Water-lubricated bearing groove parameter collaborative optimization design method and system

Abstract

The present application relates to the technical field of water-lubricated bearing, and provides a water-lubricated bearing groove parameter collaborative optimization design method and system, the method comprises the following steps: determining the basic parameters and working condition parameters of the water-lubricated bearing to be optimized, and establishing a set of water-lubricated bearing groove geometric parameter design variables; within a preset parameter range, a candidate parameter combination of groove depth and groove width is constructed; for each candidate parameter combination, a corresponding water-lubricated bearing groove structure model is established; according to the comprehensive performance evaluation value, all candidate parameter combinations are sorted or searched to determine the optimal groove depth and groove width combination under the target working condition; and according to the optimal parameter combination, an optimized groove structure is formed on the inner surface of the water-lubricated bearing lining layer. The present application integrates multiple performance indicators into a unified evaluation framework, realizes multi-objective collaborative optimization, and is conducive to obtaining a water-lubricated bearing structure with better comprehensive performance.

Description

Technical Field

[0001] This invention relates to the field of water-lubricated bearing technology, and in particular to a method and system for collaborative optimization design of groove parameters in water-lubricated bearings. Background Technology

[0002] Water-lubricated bearings use water as the lubricating medium, offering advantages such as no oil pollution, environmental friendliness, and easy maintenance. They are widely used in marine propulsion shafting, stern bearing systems, and support components of large rotating machinery. Compared to oil-lubricated bearings, water has lower viscosity, resulting in a relatively limited fluid film carrying capacity. Under conditions such as low-speed heavy loads, frequent start-stop cycles, off-center loading, and complex sea conditions, water-lubricated bearings are more prone to problems such as localized film thickness reduction, water film rupture, increased friction, enhanced vibration, and abnormal wear, thereby affecting bearing stability and service life.

[0003] Existing water-lubricated bearings typically feature lubrication grooves on the liner surface to enhance water intake, storage, chip removal, and heat dissipation, as well as improve the distribution of the lubricating medium within the bearing clearance. However, geometric parameters such as groove depth and width simultaneously affect lubricant supply, water film formation, local pressure distribution, and effective bearing area. When groove parameters are too small, insufficient lubricant replenishment hinders stable water film formation; conversely, excessively large groove parameters may weaken the effective bearing area and even cause abnormal local pressure distribution and reduced structural stiffness.

[0004] Current designs for water-lubricated bearing groove structures have the following shortcomings:

[0005] (1) Existing water-lubricated bearing groove designs mainly rely on empirical values ​​or single parameter adjustments, lacking quantitative design basis for the coupling effect of groove depth and groove width, making it difficult to obtain a parameter combination with better overall performance.

[0006] (2) Existing design methods usually only optimize a single index such as load capacity, friction coefficient or wear, making it difficult to take into account multiple performance objectives such as load capacity, film thickness, friction, temperature rise and wear.

[0007] (3) Under conditions such as low speed heavy load, off-center load, start-stop and complex sea conditions, the internal lubrication state of the bearing is more complex, and the existing groove structure design method is not adaptable to complex conditions.

[0008] (4) Although existing research shows that trench parameters have a significant impact on performance, there is a lack of a complete design process from setting candidate parameters, performance evaluation, comprehensive evaluation to determining the optimal parameters, which makes it difficult to directly guide engineering applications.

[0009] Currently, the design of groove structures for water-lubricated bearings mostly adopts empirical selection, single-parameter trial calculation, or local experimental correction methods. There is a lack of systematic optimization design methods that consider the synergistic effect of groove depth and groove width, making it difficult to achieve a comprehensive balance between load-bearing capacity, minimum film thickness, friction loss, and wear risk. Therefore, it is necessary to propose a water-lubricated bearing performance optimization design method that is oriented towards multiple index constraints and can directly serve engineering design. Summary of the Invention

[0010] The purpose of this invention is to overcome the shortcomings of the prior art by proposing a collaborative optimization design method and system for groove parameters of water-lubricated bearings. This method incorporates multiple performance indicators into a unified evaluation framework, achieving multi-objective collaborative optimization, which is beneficial for obtaining a water-lubricated bearing structure with better overall performance.

[0011] To achieve the above objectives, the present invention adopts the following technical solution:

[0012] In a first aspect, the present invention provides a method for collaborative optimization design of groove parameters in water-lubricated bearings, comprising the following steps:

[0013] Determine the basic and operating parameters of the water-lubricated bearing to be optimized, and establish a set of design variables for the geometric parameters of the water-lubricated bearing groove; within the preset parameter range, construct candidate parameter combinations for groove depth and groove width; for each set of candidate parameter combinations, establish the corresponding water-lubricated bearing groove structure model.

[0014] Based on the comprehensive performance evaluation value, all candidate parameter combinations are sorted or searched to determine the optimal groove depth and groove width combination under the target working condition; based on the optimal parameter combination, an optimized groove structure is formed on the inner surface of the water-lubricated bearing liner.

[0015] Secondly, the present invention provides a water-lubricated bearing, which is designed by the water-lubricated bearing groove parameter collaborative optimization design method described in the first aspect.

[0016] Thirdly, the present invention provides a collaborative optimization design system for water-lubricated bearing groove parameters, comprising:

[0017] The parameter determination unit is used to: determine the basic parameters and operating parameters of the water-lubricated bearing to be optimized, and establish a set of design variables for the geometric parameters of the water-lubricated bearing groove.

[0018] The groove model building unit is used to: build candidate parameter combinations for groove depth and groove width within a preset parameter range; and build a corresponding water-lubricated bearing groove structure model for each candidate parameter combination.

[0019] The groove optimization unit is used to: sort or search all candidate parameter combinations based on the comprehensive performance evaluation value, determine the optimal combination of groove depth and groove width under the target working condition; and form an optimized groove structure on the inner surface of the water-lubricated bearing liner based on the optimal parameter combination.

[0020] The parameter determination unit, trench model construction unit, and trench optimization unit sequentially establish a data flow connection.

[0021] Fourthly, the present invention provides an electronic device comprising: at least one processor, at least one memory, and a communication interface, wherein the processor, memory, and communication interface communicate with each other; the memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the collaborative optimization design method for water-lubricated bearing groove parameters described in the first aspect.

[0022] Fifthly, the present invention provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to execute the collaborative optimization design method for water-lubricated bearing groove parameters described in the first aspect.

[0023] Compared with existing technical solutions, the beneficial effects of the embodiments of the present invention are reflected in the following aspects:

[0024] (1) Based on lubrication theory, this invention uses groove depth and groove width as core design variables. It combines performance indicators such as load-bearing capacity, minimum film thickness, friction coefficient, temperature rise, vibration, and wear risk to establish a comprehensive performance evaluation function. Through evaluation and optimization of candidate parameter combinations, the optimal groove structure parameters under the target working condition are obtained, thus forming an optimized water-lubricated bearing structure. This invention incorporates multiple performance indicators such as load-bearing capacity, minimum film thickness, friction loss, and wear risk into a unified evaluation framework, achieving multi-objective collaborative optimization, which is beneficial for obtaining a water-lubricated bearing structure with superior overall performance.

[0025] (2) The embodiments of the present invention establish a performance optimization design method under the synergistic effect of groove depth and groove width of water-lubricated bearings, which no longer relies on experience selection and improves the scientificity and repeatability of structural design.

[0026] (3) The embodiments of the present invention can determine the optimal combination of trench parameters according to different working conditions and load characteristics, and can further realize the partitioned differentiated design of high load area and low load area, thereby enhancing the adaptability of the method to complex working conditions.

[0027] (4) The groove structure optimized in the embodiments of the present invention can improve the lubricant supply and film pressure distribution, improve the water film formation and maintenance ability, reduce the risk of local contact and abnormal wear, thereby improving the bearing operation stability and service life.

[0028] (5) The embodiments of the present invention introduce orthogonal experiments and response surface analysis into the trench parameter optimization process, which can improve the accuracy of optimal parameter identification while reducing the number of experiments and the amount of calculation, thereby enhancing the engineering feasibility and promotion value of the method.

[0029] (6) The method proposed in the embodiments of the present invention can be used for the design of new water-lubricated bearing structures as well as for the improvement of existing bearing structures, and has good engineering application value. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart of the collaborative optimization design method for water-lubricated bearing groove parameters in an embodiment of the present invention.

[0032] Figure 2 This is a schematic diagram of a water-lubricated bearing with a rectangular straight groove.

[0033] Figure 3 This is a schematic diagram of a U-shaped straight groove water-lubricated bearing.

[0034] Figure 4 This is a schematic diagram of a water-lubricated bearing with a rectangular spiral groove.

[0035] Figure 5 This is a schematic diagram for calculating the pressure distribution in the flow field of a water-lubricated bearing with a rectangular straight groove.

[0036] Figure 6 This is a schematic diagram for calculating the pressure distribution in the flow field of a water-lubricated bearing with a U-shaped straight groove.

[0037] Figure 7 This is a schematic diagram for calculating the pressure distribution in the flow field of a water-lubricated bearing with a rectangular helical groove.

[0038] Figure 8 This is a response surface diagram showing the impact of trench depth and trench width on overall performance in an embodiment of the present invention.

[0039] Figure 9 This is a contour map showing the influence of trench depth and trench width on overall performance in an embodiment of the present invention.

[0040] Figure 10 This is a structural block diagram of the collaborative optimization design system for water-lubricated bearing groove parameters in an embodiment of the present invention.

[0041] Figure 11 This is a structural block diagram of the trench model construction unit in an embodiment of the present invention. Detailed Implementation

[0042] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0043] Example 1: Collaborative Optimization Design Method for Groove Parameters of Water-Lubricated Bearings

[0044] See Figure 1 As shown, this embodiment of the invention provides a method for collaborative optimization design of groove parameters in water-lubricated bearings, comprising the following steps:

[0045] Step S1: Determine the basic parameters and operating parameters of the water-lubricated bearing to be optimized, and establish a set of design variables for the geometric parameters of the water-lubricated bearing groove;

[0046] Step S2: Within the preset parameter range, construct candidate parameter combinations for groove depth and groove width; for each candidate parameter combination, establish the corresponding water-lubricated bearing groove structure model.

[0047] Step S3: Based on the comprehensive performance evaluation value, sort or search all candidate parameter combinations to determine the optimal groove depth and groove width combination under the target working condition; based on the optimal parameter combination, form an optimized groove structure on the inner surface of the water-lubricated bearing liner.

[0048] Example 2: Basic parameters and operating parameters of water-lubricated bearings

[0049] Based on Example 1, this embodiment of the invention provides a method for collaborative optimization design of groove parameters in water-lubricated bearings. Specifically, in step S1 above, the basic parameters and operating parameters of the water-lubricated bearing include:

[0050] The bearing inner diameter or journal radius, bearing length, radial clearance, liner material parameters, shaft speed or surface linear velocity, external load or unit specific pressure, lubricating medium properties, and eccentricity or off-center load parameters.

[0051] Example 3: Design Variable Set of Geometric Parameters for Water-Lubricated Bearing Grooves

[0052] Based on Example 2, this embodiment of the invention provides a collaborative optimization design method for water-lubricated bearing groove parameters. Specifically, in step S1 above, the set of design variables for the geometric parameters of the water-lubricated bearing groove includes:

[0053] The trench depth, trench width, number of trenches, trench cross-sectional shape, distribution of trenches along the axial, circumferential or spiral direction, and the zoning setting method of trench parameters in different areas.

[0054] See the structural diagrams of water-lubricated bearings with different grooves. Figure 2-4 As shown, Figure 2 This is a schematic diagram of a water-lubricated bearing with rectangular straight grooves. Figure 3 This is a schematic diagram of a U-shaped straight groove water-lubricated bearing. Figure 4 This is a schematic diagram of a water-lubricated bearing with a rectangular spiral groove.

[0055] See Figure 2 As shown, This indicates the width of the rectangular groove in a water-lubricated bearing with a rectangular straight groove, which is the opening size of the groove in the unfolding direction of the water-lubricated bearing surface with a rectangular straight groove. The depth of the rectangular groove in a water-lubricated bearing with a rectangular straight groove is the vertical distance from the reference point on the inner surface of the water-lubricated bearing to the bottom of the groove. , These two structural parameters are mainly used to characterize the geometry of the axial rectangular groove of the water-lubricated bearing with a rectangular straight groove.

[0056] See Figure 3 As shown, R represents the radius of the arc-shaped groove in the U-shaped straight groove water-lubricated bearing. It describes the curvature characteristics of the groove cross-section; a larger radius results in a smoother groove cross-section, while a smaller radius leads to greater local curvature. This parameter determines the basic contour characteristics of the arc-shaped groove in the U-shaped straight groove water-lubricated bearing and directly affects the local flow field distribution and pressure gradient changes.

[0057] See Figure 4 As shown, This indicates the width of the oblique rectangular groove in a water-lubricated bearing with a rectangular helical groove. The depth of the oblique rectangular groove in a water-lubricated bearing with a rectangular helical groove is defined in the same way as... Figure 2 The difference lies in that the grooves are not arranged in a straight line along the axial direction, but are distributed in an inclined manner on the surface of the water-lubricated bearing with rectangular spiral grooves. Therefore, in addition to the cross-sectional dimensions, its spatial arrangement will also affect the fluid flow path and lubrication performance.

[0058] Example 4: Candidate parameter combinations for trench depth and trench width

[0059] Based on Example 3, this embodiment of the invention provides a collaborative optimization design method for groove parameters of water-lubricated bearings. Specifically, in step S2 above, the candidate parameter combinations of groove depth and groove width are generated through orthogonal experimental design, full factorial parameter combination, response surface design, numerical parameter scanning, or intelligent optimization algorithms. Using the water film control equation, film thickness equation, and performance integral relationship as the theoretical basis, the candidate groove parameter combinations are uniformly solved and quantitatively evaluated. The groove depth and groove width are explicitly introduced into the film thickness function to establish the transmission relationship between groove parameters, film thickness distribution, film pressure distribution, and performance indicators.

[0060] Example 5: Within a preset parameter range, construct candidate parameter combinations for groove depth and groove width; for each candidate parameter combination, establish a corresponding water-lubricated bearing groove structure model.

[0061] Based on Example 4, this embodiment of the invention provides a collaborative optimization design method for water-lubricated bearing groove parameters. Specifically, step S2 above involves constructing candidate parameter combinations for groove depth and groove width within a preset parameter range. For each candidate parameter combination, a corresponding water-lubricated bearing groove structure model is established, including the following steps:

[0062] A thin-film flow control model for water-lubricated bearings is established. The water film flow in the bearing lubrication zone is described using thin-film lubrication theory, and the film pressure distribution is solved based on mass conservation, viscous flow, and thin-film approximation assumptions.

[0063] The coupling relationship between the film thickness equation and the trench parameters is established. The trench depth changes the thickness of the local fluid domain, and the trench width changes the distribution range of the local fluid domain. The two together affect the establishment of the pressure gradient, the continuity of the water film, and the effective bearing area.

[0064] Boundary conditions and cavitation treatment: In the process of solving the membrane pressure, environmental pressure boundary conditions are used at both ends of the bearing. For the circumferential starting and ending boundaries, periodic boundaries or inlet-outlet boundary conditions are used. Cavitation boundaries or mass conservation cavitation models are introduced. For water-lubricated bearings with different groove structures, the flow field pressure distribution is calculated.

[0065] Load, friction and performance index calculation: After obtaining the water film pressure distribution, the main performance index of the bearing is calculated: the bearing load capacity is calculated by integrating the film pressure in the lubrication area; the friction force and friction coefficient are calculated based on the integration of the wall shear stress; the minimum film thickness is calculated by the film thickness distribution in the entire lubrication domain; and the temperature rise, pressure peak, film thickness fluctuation and stiffness damping coefficient are calculated.

[0066] Orthogonal experiments were used for initial parameter screening: In the preliminary optimization stage of trench depth and width, orthogonal experimental design was introduced. For a two-factor, three-level design scenario, an equivalent orthogonal array was constructed, with trench depth and width designated as Factor A and Factor B, respectively. Each factor had three levels, and load-bearing capacity, minimum film thickness, friction coefficient, temperature rise, or comprehensive performance evaluation value were used as response indicators. During the orthogonal experimental analysis, the mean response values ​​at each level were statistically analyzed to obtain the average response values ​​of Factor A and Factor B at different levels. Range analysis was then used to determine the primary and secondary influences of different factors on the performance indicators.

[0067] Response surface analysis is used for fine modeling and optimization: After completing the initial screening or parameter scanning of orthogonal experiments, response surface analysis is used to finely optimize the trench depth and width. The trench depth and width are used as independent variables, and the load-bearing capacity, minimum film thickness, friction coefficient, or comprehensive performance evaluation value are used as response values. A quadratic polynomial response surface model is established. By regression fitting of the experimental results or numerical calculation results, the continuous mapping relationship between the trench depth and width and the performance index is obtained. Based on this response surface model, response surface plots and contour plots are drawn to characterize the optimal parameter region and the variation law of parameter sensitivity.

[0068] Example 6: Calculation of flow field pressure distribution for water-lubricated bearings with different groove structures.

[0069] Based on Example 5, this embodiment of the invention provides a collaborative optimization design method for groove parameters of water-lubricated bearings. Specifically, for water-lubricated bearings with different groove structures, the flow field pressure distribution is calculated, including the following steps:

[0070] For water-lubricated bearings with different groove structures, corresponding geometric models are established, and the fluid domain of the lubricating water film between the journal and the bearing is constructed.

[0071] The mesh is divided according to the working gap and the size of the trench, and local densification is implemented for the trench edges and the film sensitive areas;

[0072] Based on the given rotational speed, external load, medium parameters, and boundary conditions, the pressure distribution in the flow field of a water-lubricated bearing is iteratively solved using a fluid-structure interaction method.

[0073] During the solution process, the pressure load output by the fluid domain acts on the surface of the bearing structure, and the deformation calculated by the solid domain in turn corrects the gap distribution of the fluid domain, so as to realize the bidirectional coupling update of the water film pressure field and the structural deformation field.

[0074] Once all field variables converge, the water film pressure distribution results of water-lubricated bearings with different groove structures are output, and the effects of different groove structures on the pressure peak, bearing area and flow field uniformity of water-lubricated bearings are compared accordingly.

[0075] Example 7: Applying Response Surface Analysis to Fine Modeling and Optimization

[0076] Based on Example 6, this embodiment of the invention provides a collaborative optimization design method for groove parameters of water-lubricated bearings. Specifically, it uses response surface analysis for fine modeling and optimization, and also includes the following steps:

[0077] The coefficients of the first-order term, interaction term, and quadratic term in the response surface model are all determined from experimental data or numerical simulation results using a multiple quadratic regression method, specifically including the following steps:

[0078] Different combinations of trench depth and width were selected for testing or numerical calculation to obtain the corresponding response values;

[0079] A design matrix is ​​constructed, and the least squares method is used to estimate the parameters of the quadratic polynomial model, obtaining the coefficients of the constant term, the coefficients of the first term, the coefficients of the interaction term, and the coefficients of the quadratic term.

[0080] Based on this, the significance of each coefficient is tested by combining analysis of variance. Response surface plots and contour plots are drawn using the obtained model to determine the optimal parameter region and the sensitivity law of the factors.

[0081] When the objective is to optimize a single performance, the response value is directly taken from a single performance index, including: load-bearing capacity, minimum film thickness, or friction coefficient.

[0082] When the objective is to optimize multiple indicators synergistically, the load-bearing capacity, minimum film thickness, water film stability, friction loss, and temperature rise indicators are made dimensionless, and a comprehensive response value is constructed according to the predetermined optimization objective.

[0083] Based on the above response surface model, the trench depth and trench width are jointly optimized to determine the optimal parameter matching interval under given working conditions.

[0084] By taking increased load-bearing capacity, increased minimum film thickness, decreased friction coefficient, and limited temperature rise as joint optimization objectives, the influence of trench parameters on comprehensive performance is obtained through response surface fitting results, and the optimal parameter region is determined accordingly.

[0085] Example 8, Specific Calculation Formula

[0086] Based on Example 7, this embodiment of the invention provides a collaborative optimization design method for groove parameters of water-lubricated bearings, and explains the calculation formulas in the above steps.

[0087] 1. Determine the basic parameters and operating parameters of the bearing.

[0088] First, determine the basic and operating parameters of the water-lubricated bearing to be optimized, including: bearing inner diameter or journal radius, bearing length, radial clearance, liner material parameters, shaft speed or surface linear velocity, external load or unit specific pressure, lubricating medium properties, and eccentricity or off-center load parameters. These parameters serve as the basic input conditions for the optimal design of the groove structure.

[0089] 2. Definition of design variables for trench structure

[0090] Establish a set of design variables for the geometric parameters of the water-lubricated bearing grooves, including at least the groove depth and groove width, and may further include the number of grooves, the shape of the groove cross-section, the distribution of the grooves along the axial, circumferential or helical direction, and the zoning setting method of the groove parameters in different areas.

[0091] 3. Construct candidate parameter combinations

[0092] Within the preset parameter range, construct candidate parameter combinations for trench depth and trench width.

[0093] Candidate parameter combinations for trench depth and trench width can be generated through: orthogonal experimental design, full factorial parameter combination, response surface design, numerical parameter scanning, or intelligent optimization algorithms.

[0094] For each combination of candidate parameters, a corresponding water-lubricated bearing groove structure model is established for subsequent performance evaluation.

[0095] 3.1 Establishment of the theoretical model for water film solution

[0096] To improve the theoretical completeness of the embodiments of the present invention, after the candidate parameter combinations are determined, a thin film flow control model for water-lubricated bearings is first established.

[0097] The water film flow in the bearing lubrication zone is described using thin film lubrication theory, and the film pressure distribution is solved based on mass conservation, viscous flow and thin film approximation assumptions.

[0098] For grooved water-lubricated bearings, when the influence of body forces is neglected and the lubricating medium is an incompressible Newtonian fluid, its governing equations can be expressed using the generalized Reynolds equations:

[0099] , , ,

[0100] in, For water film pressure, For film thickness, For the dynamic viscosity of the lubricating medium, For the density of the lubricating medium, The dynamic viscosity of the lubricating medium varies with temperature. The density of the lubricating medium varies with temperature. The relative sliding velocity of the journal surface. Circumferential coordinates For axial coordinates, For time.

[0101] This equation is used to solve for the pressure and velocity distribution in the water film and to calculate bearing performance.

[0102] When analyzing steady-state conditions, the time term in the formula... It can be zero;

[0103] When analyzing start-up, shutdown, impact load, or attitude fluctuation conditions, transient terms can be retained to describe the time-varying response of membrane pressure.

[0104] 3.2 Coupling Relationship between Film Thickness Equation and Trench Parameters

[0105] The local film thickness of a water-lubricated bearing depends not only on the basic geometric clearance and eccentricity of the bearing, but also on the direct influence of the groove depth and groove width.

[0106] For a cylindrical journal-bearing mating pair, the film thickness in the non-groove region can be expressed as:

[0107] ,

[0108] in, The water film thickness of a grooveless water-lubricated bearing is an indicator for evaluating its performance. This refers to the radial clearance of the bearing. For eccentricity, Circumferential angular coordinates The attitude angle is [value].

[0109] This equation is used to accurately determine the water film thickness of grooveless bearings, providing parameters for subsequent calculations.

[0110] When lubrication grooves exist in localized areas, the film thickness expression is corrected to:

[0111] ,

[0112] in, The thickness of the water film in a grooved water-lubricated bearing is an indicator for evaluating its performance. This is a trench geometry correction function, taking the trench depth within the trench region and zero outside the trench region. Trench width. By limiting Its effect is manifested in the circumferential or axial range.

[0113] This equation is used to accurately determine the water film thickness of grooved bearings, providing parameters for subsequent calculations.

[0114] Therefore, the trench depth changes the thickness of the local fluid domain, and the trench width changes the distribution range of the local fluid domain. Both of these factors together affect the establishment of the pressure gradient, the continuity of the water film, and the effective bearing area.

[0115] 3.3 Boundary Conditions and Cavitation Treatment

[0116] In the process of solving the membrane pressure, environmental pressure boundary conditions are usually used at both ends of the bearing, i.e. ,in, For water film pressure, It is atmospheric pressure.

[0117] For the circumferential starting and ending boundaries, periodic boundaries or inlet-outlet boundary conditions can be used.

[0118] Considering the potential for cavitation in the local negative pressure zone of water-lubricated bearings, to avoid non-physical solutions, a cavitation boundary or mass-conserving cavitation model based on the Reynolds equation can be introduced, satisfying the following conditions: ,in, This refers to cavitation pressure.

[0119] The above processing can more accurately describe the membrane pressure evolution at the boundary between the trench and non-trench regions.

[0120] For water-lubricated bearings with different groove structures, the pressure distribution of the flow field is calculated, including the following steps:

[0121] See Figure 5-7 As shown, for water-lubricated bearings with three different groove structures, the corresponding geometric models are first established, and the fluid domain of the lubricating water film between the journal and the bearing is constructed.

[0122] Then, the mesh is divided according to the working gap and the trench size, and local densification is implemented for the trench edge and the film sensitive area;

[0123] Then, based on the given rotational speed, external load, medium parameters, and boundary conditions, the pressure distribution of the flow field is iteratively solved using a fluid-structure interaction method:

[0124] During the solution process, the pressure load output by the fluid domain acts on the surface of the bearing structure, and the deformation calculated by the solid domain in turn corrects the gap distribution of the fluid domain, so as to realize the bidirectional coupling update of the water film pressure field and the structural deformation field.

[0125] Once all field variables converge, the water film pressure distribution results under the three trench structures are output, and the effects of different trench structures on pressure peak, bearing area and flow field uniformity are compared accordingly.

[0126] 3.4. Calculation of Load, Friction and Performance Indicators

[0127] After obtaining the water film pressure distribution, the main performance indicators of the bearing can be further calculated.

[0128] The bearing capacity can be obtained by integrating the membrane pressure over the lubrication zone. The formula for calculating the bearing capacity is:

[0129] ,

[0130] in, For load-bearing capacity, For water film pressure,

[0131] Frictional force can be calculated based on the integral of the wall shear stress. The formula for calculating frictional force is:

[0132] ,

[0133] in, The coefficient of friction, For tangential friction, For load-bearing capacity.

[0134] Minimum film thickness The thickness is determined from the film thickness distribution across the entire lubrication domain and is used to determine the continuity of the water film and the risk of local contact.

[0135] If necessary, further calculations can be performed on indicators such as temperature rise, peak pressure, film thickness fluctuation, and stiffness damping coefficient to form a more complete comprehensive performance evaluation system.

[0136] The embodiments of the present invention do not merely rely on empirical calculations to compare different trench parameters, but rather use the water film control equation, film thickness equation, and performance integral relationship as a theoretical basis to uniformly solve and quantitatively evaluate candidate trench parameter combinations.

[0137] This invention explicitly incorporates the groove depth and groove width of water-lubricated bearings into the film thickness function, establishing the transmission relationship between groove parameters, film thickness distribution, film pressure distribution, and performance indicators. This provides a calculable, comparable, and engineering-applicable theoretical basis for the optimization of the groove structure of water-lubricated bearings.

[0138] 3.5 Parameter Selection Method Based on Orthogonal Experiment

[0139] To improve the efficiency of candidate parameter combination screening, this embodiment of the invention introduces an orthogonal experimental design method in the preliminary optimization stage of the groove depth and groove width of the water-lubricated bearing.

[0140] For a two-factor, three-level design scenario, an equivalent orthogonal array is constructed, with the groove depth and groove width of the water-lubricated bearing designated as Factor A and Factor B, respectively. Each factor has three levels, and the load-bearing capacity, minimum film thickness, friction coefficient, temperature rise, or comprehensive performance evaluation value are used as response indicators. By reducing the number of experiments, the influence of different levels of each factor on the response value is obtained, thereby reducing parameter scanning and testing costs.

[0141] During orthogonal experimental analysis, the mean response values ​​at each level can be statistically analyzed to obtain the average response values ​​of factor A and factor B at different levels. Through range analysis, the primary and secondary influences of different factors on the performance indicators of water-lubricated bearings can be determined.

[0142] For example, in a two-factor, three-level orthogonal test, factor A is the groove depth of the water-lubricated bearing, with levels of 3mm, 4mm, and 5mm, and factor B is the groove width of the water-lubricated bearing, with levels of 3mm, 4mm, and 5mm, and load-bearing capacity is used as the response index.

[0143] Based on the bearing capacity results obtained from each test combination, the average value of factor A at each level was calculated. , , and the average value of factor B at each level. , , .

[0144] By comparing the magnitudes of the various means, the optimal level for the corresponding indicator can be determined.

[0145] By calculating the range, the influence of the groove depth and groove width on the load-bearing capacity of water-lubricated bearings can be further determined.

[0146] For indicators where larger is always better, such as load-bearing capacity and minimum film thickness, the level corresponding to the larger average value can be selected;

[0147] For indicators where smaller is better, such as friction coefficient and temperature rise, the level corresponding to the smaller mean can be selected;

[0148] For cases with multiple indicators, dimensionless processing can be performed first, and then the comprehensive evaluation value can be used as the orthogonal analysis object.

[0149] Furthermore, analysis of variance can be used to test the significance of trench depth, trench width, and error terms.

[0150] The specific process includes: calculating the sum of squares of factor A, factor B and error terms based on the response results of each experimental combination; obtaining the mean square based on the corresponding degrees of freedom; and then calculating the F-statistic of each factor based on the mean square of error.

[0151] By comparing the F-values ​​of each factor with the critical values ​​at the target significance level, or by combining the significance probability... By judging the values, it can be determined whether the trench depth and trench width have a significant impact on the response index.

[0152] Furthermore, based on the proportion of the sum of squares of each factor to the total sum of squares, the contribution rate of each factor to the change in the response index can be evaluated, and the dominant factor can be identified accordingly.

[0153] By combining the main effect analysis results, the optimal direction and reasonable range of groove parameters for water-lubricated bearings can be obtained, providing a basis for subsequent response surface optimization modeling and multi-objective collaborative design.

[0154] 3.6 Fine-grained optimization method based on response surface analysis

[0155] After completing the initial screening or parameter scanning of orthogonal experiments, this embodiment of the invention further employs response surface methodology to finely optimize the groove depth and groove width of the water-lubricated bearing.

[0156] With trench depth and trench width Using load-bearing capacity, minimum film thickness, friction coefficient, or comprehensive performance evaluation value as independent variables, a quadratic polynomial response surface model is established:

[0157] ,

[0158] in, For the target response value, For constant terms, , The coefficient of the linear term, The coefficient of the interaction term. , The coefficient of the quadratic term.

[0159] This two-factor second-order response surface model is used to solve the nonlinear coupling optimization problem of groove structure parameters and performance of water-lubricated bearings. It can accurately fit the parameter-performance mapping, efficiently find the optimal parameter combination, and achieve the technical effects of reducing friction and wear, improving load-bearing capacity and R&D efficiency.

[0160] By performing regression fitting on the experimental results or numerical calculation results, the continuous mapping relationship between the groove depth and groove width of water-lubricated bearings and the performance indicators can be obtained. Based on this, response surface models can be used to draw response surface plots and contour plots to characterize the optimal parameter region and the variation law of parameter sensitivity.

[0161] For example, if there are n groups of samples, where n is a positive integer, then the nth group of samples... Group data can be written as:

[0162] ,

[0163] in, For the first The response values ​​of a group of experiments or numerical calculations of a sample. For the first The trench depth of the group of samples, For the first The groove width of the group of samples, For fitting error, , All are positive integers.

[0164] Write all samples in matrix form:

[0165] This is a simplified version of the equation.

[0166] in,

[0167] , , ,

[0168] Then, the coefficient vector is solved using the least squares method:

[0169] ,

[0170] in, It is the least-squares optimal estimate vector of the response surface model coefficients. yes The transpose of .

[0171] Thus, we can obtain: the coefficients of the constant term, the linear term, the interaction term, and the quadratic term.

[0172] It is an estimate of the constant term. It is an estimate of the coefficient of the linear term. It is an estimate of the coefficient of the linear term. These are the coefficient estimates of the interaction terms. These are coefficient estimates. These are coefficient estimates.

[0173] The coefficients of the first-order term, interaction term, and quadratic term in the response surface model are all determined from experimental data or numerical simulation results using a multiple quadratic regression method, specifically including the following steps:

[0174] First, different combinations of trench depth and trench width are selected for experiments or numerical calculations to obtain the corresponding response values.

[0175] Subsequently, the design matrix is ​​constructed, and the least squares method is used to estimate the parameters of the quadratic polynomial model, thereby obtaining the coefficients of the constant term, the coefficients of the first term, the coefficients of the interaction term, and the coefficients of the quadratic term.

[0176] Based on this, we can further combine analysis of variance to test the significance of each coefficient, and use the two-factor second-order response surface model obtained by least squares fitting to draw response surface plots and contour plots, thereby determining the optimal combination of parameters such as the groove of the water-lubricated bearing and the sensitivity law of the factors.

[0177] When the objective is a single performance optimization, the response value Individual performance indicators such as load-bearing capacity, minimum film thickness, or friction coefficient can be directly selected;

[0178] When the objective is to optimize multiple indicators synergistically, indicators such as load-bearing capacity, minimum film thickness, water film stability, friction loss, and temperature rise can be dimensionless, and a comprehensive response value can be constructed according to the predetermined optimization objective. ;

[0179] Based on the above response surface model, the trench depth and trench width are jointly optimized to determine the optimal parameter matching interval under given working conditions.

[0180] Using increased load-bearing capacity, increased minimum film thickness, decreased friction coefficient, and limited temperature rise as joint optimization objectives, the influence of trench parameters on overall performance was obtained through response surface methodology fitting, and the optimal parameter region was determined accordingly. The response surface analysis results are as follows: Figure 8 As shown, the contour map is as follows Figure 9 As shown.

[0181] Figure 8 and Figure 9 This indicates that the groove depth and groove width of water-lubricated bearings have a significant coupled effect on their overall performance. The response surface is a downward-opening unimodal surface with closed contour lines, suggesting that the overall performance initially increases and then decreases with changes in these two parameters, exhibiting a trend of first increasing and then decreasing. =3.10mm The optimal groove depth is around 4.20 mm. In contrast, the groove depth of water-lubricated bearings has a more significant impact on their overall performance.

[0182] As can be seen from Table 1, the overall performance value F increases with trench depth. With trench width The changes exhibit significant nonlinear characteristics. Within the parameter range examined in this embodiment of the invention, when the trench depth... =3.10mm, groove width When the thickness is 4.20 mm, the overall performance value reaches its maximum value of 100.00, indicating that this parameter combination is a relatively optimal design point. As the structural parameters gradually deviate from this optimal range, the overall performance value decreases significantly.

[0183] For example, when the parameter combination is =4.00mm When the thickness is 4.00mm, the overall performance value drops to 85.58;

[0184] When the parameter deviates further to =5.00mm When the thickness is 5.00mm, the overall performance value is only 19.98.

[0185] The above results demonstrate that the parameter optimization method employed in this invention can effectively identify the optimal matching range of groove structure parameters, thereby improving the overall performance of the bearing. Therefore, this application does not simply adjust existing parameters, but rather determines a groove parameter combination with superior overall performance through parameter screening and optimization, thus achieving clear and significant technical effects and effectively improving the overall performance of water-lubricated bearings.

[0186] The following data are exemplary results calculated based on the response surface model in the embodiments of the present invention, used to illustrate the technical solutions of the embodiments of the present invention and the performance improvement effect produced by non-preferred parameter combinations. See [link to relevant documentation] for the effects. Figure 8 and Figure 9 .

[0187] Table 1. Calculation results of comprehensive performance value F under different combinations of trench parameters

[0188]

[0189] This invention uses orthogonal experiments for initial parameter screening and response surface analysis for fine modeling and optimization, forming a complete technical route of "theoretical equation solving - parameter experimental design - response surface optimization". This not only retains the physical basis of thin film lubrication theory and film pressure solution, but also improves the efficiency and engineering feasibility of the parameter optimization process.

[0190] 4. Determining the optimal parameter combination

[0191] Based on the comprehensive performance evaluation value, all candidate parameter combinations are sorted or searched to determine the optimal combination of trench depth and width under the target working condition. For different design objectives, weighting strategies of "load-bearing priority," "low friction priority," or "comprehensive performance priority" can be adopted respectively.

[0192] 5. Optimize trench structure formation

[0193] Based on the obtained optimal parameter combination, an optimized groove structure is formed on the inner surface of the water-lubricated bearing liner.

[0194] The optimized trench structure can be: rectangular trench, circular arc trench, trapezoidal trench, U-shaped trench or composite section trench, and can be arranged along the axial, circumferential or spiral direction.

[0195] 6. Simulation-experiment joint correction

[0196] The numerical optimization results are compared with the experimental test results. The weight coefficients or constraints in the comprehensive performance evaluation function are modified using the friction, temperature rise, vibration and wear data obtained from the experiment, thereby forming an iterative optimization design process oriented towards actual working conditions.

[0197] Example 9: Water-lubricated bearing

[0198] This invention provides a water-lubricated bearing, which is designed by the water-lubricated bearing groove parameter collaborative optimization design method of any one of the embodiments 1-8.

[0199] Example 10: Collaborative Optimization Design System for Groove Parameters of Water-Lubricated Bearings

[0200] Based on the same inventive concept, see Figure 10 As shown, this embodiment of the invention provides a collaborative optimization design system for groove parameters of water-lubricated bearings, comprising:

[0201] The parameter determination unit is used to: determine the basic parameters and operating parameters of the water-lubricated bearing to be optimized, and establish a set of design variables for the geometric parameters of the water-lubricated bearing groove.

[0202] The groove model building unit is used to: build candidate parameter combinations for groove depth and groove width within a preset parameter range; and build a corresponding water-lubricated bearing groove structure model for each candidate parameter combination.

[0203] The groove optimization unit is used to: sort or search all candidate parameter combinations based on the comprehensive performance evaluation value, determine the optimal combination of groove depth and groove width under the target working condition; and form an optimized groove structure on the inner surface of the water-lubricated bearing liner based on the optimal parameter combination.

[0204] The aforementioned parameter determination unit, trench model construction unit, and trench optimization unit sequentially establish data flow connections.

[0205] Example 11, Trench Model Construction Unit

[0206] Based on Example 10, see [link / reference] Figure 11 As shown in the figure, this embodiment of the invention provides a collaborative optimization design system for groove parameters of water-lubricated bearings, specifically describing the groove model construction unit, which includes:

[0207] The thin film flow control model construction sub-unit is used to: establish a thin film flow control model for water-lubricated bearings, describe the water film flow in the bearing lubrication zone using thin film lubrication theory, and solve the film pressure distribution based on mass conservation, viscous flow and thin film approximation assumptions;

[0208] The coupling relationship between the film thickness equation and the trench parameters is established in a sub-unit, which is used to: establish the coupling relationship between the film thickness equation and the trench parameters. The trench depth changes the thickness of the local fluid domain, and the trench width changes the distribution range of the local fluid domain. The two together affect the establishment of the pressure gradient, the continuity of the water film, and the effective bearing area.

[0209] The boundary conditions and cavitation treatment sub-unit is used for: applying environmental pressure boundary conditions at both ends of the bearing during the membrane pressure solution process; using periodic boundary conditions or inlet-outlet boundary conditions for the circumferential starting and ending boundaries; introducing Reynolds cavitation boundary or mass conservation cavitation model; and calculating the flow field pressure distribution for different grooves of the water-lubricated bearing.

[0210] The performance index calculation subunit is used to: calculate the main performance indexes of the bearing after obtaining the water film pressure distribution; calculate the bearing load capacity by integrating the film pressure in the lubrication area; calculate the friction force and friction coefficient based on the wall shear stress integration; calculate the minimum film thickness by the film thickness distribution in the entire lubrication domain; and calculate the temperature rise, pressure peak, film thickness fluctuation and stiffness damping coefficient.

[0211] The orthogonal initial screening unit is used to: introduce orthogonal experimental design method in the preliminary optimization stage of groove depth and groove width; construct an equivalent orthogonal table for a two-factor, three-level design scenario; take groove depth and groove width as factor A and factor B respectively; take three levels for each factor; and take load-bearing capacity, minimum film thickness, friction coefficient, temperature rise or comprehensive performance evaluation value as response index; during the orthogonal experimental analysis, the mean response value at each level is statistically analyzed to obtain the average response value of factor A and factor B at different levels; and determine the primary and secondary influences of different factors on the performance index of water-lubricated bearings through range analysis.

[0212] The response surface analysis subunit is used to: after completing the initial screening or parameter scanning of orthogonal experiments, use response surface analysis to finely optimize the trench depth and trench width. With trench depth and trench width as independent variables, and load-bearing capacity, minimum film thickness, friction coefficient or comprehensive performance evaluation value as response values, a quadratic polynomial response surface model is established. By regression fitting of experimental results or numerical calculation results, the continuous mapping relationship between trench depth and trench width and performance indicators is obtained. Based on this response surface model, response surface plots and contour plots are drawn to characterize the optimal parameter region and the variation law of parameter sensitivity.

[0213] The above-mentioned thin film flow control model construction sub-unit, film thickness equation and trench parameter coupling relationship establishment sub-unit, boundary condition and cavitation treatment sub-unit, performance index calculation sub-unit, orthogonal primary screening sub-unit, and response surface analysis sub-unit are sequentially connected to establish data flow.

[0214] Example 12, Electronic Equipment

[0215] This invention provides an electronic device, including: at least one processor, at least one memory, and a communication interface, wherein the processor, memory, and communication interface communicate with each other; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the collaborative optimization design method for water-lubricated bearing groove parameters in any of embodiments 1 to 8.

[0216] Example 13: Non-transitory computer-readable storage medium

[0217] This invention provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to execute the collaborative optimization design method for water-lubricated bearing groove parameters in any of embodiments 1 to 8.

[0218] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for collaborative optimization design of groove parameters in water-lubricated bearings, characterized in that, Includes the following steps: Determine the basic and operating parameters of the water-lubricated bearing to be optimized, and establish a set of design variables for the geometric parameters of the water-lubricated bearing groove; within the preset parameter range, construct candidate parameter combinations for groove depth and groove width; for each set of candidate parameter combinations, establish the corresponding water-lubricated bearing groove structure model. Based on the comprehensive performance evaluation value, all candidate parameter combinations are sorted or searched to determine the optimal groove depth and groove width combination under the target working condition; based on the optimal parameter combination, an optimized groove structure is formed on the inner surface of the water-lubricated bearing liner.

2. The collaborative optimization design method for water-lubricated bearing groove parameters as described in claim 1, characterized in that: The basic parameters and operating parameters of the water-lubricated bearing include: Bearing inner diameter or journal radius, bearing length, radial clearance, liner material parameters, shaft speed or surface linear velocity, external load or unit specific pressure, lubricating medium physical properties, and eccentricity or off-center load parameters; The set of design variables for the geometric parameters of the water-lubricated bearing groove includes: groove depth, groove width, number of grooves, groove cross-sectional shape, distribution of grooves along the axial, circumferential or helical direction, and the zoning setting method for groove parameters in different regions. The candidate parameter combinations for trench depth and trench width are generated through orthogonal experimental design, full factorial parameter combination, response surface design, numerical parameter scanning, or intelligent optimization algorithms. Based on the water film control equation, film thickness equation, and performance integral relationship, the candidate trench parameter combinations are solved uniformly and quantitatively evaluated. The trench depth and trench width are explicitly introduced into the film thickness function to establish the transmission relationship between trench parameters, film thickness distribution, film pressure distribution, and performance indicators.

3. The collaborative optimization design method for water-lubricated bearing groove parameters as described in claim 2, characterized in that: Within a preset parameter range, candidate parameter combinations for groove depth and groove width are constructed; for each candidate parameter combination, a corresponding water-lubricated bearing groove structure model is established, including the following steps: A thin-film flow control model for water-lubricated bearings is established. The water film flow in the bearing lubrication zone is described using thin-film lubrication theory, and the film pressure distribution is solved based on mass conservation, viscous flow, and thin-film approximation assumptions. The coupling relationship between the film thickness equation and the trench parameters is established. The trench depth changes the thickness of the local fluid domain, and the trench width changes the distribution range of the local fluid domain. The two together affect the establishment of the pressure gradient, the continuity of the water film, and the effective bearing area. Boundary conditions and cavitation treatment: In the process of solving the membrane pressure, environmental pressure boundary conditions are used at both ends of the bearing. For the circumferential starting and ending boundaries, periodic boundaries or inlet-outlet boundary conditions are used. Cavitation boundaries or mass conservation cavitation models are introduced. For water-lubricated bearings with different groove structures, the flow field pressure distribution is calculated. Load, friction and performance index calculation: After obtaining the water film pressure distribution, the bearing performance index is calculated: the bearing load capacity is calculated by integrating the film pressure in the lubrication area, and the friction force is calculated based on the integration of the wall shear stress; the minimum film thickness is calculated by the film thickness distribution in the entire lubrication domain; the temperature rise, pressure peak, film thickness fluctuation and stiffness damping coefficient are calculated. Orthogonal experiments were used for initial parameter screening: In the preliminary optimization stage of trench depth and width, orthogonal experimental design was introduced. For a two-factor, three-level design scenario, an equivalent orthogonal array was constructed, with trench depth and width designated as Factor A and Factor B, respectively. Each factor had three levels, and load-bearing capacity, minimum film thickness, friction coefficient, temperature rise, or comprehensive performance evaluation value were used as response indicators. During the orthogonal experimental analysis, the mean response values ​​at each level were statistically analyzed to obtain the average response values ​​of Factor A and Factor B at different levels. Range analysis was then used to determine the primary and secondary influences of different factors on the performance indicators. Response surface analysis is used for fine modeling and optimization: After completing the initial screening or parameter scanning of orthogonal experiments, response surface analysis is used to finely optimize the trench depth and trench width. The trench depth and trench width are used as independent variables, and the load-bearing capacity, minimum film thickness, friction coefficient or comprehensive performance evaluation value are used as response values. A quadratic polynomial response surface model is established. By regression fitting of the experimental results or numerical calculation results, the continuous mapping relationship between the trench depth and trench width and the performance index is obtained. Based on this response surface model, response surface plots and contour plots are drawn.

4. The collaborative optimization design method for water-lubricated bearing groove parameters as described in claim 3, characterized in that: The calculation of flow field pressure distribution for water-lubricated bearings with different groove structures includes the following steps: For water-lubricated bearings with different groove structures, corresponding geometric models are established, and the fluid domain of the lubricating water film between the journal and the bearing is constructed. The mesh is divided according to the working gap and the size of the trench, and local densification is implemented for the trench edges and the film sensitive areas; Based on the given rotational speed, external load, medium parameters, and boundary conditions, the pressure distribution in the flow field of a water-lubricated bearing is iteratively solved using a fluid-structure interaction method. During the solution process, the pressure load output by the fluid domain acts on the surface of the bearing structure, and the deformation calculated by the solid domain in turn corrects the gap distribution of the fluid domain, so as to realize the bidirectional coupling update of the water film pressure field and the structural deformation field. Once all field variables converge, the water film pressure distribution results of water-lubricated bearings with different groove structures are output, and the effects of different groove structures on the pressure peak, bearing area and flow field uniformity of water-lubricated bearings are compared accordingly.

5. The collaborative optimization design method for water-lubricated bearing groove parameters as described in claim 4, characterized in that: The application of response surface methodology to fine-grained modeling and optimization also includes the following steps: The coefficients of the first-order term, interaction term, and quadratic term in the response surface model are all determined from experimental data or numerical simulation results using a multiple quadratic regression method, specifically including the following steps: Different combinations of trench depth and width were selected for testing or numerical calculation to obtain the corresponding response values; A design matrix is ​​constructed, and the least squares method is used to estimate the parameters of the quadratic polynomial model, obtaining the coefficients of the constant term, the coefficients of the first term, the coefficients of the interaction term, and the coefficients of the quadratic term. By combining analysis of variance, the significance of each coefficient is tested, and response surface plots and contour plots are drawn using response surface modeling to determine the optimal parameter region and the sensitivity law of factors. When the objective is to optimize a single performance, the response value is directly taken from a single performance index, including: load-bearing capacity, minimum film thickness, or friction coefficient. When the objective is to optimize multiple indicators synergistically, the load-bearing capacity, minimum film thickness, water film stability, friction loss, and temperature rise indicators are made dimensionless, and a comprehensive response value is constructed according to the predetermined optimization objective. Based on the response surface model, the trench depth and trench width are jointly optimized to determine the optimal parameter matching interval under given working condition constraints. By taking increased load-bearing capacity, increased minimum film thickness, decreased friction coefficient, and limited temperature rise as joint optimization objectives, the influence of trench parameters on comprehensive performance is obtained through response surface fitting results, and the optimal parameter region is determined accordingly.

6. A water-lubricated bearing, characterized in that, It is designed by the collaborative optimization design method for water-lubricated bearing groove parameters as described in any one of claims 1-5.

7. A collaborative optimization design system for groove parameters of water-lubricated bearings, characterized in that, include: The parameter determination unit is used to: determine the basic parameters and operating parameters of the water-lubricated bearing to be optimized, and establish a set of design variables for the geometric parameters of the water-lubricated bearing groove. The groove model building unit is used to: build candidate parameter combinations for groove depth and groove width within a preset parameter range; and build a corresponding water-lubricated bearing groove structure model for each candidate parameter combination. The groove optimization unit is used to: sort or search all candidate parameter combinations based on the comprehensive performance evaluation value, determine the optimal combination of groove depth and groove width under the target working condition; and form an optimized groove structure on the inner surface of the water-lubricated bearing liner based on the optimal parameter combination. The parameter determination unit, trench model construction unit, and trench optimization unit sequentially establish a data flow connection.

8. The collaborative optimization design system for water-lubricated bearing groove parameters as described in claim 7, characterized in that: The trench model construction unit includes: The thin film flow control model construction sub-unit is used to: establish a thin film flow control model for water-lubricated bearings, describe the water film flow in the bearing lubrication zone using thin film lubrication theory, and solve the film pressure distribution based on mass conservation, viscous flow and thin film approximation assumptions; The coupling relationship between the film thickness equation and the trench parameters is established in a sub-unit, which is used to: establish the coupling relationship between the film thickness equation and the trench parameters. The trench depth changes the thickness of the local fluid domain, and the trench width changes the distribution range of the local fluid domain. The two together affect the establishment of the pressure gradient, the continuity of the water film, and the effective bearing area. The boundary conditions and cavitation treatment sub-unit is used for: applying environmental pressure boundary conditions at both ends of the bearing during the membrane pressure solution process; using periodic boundary conditions or inlet-outlet boundary conditions for the circumferential starting and ending boundaries; introducing cavitation boundary conditions or mass conservation cavitation models; and calculating the flow field pressure distribution for water-lubricated bearings with different groove structures. The performance index calculation subunit is used to: calculate bearing performance indexes after obtaining the water film pressure distribution; calculate bearing load capacity by integrating the film pressure in the lubrication area; calculate friction force based on the wall shear stress integration; calculate minimum film thickness by the film thickness distribution in the entire lubrication domain; and calculate temperature rise, peak pressure, film thickness fluctuation, and stiffness damping coefficient. The orthogonal initial screening unit is used to: introduce orthogonal experimental design method in the preliminary optimization stage of trench depth and trench width; construct an equivalent orthogonal array for a two-factor, three-level design scenario; treat trench depth and trench width as factor A and factor B respectively; take three levels for each factor; and use load-bearing capacity, minimum film thickness, friction coefficient, temperature rise, or comprehensive performance evaluation value as response indicators; during the orthogonal experimental analysis, statistically analyze the mean response at each level to obtain the average response values ​​of factor A and factor B at different levels; and determine the primary and secondary influences of different factors on performance indicators through range analysis. The response surface analysis subunit is used to: after completing the initial screening or parameter scanning of orthogonal experiments, use response surface analysis to finely optimize the trench depth and trench width. With trench depth and trench width as independent variables, and load-bearing capacity, minimum film thickness, friction coefficient or comprehensive performance evaluation value as response values, establish a quadratic polynomial response surface model. By performing regression fitting on the experimental results or numerical calculation results, obtain the continuous mapping relationship between trench depth and trench width and performance indicators, and draw response surface plots and contour plots based on the response surface model. The thin film flow control model construction subunit, the film thickness equation and trench parameter coupling relationship establishment subunit, the boundary condition and cavitation treatment subunit, the performance index calculation subunit, the orthogonal initial screening subunit, and the response surface analysis subunit are sequentially connected to establish data flow.

9. An electronic device, characterized in that, include: The system includes at least one processor, at least one memory, and a communication interface, wherein the processor, memory, and communication interface communicate with each other. The memory stores program instructions that can be executed by a processor; the processor invokes the program instructions to execute the collaborative optimization design method for water-lubricated bearing groove parameters as described in any one of claims 1 to 5.

10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions; the computer instructions cause the computer to execute the collaborative optimization design method for water-lubricated bearing groove parameters as described in any one of claims 1 to 5.

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