively evaluate and compare the process robustness of different split-body schemes through specific sampling strategies, calculation processes, and statistical comparisons, thereby making data-driven optimization design decisions and ensuring the objectivity and repeatability of the method. This method effectively overcomes the drawbacks of traditional methods that rely on experience-based trial and error, such as long cycles, high costs, and unstable quality. Through systematic simulation and optimization, it significantly improves the robustness of process design and production efficiency while ensuring assembly accuracy.

[0068] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0070] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for the split design of ship mooring components based on multi-process forming parameter optimization, characterized in that, include: Obtain the overall structural dimensions, material type, and target assembly accuracy requirements of the ship's mooring components; Under the conditions of meeting the forming equipment capacity and transportation constraints, multiple candidate split structure schemes are generated according to the overall structural dimensions. Each candidate split structure scheme is composed of several single-segment structures, and a corresponding multi-process forming path is determined for each candidate split structure scheme. Based on the material type and initial sheet metal state, a process state vector is constructed to characterize the structural mechanical state of a single segment in the candidate split structure scheme after the forming process. This process state vector consists of state parameters in the following three dimensions: Equivalent stiffness state parameters are used to describe the structural stiffness state of a single segment in the candidate split structure scheme after the forming process is completed. The plate thickness variation state parameter is used to describe the plate thickness variation state of a single segment structure in the candidate split structure scheme after the forming process is completed. The residual stress state parameter is used to describe the residual stress state of a single segment of the candidate split structure after the forming process is completed. For each candidate split structure scheme, a cross-process state association mechanism is established based on its corresponding multi-process forming path. The cross-process state association mechanism quantifies the influence of the mechanical state of the preceding process on the forming parameter response of the subsequent process based on the process state vector. Based on the cross-process state association mechanism, the stability analysis of the process forming parameters within its preset process disturbance range is performed so that the forming result of the candidate split structure scheme meets the forming parameter value range of the target assembly accuracy requirement. Based on the range of the forming parameters, each candidate split structure scheme is compared, and the target split structure scheme is selected and output.

2. The method according to claim 1, characterized in that, The multi-process forming path includes a bending process, a rolling process, and a cone forming process executed sequentially.

3. The method according to claim 1, characterized in that, The cross-process state association mechanism is implemented through cross-process state recursive calculation, including: Based on the process sequence of the multi-process forming path, state update calculations are performed step by step starting from the second forming process. For each current forming process, the process state vector after the completion of its preceding forming process is used as the state input, and combined with the forming parameters preset for the current forming process, the state input is used to perform a state update calculation to obtain the process state vector after the completion of the current forming process. The process state vector after the completion of the current forming process is used as the state input when performing state update calculation for the next adjacent forming process. This process is repeated until the process state vector of the final process is obtained.

4. The method according to claim 3, characterized in that, The state update calculation includes: For any current forming process, the equivalent stiffness state parameter, plate thickness variation state parameter and residual stress state parameter in the process state vector after the immediate forming process is completed are multiplied by the state transfer coefficient that corresponds to the state parameter to obtain the corresponding state inheritance quantity. For the forming parameters corresponding to the current forming process, the forming parameters that have an influence relationship with the equivalent stiffness state parameter, the plate thickness change state parameter and the residual stress state parameter are multiplied by the parameter action coefficient that corresponds to the forming parameter to obtain the corresponding parameter action amount. The state inheritance quantity, parameter action quantity, and process inherent bias quantity corresponding to the equivalent stiffness state parameter, plate thickness variation state parameter, and residual stress state parameter are algebraically summed. The summation results are used as the values ​​of the equivalent stiffness state parameter, plate thickness variation state parameter, and residual stress state parameter after the completion of the current forming process, respectively, to form the process state vector after the completion of the current forming process.

5. The method according to claim 4, characterized in that, The state transfer coefficient, parameter action coefficient, and process inherent bias are determined through the following calibration process: Based on the split structure, material type and forming process conditions of the ship mooring component, numerical simulation is used to obtain the state vector of the preceding process with a preset reference value as input and the reference process state vector corresponding to the forming parameters of the current process. While keeping the values ​​of other parameters unchanged except for the disturbed parameter, a preset disturbance amplitude is applied to each state parameter in the preceding process state vector and each forming parameter in the current process forming parameter, and numerical simulation is performed to obtain the corresponding disturbed process state vector. The change in the state parameters of the disturbance process state vector obtained from the state parameters in the disturbance preceding process state vector and the corresponding state parameters in the reference process state vector are used to calculate the corresponding state transfer coefficient in combination with the preset disturbance amplitude. Based on the change in the state parameters of the corresponding state parameters in the disturbance process state vector obtained by disturbing the current process forming parameters and the corresponding state parameters in the reference process state vector, and combined with the preset disturbance amplitude, the corresponding parameter action coefficient is calculated. Calculate the difference between the value of each state parameter in the baseline process state vector and the preset theoretical target value, and determine the difference as the corresponding process inherent bias; The state transfer coefficient, parameter action coefficient, and process inherent bias are applied to the state update calculation to realize the cross-process state recursive calculation.

6. The method according to claim 1, characterized in that, Based on the cross-process state correlation mechanism, the stability analysis of the forming parameters of the process is performed within its preset process disturbance range, so that the forming result of the candidate split structure scheme meets the forming parameter value range of the target assembly accuracy requirement, including: Based on the preset forming parameter reference values ​​for the candidate split structure scheme, within the process disturbance range, multiple sets of sampled forming parameter combinations are generated using a sampling method. Each set of the sampled forming parameters is input into the cross-process state association mechanism. By performing the cross-process state recursive calculation, the corresponding final predicted state results are obtained in batches. The final predicted state results are used to evaluate the forming accuracy. The final predicted state result corresponding to each set of sampling parameters is compared with the target assembly accuracy requirement, and all sampling forming parameter combinations with qualified prediction results are selected as qualified parameter sample sets. In the forming parameter space, a spatial distribution analysis is performed on the qualified parameter sample set to calculate a continuous subspace that can cover the qualified parameter sample set, and this continuous subspace is defined as the value range of the forming parameter.

7. The method according to claim 1, characterized in that, The process of comparing candidate split-structure schemes based on the value range of the forming parameters, selecting and outputting the target split-structure scheme includes: For each candidate split structure scheme, parameter sampling is performed within the corresponding value range of the forming parameter. The parameter sampling is a uniform grid sampling performed within the value range of the forming parameters; For each sampling point, the corresponding forming parameters are combined and input into the cross-process state association mechanism, and the cross-process state recursive calculation is performed to obtain the predicted final forming geometry. Determine whether the predicted final forming geometry meets the target assembly accuracy requirements, and count the proportion of all sampling points that meet the requirements as the process robustness pass rate of the scheme; Compare the process robustness pass rates of all schemes, and output the scheme with the highest pass rate as the target split structure scheme.

Images